High-Efficiency, High-Power Laser Transmitter for Deep-Space Communication, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — There is demand for vastly improved deep space satellite communications links. As data rates dramatically increase due to new sensor technologies and the desire to...

Manipulating the Electronic Excited State Energies of Pyrimidine-Based Thermally Activated Delayed Fluorescence Emitters To Realize Efficient Deep-Blue Emission.

Science.gov (United States)

Komatsu, Ryutaro; Ohsawa, Tatsuya; Sasabe, Hisahiro; Nakao, Kohei; Hayasaka, Yuya; Kido, Junji

2017-02-08

The development of efficient and robust deep-blue emitters is one of the key issues in organic light-emitting devices (OLEDs) for environmentally friendly, large-area displays or general lighting. As a promising technology that realizes 100% conversion from electrons to photons, thermally activated delayed fluorescence (TADF) emitters have attracted considerable attention. However, only a handful of examples of deep-blue TADF emitters have been reported to date, and the emitters generally show large efficiency roll-off at practical luminance over several hundreds to thousands of cd m -2 , most likely because of the long delayed fluorescent lifetime (τ d ). To overcome this problem, we molecularly manipulated the electronic excited state energies of pyrimidine-based TADF emitters to realize deep-blue emission and reduced τ d . We then systematically investigated the relationships among the chemical structure, properties, and device performances. The resultant novel pyrimidine emitters, called Ac-XMHPMs (X = 1, 2, and 3), contain different numbers of bulky methyl substituents at acceptor moieties, increasing the excited singlet (E S ) and triplet state (E T ) energies. Among them, Ac-3MHPM, with a high E T of 2.95 eV, exhibited a high external quantum efficiency (η ext,max ) of 18% and an η ext of 10% at 100 cd m -2 with Commission Internationale de l'Eclairage chromaticity coordinates of (0.16, 0.15). These efficiencies are among the highest values to date for deep-blue TADF OLEDs. Our molecular design strategy provides fundamental guidance to design novel deep-blue TADF emitters.

An Energy-Efficient and Scalable Deep Learning/Inference Processor With Tetra-Parallel MIMD Architecture for Big Data Applications.

Science.gov (United States)

Park, Seong-Wook; Park, Junyoung; Bong, Kyeongryeol; Shin, Dongjoo; Lee, Jinmook; Choi, Sungpill; Yoo, Hoi-Jun

2015-12-01

Deep Learning algorithm is widely used for various pattern recognition applications such as text recognition, object recognition and action recognition because of its best-in-class recognition accuracy compared to hand-crafted algorithm and shallow learning based algorithms. Long learning time caused by its complex structure, however, limits its usage only in high-cost servers or many-core GPU platforms so far. On the other hand, the demand on customized pattern recognition within personal devices will grow gradually as more deep learning applications will be developed. This paper presents a SoC implementation to enable deep learning applications to run with low cost platforms such as mobile or portable devices. Different from conventional works which have adopted massively-parallel architecture, this work adopts task-flexible architecture and exploits multiple parallelism to cover complex functions of convolutional deep belief network which is one of popular deep learning/inference algorithms. In this paper, we implement the most energy-efficient deep learning and inference processor for wearable system. The implemented 2.5 mm × 4.0 mm deep learning/inference processor is fabricated using 65 nm 8-metal CMOS technology for a battery-powered platform with real-time deep inference and deep learning operation. It consumes 185 mW average power, and 213.1 mW peak power at 200 MHz operating frequency and 1.2 V supply voltage. It achieves 411.3 GOPS peak performance and 1.93 TOPS/W energy efficiency, which is 2.07× higher than the state-of-the-art.

Efficient fluorescent deep-blue and hybrid white emitting devices based on carbazole/benzimidazole compound

KAUST Repository

Yang, Xiaohui; Zheng, Shijun; Bottger, Rebecca; Chae, HyunSik; Tanaka, Takeshi; Li, Sheng; Mochizuki, Amane; Jabbour, Ghassan E.

2011-01-01

We report the synthesis, photophysics, and electrochemical characterization of carbazole/benzimidazole-based compound (Cz-2pbb) and efficient fluorescent deep-blue light emitting devices based on Cz-2pbb with the peak external quantum efficiency

The efficient future of deep-space travel - electric rockets; Das Zeitalter der Elektrischen Raketen

Energy Technology Data Exchange (ETDEWEB)

Choueiri, Edgar Y. [Princeton Univ., NJ (United States). Electric Propulsion and Plasma Dynamics Lab.

2010-01-15

Conventional rockets generate thrust by burning chemical fuel. Electric rockets propel space vehicles by applying electric or electromagnetic fields to clouds of charged particles, or plasmas, to accelerate them. Although electric rockets offer much lower thrust levels than their chemical cousins, they can eventually enable spacecraft to reach greater speeds for the same amount of propellant. Electric rockets' high-speed capabilities and their efficient use of propellant make them valuable for deep-space missions. (orig.)

15N tracer technique for studying efficiency of deep placed fertilizer through nutriseed holder in direct seeded rice

International Nuclear Information System (INIS)

Asha, V.S.; Arulmozhiselvan, K.

2006-01-01

In order to estimate N use efficiency in deep placement of NPK straight fertilizers, two pot experiments were conducted in high clay soil with direct seeded rice. 15 N urea was used as a tracer. A newly designed 'Nutriseed Holder' was used for simultaneous deep placement of fertilizers and sowing of seeds. Each holder had two cavities, one on top for holding seed and another one at bottom for holding fertilizer material. By implanting a holder in puddled soil, a rice hill was established. The length (5 or 10 cm) and width (8 or 12 mm) of nutriseed holder was standardized while evaluating the effect of Azolla, neem and seed inoculants. Appreciably, deep placement of plain NPK fertilizer in 12 mm holder placed at 5 cm depth recorded the highest grain yield with a yield increase of 81.8 per cent during rabi 2002 (cv CO 43) and 84.8 per cent during summer 2003 (cv CO 47) over broadcast application. Further, it increased recovery of added JSN in grain + straw to the tune of 57.1 per cent in rabi and 54.7 per cent in summer as compared to broadcast application (26.1% in rabi, 34.2 in summer). Deep placement enhanced more retention in soil (up to 9.0% in rabi, 14.6% in summer) whereas broadcast application enhanced more retention in Azolla biomass that was grown in floodwater (up to 2.3 % in rabi, 4.3 % in summer). Use of 12 mm width nutriseed holder aiding deep placement at 5 cm depth was found suitable for deriving high yield and N use efficiency. (author)

Efficient using of automobile transport for the deep open-pit mines

OpenAIRE

Dastan MAHAMBETOV; Bayan RAKISHEV; Galymzhan SAMENOV; Aleksander SŁADKOWSKI

2013-01-01

In the paper the method is proposed of substantiation of the major parameters for zones of effective use of automobile transport of different load-carrying capacity by open cast development of the deep deposits. An efficient ratio is determined between the mining and transport equipment by zone-to -zone use.

Flexible deep-ultraviolet light-emitting diodes for significant improvement of quantum efficiencies by external bending

KAUST Repository

Shervin, Shahab

2018-01-26

Deep ultraviolet (DUV) light at the wavelength range of 250‒280 nm (UVC spectrum) is essential for numerous applications such as sterilization, purification, sensing, and communication. III-nitride-based DUV light-emitting diodes (DUV LEDs), like other solid-state lighting sources, offer a great potential to replace the conventional gas-discharged lamps with short lifetimes and toxic-element-bearing nature. However, unlike visible LEDs, the DUV LEDs are still suffering from low quantum efficiencies (QEs) and low optical output powers. In this work, reported is a new route to improve QEs of AlGaN-based DUV LEDs using mechanical flexibility of recently developed bendable thin-film structures. Numerical studies show that electronic band structures of AlGaN heterostructures and resulting optical and electrical characteristics of the devices can be significantly modified by external bending through active control of piezoelectric polarization. Internal quantum efficiency (IQE) is enhanced higher than three times, when the DUV LEDs are moderately bent to induce in-plane compressive strain in the heterostructure. Furthermore, efficiency droop at high injection currents is mitigated and turn-on voltage of diodes decreases with the same bending condition. The concept of bendable DUV LEDs with a controlled external strain can provide a new path for high-output-power and high-efficiency devices.

Flexible deep-ultraviolet light-emitting diodes for significant improvement of quantum efficiencies by external bending

KAUST Repository

Shervin, Shahab; Oh, Seung Kyu; Park, Hyun Jung; Lee, Keon Hwa; Asadirad, Mojtaba; Kim, Seung Hwan; Kim, Jeomoh; Pouladi, Sara; Lee, Sung-Nam; Li, Xiaohang; Kwak, Joon-Seop; Ryou, Jae-Hyun

2018-01-01

Deep ultraviolet (DUV) light at the wavelength range of 250‒280 nm (UVC spectrum) is essential for numerous applications such as sterilization, purification, sensing, and communication. III-nitride-based DUV light-emitting diodes (DUV LEDs), like other solid-state lighting sources, offer a great potential to replace the conventional gas-discharged lamps with short lifetimes and toxic-element-bearing nature. However, unlike visible LEDs, the DUV LEDs are still suffering from low quantum efficiencies (QEs) and low optical output powers. In this work, reported is a new route to improve QEs of AlGaN-based DUV LEDs using mechanical flexibility of recently developed bendable thin-film structures. Numerical studies show that electronic band structures of AlGaN heterostructures and resulting optical and electrical characteristics of the devices can be significantly modified by external bending through active control of piezoelectric polarization. Internal quantum efficiency (IQE) is enhanced higher than three times, when the DUV LEDs are moderately bent to induce in-plane compressive strain in the heterostructure. Furthermore, efficiency droop at high injection currents is mitigated and turn-on voltage of diodes decreases with the same bending condition. The concept of bendable DUV LEDs with a controlled external strain can provide a new path for high-output-power and high-efficiency devices.

Spatial walk-off compensated beta-barium borate stack for efficient deep-UV generation

Science.gov (United States)

Li, Da; Lee, Huai-Chuan; Meissner, Stephanie K.; Meissner, Helmuth E.

2018-02-01

Beta-Barium Borate (β-BBO) crystal is commonly used in nonlinear frequency conversion from visible to deep ultraviolet (DUV). However, in a single crystal BBO, its large spatial walk-off effect will reduce spatial overlap of ordinary and extraordinary beam, and thus degrade the conversion efficiency. To overcome the restrictions in current DUV conversion systems, Onyx applies adhesive-free bonding technique to replace the single crystal BBO with a spatial Walk-off Compensated (WOC) BBO stack, which is capable of correcting the spatial walk-off while retaining a constant nonlinear coefficient in the adjacent bonding layers. As a result, the β-BBO stack will provide good beam quality, high conversion efficiency, and broader acceptance angle and spectral linewidth, when compared with a single crystal of BBO. In this work, we report on performance of a spatial walk-off compensated β-BBO stack with adhesive-free bonding technique, for efficiently converting from the visible to DUV range. The physics behind the WOC BBO stack are demonstrated, followed by simulation of DUV conversion efficiency in an external resonance cavity. We also demonstrate experimentally the beam quality improvement in a 4-layer WOC BBO stack over a single BBO crystal.

Efficiency analyses of the CANDU spent fuel repository using modified disposal canisters for a deep geological disposal system design

International Nuclear Information System (INIS)

Lee, J.Y.; Cho, D.K.; Lee, M.S.; Kook, D.H.; Choi, H.J.; Choi, J.W.; Wang, L.M.

2012-01-01

Highlights: ► A reference disposal concept for spent nuclear fuels in Korea has been reviewed. ► To enhance the disposal efficiency, alternative disposal concepts were developed. ► Thermal analyses for alternative disposal concepts were performed. ► From the result of the analyses, the disposal efficiency of the concepts was reviewed. ► The most effective concept was suggested. - Abstract: Deep geological disposal concept is considered to be the most preferable for isolating high-level radioactive waste (HLW), including nuclear spent fuels, from the biosphere in a safe manner. The purpose of deep geological disposal of HLW is to isolate radioactive waste and to inhibit its release of for a long time, so that its toxicity does not affect the human beings and the biosphere. One of the most important requirements of HLW repository design for a deep geological disposal system is to keep the buffer temperature below 100 °C in order to maintain the integrity of the engineered barrier system. In this study, a reference disposal concept for spent nuclear fuels in Korea has been reviewed, and based on this concept, efficient alternative concepts that consider modified CANDU spent fuels disposal canister, were developed. To meet the thermal requirement of the disposal system, the spacing of the disposal tunnels and that of the disposal pits for each alternative concept, were drawn following heat transfer analyses. From the result of the thermal analyses, the disposal efficiency of the alternative concepts was reviewed and the most effective concept suggested. The results of these analyses can be used for a deep geological repository design and detailed analyses, based on exact site characteristics data, will reduce the uncertainty of the results.

Final LDRD report : science-based solutions to achieve high-performance deep-UV laser diodes.

Energy Technology Data Exchange (ETDEWEB)

Armstrong, Andrew M.; Miller, Mary A.; Crawford, Mary Hagerott; Alessi, Leonard J.; Smith, Michael L.; Henry, Tanya A.; Westlake, Karl R.; Cross, Karen Charlene; Allerman, Andrew Alan; Lee, Stephen Roger

2011-12-01

We present the results of a three year LDRD project that has focused on overcoming major materials roadblocks to achieving AlGaN-based deep-UV laser diodes. We describe our growth approach to achieving AlGaN templates with greater than ten times reduction of threading dislocations which resulted in greater than seven times enhancement of AlGaN quantum well photoluminescence and 15 times increase in electroluminescence from LED test structures. We describe the application of deep-level optical spectroscopy to AlGaN epilayers to quantify deep level energies and densities and further correlate defect properties with AlGaN luminescence efficiency. We further review our development of p-type short period superlattice structures as an approach to mitigate the high acceptor activation energies in AlGaN alloys. Finally, we describe our laser diode fabrication process, highlighting the development of highly vertical and smooth etched laser facets, as well as characterization of resulting laser heterostructures.

Deep features for efficient multi-biometric recognition with face and ear images

Science.gov (United States)

Omara, Ibrahim; Xiao, Gang; Amrani, Moussa; Yan, Zifei; Zuo, Wangmeng

2017-07-01

Recently, multimodal biometric systems have received considerable research interest in many applications especially in the fields of security. Multimodal systems can increase the resistance to spoof attacks, provide more details and flexibility, and lead to better performance and lower error rate. In this paper, we present a multimodal biometric system based on face and ear, and propose how to exploit the extracted deep features from Convolutional Neural Networks (CNNs) on the face and ear images to introduce more powerful discriminative features and robust representation ability for them. First, the deep features for face and ear images are extracted based on VGG-M Net. Second, the extracted deep features are fused by using a traditional concatenation and a Discriminant Correlation Analysis (DCA) algorithm. Third, multiclass support vector machine is adopted for matching and classification. The experimental results show that the proposed multimodal system based on deep features is efficient and achieves a promising recognition rate up to 100 % by using face and ear. In addition, the results indicate that the fusion based on DCA is superior to traditional fusion.

High-Redshift Radio Galaxies from Deep Fields

Indian Academy of Sciences (India)

2016-01-27

Jan 27, 2016 ... High-Redshift Radio Galaxies from Deep Fields ... Here we present results from the deep 150 MHz observations of LBDS-Lynx field, which has been imaged at 327, ... Articles are also visible in Web of Science immediately.

L-shaped fiber-chip grating couplers with high directionality and low reflectivity fabricated with deep-UV lithography.

Science.gov (United States)

Benedikovic, Daniel; Alonso-Ramos, Carlos; Pérez-Galacho, Diego; Guerber, Sylvain; Vakarin, Vladyslav; Marcaud, Guillaume; Le Roux, Xavier; Cassan, Eric; Marris-Morini, Delphine; Cheben, Pavel; Boeuf, Frédéric; Baudot, Charles; Vivien, Laurent

2017-09-01

Grating couplers enable position-friendly interfacing of silicon chips by optical fibers. The conventional coupler designs call upon comparatively complex architectures to afford efficient light coupling to sub-micron silicon-on-insulator (SOI) waveguides. Conversely, the blazing effect in double-etched gratings provides high coupling efficiency with reduced fabrication intricacy. In this Letter, we demonstrate for the first time, to the best of our knowledge, the realization of an ultra-directional L-shaped grating coupler, seamlessly fabricated by using 193 nm deep-ultraviolet (deep-UV) lithography. We also include a subwavelength index engineered waveguide-to-grating transition that provides an eight-fold reduction of the grating reflectivity, down to 1% (-20  dB). A measured coupling efficiency of -2.7  dB (54%) is achieved, with a bandwidth of 62 nm. These results open promising prospects for the implementation of efficient, robust, and cost-effective coupling interfaces for sub-micrometric SOI waveguides, as desired for large-volume applications in silicon photonics.

Analytical investigation of high temperature 1 kW solid oxide fuel cell system feasibility in methane hydrate recovery and deep ocean power generation

International Nuclear Information System (INIS)

Azizi, Mohammad Ali; Brouwer, Jacob; Dunn-Rankin, Derek

2016-01-01

Highlights: • A dynamic Solid Oxide Fuel Cell (SOFC) model was developed. • Hydrate bed methane dissociation model was integrated with the SOFC model. • SOFC operated steadily for 120 days at high pressure deep ocean environment. • Burning some of the dissociated gas for SMR heat leads to more net methane produced. • Higher SOFC fuel utilization produces higher integrated system efficiency. - Abstract: Methane hydrates are potential valuable energy resources. However, finding an efficient method for methane gas recovery from hydrate sediments is still a challenge. New challenges arise from increasing environmental protection. This is due in part to the technical difficulties involved in the efficient dissociation of methane hydrates at high pressures. In this study, a new approach is proposed to produce valuable products of: 1. Net methane gas recovery from the methane hydrate sediment, and 2. Deep ocean power generation. We have taken the first steps toward utilization of a fuel cell system in methane gas recovery from deep ocean hydrate sediments. An integrated high pressure and high temperature solid oxide fuel cell (SOFC) and steam methane reformer (SMR) system is analyzed for this application and the recoverable amount of methane from deep ocean sediments is measured. System analysis is accomplished for two major cases regarding system performance: 1. Energy for SMR is provided by the burning part of the methane gas dissociated from the hydrate sediment. 2. Energy for SMR is provided through heat exchange with fuel cell effluent gases. We found that the total production of methane gas is higher in the first case compared to the second case. The net power generated by the fuel cell system is estimated for all cases. The primary goal of this study is to evaluate the feasibility of integrated electrochemical devices to accomplish energy efficient dissociation of methane hydrate gases in deep ocean sediments. Concepts for use of electrochemical devices

submitter Accelerating high-energy physics exploration with deep learning

CERN Document Server

Ojika, Dave; Gordon-Ross, Ann; Carnes, Andrew; Gleyzer, Sergei

2017-01-01

In this work, we present our approach to using deep learning for identification of rarely produced physics particles (such as the Higgs Boson) out of a majority of uninteresting, background or noise-dominated data. A fast and efficient system to eliminate uninteresting data would result in much less data being stored, thus significantly reducing processing time and storage requirements. In this paper, we present a generalized preliminary version of our approach to motivate research interest in advancing the state-of-the-art in deep learning networks for other applications that can benefit from learning systems.

2-(2-Hydroxyphenyl)imidazole-based four-coordinate organoboron compounds with efficient deep blue photoluminescence and electroluminescence.

Science.gov (United States)

Zhang, Zhenyu; Zhang, Zuolun; Zhang, Hongyu; Wang, Yue

2017-12-19

Two new four-coordinate organoboron compounds with 2-(2-hydroxyphenyl)imidazole derivatives as the chelating ligands have been synthesized. They possess high thermal stability and are able to form an amorphous glass state. Crystallographic analyses indicate that the differences in ligand structure cause the change of ππ stacking character. The CH 2 Cl 2 solutions and thin films of these compounds display bright blue emission, and these compounds have appropriate HOMO and LUMO energy levels for carrier injection in OLEDs. By utilizing the good thermal and luminescent properties, as well as the proper frontier orbital energy levels, bright non-doped OLEDs with a simple structure have been realized. Notably, these simple devices show deep blue electroluminescence with the Commission Internationale de l'Éclairage (CIE) coordinate of ca. (0.16, 0.08), which is close to the CIE coordinate of (0.14, 0.08) for standard blue defined by the National Television System Committee. In addition, one of the devices exhibits good performance, showing brightness, current efficiency, power efficiency and external quantum efficiency up to 2692 cd m -2 , 2.50 cd A -1 , 1.81 lm W -1 and 3.63%, respectively. This study not only provides good deep-blue emitting OLED materials that are rarely achieved by using four-coordinate organoboron compounds, but also allows a deeper understanding of the structure-property relationship of 2-(2-hydroxyphenyl)imidazole-based boron complexes, which benefits the further structural design of this type of material.

Telescoping Solar Array Concept for Achieving High Packaging Efficiency

Science.gov (United States)

Mikulas, Martin; Pappa, Richard; Warren, Jay; Rose, Geoff

2015-01-01

Lightweight, high-efficiency solar arrays are required for future deep space missions using high-power Solar Electric Propulsion (SEP). Structural performance metrics for state-of-the art 30-50 kW flexible blanket arrays recently demonstrated in ground tests are approximately 40 kW/cu m packaging efficiency, 150 W/kg specific power, 0.1 Hz deployed stiffness, and 0.2 g deployed strength. Much larger arrays with up to a megawatt or more of power and improved packaging and specific power are of interest to mission planners for minimizing launch and life cycle costs of Mars exploration. A new concept referred to as the Compact Telescoping Array (CTA) with 60 kW/cu m packaging efficiency at 1 MW of power is described herein. Performance metrics as a function of array size and corresponding power level are derived analytically and validated by finite element analysis. Feasible CTA packaging and deployment approaches are also described. The CTA was developed, in part, to serve as a NASA reference solar array concept against which other proposed designs of 50-1000 kW arrays for future high-power SEP missions could be compared.

Highly Efficient Closed-Loop CO2 Removal System for Deep-Space ECLSS, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — TDA Research Inc.(TDA) in collaboration with University of Puerto Rico ? Mayaguez (UPRM is proposing to develop a highly efficient CO2 removal system based on UPRM...

Representation learning with deep extreme learning machines for efficient image set classification

KAUST Repository

Uzair, Muhammad

2016-12-09

Efficient and accurate representation of a collection of images, that belong to the same class, is a major research challenge for practical image set classification. Existing methods either make prior assumptions about the data structure, or perform heavy computations to learn structure from the data itself. In this paper, we propose an efficient image set representation that does not make any prior assumptions about the structure of the underlying data. We learn the nonlinear structure of image sets with deep extreme learning machines that are very efficient and generalize well even on a limited number of training samples. Extensive experiments on a broad range of public datasets for image set classification show that the proposed algorithm consistently outperforms state-of-the-art image set classification methods both in terms of speed and accuracy.

Representation learning with deep extreme learning machines for efficient image set classification

KAUST Repository

Uzair, Muhammad; Shafait, Faisal; Ghanem, Bernard; Mian, Ajmal

2016-01-01

Efficient and accurate representation of a collection of images, that belong to the same class, is a major research challenge for practical image set classification. Existing methods either make prior assumptions about the data structure, or perform heavy computations to learn structure from the data itself. In this paper, we propose an efficient image set representation that does not make any prior assumptions about the structure of the underlying data. We learn the nonlinear structure of image sets with deep extreme learning machines that are very efficient and generalize well even on a limited number of training samples. Extensive experiments on a broad range of public datasets for image set classification show that the proposed algorithm consistently outperforms state-of-the-art image set classification methods both in terms of speed and accuracy.

Automated analysis of high-content microscopy data with deep learning.

Science.gov (United States)

Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Growth temperature dependence of Si doping efficiency and compensating deep level defect incorporation in Al0.7Ga0.3N

International Nuclear Information System (INIS)

Armstrong, Andrew M.; Moseley, Michael W.; Allerman, Andrew A.; Crawford, Mary H.; Wierer, Jonathan J.

2015-01-01

The growth temperature dependence of Si doping efficiency and deep level defect formation was investigated for n-type Al 0.7 Ga 0.3 N. It was observed that dopant compensation was greatly reduced with reduced growth temperature. Deep level optical spectroscopy and lighted capacitance-voltage were used to understand the role of acceptor-like deep level defects on doping efficiency. Deep level defects were observed at 2.34 eV, 3.56 eV, and 4.74 eV below the conduction band minimum. The latter two deep levels were identified as the major compensators because the reduction in their concentrations at reduced growth temperature correlated closely with the concomitant increase in free electron concentration. Possible mechanisms for the strong growth temperature dependence of deep level formation are considered, including thermodynamically driven compensating defect formation that can arise for a semiconductor with very large band gap energy, such as Al 0.7 Ga 0.3 N

Deep Echo State Network (DeepESN): A Brief Survey

OpenAIRE

Gallicchio, Claudio; Micheli, Alessio

2017-01-01

The study of deep recurrent neural networks (RNNs) and, in particular, of deep Reservoir Computing (RC) is gaining an increasing research attention in the neural networks community. The recently introduced deep Echo State Network (deepESN) model opened the way to an extremely efficient approach for designing deep neural networks for temporal data. At the same time, the study of deepESNs allowed to shed light on the intrinsic properties of state dynamics developed by hierarchical compositions ...

Deep Energy Retrofit

DEFF Research Database (Denmark)

Zhivov, Alexander; Lohse, Rüdiger; Rose, Jørgen

Deep Energy Retrofit – A Guide to Achieving Significant Energy User Reduction with Major Renovation Projects contains recommendations for characteristics of some of core technologies and measures that are based on studies conducted by national teams associated with the International Energy Agency...... Energy Conservation in Buildings and Communities Program (IEA-EBC) Annex 61 (Lohse et al. 2016, Case, et al. 2016, Rose et al. 2016, Yao, et al. 2016, Dake 2014, Stankevica et al. 2016, Kiatreungwattana 2014). Results of these studies provided a base for setting minimum requirements to the building...... envelope-related technologies to make Deep Energy Retrofit feasible and, in many situations, cost effective. Use of energy efficiency measures (EEMs) in addition to core technologies bundle and high-efficiency appliances will foster further energy use reduction. This Guide also provides best practice...

Highly efficient 400  W near-fundamental-mode green thin-disk laser.

Science.gov (United States)

Piehler, Stefan; Dietrich, Tom; Rumpel, Martin; Graf, Thomas; Ahmed, Marwan Abdou

2016-01-01

We report on the efficient generation of continuous-wave, high-brightness green laser radiation. Green lasers are particularly interesting for reliable and reproducible deep-penetration welding of copper or for pumping Ti:Sa oscillators. By intracavity second-harmonic generation in a thin-disk laser resonator designed for fundamental-mode operation, an output power of up to 403 W is demonstrated at a wavelength of 515 nm with almost diffraction-limited beam quality. The unprecedented optical efficiency of 40.7% of green output power with respect to the pump power of the thin-disk laser is enabled by the intracavity use of a highly efficient grating waveguide mirror, which combines the functions of wavelength stabilization and spectral narrowing, as well as polarization selection in a single element.

Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks

Directory of Open Access Journals (Sweden)

Rui Guo

2018-03-01

Full Text Available Considering the classification of high spatial resolution remote sensing imagery, this paper presents a novel classification method for such imagery using deep neural networks. Deep learning methods, such as a fully convolutional network (FCN model, achieve state-of-the-art performance in natural image semantic segmentation when provided with large-scale datasets and respective labels. To use data efficiently in the training stage, we first pre-segment training images and their labels into small patches as supplements of training data using graph-based segmentation and the selective search method. Subsequently, FCN with atrous convolution is used to perform pixel-wise classification. In the testing stage, post-processing with fully connected conditional random fields (CRFs is used to refine results. Extensive experiments based on the Vaihingen dataset demonstrate that our method performs better than the reference state-of-the-art networks when applied to high-resolution remote sensing imagery classification.

Ultra-Lightweight High Efficiency Nanostructured Materials and Coatings for Deep Space Mission Environments, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — NanoSonic has developed a nanostructured spray self-assembly manufacturing method that has resulted in ultra-lightweight ( 1000%), and multi-layer, high efficiency...

Ultra High Power and Efficiency Space Traveling-Wave Tube Amplifier Power Combiner with Reduced Size and Mass for NASA Missions

Science.gov (United States)

Simons, Rainee N.; Wintucky, Edwin G.; Wilson, Jeffrey D.; Force, Dale A.

2009-01-01

In the 2008 International Microwave Symposium (IMS) Digest version of our paper, recent advances in high power and efficiency space traveling-wave tube amplifiers (TWTAs) for NASA s space-to-Earth communications are presented. The RF power and efficiency of a new K-Band amplifier are 40 W and 50 percent and that of a new Ka-Band amplifier are 200 W and 60 percent. An important figure-of-merit, which is defined as the ratio of the RF power output to the mass (W/kg) of a TWT, has improved by a factor of ten over the previous generation Ka-Band devices. In this extended paper, a high power, high efficiency Ka-band combiner for multiple TWTs, based on a novel hybrid magic-T waveguide circuit design, is presented. The measured combiner efficiency is as high as 90 percent. In addition, at the design frequency of 32.05 GHz, error-free uncoded BPSK/QPSK data transmission at 8 megabits per second (Mbps), which is typical for deep space communications is demonstrated. Furthermore, QPSK data transmission at 622 Mbps is demonstrated with a low bit error rate of 2.4x10(exp -8), which exceeds the deep space state-of-the-art data rate transmission capability by more than two orders of magnitude. A potential application of the TWT combiner is in deep space communication systems for planetary exploration requiring transmitter power on the order of a kilowatt or higher.

Tapering-induced enhancement of light extraction efficiency of nanowire deep ultraviolet LED by theoretical simulations

KAUST Repository

Lin, Ronghui

2018-04-21

A nanowire (NW) structure provides an alternative scheme for deep ultraviolet light emitting diodes (DUV-LEDs) that promises high material quality and better light extraction efficiency (LEE). In this report, we investigate the influence of the tapering angle of closely packed AlGaN NWs, which is found to exist naturally in molecular beam epitaxy (MBE) grown NW structures, on the LEE of NW DUV-LEDs. It is observed that, by having a small tapering angle, the vertical extraction is greatly enhanced for both transverse magnetic (TM) and transverse electric (TE) polarizations. Most notably, the vertical extraction of TM emission increased from 4.8% to 24.3%, which makes the LEE reasonably large to achieve high-performance DUV-LEDs. This is because the breaking of symmetry in the vertical direction changes the propagation of the light significantly to allow more coupling into radiation modes. Finally, we introduce errors to the NW positions to show the advantages of the tapered NW structures can be projected to random closely packed NW arrays. The results obtained in this paper can provide guidelines for designing efficient NW DUV-LEDs.

Tapering-induced enhancement of light extraction efficiency of nanowire deep ultraviolet LED by theoretical simulations

KAUST Repository

Lin, Ronghui; Galan, Sergio Valdes; Sun, Haiding; Hu, Yangrui; Alias, Mohd Sharizal; Janjua, Bilal; Ng, Tien Khee; Ooi, Boon S.; Li, Xiaohang

2018-01-01

A nanowire (NW) structure provides an alternative scheme for deep ultraviolet light emitting diodes (DUV-LEDs) that promises high material quality and better light extraction efficiency (LEE). In this report, we investigate the influence of the tapering angle of closely packed AlGaN NWs, which is found to exist naturally in molecular beam epitaxy (MBE) grown NW structures, on the LEE of NW DUV-LEDs. It is observed that, by having a small tapering angle, the vertical extraction is greatly enhanced for both transverse magnetic (TM) and transverse electric (TE) polarizations. Most notably, the vertical extraction of TM emission increased from 4.8% to 24.3%, which makes the LEE reasonably large to achieve high-performance DUV-LEDs. This is because the breaking of symmetry in the vertical direction changes the propagation of the light significantly to allow more coupling into radiation modes. Finally, we introduce errors to the NW positions to show the advantages of the tapered NW structures can be projected to random closely packed NW arrays. The results obtained in this paper can provide guidelines for designing efficient NW DUV-LEDs.

Heart-Rate Variability During Deep Sleep in World-Class Alpine Skiers: A Time-Efficient Alternative to Morning Supine Measurements.

Science.gov (United States)

Herzig, David; Testorelli, Moreno; Olstad, Daniela Schäfer; Erlacher, Daniel; Achermann, Peter; Eser, Prisca; Wilhelm, Matthias

2017-05-01

It is increasingly popular to use heart-rate variability (HRV) to tailor training for athletes. A time-efficient method is HRV assessment during deep sleep. To validate the selection of deep-sleep segments identified by RR intervals with simultaneous electroencephalography (EEG) recordings and to compare HRV parameters of these segments with those of standard morning supine measurements. In 11 world-class alpine skiers, RR intervals were monitored during 10 nights, and simultaneous EEGs were recorded during 2-4 nights. Deep sleep was determined from the HRV signal and verified by delta power from the EEG recordings. Four further segments were chosen for HRV determination, namely, a 4-h segment from midnight to 4 AM and three 5-min segments: 1 just before awakening, 1 after waking in supine position, and 1 in standing after orthostatic challenge. Training load was recorded every day. A total of 80 night and 68 morning measurements of 9 athletes were analyzed. Good correspondence between the phases selected by RR intervals vs those selected by EEG was found. Concerning root-mean-squared difference of successive RR intervals (RMSSD), a marker for parasympathetic activity, the best relationship with the morning supine measurement was found in deep sleep. HRV is a simple tool for approximating deep-sleep phases, and HRV measurement during deep sleep could provide a time-efficient alternative to HRV in supine position.

A deep learning and novelty detection framework for rapid phenotyping in high-content screening

Science.gov (United States)

Sommer, Christoph; Hoefler, Rudolf; Samwer, Matthias; Gerlich, Daniel W.

2017-01-01

Supervised machine learning is a powerful and widely used method for analyzing high-content screening data. Despite its accuracy, efficiency, and versatility, supervised machine learning has drawbacks, most notably its dependence on a priori knowledge of expected phenotypes and time-consuming classifier training. We provide a solution to these limitations with CellCognition Explorer, a generic novelty detection and deep learning framework. Application to several large-scale screening data sets on nuclear and mitotic cell morphologies demonstrates that CellCognition Explorer enables discovery of rare phenotypes without user training, which has broad implications for improved assay development in high-content screening. PMID:28954863

Radiation-hard, high efficiency InP solar cell and panel development

International Nuclear Information System (INIS)

Keavney, C.J.; Vernon, S.M.; Haven, V.E.; Nowlan, M.J.; Walters, R.J.; Slatter, R.L.; Summers, G.P.

1991-01-01

Indium phosphide solar cells with efficiencies over 19% (Air mass zero, 25 degrees C) and area of 4 cm 2 have been made and incorporated into prototype panels. The panels will be tested in space to confirm the high radiation resistance expected from InP solar cells, which makes the material attractive for space use, particularly in high-radiation orbits. Laboratory testing indicated an end-of-life efficiency of 15.5% after 10 15 1 MeV electrons, and 12% after 10 16 . These cells are made by metalorganic chemical vapor deposition, and have a shallow homojunction structure. The manufacturing process is amendable to scale-up to larger volumes; more than 200 cells were produced in the laboratory operation. Cell performance, radiation degradation, annealing behavior, and results of deep level transient spectroscopy studies are presented in this paper

Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.

Science.gov (United States)

Parsa, Maryam; Panda, Priyadarshini; Sen, Shreyas; Roy, Kaushik

2017-07-01

Recent progress in biosensor technology and wearable devices has created a formidable opportunity for remote healthcare monitoring systems as well as real-time diagnosis and disease prevention. The use of data mining techniques is indispensable for analysis of the large pool of data generated by the wearable devices. Deep learning is among the promising methods for analyzing such data for healthcare applications and disease diagnosis. However, the conventional deep neural networks are computationally intensive and it is impractical to use them in real-time diagnosis with low-powered on-body devices. We propose Staged Inference using Conditional Deep Learning (SICDL), as an energy efficient approach for creating healthcare monitoring systems. For smart diagnostics, we observe that all diagnoses are not equally challenging. The proposed approach thus decomposes the diagnoses into preliminary analysis (such as healthy vs unhealthy) and detailed analysis (such as identifying the specific type of cardio disease). The preliminary diagnosis is conducted real-time with a low complexity neural network realized on the resource-constrained on-body device. The detailed diagnosis requires a larger network that is implemented remotely in cloud and is conditionally activated only for detailed diagnosis (unhealthy individuals). We evaluated the proposed approach using available physiological sensor data from Physionet databases, and achieved 38% energy reduction in comparison to the conventional deep learning approach.

Deep borehole disposal of high-level radioactive waste.

Energy Technology Data Exchange (ETDEWEB)

Stein, Joshua S.; Freeze, Geoffrey A.; Brady, Patrick Vane; Swift, Peter N.; Rechard, Robert Paul; Arnold, Bill Walter; Kanney, Joseph F.; Bauer, Stephen J.

2009-07-01

Preliminary evaluation of deep borehole disposal of high-level radioactive waste and spent nuclear fuel indicates the potential for excellent long-term safety performance at costs competitive with mined repositories. Significant fluid flow through basement rock is prevented, in part, by low permeabilities, poorly connected transport pathways, and overburden self-sealing. Deep fluids also resist vertical movement because they are density stratified. Thermal hydrologic calculations estimate the thermal pulse from emplaced waste to be small (less than 20 C at 10 meters from the borehole, for less than a few hundred years), and to result in maximum total vertical fluid movement of {approx}100 m. Reducing conditions will sharply limit solubilities of most dose-critical radionuclides at depth, and high ionic strengths of deep fluids will prevent colloidal transport. For the bounding analysis of this report, waste is envisioned to be emplaced as fuel assemblies stacked inside drill casing that are lowered, and emplaced using off-the-shelf oilfield and geothermal drilling techniques, into the lower 1-2 km portion of a vertical borehole {approx}45 cm in diameter and 3-5 km deep, followed by borehole sealing. Deep borehole disposal of radioactive waste in the United States would require modifications to the Nuclear Waste Policy Act and to applicable regulatory standards for long-term performance set by the US Environmental Protection Agency (40 CFR part 191) and US Nuclear Regulatory Commission (10 CFR part 60). The performance analysis described here is based on the assumption that long-term standards for deep borehole disposal would be identical in the key regards to those prescribed for existing repositories (40 CFR part 197 and 10 CFR part 63).

Highly Efficient Spectrally Stable Red Perovskite Light-Emitting Diodes.

Science.gov (United States)

Tian, Yu; Zhou, Chenkun; Worku, Michael; Wang, Xi; Ling, Yichuan; Gao, Hanwei; Zhou, Yan; Miao, Yu; Guan, Jingjiao; Ma, Biwu

2018-05-01

Perovskite light-emitting diodes (LEDs) have recently attracted great research interest for their narrow emissions and solution processability. Remarkable progress has been achieved in green perovskite LEDs in recent years, but not blue or red ones. Here, highly efficient and spectrally stable red perovskite LEDs with quasi-2D perovskite/poly(ethylene oxide) (PEO) composite thin films as the light-emitting layer are reported. By controlling the molar ratios of organic salt (benzylammonium iodide) to inorganic salts (cesium iodide and lead iodide), luminescent quasi-2D perovskite thin films are obtained with tunable emission colors from red to deep red. The perovskite/polymer composite approach enables quasi-2D perovskite/PEO composite thin films to possess much higher photoluminescence quantum efficiencies and smoothness than their neat quasi-2D perovskite counterparts. Electrically driven LEDs with emissions peaked at 638, 664, 680, and 690 nm have been fabricated to exhibit high brightness and external quantum efficiencies (EQEs). For instance, the perovskite LED with an emission peaked at 680 nm exhibits a brightness of 1392 cd m -2 and an EQE of 6.23%. Moreover, exceptional electroluminescence spectral stability under continuous device operation has been achieved for these red perovskite LEDs. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prime costs and economic efficiency of deep drilling in Chechen-Ingush ASSR

Energy Technology Data Exchange (ETDEWEB)

Umanskii, L.M.

1982-04-01

The possibilities of reducing the prime costs of deep well drilling and improving the efficiency of drilling are considered. The dynamics of performance over the last two five-year plan (FYP) periods is analyzed and it is shown that the performance in the 10th FYP did not improve as compared to the 9th FYP. This is due to geological conditions and shortcomings in the technology and organization of drilling. It is shown that the speed and depth of drilling are decisive factors influencing costs.

Towards a Switched-Capacitor Based Stimulator for Efficient Deep-Brain Stimulation

Science.gov (United States)

Vidal, Jose; Ghovanloo, Maysam

2013-01-01

We have developed a novel 4-channel prototype stimulation circuit for implantable neurological stimulators (INS). This Switched-Capacitor based Stimulator (SCS) aims to utilize charge storage and charge injection techniques to take advantage of both the efficiency of conventional voltage-controlled stimulators (VCS) and the safety and controllability of current-controlled stimulators (CCS). The discrete SCS prototype offers fine control over stimulation parameters such as voltage, current, pulse width, frequency, and active electrode channel via a LabVIEW graphical user interface (GUI) when connected to a PC through USB. Furthermore, the prototype utilizes a floating current sensor to provide charge-balanced biphasic stimulation and ensure safety. The stimulator was analyzed using an electrode-electrolyte interface (EEI) model as well as with a pair of pacing electrodes in saline. The primary motivation of this research is to test the feasibility and functionality of a safe, effective, and power-efficient switched-capacitor based stimulator for use in Deep Brain Stimulation. PMID:21095987

Deep-Sky Video Astronomy

CERN Document Server

Massey, Steve

2009-01-01

A guide to using modern integrating video cameras for deep-sky viewing and imaging with the kinds of modest telescopes available commercially to amateur astronomers. It includes an introduction and a brief history of the technology and camera types. It examines the pros and cons of this unrefrigerated yet highly efficient technology

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

Science.gov (United States)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Applications of Deep Learning in Biomedicine.

Science.gov (United States)

Mamoshina, Polina; Vieira, Armando; Putin, Evgeny; Zhavoronkov, Alex

2016-05-02

Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.

Technologies in deep and ultra-deep well drilling: Present status, challenges and future trend in the 13th Five-Year Plan period (2016–2020

Directory of Open Access Journals (Sweden)

Haige Wang

2017-09-01

Full Text Available During the 12th Five-Year Plan period (2011–2015, CNPC independently developed a series of new drilling equipment, tools and chemical materials for deep and ultra-deep wells, including six packages of key drilling equipment: rigs for wells up to 8000 m deep, quadruple-joint-stand rigs, automatic pipe handling devices for rigs for wells being 5000/7000 m deep, managed pressure drilling systems & equipment, gas/fuel alternative combustion engine units, and air/gas/underbalanced drilling systems; seven sets of key drilling tools: automatic vertical well drilling tools, downhole turbine tools, high-performance PDC bits, hybrid bits, bit jet pulsation devices, no-drilling-surprise monitoring system, & casing running devices for top drive; and five kinds of drilling fluids and cementing slurries: high temperature and high density water-based drilling fluids, oil-based drilling fluids, high temperature and large temperature difference cementing slurry, and ductile cement slurry system. These new development technologies have played an important role in supporting China's oil and gas exploration and development business. During the following 13th Five-Year Plan period (2016–2020, there are still many challenges to the drilling of deep and ultra-deep wells, such as high temperatures, high pressures, narrow pressure window, wellbore integrity and so on, as well as the enormous pressure on cost reduction and efficiency improvement. Therefore, the future development trend will be focused on the development of efficient and mobile rigs, high-performance drill bits and auxiliary tools, techniques for wellbore integrity and downhole broadband telemetry, etc. In conclusion, this study will help improve the ability and level of drilling ultra-deep wells and provide support for oil and gas exploration and development services in China. Keywords: Deep well, Ultra-deep well, Drilling techniques, Progress, Challenge, Strategy, CNPC

A Programmable High-Voltage Compliance Neural Stimulator for Deep Brain Stimulation in Vivo

Directory of Open Access Journals (Sweden)

Cihun-Siyong Alex Gong

2015-05-01

Full Text Available Deep brain stimulation (DBS is one of the most effective therapies for movement and other disorders. The DBS neurosurgical procedure involves the implantation of a DBS device and a battery-operated neurotransmitter, which delivers electrical impulses to treatment targets through implanted electrodes. The DBS modulates the neuronal activities in the brain nucleus for improving physiological responses as long as an electric discharge above the stimulation threshold can be achieved. In an effort to improve the performance of an implanted DBS device, the device size, implementation cost, and power efficiency are among the most important DBS device design aspects. This study aims to present preliminary research results of an efficient stimulator, with emphasis on conversion efficiency. The prototype stimulator features high-voltage compliance, implemented with only a standard semiconductor process, without the use of extra masks in the foundry through our proposed circuit structure. The results of animal experiments, including evaluation of evoked responses induced by thalamic electrical stimuli with our fabricated chip, were shown to demonstrate the proof of concept of our design.

Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification.

Science.gov (United States)

Rueckauer, Bodo; Lungu, Iulia-Alexandra; Hu, Yuhuang; Pfeiffer, Michael; Liu, Shih-Chii

2017-01-01

Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs) can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications.

Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification

Directory of Open Access Journals (Sweden)

Bodo Rueckauer

2017-12-01

Full Text Available Spiking neural networks (SNNs can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications.

Status and prospects of exploration and exploitation key technologies of the deep petroleum resources in onshore China

Directory of Open Access Journals (Sweden)

Genshun Yao

2018-02-01

Full Text Available In recent years, China's deep oil and gas exploration and exploitation have developed rapidly. Technological advancements have played an important role in the rapid exploration and highly efficient development. Aimed at the complex engineering geological environment of deep oil and gas in China, this paper has combined the four technological systems that have made significant progress, mainly including: (1 seismic imaging and reservoir prediction techniques for deep–burial complex structures, includign “2W1S” technique (wide-band, wide azimuth, and small bin, RTM (Reverse Time Migration, integrated modeling technology for complex structures and variable velocity mapping technique, improving structural interpretation accuracy, ensuring high precision ofimaging, and prediction for deep geological bodies; (2 deep speed raising and efficiency drilling technology series, which significantly improved the drilling speed, in turn reduced the drilling cost and drilling risk; (3 development of a deep high-temperature and high-pressure logging technology series, which provided a guarantee for the accurate identification of reservoir properties and fluid properties; (4 the efficient development technology for deep reservoirs, especially the development and maturity of the reconstruction volume technology, improve the production of single well and the benefit of deep oil and gas development. This paper further points out the improvement direction of the four major technology series of deep oil based on the analysis of the current development of the four major technological systems. Moreover, the development of applicability and economy for technical system is the key to realize high efficiency and low-cost exploration and development of deep oil and gas. Keywords: Deep oil & gas, Exploration and exploitation technologies, Seismic, Logging, Drilling, Petroleum reservoir stimulation

Technology Roadmap: High-Efficiency, Low-Emissions Coal-Fired Power Generation

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-07-01

Coal is the largest source of power globally and, given its wide availability and relatively low cost, it is likely to remain so for the foreseeable future. The High-Efficiency, Low-Emissions Coal-Fired Power Generation Roadmap describes the steps necessary to adopt and further develop technologies to improve the efficiency of the global fleet of coal. To generate the same amount of electricity, a more efficient coal-fired unit will burn less fuel, emit less carbon, release less local air pollutants, consume less water and have a smaller footprint. High-efficiency, low emissions (HELE) technologies in operation already reach a thermal efficiency of 45%, and technologies in development promise even higher values. This compares with a global average efficiency for today’s fleet of coal-fired plants of 33%, where three-quarters of operating units use less efficient technologies and more than half is over 25 years old. A successful outcome to ongoing RD&D could see units with efficiencies approaching 50% or even higher demonstrated within the next decade. Generation from older, less efficient technology must gradually be phased out. Technologies exist to make coal-fired power generation much more effective and cleaner burning. Of course, while increased efficiency has a major role to play in reducing emissions, particularly over the next 10 years, carbon capture and storage (CCS) will be essential in the longer term to make the deep cuts in carbon emissions required for a low-carbon future. Combined with CCS, HELE technologies can cut CO2 emissions from coal-fired power generation plants by as much as 90%, to less than 100 grams per kilowatt-hour. HELE technologies will be an influential factor in the deployment of CCS. For the same power output, a higher efficiency coal plant will require less CO2 to be captured; this means a smaller, less costly capture plant; lower operating costs; and less CO2 to be transported and stored.

Criteria for calculating the efficiency of deep-pleated HEPA filters with aluminum separators during and after design basis accidents

International Nuclear Information System (INIS)

Bergman, W.; First, M.W.; Anderson, W.L.

1995-01-01

We have reviewed the literature on the performance of HEPA filters under normal and abnormal conditions to establish criteria for calculating the efficiency of HEPA filters in a DOE nonreactor nuclear facility during and after a Design Basis Accident (DBA). This study is only applicable to the standard deep-pleated HEPA filter with aluminum separators as specified in ASME N509[1]. Other HEPA filter designs such as the mini-pleat and separatorless filters are not included in this study. The literature review included the performance of new filters and parameters that may cause deterioration in the filter performance such as filter age, radiation, corrosive chemicals, seismic and rough handling, high temperature, moisture, particle clogging, high air flow and pressure pulses. The deterioration of the filter efficiency depends on the exposure parameters; in severe exposure conditions the filter will be damaged and have a residual efficiency of 0%. There are large gaps and limitations in the data that introduce significant error in the estimates of HEPA filter efficiencies under DBA conditions. Because of this limitation, conservative values of filter efficiency were chosen. The estimation of the efficiency of the HEPA filters under DBA conditions involves three steps: (1) The filter pressure drop and environmental parameters are determined during and after the DBA, (2) Comparing the filter pressure drop to a set of threshold values above which the filter is damaged. There is a different threshold value for each combination of environmental parameters, and (3) Determining the filter efficiency. If the filter pressure drop is greater than the threshold value, the filter is damaged and is assigned 0% efficiency. If the pressure drop is less, then the filter is not damaged and the efficiency is determined from literature values of the efficiency at the environmental conditions

Criteria for calculating the efficiency of deep-pleated HEPA filters with aluminum separators during and after design basis accidents

Energy Technology Data Exchange (ETDEWEB)

Bergman, W.; First, M.W.; Anderson, W.L. [Lawrence Livermore National Laboratory, CA (United States)] [and others

1995-02-01

We have reviewed the literature on the performance of HEPA filters under normal and abnormal conditions to establish criteria for calculating the efficiency of HEPA filters in a DOE nonreactor nuclear facility during and after a Design Basis Accident (DBA). This study is only applicable to the standard deep-pleated HEPA filter with aluminum separators as specified in ASME N509[1]. Other HEPA filter designs such as the mini-pleat and separatorless filters are not included in this study. The literature review included the performance of new filters and parameters that may cause deterioration in the filter performance such as filter age, radiation, corrosive chemicals, seismic and rough handling, high temperature, moisture, particle clogging, high air flow and pressure pulses. The deterioration of the filter efficiency depends on the exposure parameters; in severe exposure conditions the filter will be damaged and have a residual efficiency of 0%. There are large gaps and limitations in the data that introduce significant error in the estimates of HEPA filter efficiencies under DBA conditions. Because of this limitation, conservative values of filter efficiency were chosen. The estimation of the efficiency of the HEPA filters under DBA conditions involves three steps: (1) The filter pressure drop and environmental parameters are determined during and after the DBA, (2) Comparing the filter pressure drop to a set of threshold values above which the filter is damaged. There is a different threshold value for each combination of environmental parameters, and (3) Determining the filter efficiency. If the filter pressure drop is greater than the threshold value, the filter is damaged and is assigned 0% efficiency. If the pressure drop is less, then the filter is not damaged and the efficiency is determined from literature values of the efficiency at the environmental conditions.

Nearly Efficiency-Droop-Free AlGaN-Based Ultraviolet Light-Emitting Diodes with a Specifically Designed Superlattice p-Type Electron Blocking Layer for High Mg Doping Efficiency

Science.gov (United States)

Zhang, Zi-Hui; Huang Chen, Sung-Wen; Chu, Chunshuang; Tian, Kangkai; Fang, Mengqian; Zhang, Yonghui; Bi, Wengang; Kuo, Hao-Chung

2018-04-01

This work reports a nearly efficiency-droop-free AlGaN-based deep ultraviolet light-emitting diode (DUV LED) emitting in the peak wavelength of 270 nm. The DUV LED utilizes a specifically designed superlattice p-type electron blocking layer (p-EBL). The superlattice p-EBL enables a high hole concentration in the p-EBL which correspondingly increases the hole injection efficiency into the multiple quantum wells (MQWs). The enhanced hole concentration within the MQW region can more efficiently recombine with electrons in the way of favoring the radiative recombination, leading to a reduced electron leakage current level. As a result, the external quantum efficiency for the proposed DUV LED structure is increased by 100% and the nearly efficiency-droop-free DUV LED structure is obtained experimentally.

Low-cost, high-precision micro-lensed optical fiber providing deep-micrometer to deep-nanometer-level light focusing.

Science.gov (United States)

Wen, Sy-Bor; Sundaram, Vijay M; McBride, Daniel; Yang, Yu

2016-04-15

A new type of micro-lensed optical fiber through stacking appropriate high-refractive microspheres at designed locations with respect to the cleaved end of an optical fiber is numerically and experimentally demonstrated. This new type of micro-lensed optical fiber can be precisely constructed with low cost and high speed. Deep micrometer-scale and submicrometer-scale far-field light spots can be achieved when the optical fibers are multimode and single mode, respectively. By placing an appropriate teardrop dielectric nanoscale scatterer at the far-field spot of this new type of micro-lensed optical fiber, a deep-nanometer near-field spot can also be generated with high intensity and minimum joule heating, which is valuable in high-speed, high-resolution, and high-power nanoscale detection compared with traditional near-field optical fibers containing a significant portion of metallic material.

Efficiency Optimization by Considering the High Voltage Flyback Transformer Parasitics using an Automatic Winding Layout Technique

DEFF Research Database (Denmark)

Thummala, Prasanth; Schneider, Henrik; Zhang, Zhe

2015-01-01

.The energy efficiency is optimized using a proposed new automatic winding layout (AWL) technique and a comprehensive loss model.The AWL technique generates a large number of transformer winding layouts.The transformer parasitics such as dc resistance, leakage inductance and self-capacitance are calculated...... for each winding layout.An optimization technique is formulated to minimize the sum of energy losses during charge and discharge operations.The efficiency and energy loss distribution results from the optimization routine provide a deep insight into the high voltage transformer designand its impact...

A highly efficient approach to protein interactome mapping based on collaborative filtering framework.

Science.gov (United States)

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-09

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

High efficiency fourth-harmonic generation from nanosecond fiber master oscillator power amplifier

Science.gov (United States)

Mu, Xiaodong; Steinvurzel, Paul; Rose, Todd S.; Lotshaw, William T.; Beck, Steven M.; Clemmons, James H.

2016-03-01

We demonstrate high power, deep ultraviolet (DUV) conversion to 266 nm through frequency quadrupling of a nanosecond pulse width 1064 nm fiber master oscillator power amplifier (MOPA). The MOPA system uses an Yb-doped double-clad polarization-maintaining large mode area tapered fiber as the final gain stage to generate 0.5-mJ, 10 W, 1.7- ns single mode pulses at a repetition rate of 20 kHz with measured spectral bandwidth of 10.6 GHz (40 pm), and beam qualities of Mx 2=1.07 and My 2=1.03, respectively. Using LBO and BBO crystals for the second-harmonic generation (SHG) and fourth-harmonic generation (FHG), we have achieved 375 μJ (7.5 W) and 92.5 μJ (1.85 W) at wavelengths of 532 nm and 266 nm, respectively. To the best of our knowledge these are the highest narrowband infrared, green and UV pulse energies obtained to date from a fully spliced fiber amplifier. We also demonstrate high efficiency SHG and FHG with walk-off compensated (WOC) crystal pairs and tightly focused pump beam. An SHG efficiency of 75%, FHG efficiency of 47%, and an overall efficiency of 35% from 1064 nm to 266 nm are obtained.

An Exciplex Host for Deep-Blue Phosphorescent Organic Light-Emitting Diodes.

Science.gov (United States)

Lim, Hyoungcheol; Shin, Hyun; Kim, Kwon-Hyeon; Yoo, Seung-Jun; Huh, Jin-Suk; Kim, Jang-Joo

2017-11-01

The use of exciplex hosts is attractive for high-performance phosphorescent organic light-emitting diodes (PhOLEDs) and thermally activated delayed fluorescence OLEDs, which have high external quantum efficiency, low driving voltage, and low efficiency roll-off. However, exciplex hosts for deep-blue OLEDs have not yet been reported because of the difficulties in identifying suitable molecules. Here, we report a deep-blue-emitting exciplex system with an exciplex energy of 3.0 eV. It is composed of a carbazole-based hole-transporting material (mCP) and a phosphine-oxide-based electron-transporting material (BM-A10). The blue PhOLEDs exhibited maximum external quantum efficiency of 24% with CIE coordinates of (0.15, 0.21) and longer lifetime than the single host devices.

Cyclometalated Iridium(III) Carbene Phosphors for Highly Efficient Blue Organic Light-Emitting Diodes.

Science.gov (United States)

Chen, Zhao; Wang, Liqi; Su, Sikai; Zheng, Xingyu; Zhu, Nianyong; Ho, Cheuk-Lam; Chen, Shuming; Wong, Wai-Yeung

2017-11-22

Five deep blue carbene-based iridium(III) phosphors were synthesized and characterized. Interestingly, one of them can be fabricated into deep blue, sky blue and white organic light-emitting diodes (OLEDs) through changing the host materials and exciton blocking layers. These deep and sky blue devices exhibit Commission Internationale de l'Éclairage (CIE) coordinates of (0.145, 0.186) and (0.152, 0.277) with external quantum efficiency (EQE) of 15.2% and 9.6%, respectively. The EQE of the deep blue device can be further improved up to 19.0% by choosing a host with suitable energy level of its lowest unoccupied molecular orbital (LUMO).

Preliminary analyses of the deep geoenvironmental characteristics for the deep borehole disposal of high-level radioactive waste in Korea

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Youl; Lee, Min Soo; Choi, Heui Joo; Kim, Geon Young; Kim, Kyung Su [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2016-06-15

Spent fuels from nuclear power plants, as well as high-level radioactive waste from the recycling of spent fuels, should be safely isolated from human environment for an extremely long time. Recently, meaningful studies on the development of deep borehole radioactive waste disposal system in 3-5 km depth have been carried out in USA and some countries in Europe, due to great advance in deep borehole drilling technology. In this paper, domestic deep geoenvironmental characteristics are preliminarily investigated to analyze the applicability of deep borehole disposal technology in Korea. To do this, state-of-the art technologies in USA and some countries in Europe are reviewed, and geological and geothermal data from the deep boreholes for geothermal usage are analyzed. Based on the results on the crystalline rock depth, the geothermal gradient and the spent fuel types generated in Korea, a preliminary deep borehole concept including disposal canister and sealing system, is suggested.

Preliminary analyses of the deep geoenvironmental characteristics for the deep borehole disposal of high-level radioactive waste in Korea

International Nuclear Information System (INIS)

Lee, Jong Youl; Lee, Min Soo; Choi, Heui Joo; Kim, Geon Young; Kim, Kyung Su

2016-01-01

Spent fuels from nuclear power plants, as well as high-level radioactive waste from the recycling of spent fuels, should be safely isolated from human environment for an extremely long time. Recently, meaningful studies on the development of deep borehole radioactive waste disposal system in 3-5 km depth have been carried out in USA and some countries in Europe, due to great advance in deep borehole drilling technology. In this paper, domestic deep geoenvironmental characteristics are preliminarily investigated to analyze the applicability of deep borehole disposal technology in Korea. To do this, state-of-the art technologies in USA and some countries in Europe are reviewed, and geological and geothermal data from the deep boreholes for geothermal usage are analyzed. Based on the results on the crystalline rock depth, the geothermal gradient and the spent fuel types generated in Korea, a preliminary deep borehole concept including disposal canister and sealing system, is suggested

Research Update: Behind the high efficiency of hybrid perovskite solar cells

Directory of Open Access Journals (Sweden)

Azhar Fakharuddin

2016-09-01

Full Text Available Perovskite solar cells (PSCs marked tremendous progress in a short period of time and offer bright hopes for cheap solar electricity. Despite high power conversion efficiency >20%, its poor operational stability as well as involvement of toxic, volatile, and less-abundant materials hinders its practical deployment. The fact that degradation and toxicity are typically observed in the most successful perovskite involving organic cation and toxic lead, i.e., CH3NH3PbX3, requires a deep understanding of their role in photovoltaic performance in order to envisage if a non-toxic, stable yet highly efficient device is feasible. Towards this, we first provide an overview of the basic chemistry and physics of halide perovskites and its correlation with its extraordinary properties such as crystal structure, bandgap, ferroelectricity, and electronic transport. We then discuss device related aspects such as the various device designs in PSCs and role of interfaces in origin of PV parameters particularly open circuit voltage, various film processing methods and their effect on morphology and characteristics of perovskite films, and the origin and elimination of hysteresis and operational stability in these devices. We then identify future perspectives for stable and efficient PSCs for practical deployment.

High self-perceived exercise exertion before bedtime is associated with greater objectively assessed sleep efficiency.

Science.gov (United States)

Brand, Serge; Kalak, Nadeem; Gerber, Markus; Kirov, Roumen; Pühse, Uwe; Holsboer-Trachsler, Edith

2014-09-01

To assess the association between self-perceived exercise exertion before bedtime and objectively measured sleep. Fifty-two regularly exercising young adults (mean age, 19.70 years; 54% females) underwent sleep electroencephalographic recordings 1.5 h after completing moderate to vigorous exercise in the evening. Before sleeping, participants answered questions regarding degree of exertion of the exercise undertaken. Greater self-perceived exertion before bedtime was associated with higher objectively assessed sleep efficiency (r = 0.69, P associated with more deep sleep, shortened sleep onset time, fewer awakenings after sleep onset, and shorter wake duration after sleep onset. Multiple linear regression analysis showed that objective sleep efficiency was predicted by increased exercise exertion, shortened sleep onset time, increased deep sleep, and decreased light sleep. Against expectations and general recommendations for sleep hygiene, high self-perceived exercise exertion before bedtime was associated with better sleep patterns in a sample of healthy young adults. Further studies should also focus on elderly adults and adults suffering from insomnia. Copyright © 2014 Elsevier B.V. All rights reserved.

DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

OpenAIRE

Qiao Wei; Li Ying; Wu Zhong-Hai

2017-01-01

Deep neural networks (DNNs) have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling ...

DeepPy: Pythonic deep learning

DEFF Research Database (Denmark)

Larsen, Anders Boesen Lindbo

This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background in scientific computing in Python will quickly...... be able to understand and change the DeepPy codebase as it is mainly implemented using high-level NumPy primitives. Moreover, DeepPy supports complex network architectures by letting the user compose mathematical expressions as directed graphs. The latest version is available at http...

Exploration Of Deep Learning Algorithms Using Openacc Parallel Programming Model

KAUST Repository

Hamam, Alwaleed A.

2017-03-13

Deep learning is based on a set of algorithms that attempt to model high level abstractions in data. Specifically, RBM is a deep learning algorithm that used in the project to increase it\\'s time performance using some efficient parallel implementation by OpenACC tool with best possible optimizations on RBM to harness the massively parallel power of NVIDIA GPUs. GPUs development in the last few years has contributed to growing the concept of deep learning. OpenACC is a directive based ap-proach for computing where directives provide compiler hints to accelerate code. The traditional Restricted Boltzmann Ma-chine is a stochastic neural network that essentially perform a binary version of factor analysis. RBM is a useful neural net-work basis for larger modern deep learning model, such as Deep Belief Network. RBM parameters are estimated using an efficient training method that called Contrastive Divergence. Parallel implementation of RBM is available using different models such as OpenMP, and CUDA. But this project has been the first attempt to apply OpenACC model on RBM.

Exploration Of Deep Learning Algorithms Using Openacc Parallel Programming Model

KAUST Repository

Hamam, Alwaleed A.; Khan, Ayaz H.

2017-01-01

Deep learning is based on a set of algorithms that attempt to model high level abstractions in data. Specifically, RBM is a deep learning algorithm that used in the project to increase it's time performance using some efficient parallel implementation by OpenACC tool with best possible optimizations on RBM to harness the massively parallel power of NVIDIA GPUs. GPUs development in the last few years has contributed to growing the concept of deep learning. OpenACC is a directive based ap-proach for computing where directives provide compiler hints to accelerate code. The traditional Restricted Boltzmann Ma-chine is a stochastic neural network that essentially perform a binary version of factor analysis. RBM is a useful neural net-work basis for larger modern deep learning model, such as Deep Belief Network. RBM parameters are estimated using an efficient training method that called Contrastive Divergence. Parallel implementation of RBM is available using different models such as OpenMP, and CUDA. But this project has been the first attempt to apply OpenACC model on RBM.

Convolutional networks for fast, energy-efficient neuromorphic computing.

Science.gov (United States)

Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S

2016-10-11

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

Evaluation of high-perimeter electrode designs for deep brain stimulation

Science.gov (United States)

Howell, Bryan; Grill, Warren M.

2014-08-01

Objective. Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, complications including infections and mis-programing following surgical replacement of the battery-powered implantable pulse generator adversely impact the safety profile of this therapy. We sought to decrease power consumption and extend battery life by modifying the electrode geometry to increase stimulation efficiency. The specific goal of this study was to determine whether electrode contact perimeter or area had a greater effect on increasing stimulation efficiency. Approach. Finite-element method (FEM) models of eight prototype electrode designs were used to calculate the electrode access resistance, and the FEM models were coupled with cable models of passing axons to quantify stimulation efficiency. We also measured in vitro the electrical properties of the prototype electrode designs and measured in vivo the stimulation efficiency following acute implantation in anesthetized cats. Main results. Area had a greater effect than perimeter on altering the electrode access resistance; electrode (access or dynamic) resistance alone did not predict stimulation efficiency because efficiency was dependent on the shape of the potential distribution in the tissue; and, quantitative assessment of stimulation efficiency required consideration of the effects of the electrode-tissue interface impedance. Significance. These results advance understanding of the features of electrode geometry that are important for designing the next generation of efficient DBS electrodes.

Enhancing the color gamut of white displays using novel deep-blue organic fluorescent dyes to form color-changed thin films with improved efficiency

Science.gov (United States)

Liu, Wei-Ting; Huang, Wen-Yao

2012-10-01

This study used the novel fluorescence based deep-blue-emitting molecule BPVPDA in an organic fluorescent color thin film to exhibit deep blue color with CIE coordinates of (0.13, 0.16). The developed original organic RGB color thin film technology enables the optimization of the distinctive features of an organic light emitting diode (OLED) and thin-film-transistor (TFT) LCD display. The color filter structure maintains the same high resolution to obtain a higher level of brightness in comparison with conventional organic RGB color thin film. The image-processing engine is designed to achieve a sharp text image for a TFT LCD with organic color thin films. The organic color thin films structure uses an organic dye dopant in a limpid photoresist. With this technology, the following characteristics can be obtained: 1. high color reproduction of gamut ratio, and 2. improved luminous efficiency with organic color fluorescent thin film. This performance is among the best results ever reported for a color-filter used on TFT-LCD or OLED.

The influence of deep cryogenic treatment on the properties of high-vanadium alloy steel

Energy Technology Data Exchange (ETDEWEB)

Li, Haizhi [Key Laboratory of Electromagnetic Processing of Materials (Ministry of Education), Northeastern University, Shenyang 110819 (China); Tong, Weiping, E-mail: wptong@mail.neu.edu.cn [Key Laboratory of Electromagnetic Processing of Materials (Ministry of Education), Northeastern University, Shenyang 110819 (China); Cui, Junjun [State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819 (China); Zhang, Hui [Key Laboratory of Electromagnetic Processing of Materials (Ministry of Education), Northeastern University, Shenyang 110819 (China); Chen, Liqing [State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819 (China); Zuo, Liang [Key Laboratory for Anisotropy and Texture of Materials (Ministry of Education), School of Materials and Metallurgy, Northeastern University, Shenyang 110819 (China)

2016-04-26

Deep cryogenic treatment can improve the mechanical properties of many metallic materials, but there are few reports of the effect of deep cryogenic treatment on high-vanadium alloy steel. The main objective of this work is to investigate the effect of deep cryogenic treatment on the microstructure, hardness, impact toughness and abrasive wear resistance of high-vanadium alloy steel. The results show that large amounts of small secondary carbide precipitation after deep cryogenic treatment and microcracks were detected and occurred preferentially at carbide/matrix interfaces; except for the hardness, the mechanical properties increased compared to those of the conventional treatment sample. By increasing the deep cryogenic processing time and cycle number, impact toughness and abrasive wear resistance can be further improved, the carbide contents continuously increase, and the hardness decreases.

Complete genome sequence of the highly Mn(II) tolerant Staphylococcus sp. AntiMn-1 isolated from deep-sea sediment in the Clarion-Clipperton Zone.

Science.gov (United States)

Wang, Xing; Lin, Danqiu; Jing, Xiaohuan; Zhu, Sidong; Yang, Jifang; Chen, Jigang

2018-01-20

Staphylococcus sp. AntiMn-1 is a deep-sea bacterium inhabiting seafloor sediment in the Clarion-Clipperton Zone (CCZ) that is highly tolerant to Mn(II) and displays efficient Mn(II) oxidation. Herein, we present the assembly and annotation of its genome. Copyright © 2017 Elsevier B.V. All rights reserved.

Learning with hierarchical-deep models.

Science.gov (United States)

Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

2013-08-01

We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach.

Directory of Open Access Journals (Sweden)

Sofia D Karamintziou

Full Text Available Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach.

Science.gov (United States)

Karamintziou, Sofia D; Custódio, Ana Luísa; Piallat, Brigitte; Polosan, Mircea; Chabardès, Stéphan; Stathis, Pantelis G; Tagaris, George A; Sakas, Damianos E; Polychronaki, Georgia E; Tsirogiannis, George L; David, Olivier; Nikita, Konstantina S

2017-01-01

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

Overview of Ecological Agriculture with High Efficiency

OpenAIRE

Huang, Guo-qin; Zhao, Qi-guo; Gong, Shao-lin; Shi, Qing-hua

2012-01-01

From the presentation, connotation, characteristics, principles, pattern, and technologies of ecological agriculture with high efficiency, we conduct comprehensive and systematic analysis and discussion of the theoretical and practical progress of ecological agriculture with high efficiency. (i) Ecological agriculture with high efficiency was first advanced in China in 1991. (ii) Ecological agriculture with high efficiency highlights "high efficiency", "ecology", and "combination". (iii) Ecol...

High-Resolution Ultrasound-Switchable Fluorescence Imaging in Centimeter-Deep Tissue Phantoms with High Signal-To-Noise Ratio and High Sensitivity via Novel Contrast Agents.

Science.gov (United States)

Cheng, Bingbing; Bandi, Venugopal; Wei, Ming-Yuan; Pei, Yanbo; D'Souza, Francis; Nguyen, Kytai T; Hong, Yi; Yuan, Baohong

2016-01-01

For many years, investigators have sought after high-resolution fluorescence imaging in centimeter-deep tissue because many interesting in vivo phenomena-such as the presence of immune system cells, tumor angiogenesis, and metastasis-may be located deep in tissue. Previously, we developed a new imaging technique to achieve high spatial resolution in sub-centimeter deep tissue phantoms named continuous-wave ultrasound-switchable fluorescence (CW-USF). The principle is to use a focused ultrasound wave to externally and locally switch on and off the fluorophore emission from a small volume (close to ultrasound focal volume). By making improvements in three aspects of this technique: excellent near-infrared USF contrast agents, a sensitive frequency-domain USF imaging system, and an effective signal processing algorithm, for the first time this study has achieved high spatial resolution (~ 900 μm) in 3-centimeter-deep tissue phantoms with high signal-to-noise ratio (SNR) and high sensitivity (3.4 picomoles of fluorophore in a volume of 68 nanoliters can be detected). We have achieved these results in both tissue-mimic phantoms and porcine muscle tissues. We have also demonstrated multi-color USF to image and distinguish two fluorophores with different wavelengths, which might be very useful for simultaneously imaging of multiple targets and observing their interactions in the future. This work has opened the door for future studies of high-resolution centimeter-deep tissue fluorescence imaging.

Deep sequencing analysis of HBV genotype shift and correlation with antiviral efficiency during adefovir dipivoxil therapy.

Directory of Open Access Journals (Sweden)

Yuwei Wang

Full Text Available Viral genotype shift in chronic hepatitis B (CHB patients during antiviral therapy has been reported, but the underlying mechanism remains elusive.38 CHB patients treated with ADV for one year were selected for studying genotype shift by both deep sequencing and Sanger sequencing method.Sanger sequencing method found that 7.9% patients showed mixed genotype before ADV therapy. In contrast, all 38 patients showed mixed genotype before ADV treatment by deep sequencing. 95.5% mixed genotype rate was also obtained from additional 200 treatment-naïve CHB patients. Of the 13 patients with genotype shift, the fraction of the minor genotype in 5 patients (38% increased gradually during the course of ADV treatment. Furthermore, responses to ADV and HBeAg seroconversion were associated with the high rate of genotype shift, suggesting drug and immune pressure may be key factors to induce genotype shift. Interestingly, patients with genotype C had a significantly higher rate of genotype shift than genotype B. In genotype shift group, ADV treatment induced a marked enhancement of genotype B ratio accompanied by a reduction of genotype C ratio, suggesting genotype C may be more sensitive to ADV than genotype B. Moreover, patients with dominant genotype C may have a better therapeutic effect. Finally, genotype shifts was correlated with clinical improvement in terms of ALT.Our findings provided a rational explanation for genotype shift among ADV-treated CHB patients. The genotype and genotype shift might be associated with antiviral efficiency.

Efficient generation of image chips for training deep learning algorithms

Science.gov (United States)

Han, Sanghui; Fafard, Alex; Kerekes, John; Gartley, Michael; Ientilucci, Emmett; Savakis, Andreas; Law, Charles; Parhan, Jason; Turek, Matt; Fieldhouse, Keith; Rovito, Todd

2017-05-01

Training deep convolutional networks for satellite or aerial image analysis often requires a large amount of training data. For a more robust algorithm, training data need to have variations not only in the background and target, but also radiometric variations in the image such as shadowing, illumination changes, atmospheric conditions, and imaging platforms with different collection geometry. Data augmentation is a commonly used approach to generating additional training data. However, this approach is often insufficient in accounting for real world changes in lighting, location or viewpoint outside of the collection geometry. Alternatively, image simulation can be an efficient way to augment training data that incorporates all these variations, such as changing backgrounds, that may be encountered in real data. The Digital Imaging and Remote Sensing Image Image Generation (DIRSIG) model is a tool that produces synthetic imagery using a suite of physics-based radiation propagation modules. DIRSIG can simulate images taken from different sensors with variation in collection geometry, spectral response, solar elevation and angle, atmospheric models, target, and background. Simulation of Urban Mobility (SUMO) is a multi-modal traffic simulation tool that explicitly models vehicles that move through a given road network. The output of the SUMO model was incorporated into DIRSIG to generate scenes with moving vehicles. The same approach was used when using helicopters as targets, but with slight modifications. Using the combination of DIRSIG and SUMO, we quickly generated many small images, with the target at the center with different backgrounds. The simulations generated images with vehicles and helicopters as targets, and corresponding images without targets. Using parallel computing, 120,000 training images were generated in about an hour. Some preliminary results show an improvement in the deep learning algorithm when real image training data are augmented with

Convolutional networks for fast, energy-efficient neuromorphic computing

Science.gov (United States)

Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.

2016-01-01

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489

Accounting for Organic Carbon Change in Deep Soil Altered Carbon Sequestration Efficiency

Science.gov (United States)

Li, J.; Liang, F.; Xu, M.; Huang, S.

2017-12-01

Study on soil organic carbon (SOC) sequestration under fertilization practices in croplands lacks information of soil C change at depth lower than plow layer (i.e. 20 30-cm). By synthesizing long-term datasets of fertilization experiments in four typical Chinese croplands representing black soil at Gongzhuling(GZL), aquatic Chao soil at Zhengzhou(ZZ), red soil at Qiyang(QY) and purple soil at Chongqing(CQ) city, we calculated changes in SOC storage relative to initial condition (ΔSOC) in 0-20cm and 0-60cm, organic C inputs (OC) from the stubble, roots and manure amendment, and C sequestration efficiency (CSE: the ratio of ΔSOC over OC) in 0-20cm and 0-60cm. The fertilization treatments include cropping with no fertilization (CK), chemical nitrogen, phosphorus and potassium fertilizers (NPK) and combined chemical fertilizers and manure (NPKM). Results showed SOC storage generally decreased with soil depth (i.e. 0-20 > 20-40, 40-60 cm) and increased with fertilizations (i.e. initial fertilizations, soil at depth (>20cm) can act as important soil carbon sinks in intrinsically high fertility soils (i.e. black soil) but less likely at poor fertility soil (i.e. aquatic Chao soil). It thus informs the need to account for C change in deep soils for estimating soil C sequestration capacity particularly with indigenously fertile cropland soils.

Highly Manufacturable Deep (Sub-Millimeter) Etching Enabled High Aspect Ratio Complex Geometry Lego-Like Silicon Electronics

KAUST Repository

Ghoneim, Mohamed T.; Hussain, Muhammad Mustafa

2017-01-01

A highly manufacturable deep reactive ion etching based process involving a hybrid soft/hard mask process technology shows high aspect ratio complex geometry Lego-like silicon electronics formation enabling free-form (physically flexible

The cost and performance of utility commercial lighting programs. A report from the Database on Energy Efficiency Programs (DEEP) project

Energy Technology Data Exchange (ETDEWEB)

Eto, J.; Vine, E.; Shown, L.; Sonnenblick, R.; Payne, C. [Lawrence Berkeley Lab., CA (United States). Energy and Environment Div.

1994-05-01

The objective of the Database on Energy Efficiency Programs (DEEP) is to document the measured cost and performance of utility-sponsored, energy-efficiency, demand-side management (DSM) programs. Consistent documentation of DSM programs is a challenging goal because of problems with data consistency, evaluation methodologies, and data reporting formats that continue to limit the usefulness and comparability of individual program results. This first DEEP report investigates the results of 20 recent commercial lighting DSM programs. The report, unlike previous reports of its kind, compares the DSM definitions and methodologies that each utility uses to compute costs and energy savings and then makes adjustments to standardize reported program results. All 20 programs were judged cost-effective when compared to avoided costs in their local areas. At an average cost of 3.9{cents}/kWh, however, utility-sponsored energy efficiency programs are not ``too cheap to meter.`` While it is generally agreed upon that utilities must take active measures to minimize the costs and rate impacts of DSM programs, the authors believe that these activities will be facilitated by industry adoption of standard definitions and reporting formats, so that the best program designs can be readily identified and adopted.

High Power Uplink Amplifier for Deep Space Communications, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — Critical to the success of delivering on the promise of deep space optical communications is the creation of a stable and reliable high power multichannel optical...

High Power Uplink Amplifier for Deep Space Communications, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Critical to the success of delivering on the promise of deep space optical communications is the creation of a stable and reliable high power multichannel optical...

Detecting atrial fibrillation by deep convolutional neural networks.

Science.gov (United States)

Xia, Yong; Wulan, Naren; Wang, Kuanquan; Zhang, Henggui

2018-02-01

Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. Efficient and accurate diagnosis of AF based on the ECG is valuable in clinical settings and remains challenging. In this paper, we proposed a novel method with high reliability and accuracy for AF detection via deep learning. The short-term Fourier transform (STFT) and stationary wavelet transform (SWT) were used to analyze ECG segments to obtain two-dimensional (2-D) matrix input suitable for deep convolutional neural networks. Then, two different deep convolutional neural network models corresponding to STFT output and SWT output were developed. Our new method did not require detection of P or R peaks, nor feature designs for classification, in contrast to existing algorithms. Finally, the performances of the two models were evaluated and compared with those of existing algorithms. Our proposed method demonstrated favorable performances on ECG segments as short as 5 s. The deep convolutional neural network using input generated by STFT, presented a sensitivity of 98.34%, specificity of 98.24% and accuracy of 98.29%. For the deep convolutional neural network using input generated by SWT, a sensitivity of 98.79%, specificity of 97.87% and accuracy of 98.63% was achieved. The proposed method using deep convolutional neural networks shows high sensitivity, specificity and accuracy, and, therefore, is a valuable tool for AF detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Solar Stirling for deep space applications

International Nuclear Information System (INIS)

Mason, Lee S.

2000-01-01

A study was performed to quantify the performance of solar thermal power systems for deep space planetary missions. The study incorporated projected advances in solar concentrator and energy conversion technologies. These technologies included inflatable structures, lightweight primary concentrators, high efficiency secondary concentrators, and high efficiency Stirling convertors. Analyses were performed to determine the mass and deployed area of multihundred watt solar thermal power systems for missions out to 40 astronomical units. Emphasis was given to system optimization, parametric sensitivity analyses, and concentrator configuration comparisons. The results indicated that solar thermal power systems are a competitive alternative to radioisotope systems out to 10 astronomical units without the cost or safety implications associated with nuclear sources

Synthesis of gold nanoflowers using deep eutectic solvent with high surface enhanced Raman scattering properties

Science.gov (United States)

Aghakhani Mahyari, Farzaneh; Tohidi, Maryam; Safavi, Afsaneh

2016-09-01

A facile, seed-less and one-pot method was developed for synthesis of gold nanoflowers with multiple tips through reduction of HAuCl4 with deep eutectic solvent at room temperature. This solvent is eco-friendly, low-cost, non-toxic and biodegradable and can act as both reducing and shape-controlling agent. In this protocol, highly branched and stable gold nanoflowers were obtained without using any capping agent. The obtained products were characterized by different techniques including, field emission scanning electron microscopy, transmission electron microscopy, x-ray diffraction and UV-vis spectroscopy. The as-prepared gold nanoflowers exhibit efficient surface-enhanced Raman scattering (SERS) properties which can be used as excellent substrates for SERS.

Highly Manufacturable Deep (Sub-Millimeter) Etching Enabled High Aspect Ratio Complex Geometry Lego-Like Silicon Electronics

KAUST Repository

Ghoneim, Mohamed T.

2017-02-01

A highly manufacturable deep reactive ion etching based process involving a hybrid soft/hard mask process technology shows high aspect ratio complex geometry Lego-like silicon electronics formation enabling free-form (physically flexible, stretchable, and reconfigurable) electronic systems.

Progress of OLED devices with high efficiency at high luminance

Science.gov (United States)

Nguyen, Carmen; Ingram, Grayson; Lu, Zhenghong

2014-03-01

Organic light emitting diodes (OLEDs) have progressed significantly over the last two decades. For years, OLEDs have been promoted as the next generation technology for flat panel displays and solid-state lighting due to their potential for high energy efficiency and dynamic range of colors. Although high efficiency can readily be obtained at low brightness levels, a significant decline at high brightness is commonly observed. In this report, we will review various strategies for achieving highly efficient phosphorescent OLED devices at high luminance. Specifically, we will provide details regarding the performance and general working principles behind each strategy. We will conclude by looking at how some of these strategies can be combined to produce high efficiency white OLEDs at high brightness.

High-power, high-efficiency FELs

International Nuclear Information System (INIS)

Sessler, A.M.

1989-04-01

High power, high efficiency FELs require tapering, as the particles loose energy, so as to maintain resonance between the electromagnetic wave and the particles. They also require focusing of the particles (usually done with curved pole faces) and focusing of the electromagnetic wave (i.e. optical guiding). In addition, one must avoid transverse beam instabilities (primarily resistive wall) and longitudinal instabilities (i.e sidebands). 18 refs., 7 figs., 3 tabs

Research of narrow pulse width, high repetition rate, high output power fiber lasers for deep space exploration

Science.gov (United States)

Tang, Yan-feng; Li, Hong-zuo; Wang, Yan; Hao, Zi-qiang; Xiao, Dong-Ya

2013-08-01

As human beings expand the research in unknown areas constantly, the deep space exploration has become a hot research topic all over the world. According to the long distance and large amount of information transmission characteristics of deep space exploration, the space laser communication is the preferred mode because it has the advantages of concentrated energy, good security, and large information capacity and interference immunity. In a variety of laser source, fibre-optical pulse laser has become an important communication source in deep space laser communication system because of its small size, light weight and large power. For fiber lasers, to solve the contradiction between the high repetition rate and the peak value power is an important scientific problem. General Q technology is difficult to obtain a shorter pulse widths, This paper presents a DFB semiconductor laser integrated with Electro-absorption modulator to realize the narrow pulse width, high repetition rate of the seed source, and then using a two-cascaded high gain fiber amplifier as amplification mean, to realize the fibre-optical pulse laser with pulse width 3ns, pulse frequency 200kHz and peak power 1kW. According to the space laser atmospheric transmission window, the wavelength selects for 1.06um. It is adopted that full fibre technology to make seed source and amplification, pumping source and amplification of free-space coupled into fiber-coupled way. It can overcome that fibre lasers are vulnerable to changes in external conditions such as vibration, temperature drift and other factors affect, improving long-term stability. The fiber lasers can be modulated by PPM mode, to realize high rate modulation, because of its peak power, high transmission rate, narrow pulse width, high frequency stability, all technical indexes meet the requirements of the exploration of deep space communication technology.

Deep Learning and its Applications in the Natural Sciences

CERN Multimedia

CERN. Geneva

2015-01-01

Starting from a brief historical perspective on scientific discovery, this talk will review some of the theory and open problems of deep learning and describe how to design efficient feedforward and recursive deep learning architectures for applications in the natural sciences. In particular, the focus will be on multiple particle problems at different scales: in biology (e.g. prediction of protein structures), chemistry (e.g. prediction of molecular properties and reactions), and high-energy physics (e.g. detection of exotic particles, jet substructure and tagging, "dark matter and dark knowledge")

Performance Analysis of High-Speed Deep/Shallow Recessed Hybrid Bearing

Directory of Open Access Journals (Sweden)

Lei Wang

2013-01-01

Full Text Available The present paper proposes a theoretical analysis of the performance of deep/shallow recessed hybrid bearing. It is intended that, on the basis of the numerical results drawn from this study, appropriate shallow recess depth and width can be determined for use in the bearing design process. By adopting bulk flow theory, the turbulent Reynolds equation and energy equation are modified and solved numerically including concentrated inertia effects at the recess edge with different depth and width of shallow recess. The results indicate that the load capacity, drag torque increases as the depth of shallow recess is shallower and the width ratio (half angle of deep recess versus half angle of shallow recess is smaller. In contrast, the flow rate decreases as the depth of shallow recess is shallower and the width ratio is smaller. Nevertheless, the appropriate design of the depth and width of shallow recess might well induce the performance of high-speed deep/shallow recessed hybrid bearing.

Key technologies for well drilling and completion in ultra-deep sour gas reservoirs, Yuanba Gasfield, Sichuan Basin

Directory of Open Access Journals (Sweden)

Jiaxiang Xia

2016-12-01

Full Text Available The Yuanba Gasfield is a large gas field discovered by Sinopec in the Sichuan Basin in recent years, and another main exploration area for natural gas reserves and production increase after the Puguang Gasfield. The ultra-deep sour gas reservoir in the Yuanba Gasfield is characterized by complicated geologic structure, deep reservoirs and complex drilled formation, especially in the continental deep strata which are highly abrasive with low ROP (rate of penetration and long drilling period. After many years of drilling practice and technical research, the following six key drilling and completion technologies for this type reservoir are established by introducing new tools and technologies, developing specialized drill bits and optimizing drilling design. They are: casing program optimization technology for ROP increasing and safe well completion; gas drilling technology for shallow continental strata and high-efficiency drilling technology for deep high-abrasion continental strata; drilling fluid support technologies of gas–liquid conversion, ultra-deep highly-deviated wells and horizontal-well lubrication and drag reduction, hole stability control and sour gas contamination prevention; well cementing technologies for gas medium, deep-well long cementing intervals and ultra-high pressure small space; horizontal-well trajectory control technologies for measuring instrument, downhole motor optimization and bottom hole assembly design; and liner completion modes and completion string optimization technologies suitable for this gas reservoir. Field application shows that these key technologies are contributive to ROP increase and efficiency improvement of 7000 m deep horizontal wells and to significant operational cycle shortening.

Impurity effects in silicon for high efficiency solar cells

Science.gov (United States)

Hopkins, R. H.; Rohatgi, A.

1986-01-01

Model analyses indicate that sophisticated solar cell designs including, e.g., back surface fields, optical reflectors, surface passivation, and double layer antireflective coatings can produce devices with conversion efficiencies above 20 percent (AM1). To realize this potential, the quality of the silicon from which the cells are made must be improved; and these excellent electrical properties must be maintained during device processing. As the cell efficiency rises, the sensitivity to trace contaminants also increases. For example, the threshold Ti impurity concentration at which cell performance degrades is more than an order of magnitude lower for an 18-percent cell. Similar behavior occurs for numerous other metal species which introduce deep level traps that stimulate the recombination of photogenerated carriers in silicon. Purification via crystal growth in conjunction with gettering steps to preserve the large diffusion length of the as-grown material can lead to the production of devices with efficiencies aboved 18 percent, as has been verified experimentally.

Should the U.S. proceed to consider licensing deep geological disposal of high-level nuclear waste

International Nuclear Information System (INIS)

Curtiss, J.R.

1993-01-01

The United States, as well as other countries facing the question of how to handle high-level nuclear waste, has decided that the most appropriate means of disposal is in a deep geologic repository. In recent years, the Radioactive Waste Management Committee of the Nuclear Energy Agency has developed several position papers on the technical achievability of deep geologic disposal, thus demonstrating the serious consideration of deep geologic disposal in the international community. The Committee has not, as yet, formally endorsed disposal in a deep geologic repository as the preferred method of handling high-level nuclear waste. The United States, on the other hand, has studied the various methods of disposing of high-level nuclear waste, and has determined that deep geologic disposal is the method that should be developed. The purpose of this paper is to present a review of the United States' decision on selecting deep geologic disposal as the preferred method of addressing the high-level waste problem. It presents a short history of the steps taken by the U.S. in determining what method to use, discusses the NRC's waste Confidence Decision, and provides information on other issues in the U.S. program such as reconsideration of the final disposal standard and the growing inventory of spent fuel in storage

Nature vs. Nurture: The Role of Environmental Resources in Evolutionary Deep Intelligence

OpenAIRE

Chung, Audrey G.; Fieguth, Paul; Wong, Alexander

2018-01-01

Evolutionary deep intelligence synthesizes highly efficient deep neural networks architectures over successive generations. Inspired by the nature versus nurture debate, we propose a study to examine the role of external factors on the network synthesis process by varying the availability of simulated environmental resources. Experimental results were obtained for networks synthesized via asexual evolutionary synthesis (1-parent) and sexual evolutionary synthesis (2-parent, 3-parent, and 5-pa...

Deep imitation learning for 3D navigation tasks.

Science.gov (United States)

Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina

2018-01-01

Deep learning techniques have shown success in learning from raw high-dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, utilizing deep learning in imitation learning has been scarcely explored. Imitation learning can be an efficient method to teach intelligent agents by providing a set of demonstrations to learn from. However, generalizing to situations that are not represented in the demonstrations can be challenging, especially in 3D environments. In this paper, we propose a deep imitation learning method to learn navigation tasks from demonstrations in a 3D environment. The supervised policy is refined using active learning in order to generalize to unseen situations. This approach is compared to two popular deep reinforcement learning techniques: deep-Q-networks and Asynchronous actor-critic (A3C). The proposed method as well as the reinforcement learning methods employ deep convolutional neural networks and learn directly from raw visual input. Methods for combining learning from demonstrations and experience are also investigated. This combination aims to join the generalization ability of learning by experience with the efficiency of learning by imitation. The proposed methods are evaluated on 4 navigation tasks in a 3D simulated environment. Navigation tasks are a typical problem that is relevant to many real applications. They pose the challenge of requiring demonstrations of long trajectories to reach the target and only providing delayed rewards (usually terminal) to the agent. The experiments show that the proposed method can successfully learn navigation tasks from raw visual input while learning from experience methods fail to learn an effective policy. Moreover, it is shown that active learning can significantly improve the performance of the initially learned policy using a small number of active samples.

Analyses of the deep borehole drilling status for a deep borehole disposal system

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Youl; Choi, Heui Joo; Lee, Min Soo; Kim, Geon Young; Kim, Kyung Su [KAERI, Daejeon (Korea, Republic of)

2016-05-15

The purpose of disposal for radioactive wastes is not only to isolate them from humans, but also to inhibit leakage of any radioactive materials into the accessible environment. Because of the extremely high level and long-time scale radioactivity of HLW(High-level radioactive waste), a mined deep geological disposal concept, the disposal depth is about 500 m below ground, is considered as the safest method to isolate the spent fuels or high-level radioactive waste from the human environment with the best available technology at present time. Therefore, as an alternative disposal concept, i.e., deep borehole disposal technology is under consideration in number of countries in terms of its outstanding safety and cost effectiveness. In this paper, the general status of deep drilling technologies was reviewed for deep borehole disposal of high level radioactive wastes. Based on the results of these review, very preliminary applicability of deep drilling technology for deep borehole disposal analyzed. In this paper, as one of key technologies of deep borehole disposal system, the general status of deep drilling technologies in oil industry, geothermal industry and geo scientific field was reviewed for deep borehole disposal of high level radioactive wastes. Based on the results of these review, the very preliminary applicability of deep drilling technology for deep borehole disposal such as relation between depth and diameter, drilling time and feasibility classification was analyzed.

Initial observations of cell-mediated drug delivery to the deep lung.

Science.gov (United States)

Kumar, Arun; Glaum, Mark; El-Badri, Nagwa; Mohapatra, Shyam; Haller, Edward; Park, Seungjoo; Patrick, Leslie; Nattkemper, Leigh; Vo, Dawn; Cameron, Don F

2011-01-01

Using current methodologies, drug delivery to small airways, terminal bronchioles, and alveoli (deep lung) is inefficient, especially to the lower lungs. Urgent lung pathologies such as acute respiratory distress syndrome (ARDS) and post-lung transplantation complications are difficult to treat, in part due to the methodological limitations in targeting the deep lung with high efficiency drug distribution to the site of pathology. To overcome drug delivery limitations inhibiting the optimization of deep lung therapy, isolated rat Sertoli cells preloaded with chitosan nanoparticles were use to obtain a high-density distribution and concentration (92%) of the nanoparticles in the lungs of mice by way of the peripheral venous vasculature rather than the more commonly used pulmonary route. Additionally, Sertoli cells were preloaded with chitosan nanoparticles coupled with the anti-inflammatory compound curcumin and then injected intravenously into control or experimental mice with deep lung inflammation. By 24 h postinjection, most of the curcumin load (∼90%) delivered in the injected Sertoli cells was present and distributed throughout the lungs, including the perialveloar sac area in the lower lungs. This was based on the high-density, positive quantification of both nanoparticles and curcumin in the lungs. There was a marked positive therapeutic effect achieved 24 h following curcumin treatment delivered by this Sertoli cell nanoparticle protocol (SNAP). Results identify a novel and efficient protocol for targeted delivery of drugs to the deep lung mediated by extratesticular Sertoli cells. Utilization of SNAP delivery may optimize drug therapy for conditions such as ARDS, status asthmaticus, pulmonary hypertension, lung cancer, and complications following lung transplantation where the use of high concentrations of anti-inflammatory drugs is desirable, but often limited by risks of systemic drug toxicity.

High-efficiency airfoil rudders applied to submarines

Directory of Open Access Journals (Sweden)

ZHOU Yimei

2017-03-01

Full Text Available Modern submarine design puts forward higher and higher requirements for control surfaces, and this creates a requirement for designers to constantly innovate new types of rudder so as to improve the efficiency of control surfaces. Adopting the high-efficiency airfoil rudder is one of the most effective measures for improving the efficiency of control surfaces. In this paper, we put forward an optimization method for a high-efficiency airfoil rudder on the basis of a comparative analysis of the various strengths and weaknesses of the airfoil, and the numerical calculation method is adopted to analyze the influence rule of the hydrodynamic characteristics and wake field by using the high-efficiency airfoil rudder and the conventional NACA rudder comparatively; at the same time, a model load test in a towing tank was carried out, and the test results and simulation calculation obtained good consistency:the error between them was less than 10%. The experimental results show that the steerage of a high-efficiency airfoil rudder is increased by more than 40% when compared with the conventional rudder, but the total resistance is close:the error is no more than 4%. Adopting a high-efficiency airfoil rudder brings much greater lifting efficiency than the total resistance of the boat. The results show that high-efficiency airfoil rudder has obvious advantages for improving the efficiency of control, giving it good application prospects.

Approximate Inference and Deep Generative Models

CERN Multimedia

CERN. Geneva

2018-01-01

Advances in deep generative models are at the forefront of deep learning research because of the promise they offer for allowing data-efficient learning, and for model-based reinforcement learning. In this talk I'll review a few standard methods for approximate inference and introduce modern approximations which allow for efficient large-scale training of a wide variety of generative models. Finally, I'll demonstrate several important application of these models to density estimation, missing data imputation, data compression and planning.

[Characteristics of phosphorus uptake and use efficiency of rice with high yield and high phosphorus use efficiency].

Science.gov (United States)

Li, Li; Zhang, Xi-Zhou; Li, Tinx-Xuan; Yu, Hai-Ying; Ji, Lin; Chen, Guang-Deng

2014-07-01

A total of twenty seven middle maturing rice varieties as parent materials were divided into four types based on P use efficiency for grain yield in 2011 by field experiment with normal phosphorus (P) application. The rice variety with high yield and high P efficiency was identified by pot experiment with normal and low P applications, and the contribution rates of various P efficiencies to yield were investigated in 2012. There were significant genotype differences in yield and P efficiency of the test materials. GRLu17/AiTTP//Lu17_2 (QR20) was identified as a variety with high yield and high P efficiency, and its yields at the low and normal rates of P application were 1.96 and 1.92 times of that of Yuxiang B, respectively. The contribution rate of P accumulation to yield was greater than that of P grain production efficiency and P harvest index across field and pot experiments. The contribution rates of P accumulation and P grain production efficiency to yield were not significantly different under the normal P condition, whereas obvious differences were observed under the low P condition (66.5% and 26.6%). The minimal contribution to yield was P harvest index (11.8%). Under the normal P condition, the contribution rates of P accumulation to yield and P harvest index were the highest at the jointing-heading stage, which were 93.4% and 85.7%, respectively. In addition, the contribution rate of P accumulation to grain production efficiency was 41.8%. Under the low P condition, the maximal contribution rates of P accumulation to yield and grain production efficiency were observed at the tillering-jointing stage, which were 56.9% and 20.1% respectively. Furthermore, the contribution rate of P accumulation to P harvest index was 16.0%. The yield, P accumulation, and P harvest index of QR20 significantly increased under the normal P condition by 20.6%, 18.1% and 18.2% respectively compared with that in the low P condition. The rank of the contribution rates of P

High-Temperature High-Efficiency Solar Thermoelectric Generators

Energy Technology Data Exchange (ETDEWEB)

Baranowski, LL; Warren, EL; Toberer, ES

2014-03-01

Inspired by recent high-efficiency thermoelectric modules, we consider thermoelectrics for terrestrial applications in concentrated solar thermoelectric generators (STEGs). The STEG is modeled as two subsystems: a TEG, and a solar absorber that efficiently captures the concentrated sunlight and limits radiative losses from the system. The TEG subsystem is modeled using thermoelectric compatibility theory; this model does not constrain the material properties to be constant with temperature. Considering a three-stage TEG based on current record modules, this model suggests that 18% efficiency could be experimentally expected with a temperature gradient of 1000A degrees C to 100A degrees C. Achieving 15% overall STEG efficiency thus requires an absorber efficiency above 85%, and we consider two methods to achieve this: solar-selective absorbers and thermally insulating cavities. When the TEG and absorber subsystem models are combined, we expect that the STEG modeled here could achieve 15% efficiency with optical concentration between 250 and 300 suns.

A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.

Science.gov (United States)

Zhu, Yanan; Ouyang, Qi; Mao, Youdong

2017-07-21

Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecular complexes. However, high-resolution cryo-EM reconstruction often requires hundreds of thousands of single-particle images. Particle extraction from experimental micrographs thus can be laborious and presents a major practical bottleneck in cryo-EM structural determination. Existing computational methods for particle picking often use low-resolution templates for particle matching, making them susceptible to reference-dependent bias. It is critical to develop a highly efficient template-free method for the automatic recognition of particle images from cryo-EM micrographs. We developed a deep learning-based algorithmic framework, DeepEM, for single-particle recognition from noisy cryo-EM micrographs, enabling automated particle picking, selection and verification in an integrated fashion. The kernel of DeepEM is built upon a convolutional neural network (CNN) composed of eight layers, which can be recursively trained to be highly "knowledgeable". Our approach exhibits an improved performance and accuracy when tested on the standard KLH dataset. Application of DeepEM to several challenging experimental cryo-EM datasets demonstrated its ability to avoid the selection of un-wanted particles and non-particles even when true particles contain fewer features. The DeepEM methodology, derived from a deep CNN, allows automated particle extraction from raw cryo-EM micrographs in the absence of a template. It demonstrates an improved performance, objectivity and accuracy. Application of this novel method is expected to free the labor involved in single-particle verification, significantly improving the efficiency of cryo-EM data processing.

Highly Manufacturable Deep (Sub-Millimeter) Etching Enabled High Aspect Ratio Complex Geometry Lego-Like Silicon Electronics.

Science.gov (United States)

Ghoneim, Mohamed Tarek; Hussain, Muhammad Mustafa

2017-04-01

A highly manufacturable deep reactive ion etching based process involving a hybrid soft/hard mask process technology shows high aspect ratio complex geometry Lego-like silicon electronics formation enabling free-form (physically flexible, stretchable, and reconfigurable) electronic systems. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

DEEP SPACE: High Resolution VR Platform for Multi-user Interactive Narratives

Science.gov (United States)

Kuka, Daniela; Elias, Oliver; Martins, Ronald; Lindinger, Christopher; Pramböck, Andreas; Jalsovec, Andreas; Maresch, Pascal; Hörtner, Horst; Brandl, Peter

DEEP SPACE is a large-scale platform for interactive, stereoscopic and high resolution content. The spatial and the system design of DEEP SPACE are facing constraints of CAVETM-like systems in respect to multi-user interactive storytelling. To be used as research platform and as public exhibition space for many people, DEEP SPACE is capable to process interactive, stereoscopic applications on two projection walls with a size of 16 by 9 meters and a resolution of four times 1080p (4K) each. The processed applications are ranging from Virtual Reality (VR)-environments to 3D-movies to computationally intensive 2D-productions. In this paper, we are describing DEEP SPACE as an experimental VR platform for multi-user interactive storytelling. We are focusing on the system design relevant for the platform, including the integration of the Apple iPod Touch technology as VR control, and a special case study that is demonstrating the research efforts in the field of multi-user interactive storytelling. The described case study, entitled "Papyrate's Island", provides a prototypical scenario of how physical drawings may impact on digital narratives. In this special case, DEEP SPACE helps us to explore the hypothesis that drawing, a primordial human creative skill, gives us access to entirely new creative possibilities in the domain of interactive storytelling.

Series-Tuned High Efficiency RF-Power Amplifiers

DEFF Research Database (Denmark)

Vidkjær, Jens

2008-01-01

An approach to high efficiency RF-power amplifier design is presented. It addresses simultaneously efficiency optimization and peak voltage limitations when transistors are pushed towards their power limits.......An approach to high efficiency RF-power amplifier design is presented. It addresses simultaneously efficiency optimization and peak voltage limitations when transistors are pushed towards their power limits....

Exploring fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing

Science.gov (United States)

Zhang, Xiao-Yong; Wang, Guang-Hua; Xu, Xin-Ya; Nong, Xu-Hua; Wang, Jie; Amin, Muhammad; Qi, Shu-Hua

2016-10-01

The present study investigated the fungal diversity in four different deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing of the nuclear ribosomal internal transcribed spacer-1 (ITS1). A total of 40,297 fungal ITS1 sequences clustered into 420 operational taxonomic units (OTUs) with 97% sequence similarity and 170 taxa were recovered from these sediments. Most ITS1 sequences (78%) belonged to the phylum Ascomycota, followed by Basidiomycota (17.3%), Zygomycota (1.5%) and Chytridiomycota (0.8%), and a small proportion (2.4%) belonged to unassigned fungal phyla. Compared with previous studies on fungal diversity of sediments from deep-sea environments by culture-dependent approach and clone library analysis, the present result suggested that Illumina sequencing had been dramatically accelerating the discovery of fungal community of deep-sea sediments. Furthermore, our results revealed that Sordariomycetes was the most diverse and abundant fungal class in this study, challenging the traditional view that the diversity of Sordariomycetes phylotypes was low in the deep-sea environments. In addition, more than 12 taxa accounted for 21.5% sequences were found to be rarely reported as deep-sea fungi, suggesting the deep-sea sediments from Okinawa Trough harbored a plethora of different fungal communities compared with other deep-sea environments. To our knowledge, this study is the first exploration of the fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing.

Reference design and operations for deep borehole disposal of high-level radioactive waste

International Nuclear Information System (INIS)

Herrick, Courtney Grant; Brady, Patrick Vane; Pye, Steven; Arnold, Bill Walter; Finger, John Travis; Bauer, Stephen J.

2011-01-01

A reference design and operational procedures for the disposal of high-level radioactive waste in deep boreholes have been developed and documented. The design and operations are feasible with currently available technology and meet existing safety and anticipated regulatory requirements. Objectives of the reference design include providing a baseline for more detailed technical analyses of system performance and serving as a basis for comparing design alternatives. Numerous factors suggest that deep borehole disposal of high-level radioactive waste is inherently safe. Several lines of evidence indicate that groundwater at depths of several kilometers in continental crystalline basement rocks has long residence times and low velocity. High salinity fluids have limited potential for vertical flow because of density stratification and prevent colloidal transport of radionuclides. Geochemically reducing conditions in the deep subsurface limit the solubility and enhance the retardation of key radionuclides. A non-technical advantage that the deep borehole concept may offer over a repository concept is that of facilitating incremental construction and loading at multiple perhaps regional locations. The disposal borehole would be drilled to a depth of 5,000 m using a telescoping design and would be logged and tested prior to waste emplacement. Waste canisters would be constructed of carbon steel, sealed by welds, and connected into canister strings with high-strength connections. Waste canister strings of about 200 m length would be emplaced in the lower 2,000 m of the fully cased borehole and be separated by bridge and cement plugs. Sealing of the upper part of the borehole would be done with a series of compacted bentonite seals, cement plugs, cement seals, cement plus crushed rock backfill, and bridge plugs. Elements of the reference design meet technical requirements defined in the study. Testing and operational safety assurance requirements are also defined. Overall

Reference design and operations for deep borehole disposal of high-level radioactive waste.

Energy Technology Data Exchange (ETDEWEB)

Herrick, Courtney Grant; Brady, Patrick Vane; Pye, Steven; Arnold, Bill Walter; Finger, John Travis; Bauer, Stephen J.

2011-10-01

A reference design and operational procedures for the disposal of high-level radioactive waste in deep boreholes have been developed and documented. The design and operations are feasible with currently available technology and meet existing safety and anticipated regulatory requirements. Objectives of the reference design include providing a baseline for more detailed technical analyses of system performance and serving as a basis for comparing design alternatives. Numerous factors suggest that deep borehole disposal of high-level radioactive waste is inherently safe. Several lines of evidence indicate that groundwater at depths of several kilometers in continental crystalline basement rocks has long residence times and low velocity. High salinity fluids have limited potential for vertical flow because of density stratification and prevent colloidal transport of radionuclides. Geochemically reducing conditions in the deep subsurface limit the solubility and enhance the retardation of key radionuclides. A non-technical advantage that the deep borehole concept may offer over a repository concept is that of facilitating incremental construction and loading at multiple perhaps regional locations. The disposal borehole would be drilled to a depth of 5,000 m using a telescoping design and would be logged and tested prior to waste emplacement. Waste canisters would be constructed of carbon steel, sealed by welds, and connected into canister strings with high-strength connections. Waste canister strings of about 200 m length would be emplaced in the lower 2,000 m of the fully cased borehole and be separated by bridge and cement plugs. Sealing of the upper part of the borehole would be done with a series of compacted bentonite seals, cement plugs, cement seals, cement plus crushed rock backfill, and bridge plugs. Elements of the reference design meet technical requirements defined in the study. Testing and operational safety assurance requirements are also defined. Overall

High-throughput verification of transcriptional starting sites by Deep-RACE

DEFF Research Database (Denmark)

Olivarius, Signe; Plessy, Charles; Carninci, Piero

2009-01-01

We present a high-throughput method for investigating the transcriptional starting sites of genes of interest, which we named Deep-RACE (Deep–rapid amplification of cDNA ends). Taking advantage of the latest sequencing technology, it allows the parallel analysis of multiple genes and is free...

Deep Reactive Ion Etching for High Aspect Ratio Microelectromechanical Components

DEFF Research Database (Denmark)

Jensen, Søren; Yalcinkaya, Arda Deniz; Jacobsen, S.

2004-01-01

A deep reactive ion etch (DRIE) process for fabrication of high aspect ratio trenches has been developed. Trenches with aspect ratios exceeding 20 and vertical sidewalls with low roughness have been demonstrated. The process has successfully been used in the fabrication of silicon-on-insulator (SOI...

Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

International Nuclear Information System (INIS)

Carter, L.L.; Hendricks, J.S.

1983-01-01

The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays

High efficiency, long life terrestrial solar panel

Science.gov (United States)

Chao, T.; Khemthong, S.; Ling, R.; Olah, S.

1977-01-01

The design of a high efficiency, long life terrestrial module was completed. It utilized 256 rectangular, high efficiency solar cells to achieve high packing density and electrical output. Tooling for the fabrication of solar cells was in house and evaluation of the cell performance was begun. Based on the power output analysis, the goal of a 13% efficiency module was achievable.

Design and in vivo evaluation of more efficient and selective deep brain stimulation electrodes

Science.gov (United States)

Howell, Bryan; Huynh, Brian; Grill, Warren M.

2015-08-01

Objective. Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, the efficiency and selectivity of DBS can be improved. Our objective was to design electrode geometries that increased the efficiency and selectivity of DBS. Approach. We coupled computational models of electrodes in brain tissue with cable models of axons of passage (AOPs), terminating axons (TAs), and local neurons (LNs); we used engineering optimization to design electrodes for stimulating these neural elements; and the model predictions were tested in vivo. Main results. Compared with the standard electrode used in the Medtronic Model 3387 and 3389 arrays, model-optimized electrodes consumed 45-84% less power. Similar gains in selectivity were evident with the optimized electrodes: 50% of parallel AOPs could be activated while reducing activation of perpendicular AOPs from 44 to 48% with the standard electrode to 0-14% with bipolar designs; 50% of perpendicular AOPs could be activated while reducing activation of parallel AOPs from 53 to 55% with the standard electrode to 1-5% with an array of cathodes; and, 50% of TAs could be activated while reducing activation of AOPs from 43 to 100% with the standard electrode to 2-15% with a distal anode. In vivo, both the geometry and polarity of the electrode had a profound impact on the efficiency and selectivity of stimulation. Significance. Model-based design is a powerful tool that can be used to improve the efficiency and selectivity of DBS electrodes.

Detector for deep well logging

International Nuclear Information System (INIS)

1976-01-01

A substantial improvement in the useful life and efficiency of a deep-well scintillation detector is achieved by a unique construction wherein the steel cylinder enclosing the sodium iodide scintillation crystal is provided with a tapered recess to receive a glass window which has a high transmittance at the critical wavelength and, for glass, a high coefficient of thermal expansion. A special high-temperature epoxy adhesive composition is employed to form a relatively thick sealing annulus which keeps the glass window in the tapered recess and compensates for the differences in coefficients of expansion between the container and glass so as to maintain a hermetic seal as the unit is subjected to a wide range of temperature

High-Performance solar-blind flexible Deep-UV photodetectors based on quantum dots synthesized by femtosecond-laser ablation

KAUST Repository

Mitra, Somak

2018-03-31

High-performance deep ultraviolet (DUV) photodetectors operating at ambient conditions with < 280nm detection wavelengths are in high demand because of their potential applications in diverse fields. We demonstrate for the first time, high-performance flexible DUV photodetectors operating at ambient conditions based on quantum dots (QDs) synthesized by femtosecond-laser ablation in liquid (FLAL) technique. Our method is facile without complex chemical procedures, which allows large-scale cost-effective devices. This synthesis method is demonstrated to produce highly stable and reproducible ZnO QDs from zinc nitride target (Zn3N2) without any material degradation due to water and oxygen molecule species, allowing photodetectors operate at ambient conditions. Carbon-doped ZnO QD-based photodetector is capable of detecting efficiently in the DUV spectral region, down to 224nm, and exhibits high photo responsivity and stability. As fast response of DUV photodetector remains significant parameter for high-speed communication; we show fast-response QD-based DUV photodetector. Such surfactant-free synthesis by FLAL can lead to commercially available high-performance low-cost optoelectronic devices based on nanostructures for large scale applications.

High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks.

Science.gov (United States)

Rajkomar, Alvin; Lingam, Sneha; Taylor, Andrew G; Blum, Michael; Mongan, John

2017-02-01

The study aimed to determine if computer vision techniques rooted in deep learning can use a small set of radiographs to perform clinically relevant image classification with high fidelity. One thousand eight hundred eighty-five chest radiographs on 909 patients obtained between January 2013 and July 2015 at our institution were retrieved and anonymized. The source images were manually annotated as frontal or lateral and randomly divided into training, validation, and test sets. Training and validation sets were augmented to over 150,000 images using standard image manipulations. We then pre-trained a series of deep convolutional networks based on the open-source GoogLeNet with various transformations of the open-source ImageNet (non-radiology) images. These trained networks were then fine-tuned using the original and augmented radiology images. The model with highest validation accuracy was applied to our institutional test set and a publicly available set. Accuracy was assessed by using the Youden Index to set a binary cutoff for frontal or lateral classification. This retrospective study was IRB approved prior to initiation. A network pre-trained on 1.2 million greyscale ImageNet images and fine-tuned on augmented radiographs was chosen. The binary classification method correctly classified 100 % (95 % CI 99.73-100 %) of both our test set and the publicly available images. Classification was rapid, at 38 images per second. A deep convolutional neural network created using non-radiological images, and an augmented set of radiographs is effective in highly accurate classification of chest radiograph view type and is a feasible, rapid method for high-throughput annotation.

Social stakes of the reversibility in the deep storage of high level radioactive wastes

International Nuclear Information System (INIS)

Heriard-Dubreuil, G.; Schieber, C.; Schneider, T.

1998-06-01

This document proposes a study of the conditions which surrounded the reversibility introduction in high activity wastes deep storage at an international scale, as well as a reflexion on the social stakes associated there. In France, the law of december 30, 1991 concerning the research on the radioactive wastes prescribes '' the study of possibilities retrieval or non retrieval storage in deep geological deposits''. The analysis of the reversibility associated social stakes emphasizes the necessity to prevent irreversible consequences, to take care to the choices reversibility, to preserve the future generations autonomy. Thus to elaborate a more satisfactory solution between deep disposal and surface storage, a deep storage, capable of gradually evolution, concept is defined. (A.L.B.)

Neuromorphic Deep Learning Machines

OpenAIRE

Neftci, E; Augustine, C; Paul, S; Detorakis, G

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Back Propagation (BP) rule, often relies on the immediate availability of network-wide...

High-Power, Solid-State, Deep Ultraviolet Laser Generation

Directory of Open Access Journals (Sweden)

Hongwen Xuan

2018-02-01

Full Text Available At present, deep ultraviolet (DUV lasers at the wavelength of fourth harmonics of 1 μm (266 nm/258 nm and at the wavelength of 193 nm are widely utilized in science and industry. We review the generation of these DUV lasers by nonlinear frequency conversion processes using solid-state/fiber lasers as the fundamental frequency. A DUV laser at 258 nm by fourth harmonics generation (FHG could achieve an average power of 10 W with a beam quality of M2 < 1.5. Moreover, 1 W of average power at 193 nm was obtained by sum-frequency generation (SFG. A new concept of 193-nm DUV laser generation by use of the diamond Raman laser is also introduced. A proof-of-principle experiment of the diamond Raman laser is reported with the conversion efficiency of 23% from the pump to the second Stokes wavelength, which implies the potential to generate a higher power 193 nm DUV laser in the future.

Inclusive quasielastic and deep inelastic electron scattering at high energies

International Nuclear Information System (INIS)

Day, D.B.

1990-01-01

With high electron energies a kinematic regime can be reached where it will be possible to separate quasielastic and deep inelastic scattering. We present a short description of these processes which dominate the inclusive spectrum. Using the highest momentum transfer data available to guide our estimates, we give the kinematic requirements and the cross sections expected. These results indicate that inclusive scattering at high q has a yet unfilled potential. 18 refs., 13 figs

New highly efficient piezoceramic materials

International Nuclear Information System (INIS)

Dantsiger, A.Ya.; Razumovskaya, O.N.; Reznichenko, L.A.; Grineva, L.D.; Devlikanova, R.U.; Dudkina, S.I.; Gavrilyachenko, S.V.; Dergunova, N.V.

1993-01-01

New high efficient piezoceramic materials with various combination of parameters inclusing high Curie point for high-temperature transducers using in atomic power engineering are worked. They can be used in systems for heated matters nondestructive testing, controllers for varied industrial power plants and other high-temperature equipment

Efficient absorption of SO_2 with low-partial pressures by environmentally benign functional deep eutectic solvents

International Nuclear Information System (INIS)

Zhang, Kai; Ren, Shuhang; Hou, Yucui; Wu, Weize

2017-01-01

Graphical abstract: Environmentally benign deep eutectic solvents (DESs) based on betaine or L-carnitine with ethylene glycol were designed with a function and used to efficiently capture SO_2 with low partial pressures. - Highlights: • Deep eutectic solvents (DESs) were designed with a function to absorb low-conc. SO_2. • Betaine(Bet) and L-carnitine(L-car) with a functional group were used as H-bond acceptor. • Bet + ethylene glycol (EG) DES and L-car + EG DES are environmentally benign. • L-car + EG DES can absorb 0.644 mol SO_2 per mole L-car (0.37% SO_2). • L-car + EG DES is a promising absorbent for SO_2 capture. - Abstract: Sulfur dioxide (SO_2) emitted from the burning of fossil fuels is one of the main air contaminants. In this work, we found that environmentally benign solvents, deep eutectic solvents (DESs) could be designed with a function to absorb low-partial pressure SO_2 from simulated flue gas. Two kinds of biodegradable functional DESs based on betaine (Bet) and L-carnitine (L-car) as hydrogen bond accepters (HBA) and ethylene glycol (EG) as a hydrogen bond donor (HBD) were prepared with mole ratios of HBA to HBD from 1:3 to 1:5, and they were investigated to absorb SO_2 with different partial pressures at various temperatures. The results showed that the two DESs could absorb low-partial pressure SO_2 efficiently. SO_2 absorption capacities of the DESs with HBA/HBD mole ratio of 1:3 were 0.332 mol SO_2/mol HBA for Bet + EG DES and 0.820 mol SO_2/mol HBA for L-car + EG DES at 40 °C with a SO_2 partial pressure of 0.02 atm. In addition, the regeneration experiments demonstrated that the absorption capacities of DESs did not change after five absorption and desorption cycles. Furthermore, the absorption mechanism of SO_2 by DESs was studied by FT-IR, "1H NMR and "1"3C NMR spectra. It was found that there are strong acid–base interactions between SO_2 and −COO"− on HBA.

Southern Ocean Circulation: a High Resolution Examination of the Last Deglaciation from Deep-Sea Corals

Science.gov (United States)

Robinson, L. F.; Li, T.; Chen, T.; Burke, A.; Pegrum Haram, A.; Stewart, J.; Rae, J. W. B.; van de Flierdt, T.; Struve, T.; Wilson, D. J.

2017-12-01

Two decades ago it was first noted that the skeletal remains of deep-sea corals had the potential to provide absolutely dated archives of past ocean conditions. In the intervening twenty years this field has developed to the point where strategic collections and high throughput dating techniques now allow high resolution, well dated records of past deep sea behaviour to be produced. Likewise, efforts to improve understanding of biomineralisation and growth rates are leading to refinements in proxy tools useful for examining circulation, nutrient and carbon cycling, temperature and weathering processes. Deep-sea corals are particularly valuable archives in high latitude regions where radiocarbon-based age models are susceptible to large changes in surface reservoir ages. In this presentation we show new high resolution multiproxy records of the Southern Ocean (Drake Passage) made on U-Th dated corals spanning the last glacial cycle. With more than seventeen hundred reconnaissance ages, and around 200 precise isotope dilution U-Th ages, subtle changes in ocean behaviour can be identified during times of abrupt climate change. The geochemical signature of corals from the deepest sites, closest to modern day Lower Circumpolar Deep Waters, typically show a gradual shift from glacial to Holocene values during deglaciation, likely related to ventilation of the deep ocean. By contrast for the samples collected shallower in the water column (within sites currently bathed by Upper Circumpolar Deep Waters and Antarctic Intermediate and Mode Waters) the evidence points to a more complicated picture. Vertical zonation in the geochemical data suggests that periods of stratification are interspersed with mixing events within the upper 1500m of the water column. At the same time comparison to U-Th dated records from the low latitude Pacific and Atlantic points to an important role for the Southern Ocean in feeding the intermediate waters of both ocean basins throughout the

Deep geologic storage of high level radioactive wastes: conceptual generic designs

International Nuclear Information System (INIS)

1995-01-01

This report summarizes the studies on deep geologic storage of radioactive wastes and specially for the high-level radioactive wastes. The study is focussed to the geotechnical assessment and generic-conceptual designs. Methodology analysis, geotechnical feasibility, costs and operation are studied

Seasonal copepod lipid pump promotes carbon sequestration in the deep North Atlantic.

Science.gov (United States)

Jónasdóttir, Sigrún Huld; Visser, André W; Richardson, Katherine; Heath, Michael R

2015-09-29

Estimates of carbon flux to the deep oceans are essential for our understanding of global carbon budgets. Sinking of detrital material ("biological pump") is usually thought to be the main biological component of this flux. Here, we identify an additional biological mechanism, the seasonal "lipid pump," which is highly efficient at sequestering carbon into the deep ocean. It involves the vertical transport and metabolism of carbon rich lipids by overwintering zooplankton. We show that one species, the copepod Calanus finmarchicus overwintering in the North Atlantic, sequesters an amount of carbon equivalent to the sinking flux of detrital material. The efficiency of the lipid pump derives from a near-complete decoupling between nutrient and carbon cycling—a "lipid shunt," and its direct transport of carbon through the mesopelagic zone to below the permanent thermocline with very little attenuation. Inclusion of the lipid pump almost doubles the previous estimates of deep-ocean carbon sequestration by biological processes in the North Atlantic.

DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

Directory of Open Access Journals (Sweden)

Qiao Wei

2017-01-01

Full Text Available Deep neural networks (DNNs have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling data-parallel computation jobs like DNN over containerized clusters is critical for job performance, system throughput, and resource utilization. It becomes even more challenging with the complex workloads. We propose a scheduling method called Deep Learning Task Allocation Priority (DLTAP which performs scheduling decisions in a distributed manner, and each of scheduling decisions takes aggregation degree of parameter sever task and worker task into account, in particularly, to reduce cross-node network transmission traffic and, correspondingly, decrease the DNN training time. We evaluate the DLTAP scheduling method using a state-of-the-art distributed DNN training framework on 3 benchmarks. The results show that the proposed method can averagely reduce 12% cross-node network traffic, and decrease the DNN training time even with the cluster of low-end servers.

High-efficiency cavity-dumped micro-chip Yb:YAG laser

Science.gov (United States)

Nishio, M.; Maruko, A.; Inoue, M.; Takama, M.; Matsubara, S.; Okunishi, H.; Kato, K.; Kyomoto, K.; Yoshida, T.; Shimabayashi, K.; Morioka, M.; Inayoshi, S.; Yamagata, S.; Kawato, S.

2014-09-01

High-efficiency cavity-dumped ytterbium-doped yttrium aluminum garnet (Yb:YAG) laser was developed. Although the high quantum efficiency of ytterbium-doped laser materials is appropriate for high-efficiency laser oscillation, the efficiency is decreased by their quasi-three/four laser natures. High gain operation by high intensity pumping is suitable for high efficiency oscillation on the quasi-three/four lasers without extremely low temperature cooling. In our group, highest efficiency oscillations for continuous wave, nanosecond to picosecond pulse lasers were achieved at room temperature by the high gain operation in which pump intensities were beyond 100 kW/cm2.

High-level radioactive waste disposal in the deep ocean

International Nuclear Information System (INIS)

Hill, H.W.

1977-01-01

A joint programme has begun between the Fisheries Laboratory, Lowestoft and the Institute of Oceanographic Sciences, Wormley to study the dispersion of radioactivity in the deep ocean arising from the possible dumping of high level waste on the sea bed in vitrified-glass form which would permit slow leakage over a long term scale. The programme consists firstly of the development of a simple diffusion/advection model for the dispersion of radioactivity in a closed and finite ocean, which overcomes many of the criticisms of the earlier model proposed by Webb and Morley. Preliminary results from this new model are comparable to those of the Webb-Morley model for radio isotopes with half-lives of 10-300 years but are considerably more restrictive outside this range, particularly for those which are much longer-lived. The second part of the programme, towards which the emphasis is directed, concerns the field programme planned to measure the advection and diffusion parameters in the deeper layers of the ocean to provide realistic input parameters to the model and increase our fundamental understanding of the environment in which the radioactive materials may be released. The first cruises of the programme will take place in late 1976 and involve deep current meter deployments and float dispersion experiments around the present NEA dump site with some sediment sampling, so that adsorption experiments can be started on typical deep sea sediments. The programme will expand the number of long-term deep moored stations over the next five years and include further float experiments, CTD profiling, and other physical oceanography. In the second half of the 5-year programme, attempts will be made to measure diffusion parameters in the deeper layers of the ocean using radioactive tracers

LUMINOUS AND HIGH STELLAR MASS CANDIDATE GALAXIES AT z ≈ 8 DISCOVERED IN THE COSMIC ASSEMBLY NEAR-INFRARED DEEP EXTRAGALACTIC LEGACY SURVEY

International Nuclear Information System (INIS)

Yan Haojing; Finkelstein, Steven L.; Huang, Kuang-Han; Ryan, Russell E.; Ferguson, Henry C.; Koekemoer, Anton M.; Grogin, Norman A.; Dickinson, Mark; Newman, Jeffrey A.; Somerville, Rachel S.; Davé, Romeel; Faber, S. M.; Papovich, Casey; Guo Yicheng; Giavalisco, Mauro; Lee, Kyoung-soo; Reddy, Naveen; Siana, Brian D.; Cooray, Asantha R.; Hathi, Nimish P.

2012-01-01

One key goal of the Hubble Space Telescope Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey is to track galaxy evolution back to z ≈ 8. Its two-tiered ''wide and deep'' strategy bridges significant gaps in existing near-infrared surveys. Here we report on z ≈ 8 galaxy candidates selected as F105W-band dropouts in one of its deep fields, which covers 50.1 arcmin 2 to 4 ks depth in each of three near-infrared bands in the Great Observatories Origins Deep Survey southern field. Two of our candidates have J 1 mag brighter than any previously known F105W-dropouts. We derive constraints on the bright end of the rest-frame ultraviolet luminosity function of galaxies at z ≈ 8, and show that the number density of such very bright objects is higher than expected from the previous Schechter luminosity function estimates at this redshift. Another two candidates are securely detected in Spitzer Infrared Array Camera images, which are the first such individual detections at z ≈ 8. Their derived stellar masses are on the order of a few × 10 9 M ☉ , from which we obtain the first measurement of the high-mass end of the galaxy stellar mass function at z ≈ 8. The high number density of very luminous and very massive galaxies at z ≈ 8, if real, could imply a large stellar-to-halo mass ratio and an efficient conversion of baryons to stars at such an early time.

Highly efficient high temperature electrolysis

DEFF Research Database (Denmark)

Hauch, Anne; Ebbesen, Sune; Jensen, Søren Højgaard

2008-01-01

High temperature electrolysis of water and steam may provide an efficient, cost effective and environmentally friendly production of H-2 Using electricity produced from sustainable, non-fossil energy sources. To achieve cost competitive electrolysis cells that are both high performing i.e. minimum...... internal resistance of the cell, and long-term stable, it is critical to develop electrode materials that are optimal for steam electrolysis. In this article electrolysis cells for electrolysis of water or steam at temperatures above 200 degrees C for production of H-2 are reviewed. High temperature...... electrolysis is favourable from a thermodynamic point of view, because a part of the required energy can be supplied as thermal heat, and the activation barrier is lowered increasing the H-2 production rate. Only two types of cells operating at high temperature (above 200 degrees C) have been described...

Imaging-based enrichment criteria using deep learning algorithms for efficient clinical trials in mild cognitive impairment.

Science.gov (United States)

Ithapu, Vamsi K; Singh, Vikas; Okonkwo, Ozioma C; Chappell, Richard J; Dowling, N Maritza; Johnson, Sterling C

2015-12-01

The mild cognitive impairment (MCI) stage of Alzheimer's disease (AD) may be optimal for clinical trials to test potential treatments for preventing or delaying decline to dementia. However, MCI is heterogeneous in that not all cases progress to dementia within the time frame of a trial and some may not have underlying AD pathology. Identifying those MCIs who are most likely to decline during a trial and thus most likely to benefit from treatment will improve trial efficiency and power to detect treatment effects. To this end, using multimodal, imaging-derived, inclusion criteria may be especially beneficial. Here, we present a novel multimodal imaging marker that predicts future cognitive and neural decline from [F-18]fluorodeoxyglucose positron emission tomography (PET), amyloid florbetapir PET, and structural magnetic resonance imaging, based on a new deep learning algorithm (randomized denoising autoencoder marker, rDAm). Using ADNI2 MCI data, we show that using rDAm as a trial enrichment criterion reduces the required sample estimates by at least five times compared with the no-enrichment regime and leads to smaller trials with high statistical power, compared with existing methods. Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Adaptive Learning Rule for Hardware-based Deep Neural Networks Using Electronic Synapse Devices

OpenAIRE

Lim, Suhwan; Bae, Jong-Ho; Eum, Jai-Ho; Lee, Sungtae; Kim, Chul-Heung; Kwon, Dongseok; Park, Byung-Gook; Lee, Jong-Ho

2017-01-01

In this paper, we propose a learning rule based on a back-propagation (BP) algorithm that can be applied to a hardware-based deep neural network (HW-DNN) using electronic devices that exhibit discrete and limited conductance characteristics. This adaptive learning rule, which enables forward, backward propagation, as well as weight updates in hardware, is helpful during the implementation of power-efficient and high-speed deep neural networks. In simulations using a three-layer perceptron net...

Highly efficient deep ultraviolet generation by sum-frequency mixing ...

Indian Academy of Sciences (India)

Generation of deep ultraviolet radiation at 210 nm by Type-I third harmonic generation is achieved in a pair of BBO crystals with conversion efficiency as high as 36%. The fundamental source is the dye laser radiation pumped by the second harmonic of a Q-switched Nd : YAG laser. A walk-off compensated configuration ...

Deep blue exciplex organic light-emitting diodes with enhanced efficiency; P-type or E-type triplet conversion to singlet excitons?

Science.gov (United States)

Jankus, Vygintas; Chiang, Chien-Jung; Dias, Fernando; Monkman, Andrew P

2013-03-13

Simple trilayer, deep blue, fluorescent exciplex organic light-emitting diodes (OLEDs) are reported. These OLEDs emit from an exciplex state formed between the highest occupied molecular orbital (HOMO) of N,N'-bis(1-naphthyl)N,N'-diphenyl-1,1'-biphenyl-4,4'-diamine (NPB) and lowest unoccupied molecular orbital (LUMO) of 1,3,5-tri(1-phenyl-1H-benzo[d]imidazol-2-yl)phenyl (TPBi) and the NPB singlet manifold, yielding 2.7% external quantum efficiency at 450 nm. It is shown that the majority of the delayed emission in electroluminescence arises from P-type triplet fusion at NPB sites not E-type reverse intersystem crossing because of the presence of the NPB triplet state acting as a deep trap. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High levels of natural radionuclides in a deep-sea infaunal xenophyophore

Energy Technology Data Exchange (ETDEWEB)

Swinbanks, D D; Shirayama, Y

1986-03-27

The paper concerns the high levels of natural radionuclides in a deep-sea infaunal xenophyophore from the Izu-Ogasawara Trench. Measured /sup 210/Po activities and barium contents of various parts of Occultammina profunda and the surrounding sediment are given, together with their estimated /sup 210/Pb and /sup 226/Ra activities. The data suggest that xenophyphores are probably subject to unusually high levels of natural radiation.

High Efficiency Power Converter for Low Voltage High Power Applications

DEFF Research Database (Denmark)

Nymand, Morten

The topic of this thesis is the design of high efficiency power electronic dc-to-dc converters for high-power, low-input-voltage to high-output-voltage applications. These converters are increasingly required for emerging sustainable energy systems such as fuel cell, battery or photo voltaic based......, and remote power generation for light towers, camper vans, boats, beacons, and buoys etc. A review of current state-of-the-art is presented. The best performing converters achieve moderately high peak efficiencies at high input voltage and medium power level. However, system dimensioning and cost are often...

Deep Packet/Flow Analysis using GPUs

Energy Technology Data Exchange (ETDEWEB)

Gong, Qian [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Wu, Wenji [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); DeMar, Phil [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)

2017-11-12

Deep packet inspection (DPI) faces severe performance challenges in high-speed networks (40/100 GE) as it requires a large amount of raw computing power and high I/O throughputs. Recently, researchers have tentatively used GPUs to address the above issues and boost the performance of DPI. Typically, DPI applications involve highly complex operations in both per-packet and per-flow data level, often in real-time. The parallel architecture of GPUs fits exceptionally well for per-packet network traffic processing. However, for stateful network protocols such as TCP, their data stream need to be reconstructed in a per-flow level to deliver a consistent content analysis. Since the flow-centric operations are naturally antiparallel and often require large memory space for buffering out-of-sequence packets, they can be problematic for GPUs, whose memory is normally limited to several gigabytes. In this work, we present a highly efficient GPU-based deep packet/flow analysis framework. The proposed design includes a purely GPU-implemented flow tracking and TCP stream reassembly. Instead of buffering and waiting for TCP packets to become in sequence, our framework process the packets in batch and uses a deterministic finite automaton (DFA) with prefix-/suffix- tree method to detect patterns across out-of-sequence packets that happen to be located in different batches. In conclusion, evaluation shows that our code can reassemble and forward tens of millions of packets per second and conduct a stateful signature-based deep packet inspection at 55 Gbit/s using an NVIDIA K40 GPU.

Deep Boreholes Seals Subjected to High P, T conditions – Preliminary Experimental Studies

Energy Technology Data Exchange (ETDEWEB)

Caporuscio, Florie Andre [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Norskog, Katherine Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Maner, James Lavada [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-01-18

The objective of this planned experimental work is to evaluate physio-chemical processes for ‘seal’ components and materials relevant to deep borehole disposal. These evaluations will encompass multi-laboratory efforts for the development of seals concepts and application of Thermal-Mechanical-Chemical (TMC) modeling work to assess barrier material interactions with subsurface fluids, their stability at high temperatures, and the implications of these processes to the evaluation of thermal limits. Deep borehole experimental work will constrain the Pressure, Temperature (P, T) conditions which “seal” material will experience in deep borehole crystalline rock repositories. The rocks of interest to this study include the silicic (granitic gneiss) end members. The experiments will systematically add components to capture discrete changes in both water and EBS component chemistries.

Hydrophilic Conjugated Polymers with Large Bandgaps and Deep-Lying HOMO Levels as an Efficient Cathode Interlayer in Inverted Polymer Solar Cells.

Science.gov (United States)

Kan, Yuanyuan; Zhu, Yongxiang; Liu, Zhulin; Zhang, Lianjie; Chen, Junwu; Cao, Yong

2015-08-01

Two hydrophilic conjugated polymers, PmP-NOH and PmP36F-NOH, with polar diethanol-amine on the side chains and main chain structures of poly(meta-phenylene) and poly(meta-phenylene-alt-3,6-fluorene), respectively, are successfully synthesized. The films of PmP-NOH and PmP36F-NOH show absorption edges at 340 and 343 nm, respectively. The calculated optical bandgaps of the two polymers are 3.65 and 3.62 eV, respectively, the largest ones so far reported for hydrophilic conjugated polymers. PmP-NOH and PmP36F-NOH also possess deep-lying highest occupied molecular orbital levels of -6.19 and -6.15 eV, respectively. Inserting PmP-NOH and PmP36F-NOH as a cathode interlayer in inverted polymer solar cells with a PTB7/PC71 BM blend as the active layer, high power conversion efficiencies of 8.58% and 8.33%, respectively, are achieved, demonstrating that the two hydrophilic polymers are excellent interlayers for efficient inverted polymer solar cells. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High Efficiency Room Air Conditioner

Energy Technology Data Exchange (ETDEWEB)

Bansal, Pradeep [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2015-01-01

This project was undertaken as a CRADA project between UT-Battelle and Geberal Electric Company and was funded by Department of Energy to design and develop of a high efficiency room air conditioner. A number of novel elements were investigated to improve the energy efficiency of a state-of-the-art WAC with base capacity of 10,000 BTU/h. One of the major modifications was made by downgrading its capacity from 10,000 BTU/hr to 8,000 BTU/hr by replacing the original compressor with a lower capacity (8,000 BTU/hr) but high efficiency compressor having an EER of 9.7 as compared with 9.3 of the original compressor. However, all heat exchangers from the original unit were retained to provide higher EER. The other subsequent major modifications included- (i) the AC fan motor was replaced by a brushless high efficiency ECM motor along with its fan housing, (ii) the capillary tube was replaced with a needle valve to better control the refrigerant flow and refrigerant set points, and (iii) the unit was tested with a drop-in environmentally friendly binary mixture of R32 (90% molar concentration)/R125 (10% molar concentration). The WAC was tested in the environmental chambers at ORNL as per the design rating conditions of AHAM/ASHRAE (Outdoor- 95F and 40%RH, Indoor- 80F, 51.5%RH). All these modifications resulted in enhancing the EER of the WAC by up to 25%.

Long-term viability of carbon sequestration in deep-sea sediments

Science.gov (United States)

Teng, Y.; Zhang, D.

2017-12-01

Sequestration of carbon dioxide in deep-sea sediments has been proposed for the long-term storage of anthropogenic CO2, due to the negative buoyancy effect and hydrate formation under conditions of high pressure and low temperature. However, the multi-physics process of injection and post-injection fate of CO2 and the feasibility of sub-seabed disposal of CO2 under different geological and operational conditions have not been well studied. On the basis of a detailed study of the coupled processes, we investigate whether storing CO2 into deep-sea sediments is viable, efficient, and secure over the long term. Also studied are the evolution of the multiphase and multicomponent flow and the impact of hydrate formation on storage efficiency during the upward migration of the injected CO2. It is shown that low buoyancy and high viscosity slow down the ascending plume and the forming of the hydrate cap effectively reduces the permeability and finally becomes an impermeable seal, thus limiting the movement of CO2 towards the seafloor. Different flow patterns at varied time scales are identified through analyzing the mass distribution of CO2 in different phases over time. Observed is the formation of a fluid inclusion, which mainly consists of liquid CO2 and is encapsulated by an impermeable hydrate film in the diffusion-dominated stage. The trapped liquid CO2 and CO2 hydrate finally dissolve into the pore water through diffusion of the CO2 component. Sensitivity analyses are performed on storage efficiency under variable geological and operational conditions. It is found that under a deep-sea setting, CO2 sequestration in intact marine sediments is generally safe and permanent.

An Efficient Implementation of Deep Convolutional Neural Networks for MRI Segmentation.

Science.gov (United States)

Hoseini, Farnaz; Shahbahrami, Asadollah; Bayat, Peyman

2018-02-27

Image segmentation is one of the most common steps in digital image processing, classifying a digital image into different segments. The main goal of this paper is to segment brain tumors in magnetic resonance images (MRI) using deep learning. Tumors having different shapes, sizes, brightness and textures can appear anywhere in the brain. These complexities are the reasons to choose a high-capacity Deep Convolutional Neural Network (DCNN) containing more than one layer. The proposed DCNN contains two parts: architecture and learning algorithms. The architecture and the learning algorithms are used to design a network model and to optimize parameters for the network training phase, respectively. The architecture contains five convolutional layers, all using 3 × 3 kernels, and one fully connected layer. Due to the advantage of using small kernels with fold, it allows making the effect of larger kernels with smaller number of parameters and fewer computations. Using the Dice Similarity Coefficient metric, we report accuracy results on the BRATS 2016, brain tumor segmentation challenge dataset, for the complete, core, and enhancing regions as 0.90, 0.85, and 0.84 respectively. The learning algorithm includes the task-level parallelism. All the pixels of an MR image are classified using a patch-based approach for segmentation. We attain a good performance and the experimental results show that the proposed DCNN increases the segmentation accuracy compared to previous techniques.

Distinctive Microbial Community Structure in Highly Stratified Deep-Sea Brine Water Columns

KAUST Repository

Bougouffa, Salim; Yang, J. K.; Lee, O. O.; Wang, Y.; Batang, Zenon B.; Al-Suwailem, Abdulaziz M.; Qian, P. Y.

2013-01-01

Atlantis II and Discovery are two hydrothermal and hypersaline deep-sea pools in the Red Sea rift that are characterized by strong thermohalo-stratification and temperatures steadily peaking near the bottom. We conducted comprehensive vertical profiling of the microbial populations in both pools and highlighted the influential environmental factors. Pyrosequencing of the 16S rRNA genes revealed shifts in community structures vis-à-vis depth. High diversity and low abundance were features of the deepest convective layers despite the low cell density. Surprisingly, the brine interfaces had significantly higher cell counts than the overlying deep-sea water, yet they were lowest in diversity. Vertical stratification of the bacterial populations was apparent as we moved from the Alphaproteobacteria-dominated deep sea to the Planctomycetaceae- or Deferribacteres-dominated interfaces to the Gammaproteobacteria-dominated brine layers. Archaeal marine group I was dominant in the deep-sea water and interfaces, while several euryarchaeotic groups increased in the brine. Across sites, microbial phylotypes and abundances varied substantially in the brine interface of Discovery compared with Atlantis II, despite the near-identical populations in the overlying deep-sea waters. The lowest convective layers harbored interestingly similar microbial communities, even though temperature and heavy metal concentrations were very different. Multivariate analysis indicated that temperature and salinity were the major influences shaping the communities. The harsh conditions and the low-abundance phylotypes could explain the observed correlation in the brine pools.

Distinctive Microbial Community Structure in Highly Stratified Deep-Sea Brine Water Columns

KAUST Repository

Bougouffa, Salim

2013-03-29

Atlantis II and Discovery are two hydrothermal and hypersaline deep-sea pools in the Red Sea rift that are characterized by strong thermohalo-stratification and temperatures steadily peaking near the bottom. We conducted comprehensive vertical profiling of the microbial populations in both pools and highlighted the influential environmental factors. Pyrosequencing of the 16S rRNA genes revealed shifts in community structures vis-à-vis depth. High diversity and low abundance were features of the deepest convective layers despite the low cell density. Surprisingly, the brine interfaces had significantly higher cell counts than the overlying deep-sea water, yet they were lowest in diversity. Vertical stratification of the bacterial populations was apparent as we moved from the Alphaproteobacteria-dominated deep sea to the Planctomycetaceae- or Deferribacteres-dominated interfaces to the Gammaproteobacteria-dominated brine layers. Archaeal marine group I was dominant in the deep-sea water and interfaces, while several euryarchaeotic groups increased in the brine. Across sites, microbial phylotypes and abundances varied substantially in the brine interface of Discovery compared with Atlantis II, despite the near-identical populations in the overlying deep-sea waters. The lowest convective layers harbored interestingly similar microbial communities, even though temperature and heavy metal concentrations were very different. Multivariate analysis indicated that temperature and salinity were the major influences shaping the communities. The harsh conditions and the low-abundance phylotypes could explain the observed correlation in the brine pools.

Efficient absorption of SO{sub 2} with low-partial pressures by environmentally benign functional deep eutectic solvents

Energy Technology Data Exchange (ETDEWEB)

Zhang, Kai; Ren, Shuhang [State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 100029 (China); Hou, Yucui [Department of Chemistry, Taiyuan Normal University, Taiyuan, 030031 (China); Wu, Weize, E-mail: wzwu@mail.buct.edu.cn [State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 100029 (China)

2017-02-15

Graphical abstract: Environmentally benign deep eutectic solvents (DESs) based on betaine or L-carnitine with ethylene glycol were designed with a function and used to efficiently capture SO{sub 2} with low partial pressures. - Highlights: • Deep eutectic solvents (DESs) were designed with a function to absorb low-conc. SO{sub 2}. • Betaine(Bet) and L-carnitine(L-car) with a functional group were used as H-bond acceptor. • Bet + ethylene glycol (EG) DES and L-car + EG DES are environmentally benign. • L-car + EG DES can absorb 0.644 mol SO{sub 2} per mole L-car (0.37% SO{sub 2}). • L-car + EG DES is a promising absorbent for SO{sub 2} capture. - Abstract: Sulfur dioxide (SO{sub 2}) emitted from the burning of fossil fuels is one of the main air contaminants. In this work, we found that environmentally benign solvents, deep eutectic solvents (DESs) could be designed with a function to absorb low-partial pressure SO{sub 2} from simulated flue gas. Two kinds of biodegradable functional DESs based on betaine (Bet) and L-carnitine (L-car) as hydrogen bond accepters (HBA) and ethylene glycol (EG) as a hydrogen bond donor (HBD) were prepared with mole ratios of HBA to HBD from 1:3 to 1:5, and they were investigated to absorb SO{sub 2} with different partial pressures at various temperatures. The results showed that the two DESs could absorb low-partial pressure SO{sub 2} efficiently. SO{sub 2} absorption capacities of the DESs with HBA/HBD mole ratio of 1:3 were 0.332 mol SO{sub 2}/mol HBA for Bet + EG DES and 0.820 mol SO{sub 2}/mol HBA for L-car + EG DES at 40 °C with a SO{sub 2} partial pressure of 0.02 atm. In addition, the regeneration experiments demonstrated that the absorption capacities of DESs did not change after five absorption and desorption cycles. Furthermore, the absorption mechanism of SO{sub 2} by DESs was studied by FT-IR, {sup 1}H NMR and {sup 13}C NMR spectra. It was found that there are strong acid–base interactions between SO{sub 2} and

Background rejection in NEXT using deep neural networks

CERN Document Server

Renner, J.

2017-01-01

We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.

Background rejection in NEXT using deep neural networks

International Nuclear Information System (INIS)

Renner, J.; Farbin, A.; Vidal, J. Muñoz; Benlloch-Rodríguez, J. M.; Botas, A.

2017-01-01

Here, we investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.

Support technology of deep roadway under high stress and its application

Institute of Scientific and Technical Information of China (English)

Cao Rihong; Cao Ping; Lin Hang

2016-01-01

Roadway instability has been a major concern in the fields of mining engineering. This paper aims to provide practical and efficient strategy to support the roadways under high in-situ stress. A case study on the stability of deep roadways was carried out in an underground mine in Gansu province, China. Currently,the surrounding rock strata is extremely fractured, which results in a series of engineering disasters, such as side wall collapse and severe floor heave in the past decades. Aiming to solve these problems, an improved support method was proposed, which includes optimal bolt parameters and arrangement, floor beam layout by grooving, and full length grouting. Based on the modeling results by FLAC3D, the new support method is much better than the current one in terms of preventing the large deformation of surrounding rock and restricting the development of plastic zones. For implementation and verification, field experiments, along with deformation monitoring, were conducted in the 958 level roadway of Mining II areas. The results show that the improved support can significantly reduce surrounding rock deformation, avoid frequent repair, and maintain the long-term stability of the roadway. Compared to the original support, the new support method can greatly save investment of mines, and has good application value and popularization value.

High efficacy with deep nurse-administered propofol sedation for advanced gastroenterologic endoscopic procedures

DEFF Research Database (Denmark)

Jensen, Jeppe Thue; Hornslet, Pernille; Konge, Lars

2016-01-01

was requested eight times (0.4 %). One patient was intubated due to suspected aspiration. CONCLUSIONS: Intermittent deep NAPS for advanced endoscopies in selected patients provided an almost 100 % success rate. However, the rate of hypoxia, hypotension and respiratory support was high compared with previously......BACKGROUND AND STUDY AIMS: Whereas data on moderate nurse-administered propofol sedation (NAPS) efficacy and safety for standard endoscopy is abundant, few reports on the use of deep sedation by endoscopy nurses during advanced endoscopy, such as Endoscopic Retrograde Cholangiopancreatography (ERCP......) and Endoscopic Ultrasound (EUS) are available and potential benefits or hazards remain unclear. The aims of this study were to investigate the efficacy of intermittent deep sedation with propofol for a large cohort of advanced endoscopies and to provide data on the safety. PATIENTS AND METHODS: All available...

Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

Science.gov (United States)

Xin, L.

2018-04-01

Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

Microwave pumped high-efficient thermoacoustic tumor therapy with single wall carbon nanotubes.

Science.gov (United States)

Wen, Liewei; Ding, Wenzheng; Yang, Sihua; Xing, Da

2016-01-01

The ultra-short pulse microwave could excite to the strong thermoacoustic (TA) shock wave and deeply penetrate in the biological tissues. Based on this, we developed a novel deep-seated tumor therapy modality with mitochondria-targeting single wall carbon nanotubes (SWNTs) as microwave absorbing agents, which act efficiently to convert ultra-short microwave energy into TA shock wave and selectively destroy the targeted mitochondria, thereby inducing apoptosis in cancer cells. After the treatment of SWNTs (40 μg/mL) and ultra-short microwave (40 Hz, 1 min), 77.5% of cancer cells were killed and the vast majority were caused by apoptosis that initiates from mitochondrial damage. The orthotopic liver cancer mice were established as deep-seated tumor model to investigate the anti-tumor effect of mitochondria-targeting TA therapy. The results suggested that TA therapy could effectively inhibit the tumor growth without any observable side effects, while it was difficult to achieve with photothermal or photoacoustic therapy. These discoveries implied the potential application of TA therapy in deep-seated tumor models and should be further tested for development into a promising therapeutic modality for cancer treatment. Copyright © 2015 Elsevier Ltd. All rights reserved.

High-speed railway real-time localization auxiliary method based on deep neural network

Science.gov (United States)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

40 CFR 761.71 - High efficiency boilers.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false High efficiency boilers. 761.71... PROHIBITIONS Storage and Disposal § 761.71 High efficiency boilers. (a) To burn mineral oil dielectric fluid containing a PCB concentration of ≥50 ppm, but boiler shall comply with the following...

Unconventional, High-Efficiency Propulsors

DEFF Research Database (Denmark)

Andersen, Poul

1996-01-01

The development of ship propellers has generally been characterized by search for propellers with as high efficiency as possible and at the same time low noise and vibration levels and little or no cavitation. This search has lead to unconventional propulsors, like vane-wheel propulsors, contra-r...

Bacterial niche-specific genome expansion is coupled with highly frequent gene disruptions in deep-sea sediments

KAUST Repository

Wang, Yong; Yang, Jiang Ke; Lee, On On; Li, Tie Gang; Al-Suwailem, Abdulaziz M.; Danchin, Antoine; Qian, Pei-Yuan

2011-01-01

The complexity and dynamics of microbial metagenomes may be evaluated by genome size, gene duplication and the disruption rate between lineages. In this study, we pyrosequenced the metagenomes of microbes obtained from the brine and sediment of a deep-sea brine pool in the Red Sea to explore the possible genomic adaptations of the microbes in response to environmental changes. The microbes from the brine and sediments (both surface and deep layers) of the Atlantis II Deep brine pool had similar communities whereas the effective genome size varied from 7.4 Mb in the brine to more than 9 Mb in the sediment. This genome expansion in the sediment samples was due to gene duplication as evidenced by enrichment of the homologs. The duplicated genes were highly disrupted, on average by 47.6% and 70% for the surface and deep layers of the Atlantis II Deep sediment samples, respectively. The disruptive effects appeared to be mainly due to point mutations and frameshifts. In contrast, the homologs from the Atlantis II Deep brine sample were highly conserved and they maintained relatively small copy numbers. Likely, the adaptation of the microbes in the sediments was coupled with pseudogenizations and possibly functional diversifications of the paralogs in the expanded genomes. The maintenance of the pseudogenes in the large genomes is discussed. © 2011 Wang et al.

Bacterial niche-specific genome expansion is coupled with highly frequent gene disruptions in deep-sea sediments

KAUST Repository

Wang, Yong

2011-12-21

The complexity and dynamics of microbial metagenomes may be evaluated by genome size, gene duplication and the disruption rate between lineages. In this study, we pyrosequenced the metagenomes of microbes obtained from the brine and sediment of a deep-sea brine pool in the Red Sea to explore the possible genomic adaptations of the microbes in response to environmental changes. The microbes from the brine and sediments (both surface and deep layers) of the Atlantis II Deep brine pool had similar communities whereas the effective genome size varied from 7.4 Mb in the brine to more than 9 Mb in the sediment. This genome expansion in the sediment samples was due to gene duplication as evidenced by enrichment of the homologs. The duplicated genes were highly disrupted, on average by 47.6% and 70% for the surface and deep layers of the Atlantis II Deep sediment samples, respectively. The disruptive effects appeared to be mainly due to point mutations and frameshifts. In contrast, the homologs from the Atlantis II Deep brine sample were highly conserved and they maintained relatively small copy numbers. Likely, the adaptation of the microbes in the sediments was coupled with pseudogenizations and possibly functional diversifications of the paralogs in the expanded genomes. The maintenance of the pseudogenes in the large genomes is discussed. © 2011 Wang et al.

Bacterial niche-specific genome expansion is coupled with highly frequent gene disruptions in deep-sea sediments.

Directory of Open Access Journals (Sweden)

Yong Wang

Full Text Available The complexity and dynamics of microbial metagenomes may be evaluated by genome size, gene duplication and the disruption rate between lineages. In this study, we pyrosequenced the metagenomes of microbes obtained from the brine and sediment of a deep-sea brine pool in the Red Sea to explore the possible genomic adaptations of the microbes in response to environmental changes. The microbes from the brine and sediments (both surface and deep layers of the Atlantis II Deep brine pool had similar communities whereas the effective genome size varied from 7.4 Mb in the brine to more than 9 Mb in the sediment. This genome expansion in the sediment samples was due to gene duplication as evidenced by enrichment of the homologs. The duplicated genes were highly disrupted, on average by 47.6% and 70% for the surface and deep layers of the Atlantis II Deep sediment samples, respectively. The disruptive effects appeared to be mainly due to point mutations and frameshifts. In contrast, the homologs from the Atlantis II Deep brine sample were highly conserved and they maintained relatively small copy numbers. Likely, the adaptation of the microbes in the sediments was coupled with pseudogenizations and possibly functional diversifications of the paralogs in the expanded genomes. The maintenance of the pseudogenes in the large genomes is discussed.

Fragment-based lead generation: identification of seed fragments by a highly efficient fragment screening technology

Science.gov (United States)

Neumann, Lars; Ritscher, Allegra; Müller, Gerhard; Hafenbradl, Doris

2009-08-01

For the detection of the precise and unambiguous binding of fragments to a specific binding site on the target protein, we have developed a novel reporter displacement binding assay technology. The application of this technology for the fragment screening as well as the fragment evolution process with a specific modelling based design strategy is demonstrated for inhibitors of the protein kinase p38alpha. In a fragment screening approach seed fragments were identified which were then used to build compounds from the deep-pocket towards the hinge binding area of the protein kinase p38alpha based on a modelling approach. BIRB796 was used as a blueprint for the alignment of the fragments. The fragment evolution of these deep-pocket binding fragments towards the fully optimized inhibitor BIRB796 included the modulation of the residence time as well as the affinity. The goal of our study was to evaluate the robustness and efficiency of our novel fragment screening technology at high fragment concentrations, compare the screening data with biochemical activity data and to demonstrate the evolution of the hit fragments with fast kinetics, into slow kinetic inhibitors in an in silico approach.

High temperature annealing effects on deep-level defects in a high purity semi-insulating 4H-SiC substrate

Energy Technology Data Exchange (ETDEWEB)

Iwamoto, Naoya, E-mail: naoya.iwamoto@smn.uio.no; Azarov, Alexander; Svensson, Bengt G. [Department of Physics, Center for Materials Science and Nanotechnology, University of Oslo, P.O. Box 1048 Blindern, N-0316 Oslo (Norway); Ohshima, Takeshi [Japan Atomic Energy Agency, 1233 Watanuki, Takasaki, 370-1292 Gunma (Japan); Moe, Anne Marie M. [Washington Mills AS, N-7300 Orkanger (Norway)

2015-07-28

Effects of high-temperature annealing on deep-level defects in a high-purity semi-insulating 4H silicon carbide substrate have been studied by employing current-voltage, capacitance-voltage, junction spectroscopy, and chemical impurity analysis measurements. Secondary ion mass spectrometry data reveal that the substrate contains boron with concentration in the mid 10{sup 15 }cm{sup −3} range, while other impurities including nitrogen, aluminum, titanium, vanadium and chromium are below their detection limits (typically ∼10{sup 14 }cm{sup −3}). Schottky barrier diodes fabricated on substrates annealed at 1400–1700 °C exhibit metal/p-type semiconductor behavior with a current rectification of up to 8 orders of magnitude at bias voltages of ±3 V. With increasing annealing temperature, the series resistance of the Schottky barrier diodes decreases, and the net acceptor concentration in the substrates increases approaching the chemical boron content. Admittance spectroscopy results unveil the presence of shallow boron acceptors and deep-level defects with levels in lower half of the bandgap. After the 1400 °C annealing, the boron acceptor still remains strongly compensated at room temperature by deep donor-like levels located close to mid-gap. However, the latter decrease in concentration with increasing annealing temperature and after 1700 °C, the boron acceptor is essentially uncompensated. Hence, the deep donors are decisive for the semi-insulating properties of the substrates, and their thermal evolution limits the thermal budget for device processing. The origin of the deep donors is not well-established, but substantial evidence supporting an assignment to carbon vacancies is presented.

Research & Implementation of AC - DC Converter with High Power Factor & High Efficiency

Directory of Open Access Journals (Sweden)

Hsiou-Hsian Nien

2014-05-01

Full Text Available In this paper, we design and develop a high power factor, high efficiency two-stage AC - DC power converter. This paper proposes a two-stage AC - DC power converter. The first stage is boost active power factor correction circuit. The latter stage is near constant frequency LLC resonant converter. In addition to traditional LLC high efficiency advantages, light-load conversion efficiency of this power converter can be improved. And it possesses high power factor and near constant frequency operating characteristics, can significantly reduce the electromagnetic interference. This paper first discusses the main structure and control manner of power factor correction circuit. And then by the LLC resonant converter equivalent model proceed to circuit analysis to determine the important parameters of the converter circuit elements. Then design a variable frequency resonant tank. The resonant frequency can change automatically on the basis of the load to reach near constant frequency operation and a purpose of high efficiency. Finally, actually design and produce an AC – DC power converter with output of 190W to verify the characteristics and feasibility of this converter. The experimental results show that in a very light load (9.5 W the efficiency is as high as 81%, the highest efficiency of 88% (90 W. Full load efficiency is 87%. At 19 W ~ 190 W power changes, the operating frequency change is only 0.4 kHz (AC 110 V and 0.3 kHz (AC 220 V.

Efficiency of poly-generating high temperature fuel cells

Energy Technology Data Exchange (ETDEWEB)

Margalef, Pere; Brown, Tim; Brouwer, Jacob; Samuelsen, Scott [National Fuel Cell Research Center (NFCRC), University of California, Irvine, CA 92697-3550 (United States)

2011-02-15

High temperature fuel cells can be designed and operated to poly-generate electricity, heat, and useful chemicals (e.g., hydrogen) in a variety of configurations. The highly integrated and synergistic nature of poly-generating high temperature fuel cells, however, precludes a simple definition of efficiency for analysis and comparison of performance to traditional methods. There is a need to develop and define a methodology to calculate each of the co-product efficiencies that is useful for comparative analyses. Methodologies for calculating poly-generation efficiencies are defined and discussed. The methodologies are applied to analysis of a Hydrogen Energy Station (H{sub 2}ES) showing that high conversion efficiency can be achieved for poly-generation of electricity and hydrogen. (author)

Superconducting Nanowire Single Photon Detectors for High-Data-Rate Deep-Space Optical Communication

Data.gov (United States)

National Aeronautics and Space Administration — High data rate deep space optical communication (DSOC) links for manned and unmanned space exploration have been identified by NASA as a critical future capability,...

FINITE ELEMENT ANALYSIS OF DEEP BEAM UNDER DIRECT AND INDIRECT LOAD

Directory of Open Access Journals (Sweden)

Haleem K. Hussain

2018-05-01

Full Text Available This research study the effect of exist of opening in web of deep beam loaded directly and indirectly and the behavior of reinforced concrete deep beams without with and without web reinforcement, the opening size and shear span ratio (a/d was constant. Nonlinear analysis using the finite element method with ANSYS software release 12.0 program was used to predict the ultimate load capacity and crack propagation for reinforced concrete deep beams with openings. The adopted beam models depend on experimental test program of reinforced concrete deep beam with and without openings and the finite element analysis result showed a good agreement with small amount of deference in ultimate beam capacity with (ANSYS analysis and it was completely efficient to simulate the behavior of reinforced concrete deep beams. The mid-span deflection at ultimate applied load and inclined cracked were highly compatible with experimental results. The model with opening in the shear span shows a reduction in the load-carrying capacity of beam and adding the vertical stirrup has improve the capacity of ultimate beam load.

High efficiency, variable geometry, centrifugal cryogenic pump

International Nuclear Information System (INIS)

Forsha, M.D.; Nichols, K.E.; Beale, C.A.

1994-01-01

A centrifugal cryogenic pump has been developed which has a basic design that is rugged and reliable with variable speed and variable geometry features that achieve high pump efficiency over a wide range of head-flow conditions. The pump uses a sealless design and rolling element bearings to achieve high reliability and the ruggedness to withstand liquid-vapor slugging. The pump can meet a wide range of variable head, off-design flow requirements and maintain design point efficiency by adjusting the pump speed. The pump also has features that allow the impeller and diffuser blade heights to be adjusted. The adjustable height blades were intended to enhance the pump efficiency when it is operating at constant head, off-design flow rates. For small pumps, the adjustable height blades are not recommended. For larger pumps, they could provide off-design efficiency improvements. This pump was developed for supercritical helium service, but the design is well suited to any cryogenic application where high efficiency is required over a wide range of head-flow conditions

Recursive Monte Carlo method for deep-penetration problems

International Nuclear Information System (INIS)

Goldstein, M.; Greenspan, E.

1980-01-01

The Recursive Monte Carlo (RMC) method developed for estimating importance function distributions in deep-penetration problems is described. Unique features of the method, including the ability to infer the importance function distribution pertaining to many detectors from, essentially, a single M.C. run and the ability to use the history tape created for a representative region to calculate the importance function in identical regions, are illustrated. The RMC method is applied to the solution of two realistic deep-penetration problems - a concrete shield problem and a Tokamak major penetration problem. It is found that the RMC method can provide the importance function distributions, required for importance sampling, with accuracy that is suitable for an efficient solution of the deep-penetration problems considered. The use of the RMC method improved, by one to three orders of magnitude, the solution efficiency of the two deep-penetration problems considered: a concrete shield problem and a Tokamak major penetration problem. 8 figures, 4 tables

Toolkits and Libraries for Deep Learning.

Science.gov (United States)

Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy; Philbrick, Kenneth

2017-08-01

Deep learning is an important new area of machine learning which encompasses a wide range of neural network architectures designed to complete various tasks. In the medical imaging domain, example tasks include organ segmentation, lesion detection, and tumor classification. The most popular network architecture for deep learning for images is the convolutional neural network (CNN). Whereas traditional machine learning requires determination and calculation of features from which the algorithm learns, deep learning approaches learn the important features as well as the proper weighting of those features to make predictions for new data. In this paper, we will describe some of the libraries and tools that are available to aid in the construction and efficient execution of deep learning as applied to medical images.

Fusion of shallow and deep features for classification of high-resolution remote sensing images

Science.gov (United States)

Gao, Lang; Tian, Tian; Sun, Xiao; Li, Hang

2018-02-01

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.

STIMULATION TECHNOLOGIES FOR DEEP WELL COMPLETIONS

Energy Technology Data Exchange (ETDEWEB)

Stephen Wolhart

2003-06-01

The Department of Energy (DOE) is sponsoring a Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies is conducting a project to evaluate the stimulation of deep wells. The objective of the project is to assess U.S. deep well drilling & stimulation activity, review rock mechanics & fracture growth in deep, high pressure/temperature wells and evaluate stimulation technology in several key deep plays. Phase 1 was recently completed and consisted of assessing deep gas well drilling activity (1995-2007) and an industry survey on deep gas well stimulation practices by region. Of the 29,000 oil, gas and dry holes drilled in 2002, about 300 were drilled in the deep well; 25% were dry, 50% were high temperature/high pressure completions and 25% were simply deep completions. South Texas has about 30% of these wells, Oklahoma 20%, Gulf of Mexico Shelf 15% and the Gulf Coast about 15%. The Rockies represent only 2% of deep drilling. Of the 60 operators who drill deep and HTHP wells, the top 20 drill almost 80% of the wells. Six operators drill half the U.S. deep wells. Deep drilling peaked at 425 wells in 1998 and fell to 250 in 1999. Drilling is expected to rise through 2004 after which drilling should cycle down as overall drilling declines.

Tailored Materials for High Efficiency CIDI Engines

Energy Technology Data Exchange (ETDEWEB)

Grant, G.J.; Jana, S.

2012-03-30

The overall goal of the project, Tailored Materials for High Efficiency Compression Ignition Direct Injection (CIDI) Engines, is to enable the implementation of new combustion strategies, such as homogeneous charge compression ignition (HCCI), that have the potential to significantly increase the energy efficiency of current diesel engines and decrease fuel consumption and environmental emissions. These strategies, however, are increasing the demands on conventional engine materials, either from increases in peak cylinder pressure (PCP) or from increases in the temperature of operation. The specific objective of this project is to investigate the application of a new material processing technology, friction stir processing (FSP), to improve the thermal and mechanical properties of engine components. The concept is to modify the surfaces of conventional, low-cost engine materials. The project focused primarily on FSP in aluminum materials that are compositional analogs to the typical piston and head alloys seen in small- to mid-sized CIDI engines. Investigations have been primarily of two types over the duration of this project: (1) FSP of a cast hypoeutectic Al-Si-Mg (A356/357) alloy with no introduction of any new components, and (2) FSP of Al-Cu-Ni alloys (Alloy 339) by physically stirring-in various quantities of carbon nanotubes/nanofibers or carbon fibers. Experimental work to date on aluminum systems has shown significant increases in fatigue lifetime and stress-level performance in aluminum-silicon alloys using friction processing alone, but work to demonstrate the addition of carbon nanotubes and fibers into aluminum substrates has shown mixed results due primarily to the difficulty in achieving porosity-free, homogeneous distributions of the particulate. A limited effort to understand the effects of FSP on steel materials was also undertaken during the course of this project. Processed regions were created in high-strength, low-alloyed steels up to 0.5 in

HIGH EFFICIENCY TURBINE

OpenAIRE

VARMA, VIJAYA KRUSHNA

2012-01-01

Varma designed ultra modern and high efficiency turbines which can use gas, steam or fuels as feed to produce electricity or mechanical work for wide range of usages and applications in industries or at work sites. Varma turbine engines can be used in all types of vehicles. These turbines can also be used in aircraft, ships, battle tanks, dredgers, mining equipment, earth moving machines etc, Salient features of Varma Turbines. 1. Varma turbines are simple in design, easy to manufac...

Gamma-ray spectrometer system with high efficiency and high resolution

International Nuclear Information System (INIS)

Moss, C.E.; Bernard, W.; Dowdy, E.J.; Garcia, C.; Lucas, M.C.; Pratt, J.C.

1983-01-01

Our gamma-ray spectrometer system, designed for field use, offers high efficiency and high resolution for safeguards applications. The system consists of three 40% high-purity germanium detectors and a LeCroy 3500 data acquisition system that calculates a composite spectrum for the three detectors. The LeCroy 3500 mainframe can be operated remotely from the detector array with control exercised through modems and the telephone system. System performance with a mixed source of 125 Sb, 154 Eu, and 155 Eu confirms the expected efficiency of 120% with the overall resolution showing little degradation over that of the worst detector

High voltage generator circuit with low power and high efficiency applied in EEPROM

International Nuclear Information System (INIS)

Liu Yan; Zhang Shilin; Zhao Yiqiang

2012-01-01

This paper presents a low power and high efficiency high voltage generator circuit embedded in electrically erasable programmable read-only memory (EEPROM). The low power is minimized by a capacitance divider circuit and a regulator circuit using the controlling clock switch technique. The high efficiency is dependent on the zero threshold voltage (V th ) MOSFET and the charge transfer switch (CTS) charge pump. The proposed high voltage generator circuit has been implemented in a 0.35 μm EEPROM CMOS process. Measured results show that the proposed high voltage generator circuit has a low power consumption of about 150.48 μW and a higher pumping efficiency (83.3%) than previously reported circuits. This high voltage generator circuit can also be widely used in low-power flash devices due to its high efficiency and low power dissipation. (semiconductor integrated circuits)

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

Directory of Open Access Journals (Sweden)

Yunlong Yu

2018-01-01

Full Text Available One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

Detection of Thermal Erosion Gullies from High-Resolution Images Using Deep Learning

Science.gov (United States)

Huang, L.; Liu, L.; Jiang, L.; Zhang, T.; Sun, Y.

2017-12-01

Thermal erosion gullies, one type of thermokarst landforms, develop due to thawing of ice-rich permafrost. Mapping the location and extent of thermal erosion gullies can help understand the spatial distribution of thermokarst landforms and their temporal evolution. Remote sensing images provide an effective way for mapping thermokarst landforms, especially thermokarst lakes. However, thermal erosion gullies are challenging to map from remote sensing images due to their small sizes and significant variations in geometric/radiometric properties. It is feasible to manually identify these features, as a few previous studies have carried out. However manual methods are labor-intensive, therefore, cannot be used for a large study area. In this work, we conduct automatic mapping of thermal erosion gullies from high-resolution images by using Deep Learning. Our study area is located in Eboling Mountain (Qinghai, China). Within a 6 km2 peatland area underlain by ice-rich permafrost, at least 20 thermal erosional gullies are well developed. The image used is a 15-cm-resolution Digital Orthophoto Map (DOM) generated in July 2016. First, we extracted 14 gully patches and ten non-gully patches as training data. And we performed image augmentation. Next, we fine-tuned the pre-trained model of DeepLab, a deep-learning algorithm for semantic image segmentation based on Deep Convolutional Neural Networks. Then, we performed inference on the whole DOM and obtained intermediate results in forms of polygons for all identified gullies. At last, we removed misidentified polygons based on a few pre-set criteria on the size and shape of each polygon. Our final results include 42 polygons. Validated against field measurements using GPS, most of the gullies are detected correctly. There are 20 false detections due to the small number and low quality of training images. We also found three new gullies that missed in the field observations. This study shows that (1) despite a challenging

Deep Learning from Crowds

DEFF Research Database (Denmark)

Rodrigues, Filipe; Pereira, Francisco Camara

Over the last few years, deep learning has revolutionized the field of machine learning by dramatically improving the stateof-the-art in various domains. However, as the size of supervised artificial neural networks grows, typically so does the need for larger labeled datasets. Recently...... networks from crowds. We begin by describing an EM algorithm for jointly learning the parameters of the network and the reliabilities of the annotators. Then, a novel general-purpose crowd layer is proposed, which allows us to train deep neural networks end-to-end, directly from the noisy labels......, crowdsourcing has established itself as an efficient and cost-effective solution for labeling large sets of data in a scalable manner, but it often requires aggregating labels from multiple noisy contributors with different levels of expertise. In this paper, we address the problem of learning deep neural...

Deep Keck u-Band Imaging of the Hubble Ultra Deep Field: A Catalog of z ~ 3 Lyman Break Galaxies

Science.gov (United States)

Rafelski, Marc; Wolfe, Arthur M.; Cooke, Jeff; Chen, Hsiao-Wen; Armandroff, Taft E.; Wirth, Gregory D.

2009-10-01

We present a sample of 407 z ~ 3 Lyman break galaxies (LBGs) to a limiting isophotal u-band magnitude of 27.6 mag in the Hubble Ultra Deep Field. The LBGs are selected using a combination of photometric redshifts and the u-band drop-out technique enabled by the introduction of an extremely deep u-band image obtained with the Keck I telescope and the blue channel of the Low Resolution Imaging Spectrometer. The Keck u-band image, totaling 9 hr of integration time, has a 1σ depth of 30.7 mag arcsec-2, making it one of the most sensitive u-band images ever obtained. The u-band image also substantially improves the accuracy of photometric redshift measurements of ~50% of the z ~ 3 LBGs, significantly reducing the traditional degeneracy of colors between z ~ 3 and z ~ 0.2 galaxies. This sample provides the most sensitive, high-resolution multi-filter imaging of reliably identified z ~ 3 LBGs for morphological studies of galaxy formation and evolution and the star formation efficiency of gas at high redshift.

High Temperature Reactor (HTR) Deep Burn Core and Fuel Analysis: Design Selection for the Prismatic Block Reactor

Energy Technology Data Exchange (ETDEWEB)

Francesco Venneri; Chang-Keun Jo; Jae-Man Noh; Yonghee Kim; Claudio Filippone; Jonghwa Chang; Chris Hamilton; Young-Min Kim; Ji-Su Jun; Moon-Sung Cho; Hong-Sik Lim; MIchael A. Pope; Abderrafi M. Ougouag; Vincent Descotes; Brian Boer

2010-09-01

The Deep Burn (DB) Project is a U.S. Department of Energy sponsored feasibility study of Transuranic Management using high burnup fuel in the high temperature helium cooled reactor (HTR). The DB Project consists of seven tasks: project management, core and fuel analysis, spent fuel management, fuel cycle integration, TRU fuel modeling, TRU fuel qualification, and HTR fuel recycle. In the Phase II of the Project, we conducted nuclear analysis of TRU destruction/utilization in the HTR prismatic block design (Task 2.1), deep burn fuel/TRISO microanalysis (Task 2.3), and synergy with fast reactors (Task 4.2). The Task 2.1 covers the core physics design, thermo-hydraulic CFD analysis, and the thermofluid and safety analysis (low pressure conduction cooling, LPCC) of the HTR prismatic block design. The Task 2.3 covers the analysis of the structural behavior of TRISO fuel containing TRU at very high burnup level, i.e. exceeding 50% of FIMA. The Task 4.2 includes the self-cleaning HTR based on recycle of HTR-generated TRU in the same HTR. Chapter IV contains the design and analysis results of the 600MWth DB-HTR core physics with the cycle length, the average discharged burnup, heavy metal and plutonium consumptions, radial and axial power distributions, temperature reactivity coefficients. Also, it contains the analysis results of the 450MWth DB-HTR core physics and the analysis of the decay heat of a TRU loaded DB-HTR core. The evaluation of the hot spot fuel temperature of the fuel block in the DB-HTR (Deep-Burn High Temperature Reactor) core under full operating power conditions are described in Chapter V. The investigated designs are the 600MWth and 460MWth DB-HTRs. In Chapter VI, the thermo-fluid and safety of the 600MWth DB-HTRs has been analyzed to investigate a thermal-fluid design performance at the steady state and a passive safety performance during an LPCC event. Chapter VII describes the analysis results of the TRISO fuel microanalysis of the 600MWth and 450

Development and characterization of high-efficiency, high-specific impulse xenon Hall thrusters

Science.gov (United States)

Hofer, Richard Robert

This dissertation presents research aimed at extending the efficient operation of 1600 s specific impulse Hall thruster technology to the 2000--3000 s range. While recent studies of commercially developed Hall thrusters demonstrated greater than 4000 s specific impulse, maximum efficiency occurred at less than 3000 s. It was hypothesized that the efficiency maximum resulted as a consequence of modern magnetic field designs, optimized for 1600 s, which were unsuitable at high-specific impulse. Motivated by the industry efforts and mission studies, the aim of this research was to develop and characterize xenon Hall thrusters capable of both high-specific impulse and high-efficiency operation. The research divided into development and characterization phases. During the development phase, the laboratory-model NASA-173M Hall thrusters were designed with plasma lens magnetic field topographies and their performance and plasma characteristics were evaluated. Experiments with the NASA-173M version 1 (v1) validated the plasma lens design by showing how changing the magnetic field topography at high-specific impulse improved efficiency. Experiments with the NASA-173M version 2 (v2) showed there was a minimum current density and optimum magnetic field topography at which efficiency monotonically increased with voltage. Between 300--1000 V, total specific impulse and total efficiency of the NASA-173Mv2 operating at 10 mg/s ranged from 1600--3400 s and 51--61%, respectively. Comparison of the thrusters showed that efficiency can be optimized for specific impulse by varying the plasma lens design. During the characterization phase, additional plasma properties of the NASA-173Mv2 were measured and a performance model was derived accounting for a multiply-charged, partially-ionized plasma. Results from the model based on experimental data showed how efficient operation at high-specific impulse was enabled through regulation of the electron current with the magnetic field. The

Support technology of deep roadway under high stress and its application

Institute of Scientific and Technical Information of China (English)

Cao Rihong; Cao Ping; Lin Hang

2016-01-01

Roadway instability has been a major concern in the fields of mining engineering. This paper aims to pro-vide practical and efficient strategy to support the roadways under high in-situ stress. A case study on the stability of deep roadways was carried out in an underground mine in Gansu province, China. Currently, the surrounding rock strata is extremely fractured, which results in a series of engineering disasters, such as side wall collapse and severe floor heave in the past decades. Aiming to solve these problems, an improved support method was proposed, which includes optimal bolt parameters and arrangement, floor beam layout by grooving, and full length grouting. Based on the modeling results by FLAC3D, the new support method is much better than the current one in terms of preventing the large deformation of sur-rounding rock and restricting the development of plastic zones. For implementation and verification, field experiments, along with deformation monitoring, were conducted in the 958 level roadway of Mining II areas. The results show that the improved support can significantly reduce surrounding rock deforma-tion, avoid frequent repair, and maintain the long-term stability of the roadway. Compared to the original support, the new support method can greatly save investment of mines, and has good application value and popularization value.

High-efficiency white OLEDs based on small molecules

Science.gov (United States)

Hatwar, Tukaram K.; Spindler, Jeffrey P.; Ricks, M. L.; Young, Ralph H.; Hamada, Yuuhiko; Saito, N.; Mameno, Kazunobu; Nishikawa, Ryuji; Takahashi, Hisakazu; Rajeswaran, G.

2004-02-01

Eastman Kodak Company and SANYO Electric Co., Ltd. recently demonstrated a 15" full-color, organic light-emitting diode display (OLED) using a high-efficiency white emitter combined with a color-filter array. Although useful for display applications, white emission from organic structures is also under consideration for other applications, such as solid-state lighting, where high efficiency and good color rendition are important. By incorporating adjacent blue and orange emitting layers in a multi-layer structure, highly efficient, stable white emission has been attained. With suitable host and dopant combinations, a luminance yield of 20 cd/A and efficiency of 8 lm/W have been achieved at a drive voltage of less than 8 volts and luminance level of 1000 cd/m2. The estimated external efficiency of this device is 6.3% and a high level of operational stability is observed. To our knowledge, this is the highest performance reported so far for white organic electroluminescent devices. We will review white OLED technology and discuss the fabrication and operating characteristics of these devices.

Approaches to achieve high grain yield and high resource use efficiency in rice

Directory of Open Access Journals (Sweden)

Jianchang YANG

2015-06-01

Full Text Available This article discusses approaches to simultaneously increase grain yield and resource use efficiency in rice. Breeding nitrogen efficient cultivars without sacrificing rice yield potential, improving grain fill in later-flowering inferior spikelets and enhancing harvest index are three important approaches to achieving the dual goal of high grain yield and high resource use efficiency. Deeper root distribution and higher leaf photosynthetic N use efficiency at lower N rates could be used as selection criteria to develop N-efficient cultivars. Enhancing sink activity through increasing sugar-spikelet ratio at the heading time and enhancing the conversion efficiency from sucrose to starch though increasing the ratio of abscisic acid to ethylene in grains during grain fill could effectively improve grain fill in inferior spikelets. Several practices, such as post-anthesis controlled soil drying, an alternate wetting and moderate soil drying regime during the whole growing season, and non-flooded straw mulching cultivation, could substantially increase grain yield and water use efficiency, mainly via enhanced remobilization of stored carbon from vegetative tissues to grains and improved harvest index. Further research is needed to understand synergistic interaction between water and N on crop and soil and the mechanism underlying high resource use efficiency in high-yielding rice.

Efficiency and Loading Evaluation of High Efficiency Mist Eliminators (HEME) - 12003

Energy Technology Data Exchange (ETDEWEB)

Giffin, Paxton K.; Parsons, Michael S.; Waggoner, Charles A. [Institute for Clean Energy Technology, Mississippi State University, 205 Research Blvd Starkville, MS 39759 (United States)

2012-07-01

High efficiency mist eliminators (HEME) are filters primarily used to remove moisture and/or liquid aerosols from an air stream. HEME elements are designed to reduce aerosol and particulate load on primary High Efficiency Particulate Air (HEPA) filters and to have a liquid particle removal efficiency of approximately 99.5% for aerosols down to sub-micron size particulates. The investigation presented here evaluates the loading capacity of the element in the absence of a water spray cleaning system. The theory is that without the cleaning system, the HEME element will suffer rapid buildup of solid aerosols, greatly reducing the particle loading capacity. Evaluation consists of challenging the element with a waste surrogate dry aerosol and di-octyl phthalate (DOP) at varying intervals of differential pressure to examine the filtering efficiency of three different element designs at three different media velocities. Also, the elements are challenged with a liquid waste surrogate using Laskin nozzles and large dispersion nozzles. These tests allow the loading capacity of the unit to be determined and the effectiveness of washing down the interior of the elements to be evaluated. (authors)

A novel biomedical image indexing and retrieval system via deep preference learning.

Science.gov (United States)

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state

Numerical investigation of high level nuclear waste disposal in deep anisotropic geologic repositories

KAUST Repository

Salama, Amgad; El Amin, Mohamed F.; Sun, Shuyu

2015-01-01

One of the techniques that have been proposed to dispose high level nuclear waste (HLW) has been to bury them in deep geologic formations, which offer relatively enough space to accommodate the large volume of HLW accumulated over the years since

Combustion phasing for maximum efficiency for conventional and high efficiency engines

International Nuclear Information System (INIS)

Caton, Jerald A.

2014-01-01

Highlights: • Combustion phasing for max efficiency is a function of engine parameters. • Combustion phasing is most affected by heat transfer, compression ratio, burn duration. • Combustion phasing is less affected by speed, load, equivalence ratio and EGR. • Combustion phasing for a high efficiency engine was more advanced. • Exergy destruction during combustion as functions of combustion phasing is reported. - Abstract: The importance of the phasing of the combustion event for internal-combustion engines is well appreciated, but quantitative details are sparse. The objective of the current work was to examine the optimum combustion phasing (based on maximum bmep) as functions of engine design and operating variables. A thermodynamic, engine cycle simulation was used to complete this assessment. As metrics for the combustion phasing, both the crank angle for 50% fuel mass burned (CA 50 ) and the crank angle for peak pressure (CA pp ) are reported as functions of the engine variables. In contrast to common statements in the literature, the optimum CA 50 and CA pp vary depending on the design and operating variables. Optimum, as used in this paper, refers to the combustion timing that provides the maximum bmep and brake thermal efficiency (MBT timing). For this work, the variables with the greatest influence on the optimum CA 50 and CA pp were the heat transfer level, the burn duration and the compression ratio. Other variables such as equivalence ratio, EGR level, engine speed and engine load had a much smaller impact on the optimum CA 50 and CA pp . For the conventional engine, for the conditions examined, the optimum CA 50 varied between about 5 and 11°aTDC, and the optimum CA pp varied between about 9 and 16°aTDC. For a high efficiency engine (high dilution, high compression ratio), the optimum CA 50 was 2.5°aTDC, and the optimum CA pp was 7.8°aTDC. These more advanced values for the optimum CA 50 and CA pp for the high efficiency engine were

Highly efficient red electrophosphorescent devices at high current densities

International Nuclear Information System (INIS)

Wu Youzhi; Zhu Wenqing; Zheng Xinyou; Sun, Runguang; Jiang Xueyin; Zhang Zhilin; Xu Shaohong

2007-01-01

Efficiency decrease at high current densities in red electrophosphorescent devices is drastically restrained compared with that from conventional electrophosphorescent devices by using bis(2-methyl-8-quinolinato)4-phenylphenolate aluminum (BAlq) as a hole and exciton blocker. Ir complex, bis(2-(2'-benzo[4,5-α]thienyl) pyridinato-N,C 3' ) iridium (acetyl-acetonate) is used as an emitter, maximum external quantum efficiency (QE) of 7.0% and luminance of 10000cd/m 2 are obtained. The QE is still as high as 4.1% at higher current density J=100mA/cm 2 . CIE-1931 co-ordinates are 0.672, 0.321. A carrier trapping mechanism is revealed to dominate in the process of electroluminescence

Deep Ultraviolet Light Emitters Based on (Al,Ga)N/GaN Semiconductor Heterostructures

Science.gov (United States)

Liang, Yu-Han

Deep ultraviolet (UV) light sources are useful in a number of applications that include sterilization, medical diagnostics, as well as chemical and biological identification. However, state-of-the-art deep UV light-emitting diodes and lasers made from semiconductors still suffer from low external quantum efficiency and low output powers. These limitations make them costly and ineffective in a wide range of applications. Deep UV sources such as lasers that currently exist are prohibitively bulky, complicated, and expensive. This is typically because they are constituted of an assemblage of two to three other lasers in tandem to facilitate sequential harmonic generation that ultimately results in the desired deep UV wavelength. For semiconductor-based deep UV sources, the most challenging difficulty has been finding ways to optimally dope the (Al,Ga)N/GaN heterostructures essential for UV-C light sources. It has proven to be very difficult to achieve high free carrier concentrations and low resistivities in high-aluminum-containing III-nitrides. As a result, p-type doped aluminum-free III-nitrides are employed as the p-type contact layers in UV light-emitting diode structures. However, because of impedance-mismatch issues, light extraction from the device and consequently the overall external quantum efficiency is drastically reduced. This problem is compounded with high losses and low gain when one tries to make UV nitride lasers. In this thesis, we provide a robust and reproducible approach to resolving most of these challenges. By using a liquid-metal-enabled growth mode in a plasma-assisted molecular beam epitaxy process, we show that highly-doped aluminum containing III-nitride films can be achieved. This growth mode is driven by kinetics. Using this approach, we have been able to achieve extremely high p-type and n-type doping in (Al,Ga)N films with high aluminum content. By incorporating a very high density of Mg atoms in (Al,Ga)N films, we have been able to

DEEP KECK u-BAND IMAGING OF THE HUBBLE ULTRA DEEP FIELD: A CATALOG OF z ∼ 3 LYMAN BREAK GALAXIES

International Nuclear Information System (INIS)

Rafelski, Marc; Wolfe, Arthur M.; Cooke, Jeff; Chen, H.-W.; Armandroff, Taft E.; Wirth, Gregory D.

2009-01-01

We present a sample of 407 z ∼ 3 Lyman break galaxies (LBGs) to a limiting isophotal u-band magnitude of 27.6 mag in the Hubble Ultra Deep Field. The LBGs are selected using a combination of photometric redshifts and the u-band drop-out technique enabled by the introduction of an extremely deep u-band image obtained with the Keck I telescope and the blue channel of the Low Resolution Imaging Spectrometer. The Keck u-band image, totaling 9 hr of integration time, has a 1σ depth of 30.7 mag arcsec -2 , making it one of the most sensitive u-band images ever obtained. The u-band image also substantially improves the accuracy of photometric redshift measurements of ∼50% of the z ∼ 3 LBGs, significantly reducing the traditional degeneracy of colors between z ∼ 3 and z ∼ 0.2 galaxies. This sample provides the most sensitive, high-resolution multi-filter imaging of reliably identified z ∼ 3 LBGs for morphological studies of galaxy formation and evolution and the star formation efficiency of gas at high redshift.

MBARI Mapping AUV: A High-Resolution Deep Ocean Seafloor Mapping Capability

Science.gov (United States)

Caress, D. W.; Kirkwood, W. J.; Thomas, H.; McEwen, R.; Henthorn, R.; McGill, P.; Thompson, D.; Sibenac, M.; Jensen, S.; Shane, F.; Hamilton, A.

2005-05-01

The Monterey Bay Aquarium Research Institute (MBARI) is developing an autonomous seafloor mapping capability for deep ocean science applications. The MBARI Mapping AUV is a 0.53 m (21 in) diameter, 5.1 m (16.7 ft) long, Dorado-class vehicle designed to carry four mapping sonars. The primary sensor is a 200 kHz multibeam sonar producing swath bathymetry and sidescan. In addition, the vehicle carries 100 kHz and 410 kHz chirp sidescan sonars, and a 2-16 kHz sweep chirp subbottom profiler. Navigation and attitude data are obtained from an inertial navigation system (INS) incorporating a ring laser gyro and a 300 kHz Doppler velocity log (DVL). The vehicle also includes acoustic modem, ultra-short baseline navigation, and long-baseline navigation systems. The Mapping AUV is powered by 6 kWhr of Li-polymer batteries, providing expected mission duration of 12 hours at a typical speed of 1.5 m/s. All components of the vehicle are rated to 6000 m depth, allowing MBARI to conduct high-resolution mapping of the deep-ocean seafloor. The sonar package is also be mountable on ROV Ventana, allowing surveys at altitudes less than 20 m at topographically challenging sites. The vehicle was assembled and extensively tested during 2004; this year we are commencing operations for MBARI science projects while continuing the process of testing and integrating the complete suite of sensors and systems. MBARI is beginning to use this capability to observe the changing morphology of dynamic systems such as submarine canyons and active slumps, to map deep-water benthic habitats at resolutions comparable to ROV and submersible observations, to provide basemaps for ROV dives, and to provide high resolution bathymetry and subbottom profiles as part of a variety of projects requiring knowledge of the seafloor. We will present initial results from surveys in and around Monterey Canyon, including high resolution repeat surveys of four sites along the canyon axis.

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.

Science.gov (United States)

Neftci, Emre O; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

Directory of Open Access Journals (Sweden)

Emre O. Neftci

2017-06-01

Full Text Available An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

High Efficiency, Low Emission Refrigeration System

Energy Technology Data Exchange (ETDEWEB)

Fricke, Brian A [ORNL; Sharma, Vishaldeep [ORNL

2016-08-01

Supermarket refrigeration systems account for approximately 50% of supermarket energy use, placing this class of equipment among the highest energy consumers in the commercial building domain. In addition, the commonly used refrigeration system in supermarket applications is the multiplex direct expansion (DX) system, which is prone to refrigerant leaks due to its long lengths of refrigerant piping. This leakage reduces the efficiency of the system and increases the impact of the system on the environment. The high Global Warming Potential (GWP) of the hydrofluorocarbon (HFC) refrigerants commonly used in these systems, coupled with the large refrigerant charge and the high refrigerant leakage rates leads to significant direct emissions of greenhouse gases into the atmosphere. Methods for reducing refrigerant leakage and energy consumption are available, but underutilized. Further work needs to be done to reduce costs of advanced system designs to improve market utilization. In addition, refrigeration system retrofits that result in reduced energy consumption are needed since the majority of applications address retrofits rather than new stores. The retrofit market is also of most concern since it involves large-volume refrigerant systems with high leak rates. Finally, alternative refrigerants for new and retrofit applications are needed to reduce emissions and reduce the impact on the environment. The objective of this Collaborative Research and Development Agreement (CRADA) between the Oak Ridge National Laboratory and Hill Phoenix is to develop a supermarket refrigeration system that reduces greenhouse gas emissions and has 25 to 30 percent lower energy consumption than existing systems. The outcomes of this project will include the design of a low emission, high efficiency commercial refrigeration system suitable for use in current U.S. supermarkets. In addition, a prototype low emission, high efficiency supermarket refrigeration system will be produced for

High quality ceramic coatings sprayed by high efficiency hypersonic plasma spraying gun

International Nuclear Information System (INIS)

Zhu Sheng; Xu Binshi; Yao JiuKun

2005-01-01

This paper introduced the structure of the high efficiency hypersonic plasma spraying gun and the effects of hypersonic plasma jet on the sprayed particles. The optimised spraying process parameters for several ceramic powders such as Al 2 O 3 , Cr 2 O 3 , ZrO 2 , Cr 3 C 2 and Co-WC were listed. The properties and microstructure of the sprayed ceramic coatings were investigated. Nano Al 2 O 3 -TiO 2 ceramic coating sprayed by using the high efficiency hypersonic plasma spraying was also studied. Compared with the conventional air plasma spraying, high efficiency hypersonic plasma spraying improves greatly the ceramic coatings quality but at low cost. (orig.)

Simple Motor Control Concept Results High Efficiency at High Velocities

Science.gov (United States)

Starin, Scott; Engel, Chris

2013-09-01

The need for high velocity motors in space applications for reaction wheels and detectors has stressed the limits of Brushless Permanent Magnet Motors (BPMM). Due to inherent hysteresis core losses, conventional BPMMs try to balance the need for torque verses hysteresis losses. Cong-less motors have significantly less hysteresis losses but suffer from lower efficiencies. Additionally, the inherent low inductance in cog-less motors result in high ripple currents or high switching frequencies, which lowers overall efficiency and increases performance demands on the control electronics.However, using a somewhat forgotten but fully qualified technology of Isotropic Magnet Motors (IMM), extremely high velocities may be achieved at low power input using conventional drive electronics. This paper will discuss the trade study efforts and empirical test data on a 34,000 RPM IMM.

High efficiency nebulization for helium inductively coupled plasma mass spectrometry

International Nuclear Information System (INIS)

Jorabchi, Kaveh; McCormick, Ryan; Levine, Jonathan A.; Liu Huiying; Nam, S.-H.; Montaser, Akbar

2006-01-01

A pneumatically-driven, high efficiency nebulizer is explored for helium inductively coupled plasma mass spectrometry. The aerosol characteristics and analyte transport efficiencies of the high efficiency nebulizer for nebulization with helium are measured and compared to the results obtained with argon. Analytical performance indices of the helium inductively coupled plasma mass spectrometry are evaluated in terms of detection limits and precision. The helium inductively coupled plasma mass spectrometry detection limits obtained with the high efficiency nebulizer at 200 μL/min are higher than those achieved with the ultrasonic nebulizer consuming 2 mL/min solution, however, precision is generally better with high efficiency nebulizer (1-4% vs. 3-8% with ultrasonic nebulizer). Detection limits with the high efficiency nebulizer at 200 μL/min solution uptake rate approach those using ultrasonic nebulizer upon efficient desolvation with a heated spray chamber followed by a Peltier-cooled multipass condenser

High Efficiency Power Converter for Low Voltage High Power Applications

DEFF Research Database (Denmark)

Nymand, Morten

The topic of this thesis is the design of high efficiency power electronic dc-to-dc converters for high-power, low-input-voltage to high-output-voltage applications. These converters are increasingly required for emerging sustainable energy systems such as fuel cell, battery or photo voltaic based...

Polarizing beam splitter of deep-etched triangular-groove fused-silica gratings.

Science.gov (United States)

Zheng, Jiangjun; Zhou, Changhe; Feng, Jijun; Wang, Bo

2008-07-15

We investigated the use of a deep-etched fused-silica grating with triangular-shaped grooves as a highly efficient polarizing beam splitter (PBS). A triangular-groove PBS grating is designed at a wavelength of 1550 nm to be used in optical communication. When it is illuminated in Littrow mounting, the transmitted TE- and TM-polarized waves are mainly diffracted in the minus-first and zeroth orders, respectively. The design condition is based on the average differences of the grating mode indices, which is verified by using rigorous coupled-wave analysis. The designed PBS grating is highly efficient over the C+L band range for both TE and TM polarizations (>97.68%). It is shown that such a triangular-groove PBS grating can exhibit a higher diffraction efficiency, a larger extinction ratio, and less reflection loss than the binary-phase fused-silica PBS grating.

New optimized drill pipe size for deep-water, extended reach and ultra-deep drilling

Energy Technology Data Exchange (ETDEWEB)

Jellison, Michael J.; Delgado, Ivanni [Grant Prideco, Inc., Hoston, TX (United States); Falcao, Jose Luiz; Sato, Ademar Takashi [PETROBRAS, Rio de Janeiro, RJ (Brazil); Moura, Carlos Amsler [Comercial Perfuradora Delba Baiana Ltda., Rio de Janeiro, RJ (Brazil)

2004-07-01

A new drill pipe size, 5-7/8 in. OD, represents enabling technology for Extended Reach Drilling (ERD), deep water and other deep well applications. Most world-class ERD and deep water wells have traditionally been drilled with 5-1/2 in. drill pipe or a combination of 6-5/8 in. and 5-1/2 in. drill pipe. The hydraulic performance of 5-1/2 in. drill pipe can be a major limitation in substantial ERD and deep water wells resulting in poor cuttings removal, slower penetration rates, diminished control over well trajectory and more tendency for drill pipe sticking. The 5-7/8 in. drill pipe provides a significant improvement in hydraulic efficiency compared to 5-1/2 in. drill pipe and does not suffer from the disadvantages associated with use of 6-5/8 in. drill pipe. It represents a drill pipe assembly that is optimized dimensionally and on a performance basis for casing and bit programs that are commonly used for ERD, deep water and ultra-deep wells. The paper discusses the engineering philosophy behind 5-7/8 in. drill pipe, the design challenges associated with development of the product and reviews the features and capabilities of the second-generation double-shoulder connection. The paper provides drilling case history information on significant projects where the pipe has been used and details results achieved with the pipe. (author)

High Current Planar Transformer for Very High Efficiency Isolated Boost DC-DC Converters

DEFF Research Database (Denmark)

Pittini, Riccardo; Zhang, Zhe; Andersen, Michael A. E.

2014-01-01

This paper presents a design and optimization of a high current planar transformer for very high efficiency dc-dc isolated boost converters. The analysis considers different winding arrangements, including very high copper thickness windings. The analysis is focused on the winding ac-resistance a......This paper presents a design and optimization of a high current planar transformer for very high efficiency dc-dc isolated boost converters. The analysis considers different winding arrangements, including very high copper thickness windings. The analysis is focused on the winding ac......-resistance and transformer leakage inductance. Design and optimization procedures are validated based on an experimental prototype of a 6 kW dcdc isolated full bridge boost converter developed on fully planar magnetics. The prototype is rated at 30-80 V 0-80 A on the low voltage side and 700-800 V on the high voltage side...... with a peak efficiency of 97.8% at 80 V 3.5 kW. Results highlights that thick copper windings can provide good performance at low switching frequencies due to the high transformer filling factor. PCB windings can also provide very high efficiency if stacked in parallel utilizing the transformer winding window...

High-efficiency silicon solar cells for low-illumination applications

OpenAIRE

Glunz, S.W.; Dicker, J.; Esterle, M.; Hermle, M.; Isenberg, J.; Kamerewerd, F.; Knobloch, J.; Kray, D.; Leimenstoll, A.; Lutz, F.; Oßwald, D.; Preu, R.; Rein, S.; Schäffer, E.; Schetter, C.

2002-01-01

At Fraunhofer ISE the fabrication of high-efficiency solar cells was extended from a laboratory scale to a small pilot-line production. Primarily, the fabricated cells are used in small high-efficiency modules integrated in prototypes of solar-powered portable electronic devices such as cellular phones, handheld computers etc. Compared to other applications of high-efficiency cells such as solar cars and planes, the illumination densities found in these mainly indoor applications are signific...

Structure functions and parton distributions in deep inelastic lepton-hadron scattering at high energies

International Nuclear Information System (INIS)

Bluemlein, J.

1993-08-01

The possibilities to measure structure functions, to extract parton distributions, and to measure α s and Λ QCD in current and future high energy deep inelastic scattering experiments are reviewed. A comparison is given for experiments at HERA, an ep option at LEP xLHC, and a high energy neutrino experiment. (orig.)

Manipulation of Thermally Activated Delayed Fluorescence of Blue Exciplex Emission: Fully Utilizing Exciton Energy for Highly Efficient Organic Light Emitting Diodes with Low Roll-Off.

Science.gov (United States)

Wang, Zixing; Wang, Hedan; Zhu, Jun; Wu, Peng; Shen, Bowen; Dou, Dehai; Wei, Bin

2017-06-28

The application of exciplex energy has become a unique way to achieve organic light-emitting diodes (OLEDs) with high efficiencies, low turn-on voltage, and low roll-off. Novel δ-carboline derivatives with high triplet energy (T 1 ≈ 2.92 eV) and high glass transition temperature (T g ≈ 153 °C) were employed to manipulate exciplex emissions in this paper. Deep blue (peak at 436 nm) and pure blue (peak at 468 nm) thermally activated delayed fluorescence (TADF) of exciplex OLEDs were demonstrated by utilizing them as emitters with the maximum current efficiency (CE) of 4.64 cd A -1 , power efficiency (PE) of 2.91 lm W -1 , and external quantum efficiency (EQE) of 2.36%. Highly efficient blue phosphorescent OLEDs doped with FIrpic showed a maximum CE of 55.6 cd A -1 , PE of 52.9 lm W -1 , and EQE of 24.6% respectively with very low turn on voltage at 2.7 V. The devices still remain high CE of 46.5 cd A -1 at 100 cd m -2 , 45.4 cd A -1 at 1000 cd m -2 and 42.3 cd A -1 at 5000 cd m -2 with EQE close to 20% indicating low roll-off. Manipulating blue exciplex emissions by chemical structure gives an ideal strategy to fully utilize all exciton energies for lighting of OLEDs.

High Efficiency Colloidal Quantum Dot Phosphors

Energy Technology Data Exchange (ETDEWEB)

Kahen, Keith

2013-12-31

The project showed that non-Cd containing, InP-based nanocrystals (semiconductor materials with dimensions of ~6 nm) have high potential for enabling next-generation, nanocrystal-based, on chip phosphors for solid state lighting. Typical nanocrystals fall short of the requirements for on chip phosphors due to their loss of quantum efficiency under the operating conditions of LEDs, such as, high temperature (up to 150 °C) and high optical flux (up to 200 W/cm2). The InP-based nanocrystals invented during this project maintain high quantum efficiency (>80%) in polymer-based films under these operating conditions for emission wavelengths ranging from ~530 to 620 nm. These nanocrystals also show other desirable attributes, such as, lack of blinking (a common problem with nanocrystals which limits their performance) and no increase in the emission spectral width from room to 150 °C (emitters with narrower spectral widths enable higher efficiency LEDs). Prior to these nanocrystals, no nanocrystal system (regardless of nanocrystal type) showed this collection of properties; in fact, other nanocrystal systems are typically limited to showing only one desirable trait (such as high temperature stability) but being deficient in other properties (such as high flux stability). The project showed that one can reproducibly obtain these properties by generating a novel compositional structure inside of the nanomaterials; in addition, the project formulated an initial theoretical framework linking the compositional structure to the list of high performance optical properties. Over the course of the project, the synthetic methodology for producing the novel composition was evolved to enable the synthesis of these nanomaterials at a cost approximately equal to that required for forming typical conventional nanocrystals. Given the above results, the last major remaining step prior to scale up of the nanomaterials is to limit the oxidation of these materials during the tens of

Axisymmetric alternating direction explicit scheme for efficient coupled simulation of hydro-mechanical interaction in geotechnical engineering—Application to circular footing and deep tunnel in saturated ground

Directory of Open Access Journals (Sweden)

Simon Heru Prassetyo

2018-04-01

Full Text Available Explicit solution techniques have been widely used in geotechnical engineering for simulating the coupled hydro-mechanical (H-M interaction of fluid flow and deformation induced by structures built above and under saturated ground, i.e. circular footing and deep tunnel. However, the technique is only conditionally stable and requires small time steps, portending its inefficiency for simulating large-scale H-M problems. To improve its efficiency, the unconditionally stable alternating direction explicit (ADE scheme could be used to solve the flow problem. The standard ADE scheme, however, is only moderately accurate and is restricted to uniform grids and plane strain flow conditions. This paper aims to remove these drawbacks by developing a novel high-order ADE scheme capable of solving flow problems in non-uniform grids and under axisymmetric conditions. The new scheme is derived by performing a fourth-order finite difference (FD approximation to the spatial derivatives of the axisymmetric fluid–diffusion equation in a non-uniform grid configuration. The implicit Crank-Nicolson technique is then applied to the resulting approximation, and the subsequent equation is split into two alternating direction sweeps, giving rise to a new axisymmetric ADE scheme. The pore pressure solutions from the new scheme are then sequentially coupled with an existing geomechanical simulator in the computer code fast Lagrangian analysis of continua (FLAC. This coupling procedure is called the sequentially-explicit coupling technique based on the fourth-order axisymmetric ADE scheme or SEA-4-AXI. Application of SEA-4-AXI for solving axisymmetric consolidation of a circular footing and of advancing tunnel in deep saturated ground shows that SEA-4-AXI reduces computer runtime up to 42%–50% that of FLAC's basic scheme without numerical instability. In addition, it produces high numerical accuracy of the H-M solutions with average percentage difference of only 0.5%�

Effectiveness of deep cleaning followed by hydrogen peroxide decontamination during high Clostridium difficile infection incidence.

Science.gov (United States)

Best, E L; Parnell, P; Thirkell, G; Verity, P; Copland, M; Else, P; Denton, M; Hobson, R P; Wilcox, M H

2014-05-01

Clostridium difficile infection (CDI) remains an infection control challenge, especially when environmental spore contamination and suboptimal cleaning may increase transmission risk. To substantiate the long-term effectiveness throughout a stroke rehabilitation unit (SRU) of deep cleaning and hydrogen peroxide decontamination (HPD), following a high incidence of CDI. Extensive environmental sampling (342 sites on each occasion) for C. difficile using sponge wipes was performed: before and after deep cleaning with detergent/chlorine agent; immediately following HPD; and on two further occasions, 19 days and 20 weeks following HPD. C. difficile isolates underwent polymerase chain reaction ribotyping and multi-locus variable repeat analysis (MLVA). C. difficile was recovered from 10.8%, 6.1%, 0.9%, 0% and 3.5% of sites at baseline, following deep cleaning, immediately after HPD, and 19 days and 20 weeks after HPD, respectively. C. difficile ribotypes recovered after deep cleaning matched those from CDI cases in the SRU during the previous 10 months. Similarly, 10/12 of the positive sites identified at 20 weeks post-HPD harboured the same C. difficile ribotype (002) and MLVA pattern as the isolate from the first post-HPD CDI case. CDI incidence [number of cases on SRU per 10 months (January-October 2011)] declined from 20 before to seven after the intervention. HPD, after deep cleaning with a detergent/chlorine agent, was highly effective for removing environmental C. difficile contamination. Long-term follow-up demonstrated that a CDI symptomatic patient can rapidly recontaminate the immediate environment. Determining a role for HPD should include long-term cost-effectiveness evaluations. Copyright © 2014 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

Science.gov (United States)

Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The

Nitrogen Fertilizer Deep Placement for Increased Grain Yield and Nitrogen Recovery Efficiency in Rice Grown in Subtropical China

Directory of Open Access Journals (Sweden)

Meng Wu

2017-07-01

Full Text Available Field plot experiments were conducted over 3 years (from April 2014 to November 2016 in a double-rice (Oryza sativa L. cropping system in subtropical China to evaluate the effects of N fertilizer placement on grain yield and N recovery efficiency (NRE. Different N application methods included: no N application (CK; N broadcast application (NBP; N and NPK deep placement (NDP and NPKDP, respectively. Results showed that grain yield and apparent NRE significantly increased for NDP and NPKDP as compared to NBP. The main reason was that N deep placement (NDP increased the number of productive panicle per m-2. To further evaluate the increase, a pot experiment was conducted to understand the N supply in different soil layers in NDP during the whole rice growing stage and a 15N tracing technique was used in a field experiment to investigate the fate of urea-15N in the rice–soil system during rice growth and at maturity. The pot experiment indicated that NDP could maintain a higher N supply in deep soil layers than N broadcast for 52 days during rice growth. The 15N tracing study showed that NDP could maintain much higher fertilizer N in the 5–20 cm soil layer during rice growth and could induce plant to absorb more N from fertilizer and soil than NBP, which led to higher NRE. One important finding was that NDP and NPKDP significantly increased fertilizer NRE but did not lead to N declined in soil compared to NBP. Compared to NPK, NPKDP induced rice plants to absorb more fertilizer N rather than soil N.

Highly efficient fully transparent inverted OLEDs

Science.gov (United States)

Meyer, J.; Winkler, T.; Hamwi, S.; Schmale, S.; Kröger, M.; Görrn, P.; Johannes, H.-H.; Riedl, T.; Lang, E.; Becker, D.; Dobbertin, T.; Kowalsky, W.

2007-09-01

One of the unique selling propositions of OLEDs is their potential to realize highly transparent devices over the visible spectrum. This is because organic semiconductors provide a large Stokes-Shift and low intrinsic absorption losses. Hence, new areas of applications for displays and ambient lighting become accessible, for instance, the integration of OLEDs into the windshield or the ceiling of automobiles. The main challenge in the realization of fully transparent devices is the deposition of the top electrode. ITO is commonly used as transparent bottom anode in a conventional OLED. To obtain uniform light emission over the entire viewing angle and a low series resistance, a TCO such as ITO is desirable as top contact as well. However, sputter deposition of ITO on top of organic layers causes damage induced by high energetic particles and UV radiation. We have found an efficient process to protect the organic layers against the ITO rf magnetron deposition process of ITO for an inverted OLED (IOLED). The inverted structure allows the integration of OLEDs in more powerful n-channel transistors used in active matrix backplanes. Employing the green electrophosphorescent material Ir(ppy) 3 lead to IOLED with a current efficiency of 50 cd/A and power efficiency of 24 lm/W at 100 cd/m2. The average transmittance exceeds 80 % in the visible region. The on-set voltage for light emission is lower than 3 V. In addition, by vertical stacking we achieved a very high current efficiency of more than 70 cd/A for transparent IOLED.

High efficiency lithium-thionyl chloride cell

Science.gov (United States)

Doddapaneni, N.

1982-08-01

The polarization characteristics and the specific cathode capacity of Teflon bonded carbon electrodes in the Li/SOCl2 system have been evaluated. Doping of electrocatalysts such as cobalt and iron phthalocyanine complexes improved both cell voltage and cell rate capability. High efficiency Li/SOCl2 cells were thus achieved with catalyzed cathodes. The electrochemical reduction of SOCl2 seems to undergo modification at catalyzed cathode. For example, the reduction of SOCl2 at FePc catalyzed cathode involves 2-1/2 e-/mole of SOCl2. Furthermore, the reduction mechanism is simplified and unwanted chemical species are eliminated by the catalyst. Thus a potentially safer high efficiency Li/SOCl2 can be anticipated.

Explorations on High Dimensional Landscapes: Spin Glasses and Deep Learning

Science.gov (United States)

Sagun, Levent

This thesis deals with understanding the structure of high-dimensional and non-convex energy landscapes. In particular, its focus is on the optimization of two classes of functions: homogeneous polynomials and loss functions that arise in machine learning. In the first part, the notion of complexity of a smooth, real-valued function is studied through its critical points. Existing theoretical results predict that certain random functions that are defined on high dimensional domains have a narrow band of values whose pre-image contains the bulk of its critical points. This section provides empirical evidence for convergence of gradient descent to local minima whose energies are near the predicted threshold justifying the existing asymptotic theory. Moreover, it is empirically shown that a similar phenomenon may hold for deep learning loss functions. Furthermore, there is a comparative analysis of gradient descent and its stochastic version showing that in high dimensional regimes the latter is a mere speedup. The next study focuses on the halting time of an algorithm at a given stopping condition. Given an algorithm, the normalized fluctuations of the halting time follow a distribution that remains unchanged even when the input data is sampled from a new distribution. Two qualitative classes are observed: a Gumbel-like distribution that appears in Google searches, human decision times, and spin glasses and a Gaussian-like distribution that appears in conjugate gradient method, deep learning with MNIST and random input data. Following the universality phenomenon, the Hessian of the loss functions of deep learning is studied. The spectrum is seen to be composed of two parts, the bulk which is concentrated around zero, and the edges which are scattered away from zero. Empirical evidence is presented for the bulk indicating how over-parametrized the system is, and for the edges that depend on the input data. Furthermore, an algorithm is proposed such that it would

Offline High pH Reversed-Phase Peptide Fractionation for Deep Phosphoproteome Coverage

DEFF Research Database (Denmark)

Batth, Tanveer S; Olsen, Jesper V

2016-01-01

Protein phosphorylation, a process in which kinases modify serines, threonines, and tyrosines with phosphoryl groups is of major importance in eukaryotic biology. Protein phosphorylation events are key initiators of signaling responses which determine cellular outcomes after environmental...... and metabolic stimuli, and are thus highly regulated. Therefore, studying the mechanism of regulation by phosphorylation, and pinpointing the exact site of phosphorylation on proteins is of high importance. This protocol describes in detail a phosphoproteomics workflow for ultra-deep coverage by fractionating...

miRBase: annotating high confidence microRNAs using deep sequencing data.

Science.gov (United States)

Kozomara, Ana; Griffiths-Jones, Sam

2014-01-01

We describe an update of the miRBase database (http://www.mirbase.org/), the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.mirbase.org/. We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.

Focused Crawling of the Deep Web Using Service Class Descriptions

Energy Technology Data Exchange (ETDEWEB)

Rocco, D; Liu, L; Critchlow, T

2004-06-21

Dynamic Web data sources--sometimes known collectively as the Deep Web--increase the utility of the Web by providing intuitive access to data repositories anywhere that Web access is available. Deep Web services provide access to real-time information, like entertainment event listings, or present a Web interface to large databases or other data repositories. Recent studies suggest that the size and growth rate of the dynamic Web greatly exceed that of the static Web, yet dynamic content is often ignored by existing search engine indexers owing to the technical challenges that arise when attempting to search the Deep Web. To address these challenges, we present DynaBot, a service-centric crawler for discovering and clustering Deep Web sources offering dynamic content. DynaBot has three unique characteristics. First, DynaBot utilizes a service class model of the Web implemented through the construction of service class descriptions (SCDs). Second, DynaBot employs a modular, self-tuning system architecture for focused crawling of the DeepWeb using service class descriptions. Third, DynaBot incorporates methods and algorithms for efficient probing of the Deep Web and for discovering and clustering Deep Web sources and services through SCD-based service matching analysis. Our experimental results demonstrate the effectiveness of the service class discovery, probing, and matching algorithms and suggest techniques for efficiently managing service discovery in the face of the immense scale of the Deep Web.

Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters

Directory of Open Access Journals (Sweden)

Yongyang Xu

2018-01-01

Full Text Available Very high resolution (VHR remote sensing imagery has been used for land cover classification, and it tends to a transition from land-use classification to pixel-level semantic segmentation. Inspired by the recent success of deep learning and the filter method in computer vision, this work provides a segmentation model, which designs an image segmentation neural network based on the deep residual networks and uses a guided filter to extract buildings in remote sensing imagery. Our method includes the following steps: first, the VHR remote sensing imagery is preprocessed and some hand-crafted features are calculated. Second, a designed deep network architecture is trained with the urban district remote sensing image to extract buildings at the pixel level. Third, a guided filter is employed to optimize the classification map produced by deep learning; at the same time, some salt-and-pepper noise is removed. Experimental results based on the Vaihingen and Potsdam datasets demonstrate that our method, which benefits from neural networks and guided filtering, achieves a higher overall accuracy when compared with other machine learning and deep learning methods. The method proposed shows outstanding performance in terms of the building extraction from diversified objects in the urban district.

Medium Deep High Temperature Heat Storage

Science.gov (United States)

Bär, Kristian; Rühaak, Wolfram; Schulte, Daniel; Welsch, Bastian; Chauhan, Swarup; Homuth, Sebastian; Sass, Ingo

2015-04-01

Heating of buildings requires more than 25 % of the total end energy consumption in Germany. Shallow geothermal systems for indirect use as well as shallow geothermal heat storage systems like aquifer thermal energy storage (ATES) or borehole thermal energy storage (BTES) typically provide low exergy heat. The temperature levels and ranges typically require a coupling with heat pumps. By storing hot water from solar panels or thermal power stations with temperatures of up to 110 °C a medium deep high temperature heat storage (MDHTS) can be operated on relatively high temperature levels of more than 45 °C. Storage depths of 500 m to 1,500 m below surface avoid conflicts with groundwater use for drinking water or other purposes. Permeability is typically also decreasing with greater depth; especially in the crystalline basement therefore conduction becomes the dominant heat transport process. Solar-thermal charging of a MDHTS is a very beneficial option for supplying heat in urban and rural systems. Feasibility and design criteria of different system configurations (depth, distance and number of BHE) are discussed. One system is designed to store and supply heat (300 kW) for an office building. The required boreholes are located in granodioritic bedrock. Resulting from this setup several challenges have to be addressed. The drilling and completion has to be planned carefully under consideration of the geological and tectonical situation at the specific site.

Super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging

Science.gov (United States)

Wei, Lu; Zhu, Xinxin; Chen, Zhixing; Min, Wei

2014-02-01

Two-photon excited fluorescence microscopy (TPFM) offers the highest penetration depth with subcellular resolution in light microscopy, due to its unique advantage of nonlinear excitation. However, a fundamental imaging-depth limit, accompanied by a vanishing signal-to-background contrast, still exists for TPFM when imaging deep into scattering samples. Formally, the focusing depth, at which the in-focus signal and the out-of-focus background are equal to each other, is defined as the fundamental imaging-depth limit. To go beyond this imaging-depth limit of TPFM, we report a new class of super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging, including multiphoton activation and imaging (MPAI) harnessing novel photo-activatable fluorophores, stimulated emission reduced fluorescence (SERF) microscopy by adding a weak laser beam for stimulated emission, and two-photon induced focal saturation imaging with preferential depletion of ground-state fluorophores at focus. The resulting image contrasts all exhibit a higher-order (third- or fourth- order) nonlinear signal dependence on laser intensity than that in the standard TPFM. Both the physical principles and the imaging demonstrations will be provided for each super-nonlinear microscopy. In all these techniques, the created super-nonlinearity significantly enhances the imaging contrast and concurrently extends the imaging depth-limit of TPFM. Conceptually different from conventional multiphoton processes mediated by virtual states, our strategy constitutes a new class of fluorescence microscopy where high-order nonlinearity is mediated by real population transfer.

Ship detection in optical remote sensing images based on deep convolutional neural networks

Science.gov (United States)

Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Zhao, Danpei; Cai, Bowen

2017-10-01

Automatic ship detection in optical remote sensing images has attracted wide attention for its broad applications. Major challenges for this task include the interference of cloud, wave, wake, and the high computational expenses. We propose a fast and robust ship detection algorithm to solve these issues. The framework for ship detection is designed based on deep convolutional neural networks (CNNs), which provide the accurate locations of ship targets in an efficient way. First, the deep CNN is designed to extract features. Then, a region proposal network (RPN) is applied to discriminate ship targets and regress the detection bounding boxes, in which the anchors are designed by intrinsic shape of ship targets. Experimental results on numerous panchromatic images demonstrate that, in comparison with other state-of-the-art ship detection methods, our method is more efficient and achieves higher detection accuracy and more precise bounding boxes in different complex backgrounds.

Large area flexible polymer solar cells with high efficiency enabled by imprinted Ag grid and modified buffer layer

International Nuclear Information System (INIS)

Lu, Shudi; Lin, Jie; Liu, Kong; Yue, Shizhong; Ren, Kuankuan; Tan, Furui; Wang, Zhijie; Jin, Peng; Qu, Shengchun; Wang, Zhanguo

2017-01-01

To take a full advantage of polymer semiconductors on realization of large-area flexible photovoltaic devices, herein, we fabricate polymer solar cells on the basis of polyethylene terephthalate (PET) with imprinted Ag grid as transparent electrode. The key fabrication procedure is the adoption of a modified PEDOT:PSS (PH1000) solution for spin-coating the buffer layer to form a compact contact with the substrate. In comparison with the devices with intrinsic PEDOT:PSS buffer layer, the advanced devices present a much higher efficiency of 6.51%, even in a large device area of 2.25 cm"2. Subsequent characterizations reveal that such devices show an impressive performance stability as the bending angle is enlarged to 180° and bending time is up to 1000 cycles. Not only providing a general methodology to construct high efficient and flexible polymer solar cells, this paper also involves deep insights on device working mechanism in bending conditions.

Measure Guideline. High Efficiency Natural Gas Furnaces

Energy Technology Data Exchange (ETDEWEB)

Brand, L. [Partnership for Advanced Residential Retrofit (PARR), Des Plaines, IL (United States); Rose, W. [Partnership for Advanced Residential Retrofit (PARR), Des Plaines, IL (United States)

2012-10-01

This measure guideline covers installation of high-efficiency gas furnaces, including: when to install a high-efficiency gas furnace as a retrofit measure; how to identify and address risks; and the steps to be used in the selection and installation process. The guideline is written for Building America practitioners and HVAC contractors and installers. It includes a compilation of information provided by manufacturers, researchers, and the Department of Energy as well as recent research results from the Partnership for Advanced Residential Retrofit (PARR) Building America team.

AlN/GaN Digital Alloy for Mid- and Deep-Ultraviolet Optoelectronics.

Science.gov (United States)

Sun, Wei; Tan, Chee-Keong; Tansu, Nelson

2017-09-19

The AlN/GaN digital alloy (DA) is a superlattice-like nanostructure formed by stacking ultra-thin ( ≤ 4 monolayers) AlN barriers and GaN wells periodically. Here we performed a comprehensive study on the electronics and optoelectronics properties of the AlN/GaN DA for mid- and deep-ultraviolet (UV) applications. Our numerical analysis indicates significant miniband engineering in the AlN/GaN DA by tuning the thicknesses of AlN barriers and GaN wells, so that the effective energy gap can be engineered from ~3.97 eV to ~5.24 eV. The band structure calculation also shows that the valence subbands of the AlN/GaN DA is properly rearranged leading to the heavy-hole (HH) miniband being the top valence subband, which results in the desired transverse-electric polarized emission. Furthermore, our study reveals that the electron-hole wavefunction overlaps in the AlN/GaN DA structure can be remarkably enhanced up to 97% showing the great potential of improving the internal quantum efficiency for mid- and deep-UV device application. In addition, the optical absorption properties of the AlN/GaN DA are analyzed with wide spectral coverage and spectral tunability in mid- and deep-UV regime. Our findings suggest the potential of implementing the AlN/GaN DA as a promising active region design for high efficiency mid- and deep-UV device applications.

Highly Efficient Estimators of Multivariate Location with High Breakdown Point

NARCIS (Netherlands)

Lopuhaa, H.P.

1991-01-01

We propose an affine equivariant estimator of multivariate location that combines a high breakdown point and a bounded influence function with high asymptotic efficiency. This proposal is basically a location $M$-estimator based on the observations obtained after scaling with an affine equivariant

Behavior of gasketless deep bed charcoal filters for radioiodine removal in LWR power plants

International Nuclear Information System (INIS)

Wilhelm, J.G.; Deuber, H.; Furrer, J.; Gerlach, K.

1981-01-01

The removal efficiency of radioiodine filters can be affected by mechanical leakage, aging and poisoning, desorption of radioiodine originally removed by the activated carbon and also by the occurrence of penetrating iodine compounds. To provide high decontamination factors only the gasketless deep bed filter type seems to be appropriate. The experience gathered and the data given in this paper are based on the surveillance testing of radioiodine filters in all German nuclear power plants and on laboratory research work which has been done over years to evaluate the operating behavior of deep bed radioiodine filters and to prove their reliability

Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

Fan Hu

2015-11-01

Full Text Available Learning efficient image representations is at the core of the scene classification task of remote sensing imagery. The existing methods for solving the scene classification task, based on either feature coding approaches with low-level hand-engineered features or unsupervised feature learning, can only generate mid-level image features with limited representative ability, which essentially prevents them from achieving better performance. Recently, the deep convolutional neural networks (CNNs, which are hierarchical architectures trained on large-scale datasets, have shown astounding performance in object recognition and detection. However, it is still not clear how to use these deep convolutional neural networks for high-resolution remote sensing (HRRS scene classification. In this paper, we investigate how to transfer features from these successfully pre-trained CNNs for HRRS scene classification. We propose two scenarios for generating image features via extracting CNN features from different layers. In the first scenario, the activation vectors extracted from fully-connected layers are regarded as the final image features; in the second scenario, we extract dense features from the last convolutional layer at multiple scales and then encode the dense features into global image features through commonly used feature coding approaches. Extensive experiments on two public scene classification datasets demonstrate that the image features obtained by the two proposed scenarios, even with a simple linear classifier, can result in remarkable performance and improve the state-of-the-art by a significant margin. The results reveal that the features from pre-trained CNNs generalize well to HRRS datasets and are more expressive than the low- and mid-level features. Moreover, we tentatively combine features extracted from different CNN models for better performance.

Prediction and design of efficient exciplex emitters for high-efficiency, thermally activated delayed-fluorescence organic light-emitting diodes.

Science.gov (United States)

Liu, Xiao-Ke; Chen, Zhan; Zheng, Cai-Jun; Liu, Chuan-Lin; Lee, Chun-Sing; Li, Fan; Ou, Xue-Mei; Zhang, Xiao-Hong

2015-04-08

High-efficiency, thermally activated delayed-fluorescence organic light-emitting diodes based on exciplex emitters are demonstrated. The best device, based on a TAPC:DPTPCz emitter, shows a high external quantum efficiency of 15.4%. Strategies for predicting and designing efficient exciplex emitters are also provided. This approach allow prediction and design of efficient exciplex emitters for achieving high-efficiency organic light-emitting diodes, for future use in displays and lighting applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simple Retrofit High-Efficiency Natural Gas Water Heater Field Test

Energy Technology Data Exchange (ETDEWEB)

Schoenbauer, Ben [NorthernSTAR, St. Paul, MN (United States)

2017-03-01

High-performance water heaters are typically more time consuming and costly to install in retrofit applications, making high performance water heaters difficult to justify economically. However, recent advancements in high performance water heaters have targeted the retrofit market, simplifying installations and reducing costs. Four high efficiency natural gas water heaters designed specifically for retrofit applications were installed in single-family homes along with detailed monitoring systems to characterize their savings potential, their installed efficiencies, and their ability to meet household demands. The water heaters tested for this project were designed to improve the cost-effectiveness and increase market penetration of high efficiency water heaters in the residential retrofit market. The retrofit high efficiency water heaters achieved their goal of reducing costs, maintaining savings potential and installed efficiency of other high efficiency water heaters, and meeting the necessary capacity in order to improve cost-effectiveness. However, the improvements were not sufficient to achieve simple paybacks of less than ten years for the incremental cost compared to a minimum efficiency heater. Significant changes would be necessary to reduce the simple payback to six years or less. Annual energy savings in the range of $200 would also reduce paybacks to less than six years. These energy savings would require either significantly higher fuel costs (greater than $1.50 per therm) or very high usage (around 120 gallons per day). For current incremental costs, the water heater efficiency would need to be similar to that of a heat pump water heater to deliver a six year payback.

Simple Retrofit High-Efficiency Natural Gas Water Heater Field Test

Energy Technology Data Exchange (ETDEWEB)

Schoenbauer, Ben [NorthernSTAR, St. Paul, MN (United States)

2017-03-28

High performance water heaters are typically more time consuming and costly to install in retrofit applications, making high performance water heaters difficult to justify economically. However, recent advancements in high performance water heaters have targeted the retrofit market, simplifying installations and reducing costs. Four high efficiency natural gas water heaters designed specifically for retrofit applications were installed in single-family homes along with detailed monitoring systems to characterize their savings potential, their installed efficiencies, and their ability to meet household demands. The water heaters tested for this project were designed to improve the cost-effectiveness and increase market penetration of high efficiency water heaters in the residential retrofit market. The retrofit high efficiency water heaters achieved their goal of reducing costs, maintaining savings potential and installed efficiency of other high efficiency water heaters, and meeting the necessary capacity in order to improve cost-effectiveness. However, the improvements were not sufficient to achieve simple paybacks of less than ten years for the incremental cost compared to a minimum efficiency heater. Significant changes would be necessary to reduce the simple payback to six years or less. Annual energy savings in the range of $200 would also reduce paybacks to less than six years. These energy savings would require either significantly higher fuel costs (greater than $1.50 per therm) or very high usage (around 120 gallons per day). For current incremental costs, the water heater efficiency would need to be similar to that of a heat pump water heater to deliver a six year payback.

High efficiency carbon nanotube thread antennas

Science.gov (United States)

Amram Bengio, E.; Senic, Damir; Taylor, Lauren W.; Tsentalovich, Dmitri E.; Chen, Peiyu; Holloway, Christopher L.; Babakhani, Aydin; Long, Christian J.; Novotny, David R.; Booth, James C.; Orloff, Nathan D.; Pasquali, Matteo

2017-10-01

Although previous research has explored the underlying theory of high-frequency behavior of carbon nanotubes (CNTs) and CNT bundles for antennas, there is a gap in the literature for direct experimental measurements of radiation efficiency. These measurements are crucial for any practical application of CNT materials in wireless communication. In this letter, we report a measurement technique to accurately characterize the radiation efficiency of λ/4 monopole antennas made from the CNT thread. We measure the highest absolute values of radiation efficiency for CNT antennas of any type, matching that of copper wire. To capture the weight savings, we propose a specific radiation efficiency metric and show that these CNT antennas exceed copper's performance by over an order of magnitude at 1 GHz and 2.4 GHz. We also report direct experimental observation that, contrary to metals, the radiation efficiency of the CNT thread improves significantly at higher frequencies. These results pave the way for practical applications of CNT thread antennas, particularly in the aerospace and wearable electronics industries where weight saving is a priority.

Doping efficiency analysis of highly phosphorous doped epitaxial/amorphous silicon emitters grown by PECVD for high efficiency silicon solar cells

Energy Technology Data Exchange (ETDEWEB)

El-Gohary, H.G.; Sivoththaman, S. [Waterloo Univ., ON (Canada). Dept. of Electrical and Computer Engineering

2008-08-15

The efficient doping of hydrogenated amorphous and crystalline silicon thin films is a key factor in the fabrication of silicon solar cells. The most popular method for developing those films is plasma enhanced chemical vapor deposition (PECVD) because it minimizes defect density and improves doping efficiency. This paper discussed the preparation of different structure phosphorous doped silicon emitters ranging from epitaxial to amorphous films at low temperature. Phosphine (PH{sub 3}) was employed as the doping gas source with the same gas concentration for both epitaxial and amorphous silicon emitters. The paper presented an analysis of dopant activation by applying a very short rapid thermal annealing process (RTP). A spreading resistance profile (SRP) and SIMS analysis were used to detect both the active dopant and the dopant concentrations, respectively. The paper also provided the results of a structural analysis for both bulk and cross-section at the interface using high-resolution transmission electron microscopy and Raman spectroscopy, for epitaxial and amorphous films. It was concluded that a unity doping efficiency could be achieved in epitaxial layers by applying an optimized temperature profile using short time processing rapid thermal processing technique. The high quality, one step epitaxial layers, led to both high conductive and high doping efficiency layers.

Measure Guideline: High Efficiency Natural Gas Furnaces

Energy Technology Data Exchange (ETDEWEB)

Brand, L.; Rose, W.

2012-10-01

This Measure Guideline covers installation of high-efficiency gas furnaces. Topics covered include when to install a high-efficiency gas furnace as a retrofit measure, how to identify and address risks, and the steps to be used in the selection and installation process. The guideline is written for Building America practitioners and HVAC contractors and installers. It includes a compilation of information provided by manufacturers, researchers, and the Department of Energy as well as recent research results from the Partnership for Advanced Residential Retrofit (PARR) Building America team.

Innovative-Simplified Nuclear Power Plant Efficiency Evaluation with High-Efficiency Steam Injector System

International Nuclear Information System (INIS)

Shoji, Goto; Shuichi, Ohmori; Michitsugu, Mori

2006-01-01

It is possible to establish simplified system with reduced space and total equipment weight using high-efficiency Steam Injectors (SI) instead of low-pressure feedwater heaters in Nuclear Power Plant (NPP). The SI works as a heat exchanger through direct contact between feedwater from condensers and extracted steam from turbines. It can get higher pressure than supplied steam pressure. The maintenance and reliability are still higher than the feedwater ones because SI has no movable parts. This paper describes the analysis of the heat balance, plant efficiency and the operation of this Innovative-Simplified NPP with high-efficiency SI. The plant efficiency and operation are compared with the electric power of 1100 MWe-class BWR system and the Innovative-Simplified BWR system with SI. The SI model is adapted into the heat balance simulator with a simplified model. The results show that plant efficiencies of the Innovated-Simplified BWR system are almost equal to original BWR ones. The present research is one of the projects that are carried out by Tokyo Electric Power Company, Toshiba Corporation, and six Universities in Japan, funded from the Institute of Applied Energy (IAE) of Japan as the national public research-funded program. (authors)

A recursive Monte Carlo method for estimating importance functions in deep penetration problems

International Nuclear Information System (INIS)

Goldstein, M.

1980-04-01

A pratical recursive Monte Carlo method for estimating the importance function distribution, aimed at importance sampling for the solution of deep penetration problems in three-dimensional systems, was developed. The efficiency of the recursive method was investigated for sample problems including one- and two-dimensional, monoenergetic and and multigroup problems, as well as for a practical deep-penetration problem with streaming. The results of the recursive Monte Carlo calculations agree fairly well with Ssub(n) results. It is concluded that the recursive Monte Carlo method promises to become a universal method for estimating the importance function distribution for the solution of deep-penetration problems, in all kinds of systems: for many systems the recursive method is likely to be more efficient than previously existing methods; for three-dimensional systems it is the first method that can estimate the importance function with the accuracy required for an efficient solution based on importance sampling of neutron deep-penetration problems in those systems

Deep Eutectic Solvents as Efficient Media for the Extraction and Recovery of Cynaropicrin from Cynara cardunculus L. Leaves.

Science.gov (United States)

de Faria, Emanuelle L P; do Carmo, Rafael S; Cláudio, Ana Filipa M; Freire, Carmen S R; Freire, Mara G; Silvestre, Armando J D

2017-10-30

In recent years a high demand for natural ingredients with nutraceutical properties has been witnessed, for which the development of more environmentally-friendly and cost-efficient extraction solvents and methods play a primary role. In this perspective, in this work, the application of deep eutectic solvents (DES), composed of quaternary ammonium salts and organic acids, as alternative solvents for the extraction of cynaropicrin from Cynara cardunculus L. leaves was studied. After selecting the most promising DES, their aqueous solutions were investigated, allowing to obtain a maximum cynaropicrin extraction yield of 6.20 wt %, using 70 wt % of water. The sustainability of the extraction process was further optimized by carrying out several extraction cycles, reusing either the biomass or the aqueous solutions of DES. A maximum cynaropicrin extraction yield of 7.76 wt % by reusing the solvent, and of 8.96 wt % by reusing the biomass, have been obtained. Taking advantage of the cynaropicrin solubility limit in aqueous solutions, water was added as an anti-solvent, allowing to recover 73.6 wt % of the extracted cynaropicrin. This work demonstrates the potential of aqueous solutions of DES for the extraction of value-added compounds from biomass and the possible recovery of both the target compounds and solvents.

Sleep Quality Prediction From Wearable Data Using Deep Learning.

Science.gov (United States)

Sathyanarayana, Aarti; Joty, Shafiq; Fernandez-Luque, Luis; Ofli, Ferda; Srivastava, Jaideep; Elmagarmid, Ahmed; Arora, Teresa; Taheri, Shahrad

2016-11-04

The importance of sleep is paramount to health. Insufficient sleep can reduce physical, emotional, and mental well-being and can lead to a multitude of health complications among people with chronic conditions. Physical activity and sleep are highly interrelated health behaviors. Our physical activity during the day (ie, awake time) influences our quality of sleep, and vice versa. The current popularity of wearables for tracking physical activity and sleep, including actigraphy devices, can foster the development of new advanced data analytics. This can help to develop new electronic health (eHealth) applications and provide more insights into sleep science. The objective of this study was to evaluate the feasibility of predicting sleep quality (ie, poor or adequate sleep efficiency) given the physical activity wearable data during awake time. In this study, we focused on predicting good or poor sleep efficiency as an indicator of sleep quality. Actigraphy sensors are wearable medical devices used to study sleep and physical activity patterns. The dataset used in our experiments contained the complete actigraphy data from a subset of 92 adolescents over 1 full week. Physical activity data during awake time was used to create predictive models for sleep quality, in particular, poor or good sleep efficiency. The physical activity data from sleep time was used for the evaluation. We compared the predictive performance of traditional logistic regression with more advanced deep learning methods: multilayer perceptron (MLP), convolutional neural network (CNN), simple Elman-type recurrent neural network (RNN), long short-term memory (LSTM-RNN), and a time-batched version of LSTM-RNN (TB-LSTM). Deep learning models were able to predict the quality of sleep (ie, poor or good sleep efficiency) based on wearable data from awake periods. More specifically, the deep learning methods performed better than traditional logistic regression. “CNN had the highest specificity and

Stimulation Technologies for Deep Well Completions

Energy Technology Data Exchange (ETDEWEB)

Stephen Wolhart

2005-06-30

The Department of Energy (DOE) is sponsoring the Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies conducted a study to evaluate the stimulation of deep wells. The objective of the project was to review U.S. deep well drilling and stimulation activity, review rock mechanics and fracture growth in deep, high-pressure/temperature wells and evaluate stimulation technology in several key deep plays. This report documents results from this project.

A Simple and Efficient RNA Extraction Method from Deep-Sea Hydrothermal Vent Chimney Structures.

Science.gov (United States)

Muto, Hisashi; Takaki, Yoshihiro; Hirai, Miho; Mino, Sayaka; Sawayama, Shigeki; Takai, Ken; Nakagawa, Satoshi

2017-12-27

RNA-based microbiological analyses, e.g., transcriptome and reverse transcription-quantitative PCR, require a relatively large amount of high quality RNA. RNA-based analyses on microbial communities in deep-sea hydrothermal environments often encounter methodological difficulties with RNA extraction due to the presence of unique minerals in and the low biomass of samples. In the present study, we assessed RNA extraction methods for deep-sea vent chimneys that had complex mineral compositions. Mineral-RNA adsorption experiments were conducted using mock chimney minerals and Escherichia coli total RNA solution, and showed that detectable RNA significantly decreased possibly due to adsorption onto minerals. This decrease in RNA was prevented by the addition of sodium tripolyphosphate (STPP), deoxynucleotide triphosphates (dNTPs), salmon sperm DNA, and NaOH. The addition of STPP was also effective for RNA extraction from the mixture of E. coli cells and mock chimney minerals when TRIzol reagent and the RNeasy column were used, but not when the RNeasy PowerSoil total RNA kit was used. A combination of STPP, TRIzol reagent, the RNeasy column, and sonication resulted in the highest RNA yield from a natural chimney. This indirect extraction procedure is simple, rapid, inexpensive, and may be used for large-scale RNA extraction.

Energy efficiency indicators for high electric-load buildings

Energy Technology Data Exchange (ETDEWEB)

Aebischer, Bernard; Balmer, Markus A.; Kinney, Satkartar; Le Strat, Pascale; Shibata, Yoshiaki; Varone, Frederic

2003-06-01

Energy per unit of floor area is not an adequate indicator for energy efficiency in high electric-load buildings. For two activities, restaurants and computer centres, alternative indicators for energy efficiency are discussed.

Albedo Neutron Dosimetry in a Deep Geological Disposal Repository for High-Level Nuclear Waste.

Science.gov (United States)

Pang, Bo; Becker, Frank

2017-04-28

Albedo neutron dosemeter is the German official personal neutron dosemeter in mixed radiation fields where neutrons contribute to personal dose. In deep geological repositories for high-level nuclear waste, where neutrons can dominate the radiation field, it is of interest to investigate the performance of albedo neutron dosemeter in such facilities. In this study, the deep geological repository is represented by a shielding cask loaded with spent nuclear fuel placed inside a rock salt emplacement drift. Due to the backscattering of neutrons in the drift, issues concerning calibration of the dosemeter arise. Field-specific calibration of the albedo neutron dosemeter was hence performed with Monte Carlo simulations. In order to assess the applicability of the albedo neutron dosemeter in a deep geological repository over a long time scale, spent nuclear fuel with different ages of 50, 100 and 500 years were investigated. It was found out, that the neutron radiation field in a deep geological repository can be assigned to the application area 'N1' of the albedo neutron dosemeter, which is typical in reactors and accelerators with heavy shielding. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

High Efficiency Centrifugal Compressor for Rotorcraft Applications

Science.gov (United States)

Medic, Gorazd; Sharma, Om P.; Jongwook, Joo; Hardin, Larry W.; McCormick, Duane C.; Cousins, William T.; Lurie, Elizabeth A.; Shabbir, Aamir; Holley, Brian M.; Van Slooten, Paul R.

2017-01-01

A centrifugal compressor research effort conducted by United Technologies Research Center under NASA Research Announcement NNC08CB03C is documented. The objectives were to identify key technical barriers to advancing the aerodynamic performance of high-efficiency, high work factor, compact centrifugal compressor aft-stages for turboshaft engines; to acquire measurements needed to overcome the technical barriers and inform future designs; to design, fabricate, and test a new research compressor in which to acquire the requisite flow field data. A new High-Efficiency Centrifugal Compressor stage -- splittered impeller, splittered diffuser, 90 degree bend, and exit guide vanes -- with aerodynamically aggressive performance and configuration (compactness) goals were designed, fabricated, and subquently tested at the NASA Glenn Research Center.

Deep Belief Nets for Topic Modeling

DEFF Research Database (Denmark)

Maaløe, Lars; Arngren, Morten; Winther, Ole

2015-01-01

-formative. In this paper we describe large-scale content based collaborative filtering for digital publishing. To solve the digital publishing recommender problem we compare two approaches: latent Dirichlet allocation (LDA) and deep be-lief nets (DBN) that both find low-dimensional latent representations for documents....... Efficient retrieval can be carried out in the latent representation. We work both on public benchmarks and digital media content provided by Issuu, an on-line publishing platform. This article also comes with a newly developed deep belief nets toolbox for topic modeling tailored towards performance...

Quasi-kinoform type multilayer zone plate with high diffraction efficiency for high-energy X-rays

International Nuclear Information System (INIS)

Tamura, S; Yasumoto, M; Kamijo, N; Uesugi, K; Takeuchi, A; Terada, Y; Suzuki, Y

2009-01-01

Fresnel zone plate (FZP) with high diffraction efficiency leads to high performance X-ray microscopy with the reduction of the radiation damage to biological specimens. In order to attain high diffraction efficiency in high energy X-ray region, we have developed multilevel-type (6-step) multilayer FZPs with the diameter of 70 micron. The efficiencies of two FZPs were evaluated at the BL20XU beamline of SPring-8. For one FZP, the peak efficiency for the 1st-order diffraction of 51% has been obtained at 70 keV. The efficiencies higher than 40% have been achieved in the wide energy range of 70-90 keV. That for the 2nd-order diffraction of 46% has been obtained at 37.5 keV.

High-efficiency organic glass scintillators

Science.gov (United States)

Feng, Patrick L.; Carlson, Joseph S.

2017-12-19

A new family of neutron/gamma discriminating scintillators is disclosed that comprises stable organic glasses that may be melt-cast into transparent monoliths. These materials have been shown to provide light yields greater than solution-grown trans-stilbene crystals and efficient PSD capabilities when combined with 0.01 to 0.05% by weight of the total composition of a wavelength-shifting fluorophore. Photoluminescence measurements reveal fluorescence quantum yields that are 2 to 5 times greater than conventional plastic or liquid scintillator matrices, which accounts for the superior light yield of these glasses. The unique combination of high scintillation light-yields, efficient neutron/gamma PSD, and straightforward scale-up via melt-casting distinguishes the developed organic glasses from existing scintillators.

Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance

International Nuclear Information System (INIS)

Lee, Sang Hoon; Hong, Tianzhen; Piette, Mary Ann; Sawaya, Geof; Chen, Yixing; Taylor-Lange, Sarah C.

2015-01-01

Small and medium-sized commercial buildings can be retrofitted to significantly reduce their energy use, however it is a huge challenge as owners usually lack of the expertise and resources to conduct detailed on-site energy audit to identify and evaluate cost-effective energy technologies. This study presents a DEEP (database of energy efficiency performance) that provides a direct resource for quick retrofit analysis of commercial buildings. DEEP, compiled from the results of about ten million EnergyPlus simulations, enables an easy screening of ECMs (energy conservation measures) and retrofit analysis. The simulations utilize prototype models representative of small and mid-size offices and retails in California climates. In the formulation of DEEP, large scale EnergyPlus simulations were conducted on high performance computing clusters to evaluate hundreds of individual and packaged ECMs covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and service hot water. The architecture and simulation environment to create DEEP is flexible and can expand to cover additional building types, additional climates, and new ECMs. In this study DEEP is integrated into a web-based retrofit toolkit, the Commercial Building Energy Saver, which provides a platform for energy retrofit decision making by querying DEEP and unearthing recommended ECMs, their estimated energy savings and financial payback. - Highlights: • A DEEP (database of energy efficiency performance) supports building retrofit. • DEEP is an SQL database with pre-simulated results from 10 million EnergyPlus runs. • DEEP covers 7 building types, 6 vintages, 16 climates, and 100 energy measures. • DEEP accelerates retrofit of small commercial buildings to save energy use and cost. • DEEP can be expanded and integrated with third-party energy software tools.

The thermodynamic characteristics of high efficiency, internal-combustion engines

International Nuclear Information System (INIS)

Caton, Jerald A.

2012-01-01

Highlights: ► The thermodynamics of an automotive engine are determined using a cycle simulation. ► The net indicated thermal efficiency increased from 37.0% to 53.9%. ► High compression ratio, lean mixtures and high EGR were the important features. ► Efficiency increased due to lower heat losses, and increased work conversion. ► The nitric oxides were essentially zero due to the low combustion temperatures. - Abstract: Recent advancements have demonstrated new combustion modes for internal combustion engines that exhibit low nitric oxide emissions and high thermal efficiencies. These new combustion modes involve various combinations of stratification, lean mixtures, high levels of EGR, multiple injections, variable valve timings, two fuels, and other such features. Although the exact combination of these features that provides the best design is not yet clear, the results (low emissions with high efficiencies) are of major interest. The current work is directed at determining some of the fundamental thermodynamic reasons for the relatively high efficiencies and to quantify these factors. Both the first and second laws are used in this assessment. An automotive engine (5.7 l) which included some of the features mentioned above (e.g., high compression ratios, lean mixtures, and high EGR) was evaluated using a thermodynamic cycle simulation. These features were examined for a moderate load (bmep = 900 kPa), moderate speed (2000 rpm) condition. By the use of lean operation, high EGR levels, high compression ratio and other features, the net indicated thermal efficiency increased from 37.0% to 53.9%. These increases are explained in a step-by-step fashion. The major reasons for these improvements include the higher compression ratio and the dilute charge (lean mixture, high EGR). The dilute charge resulted in lower temperatures which in turn resulted in lower heat loss. In addition, the lower temperatures resulted in higher ratios of the specific heats which

Experiments on high efficiency aerosol filtration

International Nuclear Information System (INIS)

Mazzini, M.; Cuccuru, A.; Kunz, P.

1977-01-01

Research on high efficiency aerosol filtration by the Nuclear Engineering Institute of Pisa University and by CAMEN in collaboration with CNEN is outlined. HEPA filter efficiency was studied as a function of the type and size of the test aerosol, and as a function of flowrate (+-50% of the nominal value), air temperature (up to 70 0 C), relative humidity (up to 100%), and durability in a corrosive atmosphere (up to 140 hours in NaCl mist). In the selected experimental conditions these influences were appreciable but are not sufficient to be significant in industrial HEPA filter applications. Planned future research is outlined: measurement of the efficiency of two HEPA filters in series using a fixed particle size; dependence of the efficiency on air, temperatures up to 300-500 0 C; performance when subject to smoke from burning organic materials (natural rubber, neoprene, miscellaneous plastics). Such studies are relevant to possible accidental fires in a plutonium laboratory

Performance of a high efficiency high power UHF klystron

International Nuclear Information System (INIS)

Konrad, G.T.

1977-03-01

A 500 kW c-w klystron was designed for the PEP storage ring at SLAC. The tube operates at 353.2 MHz, 62 kV, a microperveance of 0.75, and a gain of approximately 50 dB. Stable operation is required for a VSWR as high as 2 : 1 at any phase angle. The design efficiency is 70%. To obtain this value of efficiency, a second harmonic cavity is used in order to produce a very tightly bunched beam in the output gap. At the present time it is planned to install 12 such klystrons in PEP. A tube with a reduced size collector was operated at 4% duty at 500 kW. An efficiency of 63% was observed. The same tube was operated up to 200 kW c-w for PEP accelerator cavity tests. A full-scale c-w tube reached 500 kW at 65 kV with an efficiency of 55%. In addition to power and phase measurements into a matched load, some data at various load mismatches are presented

Precision-cut liver slices to investigate responsiveness of deep-sea fish to contaminants at high pressure.

Science.gov (United States)

Lemaire, Benjamin; Debier, Cathy; Calderon, Pedro Buc; Thomé, Jean Pierre; Stegeman, John; Mork, Jarle; Rees, Jean François

2012-09-18

While deep-sea fish accumulate high levels of persistent organic pollutants (POPs), the toxicity associated with this contamination remains unknown. Indeed, the recurrent collection of moribund individuals precludes experimental studies to investigate POP effects in this fauna. We show that precision-cut liver slices (PCLS), an in vitro tool commonly used in human and rodent toxicology, can overcome such limitation. This technology was applied to individuals of the deep-sea grenadier Coryphaenoides rupestris directly upon retrieval from 530-m depth in Trondheimsfjord (Norway). PCLS remained viable and functional for 15 h when maintained in an appropriate culture media at 4 °C. This allowed experimental exposure of liver slices to the model POP 3-methylcholanthrene (3-MC; 25 μM) at levels of hydrostatic pressure mimicking shallow (0.1 megapascal or MPa) and deep-sea (5-15 MPa; representative of 500-1500 m depth) environments. As in shallow water fish, 3-MC induced the transcription of the detoxification enzyme cytochrome P4501A (CYP1A; a biomarker of exposure to POPs). This induction was diminished at elevated pressure, suggesting a limited responsiveness of C. rupestris toward POPs in its native environment. This very first in vitro toxicological investigation on a deep-sea fish opens the route for understanding pollutants effects in this highly exposed fauna.

High-speed rupture during the initiation of the 2015 Bonin Islands deep earthquake

Science.gov (United States)

Zhan, Z.; Ye, L.; Shearer, P. M.; Lay, T.; Kanamori, H.

2015-12-01

Among the long-standing questions on how deep earthquakes rupture, the nucleation phase of large deep events is one of the most puzzling parts. Resolving the rupture properties of the initiation phase is difficult to achieve with far-field data because of the need for accurate corrections for structural effects on the waveforms (e.g., attenuation, scattering, and site effects) and alignment errors. Here, taking the 2015 Mw 7.9 Bonin Islands earthquake (depth = 678 km) as an example, we jointly invert its far-field P waves at multiple stations for the average rupture speed during the first second of the event. We use waveforms from a closely located aftershock as empirical Green's functions, and correct for possible differences in focal mechanisms and waveform misalignments with an iterative approach. We find that the average initial rupture speed is over 5 km/s, significantly higher than the average rupture speed of 3 km/s later in the event. This contrast suggests that rupture speeds of deep earthquakes can be highly variable during individual events and may define different stages of rupture, potentially with different mechanisms.

Process development for high-efficiency silicon solar cells

Energy Technology Data Exchange (ETDEWEB)

Gee, J.M.; Basore, P.A.; Buck, M.E.; Ruby, D.S.; Schubert, W.K.; Silva, B.L.; Tingley, J.W.

1991-12-31

Fabrication of high-efficiency silicon solar cells in an industrial environment requires a different optimization than in a laboratory environment. Strategies are presented for process development of high-efficiency silicon solar cells, with a goal of simplifying technology transfer into an industrial setting. The strategies emphasize the use of statistical experimental design for process optimization, and the use of baseline processes and cells for process monitoring and quality control. 8 refs.

Deep learning in TMVA Benchmarking Benchmarking TMVA DNN Integration of a Deep Autoencoder

CERN Document Server

Huwiler, Marc

2017-01-01

The TMVA library in ROOT is dedicated to multivariate analysis, and in partic- ular oers numerous machine learning algorithms in a standardized framework. It is widely used in High Energy Physics for data analysis, mainly to perform regression and classication. To keep up to date with the state of the art in deep learning, a new deep learning module was being developed this summer, oering deep neural net- work, convolutional neural network, and autoencoder. TMVA did not have yet any autoencoder method, and the present project consists in implementing the TMVA autoencoder class based on the deep learning module. It also includes some bench- marking performed on the actual deep neural network implementation, in comparison to the Keras framework with Tensorflow and Theano backend.

Theoretical and experimental fundamentals of designing promising technological equipment to improve efficiency and environmental safety of highly viscous oil recovery from deep oil reservoirs

Science.gov (United States)

Moiseyev, V. A.; Nazarov, V. P.; Zhuravlev, V. Y.; Zhuykov, D. A.; Kubrikov, M. V.; Klokotov, Y. N.

2016-12-01

The development of new technological equipment for the implementation of highly effective methods of recovering highly viscous oil from deep reservoirs is an important scientific and technical challenge. Thermal recovery methods are promising approaches to solving the problem. It is necessary to carry out theoretical and experimental research aimed at developing oil-well tubing (OWT) with composite heatinsulating coatings on the basis of basalt and glass fibers. We used the method of finite element analysis in Nastran software, which implements complex scientific and engineering calculations, including the calculation of the stress-strain state of mechanical systems, the solution of problems of heat transfer, the study of nonlinear static, the dynamic transient analysis of frequency characteristics, etc. As a result, we obtained a mathematical model of thermal conductivity which describes the steady-state temperature and changes in the fibrous highly porous material with the heat loss by Stefan-Boltzmann's radiation. It has been performed for the first time using the method of computer modeling in Nastran software environments. The results give grounds for further implementation of the real design of the OWT when implementing thermal methods for increasing the rates of oil production and mitigating environmental impacts.

Deep Borehole Disposal as an Alternative Concept to Deep Geological Disposal

Energy Technology Data Exchange (ETDEWEB)

Lee, Jongyoul; Lee, Minsoo; Choi, Heuijoo; Kim, Kyungsu [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2016-10-15

In this paper, the general concept and key technologies for deep borehole disposal of spent fuels or HLW, as an alternative method to the mined geological disposal method, were reviewed. After then an analysis on the distance between boreholes for the disposal of HLW was carried out. Based on the results, a disposal area were calculated approximately and compared with that of mined geological disposal. These results will be used as an input for the analyses of applicability for DBD in Korea. The disposal safety of this system has been demonstrated with underground research laboratory and some advanced countries such as Finland and Sweden are implementing their disposal project on commercial stage. However, if the spent fuels or the high-level radioactive wastes can be disposed of in the depth of 3-5 km and more stable rock formation, it has several advantages. Therefore, as an alternative disposal concept to the mined deep geological disposal concept (DGD), very deep borehole disposal (DBD) technology is under consideration in number of countries in terms of its outstanding safety and cost effectiveness. In this paper, the general concept of deep borehole disposal for spent fuels or high level radioactive wastes was reviewed. And the key technologies, such as drilling technology of large diameter borehole, packaging and emplacement technology, sealing technology and performance/safety analyses technologies, and their challenges in development of deep borehole disposal system were analyzed. Also, very preliminary deep borehole disposal concept including disposal canister concept was developed according to the nuclear environment in Korea.

Deep Borehole Disposal as an Alternative Concept to Deep Geological Disposal

International Nuclear Information System (INIS)

Lee, Jongyoul; Lee, Minsoo; Choi, Heuijoo; Kim, Kyungsu

2016-01-01

In this paper, the general concept and key technologies for deep borehole disposal of spent fuels or HLW, as an alternative method to the mined geological disposal method, were reviewed. After then an analysis on the distance between boreholes for the disposal of HLW was carried out. Based on the results, a disposal area were calculated approximately and compared with that of mined geological disposal. These results will be used as an input for the analyses of applicability for DBD in Korea. The disposal safety of this system has been demonstrated with underground research laboratory and some advanced countries such as Finland and Sweden are implementing their disposal project on commercial stage. However, if the spent fuels or the high-level radioactive wastes can be disposed of in the depth of 3-5 km and more stable rock formation, it has several advantages. Therefore, as an alternative disposal concept to the mined deep geological disposal concept (DGD), very deep borehole disposal (DBD) technology is under consideration in number of countries in terms of its outstanding safety and cost effectiveness. In this paper, the general concept of deep borehole disposal for spent fuels or high level radioactive wastes was reviewed. And the key technologies, such as drilling technology of large diameter borehole, packaging and emplacement technology, sealing technology and performance/safety analyses technologies, and their challenges in development of deep borehole disposal system were analyzed. Also, very preliminary deep borehole disposal concept including disposal canister concept was developed according to the nuclear environment in Korea

Development of Deep-tow Autonomous Cable Seismic (ACS) for Seafloor Massive Sulfides (SMSs) Exploration.

Science.gov (United States)

Asakawa, Eiichi; Murakami, Fumitoshi; Tsukahara, Hitoshi; Saito, Shutaro; Lee, Sangkyun; Tara, Kenji; Kato, Masafumi; Jamali Hondori, Ehsan; Sumi, Tomonori; Kadoshima, Kazuyuki; Kose, Masami

2017-04-01

Within the EEZ of Japan, numerous surveys exploring ocean floor resources have been conducted. The exploration targets are gas hydrates, mineral resources (manganese, cobalt or rare earth) and especially seafloor massive sulphide (SMS) deposits. These resources exist in shallow subsurface areas in deep waters (>1500m). For seismic explorations very high resolution images are required. These cannot be effectively obtained with conventional marine seismic techniques. Therefore we have been developing autonomous seismic survey systems which record the data close to the seafloor to preserve high frequency seismic energy. Very high sampling rate (10kHz) and high accurate synchronization between recording systems and shot time are necessary. We adopted Cs-base atomic clock considering its power consumption. At first, we developed a Vertical Cable Seismic (VCS) system that uses hydrophone arrays moored vertically from the ocean bottom to record close to the target area. This system has been successfully applied to SMS exploration. Specifically it fixed over known sites to assess the amount of reserves with the resultant 3D volume. Based on the success of VCS, we modified the VCS system to use as a more efficient deep-tow seismic survey system. Although there are other examples of deep-tow seismic systems, signal transmission cables present challenges in deep waters. We use our autonomous recording system to avoid these problems. Combining a high frequency piezoelectric source (Sub Bottom Profiler:SBP) that automatically shots with a constant interval, we achieve the high resolution deep-tow seismic without data transmission/power cable to the board. Although the data cannot be monitored in real-time, the towing system becomes very simple. We have carried out survey trial, which showed the systems utility as a high-resolution deep-tow seismic survey system. Furthermore, the frequency ranges of deep-towed source (SBP) and surface towed sparker are 700-2300Hz and 10-200Hz

DeepBipolar: Identifying genomic mutations for bipolar disorder via deep learning.

Science.gov (United States)

Laksshman, Sundaram; Bhat, Rajendra Rana; Viswanath, Vivek; Li, Xiaolin

2017-09-01

Bipolar disorder, also known as manic depression, is a brain disorder that affects the brain structure of a patient. It results in extreme mood swings, severe states of depression, and overexcitement simultaneously. It is estimated that roughly 3% of the population of the United States (about 5.3 million adults) suffers from bipolar disorder. Recent research efforts like the Twin studies have demonstrated a high heritability factor for the disorder, making genomics a viable alternative for detecting and treating bipolar disorder, in addition to the conventional lengthy and costly postsymptom clinical diagnosis. Motivated by this study, leveraging several emerging deep learning algorithms, we design an end-to-end deep learning architecture (called DeepBipolar) to predict bipolar disorder based on limited genomic data. DeepBipolar adopts the Deep Convolutional Neural Network (DCNN) architecture that automatically extracts features from genotype information to predict the bipolar phenotype. We participated in the Critical Assessment of Genome Interpretation (CAGI) bipolar disorder challenge and DeepBipolar was considered the most successful by the independent assessor. In this work, we thoroughly evaluate the performance of DeepBipolar and analyze the type of signals we believe could have affected the classifier in distinguishing the case samples from the control set. © 2017 Wiley Periodicals, Inc.

High efficiency confinement mode by electron cyclotron heating

International Nuclear Information System (INIS)

Funahashi, Akimasa

1987-01-01

In the medium size nuclear fusion experiment facility JFT-2M in the Japan Atomic Energy Research Institute, the research on the high efficiency plasma confinement mode has been advanced, and in the experiment in June, 1987, the formation of a high efficiency confinement mode was successfully controlled by electron cyclotron heating, for the first time in the world. This result further advanced the control of the formation of a high efficiency plasma confinement mode and the elucidation of the physical mechanism of that mode, and promoted the research and development of the plasma heating by electron cyclotron heating. In this paper, the recent results of the research on a high efficiency confinement mode at the JFT-2M are reported, and the role of the JFT-2M and the experiment on the improvement of core plasma performance are outlined. Now the plasma temperature exceeding 100 million deg C has been attained in large tokamaks, and in medium size facilities, the various measures for improving confinement performance are to be brought forth and their scientific basis is elucidated to assist large facilities. The JFT-2M started the operation in April, 1983, and has accumulated the results smoothly since then. (Kako, I.)

New High Pressure Phase of CaCO3: Implication for the Deep Diamond Formation

Science.gov (United States)

Mao, Z.; Li, X.; Zhang, Z.; Lin, J. F.; Ni, H.; Prakapenka, V.

2017-12-01

Surface carbon can be transported to the Earth's deep interior through sinking subduction slabs. Carbonates, including CaCO3, MgCO3 and MgCa(CO3)2, are important carbon carriers for the deep carbon cycle. Experimental studies on the phase stability of carbonates with coexisting mantle minerals at relevant pressure and temperature conditions are thus important for understanding the deep carbon cycle. In particular, recent petrological studies have revealed the evidence for the transportation of CaCO3 to the depth at least of the top lower mantle by analyzing the diamond inclusions. Yet the phase stability of CaCO3 at relevant pressure and temperature conditions of the top lower mantle is still unclear. Previous single-crystal study has shown that CaCO3 transforms from the CaCO3-III structure to CaCO3-VI at 15 GPa and 300 K. The CaCO3-VI is stable at least up to 40 GPa at 300 K. At high temperatures, CaCO3 in the aragonite structure will directly transform into the post-aragonite structure at 40 GPa. However, a recent theoretical study predicted a new phase of CaCO3 with a space group of P21/c between 32 and 48 GPa which is different from previous experimental results. In this study, we have investigated the phase stability of CaCO3 at high pressure-temperature conditions using synchrotron X-ray diffraction in laser-heated diamond anvil cells. We report the discovery of a new phase of CaCO3 at relevant pressure-temperature conditions of the top lower mantle which is consistent with previous theoretical predictions. This new phase is an important carrier for the transportation of carbon to the Earth's lower mantle and crucial for growing deep diamonds in the region.

High energy deep inelastic scattering in perturbative quantum chromodynamics

International Nuclear Information System (INIS)

Wallon, S.

1996-01-01

In this PhD thesis, we deal with high energy Deep Inelastic Scattering in Perturbative Quantum Chromodynamics (QCD). In this work, two main topics are emphasized: The first one deals with dynamics based on perturbative renormalization group, and on perturbative Regge approaches. We discuss the applicability of these predictions, the possibility of distinguishing them in the HERA experiments, and their unification. We prove that the perturbative Regge dynamic can be successfully applied to describe the HERA data. Different observables are proposed for distinguishing these two approaches. We show that these two predictions can be unified in a system of equations. In the second one, unitarization and saturation problems in high energy QCD are discussed. In the multi-Regge approach, equivalent to the integrable one-dimensional XXX Heisenberg spin chain, we develop methods in order to solve this system, based on the Functional Bethe Ansatz. In the dipole model context, we propose a new formulation of unitarity and saturation effects, using Wilson loops. (author)

High-Order Dielectric Metasurfaces for High-Efficiency Polarization Beam Splitters and Optical Vortex Generators

Science.gov (United States)

Guo, Zhongyi; Zhu, Lie; Guo, Kai; Shen, Fei; Yin, Zhiping

2017-08-01

In this paper, a high-order dielectric metasurface based on silicon nanobrick array is proposed and investigated. By controlling the length and width of the nanobricks, the metasurfaces could supply two different incremental transmission phases for the X-linear-polarized (XLP) and Y-linear-polarized (YLP) light with extremely high efficiency over 88%. Based on the designed metasurface, two polarization beam splitters working in high-order diffraction modes have been designed successfully, which demonstrated a high transmitted efficiency. In addition, we have also designed two vortex-beam generators working in high-order diffraction modes to create vortex beams with the topological charges of 2 and 3. The employment of dielectric metasurfaces operating in high-order diffraction modes could pave the way for a variety of new ultra-efficient optical devices.

Towards a high performance vertex detector based on 3D integration of deep N-well MAPS

International Nuclear Information System (INIS)

Re, V

2010-01-01

The development of deep N-Well (DNW) CMOS active pixel sensors was driven by the ambitious goal of designing a monolithic device with similar functionalities as in hybrid pixel readout chips, such as pixel-level sparsification and time stamping. The implementation of the DNW MAPS concept in a 3D vertical integration process naturally leads the designer towards putting more intelligence in the chip and in the pixels themselves, achieving novel device structures based on the interconnection of two or more layers fabricated in the same technology. These devices are read out with a data-push scheme that makes it possible to use pixel data for the generation of a flexible level 1 track trigger, based on associative memories, with short latency and high efficiency. This paper gives an update of the present status of DNW MAPS design in both 2D and 3D versions, and presents a discussion of the architectures that are being devised for the Layer 0 of the SuperB Silicon Vertex Tracker.

Towards a high performance vertex detector based on 3D integration of deep N-well MAPS

Energy Technology Data Exchange (ETDEWEB)

Re, V, E-mail: valerio.re@unibg.i [University of Bergamo, Department of Industrial Engineering, Viale Marconi 5, 24044 Dalmine (Italy)

2010-06-15

The development of deep N-Well (DNW) CMOS active pixel sensors was driven by the ambitious goal of designing a monolithic device with similar functionalities as in hybrid pixel readout chips, such as pixel-level sparsification and time stamping. The implementation of the DNW MAPS concept in a 3D vertical integration process naturally leads the designer towards putting more intelligence in the chip and in the pixels themselves, achieving novel device structures based on the interconnection of two or more layers fabricated in the same technology. These devices are read out with a data-push scheme that makes it possible to use pixel data for the generation of a flexible level 1 track trigger, based on associative memories, with short latency and high efficiency. This paper gives an update of the present status of DNW MAPS design in both 2D and 3D versions, and presents a discussion of the architectures that are being devised for the Layer 0 of the SuperB Silicon Vertex Tracker.

Harnessing wake vortices for efficient collective swimming via deep reinfrcement learning

Science.gov (United States)

Verma, Siddartha; Novati, Guido; Koumoutsakos, Petros; ChairComputing Science Team

2017-11-01

Collective motion may bestow evolutionary advantages to a number of animal species. Soaring flocks of birds, teeming swarms of insects, and swirling masses of schooling fish, all to some extent enjoy anti-predator benefits, increased foraging success, and enhanced problem-solving abilities. Coordinated activity may also provide energetic benefits, as in the case of large groups of fish where swimmers exploit unsteady flow-patterns generated in the wake. Both experimental and computational investigations of such scenarios are hampered by difficulties associated with studying multiple swimmers. Consequentially, the precise energy-saving mechanisms at play remain largely unknown. We combine high-fidelity numerical simulations of multiple, self propelled swimmers with novel deep reinforcement learning algorithms to discover optimal ways for swimmers to interact with unsteady wakes, in a fully unsupervised manner. We identify optimal flow-interaction strategies devised by the resulting autonomous swimmers, and use it to formulate an effective control-logic. We demonstrate, via 3D simulations of controlled groups that swimmers exploiting the learned strategy exhibit a significant reduction in energy-expenditure. ERC Advanced Investigator Award 341117.

All passive architecture for high efficiency cascaded Raman conversion

Science.gov (United States)

Balaswamy, V.; Arun, S.; Chayran, G.; Supradeepa, V. R.

2018-02-01

Cascaded Raman fiber lasers have offered a convenient method to obtain scalable, high-power sources at various wavelength regions inaccessible with rare-earth doped fiber lasers. A limitation previously was the reduced efficiency of these lasers. Recently, new architectures have been proposed to enhance efficiency, but this came at the cost of enhanced complexity, requiring an additional low-power, cascaded Raman laser. In this work, we overcome this with a new, all-passive architecture for high-efficiency cascaded Raman conversion. We demonstrate our architecture with a fifth-order cascaded Raman converter from 1117nm to 1480nm with output power of ~64W and efficiency of 60%.

High-efficiency photovoltaic cells

Science.gov (United States)

Yang, H.T.; Zehr, S.W.

1982-06-21

High efficiency solar converters comprised of a two cell, non-lattice matched, monolithic stacked semiconductor configuration using optimum pairs of cells having bandgaps in the range 1.6 to 1.7 eV and 0.95 to 1.1 eV, and a method of fabrication thereof, are disclosed. The high band gap subcells are fabricated using metal organic chemical vapor deposition (MOCVD), liquid phase epitaxy (LPE) or molecular beam epitaxy (MBE) to produce the required AlGaAs layers of optimized composition, thickness and doping to produce high performance, heteroface homojunction devices. The low bandgap subcells are similarly fabricated from AlGa(As)Sb compositions by LPE, MBE or MOCVD. These subcells are then coupled to form a monolithic structure by an appropriate bonding technique which also forms the required transparent intercell ohmic contact (IOC) between the two subcells. Improved ohmic contacts to the high bandgap semiconductor structure can be formed by vacuum evaporating to suitable metal or semiconductor materials which react during laser annealing to form a low bandgap semiconductor which provides a low contact resistance structure.

Deep Reactive Ion Etching (DRIE) of High Aspect Ratio SiC Microstructures using a Time-Multiplexed Etch-Passivate Process

Science.gov (United States)

Evans, Laura J.; Beheim, Glenn M.

2006-01-01

High aspect ratio silicon carbide (SiC) microstructures are needed for microengines and other harsh environment micro-electro-mechanical systems (MEMS). Previously, deep reactive ion etching (DRIE) of low aspect ratio (AR less than or = 1) deep (greater than 100 micron) trenches in SiC has been reported. However, existing DRIE processes for SiC are not well-suited for definition of high aspect ratio features because such simple etch-only processes provide insufficient control over sidewall roughness and slope. Therefore, we have investigated the use of a time-multiplexed etch-passivate (TMEP) process, which alternates etching with polymer passivation of the etch sidewalls. An optimized TMEP process was used to etch high aspect ratio (AR greater than 5) deep (less than 100 micron) trenches in 6H-SiC. Power MEMS structures (micro turbine blades) in 6H-SiC were also fabricated.

Ultra-high Efficiency DC-DC Converter using GaN Devices

DEFF Research Database (Denmark)

Ramachandran, Rakesh

2016-01-01

properties of GaN devices can be utilized in power converters to make them more compact and highly efficient. This thesis entitled “Ultra-high Efficiency DC-DC Converter using GaN devices” focuses on achieving ultra-high conversion efficiency in an isolated dc-dc converter by the optimal utilization of Ga...... for many decades. However, the rate of improvement slowed as the silicon power materials asymptotically approached its theoretical bounds. Compared to Si, wideband gap materials such as Silicon Carbide (SiC) and Gallium Nitride (GaN) are promising semiconductors for power devices due to their superior...... in this thesis. Efficiency measurements from the hardware prototype of both the topologies are also presented in this thesis. Finally, the bidirectional operation of an optimized isolated dc-dc converter is presented. The optimized converter has achieved an ultra-high efficiency of 98.8% in both directions...

Saving energy via high-efficiency fans.

Science.gov (United States)

Heine, Thomas

2016-08-01

Thomas Heine, sales and market manager for EC Upgrades, the retrofit arm of global provider of air movement solutions, ebm-papst A&NZ, discusses the retrofitting of high-efficiency fans to existing HVAC equipment to 'drastically reduce energy consumption'.

Human-level control through deep reinforcement learning

Science.gov (United States)

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-01

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Human-level control through deep reinforcement learning.

Science.gov (United States)

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-26

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Bioblendstocks that Enable High Efficiency Engine Designs

Energy Technology Data Exchange (ETDEWEB)

McCormick, Robert L.; Fioroni, Gina M.; Ratcliff, Matthew A.; Zigler, Bradley T.; Farrell, John

2016-11-03

The past decade has seen a high level of innovation in production of biofuels from sugar, lipid, and lignocellulose feedstocks. As discussed in several talks at this workshop, ethanol blends in the E25 to E50 range could enable more highly efficient spark-ignited (SI) engines. This is because of their knock resistance properties that include not only high research octane number (RON), but also charge cooling from high heat of vaporization, and high flame speed. Emerging alcohol fuels such as isobutanol or mixed alcohols have desirable properties such as reduced gasoline blend vapor pressure, but also have lower RON than ethanol. These fuels may be able to achieve the same knock resistance benefits, but likely will require higher blend levels or higher RON hydrocarbon blendstocks. A group of very high RON (>150) oxygenates such as dimethyl furan, methyl anisole, and related compounds are also produced from biomass. While providing no increase in charge cooling, their very high octane numbers may provide adequate knock resistance for future highly efficient SI engines. Given this range of options for highly knock resistant fuels there appears to be a critical need for a fuel knock resistance metric that includes effects of octane number, heat of vaporization, and potentially flame speed. Emerging diesel fuels include highly branched long-chain alkanes from hydroprocessing of fats and oils, as well as sugar-derived terpenoids. These have relatively high cetane number (CN), which may have some benefits in designing more efficient CI engines. Fast pyrolysis of biomass can produce diesel boiling range streams that are high in aromatic, oxygen and acid contents. Hydroprocessing can be applied to remove oxygen and consequently reduce acidity, however there are strong economic incentives to leave up to 2 wt% oxygen in the product. This oxygen will primarily be present as low CN alkyl phenols and aryl ethers. While these have high heating value, their presence in diesel fuel

Stabilization void-fill encapsulation high-efficiency particulate filters

International Nuclear Information System (INIS)

Alexander, R.G.; Stewart, W.E.; Phillips, S.J.; Serkowski, M.M.; England, J.L.; Boynton, H.C.

1994-05-01

This report discusses high-efficiency particulate air (HEPA) filter systems that which are contaminated with radionuclides are part of the nuclear fuel processing systems conducted by the US Department of Energy (DOE) and require replacement and safe and efficient disposal for plant safety. Two K-3 HEPA filters were removed from service, placed burial boxes, buried, and safely and efficiently stabilized remotely which reduced radiation exposure to personnel and the environment

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

Science.gov (United States)

Kravatsky, Yuri; Chechetkin, Vladimir; Fedoseeva, Daria; Gorbacheva, Maria; Kravatskaya, Galina; Kretova, Olga; Tchurikov, Nickolai

2017-11-23

The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

High-efficient electron linacs

International Nuclear Information System (INIS)

Glavatskikh, K.V.; Zverev, B.V.; Kalyuzhnyj, V.E.; Morozov, V.L.; Nikolaev, S.V.; Plotnikov, S.N.; Sobenin, N.P.; Vovna, V.A.; Gryzlov, A.V.

1993-01-01

Comparison analysis of ELA on running and still waves designed for 10 MeV energy and with high efficiency is carried out. It is shown, that from the point of view of dimensions ELA with a still wave or that of a combined type is more preferable. From the point of view of impedance characteristics in any variant with application of magnetron as HF-generator it is necessary to implement special requirements to the accelerating structure if no ferrite isolation is provided in HF-channel. 3 refs., 4 figs., 1 tab

Segmentation of low‐cost high efficiency oxide‐based thermoelectric materials

DEFF Research Database (Denmark)

Le, Thanh Hung; Van Nong, Ngo; Linderoth, Søren

2015-01-01

Thermoelectric (TE) oxide materials have attracted great interest in advanced renewable energy research owing to the fact that they consist of abundant elements, can be manufactured by low-cost processing, sustain high temperatures, be robust and provide long lifetime. However, the low conversion...... efficiency of TE oxides has been a major drawback limiting these materials to broaden applications. In this work, theoretical calculations are used to predict how segmentation of oxide and semimetal materials, utilizing the benefits of both types of materials, can provide high efficiency, high temperature...... oxide-based segmented legs. The materials for segmentation are selected by their compatibility factors and their conversion efficiency versus material cost, i.e., “efficiency ratio”. Numerical modelling results showed that conversion efficiency could reach values of more than 10% for unicouples using...

High-efficiency CARM

Energy Technology Data Exchange (ETDEWEB)

Bratman, V.L.; Kol`chugin, B.D.; Samsonov, S.V.; Volkov, A.B. [Institute of Applied Physics, Nizhny Novgorod (Russian Federation)

1995-12-31

The Cyclotron Autoresonance Maser (CARM) is a well-known variety of FEMs. Unlike the ubitron in which electrons move in a periodical undulator field, in the CARM the particles move along helical trajectories in a uniform magnetic field. Since it is much simpler to generate strong homogeneous magnetic fields than periodical ones for a relatively low electron energy ({Brit_pounds}{le}1-3 MeV) the period of particles` trajectories in the CARM can be sufficiently smaller than in the undulator in which, moreover, the field decreases rapidly in the transverse direction. In spite of this evident advantage, the number of papers on CARM is an order less than on ubitron, which is apparently caused by the low (not more than 10 %) CARM efficiency in experiments. At the same time, ubitrons operating in two rather complicated regimes-trapping and adiabatic deceleration of particles and combined undulator and reversed guiding fields - yielded efficiencies of 34 % and 27 %, respectively. The aim of this work is to demonstrate that high efficiency can be reached even for a simplest version of the CARM. In order to reduce sensitivity to an axial velocity spread of particles, a short interaction length where electrons underwent only 4-5 cyclotron oscillations was used in this work. Like experiments, a narrow anode outlet of a field-emission electron gun cut out the {open_quotes}most rectilinear{close_quotes} near-axis part of the electron beam. Additionally, magnetic field of a small correcting coil compensated spurious electron oscillations pumped by the anode aperture. A kicker in the form of a sloping to the axis frame with current provided a control value of rotary velocity at a small additional velocity spread. A simple cavity consisting of a cylindrical waveguide section restricted by a cut-off waveguide on the cathode side and by a Bragg reflector on the collector side was used as the CARM-oscillator microwave system.

New III-V cell design approaches for very high efficiency

Energy Technology Data Exchange (ETDEWEB)

Lundstrom, M.S.; Melloch, M.R.; Lush, G.B.; Patkar, M.P.; Young, M.P. (Purdue Univ., Lafayette, IN (United States))

1993-04-01

This report describes to examine new solar cell desip approaches for achieving very high conversion efficiencies. The program consists of two elements. The first centers on exploring new thin-film approaches specifically designed for M-III semiconductors. Substantial efficiency gains may be possible by employing light trapping techniques to confine the incident photons, as well as the photons emitted by radiative recombination. The thin-film approach is a promising route for achieving substantial performance improvements in the already high-efficiency, single-junction, III-V cell. The second element of the research involves exploring desip approaches for achieving high conversion efficiencies without requiring extremely high-quality material. This work has applications to multiple-junction cells, for which the selection of a component cell often involves a compromise between optimum band pp and optimum material quality. It could also be a benefit manufacturing environment by making the cell's efficiency less dependent on materialquality.

Evaluation of the effect of media velocity on filter efficiency and most penetrating particle size of nuclear grade high-efficiency particulate air filters.

Science.gov (United States)

Alderman, Steven L; Parsons, Michael S; Hogancamp, Kristina U; Waggoner, Charles A

2008-11-01

High-efficiency particulate air (HEPA) filters are widely used to control particulate matter emissions from processes that involve management or treatment of radioactive materials. Section FC of the American Society of Mechanical Engineers AG-1 Code on Nuclear Air and Gas Treatment currently restricts media velocity to a maximum of 2.5 cm/sec in any application where this standard is invoked. There is some desire to eliminate or increase this media velocity limit. A concern is that increasing media velocity will result in higher emissions of ultrafine particles; thus, it is unlikely that higher media velocities will be allowed without data to demonstrate the effect of media velocity on removal of ultrafine particles. In this study, the performance of nuclear grade HEPA filters, with respect to filter efficiency and most penetrating particle size, was evaluated as a function of media velocity. Deep-pleat nuclear grade HEPA filters (31 cm x 31 cm x 29 cm) were evaluated at media velocities ranging from 2.0 to 4.5 cm/sec using a potassium chloride aerosol challenge having a particle size distribution centered near the HEPA filter most penetrating particle size. Filters were challenged under two distinct mass loading rate regimes through the use of or exclusion of a 3 microm aerodynamic diameter cut point cyclone. Filter efficiency and most penetrating particle size measurements were made throughout the duration of filter testing. Filter efficiency measured at the onset of aerosol challenge was noted to decrease with increasing media velocity, with values ranging from 99.999 to 99.977%. The filter most penetrating particle size recorded at the onset of testing was noted to decrease slightly as media velocity was increased and was typically in the range of 110-130 nm. Although additional testing is needed, these findings indicate that filters operating at media velocities up to 4.5 cm/sec will meet or exceed current filter efficiency requirements. Additionally

Charge transport in highly efficient iridium cored electrophosphorescent dendrimers

Science.gov (United States)

Markham, Jonathan P. J.; Samuel, Ifor D. W.; Lo, Shih-Chun; Burn, Paul L.; Weiter, Martin; Bässler, Heinz

2004-01-01

Electrophosphorescent dendrimers are promising materials for highly efficient light-emitting diodes. They consist of a phosphorescent core onto which dendritic groups are attached. Here, we present an investigation into the optical and electronic properties of highly efficient phosphorescent dendrimers. The effect of dendrimer structure on charge transport and optical properties is studied using temperature-dependent charge-generation-layer time-of-flight measurements and current voltage (I-V) analysis. A model is used to explain trends seen in the I-V characteristics. We demonstrate that fine tuning the mobility by chemical structure is possible in these dendrimers and show that this can lead to highly efficient bilayer dendrimer light-emitting diodes with neat emissive layers. Power efficiencies of 20 lm/W were measured for devices containing a second-generation (G2) Ir(ppy)3 dendrimer with a 1,3,5-tris(2-N-phenylbenzimidazolyl)benzene electron transport layer.

Design of High Efficiency Illumination for LED Lighting

OpenAIRE

Chang, Yong-Nong; Cheng, Hung-Liang; Kuo, Chih-Ming

2013-01-01

A high efficiency illumination for LED street lighting is proposed. For energy saving, this paper uses Class-E resonant inverter as main electric circuit to improve efficiency. In addition, single dimming control has the best efficiency, simplest control scheme and lowest circuit cost among other types of dimming techniques. Multiple serial-connected transformers used to drive the LED strings as they can provide galvanic isolation and have the advantage of good current distribution against de...

Plan of deep underground construction for investigations on high-level radioactive waste storage

International Nuclear Information System (INIS)

Mayanovskij, M.S.

1996-01-01

The program of studies of the Japanese PNC corporation on construction of deep underground storage for high-level radioactive wastes is presented. The program is intended for 20 years. The total construction costs equal about 20 billion yen. The total cost of the project is equal to 60 billion yen. The underground part is planned to reach 1000 m depth

High Quantum Efficiency OLED Lighting Systems

Energy Technology Data Exchange (ETDEWEB)

Shiang, Joseph [General Electric (GE) Global Research, Fairfield, CT (United States)

2011-09-30

The overall goal of the program was to apply improvements in light outcoupling technology to a practical large area plastic luminaire, and thus enable the product vision of an extremely thin form factor high efficiency large area light source. The target substrate was plastic and the baseline device was operating at 35 LPW at the start of the program. The target LPW of the program was a >2x improvement in the LPW efficacy and the overall amount of light to be delivered was relatively high 900 lumens. Despite the extremely difficult challenges associated with scaling up a wet solution process on plastic substrates, the program was able to make substantial progress. A small molecule wet solution process was successfully implemented on plastic substrates with almost no loss in efficiency in transitioning from the laboratory scale glass to large area plastic substrates. By transitioning to a small molecule based process, the LPW entitlement increased from 35 LPW to 60 LPW. A further 10% improvement in outcoupling efficiency was demonstrated via the use of a highly reflecting cathode, which reduced absorptive loss in the OLED device. The calculated potential improvement in some cases is even larger, ~30%, and thus there is considerable room for optimism in improving the net light coupling efficacy, provided absorptive loss mechanisms are eliminated. Further improvements are possible if scattering schemes such as the silver nanowire based hard coat structure are fully developed. The wet coating processes were successfully scaled to large area plastic substrate and resulted in the construction of a 900 lumens luminaire device.

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

Directory of Open Access Journals (Sweden)

Fan Zhang

2016-04-01

Full Text Available With the development of synthetic aperture radar (SAR technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO. However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

Science.gov (United States)

Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

2016-04-07

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

Transferring and generalizing deep-learning-based neural encoding models across subjects.

Science.gov (United States)

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-08-01

Recent studies have shown the value of using deep learning models for mapping and characterizing how the brain represents and organizes information for natural vision. However, modeling the relationship between deep learning models and the brain (or encoding models), requires measuring cortical responses to large and diverse sets of natural visual stimuli from single subjects. This requirement limits prior studies to few subjects, making it difficult to generalize findings across subjects or for a population. In this study, we developed new methods to transfer and generalize encoding models across subjects. To train encoding models specific to a target subject, the models trained for other subjects were used as the prior models and were refined efficiently using Bayesian inference with a limited amount of data from the target subject. To train encoding models for a population, the models were progressively trained and updated with incremental data from different subjects. For the proof of principle, we applied these methods to functional magnetic resonance imaging (fMRI) data from three subjects watching tens of hours of naturalistic videos, while a deep residual neural network driven by image recognition was used to model visual cortical processing. Results demonstrate that the methods developed herein provide an efficient and effective strategy to establish both subject-specific and population-wide predictive models of cortical representations of high-dimensional and hierarchical visual features. Copyright © 2018 Elsevier Inc. All rights reserved.

Efficient incremental relaying

KAUST Repository

Fareed, Muhammad Mehboob

2013-07-01

We propose a novel relaying scheme which improves the spectral efficiency of cooperative diversity systems by utilizing limited feedback from destination. Our scheme capitalizes on the fact that relaying is only required when direct transmission suffers deep fading. We calculate the packet error rate for the proposed efficient incremental relaying scheme with both amplify and forward and decode and forward relaying. Numerical results are also presented to verify their analytical counterparts. © 2013 IEEE.

Stimulation Technologies for Deep Well Completions

Energy Technology Data Exchange (ETDEWEB)

None

2003-09-30

The Department of Energy (DOE) is sponsoring the Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies is conducting a study to evaluate the stimulation of deep wells. The objective of the project is to assess U.S. deep well drilling & stimulation activity, review rock mechanics & fracture growth in deep, high pressure/temperature wells and evaluate stimulation technology in several key deep plays. An assessment of historical deep gas well drilling activity and forecast of future trends was completed during the first six months of the project; this segment of the project was covered in Technical Project Report No. 1. The second progress report covers the next six months of the project during which efforts were primarily split between summarizing rock mechanics and fracture growth in deep reservoirs and contacting operators about case studies of deep gas well stimulation.

High efficiency and broadband acoustic diodes

Science.gov (United States)

Fu, Congyi; Wang, Bohan; Zhao, Tianfei; Chen, C. Q.

2018-01-01

Energy transmission efficiency and working bandwidth are the two major factors limiting the application of current acoustic diodes (ADs). This letter presents a design of high efficiency and broadband acoustic diodes composed of a nonlinear frequency converter and a linear wave filter. The converter consists of two masses connected by a bilinear spring with asymmetric tension and compression stiffness. The wave filter is a linear mass-spring lattice (sonic crystal). Both numerical simulation and experiment show that the energy transmission efficiency of the acoustic diode can be improved by as much as two orders of magnitude, reaching about 61%. Moreover, the primary working band width of the AD is about two times of the cut-off frequency of the sonic crystal filter. The cut-off frequency dependent working band of the AD implies that the developed AD can be scaled up or down from macro-scale to micro- and nano-scale.

High-precision efficiency calibration of a high-purity co-axial germanium detector

Energy Technology Data Exchange (ETDEWEB)

Blank, B., E-mail: blank@cenbg.in2p3.fr [Centre d' Etudes Nucléaires de Bordeaux Gradignan, UMR 5797, CNRS/IN2P3, Université de Bordeaux, Chemin du Solarium, BP 120, 33175 Gradignan Cedex (France); Souin, J.; Ascher, P.; Audirac, L.; Canchel, G.; Gerbaux, M.; Grévy, S.; Giovinazzo, J.; Guérin, H.; Nieto, T. Kurtukian; Matea, I. [Centre d' Etudes Nucléaires de Bordeaux Gradignan, UMR 5797, CNRS/IN2P3, Université de Bordeaux, Chemin du Solarium, BP 120, 33175 Gradignan Cedex (France); Bouzomita, H.; Delahaye, P.; Grinyer, G.F.; Thomas, J.C. [Grand Accélérateur National d' Ions Lourds, CEA/DSM, CNRS/IN2P3, Bvd Henri Becquerel, BP 55027, F-14076 CAEN Cedex 5 (France)

2015-03-11

A high-purity co-axial germanium detector has been calibrated in efficiency to a precision of about 0.15% over a wide energy range. High-precision scans of the detector crystal and γ-ray source measurements have been compared to Monte-Carlo simulations to adjust the dimensions of a detector model. For this purpose, standard calibration sources and short-lived online sources have been used. The resulting efficiency calibration reaches the precision needed e.g. for branching ratio measurements of super-allowed β decays for tests of the weak-interaction standard model.

Development of in situ Brillouin spectroscopy at high pressure and high temperature with synchrotron radiation and infrared laser heating system: Application to the Earth's deep interior

Science.gov (United States)

Murakami, Motohiko; Asahara, Yuki; Ohishi, Yasuo; Hirao, Naohisa; Hirose, Kei

2009-05-01

Seismic wave velocity profiles in the Earth provide one of the strongest constraints on structure, mineralogy and elastic properties of the Earth's deep interior. Accurate sound velocity data of deep Earth materials under relevant high-pressure and high-temperature conditions, therefore, are essential for interpretation of seismic data. Such information can be directly obtained from Brillouin scattering measurement. Here we describe an in situ Brillouin scattering system for measurements at high pressure and high temperature using a laser heated diamond anvil cell and synchrotron radiation for sample characterization. The system has been used with single-crystal and polycrystalline materials, and with glass and fluid phase. It provided high quality sound velocity and elastic data with X-ray diffraction data at high pressure and/or high temperature. Those combined techniques can potentially offer the essential information for resolving many remaining issues in mineral physics.

Survival of marine heterotrophic flagellates isolated from the surface and the deep sea at high hydrostatic pressure: Literature review and own experiments

Science.gov (United States)

Živaljić, Suzana; Schoenle, Alexandra; Nitsche, Frank; Hohlfeld, Manon; Piechocki, Julia; Reif, Farina; Shumo, Marwa; Weiss, Alexandra; Werner, Jennifer; Witt, Madeleine; Voss, Janine; Arndt, Hartmut

2018-02-01

Although the abyssal seafloor represents the most common benthic environment on Earth, eukaryotic microbial life at abyssal depths is still an uncharted territory. This is in striking contrast to their potential importance regarding the material flux and bacteria consumption in the deep sea. Flagellate genotypes determined from sedimentary DNA deep-sea samples might originate from vital deep-sea populations or from cysts of organisms sedimented down from surface waters. The latter one may have never been active under deep-sea conditions. We wanted to analyze the principal ability of cultivable heterotrophic flagellates of different phylogenetic groups (choanoflagellates, ancyromonads, euglenids, kinetoplastids, bicosoecids, chrysomonads, and cercozoans) to survive exposure to high hydrostatic pressure (up to 670 bar). We summarized our own studies and the few available data from literature on pressure tolerances of flagellates isolated from different marine habitats. Our results demonstrated that many different flagellate species isolated from the surface waters and deep-sea sediments survived drastic changes in hydrostatic pressure. Barophilic behavior was also recorded for several species isolated from the deep sea indicating their possible genetic adaptation to high pressures. This is in accordance with records of heterotrophic flagellates present in environmental DNA surveys based on clone libraries established for deep-sea environments.

A Hybrid CPU/GPU Pattern-Matching Algorithm for Deep Packet Inspection.

Directory of Open Access Journals (Sweden)

Chun-Liang Lee

Full Text Available The large quantities of data now being transferred via high-speed networks have made deep packet inspection indispensable for security purposes. Scalable and low-cost signature-based network intrusion detection systems have been developed for deep packet inspection for various software platforms. Traditional approaches that only involve central processing units (CPUs are now considered inadequate in terms of inspection speed. Graphic processing units (GPUs have superior parallel processing power, but transmission bottlenecks can reduce optimal GPU efficiency. In this paper we describe our proposal for a hybrid CPU/GPU pattern-matching algorithm (HPMA that divides and distributes the packet-inspecting workload between a CPU and GPU. All packets are initially inspected by the CPU and filtered using a simple pre-filtering algorithm, and packets that might contain malicious content are sent to the GPU for further inspection. Test results indicate that in terms of random payload traffic, the matching speed of our proposed algorithm was 3.4 times and 2.7 times faster than those of the AC-CPU and AC-GPU algorithms, respectively. Further, HPMA achieved higher energy efficiency than the other tested algorithms.

Deep energetic trap states in organic photovoltaic devices

KAUST Repository

Shuttle, Christopher G.; Treat, Neil D.; Douglas, Jessica D.; Frechet, Jean; Chabinyc, Michael L.

2011-01-01

The nature of energetic disorder in organic semiconductors is poorly understood. In photovoltaics, energetic disorder leads to reductions in the open circuit voltage and contributes to other loss processes. In this work, three independent optoelectronic methods were used to determine the long-lived carrier populations in a high efficiency N-alkylthieno[3,4-c]pyrrole-4,6-dione (TPD) based polymer: fullerene solar cell. In the TPD co-polymer, all methods indicate the presence of a long-lived carrier population of ∼ 10 15 cm -3 on timescales ≤100 μs. Additionally, the behavior of these photovoltaic devices under optical bias is consistent with deep energetic lying trap states. Comparative measurements were also performed on high efficiency poly-3-hexylthiophene (P3HT): fullerene solar cells; however a similar long-lived carrier population was not observed. This observation is consistent with a higher acceptor concentration (doping) in P3HT than in the TPD-based copolymer. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deep energetic trap states in organic photovoltaic devices

KAUST Repository

Shuttle, Christopher G.

2011-11-23

The nature of energetic disorder in organic semiconductors is poorly understood. In photovoltaics, energetic disorder leads to reductions in the open circuit voltage and contributes to other loss processes. In this work, three independent optoelectronic methods were used to determine the long-lived carrier populations in a high efficiency N-alkylthieno[3,4-c]pyrrole-4,6-dione (TPD) based polymer: fullerene solar cell. In the TPD co-polymer, all methods indicate the presence of a long-lived carrier population of ∼ 10 15 cm -3 on timescales ≤100 μs. Additionally, the behavior of these photovoltaic devices under optical bias is consistent with deep energetic lying trap states. Comparative measurements were also performed on high efficiency poly-3-hexylthiophene (P3HT): fullerene solar cells; however a similar long-lived carrier population was not observed. This observation is consistent with a higher acceptor concentration (doping) in P3HT than in the TPD-based copolymer. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An adaptive sampling scheme for deep-penetration calculation

International Nuclear Information System (INIS)

Wang, Ruihong; Ji, Zhicheng; Pei, Lucheng

2013-01-01

As we know, the deep-penetration problem has been one of the important and difficult problems in shielding calculation with Monte Carlo Method for several decades. In this paper, an adaptive Monte Carlo method under the emission point as a sampling station for shielding calculation is investigated. The numerical results show that the adaptive method may improve the efficiency of the calculation of shielding and might overcome the under-estimation problem easy to happen in deep-penetration calculation in some degree

High-efficiency ballistic electrostatic generator using microdroplets

Science.gov (United States)

Xie, Yanbo; Bos, Diederik; de Vreede, Lennart J.; de Boer, Hans L.; van der Meulen, Mark-Jan; Versluis, Michel; Sprenkels, Ad J.; van den Berg, Albert; Eijkel, Jan C. T.

2014-04-01

The strong demand for renewable energy promotes research on novel methods and technologies for energy conversion. Microfluidic systems for energy conversion by streaming current are less known to the public, and the relatively low efficiencies previously obtained seemed to limit the further applications of such systems. Here we report a microdroplet-based electrostatic generator operating by an acceleration-deceleration cycle (‘ballistic’ conversion), and show that this principle enables both high efficiency and compact simple design. Water is accelerated by pumping it through a micropore to form a microjet breaking up into fast-moving charged droplets. Droplet kinetic energy is converted to electrical energy when the charged droplets decelerate in the electrical field that forms between membrane and target. We demonstrate conversion efficiencies of up to 48%, a power density of 160 kW m-2 and both high- (20 kV) and low- (500 V) voltage operation. Besides offering striking new insights, the device potentially opens up new perspectives for low-cost and robust renewable energy conversion.

High-Efficient Low-Cost Photovoltaics Recent Developments

CERN Document Server

Petrova-Koch, Vesselinka; Goetzberger, Adolf

2009-01-01

A bird's-eye view of the development and problems of recent photovoltaic cells and systems and prospects for Si feedstock is presented. High-efficient low-cost PV modules, making use of novel efficient solar cells (based on c-Si or III-V materials), and low cost solar concentrators are in the focus of this book. Recent developments of organic photovoltaics, which is expected to overcome its difficulties and to enter the market soon, are also included.

DeepBase: annotation and discovery of microRNAs and other noncoding RNAs from deep-sequencing data.

Science.gov (United States)

Yang, Jian-Hua; Qu, Liang-Hu

2012-01-01

Recent advances in high-throughput deep-sequencing technology have produced large numbers of short and long RNA sequences and enabled the detection and profiling of known and novel microRNAs (miRNAs) and other noncoding RNAs (ncRNAs) at unprecedented sensitivity and depth. In this chapter, we describe the use of deepBase, a database that we have developed to integrate all public deep-sequencing data and to facilitate the comprehensive annotation and discovery of miRNAs and other ncRNAs from these data. deepBase provides an integrative, interactive, and versatile web graphical interface to evaluate miRBase-annotated miRNA genes and other known ncRNAs, explores the expression patterns of miRNAs and other ncRNAs, and discovers novel miRNAs and other ncRNAs from deep-sequencing data. deepBase also provides a deepView genome browser to comparatively analyze these data at multiple levels. deepBase is available at http://deepbase.sysu.edu.cn/.

Development of high-efficiency solar cells on silicon web

Science.gov (United States)

Meier, D. L.; Greggi, J.; Okeeffe, T. W.; Rai-Choudhury, P.

1986-01-01

Work was performed to improve web base material with a goal of obtaining solar cell efficiencies in excess of 18% (AM1). Efforts in this program are directed toward identifying carrier loss mechanisms in web silicon, eliminating or reducing these mechanisms, designing a high efficiency cell structure with the aid of numerical models, and fabricating high efficiency web solar cells. Fabrication techniques must preserve or enhance carrier lifetime in the bulk of the cell and minimize recombination of carriers at the external surfaces. Three completed cells were viewed by cross-sectional transmission electron microscopy (TEM) in order to investigate further the relation between structural defects and electrical performance of web cells. Consistent with past TEM examinations, the cell with the highest efficiency (15.0%) had no dislocations but did have 11 twin planes.

Clustered deep shadow maps for integrated polyhedral and volume rendering

KAUST Repository

Bornik, Alexander

2012-01-01

This paper presents a hardware-accelerated approach for shadow computation in scenes containing both complex volumetric objects and polyhedral models. Our system is the first hardware accelerated complete implementation of deep shadow maps, which unifies the computation of volumetric and geometric shadows. Up to now such unified computation was limited to software-only rendering . Previous hardware accelerated techniques can handle only geometric or only volumetric scenes - both resulting in the loss of important properties of the original concept. Our approach supports interactive rendering of polyhedrally bounded volumetric objects on the GPU based on ray casting. The ray casting can be conveniently used for both the shadow map computation and the rendering. We show how anti-aliased high-quality shadows are feasible in scenes composed of multiple overlapping translucent objects, and how sparse scenes can be handled efficiently using clustered deep shadow maps. © 2012 Springer-Verlag.

Complexity-aware high efficiency video coding

CERN Document Server

Correa, Guilherme; Agostini, Luciano; Cruz, Luis A da Silva

2016-01-01

This book discusses computational complexity of High Efficiency Video Coding (HEVC) encoders with coverage extending from the analysis of HEVC compression efficiency and computational complexity to the reduction and scaling of its encoding complexity. After an introduction to the topic and a review of the state-of-the-art research in the field, the authors provide a detailed analysis of the HEVC encoding tools compression efficiency and computational complexity.  Readers will benefit from a set of algorithms for scaling the computational complexity of HEVC encoders, all of which take advantage from the flexibility of the frame partitioning structures allowed by the standard.  The authors also provide a set of early termination methods based on data mining and machine learning techniques, which are able to reduce the computational complexity required to find the best frame partitioning structures. The applicability of the proposed methods is finally exemplified with an encoding time control system that emplo...

Preparation of Novel Fused Ring Spiro[benzotetraphene-fluorene] Derivatives and Application for Deep-Blue Host Materials

Energy Technology Data Exchange (ETDEWEB)

Kim, Minji; Lee, Chilwon; Gong, Myoungseon [Dankook Univ., Yongin (Korea, Republic of)

2014-06-15

A series of novel fused-ring spiro compounds, spiro[benzo[ij]tetraphene-7,9'-fluorene] derivatives containing an end-capping aryl substituent at both the C3 and C10-positions has been designed and synthesized via multi-step Suzuki coupling reactions. 3-(1-Naphthyl)-10-phenyl, 3-(2-naphthyl)-10-phenyl and 3-[4-(1-naphthyl)phenyl]-10-phenyl showed improved glass transition temperatures (T{sub g}) with good thermal stability. Their photophysical, electrochemical, and electroluminescent properties were investigated and were used to construct blue organic light emission diodes (OLEDs). The typical OLED devices showed excellent performance; the based device exhibited highly efficient deep blue-light emission with a maximum efficiency of 5.27 cd/A (EQE, 4.63%) with CIE (x = 0.133, y = 0.144). According to these characteristics, these deep-blue light emitting materials have sufficient potential for fluorescent OLED applications.

Methyl iodide trapping efficiency of aged charcoal samples from Bruce-A emergency filtered air discharge systems

International Nuclear Information System (INIS)

Wren, J.C.; Moore, C.J.; Rasmussenn, M.T.; Weaver, K.R.

1999-01-01

Charcoal filters are installed in the emergency filtered air discharge system (EFADS) of multiunit stations to control the release of airborne radioiodine in the event of a reactor accident. These filters use highly activated charcoal impregnated with triethylenediamine (TEDA). The TEDA-impregnated charcoal is highly efficient in removing radioiodine from flowing airstreams. The iodine-removal efficiency of the charcoal is presumed to deteriorate slowly with age, but current knowledge of this effect is insufficient to predict with confidence the performance of aged charcoal following an accident. Experiments were performed to determine the methyl iodide removal efficiency of aged charcoal samples taken from the EFADS of Ontario Hydro's Bruce-A nuclear generating station. The charcoal had been in service for ∼4 yr. The adsorption rate constant and capacity were measured under post-loss-of-coolant accident conditions to determine the efficiency of the aged charcoal. The adsorption rate constants of the aged charcoal samples were observed to be extremely high, yielding a decontamination factor (DF) for a 20-cm-deep bed of the aged charcoal >1 X 10 15 . The results show that essentially no CH 3 I would escape from a 20-cm-deep bed of the aged charcoal and that the requirement for a DF of 1000 for organic iodides in the EFADS filters would be exceeded by a tremendous margin. With such high DFs, the release of iodine from a 20-cm-deep bed would be virtually impossible to detect. The adsorption capacities observed for the aged charcoal samples approach the theoretical chemisorption capacity of 5 wt% TEDA charcoal, indicating that aging in the EFADS for 4 yr has had a negligible impact on the adsorption capacity. The results indicate that the short- and long-term performances of the aged charcoal in the EFADS of Bruce-A following an accident would still far exceed performance requirements. (author)

High bandgap III-V alloys for high efficiency optoelectronics

Energy Technology Data Exchange (ETDEWEB)

Alberi, Kirstin; Mascarenhas, Angelo; Wanlass, Mark

2017-01-10

High bandgap alloys for high efficiency optoelectronics are disclosed. An exemplary optoelectronic device may include a substrate, at least one Al.sub.1-xIn.sub.xP layer, and a step-grade buffer between the substrate and at least one Al.sub.1-xIn.sub.xP layer. The buffer may begin with a layer that is substantially lattice matched to GaAs, and may then incrementally increase the lattice constant in each sequential layer until a predetermined lattice constant of Al.sub.1-xIn.sub.xP is reached.

Self-Paced Prioritized Curriculum Learning With Coverage Penalty in Deep Reinforcement Learning.

Science.gov (United States)

Ren, Zhipeng; Dong, Daoyi; Li, Huaxiong; Chen, Chunlin; Zhipeng Ren; Daoyi Dong; Huaxiong Li; Chunlin Chen; Dong, Daoyi; Li, Huaxiong; Chen, Chunlin; Ren, Zhipeng

2018-06-01

In this paper, a new training paradigm is proposed for deep reinforcement learning using self-paced prioritized curriculum learning with coverage penalty. The proposed deep curriculum reinforcement learning (DCRL) takes the most advantage of experience replay by adaptively selecting appropriate transitions from replay memory based on the complexity of each transition. The criteria of complexity in DCRL consist of self-paced priority as well as coverage penalty. The self-paced priority reflects the relationship between the temporal-difference error and the difficulty of the current curriculum for sample efficiency. The coverage penalty is taken into account for sample diversity. With comparison to deep Q network (DQN) and prioritized experience replay (PER) methods, the DCRL algorithm is evaluated on Atari 2600 games, and the experimental results show that DCRL outperforms DQN and PER on most of these games. More results further show that the proposed curriculum training paradigm of DCRL is also applicable and effective for other memory-based deep reinforcement learning approaches, such as double DQN and dueling network. All the experimental results demonstrate that DCRL can achieve improved training efficiency and robustness for deep reinforcement learning.

High temperature tensile properties and deep drawing of fully green composites

Directory of Open Access Journals (Sweden)

2009-01-01

Full Text Available In recent years, research and development of materials using biomass sources are much expected to construct a sustainable society. The so-called green composite consisting of natural fibers and biodegradable resin, is one of the most promising materials in developing biomass products. In this study, especially, we focus on the tensile deformation behavior of the green composites reinforced with ramie woven fabrics at high temperature. The results show that the fracture strain at high temperatures increases larger than that of room temperature, and initial deformation resistance of the composites seen at room temperature does not appear at high temperatures. Thus, several conditions to cause more deformability of the green composites were found. Finally, in order to utilize such deformability, Lankford-values of the green composites were clarified, and deep drawing was carried out for sheet materials made of the green composites.

Dual-wavelength photo-Hall effect spectroscopy of deep levels in high resistive CdZnTe with negative differential photoconductivity

Science.gov (United States)

Musiienko, A.; Grill, R.; Moravec, P.; Korcsmáros, G.; Rejhon, M.; Pekárek, J.; Elhadidy, H.; Šedivý, L.; Vasylchenko, I.

2018-04-01

Photo-Hall effect spectroscopy was used in the study of deep levels in high resistive CdZnTe. The monochromator excitation in the photon energy range 0.65-1.77 eV was complemented by a laser diode high-intensity excitation at selected photon energies. A single sample characterized by multiple unusual features like negative differential photoconductivity and anomalous depression of electron mobility was chosen for the detailed study involving measurements at both the steady and dynamic regimes. We revealed that the Hall mobility and photoconductivity can be both enhanced and suppressed by an additional illumination at certain photon energies. The anomalous mobility decrease was explained by an excitation of the inhomogeneously distributed deep level at the energy Ev + 1.0 eV, thus enhancing potential non-uniformities. The appearance of negative differential photoconductivity was interpreted by an intensified electron occupancy of that level by a direct valence band-to-level excitation. Modified Shockley-Read-Hall theory was used for fitting experimental results by a model comprising five deep levels. Properties of the deep levels and their impact on the device performance were deduced.

The photonic nanowire: A highly efficient single-photon source

DEFF Research Database (Denmark)

Gregersen, Niels

2014-01-01

The photonic nanowire represents an attractive platform for a quantum light emitter. However, careful optical engineering using the modal method, which elegantly allows access to all relevant physical parameters, is crucial to ensure high efficiency.......The photonic nanowire represents an attractive platform for a quantum light emitter. However, careful optical engineering using the modal method, which elegantly allows access to all relevant physical parameters, is crucial to ensure high efficiency....

Highly efficient procedure for the transesterification of vegetable oil

Energy Technology Data Exchange (ETDEWEB)

Liang, Xuezheng; Gao, Shan; He, Mingyuan [Shanghai Key Laboratory of Green Chemistry and Chemical Process, Department of Chemistry, East China Normal University, Shanghai 200062 (China); Yang, Jianguo [Shanghai Key Laboratory of Green Chemistry and Chemical Process, Department of Chemistry, East China Normal University, Shanghai 200062 (China); Energy Institute, Department of Materials Science and Engineering, Pennsylvania State University, University Park, PA 16802 (United States)

2009-10-15

The highly efficient procedure has been developed for the synthesis of biodiesel from vegetable oil and methanol. The KF/MgO has been selected as the most efficient catalyst for the reactions with the yield of 99.3%. Operational simplicity, without need of the purification of raw vegetable oil, low cost of the catalyst used, high activities, no saponification and reusability are the key features of this methodology. (author)

Highly Flexible and Efficient Solar Steam Generation Device.

Science.gov (United States)

Chen, Chaoji; Li, Yiju; Song, Jianwei; Yang, Zhi; Kuang, Yudi; Hitz, Emily; Jia, Chao; Gong, Amy; Jiang, Feng; Zhu, J Y; Yang, Bao; Xie, Jia; Hu, Liangbing

2017-08-01

Solar steam generation with subsequent steam recondensation has been regarded as one of the most promising techniques to utilize the abundant solar energy and sea water or other unpurified water through water purification, desalination, and distillation. Although tremendous efforts have been dedicated to developing high-efficiency solar steam generation devices, challenges remain in terms of the relatively low efficiency, complicated fabrications, high cost, and inability to scale up. Here, inspired by the water transpiration behavior of trees, the use of carbon nanotube (CNT)-modified flexible wood membrane (F-Wood/CNTs) is demonstrated as a flexible, portable, recyclable, and efficient solar steam generation device for low-cost and scalable solar steam generation applications. Benefitting from the unique structural merits of the F-Wood/CNTs membrane-a black CNT-coated hair-like surface with excellent light absorbability, wood matrix with low thermal conductivity, hierarchical micro- and nanochannels for water pumping and escaping, solar steam generation device based on the F-Wood/CNTs membrane demonstrates a high efficiency of 81% at 10 kW cm -2 , representing one of the highest values ever-reported. The nature-inspired design concept in this study is straightforward and easily scalable, representing one of the most promising solutions for renewable and portable solar energy generation and other related phase-change applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High Efficiency S-Band 20 Watt Amplifier

Data.gov (United States)

National Aeronautics and Space Administration — This project includes the design and build of a prototype 20 W, high efficiency, S-Band amplifier.   The design will incorporate the latest semiconductor technology,...

Barriers and opportunities for labels for highly energy-efficient houses

International Nuclear Information System (INIS)

Mlecnik, Erwin; Visscher, Henk; Van Hal, Anke

2010-01-01

Promoting energy efficiency in the building sector is essential if the agreements of the Kyoto Protocol are to be honoured. Different initiatives for energy labelling of highly energy-efficient residential buildings have emerged throughout Europe as an essential method to stimulate market demand, to control grants or to ensure the quality of demonstration projects with excellent energy performance. The paper identifies the barriers and opportunities for the further diffusion of labels for highly energy-efficient houses. A model based on the theory of the diffusion of innovation is developed to analyse perceived attributes of existing European labels. The paper investigates the innovation characteristics of existing labels in Europe, with a focus on advanced countries. The question of compatibility with the development of the European Energy Performance of Buildings Directive (EPBD) is examined in detail. We found that the diffusion of emerging and already existing voluntary European labels for highly energy-efficient houses is needed. Their complexity can be lowered and relative advantage, trialability, observability, and compatibility can be increased. EPBD calculation procedures should be able to receive highly energy-efficient houses. In the framework of the recast of the EPBD, official recognition of existing voluntary labels is recommended. (author)

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology

Directory of Open Access Journals (Sweden)

Yuri Kravatsky

2017-11-01

Full Text Available The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs, requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s. Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s. The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi targets in human immunodeficiency virus 1 (HIV-1 subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

High Efficiency Heat Exchanger for High Temperature and High Pressure Applications

Energy Technology Data Exchange (ETDEWEB)

Sienicki, James J. [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division; Lv, Qiuping [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division; Moisseytsev, Anton [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division

2017-09-29

CompRex, LLC (CompRex) specializes in the design and manufacture of compact heat exchangers and heat exchange reactors for high temperature and high pressure applications. CompRex’s proprietary compact technology not only increases heat exchange efficiency by at least 25 % but also reduces footprint by at least a factor of ten compared to traditional shell-and-tube solutions of the same capacity and by 15 to 20 % compared to other currently available Printed Circuit Heat Exchanger (PCHE) solutions. As a result, CompRex’s solution is especially suitable for Brayton cycle supercritical carbon dioxide (sCO2) systems given its high efficiency and significantly lower capital and operating expenses. CompRex has already successfully demonstrated its technology and ability to deliver with a pilot-scale compact heat exchanger that was under contract by the Naval Nuclear Laboratory for sCO2 power cycle development. The performance tested unit met or exceeded the thermal and hydraulic specifications with measured heat transfer between 95 to 98 % of maximum heat transfer and temperature and pressure drop values all consistent with the modeled values. CompRex’s vision is to commercialize its compact technology and become the leading provider for compact heat exchangers and heat exchange reactors for various applications including Brayton cycle sCO2 systems. One of the limitations of the sCO2 Brayton power cycle is the design and manufacturing of efficient heat exchangers at extreme operating conditions. Current diffusion-bonded heat exchangers have limitations on the channel size through which the fluid travels, resulting in excessive solid material per heat exchanger volume. CompRex’s design allows for more open area and shorter fluid proximity for increased heat transfer efficiency while sustaining the structural integrity needed for the application. CompRex is developing a novel improvement to its current heat exchanger design where fluids are directed to alternating

High efficiency novel window air conditioner

International Nuclear Information System (INIS)

Bansal, Pradeep

2015-01-01

Highlights: • Use of novel refrigerant mixture of R32/R125 (85/15% molar conc.) to reduce global warming and improve energy efficiency. • Use of novel features such as electronically commuted motor (ECM) fan motor, slinger and sub-merged sub-cooler. • Energy savings of up to 0.1 Quads per year in USA and much more in Asia/Middle East where WACs are used in large numbers. • Payback period of only 1.4 years of the novel efficient WAC. - Abstract: This paper presents the results of an experimental and analytical evaluation of measures to raise the efficiency of window air conditioners (WAC). In order to achieve a higher energy efficiency ratio (EER), the original capacity of a baseline R410A unit was reduced by replacing the original compressor with a lower capacity but higher EER compressor, while all heat exchangers and the chassis from the original unit were retained. Subsequent major modifications included – replacing the alternating current fan motor with a brushless high efficiency electronically commutated motor (ECM) motor, replacing the capillary tube with a needle valve to better control the refrigerant flow and refrigerant set points, and replacing R410A with a ‘drop-in’ lower global warming potential (GWP) binary mixture of R32/R125 (85/15% molar concentration). All these modifications resulted in significant enhancement in the EER of the baseline WAC. Further, an economic analysis of the new WAC revealed an encouraging payback period

Compact high efficiency, light weight 200-800 MHz high power RF source

International Nuclear Information System (INIS)

Shrader, M.B.; Preist, D.H.

1985-01-01

There has long been a need for a new more efficient less bulky high power RF power source to drive accelerators in the 200 to 800 MHz region. Results on a recent 5-year EIMAC sponsored R and D program which have lead to the introduction of the Klystrode for UHF television and troposcatter applications indicate that at power levels of 1MW or more efficiencies in excess of 75% can be obtained at 450 MHz. Efficiencies of this order coupled with potential size and weight parameters which are a fraction of those of existing high power UHF generators open up new applications which heretofore would have been impractical if not impossible. Measurements at 470 MHz on existing Klystrodes are given. Projected operating conditions for a 1MW 450 MHz Klystrode having an overall length of 60 inches and a total tube, circuit, and magnet weight of 250 pounds is presented

Charged particle production in high Q deep-inelastic scattering at HERA

Science.gov (United States)

H1 Collaboration; Aaron, F. D.; Aktas, A.; Alexa, C.; Andreev, V.; Antunovic, B.; Aplin, S.; Asmone, A.; Astvatsatourov, A.; Backovic, S.; Baghdasaryan, A.; Baranov, P.; Barrelet, E.; Bartel, W.; Baudrand, S.; Beckingham, M.; Begzsuren, K.; Behnke, O.; Behrendt, O.; Belousov, A.; Berger, N.; Bizot, J. C.; Boenig, M.-O.; Boudry, V.; Bozovic-Jelisavcic, I.; Bracinik, J.; Brandt, G.; Brinkmann, M.; Brisson, V.; Bruncko, D.; Büsser, F. W.; Bunyatyan, A.; Buschhorn, G.; Bystritskaya, L.; Campbell, A. J.; Avila, K. B. Cantun; Cassol-Brunner, F.; Cerny, K.; Cerny, V.; Chekelian, V.; Cholewa, A.; Contreras, J. G.; Coughlan, J. A.; Cozzika, G.; Cvach, J.; Dainton, J. B.; Daum, K.; Deak, M.; de Boer, Y.; Delcourt, B.; Del Degan, M.; Delvax, J.; de Roeck, A.; de Wolf, E. A.; Diaconu, C.; Dodonov, V.; Dubak, A.; Eckerlin, G.; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Eliseev, A.; Elsen, E.; Essenov, S.; Falkiewicz, A.; Faulkner, P. J. W.; Favart, L.; Fedotov, A.; Felst, R.; Feltesse, J.; Ferencei, J.; Finke, L.; Fleischer, M.; Fomenko, A.; Franke, G.; Frisson, T.; Gabathuler, E.; Gayler, J.; Ghazaryan, S.; Ginzburgskaya, S.; Glazov, A.; Glushkov, I.; Goerlich, L.; Goettlich, M.; Gogitidze, N.; Gorbounov, S.; Gouzevitch, M.; Grab, C.; Greenshaw, T.; Gregori, M.; Grell, B. R.; Grindhammer, G.; Habib, S.; Haidt, D.; Hansson, M.; Heinzelmann, G.; Helebrant, C.; Henderson, R. C. W.; Henschel, H.; Herrera, G.; Hildebrandt, M.; Hiller, K. H.; Hoffmann, D.; Horisberger, R.; Hovhannisyan, A.; Hreus, T.; Jacquet, M.; Janssen, M. E.; Janssen, X.; Jemanov, V.; Jönsson, L.; Johnson, D. P.; Jung, A. W.; Jung, H.; Kapichine, M.; Katzy, J.; Kenyon, I. R.; Kiesling, C.; Klein, M.; Kleinwort, C.; Klimkovich, T.; Kluge, T.; Knutsson, A.; Korbel, V.; Kostka, P.; Kraemer, M.; Krastev, K.; Kretzschmar, J.; Kropivnitskaya, A.; Krüger, K.; Landon, M. P. J.; Lange, W.; Laštovička-Medin, G.; Laycock, P.; Lebedev, A.; Leibenguth, G.; Lendermann, V.; Levonian, S.; Li, G.; Lindfeld, L.; Lipka, K.; Liptaj, A.; List, B.; List, J.; Loktionova, N.; Lopez-Fernandez, R.; Lubimov, V.; Lucaci-Timoce, A.-I.; Lytkin, L.; Makankine, A.; Malinovski, E.; Marage, P.; Marti, Ll.; Martisikova, M.; Martyn, H.-U.; Maxfield, S. J.; Mehta, A.; Meier, K.; Meyer, A. B.; Meyer, H.; Meyer, H.; Meyer, J.; Michels, V.; Mikocki, S.; Milcewicz-Mika, I.; Mohamed, A.; Moreau, F.; Morozov, A.; Morris, J. V.; Mozer, M. U.; Müller, K.; Murín, P.; Nankov, K.; Naroska, B.; Naumann, Th.; Newman, P. R.; Niebuhr, C.; Nikiforov, A.; Nowak, G.; Nowak, K.; Nozicka, M.; Oganezov, R.; Olivier, B.; Olsson, J. E.; Osman, S.; Ozerov, D.; Palichik, V.; Panagoulias, I.; Pandurovic, M.; Papadopoulou, Th.; Pascaud, C.; Patel, G. D.; Peng, H.; Perez, E.; Perez-Astudillo, D.; Perieanu, A.; Petrukhin, A.; Picuric, I.; Piec, S.; Pitzl, D.; Plačakytė, R.; Polifka, R.; Povh, B.; Preda, T.; Prideaux, P.; Radescu, V.; Rahmat, A. J.; Raicevic, N.; Ravdandorj, T.; Reimer, P.; Risler, C.; Rizvi, E.; Robmann, P.; Roland, B.; Roosen, R.; Rostovtsev, A.; Rurikova, Z.; Rusakov, S.; Salek, D.; Salvaire, F.; Sankey, D. P. C.; Sauter, M.; Sauvan, E.; Schmidt, S.; Schmitt, S.; Schmitz, C.; Schoeffel, L.; Schöning, A.; Schultz-Coulon, H.-C.; Sefkow, F.; Shaw-West, R. N.; Sheviakov, I.; Shtarkov, L. N.; Sloan, T.; Smiljanic, I.; Smirnov, P.; Soloviev, Y.; South, D.; Spaskov, V.; Specka, A.; Staykova, Z.; Steder, M.; Stella, B.; Stiewe, J.; Straumann, U.; Sunar, D.; Sykora, T.; Tchoulakov, V.; Thompson, G.; Thompson, P. D.; Toll, T.; Tomasz, F.; Tran, T. H.; Traynor, D.; Trinh, T. N.; Truöl, P.; Tsakov, I.; Tseepeldorj, B.; Tsipolitis, G.; Tsurin, I.; Turnau, J.; Tzamariudaki, E.; Urban, K.; Utkin, D.; Valkárová, A.; Vallée, C.; van Mechelen, P.; Trevino, A. Vargas; Vazdik, Y.; Vinokurova, S.; Volchinski, V.; Weber, G.; Weber, R.; Wegener, D.; Werner, C.; Wessels, M.; Wissing, Ch.; Wolf, R.; Wünsch, E.; Xella, S.; Yeganov, V.; Žáček, J.; Zálešák, J.; Zhang, Z.; Zhelezov, A.; Zhokin, A.; Zhu, Y. C.; Zimmermann, T.; Zohrabyan, H.; Zomer, F.

2007-10-01

The average charged track multiplicity and the normalised distribution of the scaled momentum, x, of charged final state hadrons are measured in deep-inelastic ep scattering at high Q in the Breit frame of reference. The analysis covers the range of photon virtuality 100

Review of status developments of high-efficiency crystalline silicon solar cells

Science.gov (United States)

Liu, Jingjing; Yao, Yao; Xiao, Shaoqing; Gu, Xiaofeng

2018-03-01

In order to further improve cell efficiency and reduce cost in achieving grid parity, a large number of PV manufacturing companies, universities and research institutes have been devoted to a variety of low-cost and high-efficiency crystalline Si solar cells. In this article, the cell structures, characteristics and efficiency progresses of several types of high-efficiency crystalline Si solar cells that have been in small scale production or are promising in mass production are presented, including passivated emitter rear cell, tunnel oxide passivated contact solar cell, interdigitated back contact cell, heterojunction with intrinsic thin-layer cell, and heterojunction solar cells with interdigitated back contacts. Both the industrialization status and future development trend of high-efficiency crystalline silicon solar cells are also pinpointed.

Blanket options for high-efficiency fusion power

International Nuclear Information System (INIS)

Usher, J.L.; Lazareth, O.W.; Fillo, J.A.; Horn, F.L.; Powell, J.R.

1980-01-01

The efficiencies of blankets for fusion reactors are usually in the range of 30 to 40%, limited by the operating temperatures (500 0 C) of conventional structural materials such as stainless steels. In this project two-zone blankets are proposed; these blankets consist of a low-temperature shell surrounding a high-temperature interior zone. A survey of nucleonics and thermal hydraulic parameters has led to a reference blanket design consisting of a water-cooled stainless steel shell around a BeO, ZrO 2 interior (cooled by argon) utilizing Li 2 O for tritium breeding. In this design, approximately 60% of the fusion energy is deposited in the high-temperature interior. The maximum argon temperature is 2230 0 C leading to an overall efficiency estimate of 55 to 60% for this reference case

Fusion blankets for high-efficiency power cycles

International Nuclear Information System (INIS)

Usher, J.L.; Lazareth, O.W.; Fillo, J.A.; Horn, F.L.; Powell, J.R.

1980-01-01

The efficiencies of blankets for fusion reactors are usually in the range of 30 to 40%, limited by the operating temperatures (500 0 C) of conventional structural materials such as stainless steels. In this project two-zone blankets are proposed; these blankets consist of a low-temperature shell surrounding a high-temperature interior zone. A survey of nucleonics and thermal hydraulic parameters has led to a reference blanket design consisting of a water-cooled stainless steel shell around a BeO, ZrO 2 interior (cooled by argon) utilizing Li 2 O for tritium breeding. In this design, approximately 60% of the fusion energy is deposited in the high-temperature interior. The maximum argon temperature is 2230 0 C leading to an overall efficiency estimate of 55 to 60% for this reference case

Fusion blanket for high-efficiency power cycles

International Nuclear Information System (INIS)

Usher, J.L.; Powell, J.R.; Fillo, J.A.; Horn, F.L.; Lazareth, O.W.; Taussig, R.

1980-01-01

The efficiencies of blankets for fusion reactors are usually in the range of 30 to 40%, limited by the operating temperature (500 0 C) of conventional structural materials such as stainless steels. In this project two-zone blankets are proposed; these blankets consist of a low-temperature shell surrounding a high-temperature interior zone. A survey of nucleonics and thermal hydraulic parameters has led to a reference blanket design consisting of a water-cooled stainless steel shell around a BeO, ZrO 2 interior (cooled by Ar) utilizing Li 2 O for tritium breeding. In this design, approx. 60% of the fusion energy is deposited in the high-temperature interior. The maximum Ar temperature is 2230 0 C leading to an overall efficiency estimate of 55 to 60% for this reference case

Fusion blankets for high-efficiency power cycles

International Nuclear Information System (INIS)

Usher, J.L.; Lazareth, O.W.; Fillo, J.A.; Horn, F.L.; Powell, J.R.

1981-01-01

The efficiencies of blankets for fusion reactors are usually in the range of 30 to 40%, limited by the operating temperatures (500 deg C) of conventional structural materials such as stainless steels. In this project 'two-zone' blankets are proposed; these blankets consist of a low-temperature shell surrounding a high-temperature interior zone. A survey of nucleonics and thermal hydraulic parameters has led to a reference blanket design consisting of a water-cooled stainless steel shell around a BeO, ZrO 2 interior (cooled by argon) utilizing Li 2 O for tritium breeding. In this design, approximately 60% of the fusion energy is deposited in the high-temperature interior. The maximum argon temperature is 2230 deg C leading to an overall efficiency estimate of 55 to 60% for this reference case. (author)

Molecular Characterization of a Novel N-Acetylneuraminate Lyase from a Deep-Sea Symbiotic Mycoplasma

Directory of Open Access Journals (Sweden)

Shao-lu Wang

2018-03-01

Full Text Available N-acetylneuraminic acid (Neu5Ac based novel pharmaceutical agents and diagnostic reagents are highly required in medical fields. However, N-acetylneuraminate lyase（NAL）for Neu5Ac synthesis is not applicable for industry due to its low catalytic efficiency. In this study, we biochemically characterized a deep-sea NAL enzyme (abbreviated form: MyNal from a symbiotic Mycoplasma inhabiting the stomach of a deep-sea isopod, Bathynomus jamesi. Enzyme kinetic studies of MyNal showed that it exhibited a very low Km for both cleavage and synthesis activities compared to previously described NALs. Though it favors the cleavage process, MyNal out-competes the known NALs with respect to the efficiency of Neu5Ac synthesis and exhibits the highest kcat/Km values. High expression levels of recombinant MyNal could be achieved (9.56 mol L−1 culture with a stable activity in a wide pH (5.0–9.0 and temperature (40–60 °C range. All these features indicated that the deep-sea NAL has potential in the industrial production of Neu5Ac. Furthermore, we found that the amino acid 189 of MyNal (equivalent to Phe190 in Escherichia coli NAL, located in the sugar-binding domain, GX189DE, was also involved in conferring its enzymatic features. Therefore, the results of this study improved our understanding of the NALs from different environments and provided a model for protein engineering of NAL for biosynthesis of Neu5Ac.

DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM.

Science.gov (United States)

Wang, Feng; Gong, Huichao; Liu, Gaochao; Li, Meijing; Yan, Chuangye; Xia, Tian; Li, Xueming; Zeng, Jianyang

2016-09-01

Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated electron cryo-microscopy (cryo-EM). Here we report a deep learning framework, called DeepPicker, to address this problem and fill the current gaps toward a fully automated cryo-EM pipeline. DeepPicker employs a novel cross-molecule training strategy to capture common features of particles from previously-analyzed micrographs, and thus does not require any human intervention during particle picking. Tests on the recently-published cryo-EM data of three complexes have demonstrated that our deep learning based scheme can successfully accomplish the human-level particle picking process and identify a sufficient number of particles that are comparable to those picked manually by human experts. These results indicate that DeepPicker can provide a practically useful tool to significantly reduce the time and manual effort spent in single-particle analysis and thus greatly facilitate high-resolution cryo-EM structure determination. DeepPicker is released as an open-source program, which can be downloaded from https://github.com/nejyeah/DeepPicker-python. Copyright © 2016 Elsevier Inc. All rights reserved.

Fusion blanket high-temperature heat transfer

International Nuclear Information System (INIS)

Fillo, J.A.

1983-01-01

Deep penetration of 14 MeV neutrons makes two-temperature region blankets feasible. A relatively low-temperature (approx. 300 0 C) metallic structure is the vacuum/coolant pressure boundary, while the interior of the blanket, which is a simple packed bed of nonstructural material, operates at very high temperatures (>1000 0 C). The water-cooled shell structure is thermally insulated from the steam-cooled interior. High-temperature steam can dramatically increase the efficiency of electric power generation, as well as produce hydrogen and oxygen-based synthetic fuels at high-efficiency

Study of the earth's deep interior and crystallography. X-ray and neutron diffraction experiments under high pressures

International Nuclear Information System (INIS)

Yagi, Takehiko

2014-01-01

History of the study of the Earth's deep interior was reviewed. In order to understand Earth's deep interior from the view point of materials science, X-ray diffraction under high pressure and high temperature played very important role. Use of synchrotron radiation dramatically advanced this experimental technique and it is now possible to make precise X-ray study under the P-T conditions corresponding even to the center of the Earth. In order to clarify the behavior of light elements such as hydrogen, however, studies using neutron diffraction are also required. A new neutron beam line dedicated for high-pressure science is constructed at J-PARC and is now ready for use. (author)

Highly Efficient Spontaneous Emission from Self-Assembled Quantum Dots

DEFF Research Database (Denmark)

Johansen, Jeppe; Lund-Hansen, Toke; Hvam, Jørn Märcher

2006-01-01

We present time resolved measurements of spontaneous emission (SE) from InAs/GaAs quantum dots (QDs). The measurements are interpreted using Fermi's Golden Rule and from this analysis we establish the parameters for high quantum efficiency.......We present time resolved measurements of spontaneous emission (SE) from InAs/GaAs quantum dots (QDs). The measurements are interpreted using Fermi's Golden Rule and from this analysis we establish the parameters for high quantum efficiency....

High efficiency inverter and ballast circuits

International Nuclear Information System (INIS)

Nilssen, O.K.

1984-01-01

A high efficiency push-pull inverter circuit employing a pair of relatively high power switching transistors is described. The switching on and off of the transistors is precisely controlled to minimize power losses due to common-mode conduction or due to transient conditions that occur in the process of turning a transistor on or off. Two current feed-back transformers are employed in the transistor base drives; one being saturable for providing a positive feedback, and the other being non-saturable for providing a subtractive feedback

Highly efficient light management for perovskite solar cells.

Science.gov (United States)

Wang, Dong-Lin; Cui, Hui-Juan; Hou, Guo-Jiao; Zhu, Zhen-Gang; Yan, Qing-Bo; Su, Gang

2016-01-06

Organic-inorganic halide perovskite solar cells have enormous potential to impact the existing photovoltaic industry. As realizing a higher conversion efficiency of the solar cell is still the most crucial task, a great number of schemes were proposed to minimize the carrier loss by optimizing the electrical properties of the perovskite solar cells. Here, we focus on another significant aspect that is to minimize the light loss by optimizing the light management to gain a high efficiency for perovskite solar cells. In our scheme, the slotted and inverted prism structured SiO2 layers are adopted to trap more light into the solar cells, and a better transparent conducting oxide layer is employed to reduce the parasitic absorption. For such an implementation, the efficiency and the serviceable angle of the perovskite solar cell can be promoted impressively. This proposal would shed new light on developing the high-performance perovskite solar cells.

Development of a 200 W CW high efficiency traveling wave tube at 12 GHz. [for use in communication technology satellites

Science.gov (United States)

Christensen, J. A.; Tammaru, I.

1974-01-01

The design, development, and test results are reported for an experimental PPM focused, traveling-wave tube that produces 235 watts of CW RF power over 85 MHz centered at 12.080 GHz. The tube uses a coupled cavity RF circuit with a velocity taper for greater than 30 percent basic efficiency. Overall efficiency of 51 percent is achieved by means of a nine stage depressed collector designed at NASA Lewis Research Center. This collector is cooled by direct radiation to deep space.

Building Program Vector Representations for Deep Learning

OpenAIRE

Mou, Lili; Li, Ge; Liu, Yuxuan; Peng, Hao; Jin, Zhi; Xu, Yan; Zhang, Lu

2014-01-01

Deep learning has made significant breakthroughs in various fields of artificial intelligence. Advantages of deep learning include the ability to capture highly complicated features, weak involvement of human engineering, etc. However, it is still virtually impossible to use deep learning to analyze programs since deep architectures cannot be trained effectively with pure back propagation. In this pioneering paper, we propose the "coding criterion" to build program vector representations, whi...

Fracturing Fluid Leak-off for Deep Volcanic Rock in Zhungeer Basin: Mechanism and Control Method

Directory of Open Access Journals (Sweden)

Huang Bo

2017-01-01

Full Text Available The deep volcanic reservoir in Zhungeer Basin is buried in over 4000m depth, which is characterized by complex lithology (breccia, andesite, basalt, etc., high elastic modulus and massive natural fractures. During hydraulic fracturing, hydraulic fracture will propagate and natural fractures will be triggered by the increasing net pressure. However, the extension of fractures, especially natural fractures, would aggravate the leak-off effect of fracturing fluid, and consequently decrease the fracturing success rate. 4 out of 12 fracturing wells in the field have failed to add enough proppants due to fluid loss. In order to increase the success rate and efficiency of hydraulic fracturing for deep volcanic reservoir, based on theoretical and experimental method, the mechanism of fracturing fluid leak-off is deeply studied. We propose a dualistic proppant scheme and employ the fluid loss reducer to control the fluid leak-off in macro-fractures and micro-fractures respectively. The proposed technique remarkably improved the success rate in deep volcanic rock fracturing. It bears important theoretical value and practical significance to improve the hydraulic fracturing design for deep volcanic reservoir.

Design considerations of a MW-scale, high-efficiency, industrial-use, ultraviolet FEL amplifier

International Nuclear Information System (INIS)

Pagani, C.; Saldin, E.L.; Schneidmiller, E.A.; Yurkov, M.V.

2000-01-01

Theoretical and experimental work in free electron laser (FEL) physics, and the physics of particle accelerators over the last 10 years has pointed to the possibility of the generation of MW-level optical beams with laser-like characteristics in the ultraviolet (UV) spectral range. The concept is based on generation of the radiation in the master oscillator-power FEL amplifier (MOPA) configuration. The FEL amplifier concept eliminates the need for an optical cavity. As a result, there are no thermal loading limitations to increase the average output power of this device up to the MW-level. The problem of a tunable master oscillator can be solved with available conventional quantum lasers. The use of a superconducting energy-recovery linac could produce a major, cost-effective facility with wall plug power to output optical power efficiency of about 20% that spans wavelengths from the visible to the deep ultraviolet regime. The stringent electron beam qualities required for UV FEL amplifier operation can be met with a conservative injector design (using a conventional thermionic gun and subharmonic bunchers) and the beam compression and linear acceleration technology, recently developed in connection with high-energy linear collider and X-ray FEL programs

Dynamics of a Marine Turbine for Deep Ocean Currents

Directory of Open Access Journals (Sweden)

Ling-Yuan Chang

2016-09-01

Full Text Available For most of the ocean currents, such as the Kuroshio at east Taiwan, the Gulf Stream at east Florida and the Agulhas Current at southeast Africa, the depth of the seabed is generally deeper than one hundred meters, some waters of which can even reach one thousand meters. In such deep waters, the design of the turbine, as well as the anchoring system shall have special features so that existing ocean engineering technologies can be applied and the engineering cost can be lowered. Thus, as regards design, in addition to the analysis of the interaction between turbine and current, priority shall also be given to the design of the anchoring system of the turbine. To address the concerns, the authors propose an ocean turbine featured as follows: (1 it can be anchored in deep waters with a single cable; (2 it can generate high power in a current of moderate flow speed while producing low drag; (3 it can be self-balanced against current disturbance; (4 it is shrouded to enhance power efficiency; (5 the dynamic variations due to the interaction between the turbine and current are small. All of these features are confirmed with the computational results, leading to a detailed design of the turbine structure. If the easy-to-install high-efficiency shrouded turbines, having the capability to self-balance and requiring minimum maintenance effort, are successfully developed, the power supply pressure in Taiwan can be greatly alleviated. The Kuroshio was chosen as the typical current for the present dynamic analysis because, firstly, the flow characteristics of Kuroshio are similar to those of other large-scale currents mentioned above, and secondly, the data of Kuroshio are highly available to us so that a thorough analysis can be done.

Streptavidin-functionalized capillary immune microreactor for highly efficient chemiluminescent immunoassay

Energy Technology Data Exchange (ETDEWEB)

Yang Zhanjun [State Key Laboratory of Analytical Chemistry for Life Science, Department of Chemistry, Nanjing University, Nanjing 210093 (China); College of Chemistry and Engineering, Yangzhou University, 88 South University Avenue, Yangzhou 225002 (China); Zong Chen [State Key Laboratory of Analytical Chemistry for Life Science, Department of Chemistry, Nanjing University, Nanjing 210093 (China); Ju Huangxian, E-mail: hxju@nju.edu.cn [State Key Laboratory of Analytical Chemistry for Life Science, Department of Chemistry, Nanjing University, Nanjing 210093 (China); Yan Feng, E-mail: yanfeng2007@sohu.com [Jiangsu Institute of Cancer Prevention and Cure, Nanjing 210009 (China)

2011-11-07

Highlights: {yields} A novel capillary immune microreactor was proposed for highly efficient flow-through chemiluminescent immunoassay. {yields} The microreactor was prepared by functionalizing capillary inner wall with streptavidin for capture of biotinylated antibody. {yields} The proposed immunoassay method showed wide dynamic range, good reproducibility, stability and practicality. {yields} The microreactor was low-cost and disposable, and possessed several advantages over the conventional immunoreactors. - Abstract: A streptavidin functionalized capillary immune microreactor was designed for highly efficient flow-through chemiluminescent (CL) immunoassay. The functionalized capillary could be used as both a support for highly efficient immobilization of antibody and a flow cell for flow-through immunoassay. The functionalized inner wall and the capture process were characterized using scanning electron microscopy. Compared to conventional packed tube or thin-layer cell immunoreactor, the proposed microreactor showed remarkable properties such as lower cost, simpler fabrication, better practicality and wider dynamic range for fast CL immunoassay with good reproducibility and stability. Using {alpha}-fetoprotein as model analyte, the highly efficient CL flow-through immunoassay system showed a linear range of 3 orders of magnitude from 0.5 to 200 ng mL{sup -1} and a low detection limit of 0.1 ng mL{sup -1}. The capillary immune microreactor could make up the shortcoming of conventional CL immunoreactors and provided a promising alternative for highly efficient flow-injection immunoassay.

High efficiency, monolithic fiber chirped pulse amplification system for high energy femtosecond pulse generation.

Science.gov (United States)

Peng, Xiang; Kim, Kyungbum; Mielke, Michael; Jennings, Stephen; Masor, Gordon; Stohl, Dave; Chavez-Pirson, Arturo; Nguyen, Dan T; Rhonehouse, Dan; Zong, Jie; Churin, Dmitriy; Peyghambarian, N

2013-10-21

A novel monolithic fiber-optic chirped pulse amplification (CPA) system for high energy, femtosecond pulse generation is proposed and experimentally demonstrated. By employing a high gain amplifier comprising merely 20 cm of high efficiency media (HEM) gain fiber, an optimal balance of output pulse energy, optical efficiency, and B-integral is achieved. The HEM amplifier is fabricated from erbium-doped phosphate glass fiber and yields gain of 1.443 dB/cm with slope efficiency >45%. We experimentally demonstrate near diffraction-limited beam quality and near transform-limited femtosecond pulse quality at 1.55 µm wavelength. With pulse energy >100 µJ and pulse duration of 636 fs (FWHM), the peak power is estimated to be ~160 MW. NAVAIR Public Release Distribution Statement A-"Approved for Public release; distribution is unlimited".

Metallic metasurfaces for high efficient polarization conversion control in transmission mode.

Science.gov (United States)

Li, Tong; Hu, Xiaobin; Chen, Huamin; Zhao, Chen; Xu, Yun; Wei, Xin; Song, Guofeng

2017-10-02

A high efficient broadband polarization converter is an important component in integrated miniaturized optical systems, but its performances is often restricted by the material structures, metallic metasurfaces for polarization control in transmission mode never achieved efficiency above 0.5. Herein, we theoretically demonstrate that metallic metasurfaces constructed by thick cross-shaped particles can realize a high efficient polarization transformation over a broadband. We investigated the resonant properties of designed matesurfaces and found that the interaction between double FP cavity resonances and double bulk magnetic resonances is the main reason to generate a high transmissivity over a broadband. In addition, through using four resonances effect and tuning the anisotropic optical response, we realized a high efficient (> 0.85) quarter-wave plate at the wavelength range from 1175nm to 1310nm and a high efficient (> 0.9) half-wave plate at the wavelength range from 1130nm to 1230nm. The proposed polarization converters may have many potential applications in integrated polarization conversion devices and optical data storage systems.

Investigation on the Potential of High Efficiency for Internal Combustion Engines

Directory of Open Access Journals (Sweden)

Haifeng Liu

2018-02-01

Full Text Available The current brake thermal efficiency of advanced internal combustion engines is limited to 50%, and how to further improve the efficiency is a challenge. In this study, a theoretical investigation on engine thermal efficiency was carried out using one-dimension simulations based on the first law of thermodynamics. The energy balance was evaluated by varying parameters such as compression ratio (CR; heat transfer coefficient; intake charge properties; and combustion phasing etc.—their influences on the efficiency limits were demonstrated. Results show that for a given heat transfer coefficient, an optimal CR exists to obtain the peak efficiency. The optimal CR decreases with the increase of heat transfer coefficient, and high CR with a low heat-transfer coefficient can achieve a significantly high efficiency. A higher density and specific heat ratio of intake charge, as well as a shorter combustion duration with a proper CA50 (crank angle at 50% of total heat release, can increase efficiency significantly. Methanol shows an excellent ability in decreasing the peak in-cylinder temperature; and the peak indicated efficiency is relatively higher than other tested fuels. The displacement has few effects on the indicated efficiency, while it shows a strong effect on the energy distribution between heat transfer and exhaust energy. All these strategies with high CR result in high in-cylinder pressure and temperature; which means a breakthrough of material is needed in the future.

Large-scale transportation network congestion evolution prediction using deep learning theory.

Science.gov (United States)

Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

2015-01-01

Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

Deep Unconventional Geothermal Resources: a major opportunity to harness new sources of sustainable energy

Energy Technology Data Exchange (ETDEWEB)

Fridleifsson, G.O.; Albertsson, A.; Stefansson, B.; Gunnlaugsson, E.; Adalsteinsson, H.

2007-07-01

The Iceland Deep Drilling Project (IDDP) is a long-term program to improve the efficiency and economics of geothermal energy by harnessing Deep Unconventional Geothermal Resources (DUGR). Its aim is to produce electricity from natural supercritical hydrous fluids from drillable depths. Producing supercritical fluids will require drilling wells and sampling fluids and rocks to depths of 3.5 to 5 km, and at temperatures of 450-600{sup o}C. The long-term plan is to drill and test a series of such deep boreholes in Iceland at the Krafla, the Hengill, and the Reykjanes high temperature geothermal systems. Beneath these three developed drill fields temperatures should exceed 550-650{sup o}C, and the occurrence of frequent seismic activity below 5 km, indicates that the rocks are brittle and therefore likely to be permeable. Modeling indicates that if the wellhead enthalpy is to exceed that of conventionally produced geothermal steam, the reservoir temperature must be higher than 450{sup o}C. A deep well producing 0.67 m3/sec steam ({approx}2400 m3/h) from a reservoir with a temperature significantly above 450{sup o}C could yield enough high-enthalpy steam to generate 40-50 MW of electric power. This exceeds by an order of magnitude the power typically obtained from conventional geothermal wells. (auth)

Hot, deep origin of petroleum: deep basin evidence and application

Science.gov (United States)

Price, Leigh C.

1978-01-01

Use of the model of a hot deep origin of oil places rigid constraints on the migration and entrapment of crude oil. Specifically, oil originating from depth migrates vertically up faults and is emplaced in traps at shallower depths. Review of petroleum-producing basins worldwide shows oil occurrence in these basins conforms to the restraints of and therefore supports the hypothesis. Most of the world's oil is found in the very deepest sedimentary basins, and production over or adjacent to the deep basin is cut by or directly updip from faults dipping into the basin deep. Generally the greater the fault throw the greater the reserves. Fault-block highs next to deep sedimentary troughs are the best target areas by the present concept. Traps along major basin-forming faults are quite prospective. The structural style of a basin governs the distribution, types, and amounts of hydrocarbons expected and hence the exploration strategy. Production in delta depocenters (Niger) is in structures cut by or updip from major growth faults, and structures not associated with such faults are barren. Production in block fault basins is on horsts next to deep sedimentary troughs (Sirte, North Sea). In basins whose sediment thickness, structure and geologic history are known to a moderate degree, the main oil occurrences can be specifically predicted by analysis of fault systems and possible hydrocarbon migration routes. Use of the concept permits the identification of significant targets which have either been downgraded or ignored in the past, such as production in or just updip from thrust belts, stratigraphic traps over the deep basin associated with major faulting, production over the basin deep, and regional stratigraphic trapping updip from established production along major fault zones.

High-concentration planar microtracking photovoltaic system exceeding 30% efficiency

Science.gov (United States)

Price, Jared S.; Grede, Alex J.; Wang, Baomin; Lipski, Michael V.; Fisher, Brent; Lee, Kyu-Tae; He, Junwen; Brulo, Gregory S.; Ma, Xiaokun; Burroughs, Scott; Rahn, Christopher D.; Nuzzo, Ralph G.; Rogers, John A.; Giebink, Noel C.

2017-08-01

Prospects for concentrating photovoltaic (CPV) power are growing as the market increasingly values high power conversion efficiency to leverage now-dominant balance of system and soft costs. This trend is particularly acute for rooftop photovoltaic power, where delivering the high efficiency of traditional CPV in the form factor of a standard rooftop photovoltaic panel could be transformative. Here, we demonstrate a fully automated planar microtracking CPV system 660× concentration ratio over a 140∘ full field of view. In outdoor testing over the course of two sunny days, the system operates automatically from sunrise to sunset, outperforming a 17%-efficient commercial silicon solar cell by generating >50% more energy per unit area per day in a direct head-to-head competition. These results support the technical feasibility of planar microtracking CPV to deliver a step change in the efficiency of rooftop solar panels at a commercially relevant concentration ratio.

High Efficiency Reversible Fuel Cell Power Converter

DEFF Research Database (Denmark)

Pittini, Riccardo

as well as different dc-ac and dc-dc converter topologies are presented and analyzed. A new ac-dc topology for high efficiency data center applications is proposed and an efficiency characterization based on the fuel cell stack I-V characteristic curve is presented. The second part discusses the main...... converter components. Wide bandgap power semiconductors are introduced due to their superior performance in comparison to traditional silicon power devices. The analysis presents a study based on switching loss measurements performed on Si IGBTs, SiC JFETs, SiC MOSFETs and their respective gate drivers...

Charge deep-level transient spectroscopy study of high-energy-electron-beam-irradiated hydrogenated amorphous silicon

NARCIS (Netherlands)

Klaver, A.; Nádaždy, V.; Zeman, M.; Swaaiij, R.A.C.M.M.

2006-01-01

We present a study of changes in the defect density of states in hydrogenated amorphous silicon (a-Si:H) due to high-energy electron irradiation using charged deep-level transient spectroscopy. It was found that defect states near the conduction band were removed, while in other band gap regions the

High efficiency USC power plant - present status and future potential

Energy Technology Data Exchange (ETDEWEB)

Blum, R [Faelleskemikerne I/S Fynsvaerket (Denmark); Hald, J [Elsam/Elkraft/TU Denmark (Denmark)

1999-12-31

Increasing demand for energy production with low impact on the environment and minimised fuel consumption can be met with high efficient coal fired power plants with advanced steam parameters. An important key to this improvement is the development of high temperature materials with optimised mechanical strength. Based on the results of more than ten years of development a coal fired power plant with an efficiency above 50 % can now be realised. Future developments focus on materials which enable an efficiency of 52-55 %. (orig.) 25 refs.

High efficiency USC power plant - present status and future potential

Energy Technology Data Exchange (ETDEWEB)

Blum, R. [Faelleskemikerne I/S Fynsvaerket (Denmark); Hald, J. [Elsam/Elkraft/TU Denmark (Denmark)

1998-12-31

Increasing demand for energy production with low impact on the environment and minimised fuel consumption can be met with high efficient coal fired power plants with advanced steam parameters. An important key to this improvement is the development of high temperature materials with optimised mechanical strength. Based on the results of more than ten years of development a coal fired power plant with an efficiency above 50 % can now be realised. Future developments focus on materials which enable an efficiency of 52-55 %. (orig.) 25 refs.

Prediction of pressure between packers of staged fracturing pipe strings in high-pressure deep wells and its application

Directory of Open Access Journals (Sweden)

Fuxiang Zhang

2015-03-01

Full Text Available Addressing to the deteriorated load conditions of working string and packers caused by annular pressure drop between packers during the staged stimulation of high-pressure deep well, one 2D temperature field transient prediction model for borehole under injecting conditions which considers such influences as friction heat, convection heat exchange was set up, based on energy conservation principle and borehole heat transfer theory. By means of analyzing the influences of borehole temperature and pressure changes on the annular volume between packers, and in combination with borehole temperature transient prediction model, annular fluid PVT equations of state, radial deformation model of tubing and formation transient seepage equation, a typical high-pressure deep well inter-packer annular pressure prediction model was established. Taking a high-pressure gas well in Tarim Oilfield for example, the inter-packer annular pressure prediction was conducted, on which, the mechanical analysis on packers and working strings was carried out. The analysis results show that although the pipe string is safe in the viewpoint of conventional design methods, it is still susceptible to failure after the annular pressure drop between packers was taken into consideration. Such factor should be fully considered in the design of staged stimulation pipe strings, and this prediction model provides new thoughts for the optimal design of high-pressure deep well staged stimulation pipe strings.

Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

OpenAIRE

Li, Xiangang; Wu, Xihong

2014-01-01

Long short-term memory (LSTM) based acoustic modeling methods have recently been shown to give state-of-the-art performance on some speech recognition tasks. To achieve a further performance improvement, in this research, deep extensions on LSTM are investigated considering that deep hierarchical model has turned out to be more efficient than a shallow one. Motivated by previous research on constructing deep recurrent neural networks (RNNs), alternative deep LSTM architectures are proposed an...

The analysis of energy efficiency in water electrolysis under high temperature and high pressure

Science.gov (United States)

Hourng, L. W.; Tsai, T. T.; Lin, M. Y.

2017-11-01

This paper aims to analyze the energy efficiency of water electrolysis under high pressure and high temperature conditions. The effects of temperature and pressure on four different kinds of reaction mechanisms, namely, reversible voltage, activation polarization, ohmic polarization, and concentration polarization, are investigated in details. Results show that the ohmic and concentration over-potentials are increased as temperature is increased, however, the reversible and activation over-potentials are decreased as temperature is increased. Therefore, the net efficiency is enhanced as temperature is increased. The efficiency of water electrolysis at 350°C/100 bars is increased about 17%, compared with that at 80°C/1bar.

Coordinated motility of cyanobacteria favor mat formation, photosynthesis and carbon burial in low-oxygen, high-sulfur shallow sinkholes of Lake Huron; whereas deep-water aphotic sinkholes are analogs of deep-sea seep and vent ecosystems

Science.gov (United States)

Biddanda, B. A.; McMillan, A. C.; Long, S. A.; Snider, M. J.; Weinke, A. D.; Dick, G.; Ruberg, S. A.

2016-02-01

Microbial life in submerged sinkhole ecosystems of the Laurentian Great Lakes is relatively understudied in comparison to seeps and vents of the deep-sea. We studied the filamentous benthic mat-forming cyanobacteria consisting primarily of Oscillatoria-like cells growing under low-light, low-oxygen and high-sulfur conditions in Lake Huron's submerged sinkholes using in situ observations, in vitro measurements and time-lapse microscopy. Gliding movement of the cyanobacterial trichomes revealed individual as well as group-coordinated motility. When placed in a petri dish and dispersed in ground water from the sinkhole, filaments re-aggregated into defined colonies within minutes. Measured speed of individual filaments ranged from 50 µm minute-1 or 15 body lengths minute-1 to 215 µm minute-1 or 70 body lengths minute-1 - rates that are rapid relative to non-flagellated/ciliated microbes. Filaments exhibited precise and coordinated positive phototaxis towards pinpoints of light and congregated under the light of foil cutouts. Such light-responsive clusters showed an increase in photosynthetic yield - suggesting phototactic motility aids in light acquisition as well as photosynthesis. Pebbles and pieces of broken shells placed upon the mat in intact sediemnt cores were quickly covered by vertically motile filaments within hours and became fully buried in the anoxic sediments over 3-4 diurnal cycles - likely facilitating the preservation of falling plankton debris. Coordinated horizontal and vertical filament motility optimize mat cohesion and dynamics, photosynthetic efficiency and sedimentary carbon burial in modern-day sinkhole habitats where life operates across sharp redox gradients. Analogous cyanobacterial motility in the shallow seas during Earth's early history, may have played a key role in the oxygenation of the planet by optimizing photosynthesis while favoring carbon burial. We are now eagerly mapping and exploring life in deep-water aphotic sinkholes of

Evaluating performance of high efficiency mist eliminators

Energy Technology Data Exchange (ETDEWEB)

Waggoner, Charles A.; Parsons, Michael S.; Giffin, Paxton K. [Mississippi State University, Institute for Clean Energy Technology, 205 Research Blvd, Starkville, MS (United States)

2013-07-01

Processing liquid wastes frequently generates off gas streams with high humidity and liquid aerosols. Droplet laden air streams can be produced from tank mixing or sparging and processes such as reforming or evaporative volume reduction. Unfortunately these wet air streams represent a genuine threat to HEPA filters. High efficiency mist eliminators (HEME) are one option for removal of liquid aerosols with high dissolved or suspended solids content. HEMEs have been used extensively in industrial applications, however they have not seen widespread use in the nuclear industry. Filtering efficiency data along with loading curves are not readily available for these units and data that exist are not easily translated to operational parameters in liquid waste treatment plants. A specialized test stand has been developed to evaluate the performance of HEME elements under use conditions of a US DOE facility. HEME elements were tested at three volumetric flow rates using aerosols produced from an iron-rich waste surrogate. The challenge aerosol included submicron particles produced from Laskin nozzles and super micron particles produced from a hollow cone spray nozzle. Test conditions included ambient temperature and relative humidities greater than 95%. Data collected during testing HEME elements from three different manufacturers included volumetric flow rate, differential temperature across the filter housing, downstream relative humidity, and differential pressure (dP) across the filter element. Filter challenge was discontinued at three intermediate dPs and the filter to allow determining filter efficiency using dioctyl phthalate and then with dry surrogate aerosols. Filtering efficiencies of the clean HEME, the clean HEME loaded with water, and the HEME at maximum dP were also collected using the two test aerosols. Results of the testing included differential pressure vs. time loading curves for the nine elements tested along with the mass of moisture and solid

Design of High Efficiency Illumination for LED Lighting

Directory of Open Access Journals (Sweden)

Yong-Nong Chang

2013-01-01

Full Text Available A high efficiency illumination for LED street lighting is proposed. For energy saving, this paper uses Class-E resonant inverter as main electric circuit to improve efficiency. In addition, single dimming control has the best efficiency, simplest control scheme and lowest circuit cost among other types of dimming techniques. Multiple serial-connected transformers used to drive the LED strings as they can provide galvanic isolation and have the advantage of good current distribution against device difference. Finally, a prototype circuit for driving 112 W LEDs in total was built and tested to verify the theoretical analysis.

The Energy Efficiency of High Intensity Proton Driver Concepts

Energy Technology Data Exchange (ETDEWEB)

Yakovlev, Vyacheslav [Fermilab; Grillenberger, Joachim [PSI, Villigen; Kim, Sang-Ho [ORNL, Oak Ridge (main); Seidel, Mike [PSI, Villigen; Yoshii, Masahito [JAEA, Ibaraki

2017-05-01

For MW class proton driver accelerators the energy efficiency is an important aspect; the talk reviews the efficiency of different accelerator concepts including s.c./n.c. linac, rapid cycling synchrotron, cyclotron; the potential of these concepts for very high beam power is discussed.

Overview of deep learning in medical imaging.

Science.gov (United States)

Suzuki, Kenji

2017-09-01

The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a

High-Tech Means High-Efficiency: The Business Case for EnergyManagement in High-Tech Industries

Energy Technology Data Exchange (ETDEWEB)

Shanshoian, Gary; Blazek, Michele; Naughton, Phil; Seese, RobertS.; Mills, Evan; Tschudi, William

2005-11-15

In the race to apply new technologies in ''high-tech'' facilities such as data centers, laboratories, and clean rooms, much emphasis has been placed on improving service, building capacity, and increasing speed. These facilities are socially and economically important, as part of the critical infrastructure for pharmaceuticals,electronics, communications, and many other sectors. With a singular focus on throughput, some important design issues can be overlooked, such as the energy efficiency of individual equipment (e.g., lasers, routers and switches) as well as the integration of high-tech equipment into the power distribution system and the building envelope. Among technology-based businesses, improving energy efficiency presents an often untapped opportunity to increase profits, enhance process control,maximize asset value, improve the work place environment, and manage a variety of business risks. Oddly enough, the adoption of energy efficiency improvements in this sector lags behind many others. As a result, millions of dollars are left on the table with each year ofoperation.

A high efficiency hybrid stirling-pulse tube cryocooler

Directory of Open Access Journals (Sweden)

Xiaotao Wang

2015-03-01

Full Text Available This article presented a hybrid cryocooler which combines the room temperature displacers and the pulse tube in one system. Compared with a traditional pulse tube cryocooler, the system uses the rod-less ambient displacer to recover the expansion work from the pulse tube cold end to improve the efficiency while still keeps the advantage of the pulse tube cryocooler with no moving parts at the cold region. In the meantime, dual-opposed configurations for both the compression pistons and displacers reduce the cooler vibration to a very low level. In the experiments, a lowest no-load temperature of 38.5 K has been obtained and the cooling power at 80K was 26.4 W with an input electric power of 290 W. This leads to an efficiency of 24.2% of Carnot, marginally higher than that of an ordinary pulse tube cryocooler. The hybrid configuration herein provides a very competitive option when a high efficiency, high-reliability and robust cryocooler is desired.

Highly efficient green light harvesting from Mg doped ZnO nanoparticles: Structural and optical studies

Energy Technology Data Exchange (ETDEWEB)

Sharma, Sarla, E-mail: mail2sarlasharma@gmail.com [Department of Physics, University of Rajasthan, Jaipur 302055 (India); Vyas, Rishi [Department of Physics, Malaviya National Institute of Technology, Jaipur 302017 (India); Sharma, Neha [Department of Physics, University of Rajasthan, Jaipur 302055 (India); Singh, Vidyadhar [Okinawa Institute of Science and Technology, Graduate University, Okinawa 9040495 (Japan); Singh, Arvind [Department of Physics, Institute of Chemical Technology, Mumbai 400 019 (India); Kataria, Vanjula; Gupta, Bipin Kumar [National Physical Laboratory (CSIR), New Delhi 110012 (India); Vijay, Y.K. [Department of Physics, University of Rajasthan, Jaipur 302055 (India)

2013-03-05

Graphical abstract: Demonstration of highly efficient green light emission harvesting from Mg doped ZnO nanoparticles were synthesized via facile wet chemical route with an average particle size ∼15 nm. The resulted nanoparticles exhibit intense green emission peaking at 530 nm upon 325 nm excitation. The photoluminescence (PL) intensity of visible emission depends upon the doping concentration of Mg. The PL intensity was found maximum up to 4% doping of Mg and beyond it exhibits a decrees in emission. The obtained highly luminescent green emission of ZnO nanoparticle would be an ultimate choice for next generation optoelectronics device materials. Highlights: ► Zn{sub 1−x}Mg{sub x}O nanoparticles were prepared by mechanochemical processing. ► High blue emission intensity was observed contrary to previous reports. ► Blue emission is suggested to be originating from the high density of defects. ► Defect density in as-milled condition is very high resulting in high emission. ► Mg promoted non-radiative recombination and lowered intensities. -- Abstract: Highly efficient green light emission was observed from Mg doped ZnO nanoparticles synthesized via facile wet chemical route with an average particle size ∼15 nm. The XRD analysis confirmed the growth of wurtzite phase of ZnO nanoparticles. Moreover, the optical properties of these nanoparticles were investigated by different spectroscopic techniques. The resulted nanoparticles exhibit intense green emission peaking at 530 nm (2.34 eV) upon 325 nm (3.81 eV) excitation. The photoluminescence (PL) intensity of visible emission depends upon the doping concentration of Mg. The PL intensity was found maximum up to 4% doping of Mg, and beyond it exhibits a decrees in emission. Furthermore, by varying the band gap from 3.50 to 3.61 eV, the PL spectra showed a near band edge (NBE) emission at wavelength around 370 nm (3.35 eV) and a broad deep level emission in the visible region. The obtained highly

Deep Visual Attention Prediction

Science.gov (United States)

Wang, Wenguan; Shen, Jianbing

2018-05-01

In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

Lightweight High Efficiency Electric Motors for Space Applications

Science.gov (United States)

Robertson, Glen A.; Tyler, Tony R.; Piper, P. J.

2011-01-01

Lightweight high efficiency electric motors are needed across a wide range of space applications from - thrust vector actuator control for launch and flight applications to - general vehicle, base camp habitat and experiment control for various mechanisms to - robotics for various stationary and mobile space exploration missions. QM Power?s Parallel Path Magnetic Technology Motors have slowly proven themselves to be a leading motor technology in this area; winning a NASA Phase II for "Lightweight High Efficiency Electric Motors and Actuators for Low Temperature Mobility and Robotics Applications" a US Army Phase II SBIR for "Improved Robot Actuator Motors for Medical Applications", an NSF Phase II SBIR for "Novel Low-Cost Electric Motors for Variable Speed Applications" and a DOE SBIR Phase I for "High Efficiency Commercial Refrigeration Motors" Parallel Path Magnetic Technology obtains the benefits of using permanent magnets while minimizing the historical trade-offs/limitations found in conventional permanent magnet designs. The resulting devices are smaller, lower weight, lower cost and have higher efficiency than competitive permanent magnet and non-permanent magnet designs. QM Power?s motors have been extensively tested and successfully validated by multiple commercial and aerospace customers and partners as Boeing Research and Technology. Prototypes have been made between 0.1 and 10 HP. They are also in the process of scaling motors to over 100kW with their development partners. In this paper, Parallel Path Magnetic Technology Motors will be discussed; specifically addressing their higher efficiency, higher power density, lighter weight, smaller physical size, higher low end torque, wider power zone, cooler temperatures, and greater reliability with lower cost and significant environment benefit for the same peak output power compared to typically motors. A further discussion on the inherent redundancy of these motors for space applications will be provided.

Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning.

Science.gov (United States)

Sadeghi, Zahra; Testolin, Alberto

2017-08-01

In humans, efficient recognition of written symbols is thought to rely on a hierarchical processing system, where simple features are progressively combined into more abstract, high-level representations. Here, we present a computational model of Persian character recognition based on deep belief networks, where increasingly more complex visual features emerge in a completely unsupervised manner by fitting a hierarchical generative model to the sensory data. Crucially, high-level internal representations emerging from unsupervised deep learning can be easily read out by a linear classifier, achieving state-of-the-art recognition accuracy. Furthermore, we tested the hypothesis that handwritten digits and letters share many common visual features: A generative model that captures the statistical structure of the letters distribution should therefore also support the recognition of written digits. To this aim, deep networks trained on Persian letters were used to build high-level representations of Persian digits, which were indeed read out with high accuracy. Our simulations show that complex visual features, such as those mediating the identification of Persian symbols, can emerge from unsupervised learning in multilayered neural networks and can support knowledge transfer across related domains.

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality.

Science.gov (United States)

Li, Zhongyu; Butler, Erik; Li, Kang; Lu, Aidong; Ji, Shuiwang; Zhang, Shaoting

2018-02-12

Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i.e., stacked convolutional autoencoders (SCAEs). The deep features are subsequently fused with the hand-crafted features for more accurate representation. Considering the exhaustive search is usually very time-consuming in large-scale databases, we employ a novel binary coding method to compress feature vectors into short binary codes. Our framework is validated on a public data set including 58,000 neurons, showing promising retrieval precision and efficiency compared with state-of-the-art methods. In addition, we develop a novel neuron visualization program based on the techniques of augmented reality (AR), which can help users take a deep exploration of neuron morphologies in an interactive and immersive manner.

Inclusive gluon production in deep inelastic scattering at high parton density

International Nuclear Information System (INIS)

Kovchegov, Yuri V.; Tuchin, Kirill

2002-01-01

We calculate the cross section of single inclusive gluon production in deep inelastic scattering at very high energies in the saturation regime, where the parton densities inside hadrons and nuclei are large and the evolution of structure functions with energy is nonlinear. The expression we obtain for the inclusive gluon production cross section is generated by this nonlinear evolution. We analyze the rapidity distribution of the produced gluons as well as their transverse momentum spectrum given by the derived expression for the inclusive cross section. We propose an ansatz for the multiplicity distribution of gluons produced in nuclear collisions which includes the effects of nonlinear evolution in both colliding nuclei

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

OpenAIRE

Neftci, Emre O.; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of net...

Summary of efficiency testing of standard and high-capacity high-efficiency particulate air filters subjected to simulated tornado depressurization and explosive shock waves

International Nuclear Information System (INIS)

Smith, P.R.; Gregory, W.S.

1985-04-01

Pressure transients in nuclear facility air cleaning systems can originate from natural phenomena such as tornadoes or from accident-induced explosive blast waves. This study was concerned with the effective efficiency of high-efficiency particulate air (HEPA) filters during pressure surges resulting from simulated tornado and explosion transients. The primary objective of the study was to examine filter efficiencies at pressure levels below the point of structural failure. Both standard and high-capacity 0.61-m by 0.61-m HEPA filters were evaluated, as were several 0.2-m by 0.2-m HEPA filters. For a particular manufacturer, the material release when subjected to tornado transients is the same (per unit area) for both the 0.2-m by 0.2-m and the 0.61-m by 0.61-m filters. For tornado transients, the material release was on the order of micrograms per square meter. When subjecting clean HEPA filters to simulated tornado transients with aerosol entrained in the pressure pulse, all filters tested showed a degradation of filter efficiency. For explosive transients, the material release from preloaded high-capacity filters was as much as 340 g. When preloaded high-capacity filters were subjected to shock waves approximately 50% of the structural limit level, 1 to 2 mg of particulate was released

High-efficiency single-photon source: The photonic wire geometry

DEFF Research Database (Denmark)

Claudon, J.; Bazin, Maela; Malik, Nitin S.

2009-01-01

We present a single-photon-source design based on the emission of a quantum dot embedded in a semiconductor (GaAs) nanowire. The nanowire ends are engineered (efficient metallic mirror and tip taper) to reach a predicted record-high collection efficiency of 90% with a realistic design. Preliminar...

High-efficiency FEL with Bragg resonator driven by linear induction accelerator

Energy Technology Data Exchange (ETDEWEB)

Ginzburg, N S; Kaminskij, A A; Kaminskij, A K; Peskov, N Yu; Sedykh, S N; Sergeev, A P; Sergeev, A S [Russian Academy of Sciences, Nizhny Novgorod (Russian Federation). Inst. of Applied Physics

1997-12-31

A narrow-band high-efficiency FEL-oscillator with a Bragg resonator was constructed based on a linear induction accelerator which formed a 1 MeV, 200 A, 200 ns electron beam. At the frequency of 31 GHz, radiation with a power of 31 MW and efficiency of 25% was measured. A high efficiency and a narrow width of the spectrum were achieved owing to the selective properties of the Bragg resonator in combination with the high quality of the helical electron beam formed in the reversed guide field regime. (author). 3 figs., 3 refs.

Deep Learning in Neuroradiology.

Science.gov (United States)

Zaharchuk, G; Gong, E; Wintermark, M; Rubin, D; Langlotz, C P

2018-02-01

Deep learning is a form of machine learning using a convolutional neural network architecture that shows tremendous promise for imaging applications. It is increasingly being adapted from its original demonstration in computer vision applications to medical imaging. Because of the high volume and wealth of multimodal imaging information acquired in typical studies, neuroradiology is poised to be an early adopter of deep learning. Compelling deep learning research applications have been demonstrated, and their use is likely to grow rapidly. This review article describes the reasons, outlines the basic methods used to train and test deep learning models, and presents a brief overview of current and potential clinical applications with an emphasis on how they are likely to change future neuroradiology practice. Facility with these methods among neuroimaging researchers and clinicians will be important to channel and harness the vast potential of this new method. © 2018 by American Journal of Neuroradiology.

Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting

NARCIS (Netherlands)

K.L. Groenland (Koen); S.M. Bohte (Sander)

2016-01-01

textabstractWhen a Convolutional Neural Network is used for on-the-fly evaluation of continuously updating time-sequences, many redundant convolution operations are performed. We propose the method of Deep Shifting, which remembers previously calculated results of convolution operations in order

A metamaterial electromagnetic energy rectifying surface with high harvesting efficiency

Science.gov (United States)

Duan, Xin; Chen, Xing; Zhou, Lin

2016-12-01

A novel metamaterial rectifying surface (MRS) for electromagnetic energy capture and rectification with high harvesting efficiency is presented. It is fabricated on a three-layer printed circuit board, which comprises an array of periodic metamaterial particles in the shape of mirrored split rings, a metal ground, and integrated rectifiers employing Schottky diodes. Perfect impedance matching is engineered at two interfaces, i.e. one between free space and the surface, and the other between the metamaterial particles and the rectifiers, which are connected through optimally positioned vias. Therefore, the incident electromagnetic power is captured with almost no reflection by the metamaterial particles, then channeled maximally to the rectifiers, and finally converted to direct current efficiently. Moreover, the rectifiers are behind the metal ground, avoiding the disturbance of high power incident electromagnetic waves. Such a MRS working at 2.45 GHz is designed, manufactured and measured, achieving a harvesting efficiency up to 66.9% under an incident power density of 5 mW/cm2, compared with a simulated efficiency of 72.9%. This high harvesting efficiency makes the proposed MRS an effective receiving device in practical microwave power transmission applications.

A metamaterial electromagnetic energy rectifying surface with high harvesting efficiency

Directory of Open Access Journals (Sweden)

Xin Duan

2016-12-01

Full Text Available A novel metamaterial rectifying surface (MRS for electromagnetic energy capture and rectification with high harvesting efficiency is presented. It is fabricated on a three-layer printed circuit board, which comprises an array of periodic metamaterial particles in the shape of mirrored split rings, a metal ground, and integrated rectifiers employing Schottky diodes. Perfect impedance matching is engineered at two interfaces, i.e. one between free space and the surface, and the other between the metamaterial particles and the rectifiers, which are connected through optimally positioned vias. Therefore, the incident electromagnetic power is captured with almost no reflection by the metamaterial particles, then channeled maximally to the rectifiers, and finally converted to direct current efficiently. Moreover, the rectifiers are behind the metal ground, avoiding the disturbance of high power incident electromagnetic waves. Such a MRS working at 2.45 GHz is designed, manufactured and measured, achieving a harvesting efficiency up to 66.9% under an incident power density of 5 mW/cm2, compared with a simulated efficiency of 72.9%. This high harvesting efficiency makes the proposed MRS an effective receiving device in practical microwave power transmission applications.

Efficient Unsteady Flow Visualization with High-Order Access Dependencies

Energy Technology Data Exchange (ETDEWEB)

Zhang, Jiang; Guo, Hanqi; Yuan, Xiaoru

2016-04-19

We present a novel high-order access dependencies based model for efficient pathline computation in unsteady flow visualization. By taking longer access sequences into account to model more sophisticated data access patterns in particle tracing, our method greatly improves the accuracy and reliability in data access prediction. In our work, high-order access dependencies are calculated by tracing uniformly-seeded pathlines in both forward and backward directions in a preprocessing stage. The effectiveness of our proposed approach is demonstrated through a parallel particle tracing framework with high-order data prefetching. Results show that our method achieves higher data locality and hence improves the efficiency of pathline computation.

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network.

Science.gov (United States)

Katzman, Jared L; Shaham, Uri; Cloninger, Alexander; Bates, Jonathan; Jiang, Tingting; Kluger, Yuval

2018-02-26

Medical practitioners use survival models to explore and understand the relationships between patients' covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear Cox proportional hazards model require extensive feature engineering or prior medical knowledge to model treatment interaction at an individual level. While nonlinear survival methods, such as neural networks and survival forests, can inherently model these high-level interaction terms, they have yet to be shown as effective treatment recommender systems. We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's covariates and treatment effectiveness in order to provide personalized treatment recommendations. We perform a number of experiments training DeepSurv on simulated and real survival data. We demonstrate that DeepSurv performs as well as or better than other state-of-the-art survival models and validate that DeepSurv successfully models increasingly complex relationships between a patient's covariates and their risk of failure. We then show how DeepSurv models the relationship between a patient's features and effectiveness of different treatment options to show how DeepSurv can be used to provide individual treatment recommendations. Finally, we train DeepSurv on real clinical studies to demonstrate how it's personalized treatment recommendations would increase the survival time of a set of patients. The predictive and modeling capabilities of DeepSurv will enable medical researchers to use deep neural networks as a tool in their exploration, understanding, and prediction of the effects of a patient's characteristics on their risk of failure.

Noise-free high-efficiency photon-number-resolving detectors

International Nuclear Information System (INIS)

Rosenberg, Danna; Lita, Adriana E.; Miller, Aaron J.; Nam, Sae Woo

2005-01-01

High-efficiency optical detectors that can determine the number of photons in a pulse of monochromatic light have applications in a variety of physics studies, including post-selection-based entanglement protocols for linear optics quantum computing and experiments that simultaneously close the detection and communication loopholes of Bell's inequalities. Here we report on our demonstration of fiber-coupled, noise-free, photon-number-resolving transition-edge sensors with 88% efficiency at 1550 nm. The efficiency of these sensors could be made even higher at any wavelength in the visible and near-infrared spectrum without resulting in a higher dark-count rate or degraded photon-number resolution

Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval

Directory of Open Access Journals (Sweden)

Lijuan Duan

2017-01-01

Full Text Available Hashing has been widely deployed to perform the Approximate Nearest Neighbor (ANN search for the large-scale image retrieval to solve the problem of storage and retrieval efficiency. Recently, deep hashing methods have been proposed to perform the simultaneous feature learning and the hash code learning with deep neural networks. Even though deep hashing has shown the better performance than traditional hashing methods with handcrafted features, the learned compact hash code from one deep hashing network may not provide the full representation of an image. In this paper, we propose a novel hashing indexing method, called the Deep Hashing based Fusing Index (DHFI, to generate a more compact hash code which has stronger expression ability and distinction capability. In our method, we train two different architecture’s deep hashing subnetworks and fuse the hash codes generated by the two subnetworks together to unify images. Experiments on two real datasets show that our method can outperform state-of-the-art image retrieval applications.

PC operated acoustic transient spectroscopy of deep levels in MIS structures

International Nuclear Information System (INIS)

Bury, P.; Jamnicky, I.

1996-01-01

A new version of acoustic deep-level transient spectroscopy is presented to study the traps at the insulator-semiconductor interface. The acoustic deep-level transient spectroscopy uses an acoustoelectric response signal produced by the MIS structure interface when a longitudinal acoustic wave propagates through a structure. The acoustoelectric response signal is extremely sensitive to external conditions of the structure and reflects any changes in the charge distribution, connected also with charged traps. In comparison with previous version of acoustic deep-level transient spectroscopy that closely coincides with the principle of the original deep-level transient spectroscopy technique, the present technique is based on the computer-evaluated isothermal transients and represents an improved, more efficient and time saving technique. Many tests on the software used for calculation as well as on experimental setup have been performed. The improved acoustic deep-level transient spectroscopy method has been applied for the Si(p) MIS structures. The deep-level parameters as activation energy and capture cross-section have been determined. (authors)

Preparation of reflective CsI photocathodes with reproducible high quantum efficiency

Science.gov (United States)

Maier-Komor, P.; Bauer, B. B.; Friese, J.; Gernhäuser, R.; Kienle, P.; Körner, H. J.; Montermann, G.; Zeitelhack, K.

1995-02-01

CsI as a solid UV-photocathode material has many promising applications in fast gaseous photon detectors. They are proposed in large area Ring Imaging CHerenkov (RICH) devices in forthcoming experiments at various high-energy particle accelerators. A high photon-to-electron conversion efficiency is a basic requirement for the successful operation of these devices. High reproducible quantum efficiencies could be achieved with CsI layers prepared by electron beam evaporation from a water-cooled copper crucible. CsI films were deposited in the thickness range of 30 to 500 μg/cm 2. Absorption coefficients and quantum efficiencies were measured in the wavelength region of 150 nm to 250 nm. The influence of various evaporation parameters on the quantum efficiency were investigated.

Preparation of reflective CsI photocathodes with reproducible high quantum efficiency

Energy Technology Data Exchange (ETDEWEB)

Maier-Komor, P. [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Bauer, B.B. [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Friese, J. [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Gernhaeuser, R. [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Kienle, P. [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Koerner, H.J. [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Montermann, G. [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Zeitelhack, K. [Technische Univ. Muenchen, Garching (Germany). Physik-Department

1995-08-01

CsI as a solid UV-photocathode material has many promising applications in fast gaseous photon detectors. They are proposed in large area Ring Imaging CHerenkov (RICH) devices in forthcoming experiments at various high-energy particle accelerators. A high photon-to-electron conversion efficiency is a basic requirement for the successful operation of these devices. High reproducible quantum efficiencies could be achieved with CsI layers prepared by electron beam evaporation from a water-cooled copper crucible. CsI films were deposited in the thickness range of 30 to 500 {mu}g/cm{sup 2}. Absorption coefficients and quantum efficiencies were measured in the wavelength region of 150 nm to 250 nm. The influence of various evaporation parameters on the quantum efficiency were investigated. (orig.).

Irradiation effects on high efficiency Si solar cells

International Nuclear Information System (INIS)

Nguyen Duy, T.; Amingual, D.; Colardelle, P.; Bernard, J.

1974-01-01

By optimizing the diffusion parameters, high efficiency cells are obtained with 2ohmsxcm (13.5% AMO) and 10ohmsxcm (12.5% AMO) silicon material. These new cells have been submitted to radiation tests under 1MeV, 2MeV electrons and 2.5MeV protons. Their behavior under irradiation is found to be dependent only on the bulk material. By using the same resistivity silicon, the rate of degradation is exactly the same than those of conventional cells. The power increase, due to a better superficial response of the cell, is maintained after irradiation. These results show that new high efficiency cells offer an E.O.L. power higher than conventional cells [fr

Deep-water oilfield development cost analysis and forecasting —— Take gulf of mexico for example

Science.gov (United States)

Shi, Mingyu; Wang, Jianjun; Yi, Chenggao; Bai, Jianhui; Wang, Jing

2017-11-01

Gulf of Mexico (GoM) is the earliest offshore oilfield which has ever been developed. It tends to breed increasingly value of efficient, secure and cheap key technology of deep-water development. Thus, the analyze of development expenditure in this area is significantly important the evaluation concept of deep-water oilfield all over the world. This article emphasizes on deep-water development concept and EPC contract value in GoM in recent 10 years in case of comparison and selection to the economic efficiency. Besides, the QUETOR has been put into use in this research processes the largest upstream cost database to simulate and calculate the calculating examples’ expenditure. By analyzing and forecasting the deep-water oilfield development expenditure, this article explores the relevance between expenditure index and oil price.

Design Strategies for Ultra-high Efficiency Photovoltaics

Science.gov (United States)

Warmann, Emily Cathryn

While concentrator photovoltaic cells have shown significant improvements in efficiency in the past ten years, once these cells are integrated into concentrating optics, connected to a power conditioning system and deployed in the field, the overall module efficiency drops to only 34 to 36%. This efficiency is impressive compared to conventional flat plate modules, but it is far short of the theoretical limits for solar energy conversion. Designing a system capable of achieving ultra high efficiency of 50% or greater cannot be achieved by refinement and iteration of current design approaches. This thesis takes a systems approach to designing a photovoltaic system capable of 50% efficient performance using conventional diode-based solar cells. The effort began with an exploration of the limiting efficiency of spectrum splitting ensembles with 2 to 20 sub cells in different electrical configurations. Incorporating realistic non-ideal performance with the computationally simple detailed balance approach resulted in practical limits that are useful to identify specific cell performance requirements. This effort quantified the relative benefit of additional cells and concentration for system efficiency, which will help in designing practical optical systems. Efforts to improve the quality of the solar cells themselves focused on the development of tunable lattice constant epitaxial templates. Initially intended to enable lattice matched multijunction solar cells, these templates would enable increased flexibility in band gap selection for spectrum splitting ensembles and enhanced radiative quality relative to metamorphic growth. The III-V material family is commonly used for multijunction solar cells both for its high radiative quality and for the ease of integrating multiple band gaps into one monolithic growth. The band gap flexibility is limited by the lattice constant of available growth templates. The virtual substrate consists of a thin III-V film with the desired

Deep subsurface microbial processes

Science.gov (United States)

Lovley, D.R.; Chapelle, F.H.

1995-01-01

Information on the microbiology of the deep subsurface is necessary in order to understand the factors controlling the rate and extent of the microbially catalyzed redox reactions that influence the geophysical properties of these environments. Furthermore, there is an increasing threat that deep aquifers, an important drinking water resource, may be contaminated by man's activities, and there is a need to predict the extent to which microbial activity may remediate such contamination. Metabolically active microorganisms can be recovered from a diversity of deep subsurface environments. The available evidence suggests that these microorganisms are responsible for catalyzing the oxidation of organic matter coupled to a variety of electron acceptors just as microorganisms do in surface sediments, but at much slower rates. The technical difficulties in aseptically sampling deep subsurface sediments and the fact that microbial processes in laboratory incubations of deep subsurface material often do not mimic in situ processes frequently necessitate that microbial activity in the deep subsurface be inferred through nonmicrobiological analyses of ground water. These approaches include measurements of dissolved H2, which can predict the predominant microbially catalyzed redox reactions in aquifers, as well as geochemical and groundwater flow modeling, which can be used to estimate the rates of microbial processes. Microorganisms recovered from the deep subsurface have the potential to affect the fate of toxic organics and inorganic contaminants in groundwater. Microbial activity also greatly influences 1 the chemistry of many pristine groundwaters and contributes to such phenomena as porosity development in carbonate aquifers, accumulation of undesirably high concentrations of dissolved iron, and production of methane and hydrogen sulfide. Although the last decade has seen a dramatic increase in interest in deep subsurface microbiology, in comparison with the study of

Deep Drawing Behavior of CoCrFeMnNi High-Entropy Alloys

Science.gov (United States)

Bae, Jae Wung; Moon, Jongun; Jang, Min Ji; Ahn, Dong-Hyun; Joo, Soo-Hyun; Jung, Jaimyun; Yim, Dami; Kim, Hyoung Seop

2017-09-01

Herein, the deep drawability and deep drawing behavior of an equiatomic CoCrFeMnNi HEA and its microstructure and texture evolution are first studied for future applications. The CoCrFeMnNi HEA is successfully drawn to a limit drawing ratio (LDR) of 2.14, while the planar anisotropy of the drawn cup specimen is negligible. The moderate combination of strain hardening exponent and strain rate sensitivity and the formation of deformation twins in the edge region play important roles in successful deep drawing. In the meanwhile, the texture evolution of CoCrFeMnNi HEA has similarities with conventional fcc metals.

High efficiency targets for high gain inertial confinement fusion

International Nuclear Information System (INIS)

Gardner, J.H.; Bodner, S.E.

1986-01-01

Rocket efficiencies as high as 15% are possible using short wavelength lasers and moderately high aspect ratio pellet designs. These designs are made possible by two recent breakthroughs in physics constraints. First is the development of the Induced Spatial Incoherence (ISI) technique which allows uniform illumination of the pellet and relaxes the constraint of thermal smoothing, permitting the use of short wavelength laser light. Second is the discovery that the Rayleigh-Taylor growth rate is considerably reduced at the short laser wavelengths. By taking advantage of the reduced constraints imposed by nonuniform laser illumination and Rayleigh-Taylor instability, pellets using 1/4 micron laser light and initial aspect ratios of about 10 (with in flight aspect ratios of about 150 to 200) may produce energy gains as high as 200 to 250

High-efficiency targets for high-gain inertial confinement fusion

International Nuclear Information System (INIS)

Gardner, J.H.; Bodner, S.E.

1986-01-01

Rocket efficiencies as high as 15% are possible using short wavelength lasers and moderately high aspect ratio pellet designs. These designs are made possible by two recent breakthroughs in physics constraints. First is the development of the induced spatial incoherence (ISI) technique, which allows uniform illumination of the pellet and relaxes the constraint of thermal smoothing, permitting the use of short wavelength laser light. Second is the discovery that the Rayleigh--Taylor growth rate is considerably reduced at short laser wavelengths. By taking advantage of the reduced constraints imposed by nonuniform laser illumination and Rayleigh--Taylor instability, pellets using (1)/(4) μm laser light and initial aspect ratios of about 10 (with in flight aspect ratios of about 150--200) may produce energy gains as high as 200--250

High power klystrons for efficient reliable high power amplifiers

Science.gov (United States)

Levin, M.

1980-11-01

This report covers the design of reliable high efficiency, high power klystrons which may be used in both existing and proposed troposcatter radio systems. High Power (10 kW) klystron designs were generated in C-band (4.4 GHz to 5.0 GHz), S-band (2.5 GHz to 2.7 GHz), and L-band or UHF frequencies (755 MHz to 985 MHz). The tubes were designed for power supply compatibility and use with a vapor/liquid phase heat exchanger. Four (4) S-band tubes were developed in the course of this program along with two (2) matching focusing solenoids and two (2) heat exchangers. These tubes use five (5) tuners with counters which are attached to the focusing solenoids. A reliability mathematical model of the tube and heat exchanger system was also generated.

Deep geothermics

International Nuclear Information System (INIS)

Anon.

1995-01-01

The hot-dry-rocks located at 3-4 km of depth correspond to low permeable rocks carrying a large amount of heat. The extraction of this heat usually requires artificial hydraulic fracturing of the rock to increase its permeability before water injection. Hot-dry-rocks geothermics or deep geothermics is not today a commercial channel but only a scientific and technological research field. The Soultz-sous-Forets site (Northern Alsace, France) is characterized by a 6 degrees per meter geothermal gradient and is used as a natural laboratory for deep geothermal and geological studies in the framework of a European research program. Two boreholes have been drilled up to 3600 m of depth in the highly-fractured granite massif beneath the site. The aim is to create a deep heat exchanger using only the natural fracturing for water transfer. A consortium of german, french and italian industrial companies (Pfalzwerke, Badenwerk, EdF and Enel) has been created for a more active participation to the pilot phase. (J.S.). 1 fig., 2 photos

High-efficiency concentrator silicon solar cells

Energy Technology Data Exchange (ETDEWEB)

Sinton, R.A.; Cuevas, A.; King, R.R.; Swanson, R.M. (Stanford Univ., CA (USA). Solid-State Electronics Lab.)

1990-11-01

This report presents results from extensive process development in high-efficiency Si solar cells. An advanced design for a 1.56-cm{sup 2} cell with front grids achieved 26% efficiency at 90 suns. This is especially significant since this cell does not require a prismatic cover glass. New designs for simplified backside-contact solar cells were advanced from a status of near-nonfunctionality to demonstrated 21--22% for one-sun cells in sizes up to 37.5 cm{sup 2}. An efficiency of 26% was achieved for similar 0.64-cm{sup 2} concentrator cells at 150 suns. More fundamental work on dopant-diffused regions is also presented here. The recombination vs. various process and physical parameters was studied in detail for boron and phosphorous diffusions. Emitter-design studies based solidly upon these new data indicate the performance vs design parameters for a variety of the cases of most interest to solar cell designers. Extractions of p-type bandgap narrowing and the surface recombination for p- and n-type regions from these studies have a generality that extends beyond solar cells into basic device modeling. 68 refs., 50 figs.

Prediction of visual saliency in video with deep CNNs

Science.gov (United States)

Chaabouni, Souad; Benois-Pineau, Jenny; Hadar, Ofer

2016-09-01

Prediction of visual saliency in images and video is a highly researched topic. Target applications include Quality assessment of multimedia services in mobile context, video compression techniques, recognition of objects in video streams, etc. In the framework of mobile and egocentric perspectives, visual saliency models cannot be founded only on bottom-up features, as suggested by feature integration theory. The central bias hypothesis, is not respected neither. In this case, the top-down component of human visual attention becomes prevalent. Visual saliency can be predicted on the basis of seen data. Deep Convolutional Neural Networks (CNN) have proven to be a powerful tool for prediction of salient areas in stills. In our work we also focus on sensitivity of human visual system to residual motion in a video. A Deep CNN architecture is designed, where we incorporate input primary maps as color values of pixels and magnitude of local residual motion. Complementary contrast maps allow for a slight increase of accuracy compared to the use of color and residual motion only. The experiments show that the choice of the input features for the Deep CNN depends on visual task:for th eintersts in dynamic content, the 4K model with residual motion is more efficient, and for object recognition in egocentric video the pure spatial input is more appropriate.

Efficient estimation for high similarities using odd sketches

DEFF Research Database (Denmark)

Mitzenmacher, Michael; Pagh, Rasmus; Pham, Ninh Dang

2014-01-01

. This means that Odd Sketches provide a highly space-efficient estimator for sets of high similarity, which is relevant in applications such as web duplicate detection, collaborative filtering, and association rule learning. The method extends to weighted Jaccard similarity, relevant e.g. for TF-IDF vector...... and web duplicate detection tasks....

Deep Eutectic Solvents Enable More Robust Chemoenzymatic Epoxidation Reactions

NARCIS (Netherlands)

Zhou, Pengfei; Wang, Xuping; Zeng, Chaoxi; Wang, Weifei; Yang, Bo; Hollmann, F.; Wang, Yonghua

2017-01-01

A chemoenzymatic method for the production of epoxidized vegetable oils was developed. The unique combination of the commercial lipase G from Penicillieum camembertii with certain deep eutectic solvents enabled the efficient production of epoxidized vegetable oils.

3rd symposium on high-efficiency boiler technology: potential, performance, shortcomings of natural gas fuelled high-efficiency boilers

International Nuclear Information System (INIS)

1993-01-01

The brochure contains abstracts of the papers presented at the symposium. The potential, performance and marketing problems of natural gas high-efficiency boiler systems are outlined, and new ideas are presented for gas utilities, producers of appliances, fitters, and chimneysweeps. 13 papers are available as separate regards in this database. (HW) [de

High efficiency inductive output tubes with intense annular electron beams

Science.gov (United States)

Appanam Karakkad, J.; Matthew, D.; Ray, R.; Beaudoin, B. L.; Narayan, A.; Nusinovich, G. S.; Ting, A.; Antonsen, T. M.

2017-10-01

For mobile ionospheric heaters, it is necessary to develop highly efficient RF sources capable of delivering radiation in the frequency range from 3 to 10 MHz with an average power at a megawatt level. A promising source, which is capable of offering these parameters, is a grid-less version of the inductive output tube (IOT), also known as a klystrode. In this paper, studies analyzing the efficiency of grid-less IOTs are described. The basic trade-offs needed to reach high efficiency are investigated. In particular, the trade-off between the peak current and the duration of the current micro-pulse is analyzed. A particle in the cell code is used to self-consistently calculate the distribution in axial and transverse momentum and in total electron energy from the cathode to the collector. The efficiency of IOTs with collectors of various configurations is examined. It is shown that the efficiency of IOTs can be in the 90% range even without using depressed collectors.

Ultra-high efficiency photovoltaic cells for large scale solar power generation.

Science.gov (United States)

Nakano, Yoshiaki

2012-01-01

The primary targets of our project are to drastically improve the photovoltaic conversion efficiency and to develop new energy storage and delivery technologies. Our approach to obtain an efficiency over 40% starts from the improvement of III-V multi-junction solar cells by introducing a novel material for each cell realizing an ideal combination of bandgaps and lattice-matching. Further improvement incorporates quantum structures such as stacked quantum wells and quantum dots, which allow higher degree of freedom in the design of the bandgap and the lattice strain. Highly controlled arrangement of either quantum dots or quantum wells permits the coupling of the wavefunctions, and thus forms intermediate bands in the bandgap of a host material, which allows multiple photon absorption theoretically leading to a conversion efficiency exceeding 50%. In addition to such improvements, microfabrication technology for the integrated high-efficiency cells and the development of novel material systems that realizes high efficiency and low cost at the same time are investigated.

High-efficiency water-loaded microwave antenna in ultra-high-frequency band

Science.gov (United States)

Gong, Zilun; Bartone, Chris; Yang, Fuyi; Yao, Jie

2018-03-01

High-index dielectrics are widely used in microwave antennas to control the radiation characteristics. Liquid water, with a high dielectric index at microwave frequency, is an interesting material to achieving tunable functionalities. Here, we demonstrate a water-loaded microwave antenna system that has high loss-tolerance and wideband tunability enabled by fluidity. Our simulation and experimental results show that the resonance frequency can be effectively tuned by the size of loading water. Furthermore, the antenna systems with water loading can achieve high radiation efficiency (>90%) in the ultra-high-frequency (0.3-3 GHz) band. This work brings about opportunities in realistic tunable microwave antenna designs enabled by liquid.

Image Captioning with Deep Bidirectional LSTMs

OpenAIRE

Wang, Cheng; Yang, Haojin; Bartz, Christian; Meinel, Christoph

2016-01-01

This work presents an end-to-end trainable deep bidirectional LSTM (Long-Short Term Memory) model for image captioning. Our model builds on a deep convolutional neural network (CNN) and two separate LSTM networks. It is capable of learning long term visual-language interactions by making use of history and future context information at high level semantic space. Two novel deep bidirectional variant models, in which we increase the depth of nonlinearity transition in different way, are propose...

Highly Efficient Coherent Optical Memory Based on Electromagnetically Induced Transparency

Science.gov (United States)

Hsiao, Ya-Fen; Tsai, Pin-Ju; Chen, Hung-Shiue; Lin, Sheng-Xiang; Hung, Chih-Chiao; Lee, Chih-Hsi; Chen, Yi-Hsin; Chen, Yong-Fan; Yu, Ite A.; Chen, Ying-Cheng

2018-05-01

Quantum memory is an important component in the long-distance quantum communication based on the quantum repeater protocol. To outperform the direct transmission of photons with quantum repeaters, it is crucial to develop quantum memories with high fidelity, high efficiency and a long storage time. Here, we achieve a storage efficiency of 92.0 (1.5)% for a coherent optical memory based on the electromagnetically induced transparency scheme in optically dense cold atomic media. We also obtain a useful time-bandwidth product of 1200, considering only storage where the retrieval efficiency remains above 50%. Both are the best record to date in all kinds of schemes for the realization of optical memory. Our work significantly advances the pursuit of a high-performance optical memory and should have important applications in quantum information science.

Ultra-bright and highly efficient inorganic based perovskite light-emitting diodes

Science.gov (United States)

Zhang, Liuqi; Yang, Xiaolei; Jiang, Qi; Wang, Pengyang; Yin, Zhigang; Zhang, Xingwang; Tan, Hairen; Yang, Yang (Michael); Wei, Mingyang; Sutherland, Brandon R.; Sargent, Edward H.; You, Jingbi

2017-06-01

Inorganic perovskites such as CsPbX3 (X=Cl, Br, I) have attracted attention due to their excellent thermal stability and high photoluminescence quantum efficiency. However, the electroluminescence quantum efficiency of their light-emitting diodes was CsPbBr3 lattice and by depositing a hydrophilic and insulating polyvinyl pyrrolidine polymer atop the ZnO electron-injection layer to overcome these issues. As a result, we obtained light-emitting diodes exhibiting a high brightness of 91,000 cd m-2 and a high external quantum efficiency of 10.4% using a mixed-cation perovskite Cs0.87MA0.13PbBr3 as the emitting layer. To the best of our knowledge, this is the brightest and most-efficient green perovskite light-emitting diodes reported to date.

High Efficiency of Two Efficient QSDC with Authentication Is at the Cost of Their Security

International Nuclear Information System (INIS)

Su-Juan, Qin; Qiao-Yan, Wen; Luo-Ming, Meng; Fu-Chen, Zhu

2009-01-01

Two efficient protocols of quantum secure direct communication with authentication [Chin. Phys. Lett. 25 (2008) 2354] were recently proposed by Liu et al. to improve the efficiency of two protocols presented in [Phys. Rev. A 75 (2007) 026301] by four Pauli operations. We show that the high efficiency of the two protocols is at the expense of their security. The authenticator Trent can reach half the secret by a particular attack strategy in the first protocol. In the second protocol, not only Trent but also an eavesdropper outside can elicit half-information about the secret from the public declaration

A novel approach reveals high zooplankton standing stock deep in the sea

Directory of Open Access Journals (Sweden)

A. Vereshchaka

2016-11-01

Full Text Available In a changing ocean there is a critical need to understand global biogeochemical cycling, particularly regarding carbon. We have made strides in understanding upper ocean dynamics, but the deep ocean interior (> 1000 m is still largely unknown, despite representing the overwhelming majority of Earth's biosphere. Here we present a method for estimating deep-pelagic zooplankton biomass on an ocean-basin scale. We have made several new discoveries about the Atlantic, which likely apply to the world ocean. First, multivariate analysis showed that depth and Chl were the basic factors affecting the wet biomass of the main plankton groups. Wet biomass of all major groups was significantly correlated with Chl. Second, zooplankton biomass in the upper bathypelagic domain is higher than expected. Third, the majority of this biomass comprises macroplanktonic shrimps, which have been historically underestimated. These findings, coupled with recent findings of increased global deep-pelagic fish biomass, suggest that the contribution of the deep-ocean pelagic fauna for biogeochemical cycles may be more important than previously thought.

Deep desulfurization by amphiphilic lanthanide-containing polyoxometalates in ionic-liquid emulsion systems under mild conditions.

Science.gov (United States)

Xu, Junhua; Zhao, Shen; Ji, Yuanchun; Song, Yu-Fei

2013-01-07

Amphiphilic lanthanide-containing polyoxometalates (POMs) were prepared by surfactant encapsulation. Investigation of these lanthanide-containing POMs in oxidative desulfurization (ODS) showed that highly efficient deep desulfurization could be achieved in only 14 min with 100% conversion of dibenzothiophene under mild conditions by using (DDA)(9)LaW(10)/[omim]PF(6) (DDA=dimethyldioctadecylammonium, omim=1-octyl-3-methyl-imidazolium) in the presence of H(2) O(2) . Furthermore, deep desulfurization proceeds smoothly in model oil with an S content as low as 50 ppm. A scaled-up experiment in which the volume of model oil was increased from 5 to 1000 mL with S content of 1000 ppm indicated that about 99% sulfur removal can be achieved in 40 mins in an ionic-liquid emulsion system. To the best of our knowledge, the (DDA)(9)LaW(10)/[omim]PF(6) catalyst system with H(2)O(2) as oxidant is one of the most efficient desulfurization systems reported so far. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Is Multitask Deep Learning Practical for Pharma?

Science.gov (United States)

Ramsundar, Bharath; Liu, Bowen; Wu, Zhenqin; Verras, Andreas; Tudor, Matthew; Sheridan, Robert P; Pande, Vijay

2017-08-28

Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack of acceptance stems from both software difficulties and lack of understanding of the robustness of multitask deep networks. Our work aims to resolve both of these barriers to adoption. We introduce a high-quality open-source implementation of multitask deep networks as part of the DeepChem open-source platform. Our implementation enables simple python scripts to construct, fit, and evaluate sophisticated deep models. We use our implementation to analyze the performance of multitask deep networks and related deep models on four collections of pharmaceutical data (three of which have not previously been analyzed in the literature). We split these data sets into train/valid/test using time and neighbor splits to test multitask deep learning performance under challenging conditions. Our results demonstrate that multitask deep networks are surprisingly robust and can offer strong improvement over random forests. Our analysis and open-source implementation in DeepChem provide an argument that multitask deep networks are ready for widespread use in commercial drug discovery.