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

NASA Astrophysics Data System (ADS)

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

2018-03-01

We report a new route to improve quantum efficiencies of AlGaN-based deep-ultraviolet light-emitting diodes (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 is enhanced higher than three times, when the DUV LEDs are moderately bent with concave curvatures. Furthermore, an 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.

Origin of reduced efficiency in high Ga concentration Cu(In,Ga)Se2 solar cell

NASA Astrophysics Data System (ADS)

Wei, S.-H.; Huang, B.; Deng, H.; Contreras, M. A.; Noufi, R.; Chen, S.; Wang, L. W.

2014-03-01

CuInSe2 (CIS) is one of the most attractive thin-film materials for solar cells. It is well know that alloying Ga into CIS forming Cu(In,Ga)Se2 (CIGS) alloy is crucial to achieve the high efficiency, but adding too much Ga will lead to a decline of the solar cell efficiency. The exact origin of this puzzling phenomenon is currently still under debate. Using first-principles method, we have systemically studied the structural and electronic properties of CIGS alloys. Our phase diagram calculations suggest that increasing growth temperature may not be a critical factor in enhancing the cell performance of CIGS under equilibrium growth condition. On the other hand, our defect calculations identify that high concentration of antisite defects MCu(M =In, Ga) rather than anion defects are the key deep-trap centers in CIGS. The more the Ga concentration in CIGS, the more harmful the deep-trap is. Self-compensation in CIGS, which forms 2VCu + MCudefect complexes, is found to be beneficial to quench the deep-trap levels induced by MCu in CIGS, especially at low Ga concentration. Unfortunately, the density of isolated MCu is quite high and cannot be largely converted into 2VCu + MCu complexes under thermal equilibrium condition. Thus, nonequilibrium growth conditions or low growth temperature that can suppress the formation of the deep-trap centers MCu may be necessary for improving the efficiency of CIGS solar cells with high Ga concentrations.

Deep ocean nutrients imply large latitudinal variation in particle transfer efficiency.

PubMed

Weber, Thomas; Cram, Jacob A; Leung, Shirley W; DeVries, Timothy; Deutsch, Curtis

2016-08-02

The "transfer efficiency" of sinking organic particles through the mesopelagic zone and into the deep ocean is a critical determinant of the atmosphere-ocean partition of carbon dioxide (CO2). Our ability to detect large-scale spatial variations in transfer efficiency is limited by the scarcity and uncertainties of particle flux data. Here we reconstruct deep ocean particle fluxes by diagnosing the rate of nutrient accumulation along transport pathways in a data-constrained ocean circulation model. Combined with estimates of organic matter export from the surface, these diagnosed fluxes reveal a global pattern of transfer efficiency to 1,000 m that is high (∼25%) at high latitudes and low (∼5%) in subtropical gyres, with intermediate values in the tropics. This pattern is well correlated with spatial variations in phytoplankton community structure and the export of ballast minerals, which control the size and density of sinking particles. These findings accentuate the importance of high-latitude oceans in sequestering carbon over long timescales, and highlight potential impacts on remineralization depth as phytoplankton communities respond to a warming climate.

2-(2-Hydroxyphenyl)benzimidazole-based four-coordinate boron-containing materials with highly efficient deep-blue photoluminescence and electroluminescence.

PubMed

Zhang, Zhenyu; Zhang, Houyu; Jiao, Chuanjun; Ye, Kaiqi; Zhang, Hongyu; Zhang, Jingying; Wang, Yue

2015-03-16

Two novel four-coordinate boron-containing emitters 1 and 2 with deep-blue emissions were synthesized by refluxing a 2-(2-hydroxyphenyl)benzimidazole ligand with triphenylborane or bromodibenzoborole. The boron chelation produced a new π-conjugated skeleton, which rendered the synthesized boron materials with intense fluorescence, good thermal stability, and high carrier mobility. Both compounds displayed deep-blue emissions in solutions with very high fluorescence quantum yields (over 0.70). More importantly, the samples showed identical fluorescence in the solution and solid states, and the efficiency was maintained at a high level (approximately 0.50) because of the bulky substituents between the boron atom and the benzimidazole unit, which can effectively separate the flat luminescent units. In addition, neat thin films composed of 1 or 2 exhibited high electron and hole mobility in the same order of magnitude 10(-4), as determined by time-of-flight. The fabricated electroluminescent devices that employed 1 or 2 as emitting materials showed high-performance deep-blue emissions with Commission Internationale de L'Eclairage (CIE) coordinates of (X = 0.15, Y = 0.09) and (X = 0.16, Y = 0.08), respectively. Thus, the synthesized boron-containing materials are ideal candidates for fabricating high-performance deep-blue organic light-emitting diodes.

Methods for enhancing the efficiency of creating a borehole using high power laser systems

DOEpatents

Zediker, Mark S.; Rinzler, Charles C.; Faircloth, Brian O.; Koblick, Yeshaya; Moxley, Joel F.

2014-06-24

Methods for utilizing 10 kW or more laser energy transmitted deep into the earth with the suppression of associated nonlinear phenomena to enhance the formation of Boreholes. Methods for the laser operations to reduce the critical path for forming a borehole in the earth. These methods can deliver high power laser energy down a deep borehole, while maintaining the high power to perform operations in such boreholes deep within the earth.

Fabricating binary optics: An overview of binary optics process technology

NASA Technical Reports Server (NTRS)

Stern, Margaret B.

1993-01-01

A review of binary optics processing technology is presented. Pattern replication techniques have been optimized to generate high-quality efficient microoptics in visible and infrared materials. High resolution optical photolithography and precision alignment is used to fabricate maximally efficient fused silica diffractive microlenses at lambda = 633 nm. The degradation in optical efficiency of four-phase-level fused silica microlenses resulting from an intentional 0.35 micron translational error has been systematically measured as a function of lens speed (F/2 - F/60). Novel processes necessary for high sag refractive IR microoptics arrays, including deep anisotropic Si-etching, planarization of deep topography and multilayer resist techniques, are described. Initial results are presented for monolithic integration of photonic and microoptic systems.

Convolutional networks for fast, energy-efficient neuromorphic computing

PubMed Central

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

Convolutional networks for fast, energy-efficient neuromorphic computing.

PubMed

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.

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

PubMed

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).

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

NASA Technical Reports Server (NTRS)

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.

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

PubMed

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.

Deep Blue Phosphorescent Organic Light-Emitting Diodes with CIEy Value of 0.11 and External Quantum Efficiency up to 22.5.

PubMed

Li, Xiaoyue; Zhang, Juanye; Zhao, Zifeng; Wang, Liding; Yang, Hannan; Chang, Qiaowen; Jiang, Nan; Liu, Zhiwei; Bian, Zuqiang; Liu, Weiping; Lu, Zhenghong; Huang, Chunhui

2018-03-01

Organic light-emitting diodes (OLEDs) based on red and green phosphorescent iridium complexes are successfully commercialized in displays and solid-state lighting. However, blue ones still remain a challenge on account of their relatively dissatisfactory Commission International de L'Eclairage (CIE) coordinates and low efficiency. After analyzing the reported blue iridium complexes in the literature, a new deep-blue-emitting iridium complex with improved photoluminescence quantum yield is designed and synthesized. By rational screening host materials showing high triplet energy level in neat film as well as the OLED architecture to balance electron and hole recombination, highly efficient deep-blue-emission OLEDs with a CIE at (0.15, 0.11) and maximum external quantum efficiency (EQE) up to 22.5% are demonstrated. Based on the transition dipole moment vector measurement with a variable-angle spectroscopic ellipsometry method, the ultrahigh EQE is assigned to a preferred horizontal dipole orientation of the iridium complex in doped film, which is beneficial for light extraction from the OLEDs. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deep ocean nutrients imply large latitudinal variation in particle transfer efficiency

PubMed Central

Weber, Thomas; Cram, Jacob A.; Leung, Shirley W.; DeVries, Timothy; Deutsch, Curtis

2016-01-01

The “transfer efficiency” of sinking organic particles through the mesopelagic zone and into the deep ocean is a critical determinant of the atmosphere−ocean partition of carbon dioxide (CO2). Our ability to detect large-scale spatial variations in transfer efficiency is limited by the scarcity and uncertainties of particle flux data. Here we reconstruct deep ocean particle fluxes by diagnosing the rate of nutrient accumulation along transport pathways in a data-constrained ocean circulation model. Combined with estimates of organic matter export from the surface, these diagnosed fluxes reveal a global pattern of transfer efficiency to 1,000 m that is high (∼25%) at high latitudes and low (∼5%) in subtropical gyres, with intermediate values in the tropics. This pattern is well correlated with spatial variations in phytoplankton community structure and the export of ballast minerals, which control the size and density of sinking particles. These findings accentuate the importance of high-latitude oceans in sequestering carbon over long timescales, and highlight potential impacts on remineralization depth as phytoplankton communities respond to a warming climate. PMID:27457946

Deep ocean nutrients imply large latitudinal variation in particle transfer efficiency

NASA Astrophysics Data System (ADS)

Weber, Thomas; Cram, Jacob A.; Leung, Shirley W.; DeVries, Timothy; Deutsch, Curtis

2016-08-01

The “transfer efficiency” of sinking organic particles through the mesopelagic zone and into the deep ocean is a critical determinant of the atmosphere-ocean partition of carbon dioxide (CO2). Our ability to detect large-scale spatial variations in transfer efficiency is limited by the scarcity and uncertainties of particle flux data. Here we reconstruct deep ocean particle fluxes by diagnosing the rate of nutrient accumulation along transport pathways in a data-constrained ocean circulation model. Combined with estimates of organic matter export from the surface, these diagnosed fluxes reveal a global pattern of transfer efficiency to 1,000 m that is high (˜25%) at high latitudes and low (˜5%) in subtropical gyres, with intermediate values in the tropics. This pattern is well correlated with spatial variations in phytoplankton community structure and the export of ballast minerals, which control the size and density of sinking particles. These findings accentuate the importance of high-latitude oceans in sequestering carbon over long timescales, and highlight potential impacts on remineralization depth as phytoplankton communities respond to a warming climate.

Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

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

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.

Deep Learning for Flow Sculpting: Insights into Efficient Learning using Scientific Simulation Data

NASA Astrophysics Data System (ADS)

Stoecklein, Daniel; Lore, Kin Gwn; Davies, Michael; Sarkar, Soumik; Ganapathysubramanian, Baskar

2017-04-01

A new technique for shaping microfluid flow, known as flow sculpting, offers an unprecedented level of passive fluid flow control, with potential breakthrough applications in advancing manufacturing, biology, and chemistry research at the microscale. However, efficiently solving the inverse problem of designing a flow sculpting device for a desired fluid flow shape remains a challenge. Current approaches struggle with the many-to-one design space, requiring substantial user interaction and the necessity of building intuition, all of which are time and resource intensive. Deep learning has emerged as an efficient function approximation technique for high-dimensional spaces, and presents a fast solution to the inverse problem, yet the science of its implementation in similarly defined problems remains largely unexplored. We propose that deep learning methods can completely outpace current approaches for scientific inverse problems while delivering comparable designs. To this end, we show how intelligent sampling of the design space inputs can make deep learning methods more competitive in accuracy, while illustrating their generalization capability to out-of-sample predictions.

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

PubMed

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.

Eutectic salt catalyzed environmentally benign and highly efficient Biginelli reaction.

PubMed

Azizi, Najmadin; Dezfuli, Sahar; Hahsemi, Mohmmad Mahmoodi

2012-01-01

A simple deep eutectic solvent based on tin (II) chloride was used as a dual catalyst and environmentally benign reaction medium for an efficient synthesis of 3,4-dihydropyrimidin-2(1H)-one derivatives, from aromatic and aliphatic aldehydes, 1,3-dicarbonyl compounds, and urea in good-to-excellent yields and short reaction time. This simple ammonium deep eutectic solvent, easily synthesized from choline chloride and tin chloride, is relatively inexpensive and recyclable, making it applicable for industrial applications.

Eutectic Salt Catalyzed Environmentally Benign and Highly Efficient Biginelli Reaction

PubMed Central

Azizi, Najmadin; Dezfuli, Sahar; Hahsemi, Mohmmad Mahmoodi

2012-01-01

A simple deep eutectic solvent based on tin (II) chloride was used as a dual catalyst and environmentally benign reaction medium for an efficient synthesis of 3,4-dihydropyrimidin-2(1H)-one derivatives, from aromatic and aliphatic aldehydes, 1,3-dicarbonyl compounds, and urea in good-to-excellent yields and short reaction time. This simple ammonium deep eutectic solvent, easily synthesized from choline chloride and tin chloride, is relatively inexpensive and recyclable, making it applicable for industrial applications. PMID:22649326

A Zero-Dimensional Organic Seesaw-Shaped Tin Bromide with Highly Efficient Strongly Stokes-Shifted Deep-Red Emission

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

Zhou, Chenkun; Lin, Haoran; Shi, Hongliang

The synthesis and characterization is reported of (C 9NH 20) 2SnBr 4, a novel organic metal halide hybrid with a zero-dimensional (0D) structure, in which individual seesaw-shaped tin (II) bromide anions (SnBr 4 2-) are co-crystallized with 1-butyl-1-methylpyrrolidinium cations (C 9NH 20 +). Upon photoexcitation, the bulk crystals exhibit a highly efficient broadband deep-red emission peaked at 695 nm, with a large Stokes shift of 332 nm and a high quantum efficiency of around 46 %. Furthermore, the unique photophysical properties of this hybrid material are attributed to two major factors: 1) the 0D structure allowing the bulk crystals tomore » exhibit the intrinsic properties of individual SnBr 4 2- species, and 2) the seesaw structure then enables a pronounced excited state structural deformation as confirmed by density functional theory (DFT) calculations.« less

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

NASA Astrophysics Data System (ADS)

Wang, Han; Zhang, Linfeng; Han, Jiequn; E, Weinan

2018-07-01

Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in Python/C++ that has been designed to minimize the effort required to build deep learning based representation of potential energy and force field and to perform molecular dynamics. Potential applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems. DeePMD-kit is interfaced with TensorFlow, one of the most popular deep learning frameworks, making the training process highly automatic and efficient. On the other end, DeePMD-kit is interfaced with high-performance classical molecular dynamics and quantum (path-integral) molecular dynamics packages, i.e., LAMMPS and the i-PI, respectively. Thus, upon training, the potential energy and force field models can be used to perform efficient molecular simulations for different purposes. As an example of the many potential applications of the package, we use DeePMD-kit to learn the interatomic potential energy and forces of a water model using data obtained from density functional theory. We demonstrate that the resulted molecular dynamics model reproduces accurately the structural information contained in the original model.

Method and system for advancement of a borehole using a high power laser

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

Moxley, Joel F.; Land, Mark S.; Rinzler, Charles C.

2014-09-09

There is provided a system, apparatus and methods for the laser drilling of a borehole in the earth. There is further provided with in the systems a means for delivering high power laser energy down a deep borehole, while maintaining the high power to advance such boreholes deep into the earth and at highly efficient advancement rates, a laser bottom hole assembly, and fluid directing techniques and assemblies for removing the displaced material from the borehole.

The dynamic ocean biological pump: Insights from a global compilation of particulate organic carbon, CaCO3, and opal concentration profiles from the mesopelagic

NASA Astrophysics Data System (ADS)

Lam, Phoebe J.; Doney, Scott C.; Bishop, James K. B.

2011-09-01

We have compiled a global data set of 62 open ocean profiles of particulate organic carbon (POC), CaCO3, and opal concentrations collected by large volume in situ filtration in the upper 1000 m over the last 30 years. We define concentration-based metrics for the strength (POC concentration at depth) and efficiency (attenuation of POC with depth in the mesopelagic) of the biological pump. We show that the strength and efficiency of the biological pump are dynamic and are characterized by a regime of constant and high transfer efficiency at low to moderate surface POC and a bloom regime where the height of the bloom is characterized by a weak deep biological pump and low transfer efficiency. The variability in POC attenuation length scale manifests in a clear decoupling between the strength of the shallow biological pump (e.g., POC at the export depth) and the strength of the deep biological pump (POC at 500 m). We suggest that the paradigm of diatom-driven export production is driven by a too restrictive perspective on upper mesopelagic dynamics. Indeed, our full mesopelagic analysis suggests that large, blooming diatoms have low transfer efficiency and thus may not export substantially to depth; rather, our analysis suggests that ecosystems characterized by smaller cells and moderately high %CaCO3 have a high mesopelagic transfer efficiency and can have higher POC concentrations in the deep mesopelagic even with relatively low surface or near-surface POC. This has negative implications for the carbon sequestration prospects of deliberate iron fertilization.

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

PubMed

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.

Surface hole gas enabled transparent deep ultraviolet light-emitting diode

NASA Astrophysics Data System (ADS)

Zhang, Jianping; Gao, Ying; Zhou, Ling; Gil, Young-Un; Kim, Kyoung-Min

2018-07-01

The inherent deep-level nature of acceptors in wide-band-gap semiconductors makes p-ohmic contact formation and hole supply difficult, impeding progress for short-wavelength optoelectronics and high-power high-temperature bipolar electronics. We provide a general solution by demonstrating an ultrathin rather than a bulk wide-band-gap semiconductor to be a successful hole supplier and ohmic contact layer. Free holes in this ultrathin semiconductor are assisted to activate from deep acceptors and swept to surface to form hole gases by a large electric field, which can be provided by engineered spontaneous and piezoelectric polarizations. Experimentally, a 6 nm thick AlN layer with surface hole gas had formed p-ohmic contact to metals and provided sufficient hole injection to a 280 nm light-emitting diode, demonstrating a record electrical-optical conversion efficiency exceeding 8.5% at 20 mA (55 A cm‑2). Our approach of forming p-type wide-band-gap semiconductor ohmic contact is critical to realizing high-efficiency ultraviolet optoelectronic devices.

Deep Learning for Flow Sculpting: Insights into Efficient Learning using Scientific Simulation Data

PubMed Central

Stoecklein, Daniel; Lore, Kin Gwn; Davies, Michael; Sarkar, Soumik; Ganapathysubramanian, Baskar

2017-01-01

A new technique for shaping microfluid flow, known as flow sculpting, offers an unprecedented level of passive fluid flow control, with potential breakthrough applications in advancing manufacturing, biology, and chemistry research at the microscale. However, efficiently solving the inverse problem of designing a flow sculpting device for a desired fluid flow shape remains a challenge. Current approaches struggle with the many-to-one design space, requiring substantial user interaction and the necessity of building intuition, all of which are time and resource intensive. Deep learning has emerged as an efficient function approximation technique for high-dimensional spaces, and presents a fast solution to the inverse problem, yet the science of its implementation in similarly defined problems remains largely unexplored. We propose that deep learning methods can completely outpace current approaches for scientific inverse problems while delivering comparable designs. To this end, we show how intelligent sampling of the design space inputs can make deep learning methods more competitive in accuracy, while illustrating their generalization capability to out-of-sample predictions. PMID:28402332

Large enhancement of light extraction efficiency in AlGaN-based nanorod ultraviolet light-emitting diode structures.

PubMed

Ryu, Han-Youl

2014-02-04

Light extraction efficiency (LEE) of AlGaN-based nanorod deep ultraviolet (UV) light-emitting diodes (LEDs) is numerically investigated using three-dimensional finite-difference time-domain simulations. LEE of deep UV LEDs is limited by strong light absorption in the p-GaN contact layer and total internal reflection. The nanorod structure is found to be quite effective in increasing LEE of deep UV LEDs especially for the transverse magnetic (TM) mode. In the nanorod LED, strong dependence of LEE on structural parameters such as the diameter of a nanorod and the p-GaN thickness is observed, which can be attributed to the formation of resonant modes inside the nanorod structure. Simulation results show that, when the structural parameters of the nanorod LED are optimized, LEE can be higher than 50% and 60% for the transverse electric (TE) and TM modes, respectively. The nanorod structure is expected to be a good candidate for the application to future high-efficiency deep UV LEDs. PACS: 41.20.Jb; 42.72.Bj; 85.60.Jb.

Large enhancement of light extraction efficiency in AlGaN-based nanorod ultraviolet light-emitting diode structures

PubMed Central

2014-01-01

Light extraction efficiency (LEE) of AlGaN-based nanorod deep ultraviolet (UV) light-emitting diodes (LEDs) is numerically investigated using three-dimensional finite-difference time-domain simulations. LEE of deep UV LEDs is limited by strong light absorption in the p-GaN contact layer and total internal reflection. The nanorod structure is found to be quite effective in increasing LEE of deep UV LEDs especially for the transverse magnetic (TM) mode. In the nanorod LED, strong dependence of LEE on structural parameters such as the diameter of a nanorod and the p-GaN thickness is observed, which can be attributed to the formation of resonant modes inside the nanorod structure. Simulation results show that, when the structural parameters of the nanorod LED are optimized, LEE can be higher than 50% and 60% for the transverse electric (TE) and TM modes, respectively. The nanorod structure is expected to be a good candidate for the application to future high-efficiency deep UV LEDs. PACS 41.20.Jb; 42.72.Bj; 85.60.Jb PMID:24495598

Advanced Thermophotovoltaic Cells Modeling, Optimized for Use in Radioisotope Thermoelectric Generators (RTGs) for Mars and Deep Space Missions

DTIC Science & Technology

2004-06-01

PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Thermophotovoltaic cells are a good candidate for use in high efficiency radioiso- tope...ongoing in this field since the 1950’s, but the exotic materials necessary for high efficiency cells has only been recently available. Here, several...This cell was able to operate at 24% efficiency which is very high for a silicon cell [Ref. 6]. The inverted pyramids labeled in the figure are

Efficient, deep-blue TADF-emitters for OLED display applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Volz, Daniel; Baumann, Thomas

2016-09-01

Currently, the mobile display market is strongly shifting towards AMOLED technology, in order to enable curved and flexible displays. This leads to a growing demand for highly efficient OLED emitters to reduce the power consumption and increase display resolution at the same time. While highly efficient green and red OLEDs already found their place in commercial OLED-displays, the lack of efficient blue emitters is still an issue. Consequently, the active area for blue is considerably larger than for green and red pixels, to make up for the lower efficiency. We intend to close this efficiency-gap with novel emitters based on thermally activated delayed fluorescence (TADF) technology. Compared to state-of-the-art fluorescent dopants, the efficiency of TADF-emitters is up to four times higher. At the same time, it is possible to design them in a way to maintain deep blue emission, i.e. CIE y < 0.2. These aspects are relevant to produce efficient high resolution AMOLED displays. Apart from these direct customer benefits, our TADF technology does not contain any rare elements, which allows for the fabrication of sustainable OLED technology. In this work, we highlight one of our recently developed blue TADF materials. Basic material properties as well as first device results are discussed. In a bottom-emitting device, a CIEx/CIEy coordinate of (0.16/0.17) was achieved with efficiency values close to 20% EQE.

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

PubMed

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.

Direct nanopatterning of 100 nm metal oxide periodic structures by Deep-UV immersion lithography.

PubMed

Stehlin, Fabrice; Bourgin, Yannick; Spangenberg, Arnaud; Jourlin, Yves; Parriaux, Olivier; Reynaud, Stéphanie; Wieder, Fernand; Soppera, Olivier

2012-11-15

Deep-UV lithography using high-efficiency phase mask has been developed to print 100 nm period grating on sol-gel based thin layer. High efficiency phase mask has been designed to produce a high-contrast interferogram (periodic fringes) under water immersion conditions for 244 nm laser. The demonstration has been applied to a new developed immersion-compatible sol-gel layer. A sol-gel photoresist prepared from zirconium alkoxides caped with methacrylic acids was developed to achieve 50 nm resolution in a single step exposure. The nanostructures can be thermally annealed into ZrO(2). Such route considerably simplifies the process for elaborating nanopatterned surfaces of transition metal oxides, and opens new routes for integrating materials of interest for applications in the field of photocatalysis, photovoltaic, optics, photonics or microelectronics.

Efficiency of the neighbor-joining method in reconstructing deep and shallow evolutionary relationships in large phylogenies.

PubMed

Kumar, S; Gadagkar, S R

2000-12-01

The neighbor-joining (NJ) method is widely used in reconstructing large phylogenies because of its computational speed and the high accuracy in phylogenetic inference as revealed in computer simulation studies. However, most computer simulation studies have quantified the overall performance of the NJ method in terms of the percentage of branches inferred correctly or the percentage of replications in which the correct tree is recovered. We have examined other aspects of its performance, such as the relative efficiency in correctly reconstructing shallow (close to the external branches of the tree) and deep branches in large phylogenies; the contribution of zero-length branches to topological errors in the inferred trees; and the influence of increasing the tree size (number of sequences), evolutionary rate, and sequence length on the efficiency of the NJ method. Results show that the correct reconstruction of deep branches is no more difficult than that of shallower branches. The presence of zero-length branches in realized trees contributes significantly to the overall error observed in the NJ tree, especially in large phylogenies or slowly evolving genes. Furthermore, the tree size does not influence the efficiency of NJ in reconstructing shallow and deep branches in our simulation study, in which the evolutionary process is assumed to be homogeneous in all lineages.

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

PubMed

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.

An AlGaN Core-Shell Tunnel Junction Nanowire Light-Emitting Diode Operating in the Ultraviolet-C Band.

PubMed

Sadaf, S M; Zhao, S; Wu, Y; Ra, Y-H; Liu, X; Vanka, S; Mi, Z

2017-02-08

To date, semiconductor light emitting diodes (LEDs) operating in the deep ultraviolet (UV) spectral range exhibit very low efficiency due to the presence of large densities of defects and extremely inefficient p-type conduction of conventional AlGaN quantum well heterostructures. We have demonstrated that such critical issues can be potentially addressed by using nearly defect-free AlGaN tunnel junction core-shell nanowire heterostructures. The core-shell nanowire arrays exhibit high photoluminescence efficiency (∼80%) in the UV-C band at room temperature. With the incorporation of an epitaxial Al tunnel junction, the p-(Al)GaN contact-free nanowire deep UV LEDs showed nearly one order of magnitude reduction in the device resistance, compared to the conventional nanowire p-i-n device. The unpackaged Al tunnel junction deep UV LEDs exhibit an output power >8 mW and a peak external quantum efficiency ∼0.4%, which are nearly one to two orders of magnitude higher than previously reported AlGaN nanowire devices. Detailed studies further suggest that the maximum achievable efficiency is limited by electron overflow and poor light extraction efficiency due to the TM polarized emission.

Mesoporous composite nanoparticles for dual-modality ultrasound/magnetic resonance imaging and synergistic chemo-/thermotherapy against deep tumors.

PubMed

Zhang, Nan; Wang, Ronghui; Hao, Junnian; Yang, Yang; Zou, Hongmi; Wang, Zhigang

2017-01-01

High-intensity focused ultrasound (HIFU) is a promising and noninvasive treatment for solid tumors, which has been explored for potential clinical applications. However, the clinical applications of HIFU for large and deep tumors such as hepatocellular carcinoma (HCC) are severely limited by unsatisfactory imaging guidance, long therapeutic times, and damage to normal tissue around the tumor due to the high power applied. In this study, we developed doxorubicin/perfluorohexane-encapsulated hollow mesoporous Prussian blue nanoparticles (HMPBs-DOX/PFH) as theranostic agents, which can effectively guide HIFU therapy and enhance its therapeutic effects in combination with chemotherapy, by decreasing the cavitation threshold. We investigated the effects of this agent on ultrasound and magnetic resonance imaging in vitro and in vivo. In addition, we showed a highly efficient HIFU therapeutic effect against HCC tumors, as well as controlled drug release, owing to the phase-transitional performance of the PFH. We therefore conclude that HMPB-DOX/PFH is a safe and efficient nanoplatform, which holds significant promise for cancer theranostics against deep tumors in clinical settings.

Mesoporous composite nanoparticles for dual-modality ultrasound/magnetic resonance imaging and synergistic chemo-/thermotherapy against deep tumors

PubMed Central

Zhang, Nan; Wang, Ronghui; Hao, Junnian; Yang, Yang; Zou, Hongmi; Wang, Zhigang

2017-01-01

High-intensity focused ultrasound (HIFU) is a promising and noninvasive treatment for solid tumors, which has been explored for potential clinical applications. However, the clinical applications of HIFU for large and deep tumors such as hepatocellular carcinoma (HCC) are severely limited by unsatisfactory imaging guidance, long therapeutic times, and damage to normal tissue around the tumor due to the high power applied. In this study, we developed doxorubicin/perfluorohexane-encapsulated hollow mesoporous Prussian blue nanoparticles (HMPBs-DOX/PFH) as theranostic agents, which can effectively guide HIFU therapy and enhance its therapeutic effects in combination with chemotherapy, by decreasing the cavitation threshold. We investigated the effects of this agent on ultrasound and magnetic resonance imaging in vitro and in vivo. In addition, we showed a highly efficient HIFU therapeutic effect against HCC tumors, as well as controlled drug release, owing to the phase-transitional performance of the PFH. We therefore conclude that HMPB-DOX/PFH is a safe and efficient nanoplatform, which holds significant promise for cancer theranostics against deep tumors in clinical settings. PMID:29042775

Deep Space Systems Technology Program Future Deliveries

NASA Technical Reports Server (NTRS)

Salvo, Christopher G.; Keuneke, Matthew S.

2000-01-01

NASA is in a period of frequent launches of low cost deep space missions with challenging performance needs. The modest budgets of these missions make it impossible for each to develop its own technology, therefore, efficient and effective development and insertion of technology for these missions must be approached at a higher level than has been done in the past. The Deep Space Systems Technology Program (DSST), often referred to as X2000, has been formed to address this need. The program is divided into a series of "Deliveries" that develop and demonstrate a set of spacecraft system capabilities with broad applicability for use by multiple missions. The First Delivery Project, to be completed in 2001, will provide a one MRAD-tolerant flight computer, power switching electronics, efficient radioisotope power source, and a transponder with services at 8.4 GHz and 32 GHz bands. Plans call for a Second Delivery in late 2003 to enable complete deep space systems in the 10 to 50 kg class, and a Third Delivery built around Systems on a Chip (extreme levels of electronic and microsystems integration) around 2006. Formulation of Future Deliveries (past the First Delivery) is ongoing and includes plans for such developments as highly miniaturized digital/analog/power electronics, optical communications, multifunctional structures, miniature lightweight propulsion, advanced thermal control techniques, highly efficient radioisotope power sources, and a unified flight ground software architecture to support the needs of future highly intelligent space systems. All developments are targeted at broad applicability and reuse, and will be commercialized within the US.

Applications of Deep Learning in Biomedicine.

PubMed

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.

Spitzer Operations: Scheduling the Out Years

NASA Technical Reports Server (NTRS)

Mahoney, William A.; Effertz, Mark J.; Fisher, Mark E.; Garcia, Lisa J.; Hunt, Joseph C. Jr.; Mannings, Vincent; McElroy, Douglas B.; Scire, Elena

2012-01-01

Spitzer Warm Mission operations have remained robust and exceptionally efficient since the cryogenic mission ended in mid-2009. The distance to the now exceeds 1 AU, making telecommunications increasingly difficult; however, analysis has shown that two-way communication could be maintained through at least 2017 with minimal loss in observing efficiency. The science program continues to emphasize the characterization of exoplanets, time domain studies, and deep surveys, all of which can impose interesting scheduling constraints. Recent changes have significantly improved on-board data compression, which both enables certain high volume observations and reduces Spitzer's demand for competitive Deep Space Network resources.

Excellent deep-blue emitting materials based on anthracene derivatives for non-doped organic light-emitting diodes

NASA Astrophysics Data System (ADS)

Wang, Zhiqiang; Liu, Wei; Xu, Chen; Ji, Baoming; Zheng, Caijun; Zhang, Xiaohong

2016-08-01

Two deep-blue emitting materials 2-tert-butyl-9,10-bis(3,5-diphenylphenyl)anthracene (An-1) and 2-tert-butyl-9,10-bis(3,5-diphenylbiphenyl-4‧-yl)anthracene (An-2) were successfully synthesized by the Pd-catalyzed Suzuki coupling reaction. Both of these compounds have high thermal stabilities and show strong deep-blue emission as solid-state film as well as in n-hexane solution. Two non-doped electroluminescent devices employing An-1 and An-2 as emitting layers were fabricated by vacuum vapor deposition. These devices exhibited highly efficient and stable deep-blue emission with high color purity. The CIE coordinate and maximum EQE of An-1 based device are 4.2% and (0.16, 0.06), respectively. Device based on An-2 achieved a maximum EQE of 4.0% and a CIE coordinate of (0.16, 0.10).

High-efficiency, deep-junction, epitaxial InP solar cells on (100) and (111)B InP substrates

NASA Technical Reports Server (NTRS)

Venkatasubramanian, R.; Timmons, M. L.; Hutchby, J. A.; Walters, Robert J.; Summers, Geoffrey P.

1994-01-01

We report on the development and performance of deep-junction (approximately 0.25 micron), graded-emitter-doped, n(sup +)-p InP solar cells grown by metallorganic chemical vapor deposition (MOCVD). A novel, diffusion-transport process for obtaining lightly-doped p-type base regions of the solar cell is described. The I-V data and external quantum-efficiency response of these cells are presented. The best active-area AMO efficiency for these deep-junction cells on (100)-oriented InP substrates is 16.8 percent, with a J(sub SC) of 31.8 mA/sq cm, a V(sub OC) of 0.843 V, and a fill-factor of 0.85. By comparison, the best cell efficiency on the (111)B-oriented InP substrates was 15.0 percent. These efficiency values for deep-junction cells are encouraging and compare favorably with performance of thin-emitter (0.03 micron) epitaxial cells as well as that of deep-emitter diffused cells. The cell performance and breakdown voltage characteristics of a batch of 20 cells on each of the orientations are presented, indicating the superior breakdown voltage properties and other characteristics of InP cells on the (111)B orientation. Spectral response, dark I-V data, and photoluminescence (PL) measurements on the InP cells are presented with an analysis on the variation in J(sub SC) and V(sub OC) of the cells. It is observed, under open-circuit conditions, that lower-V(sub OC) cells exhibit higher band-edge PL intensity for both the (100) and (111)B orientations. This anomalous behavior suggests that radiative recombination in the heavily-doped n(sup +)-InP emitter may be detrimental to achieving higher V(sub OC) in n(sup +)-p InP solar cells.

High Efficiency Power Combining of Ka-Band TWTs for High Data Rate Communications

NASA Technical Reports Server (NTRS)

Wintucky, E. G.; Simons, R. N.; Vaden, K. R.; Lesny, G. G.; Glass, J. L.

2006-01-01

Future NASA deep space exploration missions are expected in some cases to require telecommunication systems capable of operating at very high data rates (potentially 1 Gbps or more) for the transmission back to Earth of large volumes of scientific data, which means high frequency transmitters with large bandwidth. Among the Ka band frequencies of interest are the present 500 MHz Deep Space Network (DSN) band of 31.8 to 32.3 GHz and a broader band at 37-38 GHz allocated for space science [1]. The large distances and use of practical antenna sizes dictate the need for high transmitter power of up to 1 kW or more. High electrical efficiency is also a requirement. The approach investigated by NASA GRC is a novel wave guide power combiner architecture based on a hybrid magic-T junction for combining the power output from multiple TWTs [1,2]. This architecture was successfully demonstrated and is capable of both high efficiency (90-95%, depending on frequency) and high data rate transmission (up to 622 Mbps) in a two-way power combiner circuit for two different pairs of Ka band TWTs at two different frequency bands. One pair of TWTs, tested over a frequency range of 29.1 to 29.6 GHz, consisted of two 110-115W TWTs previously used in uplink data transmission evaluation terminals in the NASA Advanced Communications Technology Satellite (ACTS) program [1,2]. The second pair was two 100W TWTs (Boeing 999H) designed for high efficiency operation (greater than 55%) over the DSN frequency band of 31.8 to 32.3 GHz [3]. The presentation will provide a qualitative description of the wave guide circuit, results for power combining and data transmission measurements, and results of computer modeling of the magic-T and alternative hybrid junctions for improvements in efficiency and power handling capability. The power combiner results presented here are relevant not only to NASA deep space exploration missions, but also to other U.S. Government agency programs.

Cognitive Load Theory vs. Constructivist Approaches: Which Best Leads to Efficient, Deep Learning?

ERIC Educational Resources Information Center

Vogel-Walcutt, J. J.; Gebrim, J. B.; Bowers, C.; Carper, T. M.; Nicholson, D.

2011-01-01

Computer-assisted learning, in the form of simulation-based training, is heavily focused upon by the military. Because computer-based learning offers highly portable, reusable, and cost-efficient training options, the military has dedicated significant resources to the investigation of instructional strategies that improve learning efficiency…

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

PubMed Central

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

2015-01-01

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. PMID:26338976

Development of a New Generation of High-Temperature Thermoelectric Unicouples for Space Applications

NASA Technical Reports Server (NTRS)

Caillat, Thierry; Gogna, P.; Sakamoto, J.; Jewell, A.; Cheng, J.; Blair, R.; Fleurial, J. -P.; Ewell, R.

2006-01-01

RTG's have enabled surface and deep space missions since 1961: a) 26 flight missions without any RTG failures; and b) Mission durations in excess of 25 years. Future NASA missions require RTG s with high specific power and high efficiency, while retaining long life (> 14 years) and high reliability, (i.e. 6-8 W/kg, 10-15% efficiency). JPL in partnership with NASA-GRC, NASA-MSFC, DOE, Universities and Industry is developing advanced thermoelectric materials and converters to meet future NASA needs.

Cryogenically cooled low-noise amplifier for radio-astronomical observations and centimeter-wave deep-space communications systems

NASA Astrophysics Data System (ADS)

Vdovin, V. F.; Grachev, V. G.; Dryagin, S. Yu.; Eliseev, A. I.; Kamaletdinov, R. K.; Korotaev, D. V.; Lesnov, I. V.; Mansfeld, M. A.; Pevzner, E. L.; Perminov, V. G.; Pilipenko, A. M.; Sapozhnikov, B. D.; Saurin, V. P.

2016-01-01

We report a design solution for a highly reliable, low-noise and extremely efficient cryogenically cooled transmit/receive unit for a large antenna system meant for radio-astronomical observations and deep-space communications in the X band. We describe our design solution and the results of a series of laboratory and antenna tests carried out in order to investigate the properties of the cryogenically cooled low-noise amplifier developed. The transmit/receive unit designed for deep-space communications (Mars missions, radio observatories located at Lagrangian point L2, etc.) was used in practice for communication with live satellites including "Radioastron" observatory, which moves in a highly elliptical orbit.

Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing.

PubMed

Ghesu, Florin C; Krubasik, Edward; Georgescu, Bogdan; Singh, Vivek; Yefeng Zheng; Hornegger, Joachim; Comaniciu, Dorin

2016-05-01

Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volumetric medical image data are typically based on machine learning methods that exploit large annotated image databases. Two main challenges need to be addressed, these are the efficiency in scanning high-dimensional parametric spaces and the need for representative image features which require significant efforts of manual engineering. We propose a pipeline for object detection and segmentation in the context of volumetric image parsing, solving a two-step learning problem: anatomical pose estimation and boundary delineation. For this task we introduce Marginal Space Deep Learning (MSDL), a novel framework exploiting both the strengths of efficient object parametrization in hierarchical marginal spaces and the automated feature design of Deep Learning (DL) network architectures. In the 3D context, the application of deep learning systems is limited by the very high complexity of the parametrization. More specifically 9 parameters are necessary to describe a restricted affine transformation in 3D, resulting in a prohibitive amount of billions of scanning hypotheses. The mechanism of marginal space learning provides excellent run-time performance by learning classifiers in clustered, high-probability regions in spaces of gradually increasing dimensionality. To further increase computational efficiency and robustness, in our system we learn sparse adaptive data sampling patterns that automatically capture the structure of the input. Given the object localization, we propose a DL-based active shape model to estimate the non-rigid object boundary. Experimental results are presented on the aortic valve in ultrasound using an extensive dataset of 2891 volumes from 869 patients, showing significant improvements of up to 45.2% over the state-of-the-art. To our knowledge, this is the first successful demonstration of the DL potential to detection and segmentation in full 3D data with parametrized representations.

Acquiring High-Performance Deep-Blue OLED Emitters through an Unexpected Blueshift Color-Tuning Effect Induced by Electron-Donating -OMe Substituents.

PubMed

Peng, Song; Zhao, Yihuan; Fu, Caixia; Pu, Xuemei; Zhou, Liang; Huang, Yan; Lu, Zhiyun

2018-06-07

A series of blue-emissive 7-(diphenylamino)-4-phenoxycoumarin derivatives bearing -CF 3 , -OMe, or -N(Me) 2 substituents on the phenoxy subunit were synthesized. Although both the -CF 3 and -N(Me) 2 modifications were found to trigger redshifted fluorescence, the -OMe substitution was demonstrated to exert an unexpected blueshift color-tuning effect toward the deep-blue region. The reason is that the moderate electron-donating -OMe group can endow coumarins with unaltered HOMO but elevated LUMO energy levels. Moreover, the -OMe substitution was found to be beneficial to the thermal stability of these coumarins. Therefore, the trimethoxy-substituted objective compound can act as a high-performance deep-blue organic light-emitting diode (OLED) emitter, and OLED based on it emits deep-blue light with CIE coordinates of (0.148, 0.084), maximum luminance of 7800 cd m -2 , and maximum external quantum efficiency of 5.1 %. These results not only shed light on the molecular design strategy for high-performance deep-blue OLED emitters through color-tuning, but also show the perspective of coumarin derivatives as deep-blue OLED emitters. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Impact of Tropopause Structures on Deep Convective Transport Observed during MACPEX

NASA Astrophysics Data System (ADS)

Mullendore, G. L.; Bigelbach, B. C.; Christensen, L. E.; Maddox, E.; Pinkney, K.; Wagner, S.

2016-12-01

Deep convection is the most efficient method of transporting boundary layer mass to the upper troposphere and stratosphere (UTLS). The Mid-latitude Airborne Cirrus Properties Experiment (MACPEX) was conducted during April of 2011 over the central U.S. With a focus on cirrus clouds, the campaign flights often sampled large cirrus anvils downstream from deep convection and included an extensive observational suite of chemical measurements on a high altitude aircraft. As double-tropopause structures are a common feature in the central U.S. during the springtime, the MACPEX campaign provides a good opportunity to gather cases of deep convective transport in the context of both single and double tropopause structures. Sampling of chemical plumes well downstream from convection allows for sampling in relatively quiescent conditions and analysis of irreversible transport. The analysis presented includes multiple methods to assess air mass source and possible convective processing, including back trajectories and ratios of chemical concentrations. Although missions were flown downstream of deep convection, recent processing by convection does not seem likely in all cases that high altitude carbon monoxide plumes were observed. Additionally, the impact of single and double tropopause structures on deep convective transport is shown to be strongly dependent on high stability layers.

Medium Bandgap Conjugated Polymer for High Performance Polymer Solar Cells Exceeding 9% Power Conversion Efficiency.

PubMed

Jung, Jae Woong; Liu, Feng; Russell, Thomas P; Jo, Won Ho

2015-12-02

Two medium-bandgap polymers composed of benzo[1,2-b:4,5-b']dithiohpene and 2,1,3-benzothiadiazole with 6-octyl-thieno[3,2-b]thiophene as a π-bridge unit are synthesized and their photovoltaic properties are analyzed. The two polymers have deep highest occupied molecular orbital energy levels, high crystallinity, optimal bulk-heterojunction morphology, and efficient charge transport, resulting in a power conversion efficiency of as high as 9.44% for a single-junction polymer solar-cell device. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effect of inversion layer at iron pyrite surface on photovoltaic device

NASA Astrophysics Data System (ADS)

Uchiyama, Shunsuke; Ishikawa, Yasuaki; Uraoka, Yukiharu

2018-03-01

Iron pyrite has great potential as a thin-film solar cell material because it has high optical absorption, low cost, and is earth-abundant. However, previously reported iron pyrite solar cells showed poor photovoltaic characteristics. Here, we have numerically simulated its photovoltaic characteristics and band structures by utilizing a two-dimensional (2D) device simulator, ATLAS, to evaluate the effects of an inversion layer at the surface and a high density of deep donor defect states in the bulk. We found that previous device structures did not consider the inversion layer at the surface region of iron pyrite, which made it difficult to obtain the conversion efficiency. Therefore, we remodeled the device structure and suggested that removing the inversion layer and reducing the density of deep donor defect states would lead to a high conversion efficiency of iron pyrite solar cells.

Enhanced wall-plug efficiency in AlGaN-based deep-ultraviolet light-emitting diodes with uniform current spreading p-electrode structures

NASA Astrophysics Data System (ADS)

Hao, Guo-Dong; Taniguchi, Manabu; Tamari, Naoki; Inoue, Shin-ichiro

2016-06-01

The current crowding is an especially severe issue in AlGaN-based deep-ultraviolet (DUV) light-emitting diodes (LEDs) because of the low conductivity of the n-AlGaN cladding layer that has a high Al fraction. We theoretically investigated the improvement in internal quantum efficiency and total resistances in DUV-LEDs with an emission wavelength of 265 nm by a well-designed p-electrode geometry to produce uniform current spreading. As a result, the wall-plug efficiency was enhanced by a factor of 60% at an injection current of 350 mA in the designed uniform-current-spreading p-electrode LED when compared with an LED with a conventional cross-bar p-electrode pattern.

Versatile Polymer Nanoparticles as Two-Photon-Triggered Photosensitizers for Simultaneous Cellular, Deep-Tissue Imaging, and Photodynamic Therapy.

PubMed

Guo, Liang; Ge, Jiechao; Liu, Qian; Jia, Qingyan; Zhang, Hongyan; Liu, Weimin; Niu, Guangle; Liu, Sha; Gong, Jianru; Hackbarth, Steffen; Wang, Pengfei

2017-06-01

Clinical applications of current photodynamic therapy (PDT) photosensitizers (PSs) are often limited by their absorption in the UV-vis range that possesses limited tissue penetration ability, leading to ineffective therapeutic response for deep-seated tumors. Alternatively, two-photon excited PS (TPE-PS) using NIR light triggered is one the most promising candidates for PDT improvement. Herein, multimodal polymer nanoparticles (PNPs) from polythiophene derivative as two-photon fluorescence imaging as well as two-photon-excited PDT agent are developed. The prepared PNPs exhibit excellent water dispersibility, high photostability and pH stability, strong fluorescence brightness, and low dark toxicity. More importantly, the PNPs also possess other outstanding features including: (1) the high 1 O 2 quantum yield; (2) the strong two-photon-induced fluorescence and efficient 1 O 2 generation; (3) the specific accumulation in lysosomes of HeLa cells; and (4) the imaging detection depth up to 2100 µm in the mock tissue under two-photon. The multifunctional PNPs are promising candidates as TPE-PDT agent for simultaneous cellular, deep-tissue imaging, and highly efficient in vivo PDT of cancer. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Crystal Engineering for Low Defect Density and High Efficiency Hybrid Chemical Vapor Deposition Grown Perovskite Solar Cells.

PubMed

Ng, Annie; Ren, Zhiwei; Shen, Qian; Cheung, Sin Hang; Gokkaya, Huseyin Cem; So, Shu Kong; Djurišić, Aleksandra B; Wan, Yangyang; Wu, Xiaojun; Surya, Charles

2016-12-07

Synthesis of high quality perovskite absorber is a key factor in determining the performance of the solar cells. We demonstrate that hybrid chemical vapor deposition (HCVD) growth technique can provide high level of versatility and repeatability to ensure the optimal conditions for the growth of the perovskite films as well as potential for batch processing. It is found that the growth ambient and degree of crystallization of CH 3 NH 3 PbI 3 (MAPI) have strong impact on the defect density of MAPI. We demonstrate that HCVD process with slow postdeposition cooling rate can significantly reduce the density of shallow and deep traps in the MAPI due to enhanced material crystallization, while a mixed O 2 /N 2 carrier gas is effective in passivating both shallow and deep traps. By careful control of the perovskite growth process, a champion device with power conversion efficiency of 17.6% is achieved. Our work complements the existing theoretical studies on different types of trap states in MAPI and fills the gap on the theoretical analysis of the interaction between deep levels and oxygen. The experimental results are consistent with the theoretical predictions.

The design and performance of IceCube DeepCore

NASA Astrophysics Data System (ADS)

Abbasi, R.; Abdou, Y.; Abu-Zayyad, T.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Allen, M. M.; Altmann, D.; Andeen, K.; Auffenberg, J.; Bai, X.; Baker, M.; Barwick, S. W.; Bay, R.; Bazo Alba, J. L.; Beattie, K.; Beatty, J. J.; Bechet, S.; Becker, J. K.; Becker, K.-H.; Benabderrahmane, M. L.; BenZvi, S.; Berdermann, J.; Berghaus, P.; Berley, D.; Bernardini, E.; Bertrand, D.; Besson, D. Z.; Bindig, D.; Bissok, M.; Blaufuss, E.; Blumenthal, J.; Boersma, D. J.; Bohm, C.; Bose, D.; Böser, S.; Botner, O.; Brown, A. M.; Buitink, S.; Caballero-Mora, K. S.; Carson, M.; Chirkin, D.; Christy, B.; Clevermann, F.; Cohen, S.; Colnard, C.; Cowen, D. F.; Cruz Silva, A. H.; D'Agostino, M. V.; Danninger, M.; Daughhetee, J.; Davis, J. C.; De Clercq, C.; Degner, T.; Demirörs, L.; Descamps, F.; Desiati, P.; de Vries-Uiterweerd, G.; DeYoung, T.; Díaz-Vélez, J. C.; Dierckxsens, M.; Dreyer, J.; Dumm, J. P.; Dunkman, M.; Eisch, J.; Ellsworth, R. W.; Engdegård, O.; Euler, S.; Evenson, P. A.; Fadiran, O.; Fazely, A. R.; Fedynitch, A.; Feintzeig, J.; Feusels, T.; Filimonov, K.; Finley, C.; Fischer-Wasels, T.; Fox, B. D.; Franckowiak, A.; Franke, R.; Gaisser, T. K.; Gallagher, J.; Gerhardt, L.; Gladstone, L.; Glüsenkamp, T.; Goldschmidt, A.; Goodman, J. A.; Góra, D.; Grant, D.; Griesel, T.; Groß, A.; Grullon, S.; Gurtner, M.; Ha, C.; Haj Ismail, A.; Hallgren, A.; Halzen, F.; Han, K.; Hanson, K.; Heinen, D.; Helbing, K.; Hellauer, R.; Hickford, S.; Hill, G. C.; Hoffman, K. D.; Hoffmann, B.; Homeier, A.; Hoshina, K.; Huelsnitz, W.; Hülß, J.-P.; Hulth, P. O.; Hultqvist, K.; Hussain, S.; Ishihara, A.; Jacobi, E.; Jacobsen, J.; Japaridze, G. S.; Johansson, H.; Kampert, K.-H.; Kappes, A.; Karg, T.; Karle, A.; Kenny, P.; Kiryluk, J.; Kislat, F.; Klein, S. R.; Köhne, J.-H.; Kohnen, G.; Kolanoski, H.; Köpke, L.; Koskinen, D. J.; Kowalski, M.; Kowarik, T.; Krasberg, M.; Kroll, G.; Kurahashi, N.; Kuwabara, T.; Labare, M.; Laihem, K.; Landsman, H.; Larson, M. J.; Lauer, R.; Lünemann, J.; Madsen, J.; Marotta, A.; Maruyama, R.; Mase, K.; Matis, H. S.; Meagher, K.; Merck, M.; Mészáros, P.; Meures, T.; Miarecki, S.; Middell, E.; Milke, N.; Miller, J.; Montaruli, T.; Morse, R.; Movit, S. M.; Nahnhauer, R.; Nam, J. W.; Naumann, U.; Nygren, D. R.; Odrowski, S.; Olivas, A.; Olivo, M.; O'Murchadha, A.; Panknin, S.; Paul, L.; Pérez de los Heros, C.; Petrovic, J.; Piegsa, A.; Pieloth, D.; Porrata, R.; Posselt, J.; Price, P. B.; Przybylski, G. T.; Rawlins, K.; Redl, P.; Resconi, E.; Rhode, W.; Ribordy, M.; Richman, M.; Rodrigues, J. P.; Rothmaier, F.; Rott, C.; Ruhe, T.; Rutledge, D.; Ruzybayev, B.; Ryckbosch, D.; Sander, H.-G.; Santander, M.; Sarkar, S.; Schatto, K.; Schmidt, T.; Schönwald, A.; Schukraft, A.; Schultes, A.; Schulz, O.; Schunck, M.; Seckel, D.; Semburg, B.; Seo, S. H.; Sestayo, Y.; Seunarine, S.; Silvestri, A.; Spiczak, G. M.; Spiering, C.; Stamatikos, M.; Stanev, T.; Stezelberger, T.; Stokstad, R. G.; Stößl, A.; Strahler, E. A.; Ström, R.; Stüer, M.; Sullivan, G. W.; Swillens, Q.; Taavola, H.; Taboada, I.; Tamburro, A.; Tepe, A.; Ter-Antonyan, S.; Tilav, S.; Toale, P. A.; Toscano, S.; Tosi, D.; van Eijndhoven, N.; Vandenbroucke, J.; Van Overloop, A.; van Santen, J.; Vehring, M.; Voge, M.; Walck, C.; Waldenmaier, T.; Wallraff, M.; Walter, M.; Weaver, Ch.; Wendt, C.; Westerhoff, S.; Whitehorn, N.; Wiebe, K.; Wiebusch, C. H.; Williams, D. R.; Wischnewski, R.; Wissing, H.; Wolf, M.; Wood, T. R.; Woschnagg, K.; Xu, C.; Xu, D. L.; Xu, X. W.; Yanez, J. P.; Yodh, G.; Yoshida, S.; Zarzhitsky, P.; Zoll, M.

2012-05-01

The IceCube neutrino observatory in operation at the South Pole, Antarctica, comprises three distinct components: a large buried array for ultrahigh energy neutrino detection, a surface air shower array, and a new buried component called DeepCore. DeepCore was designed to lower the IceCube neutrino energy threshold by over an order of magnitude, to energies as low as about 10 GeV. DeepCore is situated primarily 2100 m below the surface of the icecap at the South Pole, at the bottom center of the existing IceCube array, and began taking physics data in May 2010. Its location takes advantage of the exceptionally clear ice at those depths and allows it to use the surrounding IceCube detector as a highly efficient active veto against the principal background of downward-going muons produced in cosmic-ray air showers. DeepCore has a module density roughly five times higher than that of the standard IceCube array, and uses photomultiplier tubes with a new photocathode featuring a quantum efficiency about 35% higher than standard IceCube PMTs. Taken together, these features of DeepCore will increase IceCube's sensitivity to neutrinos from WIMP dark matter annihilations, atmospheric neutrino oscillations, galactic supernova neutrinos, and point sources of neutrinos in the northern and southern skies. In this paper we describe the design and initial performance of DeepCore.

The Design and Performance of IceCube DeepCore

NASA Technical Reports Server (NTRS)

Stamatikos, M.

2012-01-01

The IceCube neutrino observatory in operation at the South Pole, Antarctica, comprises three distinct components: a large buried array for ultrahigh energy neutrino detection, a surface air shower array, and a new buried component called DeepCore. DeepCore was designed to lower the IceCube neutrino energy threshold by over an order of magnitude, to energies as low as about 10 GeV. DeepCore is situated primarily 2100 m below the surface of the icecap at the South Pole, at the bottom center of the existing IceCube array, and began taking pbysics data in May 2010. Its location takes advantage of the exceptionally clear ice at those depths and allows it to use the surrounding IceCube detector as a highly efficient active veto against the principal background of downward-going muons produced in cosmic-ray air showers. DeepCore has a module density roughly five times higher than that of the standard IceCube array, and uses photomultiplier tubes with a new photocathode featuring a quantum efficiency about 35% higher than standard IceCube PMTs. Taken together, these features of DeepCore will increase IceCube's sensitivity to neutrinos from WIMP dark matter annihilations, atmospheric neutrino oscillations, galactic supernova neutrinos, and point sources of neutrinos in the northern and southern skies. In this paper we describe the design and initial performance of DeepCore.

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

PubMed

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.

Study on Ultra-deep Azimuthal Electromagnetic Resistivity LWD Tool by Influence Quantification on Azimuthal Depth of Investigation and Real Signal

NASA Astrophysics Data System (ADS)

Li, Kesai; Gao, Jie; Ju, Xiaodong; Zhu, Jun; Xiong, Yanchun; Liu, Shuai

2018-05-01

This paper proposes a new tool design of ultra-deep azimuthal electromagnetic (EM) resistivity logging while drilling (LWD) for deeper geosteering and formation evaluation, which can benefit hydrocarbon exploration and development. First, a forward numerical simulation of azimuthal EM resistivity LWD is created based on the fast Hankel transform (FHT) method, and its accuracy is confirmed under classic formation conditions. Then, a reasonable range of tool parameters is designed by analyzing the logging response. However, modern technological limitations pose challenges to selecting appropriate tool parameters for ultra-deep azimuthal detection under detectable signal conditions. Therefore, this paper uses grey relational analysis (GRA) to quantify the influence of tool parameters on voltage and azimuthal investigation depth. After analyzing thousands of simulation data under different environmental conditions, the random forest is used to fit data and identify an optimal combination of tool parameters due to its high efficiency and accuracy. Finally, the structure of the ultra-deep azimuthal EM resistivity LWD tool is designed with a theoretical azimuthal investigation depth of 27.42-29.89 m in classic different isotropic and anisotropic formations. This design serves as a reliable theoretical foundation for efficient geosteering and formation evaluation in high-angle and horizontal (HA/HZ) wells in the future.

Development of carbon plasma-coated multiwell plates for high-throughput mass spectrometric analysis of highly lipophilic fermentation products.

PubMed

Heinig, Uwe; Scholz, Susanne; Dahm, Pia; Grabowy, Udo; Jennewein, Stefan

2010-08-01

Classical approaches to strain improvement and metabolic engineering rely on rapid qualitative and quantitative analyses of the metabolites of interest. As an analytical tool, mass spectrometry (MS) has proven to be efficient and nearly universally applicable for timely screening of metabolites. Furthermore, gas chromatography (GC)/MS- and liquid chromatography (LC)/MS-based metabolite screens can often be adapted to high-throughput formats. We recently engineered a Saccharomyces cerevisiae strain to produce taxa-4(5),11(12)-diene, the first pathway-committing biosynthetic intermediate for the anticancer drug Taxol, through the heterologous and homologous expression of several genes related to isoprenoid biosynthesis. To date, GC/MS- and LC/MS-based high-throughput methods have been inherently difficult to adapt to the screening of isoprenoid-producing microbial strains due to the need for extensive sample preparation of these often highly lipophilic compounds. In the current work, we examined different approaches to the high-throughput analysis of taxa-4(5),11(12)-diene biosynthesizing yeast strains in a 96-deep-well format. Carbon plasma coating of standard 96-deep-well polypropylene plates allowed us to circumvent the inherent solvent instability of commonly used deep-well plates. In addition, efficient adsorption of the target isoprenoid product by the coated plates allowed rapid and simple qualitative and quantitative analyses of the individual cultures. Copyright 2010 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Liu, Wei-ting; Huang, Wen-Yao

2012-06-01

This study used novel fluorescence based deep-blue-emitting molecules, namely BPVPDA, an organic fluorescence color thin film using BPVPDA exhibit deep blue fluorine 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 (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 thin-film-transistor (TFT) LCD with organic color thin films. The organic color thin films structure uses organic dye dopent in limpid photo resist. With this technology , the following characteristics can be obtained: (1) high color reproduction of gamut ratio, and (2) improved luminous efficiency with organic color fluorescence thin film. This performance is among the best results ever reported for a color-filter used on TFT-LCD and OLED.

Deep-UV emission at 219 nm from ultrathin MBE GaN/AlN quantum heterostructures

NASA Astrophysics Data System (ADS)

Islam, S. M.; Protasenko, Vladimir; Lee, Kevin; Rouvimov, Sergei; Verma, Jai; Xing, Huili Grace; Jena, Debdeep

2017-08-01

Deep ultraviolet (UV) optical emission below 250 nm (˜5 eV) in semiconductors is traditionally obtained from high aluminum containing AlGaN alloy quantum wells. It is shown here that high-quality epitaxial ultrathin binary GaN quantum disks embedded in an AlN matrix can produce efficient optical emission in the 219-235 nm (˜5.7-5.3 eV) spectral range, far above the bulk bandgap (3.4 eV) of GaN. The quantum confinement energy in these heterostructures is larger than the bandgaps of traditional semiconductors, made possible by the large band offsets. These molecular beam epitaxy-grown extreme quantum-confinement GaN/AlN heterostructures exhibit an internal quantum efficiency of 40% at wavelengths as short as 219 nm. These observations together with the ability to engineer the interband optical matrix elements to control the direction of photon emission in such binary quantum disk active regions offer unique advantages over alloy AlGaN quantum well counterparts for the realization of deep-UV light-emitting diodes and lasers.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

The effect of shallow vs. deep level doping on the performance of thermoelectric materials

NASA Astrophysics Data System (ADS)

Song, Qichen; Zhou, Jiawei; Meroueh, Laureen; Broido, David; Ren, Zhifeng; Chen, Gang

2016-12-01

It is well known that the efficiency of a good thermoelectric material should be optimized with respect to doping concentration. However, much less attention has been paid to the optimization of the dopant's energy level. Thermoelectric materials doped with shallow levels may experience a dramatic reduction in their figures of merit at high temperatures due to the excitation of minority carriers that reduces the Seebeck coefficient and increases bipolar heat conduction. Doping with deep level impurities can delay the excitation of minority carriers as it requires a higher temperature to ionize all dopants. We find through modeling that, depending on the material type and temperature range of operation, different impurity levels (shallow or deep) will be desired to optimize the efficiency of a thermoelectric material. For different materials, we further clarify where the most preferable position of the impurity level within the bandgap falls. Our research provides insight on why different dopants often affect thermoelectric transport properties differently and directions in searching for the most appropriate dopants for a thermoelectric material in order to maximize the device efficiency.

Performance of a Low-Power Cylindrical Hall Thruster

NASA Technical Reports Server (NTRS)

Polzin, Kurt A.; Markusic, Thomas E.; Stanojev, Boris J.; Dehoyos, Amado; Raitses, Yevgeny; Smirnov, Artem; Fisch, Nathaniel J.

2007-01-01

Recent mission studies have shown that a Hall thruster which operates at relatively constant thrust efficiency (45-55%) over a broad power range (300W - 3kW) is enabling for deep space science missions when compared with slate-of-the-art ion thrusters. While conventional (annular) Hall thrusters can operate at high thrust efficiency at kW power levels, it is difficult to construct one that operates over a broad power envelope down to 0 (100 W) while maintaining relatively high efficiency. In this note we report the measured performance (I(sub sp), thrust and efficiency) of a cylindrical Hall thruster operating at 0 (100 W) input power.

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

PubMed

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 <0.001); self-perceived exertion explained 48% of the variance in sleep efficiency (R2 = 0.48). Moreover, high self-perceived exercise exertion was 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.

Parametric Study of Radiator Concepts for a Stirling Radioisotope Power System Applicable to Deep Space Mission

NASA Technical Reports Server (NTRS)

Juhasz, Albert J.; Tew, Roy C.; Thieme, Lanny G.

2000-01-01

The Department of Energy (DOE) and the NASA Glenn Research Center are developing a Stirling converter for an advanced radioisotope power system to provide spacecraft onboard electric power for NASA deep space missions. This high-efficiency converter is being evaluated as an alternative to replace the much lower efficiency radioisotope thermoelectric generator (RTG). The current power requirement (six years after beginning of mission (BOM) for a mission to Jupiter) is 210 W(sub e) (watts electric) to be generated by two separate power systems, one on each side of the spacecraft. Both two-converter and four-converter system designs are being considered, depending on the amount of required redundancy.

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

PubMed Central

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

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

NASA Astrophysics Data System (ADS)

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 show, by temperature-dependent photoluminescence, that the activation energy of the acceptors is substantially lower, thus allowing a higher hole concentration than usual to be available for conduction. It is believed that the lower activation energy is a result of an impurity band tail induced by the high Mg concentration. The successful p-type doping of high aluminum-content (Al,Ga)N has allowed us to demonstrate operation of deep ultraviolet LEDs emitting at 274 nm. This achievement paves the way for making lasers that emit in the UV-C region of the spectrum. In this thesis, we performed preliminary work on using our structures to make UV-C lasers based on photonic crystal nanocavity structures. The nanocavity laser structures show that the threshold optical pumping power necessary to reach lasing is much lower than in conventional edge-emitting lasers. Furthermore, the photonic crystal nanocavity structure has a small mode volume and does not need mirrors for optical feedback. These advantages significantly reduce material loss and eliminate mirror loss. This structure therefore potentially opens the door to achieving efficient and compact lasers in the UV-C region of the spectrum.

Hydroxynaphthyridine-derived group III metal chelates: wide band gap and deep blue analogues of green Alq3 (tris(8-hydroxyquinolate)aluminum) and their versatile applications for organic light-emitting diodes.

PubMed

Liao, Szu-Hung; Shiu, Jin-Ruei; Liu, Shun-Wei; Yeh, Shi-Jay; Chen, Yu-Hung; Chen, Chin-Ti; Chow, Tahsin J; Wu, Chih-I

2009-01-21

A series of group III metal chelates have been synthesized and characterized for the versatile application of organic light-emitting diodes (OLEDs). These metal chelates are based on 4-hydroxy-1,5-naphthyridine derivates as chelating ligands, and they are the blue version analogues of well-known green fluorophore Alq(3) (tris(8-hydroxyquinolinato)aluminum). These chelating ligands and their metal chelates were easily prepared with an improved synthetic method, and they were facially purified by a sublimation process, which enables the materials to be readily available in bulk quantity and facilitates their usage in OLEDs. Unlike most currently known blue analogues of Alq(3) or other deep blue materials, metal chelates of 4-hydroxy-1,5-naphthyridine exhibit very deep blue fluorescence, wide band gap energy, high charge carrier mobility, and superior thermal stability. Using a vacuum-thermal-deposition process in the fabrication of OLEDs, we have successfully demonstrated that the application of these unusual hydroxynaphthyridine metal chelates can be very versatile and effective. First, we have solved or alleviated the problem of exciplex formation that took place between the hole-transporting layer and hydroxynaphthyridine metal chelates, of which OLED application has been prohibited to date. Second, these deep blue materials can play various roles in OLED application. They can be a highly efficient nondopant deep blue emitter: maximum external quantum efficiency eta(ext) of 4.2%; Commision Internationale de L'Eclairage x, y coordinates, CIE(x,y) = 0.15, 0.07. Compared with Alq(3), Bebq(2) (beryllium bis(benzoquinolin-10-olate)), or TPBI (2,2',2''-(1,3,5-phenylene)tris(1-phenyl-1H-benzimidazole), they are a good electron-transporting material: low HOMO energy level of 6.4-6.5 eV and not so high LUMO energy level of 3.0-3.3 eV. They can be ambipolar and possess a high electron mobility of 10(-4) cm(2)/V s at an electric field of 6.4 x 10(5) V/cm. They are a qualified wide band gap host material for efficient blue perylene (CIE(x,y) = 0.14, 0.17 and maximum eta(ext) 3.8%) or deep blue 9,10-diphenylanthracene (CIE(x,y) = 0.15, 0.06 and maximum eta(ext) 2.8%). For solid state lighting application, they are desirable as a host material for yellow dopant (rubrene) in achieving high efficiency (eta(ext) 4.3% and eta(P) 8.7 lm/W at an electroluminance of 100 cd/m(2) or eta(ext) 3.9% and eta(P) 5.1 lm/W at an electroluminance of 1000 cd/m(2)) white electroluminescence (CIE(x,y) = 0.30, 0.35).

Deep Crustal Melting and the Survival of Continental Crust

NASA Astrophysics Data System (ADS)

Whitney, D.; Teyssier, C. P.; Rey, P. F.; Korchinski, M.

2017-12-01

Plate convergence involving continental lithosphere leads to crustal melting, which ultimately stabilizes the crust because it drives rapid upward flow of hot deep crust, followed by rapid cooling at shallow levels. Collision drives partial melting during crustal thickening (at 40-75 km) and/or continental subduction (at 75-100 km). These depths are not typically exceeded by crustal rocks that are exhumed in each setting because partial melting significantly decreases viscosity, facilitating upward flow of deep crust. Results from numerical models and nature indicate that deep crust moves laterally and then vertically, crystallizing at depths as shallow as 2 km. Deep crust flows en masse, without significant segregation of melt into magmatic bodies, over 10s of kms of vertical transport. This is a major mechanism by which deep crust is exhumed and is therefore a significant process of heat and mass transfer in continental evolution. The result of vertical flow of deep, partially molten crust is a migmatite dome. When lithosphere is under extension or transtension, the deep crust is solicited by faulting of the brittle upper crust, and the flow of deep crust in migmatite domes traverses nearly the entire thickness of orogenic crust in <10 million years. This cycle of burial, partial melting, rapid ascent, and crystallization/cooling preserves the continents from being recycled into the mantle by convergent tectonic processes over geologic time. Migmatite domes commonly preserve a record of high-T - low-P metamorphism. Domes may also contain rocks or minerals that record high-T - high-P conditions, including high-P metamorphism broadly coeval with host migmatite, evidence for the deep crustal origin of migmatite. There exists a spectrum of domes, from entirely deep-sourced to mixtures of deep and shallow sources. Controlling factors in deep vs. shallow sources are relative densities of crustal layers and rate of extension: fast extension (cm/yr) promotes efficient ascent of deep crust, whereas slow extension (mm/yr) produces significantly less exhumation. Recognition of the importance of migmatite (gneiss) domes as archives of orogenic deep crust is applicable to determining the chemical and physical properties of continental crust, as well as mechanisms and timescales of crustal differentiation.

Advancing Navigation, Timing, and Science with the Deep Space Atomic Clock

NASA Technical Reports Server (NTRS)

Ely, Todd A.; Seubert, Jill; Bell, Julia

2014-01-01

NASA's Deep Space Atomic Clock mission is developing a small, highly stable mercury ion atomic clock with an Allan deviation of at most 1e-14 at one day, and with current estimates near 3e-15. This stability enables one-way radiometric tracking data with accuracy equivalent to and, in certain conditions, better than current two-way deep space tracking data; allowing a shift to a more efficient and flexible one-way deep space navigation architecture. DSAC-enabled one-way tracking will benefit navigation and radio science by increasing the quantity and quality of tracking data. Additionally, DSAC would be a key component to fully-autonomous onboard radio navigation useful for time-sensitive situations. Potential deep space applications of DSAC are presented, including orbit determination of a Mars orbiter and gravity science on a Europa flyby mission.

Power and Efficiency Optimized in Traveling-Wave Tubes Over a Broad Frequency Bandwidth

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.

2001-01-01

A traveling-wave tube (TWT) is an electron beam device that is used to amplify electromagnetic communication waves at radio and microwave frequencies. TWT's are critical components in deep space probes, communication satellites, and high-power radar systems. Power conversion efficiency is of paramount importance for TWT's employed in deep space probes and communication satellites. A previous effort was very successful in increasing efficiency and power at a single frequency (ref. 1). Such an algorithm is sufficient for narrow bandwidth designs, but for optimal designs in applications that require high radiofrequency power over a wide bandwidth, such as high-density communications or high-resolution radar, the variation of the circuit response with respect to frequency must be considered. This work at the NASA Glenn Research Center is the first to develop techniques for optimizing TWT efficiency and output power over a broad frequency bandwidth (ref. 2). The techniques are based on simulated annealing, which has the advantage over conventional optimization techniques in that it enables the best possible solution to be obtained (ref. 3). Two new broadband simulated annealing algorithms were developed that optimize (1) minimum saturated power efficiency over a frequency bandwidth and (2) simultaneous bandwidth and minimum power efficiency over the frequency band with constant input power. The algorithms were incorporated into the NASA coupled-cavity TWT computer model (ref. 4) and used to design optimal phase velocity tapers using the 59- to 64-GHz Hughes 961HA coupled-cavity TWT as a baseline model. In comparison to the baseline design, the computational results of the first broad-band design algorithm show an improvement of 73.9 percent in minimum saturated efficiency (see the top graph). The second broadband design algorithm (see the bottom graph) improves minimum radiofrequency efficiency with constant input power drive by a factor of 2.7 at the high band edge (64 GHz) and increases simultaneous bandwidth by 500 MHz.

SURPHEX (tm): New dry photopolymers for replication of surface relief diffractive optics

NASA Technical Reports Server (NTRS)

Shvartsman, Felix P.

1993-01-01

High efficiency, deep groove, surface relief Diffractive Optical Elements (DOE) with various optical functions can be recorded in a photoresist using conventional interferometric holographic and computer generated photolithographic recording techniques. While photoresist recording media are satisfactory for recording individual surface relief DOE, a reliable and precise method is needed to replicate these diffractive microstructures to maintain the high aspect ratio in each replicated DOE. The term 'high aspect ratio' means that the depth of a groove is substantially greater, i.e. 2, 3, or more times greater, than the width of the groove. A new family of dry photopolymers SURPHEX was developed recently at Du Pont to replicate such highly efficient, deep groove DOE's. SURPHEX photopolymers are being utilized in Du Pont's proprietary Dry Photopolymer Embossing (DPE) technology to replicate with very high degree of precision almost any type of surface relief DOE. Surfaces relief microstructures with width/depth aspect ratio of 1:20 (0.1 micron/2.0 micron) were faithfully replicated by DPE technology. Several types of plastic and glass/quartz optical substrates can be used for economical replication of DOE.

Versatile benzimidazole/triphenylamine hybrids: efficient nondoped deep-blue electroluminescence and good host materials for phosphorescent emitters.

PubMed

Gong, Shaolong; Zhao, Yongbiao; Wang, Meng; Yang, Chuluo; Zhong, Cheng; Qin, Jingui; Ma, Dongge

2010-09-03

Two new bipolar compounds, N,N,N',N'-tetraphenyl-5'-(1-phenyl-1H-benzimidazol-2-yl)-1,1':3',1''-terphenyl-4,4''-diamine (1) and N,N,N',N'-tetraphenyl-5'-(1-phenyl-1H-benzimidazol-2-yl)-1,1':3',1''-terphenyl-3,3''-diamine (2), were synthesized and characterized, and their thermal, photophysical, and electrochemical properties were investigated. Compounds 1 and 2 possess good thermal stability with high glass-transition temperatures of 109-129 degrees C and thermal decomposition temperatures of 501-531 degrees C. The fluorescence quantum yield of 1 (0.52) is higher than that of 2 (0.16), which could be attributed to greater pi conjugation between the donor and acceptor moieties. A nondoped deep-blue fluorescent organic light-emitting diode (OLED) using 1 as the blue emitter displays high performance, with a maximum current efficiency of 2.2 cd A(-1) and a maximum external efficiency of 2.9 % at the CIE coordinates of (0.17, 0.07) that are very close to the National Television System Committee's blue standard (0.15, 0.07). Electrophosphorescent devices using the two compounds as host materials for green and red phosphor emitters show high efficiencies. The best performance of a green phosphorescent device was achieved using 2 as the host, with a maximum current efficiency of 64.3 cd A(-1) and a maximum power efficiency of 68.3 lm W(-1); whereas the best performance of a red phosphorescent device was achieved using 1 as the host, with a maximum current efficiency of 11.5 cd A(-1), and a maximum power efficiency of 9.8 lm W(-1). The relationship between the molecular structures and optoelectronic properties are discussed.

Unified design of sinusoidal-groove fused-silica grating.

PubMed

Feng, Jijun; Zhou, Changhe; Cao, Hongchao; Lu, Peng

2010-10-20

A general design rule of deep-etched subwavelength sinusoidal-groove fused-silica grating as a highly efficient polarization-independent or polarization-selective device is studied based on the simplified modal method, which shows that the device structure depends little on the incident wavelength, but mainly on the ratio of groove depth to incident wavelength and the ratio of wavelength to grating period. These two ratios could be used as the design guidelines for wavelength-independent structure from deep ultraviolet to far infrared. The optimized grating profile with a different function as a polarizing beam splitter, a polarization-independent two-port beam splitter, or a polarization-independent grating with high efficiency of -1st order is obtained at a wavelength of 1064 nm, and verified by using the rigorous coupled-wave analysis. The performance of the sinusoidal grating is better than a conventional rectangular one, which could be useful for practical applications.

Magnetic Fe-Co films electroplated in a deep-eutectic-solvent-based plating bath

NASA Astrophysics Data System (ADS)

Yanai, T.; Shiraishi, K.; Watanabe, Y.; Ohgai, T.; Nakano, M.; Suzuki, K.; Fukunaga, H.

2015-05-01

We fabricated Fe-Co films from a deep eutectic solvent (DES)-based plating bath and investigated magnetic properties of the plated films. The plating baths were obtained by stirring the mixture of choline chloride, ethylene glycol, FeCl2.4H2O, and CoCl2.6H2O. The composition of the plated films depended on the amount of FeCl2.4H2O in the plating bath, and Fe content of the films was varied from 0 to 100 at. %. Depending on the Fe content, the saturation magnetization and the coercivity of the films varied. The Fe76Co24 film shows high saturation magnetization and smooth surface, and the change in the saturation magnetization shows good agreement with the expected change by the Slater-Pauling curve. High current efficiency (>90%) could be obtained in the wide film composition. From these results, we concluded that the DES-based plating bath is one of effective baths for the Fe-Co films with high current efficiency.

Absolute S- and P-plane polarization efficiencies for high frequency holographic gratings in the VUV

NASA Technical Reports Server (NTRS)

Caruso, A. J.; Woodgate, B. E.; Mount, G. H.

1981-01-01

High frequency plane gratings (3500 and 3600 gr/mm) have been holographically ruled and blazed for the VUV spectral region. All gratings were coated with 70 nm Al + 25 nm MgF2. Absolute unpolarized and S- and P-plane polarization efficiencies have been measured for the first and second orders in the 120- to 450-nm spectral region at 18.5 and 30 deg angles of deviation. For deep grooves, anomalous features are more pronounced for the P-plane polarization efficiency than for the S-plane polarization efficiency. Holographic gratings can be tailored to produce high polarization or low polarization in the VUV. For comparison, efficiencies and polarization of the best conventional high frequency gratings were also determined. Measurements show that scattered light is significantly lower for holographic gratings in the VUV when compared with the conventional gratings.

Technique Developed for Optimizing Traveling-Wave Tubes

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.

1999-01-01

A traveling-wave tube (TWT) is an electron beam device that is used to amplify electromagnetic communication waves at radio and microwave frequencies. TWT s are critical components in deep-space probes, geosynchronous communication satellites, and high-power radar systems. Power efficiency is of paramount importance for TWT s employed in deep-space probes and communications satellites. Consequently, increasing the power efficiency of TWT s has been the primary goal of the TWT group at the NASA Lewis Research Center over the last 25 years. An in-house effort produced a technique (ref. 1) to design TWT's for optimized power efficiency. This technique is based on simulated annealing, which has an advantage over conventional optimization techniques in that it enables the best possible solution to be obtained (ref. 2). A simulated annealing algorithm was created and integrated into the NASA TWT computer model (ref. 3). The new technique almost doubled the computed conversion power efficiency of a TWT from 7.1 to 13.5 percent (ref. 1).

Deep eutectic solvent-based valorization of spent coffee grounds.

PubMed

Yoo, Da Eun; Jeong, Kyung Min; Han, Se Young; Kim, Eun Mi; Jin, Yan; Lee, Jeongmi

2018-07-30

Spent coffee grounds (SCGs) are viewed as a valuable resource for useful bioactive compounds, such as chlorogenic acids and flavonoids, and we suggest an eco-friendly and efficient valorization method. A series of choline chloride-based deep eutectic solvents (DESs) were tested as green extraction solvents for use with ultrasound-assisted extraction. Extraction efficiency was evaluated based on total phenolic content (TPC), total flavonoid content, total chlorogenic acids, and/or anti-oxidant activity. A binary DES named HC-6, which was composed of 1,6-hexanediol:choline chloride (molar ratio 7:1) was designed to produce the highest efficiency. Experimental conditions were screened and optimized for maximized efficiency using a two-level fractional factorial design and a central composite design, respectively. As a result, the proposed method presented significantly enhanced TPC and anti-oxidant activity. In addition, phenolic compounds could be easily recovered from extracts at high recovery yields (>90%) by adsorption chromatography. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Seismic tomography as a tool for measuring stress in mines

USGS Publications Warehouse

Scott, Douglas F.; Williams, T.J.; Denton, D.K.; Friedel, M.J.

1999-01-01

Spokane Research Center personnel have been investigating the use of seismic tomography to monitor the behavior of a rock mass, detect hazardous ground conditions and assess the mechanical integrity of a rock mass affected by mining. Seismic tomography can be a valuable tool for determining relative stress in deep, >1,220-m (>4,000-ft), underground pillars. If high-stress areas are detected, they can be destressed prior to development or they can be avoided. High-stress areas can be monitored with successive seismic surveys to determine if stress decreases to a level where development can be initiated safely. There are several benefits to using seismic tomography to identify high stress in deep underground pillars. The technique is reliable, cost-effective, efficient and noninvasive. Also, investigators can monitor large rock masses, as well as monitor pillars during the mining cycle. By identifying areas of high stress, engineers will be able to assure that miners are working in a safer environment.Spokane Research Center personnel have been investigating the use of seismic tomography to monitor the behavior of a rock mass, detect hazardous ground conditions and assess the mechanical integrity of a rock mass affected by mining. Seismic tomography can be a valuable tool for determining relative stress in deep, >1,200-m (>4,000-ft), underground pillars. If high-stress areas are detected, they can be destressed prior to development or they can be avoided. High-stress areas can be monitored with successive seismic surveys to determine if stress decreases to a level where development can be initiated safely. There are several benefits to using seismic tomography to identify high stress in deep underground pillars. The technique is reliable, cost-effective, efficient and noninvasive. Also, investigators can monitor large rock masses, as well as monitor pillars during the mining cycle. By identifying areas of high stress. engineers will be able to assure that miners are working in a safer environment.

Impacts on the deep-sea ecosystem by a severe coastal storm.

PubMed

Sanchez-Vidal, Anna; Canals, Miquel; Calafat, Antoni M; Lastras, Galderic; Pedrosa-Pàmies, Rut; Menéndez, Melisa; Medina, Raúl; Company, Joan B; Hereu, Bernat; Romero, Javier; Alcoverro, Teresa

2012-01-01

Major coastal storms, associated with strong winds, high waves and intensified currents, and occasionally with heavy rains and flash floods, are mostly known because of the serious damage they can cause along the shoreline and the threats they pose to navigation. However, there is a profound lack of knowledge on the deep-sea impacts of severe coastal storms. Concurrent measurements of key parameters along the coast and in the deep-sea are extremely rare. Here we present a unique data set showing how one of the most extreme coastal storms of the last decades lashing the Western Mediterranean Sea rapidly impacted the deep-sea ecosystem. The storm peaked the 26(th) of December 2008 leading to the remobilization of a shallow-water reservoir of marine organic carbon associated with fine particles and resulting in its redistribution across the deep basin. The storm also initiated the movement of large amounts of coarse shelf sediment, which abraded and buried benthic communities. Our findings demonstrate, first, that severe coastal storms are highly efficient in transporting organic carbon from shallow water to deep water, thus contributing to its sequestration and, second, that natural, intermittent atmospheric drivers sensitive to global climate change have the potential to tremendously impact the largest and least known ecosystem on Earth, the deep-sea ecosystem.

Impacts on the Deep-Sea Ecosystem by a Severe Coastal Storm

PubMed Central

Sanchez-Vidal, Anna; Canals, Miquel; Calafat, Antoni M.; Lastras, Galderic; Pedrosa-Pàmies, Rut; Menéndez, Melisa; Medina, Raúl; Company, Joan B.; Hereu, Bernat; Romero, Javier; Alcoverro, Teresa

2012-01-01

Major coastal storms, associated with strong winds, high waves and intensified currents, and occasionally with heavy rains and flash floods, are mostly known because of the serious damage they can cause along the shoreline and the threats they pose to navigation. However, there is a profound lack of knowledge on the deep-sea impacts of severe coastal storms. Concurrent measurements of key parameters along the coast and in the deep-sea are extremely rare. Here we present a unique data set showing how one of the most extreme coastal storms of the last decades lashing the Western Mediterranean Sea rapidly impacted the deep-sea ecosystem. The storm peaked the 26th of December 2008 leading to the remobilization of a shallow-water reservoir of marine organic carbon associated with fine particles and resulting in its redistribution across the deep basin. The storm also initiated the movement of large amounts of coarse shelf sediment, which abraded and buried benthic communities. Our findings demonstrate, first, that severe coastal storms are highly efficient in transporting organic carbon from shallow water to deep water, thus contributing to its sequestration and, second, that natural, intermittent atmospheric drivers sensitive to global climate change have the potential to tremendously impact the largest and least known ecosystem on Earth, the deep-sea ecosystem. PMID:22295084

Plasmonic based light manipulation and applications in AIGaN deep-UV devices (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yin, Jun; Li, Jing; Kang, Junyong

2016-09-01

Recently, surface plasmon (SP)-exciton coupling has been wildly applied in nitride semiconductors in order to improve the spontaneous radiative recombination rate [1-3]. However, most works have been focused on the emission enhancement in InGaN-based blue or green light emitting diodes (LEDs). Practically, it is significantly important to improve the emission efficiency in deep-UV AlGaN-base quantum well (QW) structure due to its intrinsically low internal quantum efficiency (IQE) induced by the high defect density in its epitaxy layer [4]. But, the effective SP-exciton coupling with matched energy in deep-UV region is still a challenge issue due to the lack of appropriate metal structures and compatible fabrication techniques. In this work, the Al nanoparticles (NPs) were introduced by the nanosphere lithography (NSL) and deposition techniques into the AlGaN based MQWs with optimized size and structure. Due to the local surface plasmon (LSP) coupling with the excitons in QWs, emission enhancement in deep UV region has been achieved in the Al NPs decorated AlGaN MQWs structure with comparison to the bare MQWs. Theoretical calculations on the energy subbands of AlGaN QWs were further carried out to investigate the corresponding mechanisms, in which the hot carrier transition activated by SP-exciton coupling was believed to be mainly responsible for the enhancement. This work demonstrated a low cost, wafer scale fabrication process, which can be potentially employed to the practical SP-enhanced AlGaN-based deep UV LEDs with high IQEs.

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

PubMed Central

Gong, Cihun-Siyong Alex; Lai, Hsin-Yi; Huang, Sy-Han; Lo, Yu-Chun; Lee, Nicole; Chen, Pin-Yuan; Tu, Po-Hsun; Yang, Chia-Yen; Lin, James Chang-Chieh; Chen, You-Yin

2015-01-01

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. PMID:26029954

Enhancing the light-extraction efficiency of AlGaN deep-ultraviolet light-emitting diodes using highly reflective Ni/Mg and Rh as p-type electrodes

NASA Astrophysics Data System (ADS)

Maeda, Noritoshi; Yun, Joosun; Jo, Masafumi; Hirayama, Hideki

2018-04-01

Improving the light-extraction efficiency (LEE) is a major issue for the development of deep-ultraviolet (DUV) light-emitting diodes (LEDs). For this improvement, we introduced a transparent p-AlGaN contact layer and a reflective p-type electrode. In this work, we investigated the improvements obtained by replacing conventional Ni/Au p-type electrodes with highly reflective Ni/Mg and Rh electrodes. The external quantum efficiencies (EQEs) of 279 nm DUV LEDs were increased from 4.2 to 6.6% and from 3.4 to 4.5% by introducing Ni/Mg and Rh p-type electrodes, respectively. The LEE enhancement factors for the Ni/Mg and Rh electrodes were 1.6 and 1.4, respectively. These results are explained by the fact that the measured reflectances of the Ni/Mg and Rh electrodes were approximately 80 and 55%, respectively. Moreover, it was concluded that a passivation layer is required for Ni/Mg electrodes to prevent the degradation of the LED properties by the oxidation of Mg.

Effects of electrolysis time and electric potential on chlorine generation of electrolyzed deep ocean water.

PubMed

Hsu, Guoo-Shyng Wang; Lu, Yi-Fa; Hsu, Shun-Yao

2017-10-01

Electrolyzed water is a sustainable disinfectant, which can comply with food safety regulations and is environmentally friendly. A two-factor central composite design was adopted for studying the effects of electrolysis time and electric potential on the chlorine generation efficiency of electrolyzed deep ocean water (DOW). DOW was electrolyzed in a glass electrolyzing cell equipped with platinum-plated titanium anode and cathode. The results showed that chlorine concentration reached maximal level in the batch process. Prolonged electrolysis reduced chlorine concentration in the electrolyte and was detrimental to electrolysis efficiency, especially under high electric potential conditions. Therefore, the optimal choice of electrolysis time depends on the electrolyzable chloride in DOW and cell potential adopted for electrolysis. The higher the electric potential, the faster the chlorine level reaches its maximum, but the lower the electric efficiency will be. Copyright © 2016. Published by Elsevier B.V.

Widely tunable asymmetric long-period fiber grating with high sensitivity using optical polymer on laser-ablated cladding.

PubMed

Chen, Nan-Kuang; Hsu, Der-Yi; Chi, Sien

2007-08-01

We demonstrate high-efficiency, wideband-tunable, laser-ablated long-period fiber gratings that use an optical polymer overlay. Portions of the fiber cladding are periodically removed by CO(2) laser pulses to induce periodic index changes for coupling the core mode into cladding modes. An optical polymer with a high thermo-optic coefficient with a dispersion distinct from that of silica is used on a deep-ablated cladding structure so that the effective indices of cladding modes become dispersive and the resonant wavelengths can be efficiently tuned. The tuning efficiency can be as high as 15.8 nm/ degrees C, and the tuning range can be wider than 105 nm (1545-1650 nm).

Deep-UV-sensitive high-frame-rate backside-illuminated CCD camera developments

NASA Astrophysics Data System (ADS)

Dawson, Robin M.; Andreas, Robert; Andrews, James T.; Bhaskaran, Mahalingham; Farkas, Robert; Furst, David; Gershstein, Sergey; Grygon, Mark S.; Levine, Peter A.; Meray, Grazyna M.; O'Neal, Michael; Perna, Steve N.; Proefrock, Donald; Reale, Michael; Soydan, Ramazan; Sudol, Thomas M.; Swain, Pradyumna K.; Tower, John R.; Zanzucchi, Pete

2002-04-01

New applications for ultra-violet imaging are emerging in the fields of drug discovery and industrial inspection. High throughput is critical for these applications where millions of drug combinations are analyzed in secondary screenings or high rate inspection of small feature sizes over large areas is required. Sarnoff demonstrated in1990 a back illuminated, 1024 X 1024, 18 um pixel, split-frame-transfer device running at > 150 frames per second with high sensitivity in the visible spectrum. Sarnoff designed, fabricated and delivered cameras based on these CCDs and is now extending this technology to devices with higher pixel counts and higher frame rates through CCD architectural enhancements. The high sensitivities obtained in the visible spectrum are being pushed into the deep UV to support these new medical and industrial inspection applications. Sarnoff has achieved measured quantum efficiencies > 55% at 193 nm, rising to 65% at 300 nm, and remaining almost constant out to 750 nm. Optimization of the sensitivity is being pursued to tailor the quantum efficiency for particular wavelengths. Characteristics of these high frame rate CCDs and cameras will be described and results will be presented demonstrating high UV sensitivity down to 150 nm.

Aerosol transport and wet scavenging in deep convective clouds: a case study and model evaluation using a multiple passive tracer analysis approach

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

Yang, Qing; Easter, Richard C.; Campuzano-Jost, Pedro

2015-08-20

The effect of wet scavenging on ambient aerosols in deep, continental convective clouds in the mid-latitudes is studied for a severe storm case in Oklahoma during the Deep Convective Clouds and Chemistry (DC3) field campaign. A new passive-tracer based transport analysis framework is developed to characterize the convective transport based on the vertical distribution of several slowly reacting and nearly insoluble trace gases. The passive gas concentration in the upper troposphere convective outflow results from a mixture of 47% from the lower level (0-3 km), 21% entrained from the upper troposphere, and 32% from mid-atmosphere based on observations. The transportmore » analysis framework is applied to aerosols to estimate aerosol transport and wet-scavenging efficiency. Observations yield high overall scavenging efficiencies of 81% and 68% for aerosol mass (Dp < 1μm) and aerosol number (0.03< Dp < 2.5μm), respectively. Little chemical selectivity to wet scavenging is seen among observed submicron sulfate (84%), organic (82%), and ammonium (80%) aerosols, while nitrate has a much lower scavenging efficiency of 57% likely due to the uptake of nitric acid. Observed larger size particles (0.15 - 2.5μm) are scavenged more efficiently (84%) than smaller particles (64%; 0.03 - 0.15μm). The storm is simulated using the chemistry version of the WRF model. Compared to the observation based analysis, the standard model underestimates the wet scavenging efficiency for both mass and number concentrations with low biases of 31% and 40%, respectively. Adding a new treatment of secondary activation significantly improves simulation results, so that the bias in scavenging efficiency in mass and number concentrations is reduced to <10%. This supports the hypothesis that secondary activation is an important process for wet removal of aerosols in deep convective storms.« less

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

PubMed

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.

Electrical Activation Studies of Silicon Implanted Aluminum Gallium Nitride with High Aluminum Mole Fraction

DTIC Science & Technology

2007-12-01

realized with silicon due to its indirect band gap that results in poor quantum efficiency . The first LEDs and laser diodes were developed with...deep UV (λ < 340 nm) still face many challenges and have low internal quantum efficiency . Jong Kyu Kim et al. have developed a light emitting triode...LET) to try to overcome some of the challenges and 16 have produced a lighting device with increased quantum efficiency (16). AlxGa1-xN has been

On the impact of approximate computation in an analog DeSTIN architecture.

PubMed

Young, Steven; Lu, Junjie; Holleman, Jeremy; Arel, Itamar

2014-05-01

Deep machine learning (DML) holds the potential to revolutionize machine learning by automating rich feature extraction, which has become the primary bottleneck of human engineering in pattern recognition systems. However, the heavy computational burden renders DML systems implemented on conventional digital processors impractical for large-scale problems. The highly parallel computations required to implement large-scale deep learning systems are well suited to custom hardware. Analog computation has demonstrated power efficiency advantages of multiple orders of magnitude relative to digital systems while performing nonideal computations. In this paper, we investigate typical error sources introduced by analog computational elements and their impact on system-level performance in DeSTIN--a compositional deep learning architecture. These inaccuracies are evaluated on a pattern classification benchmark, clearly demonstrating the robustness of the underlying algorithm to the errors introduced by analog computational elements. A clear understanding of the impacts of nonideal computations is necessary to fully exploit the efficiency of analog circuits.

Detecting atrial fibrillation by deep convolutional neural networks.

PubMed

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.

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

PubMed

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-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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.

Deep imitation learning for 3D navigation tasks.

PubMed

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.

Slow slip rate and excitation efficiency of deep low-frequency tremors beneath southwest Japan

NASA Astrophysics Data System (ADS)

Daiku, Kumiko; Hiramatsu, Yoshihiro; Matsuzawa, Takanori; Mizukami, Tomoyuki

2018-01-01

We estimated the long-term average slip rate on the plate interface across the Nankai subduction zone during 2002-2013 using deep low-frequency tremors as a proxy for short-term slow slip events based on empirical relations between the seismic moment of short-term slow slip events and tremor activities. The slip rate in each region is likely to compensate for differences between the convergence rate and the slip deficit rate of the subducting Philippine Sea plate estimated geodetically, although the uncertainty is large. This implies that the strain because of the subduction of the plate is partially stored as the slip deficit and partially released by slow slip events during the interseismic period. The excitation efficiency of the tremors for the slow slip events differs among regions: it is high in the northern Kii region. Some events in the western Shikoku region show a somewhat large value. Antigorite serpentinite of two types exists in the mantle wedge beneath southwest Japan. Slips with more effective excitation of tremors presumably occur in high-temperature conditions in the antigorite + olivine stability field. Other slip events with low excitation efficiency are distributed in the antigorite + brucite stability field. Considering the formation reactions of these minerals and their characteristic structures, events with high excitation efficiency can be correlated with a high pore fluid pressure condition. This result suggests that variation in pore fluid pressure on the plate interface affects the magnitude of tremors excited by slow slip events.

Ocean sequestration of crop residue carbon: recycling fossil fuel carbon back to deep sediments.

PubMed

Strand, Stuart E; Benford, Gregory

2009-02-15

For significant impact any method to remove CO2 from the atmosphere must process large amounts of carbon efficiently, be repeatable, sequester carbon for thousands of years, be practical, economical and be implemented soon. The only method that meets these criteria is removal of crop residues and burial in the deep ocean. We show here that this method is 92% efficient in sequestration of crop residue carbon while cellulosic ethanol production is only 32% and soil sequestration is about 14% efficient. Deep ocean sequestration can potentially capture 15% of the current global CO2 annual increase, returning that carbon backto deep sediments, confining the carbon for millennia, while using existing capital infrastructure and technology. Because of these clear advantages, we recommend enhanced research into permanent sequestration of crop residues in the deep ocean.

Deep subwavelength fourfold rotationally symmetric split-ring-resonator metamaterials for highly sensitive and robust biosensing platform

PubMed Central

Tobing, Landobasa Y. M.; Tjahjana, Liliana; Zhang, Dao Hua; Zhang, Qing; Xiong, Qihua

2013-01-01

Metamaterials provide a good platform for biochemical sensing due to its strong field localization at nanoscale. In this work, we show that electric and magnetic resonant modes in split-ring-resonator (SRR) can be efficiently excited under unpolarized light illumination when the SRRs are arranged in fourfold rotationally symmetric lattice configuration. The fabrication and characterization of deep subwavelength (~λ/15) gold-based SRR structures with resonator size as small as ~ 60 nm are reported with magnetic resonances in Vis-NIR spectrum range. The feasibility for sensing is demonstrated with refractive index sensitivity as high as ~ 636 nm/RIU. PMID:23942416

Quantum Phenomena in High Energy Density Plasmas

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

Murnane, Margaret; Kapteyn, Henry

The possibility of implementing efficient (phase matched) HHG upconversion of deep- UV lasers in multiply-ionized plasmas, with potentially unprecedented conversion efficiency is a fascinating prospect. HHG results from the extreme nonlinear response of matter to intense laser light:high harmonics are radiated as a result of a quantum coherent electron recollision process that occurs during laser field ionization of an atom. Under current support from this grant in work published in Science in 2015, we discovered a new regime of bright HHG in highly-ionized plasmas driven by intense UV lasers, that generates bright harmonics to photon energies >280eV

deepTools: a flexible platform for exploring deep-sequencing data.

PubMed

Ramírez, Fidel; Dündar, Friederike; Diehl, Sarah; Grüning, Björn A; Manke, Thomas

2014-07-01

We present a Galaxy based web server for processing and visualizing deeply sequenced data. The web server's core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straight-forward, yet highly customizable manner. In addition, we offer several tools for the analysis of files containing aligned reads and enable efficient and reproducible generation of normalized coverage files. As a modular and open-source platform, deepTools can easily be expanded and customized to future demands and developments. The deepTools webserver is freely available at http://deeptools.ie-freiburg.mpg.de and is accompanied by extensive documentation and tutorials aimed at conveying the principles of deep-sequencing data analysis. The web server can be used without registration. deepTools can be installed locally either stand-alone or as part of Galaxy. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

High performance cryogenic turboexpanders

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

Agahi, R.R.; Ershaghi, B.; Lin, M.C.

1996-12-31

The use of turboexpanders for deep cryogenic temperatures has been constrained because of thermal efficiency limitations. This limited thermal efficiency was mostly due to mechanical constraints. Recent improvements in analytical techniques, bearing technology, and design features have made it possible to design and operate turboexpanders at more favorable conditions, such as of higher rotational speeds. Several turboexpander installations in helium and hydrogen processes have shown a significant improvement in plant performance over non-turboexpander options.

Project DEEP STEAM

NASA Astrophysics Data System (ADS)

Aeschliman, D. P.; Clay, R. G.; Donaldson, A. B.; Eisenhawer, S. W.; Fox, R. L.; Johnson, D. R.; Mulac, A. J.

1982-01-01

The objective of Project DEEP STEAM is to develop the technology to economically produce heavy oils from deep reservoirs. The tasks included in this project are the development of thermally efficient delivery systems and downhole steam generation systems. During the period January 1-March 31, 1981, effort has continued on a low pressure combustion downhole generator (Rocketdyne), and on two high pressure designs (Foster-Miller Associates, Sandia National Laboratories). The Sandia design was prepared for deployment in the Wilmington Field at Long Beach, California. Progress continued on the Min-Stress II packer concept at L'Garde, Inc., and on the extruded metal packer at Foster-Miller. Initial bare string field data are reported on the insulated tubular test at Lloydminster, Saskatchewan, Canada.

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.

PubMed

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

2018-04-24

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.

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

NASA Astrophysics Data System (ADS)

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.

Efficient collective swimming by harnessing vortices through deep reinforcement learning.

PubMed

Verma, Siddhartha; Novati, Guido; Koumoutsakos, Petros

2018-06-05

Fish in schooling formations navigate complex flow fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behavior has been associated with evolutionary advantages including energy savings, yet the underlying physical mechanisms remain unknown. We show that fish can improve their sustained propulsive efficiency by placing themselves in appropriate locations in the wake of other swimmers and intercepting judiciously their shed vortices. This swimming strategy leads to collective energy savings and is revealed through a combination of high-fidelity flow simulations with a deep reinforcement learning (RL) algorithm. The RL algorithm relies on a policy defined by deep, recurrent neural nets, with long-short-term memory cells, that are essential for capturing the unsteadiness of the two-way interactions between the fish and the vortical flow field. Surprisingly, we find that swimming in-line with a leader is not associated with energetic benefits for the follower. Instead, "smart swimmer(s)" place themselves at off-center positions, with respect to the axis of the leader(s) and deform their body to synchronize with the momentum of the oncoming vortices, thus enhancing their swimming efficiency at no cost to the leader(s). The results confirm that fish may harvest energy deposited in vortices and support the conjecture that swimming in formation is energetically advantageous. Moreover, this study demonstrates that deep RL can produce navigation algorithms for complex unsteady and vortical flow fields, with promising implications for energy savings in autonomous robotic swarms.

Optimal Cooling of High Purity Germanium Spectrometers for Missions to Planets and Moons

NASA Astrophysics Data System (ADS)

Chernenko, A.; Kostenko, V.; Konev, S.; Rybkin, B.; Paschin, A.; Prokopenko, I.

2004-04-01

Gamma-ray spectrometers based on high purity germanium (HPGe) detectors are ultimately sensitive instruments for composition studies of surfaces of planets and moons. However, they require deep cooling well below 120K for the entire duration of space mission, and this challenges the feasibility of such instruments in the era of small and cost-efficient missions. In this paper we summarise our experience in the field of the theoretical and experimental studies of optimal cryogenic cooling of gamma-ray spectrometers based on HPGe detectors in order to find out how efficient, light and compact these instruments could be, provided such technologies like cryogenic heat pipe diodes (HPDs), efficient thermal insulation and efficient miniature cryocoolers are used.

High efficiency single Ag nanowire/p-GaN substrate Schottky junction-based ultraviolet light emitting diodes

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

Wu, Y.; Li, X.; Xu, P.

2015-02-02

We report a high efficiency single Ag nanowire (NW)/p-GaN substrate Schottky junction-based ultraviolet light emitting diode (UV-LED). The device demonstrates deep UV free exciton electroluminescence at 362.5 nm. The dominant emission, detectable at ultralow (<1 μA) forward current, does not exhibit any shifts when the forward current is increased. External quantum efficiency (EQE) as high as 0.9% is achieved at 25 μA current at room temperature. Experiments and simulation analysis show that devices fabricated with thinner Ag NWs have higher EQE. However, for very thin Ag NWs (diameter < 250 nm), this trend breaks down due to heat accumulation in the NWs. Our simple device architecturemore » offers a potentially cost-effective scheme to fabricate high efficiency Schottky junction-based UV-LEDs.« less

Enabling High Efficiency Nanoplasmonics with Novel Nanoantenna Architectures

PubMed Central

Cohen, Moshik; Shavit, Reuven; Zalevsky, Zeev

2015-01-01

Surface plasmon polaritons (SPPs) are propagating excitations that arise from coupling of light with collective electron oscillations. Characterized by high field intensity and nanometric dimensions, SPPs fashion rapid expansion of interest from fundamental and applicative perspectives. However, high metallic losses at optical frequencies still make nanoplasmonics impractical when high absolute efficiency is paramount, with major challenge is efficient plasmon generation in deep nanoscale. Here we introduce the Plantenna, the first reported nanodevice with the potential of addressing these limitations utilizing novel plasmonic architecture. The Plantenna has simple 2D structure, ultracompact dimensions and is fabricated on Silicon chip for future CMOS integration. We design the Plantenna to feed channel (20 nm × 20 nm) nanoplasmonic waveguides, achieving 52% coupling efficiency with Plantenna dimensions of λ3/17,000. We theoretically and experimentally show that the Plantenna enormously outperforms dipole couplers, achieving 28 dB higher efficiency with broad polarization diversity and huge local field enhancement. Our findings confirm the Plantenna as enabling device for high efficiency plasmonic technologies such as quantum nanoplasmonics, molecular strong coupling and plasmon nanolasers. PMID:26620270

Long-lived and highly efficient green and blue phosphorescent emitters and device architectures for OLED displays

NASA Astrophysics Data System (ADS)

Eickhoff, Christian; Murer, Peter; Geßner, Thomas; Birnstock, Jan; Kröger, Michael; Choi, Zungsun; Watanabe, Soichi; May, Falk; Lennartz, Christian; Stengel, Ilona; Münster, Ingo; Kahle, Klaus; Wagenblast, Gerhard; Mangold, Hannah

2015-09-01

In this paper, two OLED device concepts are introduced. First, classical phosphorescent green carbene emitters with unsurpassed lifetime, combined with low voltage and high efficiency are presented and the associated optimized OLED stacks are explained. Second, a path towards highly efficient, long-lived deep blue systems is shown. The high efficiencies can be reached by having the charge-recombination on the phosphorescent carbene emitter while at the same time short emissive lifetimes are realized by fast energy transfer to the fluorescent emitter, which eventually allows for higher OLED stability in the deep blue. Device architectures, materials and performance data are presented showing that carbene type emitters have the potential to outperform established phosphorescent green emitters both in terms of lifetime and efficiency. The specific class of green emitters under investigation shows distinctly larger electron affinities (2.1 to 2.5 eV) and ionization potentials (5.6 to 5.8 eV) as compared to the "standard" emitter Ir(ppy)3 (5.0/1.6 eV). This difference in energy levels requires an adopted OLED design, in particular with respect to emitter hosts and blocking layers. Consequently, in the diode setup presented here, the emitter species is electron transporting or electron trapping. For said green carbene emitters, the typical peak wavelength is 525 nm yielding CIE color coordinates of (x = 0.33, y = 0.62). Device data of green OLEDs are shown with EQEs of 26 %. Driving voltage at 1000 cd/m2 is below 3 V. In an optimized stack, a device lifetime of LT95 > 15,000 h (1000 cd/m2) has been reached, thus fulfilling AMOLED display requirements.

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

NASA Astrophysics Data System (ADS)

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.

Exponential decline of deep-sea ecosystem functioning linked to benthic biodiversity loss.

PubMed

Danovaro, Roberto; Gambi, Cristina; Dell'Anno, Antonio; Corinaldesi, Cinzia; Fraschetti, Simonetta; Vanreusel, Ann; Vincx, Magda; Gooday, Andrew J

2008-01-08

Recent investigations suggest that biodiversity loss might impair the functioning and sustainability of ecosystems. Although deep-sea ecosystems are the most extensive on Earth, represent the largest reservoir of biomass, and host a large proportion of undiscovered biodiversity, the data needed to evaluate the consequences of biodiversity loss on the ocean floor are completely lacking. Here, we present a global-scale study based on 116 deep-sea sites that relates benthic biodiversity to several independent indicators of ecosystem functioning and efficiency. We show that deep-sea ecosystem functioning is exponentially related to deep-sea biodiversity and that ecosystem efficiency is also exponentially linked to functional biodiversity. These results suggest that a higher biodiversity supports higher rates of ecosystem processes and an increased efficiency with which these processes are performed. The exponential relationships presented here, being consistent across a wide range of deep-sea ecosystems, suggest that mutually positive functional interactions (ecological facilitation) can be common in the largest biome of our biosphere. Our results suggest that a biodiversity loss in deep-sea ecosystems might be associated with exponential reductions of their functions. Because the deep sea plays a key role in ecological and biogeochemical processes at a global scale, this study provides scientific evidence that the conservation of deep-sea biodiversity is a priority for a sustainable functioning of the worlds' oceans.

Investigation and development of an effective, economical and efficient concrete pile splice.

DOT National Transportation Integrated Search

2015-06-01

Structures such as bridges or tall buildings often require deep foundations in order to reach soil or rock strata capable of resisting the associated high loads. In Florida, concrete elements such as driven piles, drilled shafts or other cast-in-plac...

Effects of Slow Deep Breathing at High Altitude on Oxygen Saturation, Pulmonary and Systemic Hemodynamics

PubMed Central

Bilo, Grzegorz; Revera, Miriam; Bussotti, Maurizio; Bonacina, Daniele; Styczkiewicz, Katarzyna; Caldara, Gianluca; Giglio, Alessia; Faini, Andrea; Giuliano, Andrea; Lombardi, Carolina; Kawecka-Jaszcz, Kalina; Mancia, Giuseppe; Agostoni, Piergiuseppe; Parati, Gianfranco

2012-01-01

Slow deep breathing improves blood oxygenation (SpO2) and affects hemodynamics in hypoxic patients. We investigated the ventilatory and hemodynamic effects of slow deep breathing in normal subjects at high altitude. We collected data in healthy lowlanders staying either at 4559 m for 2–3 days (Study A; N = 39) or at 5400 m for 12–16 days (Study B; N = 28). Study variables, including SpO2 and systemic and pulmonary arterial pressure, were assessed before, during and after 15 minutes of breathing at 6 breaths/min. At the end of slow breathing, an increase in SpO2 (Study A: from 80.2±7.7% to 89.5±8.2%; Study B: from 81.0±4.2% to 88.6±4.5; both p<0.001) and significant reductions in systemic and pulmonary arterial pressure occurred. This was associated with increased tidal volume and no changes in minute ventilation or pulmonary CO diffusion. Slow deep breathing improves ventilation efficiency for oxygen as shown by blood oxygenation increase, and it reduces systemic and pulmonary blood pressure at high altitude but does not change pulmonary gas diffusion. PMID:23152851

Effects of slow deep breathing at high altitude on oxygen saturation, pulmonary and systemic hemodynamics.

PubMed

Bilo, Grzegorz; Revera, Miriam; Bussotti, Maurizio; Bonacina, Daniele; Styczkiewicz, Katarzyna; Caldara, Gianluca; Giglio, Alessia; Faini, Andrea; Giuliano, Andrea; Lombardi, Carolina; Kawecka-Jaszcz, Kalina; Mancia, Giuseppe; Agostoni, Piergiuseppe; Parati, Gianfranco

2012-01-01

Slow deep breathing improves blood oxygenation (Sp(O2)) and affects hemodynamics in hypoxic patients. We investigated the ventilatory and hemodynamic effects of slow deep breathing in normal subjects at high altitude. We collected data in healthy lowlanders staying either at 4559 m for 2-3 days (Study A; N = 39) or at 5400 m for 12-16 days (Study B; N = 28). Study variables, including Sp(O2) and systemic and pulmonary arterial pressure, were assessed before, during and after 15 minutes of breathing at 6 breaths/min. At the end of slow breathing, an increase in Sp(O2) (Study A: from 80.2±7.7% to 89.5±8.2%; Study B: from 81.0±4.2% to 88.6±4.5; both p<0.001) and significant reductions in systemic and pulmonary arterial pressure occurred. This was associated with increased tidal volume and no changes in minute ventilation or pulmonary CO diffusion. Slow deep breathing improves ventilation efficiency for oxygen as shown by blood oxygenation increase, and it reduces systemic and pulmonary blood pressure at high altitude but does not change pulmonary gas diffusion.

An examination of photoacclimatory responses of Zostera marina transplants along a depth gradient for transplant-site selection in a disturbed estuary

NASA Astrophysics Data System (ADS)

Li, Wen-Tao; Kim, Seung Hyeon; Kim, Jae Woo; Kim, Jong-Hyeob; Lee, Kun-Seop

2013-02-01

Growth and photosynthetic responses of Zostera marina transplants along a depth gradient were examined to determine appropriate transplanting areas for seagrass restoration. Seagrass Z. marina was once widely distributed in the Taehwa River estuary in southeastern Korea, but has disappeared since the 1960s due to port construction and large scale pollutant inputs from upstream industrial areas. Recently, water quality has been considerably improved as a result of effective sewage treatment, and the local government is attempting to restore Z. marina to the estuary. For seagrass restoration in this estuary, a pilot transplantation trial of Z. marina at three water depths (shallow: 0.5 m; intermediate: 1.5 m; deep: 2.5 m relative to MLLW) was conducted in November 2008. The transplant shoot density increased gradually at the intermediate and deep sites, whereas the transplants at the shallow site disappeared after 3 months. To find the optimal transplantation locations in this estuary, the growth and photosynthetic responses of the transplants along a depth gradient were examined for approximately 4 months following transplantation in March 2009. In the 2009 experimental transplantation trial, shoot density of transplants at the shallow site was significantly higher than those at the intermediate and deep sites during the first 3 months following transplantation, but rapidly decreased approximately 4 months after transplantation. The chlorophyll content, photosynthetic efficiency (α), and maximum quantum yield (Fv/Fm) of the transplants were significantly higher at the deep site than at the shallow site. Shoot size, biomass and leaf productivity were also significantly higher at the deep site than at the shallow site. Although underwater irradiance was significantly lower at the deep site than at the shallow site, transplants at the deep site were morphologically and physiologically acclimated to the low light. Transplants at the shallow site exhibited high mortality during the early period of transplantation perhaps due to high physical disturbances at the site, but transplants at the intermediate and deep sites showed higher growth through more efficient photosynthesis and morphological adaptation. Thus, the intermediate and deep sites (1.5-2.5 m relative to MLLW) appeared to be more appropriate seagrass transplantation sites in this estuary.

Study of the effects of impurities on the properties of silicon solar cell

NASA Technical Reports Server (NTRS)

Sah, C. T.

1981-01-01

The effect of defects across the back-surface-field junction on the performance of high efficiency and thin solar cells, using a developed-perimeter device model for the three-dimensional defects is investigated. Significant degradation of open-circuit voltage can occur even if there are only a few defects distributed in the bulk of the solar cell. Two features in the thickness dependences of the fill factor and efficiency in impurity-doped back-surface-field solar cells are discovered in the exact numerical solution which are associated with the high injection level effect in the base and not predicted by the low-level analytical theory. What are believed to be the most accurate recombination parameters at the Ti center to date are also given and a theory is developed which is capable of distinguishing an acceptor-like deep level from a donor-like deep level using the measured values of the thermal emission and capture cross sections.

Green extraction of grape skin phenolics by using deep eutectic solvents.

PubMed

Cvjetko Bubalo, Marina; Ćurko, Natka; Tomašević, Marina; Kovačević Ganić, Karin; Radojčić Redovniković, Ivana

2016-06-01

Conventional extraction techniques for plant phenolics are usually associated with high organic solvent consumption and long extraction times. In order to establish an environmentally friendly extraction method for grape skin phenolics, deep eutectic solvents (DES) as a green alternative to conventional solvents coupled with highly efficient microwave-assisted and ultrasound-assisted extraction methods (MAE and UAE, respectively) have been considered. Initially, screening of five different DES for proposed extraction was performed and choline chloride-based DES containing oxalic acid as a hydrogen bond donor with 25% of water was selected as the most promising one, resulting in more effective extraction of grape skin phenolic compounds compared to conventional solvents. Additionally, in our study, UAE proved to be the best extraction method with extraction efficiency superior to both MAE and conventional extraction method. The knowledge acquired in this study will contribute to further DES implementation in extraction of biologically active compounds from various plant sources. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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.

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

NASA Astrophysics Data System (ADS)

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 respectively. Therefore we can use these sources simultaneously and distinguish the records of each source in the data processing stage. We have developed new marine seismic survey systems with autonomous recording for the exploration of the ocean floor resources. The applications are vertical cable seismic (VCS) and deep-tow seismic (ACS). These enable us the recording close to the seafloor and give the high resolution results with a simple, cost-effective configuration.

Near-field thermal radiation of deep- subwavelength slits in the near infrared range.

PubMed

Guo, Yan; Li, Kuanbiao; Xu, Ying; Wei, Kaihua

2017-09-18

We numerically investigate the thermal radiation of one-dimensional deep subwavelength slits in the near infrared range. Using numerical calculations of single-slit and multi-slit structures, we find that high-level radiation efficiency can be achieved for a wide spectrum when ultra-thin intermediate layers are used, and it is less affected by structure parameters. The underlying mechanisms involve Surface Plasmon Polaritons resonance and Fabry-Perot interference at each slit and the interaction between adjacent slits. This structure helps understand and improve the design of thermal radiation control devices.

Evaluation of high-perimeter electrode designs for deep brain stimulation

NASA Astrophysics Data System (ADS)

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.

[Effects of deep plowing and mulch in fallow period on soil water and yield of wheat in dryland].

PubMed

Deng, Yan; Gao, Zhi-Qiang; Sun, Min; Zhao, Wei-Feng; Zhao, Hong-Mei; Li, Qing

2014-01-01

A field test was carried out in Qiujialing Village, Wenxi, Shanxi from 2009 to 2011 to study the soil water movement of 0-300 cm layer, yield formation and water use efficiency (WUE) of wheat with deep plowing and mulching the whole ground immediately (no mulch as control) 15 days and 45 days after harvest. The results indicated that deep plowing and mulch in fallow period could improve soil water storage of the 100-180 cm layer before sowing, the soil water storage efficiency in fallow period, and soil water storage from pre-wintering stage to booting stage. Compared with deep plowing 15 days after wheat harvest, deep plowing 45 days after wheat harvest did better in improving soil water storage and water use efficiency, as well as ear number and yield, which was more conducive in the year with more precipitation. Generally, deep plowing and mulching after raining during fallow period could benefit the soil water storage and conservation, thus would be helpful to improve wheat yield in dryland.

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 7 2014-10-01 2014-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea...

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 7 2012-10-01 2012-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea...

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 7 2013-10-01 2013-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea...

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea... 46 Shipping 7 2011-10-01 2011-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20...

46 CFR 167.40-20 - Deep-sea sounding apparatus.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SHIPS Certain Equipment Requirements § 167.40-20 Deep-sea sounding apparatus. Nautical school ships shall be equipped with an efficient or electronic deep-sea sounding apparatus. The electronic deep-sea... 46 Shipping 7 2010-10-01 2010-10-01 false Deep-sea sounding apparatus. 167.40-20 Section 167.40-20...

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

NASA Astrophysics Data System (ADS)

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.

Ultra High Work, High Efficiency Turbines For UAVs

DTIC Science & Technology

2006-06-01

same amount of work, thereby reducing the weight of the LPT. Howell et al. and Arts and Coton , 15-17 estimated that a 34% reduction in blade count...dimple a few mm in diameter and 0.1 mm to 0.3 mm deep. A typical surface finish on newly manufactured blading is typically 1-2 μm. In- use LP

Deep desulfurization by amphiphilic lanthanide-containing polyoxometalates in ionic-liquid emulsion systems under mild conditions.

PubMed

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.

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

PubMed Central

Chen, Yaw-Chung

2015-01-01

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. PMID:26437335

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

PubMed

Lee, Chun-Liang; Lin, Yi-Shan; Chen, Yaw-Chung

2015-01-01

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.

Numerical Analysis of Neutral Entrainment Effect on Field-Reversed Configuration Thruster Efficiency

DTIC Science & Technology

2014-12-01

and acceleration. Whereas such a high Isp may be highly desirable for deep space missions, the low - Earth - orbit and geosynchronous- Earth - orbit ...Due to the aforementioned factors, the optimal conditions are achieved for low -Z plasma at high (∼50 eV) temperature and in strong magnetic fields...cannot capture strongly nonequilibrium velocity distributions of charged and neutral species typical for high-energy plasma –neutral interaction . A

Background rejection in NEXT using deep neural networks

DOE PAGES

Renner, J.; Farbin, A.; Vidal, J. Muñoz; ...

2017-01-16

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 usemore » of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.« less

Designing a deep brain stimulator to suppress pathological neuronal synchrony.

PubMed

Montaseri, Ghazal; Yazdanpanah, Mohammad Javad; Bahrami, Fariba

2015-03-01

Some of neuropathologies are believed to be related to abnormal synchronization of neurons. In the line of therapy, designing effective deep brain stimulators to suppress the pathological synchrony among neuronal ensembles is a challenge of high clinical relevance. The stimulation should be able to disrupt the synchrony in the presence of latencies due to imperfect knowledge about parameters of a neuronal ensemble and stimulation impacts on the ensemble. We propose an adaptive desynchronizing deep brain stimulator capable of dealing with these uncertainties. We analyze the collective behavior of the stimulated neuronal ensemble and show that, using the designed stimulator, the resulting asynchronous state is stable. Simulation results reveal the efficiency of the proposed technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

SNP discovery through de novo deep sequencing using the next generation of DNA sequencers

USDA-ARS?s Scientific Manuscript database

The production of high volumes of DNA sequence data using new technologies has permitted more efficient identification of single nucleotide polymorphisms in vertebrate genomes. This chapter presented practical methodology for production and analysis of DNA sequence data for SNP discovery....

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

PubMed

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.

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

PubMed

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.

Li 2Se as a Neutron Scintillator

DOE PAGES

Du, Mao-Hua; Shi, Hongliang; Singh, David J.

2015-06-23

We show that Li 2Se:Te is a potential neutron scintillator material based on density functional calculations. Li 2Se exhibits a number of properties favorable for efficient neutron detection, such as a high Li concentration for neutron absorption, a small effective atomic mass and a low density for reduced sensitivity to background gamma rays, and a small band gap for a high light yield. Our calculations show that Te doping should lead to the formation of deep acceptor complex V Li-Te Se, which can facilitate efficient light emission, similar to the emission activation in Te doped ZnSe.

A polymer tandem solar cell with 10.6% power conversion efficiency.

PubMed

You, Jingbi; Dou, Letian; Yoshimura, Ken; Kato, Takehito; Ohya, Kenichiro; Moriarty, Tom; Emery, Keith; Chen, Chun-Chao; Gao, Jing; Li, Gang; Yang, Yang

2013-01-01

An effective way to improve polymer solar cell efficiency is to use a tandem structure, as a broader part of the spectrum of solar radiation is used and the thermalization loss of photon energy is minimized. In the past, the lack of high-performance low-bandgap polymers was the major limiting factor for achieving high-performance tandem solar cell. Here we report the development of a high-performance low bandgap polymer (bandgap <1.4 eV), poly[2,7-(5,5-bis-(3,7-dimethyloctyl)-5H-dithieno[3,2-b:2',3'-d]pyran)-alt-4,7-(5,6-difluoro-2,1,3-benzothia diazole)] with a bandgap of 1.38 eV, high mobility, deep highest occupied molecular orbital. As a result, a single-junction device shows high external quantum efficiency of >60% and spectral response that extends to 900 nm, with a power conversion efficiency of 7.9%. The polymer enables a solution processed tandem solar cell with certified 10.6% power conversion efficiency under standard reporting conditions (25 °C, 1,000 Wm(-2), IEC 60904-3 global), which is the first certified polymer solar cell efficiency over 10%.

A polymer tandem solar cell with 10.6% power conversion efficiency

PubMed Central

You, Jingbi; Dou, Letian; Yoshimura, Ken; Kato, Takehito; Ohya, Kenichiro; Moriarty, Tom; Emery, Keith; Chen, Chun-Chao; Gao, Jing; Li, Gang; Yang, Yang

2013-01-01

An effective way to improve polymer solar cell efficiency is to use a tandem structure, as a broader part of the spectrum of solar radiation is used and the thermalization loss of photon energy is minimized. In the past, the lack of high-performance low-bandgap polymers was the major limiting factor for achieving high-performance tandem solar cell. Here we report the development of a high-performance low bandgap polymer (bandgap <1.4 eV), poly[2,7-(5,5-bis-(3,7-dimethyloctyl)-5H-dithieno[3,2-b:2′,3′-d]pyran)-alt-4,7-(5,6-difluoro-2,1,3-benzothia diazole)] with a bandgap of 1.38 eV, high mobility, deep highest occupied molecular orbital. As a result, a single-junction device shows high external quantum efficiency of >60% and spectral response that extends to 900 nm, with a power conversion efficiency of 7.9%. The polymer enables a solution processed tandem solar cell with certified 10.6% power conversion efficiency under standard reporting conditions (25 °C, 1,000 Wm−2, IEC 60904-3 global), which is the first certified polymer solar cell efficiency over 10%. PMID:23385590

A pulse-compression-ring circuit for high-efficiency electric propulsion.

PubMed

Owens, Thomas L

2008-03-01

A highly efficient, highly reliable pulsed-power system has been developed for use in high power, repetitively pulsed inductive plasma thrusters. The pulsed inductive thruster ejects plasma propellant at a high velocity using a Lorentz force developed through inductive coupling to the plasma. Having greatly increased propellant-utilization efficiency compared to chemical rockets, this type of electric propulsion system may one day propel spacecraft on long-duration deep-space missions. High system reliability and electrical efficiency are extremely important for these extended missions. In the prototype pulsed-power system described here, exceptional reliability is achieved using a pulse-compression circuit driven by both active solid-state switching and passive magnetic switching. High efficiency is achieved using a novel ring architecture that recovers unused energy in a pulse-compression system with minimal circuit loss after each impulse. As an added benefit, voltage reversal is eliminated in the ring topology, resulting in long lifetimes for energy-storage capacitors. System tests were performed using an adjustable inductive load at a voltage level of 3.3 kV, a peak current of 20 kA, and a current switching rate of 15 kA/micros.

Bioprocess exploration for thermostable α-amylase production of a deep-sea thermophile Geobacillus sp. in high-temperature bioreactor.

PubMed

Jiang, Tao; Huang, Mengmeng; He, Hao; Lu, Jian; Zhou, Xiangshan; Cai, Menghao; Zhang, Yuanxing

2016-08-17

Geobacillus sp. 4j, a deep-sea high-salt thermophile, was found to produce thermostable α-amylase. In this work, culture medium and conditions were first optimized to enhance the production of thermostable α-amylase by statistical methodologies. The resulting extracellular production was increased by five times and reached 6.40 U/ml. Then, a high-temperature batch culture of the thermophile in a 15 l in-house-designed bioreactor was studied. The results showed that a relatively high dissolved oxygen (600 rpm and 15 l/min) and culture temperature of 60°C facilitated both cell growth and α-amylase production. Thus, an efficient fermentation process was established with initial medium of pH 6.0, culture temperature of 60°C, and dissolved oxygen above 20%. It gave an α-amylase production of 79 U/ml and productivity of 19804 U/l·hr, which were 10.8 and 208 times higher than those in shake flask, respectively. This work is useful for deep-sea high-salt thermophile culture, where efforts are lacking presently.

Seafloor heterogeneity influences the biodiversity–ecosystem functioning relationships in the deep sea

PubMed Central

Zeppilli, Daniela; Pusceddu, Antonio; Trincardi, Fabio; Danovaro, Roberto

2016-01-01

Theoretical ecology predicts that heterogeneous habitats allow more species to co-exist in a given area. In the deep sea, biodiversity is positively linked with ecosystem functioning, suggesting that deep-seabed heterogeneity could influence ecosystem functions and the relationships between biodiversity and ecosystem functioning (BEF). To shed light on the BEF relationships in a heterogeneous deep seabed, we investigated variations in meiofaunal biodiversity, biomass and ecosystem efficiency within and among different seabed morphologies (e.g., furrows, erosional troughs, sediment waves and other depositional structures, landslide scars and deposits) in a narrow geo-morphologically articulated sector of the Adriatic Sea. We show that distinct seafloor morphologies are characterized by highly diverse nematode assemblages, whereas areas sharing similar seabed morphologies host similar nematode assemblages. BEF relationships are consistently positive across the entire region, but different seabed morphologies are characterised by different slope coefficients of the relationship. Our results suggest that seafloor heterogeneity, allowing diversified assemblages across different habitats, increases diversity and influence ecosystem processes at the regional scale, and BEF relationships at smaller spatial scales. We conclude that high-resolution seabed mapping and a detailed analysis of the species distribution at the habitat scale are crucial for improving management of goods and services delivered by deep-sea ecosystems. PMID:27211908

Local surface plasmon enhanced polarization and internal quantum efficiency of deep ultraviolet emissions from AlGaN-based quantum wells.

PubMed

Zhang, Cai; Tang, Ning; Shang, Liangliang; Fu, Lei; Wang, Weiying; Xu, Fujun; Wang, Xinqiang; Ge, Weikun; Shen, Bo

2017-05-24

We report the enhancement of the polarization and internal quantum efficiency (IQE) of deep-UV LEDs by evaporating Al nanoparticles on the device surface to induce localized surface plasmons (LSPs). The deep-UV LEDs polarization is improved due to part of TM emission turns into TE emission through LSPs coupling. The significantly enhanced IQE is attributed to LSPs coupling, which suppress the participation of delocalized and dissociated excitons to non-radiative recombination process.

Defective TiO 2 with high photoconductive gain for efficient and stable planar heterojunction perovskite solar cells

DOE PAGES

Li, Yanbo; Cooper, Jason K.; Liu, Wenjun; ...

2016-08-18

Formation of planar heterojunction perovskite solar cells exhibiting both high efficiency and stability under continuous operation remains a challenge. Here, we show this can be achieved by using a defective TiO 2 thin film as the electron transport layer. TiO 2 layers with native defects are deposited by electron beam evaporation in an oxygen-deficient environment. Deep-level hole traps are introduced in the TiO 2 layers and contribute to a high photoconductive gain and reduced photocatalytic activity. The high photoconductivity of the TiO 2 electron transport layer leads to improved efficiency for the fabricated planar devices. A maximum power conversion efficiencymore » of 19.0% and an average PCE of 17.5% are achieved. In addition, the reduced photocatalytic activity of the TiO 2 layer leads to enhanced long-Term stability for the planar devices. Under continuous operation near the maximum power point, an efficiency of over 15.4% is demonstrated for 100 h.« less

A Power-Efficient Wireless System With Adaptive Supply Control for Deep Brain Stimulation.

PubMed

Lee, Hyung-Min; Park, Hangue; Ghovanloo, Maysam

2013-09-01

A power-efficient wireless stimulating system for a head-mounted deep brain stimulator (DBS) is presented. A new adaptive rectifier generates a variable DC supply voltage from a constant AC power carrier utilizing phase control feedback, while achieving high AC-DC power conversion efficiency (PCE) through active synchronous switching. A current-controlled stimulator adopts closed-loop supply control to automatically adjust the stimulation compliance voltage by detecting stimulation site potentials through a voltage readout channel, and improve the stimulation efficiency. The stimulator also utilizes closed-loop active charge balancing to maintain the residual charge at each site within a safe limit, while receiving the stimulation parameters wirelessly from the amplitude-shift-keyed power carrier. A 4-ch wireless stimulating system prototype was fabricated in a 0.5-μm 3M2P standard CMOS process, occupying 2.25 mm². With 5 V peak AC input at 2 MHz, the adaptive rectifier provides an adjustable DC output between 2.5 V and 4.6 V at 2.8 mA loading, resulting in measured PCE of 72 ~ 87%. The adaptive supply control increases the stimulation efficiency up to 30% higher than a fixed supply voltage to 58 ~ 68%. The prototype wireless stimulating system was verified in vitro .

A Power-Efficient Wireless System With Adaptive Supply Control for Deep Brain Stimulation

PubMed Central

Lee, Hyung-Min; Park, Hangue; Ghovanloo, Maysam

2014-01-01

A power-efficient wireless stimulating system for a head-mounted deep brain stimulator (DBS) is presented. A new adaptive rectifier generates a variable DC supply voltage from a constant AC power carrier utilizing phase control feedback, while achieving high AC-DC power conversion efficiency (PCE) through active synchronous switching. A current-controlled stimulator adopts closed-loop supply control to automatically adjust the stimulation compliance voltage by detecting stimulation site potentials through a voltage readout channel, and improve the stimulation efficiency. The stimulator also utilizes closed-loop active charge balancing to maintain the residual charge at each site within a safe limit, while receiving the stimulation parameters wirelessly from the amplitude-shift-keyed power carrier. A 4-ch wireless stimulating system prototype was fabricated in a 0.5-μm 3M2P standard CMOS process, occupying 2.25 mm². With 5 V peak AC input at 2 MHz, the adaptive rectifier provides an adjustable DC output between 2.5 V and 4.6 V at 2.8 mA loading, resulting in measured PCE of 72 ~ 87%. The adaptive supply control increases the stimulation efficiency up to 30% higher than a fixed supply voltage to 58 ~ 68%. The prototype wireless stimulating system was verified in vitro. PMID:24678126

Dopant incorporation in Al0.9Ga0.1As0.06Sb0.94 grown by molecular beam epitaxy

NASA Astrophysics Data System (ADS)

Patra, Saroj Kumar; Tran, Thanh-Nam; Vines, Lasse; Kolevatov, Ilia; Monakhov, Edouard; Fimland, Bjørn-Ove

2017-04-01

Incorporation of beryllium (Be) and tellurium (Te) dopants in epitaxially grown Al0.9Ga0.1As0.06Sb0.94 layers was investigated. Carrier concentrations and mobilities of the doped layers were obtained from room temperature Hall effect measurements, and dopant densities from secondary ion mass spectrometry depth profiling. An undoped Al0.3Ga0.7As cap layer and side wall passivation were used to reduce oxidation and improve accuracy in Hall effect measurements. The measurements on Be-doped samples revealed high doping efficiency and the carrier concentration varied linearly with dopant density up to the highest Be dopant density of 2.9 × 1019 cm-3, whereas for Te doped samples the doping efficiency was in general low and the carrier concentration saturated for Te-dopant densities above 8.0 × 1018 cm-3. The low doping efficiency in Te-doped Al0.9Ga0.1As0.06Sb0.94 layer was studied by deep-level transient spectroscopy, revealing existence of deep trap levels and related DX-centers which explains the low doping efficiency.

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

NASA Astrophysics Data System (ADS)

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 efficient extraction of anthocyanins from grape skin using deep eutectic solvents as green and tunable media.

PubMed

Jeong, Kyung Min; Zhao, Jing; Jin, Yan; Heo, Seong Rok; Han, Se Young; Yoo, Da Eun; Lee, Jeongmi

2015-12-01

Deep eutectic solvents (DESs) were investigated as tunable, environmentally benign, yet superior extraction media to enhance the extraction of anthocyanins from grape skin, which is usually discarded as waste. Ten DESs containing choline chloride as hydrogen bond acceptor combined with different hydrogen bond donors were screened for high extraction efficiencies based on the anthocyanin extraction yields. As a result, citric acid, D-(+)-maltose, and fructose were selected as the effective DES components, and the newly designed DES, CM-6 that is composed of citric acid and D-(+)-maltose at 4:1 molar ratio, exhibited significantly higher levels of anthocyanin extraction yields than conventional extraction solvents such as 80% aqueous methanol. The final extraction method was established based on the ultrasound-assisted extraction under conditions optimized using response surface methodology. Its extraction yields were double or even higher than those of conventional methods that are time-consuming and use volatile organic solvents. Our method is truly a green method for anthocyanin extraction with great extraction efficiency using a minimal amount of time and solvent. Moreover, this study suggested that grape skin, the by-products of grape juice processing, could serve as a valuable source for safe, natural colorants or antioxidants by use of the eco-friendly extraction solvent, CM-6.

Embedded Streaming Deep Neural Networks Accelerator With Applications.

PubMed

Dundar, Aysegul; Jin, Jonghoon; Martini, Berin; Culurciello, Eugenio

2017-07-01

Deep convolutional neural networks (DCNNs) have become a very powerful tool in visual perception. DCNNs have applications in autonomous robots, security systems, mobile phones, and automobiles, where high throughput of the feedforward evaluation phase and power efficiency are important. Because of this increased usage, many field-programmable gate array (FPGA)-based accelerators have been proposed. In this paper, we present an optimized streaming method for DCNNs' hardware accelerator on an embedded platform. The streaming method acts as a compiler, transforming a high-level representation of DCNNs into operation codes to execute applications in a hardware accelerator. The proposed method utilizes maximum computational resources available based on a novel-scheduled routing topology that combines data reuse and data concatenation. It is tested with a hardware accelerator implemented on the Xilinx Kintex-7 XC7K325T FPGA. The system fully explores weight-level and node-level parallelizations of DCNNs and achieves a peak performance of 247 G-ops while consuming less than 4 W of power. We test our system with applications on object classification and object detection in real-world scenarios. Our results indicate high-performance efficiency, outperforming all other presented platforms while running these applications.

Aluminum nitride nanowire light emitting diodes: Breaking the fundamental bottleneck of deep ultraviolet light sources

PubMed Central

Zhao, S.; Connie, A. T.; Dastjerdi, M. H. T.; Kong, X. H.; Wang, Q.; Djavid, M.; Sadaf, S.; Liu, X. D.; Shih, I.; Guo, H.; Mi, Z.

2015-01-01

Despite broad interest in aluminum gallium nitride (AlGaN) optoelectronic devices for deep ultraviolet (DUV) applications, the performance of conventional Al(Ga)N planar devices drastically decays when approaching the AlN end, including low internal quantum efficiencies (IQEs) and high device operation voltages. Here we show that these challenges can be addressed by utilizing nitrogen (N) polar Al(Ga)N nanowires grown directly on Si substrate. By carefully tuning the synthesis conditions, a record IQE of 80% can be realized with N-polar AlN nanowires, which is nearly ten times higher compared to high quality planar AlN. The first 210 nm emitting AlN nanowire light emitting diodes (LEDs) were achieved, with a turn on voltage of about 6 V, which is significantly lower than the commonly observed 20 – 40 V. This can be ascribed to both efficient Mg doping by controlling the nanowire growth rate and N-polarity induced internal electrical field that favors hole injection. In the end, high performance N-polar AlGaN nanowire LEDs with emission wavelengths covering the UV-B/C bands were also demonstrated. PMID:25684335

Identification of inelastic parameters based on deep drawing forming operations using a global-local hybrid Particle Swarm approach

NASA Astrophysics Data System (ADS)

Vaz, Miguel; Luersen, Marco A.; Muñoz-Rojas, Pablo A.; Trentin, Robson G.

2016-04-01

Application of optimization techniques to the identification of inelastic material parameters has substantially increased in recent years. The complex stress-strain paths and high nonlinearity, typical of this class of problems, require the development of robust and efficient techniques for inverse problems able to account for an irregular topography of the fitness surface. Within this framework, this work investigates the application of the gradient-based Sequential Quadratic Programming method, of the Nelder-Mead downhill simplex algorithm, of Particle Swarm Optimization (PSO), and of a global-local PSO-Nelder-Mead hybrid scheme to the identification of inelastic parameters based on a deep drawing operation. The hybrid technique has shown to be the best strategy by combining the good PSO performance to approach the global minimum basin of attraction with the efficiency demonstrated by the Nelder-Mead algorithm to obtain the minimum itself.

Comparative evaluation of surface and downhole steam-generation techniques

NASA Astrophysics Data System (ADS)

Hart, C.

The application of heat to reservoirs containing high API gravity oils can substantially improve recovery. Although steam injection is currently the principal thermal recovery method, heat transmission losses associated with delivery of the steam from the surface generators to the oil bearing formation has limited conventional steam injection to shallow reservoirs. The objective of the Department of Energy's Project DEEP STEAM is to develop the technology required to economically produce heavy oil from deep reservoirs. The tasks included in this effort are the development and evaluation of thermally efficient delivery systems and downhole steam generation systems. The technical and economic performance of conventional surface steam drives, which are strongly influenced by heat losses are compared. The selection of a preferred technology based upon either total efficiency or cost is found to be strongly influenced by reservoir depth, steam mass flow rate, and sandface steam quality.

Vapor transport deposition of antimony selenide thin film solar cells with 7.6% efficiency.

PubMed

Wen, Xixing; Chen, Chao; Lu, Shuaicheng; Li, Kanghua; Kondrotas, Rokas; Zhao, Yang; Chen, Wenhao; Gao, Liang; Wang, Chong; Zhang, Jun; Niu, Guangda; Tang, Jiang

2018-06-05

Antimony selenide is an emerging promising thin film photovoltaic material thanks to its binary composition, suitable bandgap, high absorption coefficient, inert grain boundaries and earth-abundant constituents. However, current devices produced from rapid thermal evaporation strategy suffer from low-quality film and unsatisfactory performance. Herein, we develop a vapor transport deposition technique to fabricate antimony selenide films, a technique that enables continuous and low-cost manufacturing of cadmium telluride solar cells. We improve the crystallinity of antimony selenide films and then successfully produce superstrate cadmium sulfide/antimony selenide solar cells with a certified power conversion efficiency of 7.6%, a net 2% improvement over previous 5.6% record of the same device configuration. We analyze the deep defects in antimony selenide solar cells, and find that the density of the dominant deep defects is reduced by one order of magnitude using vapor transport deposition process.

Degradation of CMOS image sensors in deep-submicron technology due to γ-irradiation

NASA Astrophysics Data System (ADS)

Rao, Padmakumar R.; Wang, Xinyang; Theuwissen, Albert J. P.

2008-09-01

In this work, radiation induced damage mechanisms in deep submicron technology is resolved using finger gated-diodes (FGDs) as a radiation sensitive tool. It is found that these structures are simple yet efficient structures to resolve radiation induced damage in advanced CMOS processes. The degradation of the CMOS image sensors in deep-submicron technology due to γ-ray irradiation is studied by developing a model for the spectral response of the sensor and also by the dark-signal degradation as a function of STI (shallow-trench isolation) parameters. It is found that threshold shifts in the gate-oxide/silicon interface as well as minority carrier life-time variations in the silicon bulk are minimal. The top-layer material properties and the photodiode Si-SiO2 interface quality are degraded due to γ-ray irradiation. Results further suggest that p-well passivated structures are inevitable for radiation-hard designs. It was found that high electrical fields in submicron technologies pose a threat to high quality imaging in harsh environments.

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

PubMed Central

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

2016-01-01

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. PMID:27070606

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

PubMed

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.

PubMed

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.

High performance small molecule photodetector with broad spectral response range from 200 to 900 nm

NASA Astrophysics Data System (ADS)

Wu, Shuang-hong; Li, Wen-lian; Chu, Bei; Su, Zi-sheng; Zhang, Feng; Lee, C. S.

2011-07-01

We demonstrate a photodetector (PD) with broad spectral response by taking the advantages of more flexible device design in using small molecule materials. The optimized device shows an external quantum efficiency of over 20% from 200 to 900 nm. The high performance is achieved by jointing two donor (D)/acceptor (A) hetero-junctions [m-MTDATA(D)/TiOPc(A) and TiOPc(D)/F16CuPc: PTCDI-C8(A)] such that photoresponses over the deep-ultraviolet (UV) and visible-near infrared regions can be independently optimized. By choosing D- and A-materials with matched energy level alignment, high carrier mobility, and balanced carrier transporting properties, the present PD shows a fast response of 56 ns. The high speed and deep-UV sensitivity might lead to potential military applications such as missile tracking in addition to optical communications, chemical/biological sensing etc.

Antenna servo control system characterization: Rate loop analysis for 34-m antenna at DSS 15

NASA Technical Reports Server (NTRS)

Nickerson, J. A.; Cox, D. G.; Smith, H. K.; Engel, J. H.; Ahlstrom, H. G.

1986-01-01

The elevation and azimuth servo rate loops at the 34-m High Efficiency Deep Space Station 15 (DSS 15) are described. Time and frequency response performance criteria were measured. The results are compared to theoretically deduced performance criteria. Unexpected anomalies in the frequency response are observed and identified.

Minimize emissions and improve efficacy with low permeability tarp and deep injection in soil fumigation

USDA-ARS?s Scientific Manuscript database

Soil fumigation targets high pest control efficiency and low environmental impact. Earlier field data show that most fumigated treatments provided 100% kill for plant parasitic nematodes in the soil above 3 ft depth, but not below due to insufficient fumigant delivery. A fumigation trial was conduct...

Small molecule BODIPY dyes as non-fullerene acceptors in bulk heterojunction organic photovoltaics.

PubMed

Poe, Ambata M; Della Pelle, Andrea M; Subrahmanyam, Ayyagari V; White, William; Wantz, Guillaume; Thayumanavan, S

2014-03-18

A series of acceptor-donor-acceptor molecules containing terminal BODIPY moieties conjugated through the meso position were synthesized. Deep LUMO energy levels and good visible absorption led to their use as acceptors in bulk heterojunction solar cells. Inverted devices were fabricated, reaching efficiencies as high as 1.51%.

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

PubMed

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.

PODIO: An Event-Data-Model Toolkit for High Energy Physics Experiments

NASA Astrophysics Data System (ADS)

Gaede, F.; Hegner, B.; Mato, P.

2017-10-01

PODIO is a C++ library that supports the automatic creation of event data models (EDMs) and efficient I/O code for HEP experiments. It is developed as a new EDM Toolkit for future particle physics experiments in the context of the AIDA2020 EU programme. Experience from LHC and the linear collider community shows that existing solutions partly suffer from overly complex data models with deep object-hierarchies or unfavorable I/O performance. The PODIO project was created in order to address these problems. PODIO is based on the idea of employing plain-old-data (POD) data structures wherever possible, while avoiding deep object-hierarchies and virtual inheritance. At the same time it provides the necessary high-level interface towards the developer physicist, such as the support for inter-object relations and automatic memory-management, as well as a Python interface. To simplify the creation of efficient data models PODIO employs code generation from a simple yaml-based markup language. In addition, it was developed with concurrency in mind in order to support the use of modern CPU features, for example giving basic support for vectorization techniques.

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

NASA Astrophysics Data System (ADS)

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.

High Tolerance to Iron Contamination in Lead Halide Perovskite Solar Cells

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

Poindexter, Jeremy R.; Hoye, Robert L. Z.; Nienhaus, Lea

The relationship between charge-carrier lifetime and the tolerance of lead halide perovskite (LHP) solar cells to intrinsic point defects has drawn much attention by helping to explain rapid improvements in device efficiencies. However, little is known about how charge-carrier lifetime and solar cell performance in LHPs are affected by extrinsic defects (i.e., impurities), including those that are common in manufacturing environments and known to introduce deep levels in other semiconductors. Here, we evaluate the tolerance of LHP solar cells to iron introduced via intentional contamination of the feedstock and examine the root causes of the resulting efficiency losses. We findmore » that comparable efficiency losses occur in LHPs at feedstock iron concentrations approximately 100 times higher than those in p-type silicon devices. Photoluminescence measurements correlate iron concentration with nonradiative recombination, which we attribute to the presence of deep-level iron interstitials, as calculated from first-principles, as well as iron-rich particles detected by synchrotron-based X-ray fluorescence microscopy. At moderate contamination levels, we witness prominent recovery of device efficiencies to near-baseline values after biasing at 1.4 V for 60 s in the dark. We theorize that this temporary effect arises from improved charge-carrier collection enhanced by electric fields strengthened from ion migration toward interfaces. Lastly, our results demonstrate that extrinsic defect tolerance contributes to high efficiencies in LHP solar cells, which inspires further investigation into potential large-scale manufacturing cost savings as well as the degree of overlap between intrinsic and extrinsic defect tolerance in LHPs and 'perovskite-inspired' lead-free stable alternatives.« less

High Tolerance to Iron Contamination in Lead Halide Perovskite Solar Cells

DOE PAGES

Poindexter, Jeremy R.; Hoye, Robert L. Z.; Nienhaus, Lea; ...

2017-06-28

The relationship between charge-carrier lifetime and the tolerance of lead halide perovskite (LHP) solar cells to intrinsic point defects has drawn much attention by helping to explain rapid improvements in device efficiencies. However, little is known about how charge-carrier lifetime and solar cell performance in LHPs are affected by extrinsic defects (i.e., impurities), including those that are common in manufacturing environments and known to introduce deep levels in other semiconductors. Here, we evaluate the tolerance of LHP solar cells to iron introduced via intentional contamination of the feedstock and examine the root causes of the resulting efficiency losses. We findmore » that comparable efficiency losses occur in LHPs at feedstock iron concentrations approximately 100 times higher than those in p-type silicon devices. Photoluminescence measurements correlate iron concentration with nonradiative recombination, which we attribute to the presence of deep-level iron interstitials, as calculated from first-principles, as well as iron-rich particles detected by synchrotron-based X-ray fluorescence microscopy. At moderate contamination levels, we witness prominent recovery of device efficiencies to near-baseline values after biasing at 1.4 V for 60 s in the dark. We theorize that this temporary effect arises from improved charge-carrier collection enhanced by electric fields strengthened from ion migration toward interfaces. Lastly, our results demonstrate that extrinsic defect tolerance contributes to high efficiencies in LHP solar cells, which inspires further investigation into potential large-scale manufacturing cost savings as well as the degree of overlap between intrinsic and extrinsic defect tolerance in LHPs and 'perovskite-inspired' lead-free stable alternatives.« less

RF rectifiers for EM power harvesting in a Deep Brain Stimulating device.

PubMed

Hosain, Md Kamal; Kouzani, Abbas Z; Tye, Susannah; Kaynak, Akif; Berk, Michael

2015-03-01

A passive deep brain stimulation (DBS) device can be equipped with a rectenna, consisting of an antenna and a rectifier, to harvest energy from electromagnetic fields for its operation. This paper presents optimization of radio frequency rectifier circuits for wireless energy harvesting in a passive head-mountable DBS device. The aim is to achieve a compact size, high conversion efficiency, and high output voltage rectifier. Four different rectifiers based on the Delon doubler, Greinacher voltage tripler, Delon voltage quadrupler, and 2-stage charge pumped architectures are designed, simulated, fabricated, and evaluated. The design and simulation are conducted using Agilent Genesys at operating frequency of 915 MHz. A dielectric substrate of FR-4 with thickness of 1.6 mm, and surface mount devices (SMD) components are used to fabricate the designed rectifiers. The performance of the fabricated rectifiers is evaluated using a 915 MHz radio frequency (RF) energy source. The maximum measured conversion efficiency of the Delon doubler, Greinacher tripler, Delon quadrupler, and 2-stage charge pumped rectifiers are 78, 75, 73, and 76 % at -5 dBm input power and for load resistances of 5-15 kΩ. The conversion efficiency of the rectifiers decreases significantly with the increase in the input power level. The Delon doubler rectifier provides the highest efficiency at both -5 and 5 dBm input power levels, whereas the Delon quadrupler rectifier gives the lowest efficiency for the same inputs. By considering both efficiency and DC output voltage, the charge pump rectifier outperforms the other three rectifiers. Accordingly, the optimised 2-stage charge pumped rectifier is used together with an antenna to harvest energy in our DBS device.

Improving the performance of AlGaN-based deep-ultraviolet light-emitting diodes using electron blocking layer with a heart-shaped graded Al composition

NASA Astrophysics Data System (ADS)

Kwon, M. R.; Park, T. H.; Lee, T. H.; Lee, B. R.; Kim, T. G.

2018-04-01

We propose a design for highly efficient AlGaN-based deep-ultraviolet light-emitting diodes (DUV LEDs) using a heart-shaped graded Al composition electron-blocking layer (EBL). This novel structure reduced downward band bending at the interface between the last quantum barrier and the EBL and flattened the electrostatic field in the interlayer between the barriers of the multi-quantum barrier EBL. Consequently, electron leakage was significantly suppressed and hole injection efficiency was found to have improved. The parameter values of simulation were extracted from the experimental data of the reference DUV LEDs. Using the SimuLED, we compared the electrical and optical properties of three structures with different Al compositions in the active region and the EBL. The internal quantum efficiency of the proposed structure was shown to exceed those of the reference DUV LEDs by a factor of 1.9. Additionally, the output power at 20 mA was found to increase by a factor of 2.1.

Microbial communities involved in arsenic mobilization and release from the deep sediments into groundwater in Jianghan plain, Central China.

PubMed

Chen, Xiaoming; Zeng, Xian-Chun; Wang, Jianing; Deng, Yamin; Ma, Teng; Guoji E; Mu, Yao; Yang, Ye; Li, Hao; Wang, Yanxin

2017-02-01

It was shown that groundwater in Jianghan Plain was severely contaminated by arsenic; however, little is known about the mechanism by which the mineral arsenic was mobilized and released into groundwater from the high-arsenic sediments in this area. Here, we collected sediment samples from the depths of 5-230m in Jianghan Plain. Although all of the samples contain high contents of total arsenic, the soluble arsenic was only detectable in few of the shallow sediments, but was readily detectable in all of the deep sediments at the depths of 190-230m. Analysis of the genes of arsenate-respiring reductases indicated that they were not present in all of the shallow sediments from the depths of 5-185m, but were detectable in all of the deep sediments from the depths of 190-230m; all of the identified reductase genes are new or new-type, and they display unique diversity. Microcosm assay indicated that the microbial communities from the deep sediments were able to reduce As(V) into As(III) using lactate, formate, pyruvate or acetate as an electron donor under anaerobic condition. Arsenic release assay demonstrated that these microbial communalities efficiently catalyzed the mobilization and release of the mineral arsenic into aqueous phase. We also isolated a novel cultivable dissimilatory As(V)-respiring bacterium Aeromonas sp. JH155 from the sediments. It is able to completely reduce 2.0mM As(V) into As(III) in 72h, and efficiently promote the reduction and release of the mineral arsenic into aqueous phase. Analysis of the 16S rRNA genes indicated that the deep sediments contain diversities of microbial communities, which were shaped by the environmental factors, such as As, SO 4 2- , NO 3 - , Fe and pH value. These data suggest that the microorganisms in the deep sediments in Jianghan Plain played key roles in the mobilization and release of insoluble arsenic into the groundwater. Copyright © 2016 Elsevier B.V. All rights reserved.

The export and fate of organic matter in the ocean: New constraints from combining satellite and oceanographic tracer observations

NASA Astrophysics Data System (ADS)

DeVries, Tim; Weber, Thomas

2017-03-01

The ocean's biological pump transfers carbon from the surface euphotic zone into the deep ocean, reducing the atmospheric CO2 concentration. Despite its climatic importance, there are large uncertainties in basic metrics of the biological pump. Previous estimates of the strength of the biological pump, as measured by the amount of organic carbon exported from the euphotic zone, range from about 4 to 12 Pg C yr-1. The fate of exported carbon, in terms of how efficiently it is transferred into the deep ocean, is even more uncertain. Here we present a new model of the biological pump that assimilates satellite and oceanographic tracer observations to constrain rates and patterns of organic matter production, export, and remineralization in the ocean. The data-assimilated model predicts a global particulate organic carbon (POC) flux out of the euphotic zone of ˜9 Pg C yr-1. The particle export ratio (the ratio of POC export to net primary production) is highest at high latitudes and lowest at low latitudes, but low-latitude export is greater than predicted by previous models, in better agreement with observed patterns of long-term carbon export. Particle transfer efficiency (Teff) through the mesopelagic zone is controlled by temperature and oxygen, with highest Teff for high-latitude regions and oxygen minimum zones. In contrast, Teff in the deep ocean (below 1000 m) is controlled by particle sinking speed, with highest deep ocean Teff below the subtropical gyres. These results emphasize the utility of both remote sensing and oceanographic tracer observations for constraining the operation of the biological pump.

Deep space telecommunications, navigation, and information management. Support of the space exploration initiative

NASA Astrophysics Data System (ADS)

Hall, Justin R.; Hastrup, Rolf C.

The United States Space Exploration Initiative (SEI) calls for the charting of a new and evolving manned course to the Moon, Mars, and beyond. This paper discusses key challenges in providing effective deep space telecommunications, navigation, and information management (TNIM) architectures and designs for Mars exploration support. The fundamental objectives are to provide the mission with means to monitor and control mission elements, acquire engineering, science, and navigation data, compute state vectors and navigate, and move these data efficiently and automatically between mission nodes for timely analysis and decision-making. Although these objectives do not depart, fundamentally, from those evolved over the past 30 years in supporting deep space robotic exploration, there are several new issues. This paper focuses on summarizing new requirements, identifying related issues and challenges, responding with concepts and strategies which are enabling, and, finally, describing candidate architectures, and driving technologies. The design challenges include the attainment of: 1) manageable interfaces in a large distributed system, 2) highly unattended operations for in-situ Mars telecommunications and navigation functions, 3) robust connectivity for manned and robotic links, 4) information management for efficient and reliable interchange of data between mission nodes, and 5) an adequate Mars-Earth data rate.

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

PubMed

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.

Hydrothermal systems are a sink for dissolved black carbon in the deep ocean

NASA Astrophysics Data System (ADS)

Niggemann, J.; Hawkes, J. A.; Rossel, P. E.; Stubbins, A.; Dittmar, T.

2016-02-01

Exposure to heat during fires on land or geothermal processes in Earth's crust induces modifications in the molecular structure of organic matter. The products of this thermogenesis are collectively termed black carbon. Dissolved black carbon (DBC) is a significant component of the oceanic dissolved organic carbon (DOC) pool. In the deep ocean, DBC accounts for 2% of DOC and has an apparent radiocarbon age of 18,000 years. Thus, DBC is much older than the bulk DOC pool, suggesting that DBC is highly refractory. Recently, it has been shown that recalcitrant deep-ocean DOC is efficiently removed during hydrothermal circulation. Here, we hypothesize that hydrothermal circulation is also a net sink for deep ocean DBC. We analyzed DBC in samples collected at different vent sites in the Atlantic, Pacific and Southern oceans. DBC was quantified in solid-phase extracts as benzenepolycarboxylic acids (BPCAs) following nitric acid digestion. Concentrations of DBC were much lower in hydrothermal fluids than in surrounding deep ocean seawater, confirming that hydrothermal circulation acts as a net sink for oceanic DBC. The relative contribution of DBC to bulk DOC did not change during hydrothermal circulation, indicating that DBC is removed at similar rates as bulk DOC. The ratio of the oxidation products benzenehexacarboxylic acid (B6CA) to benzenepentacarboxylic acid (B5CA) was significantly higher in hydrothermally altered samples compared to ratios typically found in the deep ocean, reflecting a higher degree of condensation of DBC molecules after hydrothermal circulation. Our study identified hydrothermal circulation as a quantitatively important sink for refractory DBC in the deep ocean. In contrast to photodegradation of DBC at the sea surface, which is more efficient for more condensed DBC, i.e. decreasing the B6CA/B5CA ratio, hydrothermal processing increases the B6CA/B5CA ratio, introducing a characteristic hydrothermal DBC signature.

Deep-water oilfield development cost analysis and forecasting —— Take gulf of mexico for example

NASA Astrophysics Data System (ADS)

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.

Building America Case Study: Pilot Demonstration of Phased Energy Efficiency Retrofits: Deep Retrofits, Central and South Florida

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

D. Parker, K. Sutherland, D. Chasar, J. Montemurno, B. Amos, J. Kono

2017-02-01

The Florida Solar Energy Center (FSEC), in collaboration with Florida Power & Light (FPL), is pursuing a phased residential energy-efficiency retrofit program in Florida. Researchers are looking to establish the impacts of technologies of two retrofit packages -- shallow and deep -- on annual energy and peak energy reductions.

Building America Case Study: Pilot Demonstration of Phased Energy Efficiency Retrofits: Deep Retrofits, Central and South Florida

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

2017-02-22

The Florida Solar Energy Center (FSEC), in collaboration with Florida Power & Light (FPL), is pursuing a phased residential energy-efficiency retrofit program in Florida. Researchers are looking to establish the impacts of technologies of two retrofit packages -- shallow and deep -- on annual energy and peak energy reductions.

A fast complex domain-matching pursuit algorithm and its application to deep-water gas reservoir detection

NASA Astrophysics Data System (ADS)

Zeng, Jing; Huang, Handong; Li, Huijie; Miao, Yuxin; Wen, Junxiang; Zhou, Fei

2017-12-01

The main emphasis of exploration and development is shifting from simple structural reservoirs to complex reservoirs, which all have the characteristics of complex structure, thin reservoir thickness and large buried depth. Faced with these complex geological features, hydrocarbon detection technology is a direct indication of changes in hydrocarbon reservoirs and a good approach for delimiting the distribution of underground reservoirs. It is common to utilize the time-frequency (TF) features of seismic data in detecting hydrocarbon reservoirs. Therefore, we research the complex domain-matching pursuit (CDMP) method and propose some improvements. First is the introduction of a scale parameter, which corrects the defect that atomic waveforms only change with the frequency parameter. Its introduction not only decomposes seismic signal with high accuracy and high efficiency but also reduces iterations. We also integrate jumping search with ergodic search to improve computational efficiency while maintaining the reasonable accuracy. Then we combine the improved CDMP with the Wigner-Ville distribution to obtain a high-resolution TF spectrum. A one-dimensional modeling experiment has proved the validity of our method. Basing on the low-frequency domain reflection coefficient in fluid-saturated porous media, we finally get an approximation formula for the mobility attributes of reservoir fluid. This approximation formula is used as a hydrocarbon identification factor to predict deep-water gas-bearing sand of the M oil field in the South China Sea. The results are consistent with the actual well test results and our method can help inform the future exploration of deep-water gas reservoirs.

Interpreting the strongest deep earthquake ever observed

NASA Astrophysics Data System (ADS)

Schultz, Colin

2013-12-01

Massive earthquakes that strike deep within the Earth may be more efficient at dissipating pent-up energy than similar quakes near the surface, according to new research by Wei et al. The authors analyzed the rupture of the most powerful deep earthquake ever recorded.

A high-rate and long cycle life aqueous electrolyte battery for grid-scale energy storage.

PubMed

Pasta, Mauro; Wessells, Colin D; Huggins, Robert A; Cui, Yi

2012-01-01

New types of energy storage are needed in conjunction with the deployment of solar, wind and other volatile renewable energy sources and their integration with the electric grid. No existing energy storage technology can economically provide the power, cycle life and energy efficiency needed to respond to the costly short-term transients that arise from renewables and other aspects of grid operation. Here we demonstrate a new type of safe, fast, inexpensive, long-life aqueous electrolyte battery, which relies on the insertion of potassium ions into a copper hexacyanoferrate cathode and a novel activated carbon/polypyrrole hybrid anode. The cathode reacts rapidly with very little hysteresis. The hybrid anode uses an electrochemically active additive to tune its potential. This high-rate, high-efficiency cell has a 95% round-trip energy efficiency when cycled at a 5C rate, and a 79% energy efficiency at 50C. It also has zero-capacity loss after 1,000 deep-discharge cycles.

Deep-UV Based Acousto-Optic Tunable Filter for Spectral Sensing Applications

NASA Technical Reports Server (NTRS)

Prasad, Narasimha S.

2006-01-01

In this paper, recent progress made in the development of quartz and KDP crystal based acousto-optic tunable filters (AOTF) are presented. These AOTFs are developed for operation over deep-UV to near-UV wavelengths of 190 nm to 400 nm. Preliminary output performance measurements of quartz AOTF and design specifications of KDP AOTF are presented. At 355 nm, the quartz AOTF device offered approx.15% diffraction efficiency with a passband full-width-half-maximum (FWHM) of less than 0.0625 nm. Further characterization of quartz AOTF devices at deep-UV wavelengths is progressing. The hermetic packaging of KDP AOTF is nearing completion. The solid-state optical sources being used for excitation include nonlinear optics based high-energy tunable UV transmitters that operate around 320 nm and 308 nm wavelengths, and a tunable deep-UV laser operating over 193 nm to 210 nm. These AOTF devices have been developed as turn-key devices for primarily for space-based chemical and biological sensing applications using laser induced Fluorescence and resonance Raman techniques.

Tactical Synthesis Of Efficient Global Search Algorithms

NASA Technical Reports Server (NTRS)

Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.

2009-01-01

Algorithm synthesis transforms a formal specification into an efficient algorithm to solve a problem. Algorithm synthesis in Specware combines the formal specification of a problem with a high-level algorithm strategy. To derive an efficient algorithm, a developer must define operators that refine the algorithm by combining the generic operators in the algorithm with the details of the problem specification. This derivation requires skill and a deep understanding of the problem and the algorithmic strategy. In this paper we introduce two tactics to ease this process. The tactics serve a similar purpose to tactics used for determining indefinite integrals in calculus, that is suggesting possible ways to attack the problem.

The DUV Stability of Superlattice-Doped CMOS Detector Arrays

NASA Technical Reports Server (NTRS)

Hoenk, M. E.; Carver, A. G.; Jones, T.; Dickie, M.; Cheng, P.; Greer, H. F.; Nikzad, S.; Sgro, J.; Tsur, S.

2013-01-01

JPL and Alacron have recently developed a high performance, DUV camera with a superlattice doped CMOS imaging detector. Supperlattice doped detectors achieve nearly 100% internal quantum efficiency in the deep and far ultraviolet, and a single layer, Al2O3 antireflection coating enables 64% external quantum efficiency at 263nm. In lifetime tests performed at Applied Materials using 263 nm pulsed, solid state and 193 nm pulsed excimer laser, the quantum efficiency and dark current of the JPL/Alacron camera remained stable to better than 1% precision during long-term exposure to several billion laser pulses, with no measurable degradation, no blooming and no image memory at 1000 fps.

DSN 63 64-meter antenna S- and X-band efficiency and system noise temperature calibrations, July 1986

NASA Technical Reports Server (NTRS)

Slobin, S. D.

1987-01-01

The Deep Space Network (DSN) 64-meter antenna in Spain (DSN 63) has been calibrated prior to its upgrading to a 70-meter high efficiency configuration in preparation for the Voyager Neptune encounter in August 1989. The S-band (2285 MHz) and X-band (8420 MHz) effective area efficiency and system noise temperature calibrations were carried out during July 1986 to establish a baseline system performance for this station. It is expected that the 70-meter will result in at least a 1.9 dB G/T improvement at X-band relative to the 64-meter baseline reference.

Rational Protein Engineering Guided by Deep Mutational Scanning

PubMed Central

Shin, HyeonSeok; Cho, Byung-Kwan

2015-01-01

Sequence–function relationship in a protein is commonly determined by the three-dimensional protein structure followed by various biochemical experiments. However, with the explosive increase in the number of genome sequences, facilitated by recent advances in sequencing technology, the gap between protein sequences available and three-dimensional structures is rapidly widening. A recently developed method termed deep mutational scanning explores the functional phenotype of thousands of mutants via massive sequencing. Coupled with a highly efficient screening system, this approach assesses the phenotypic changes made by the substitution of each amino acid sequence that constitutes a protein. Such an informational resource provides the functional role of each amino acid sequence, thereby providing sufficient rationale for selecting target residues for protein engineering. Here, we discuss the current applications of deep mutational scanning and consider experimental design. PMID:26404267

Growth and device processing of hexagonal boron nitride epilayers for thermal neutron and deep ultraviolet detectors

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

Doan, T. C.; Li, J.; Lin, J. Y.

2016-07-15

Solid-state neutron detectors with high performance are highly sought after for the detection of fissile materials. However, direct-conversion neutron detectors based on semiconductors with a measureable efficiency have not been realized. We report here the first successful demonstration of a direct-conversion semiconductor neutron detector with an overall detection efficiency for thermal neutrons of 4% and a charge collection efficiency as high as 83%. The detector is based on a 2.7 μm thick {sup 10}B-enriched hexagonal boron nitride (h-BN) epitaxial layer. The results represent a significant step towards the realization of practical neutron detectors based on h-BN epilayers. Neutron detectors basedmore » on h-BN are expected to possess all the advantages of semiconductor devices including wafer-scale processing, compact size, light weight, and ability to integrate with other functional devices.« less

Metallic Junction Thermoelectric Device Simulations

NASA Technical Reports Server (NTRS)

Duzik, Adam J.; Choi, Sang H.

2017-01-01

Thermoelectric junctions made of semiconductors have existed in radioisotope thermoelectric generators (RTG) for deep space missions, but are currently being adapted for terrestrial energy harvesting. Unfortunately, these devices are inefficient, operating at only 7% efficiency. This low efficiency has driven efforts to make high-figure-of-merit thermoelectric devices, which require a high electrical conductivity but a low thermal conductivity, a combination that is difficult to achieve. Lowered thermal conductivity has increased efficiency, but at the cost of power output. An alternative setup is to use metallic junctions rather than semiconductors as thermoelectric devices. Metals have orders of magnitude more electrons and electronic conductivities higher than semiconductors, but thermal conductivity is higher as well. To evaluate the viability of metallic junction thermoelectrics, a two dimensional heat transfer MATLAB simulation was constructed to calculate efficiency and power output. High Seebeck coefficient alloys, Chromel (90%Ni-10%Cr) and Constantan (55%Cu-45%Ni), produced efficiencies of around 20-30%. Parameters such as the number of layers of junctions, lateral junction density, and junction sizes for both series- and parallel-connected junctions were explored.

Thermoacoustic Imaging and Therapy Guidance based on Ultra-short Pulsed Microwave Pumped Thermoelastic Effect Induced with Superparamagnetic Iron Oxide Nanoparticles

PubMed Central

Wen, Liewei; Yang, Sihua; Zhong, Junping; Zhou, Quan; Xing, Da

2017-01-01

Multifunctional nanoparticle-mediated imaging and therapeutic techniques are promising modalities for accurate localization and targeted treatment of cancer in clinical settings. Thermoacoustic (TA) imaging is highly sensitive to detect the distribution of water, ions or specific nanoprobes and provides excellent resolution, good contrast and superior tissue penetrability. TA therapy is a potential non-invasive approach for the treatment of deep-seated tumors. In this study, human serum albumin (HSA)-functionalized superparamagnetic iron oxide nanoparticle (HSA-SPIO) is used as a multifunctional nanoprobe with clinical application potential for MRI, TA imaging and treatment of tumor. In addition to be a MRI contrast agent for tumor localization, HSA-SPIO can absorb pulsed microwave energy and transform it into shockwave via the thermoelastic effect. Thereby, the reconstructed TA image by detecting TA signal is expected to be a sensitive and accurate representation of the HSA-SPIO accumulation in tumor. More importantly, owing to the selective retention of HSA-SPIO in tumor tissues and strong TA shockwave at the cellular level, HSA-SPIO induced TA effect under microwave-pulse radiation can be used to highly-efficiently kill cancer cells and inhibit tumor growth. Furthermore, ultra-short pulsed microwave with high excitation efficiency and deep penetrability in biological tissues makes TA therapy a highly-efficient anti-tumor modality on the versatile platform. Overall, HSA-SPIO mediated MRI and TA imaging would offer more comprehensive diagnostic information and enable dynamic visualization of nanoagents in the tumorous tissue thereby tumor-targeted therapy. PMID:28638483

Thermoacoustic Imaging and Therapy Guidance based on Ultra-short Pulsed Microwave Pumped Thermoelastic Effect Induced with Superparamagnetic Iron Oxide Nanoparticles.

PubMed

Wen, Liewei; Yang, Sihua; Zhong, Junping; Zhou, Quan; Xing, Da

2017-01-01

Multifunctional nanoparticle-mediated imaging and therapeutic techniques are promising modalities for accurate localization and targeted treatment of cancer in clinical settings. Thermoacoustic (TA) imaging is highly sensitive to detect the distribution of water, ions or specific nanoprobes and provides excellent resolution, good contrast and superior tissue penetrability. TA therapy is a potential non-invasive approach for the treatment of deep-seated tumors. In this study, human serum albumin (HSA)-functionalized superparamagnetic iron oxide nanoparticle (HSA-SPIO) is used as a multifunctional nanoprobe with clinical application potential for MRI, TA imaging and treatment of tumor. In addition to be a MRI contrast agent for tumor localization, HSA-SPIO can absorb pulsed microwave energy and transform it into shockwave via the thermoelastic effect. Thereby, the reconstructed TA image by detecting TA signal is expected to be a sensitive and accurate representation of the HSA-SPIO accumulation in tumor. More importantly, owing to the selective retention of HSA-SPIO in tumor tissues and strong TA shockwave at the cellular level, HSA-SPIO induced TA effect under microwave-pulse radiation can be used to highly-efficiently kill cancer cells and inhibit tumor growth. Furthermore, ultra-short pulsed microwave with high excitation efficiency and deep penetrability in biological tissues makes TA therapy a highly-efficient anti-tumor modality on the versatile platform. Overall, HSA-SPIO mediated MRI and TA imaging would offer more comprehensive diagnostic information and enable dynamic visualization of nanoagents in the tumorous tissue thereby tumor-targeted therapy.

National Grid Deep Energy Retrofit Pilot Program—Clark Residence

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

None

2010-03-30

In this case study, Building Science Corporation partnered with local utility company, National Grid, Massachusetts homes. This project involved the renovation of a 18th century Cape-style building and achieved a super-insulated enclosure (R-35 walls, R-50+ roof, R-20+ foundation), extensive water management improvements, high-efficiency water heater, and state-of-the-art ventilation.

X-band preamplifier filter

NASA Technical Reports Server (NTRS)

Manshadi, F.

1986-01-01

A low-loss bandstop filter designed and developed for the Deep Space Network's 34-meter high-efficiency antennas is described. The filter is used for protection of the X-band traveling wave masers from the 20-kW transmitter signal. A combination of empirical and theoretical techniques was employed as well as computer simulation to verify the design before fabrication.

Large dielectric constant, high acceptor density, and deep electron traps in perovskite solar cell material CsGeI 3

DOE PAGES

Ming, Wenmei; Shi, Hongliang; Du, Mao-Hua

2016-01-01

Here we report that many metal halides that contain cations with the ns 2 electronic configuration have recently been discovered as high-performance optoelectronic materials. In particular, solar cells based on lead halide perovskites have shown great promise as evidenced by the rapid increase of the power conversion efficiency. In this paper, we show density functional theory calculations of electronic structure and dielectric and defect properties of CsGeI 3 (a lead-free halide perovskite material). The potential of CsGeI 3 as a solar cell material is assessed based on its intrinsic properties. We find anomalously large Born effective charges and a largemore » static dielectric constant dominated by lattice polarization, which should reduce carrier scattering, trapping, and recombination by screening charged defects and impurities. Defect calculations show that CsGeI 3 is a p-type semiconductor and its hole density can be modified by varying the chemical potentials of the constituent elements. Despite the reduction of long-range Coulomb attraction by strong screening, the iodine vacancy in CsGeI3 is found to be a deep electron trap due to the short-range potential, i.e., strong Ge–Ge covalent bonding, which should limit electron transport efficiency in p-type CsGeI 3. This is in contrast to the shallow iodine vacancies found in several Pb and Sn halide perovskites (e.g., CH 3NH 3PbI 3, CH 3NH 3SnI 3, and CsSnI 3). The low-hole-density CsGeI 3 may be a useful solar absorber material but the presence of the low-energy deep iodine vacancy may significantly reduce the open circuit voltage of the solar cell. Still, on the other hand, CsGeI 3 may be used as an efficient hole transport material in solar cells due to its small hole effective mass, the absence of low-energy deep hole traps, and the favorable band offset with solar absorber materials such as dye molecules and CH 3NH 3PbI 3.« less

Sleep and breathing in high altitude pulmonary edema susceptible subjects at 4,559 meters.

PubMed

Nussbaumer-Ochsner, Yvonne; Schuepfer, Nicole; Ursprung, Justyna; Siebenmann, Christoph; Maggiorini, Marco; Bloch, Konrad E

2012-10-01

Susceptible subjects ascending rapidly to high altitude develop pulmonary edema (HAPE). We evaluated whether HAPE leads to sleep and breathing disturbances that are alleviated by dexamethasone. Double-blind, randomized, placebo-controlled trial with open-label extension. One night in sleep laboratory at 490 m, 2 nights in mountain hut at 4,559 m. 21 HAPE susceptibles. Dexamethasone 2 × 8 mg/d, either 24 h prior to ascent and at 4,559 m (dex-early), or started on day 2 at 4,559 m only (dex-late). Polysomnography, questionnaires on sleep and acute mountain sickness. Polysomnographies at 490 m were normal. In dex-late (n = 12) at 4,559 m, night 1 and 3, median oxygen saturation was 71% and 80%, apnea/hypopnea index 91.3/h and 9.6/h. In dex-early (n = 9), corresponding values were 78% and 79%, and 85.3/h and 52.3/h (P < 0.05 vs. 490 m, all instances). In dex-late, ascending from 490 m to 4,559 m (night 1), sleep efficiency decreased from 91% to 65%, slow wave sleep from 20% to 8% (P < 0.05, both instances). In dex-early, corresponding sleep efficiencies were 96% and 95%, slow wave sleep 18% and 9% (P < 0.05). From night 1 to 3, sleep efficiency remained unchanged in both groups while slow wave sleep increased to 20% in dex-late (P < 0.01). Compared to dex-early, initial AMS scores in dex-late were higher but improved during stay at altitude. HAPE susceptibles ascending rapidly to high altitude experience pronounced nocturnal hypoxemia, and reduced sleep efficiency and deep sleep. Dexamethasone taken before ascent prevents severe hypoxemia and sleep disturbances, while dexamethasone taken 24 h after arrival at 4,559 m increases oxygenation and deep sleep.

Telescoping Solar Array Concept for Achieving High Packaging Efficiency

NASA Technical Reports Server (NTRS)

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.

Reconsideration of the Zincke salt: An efficient colorimetric chemosensor for detection of ethylamines

NASA Astrophysics Data System (ADS)

Kim, Jong H.

2018-03-01

In this work, an efficient colorimetric chemosensor for the detection of ethylamines using a pyridinium salt (the Zincke salt) is reported. Highly sensitive and selective reactivity of the Zincke salt enables colorimetric response of the Zincke salt solution to the ethylamines by showing well-defined visible color changes from colorless to the deep red. Furthermore, the Zincke salt thin film exhibits discernable color changes in response to ethylamine gas as well, which allows fabrication of simple, fast and portable strip- and textile-type ethylamine sensors.

Metal modulation epitaxy growth for extremely high hole concentrations above 1019 cm-3 in GaN

NASA Astrophysics Data System (ADS)

Namkoong, Gon; Trybus, Elaissa; Lee, Kyung Keun; Moseley, Michael; Doolittle, W. Alan; Look, David C.

2008-10-01

The free hole carriers in GaN have been limited to concentrations in the low 1018cm-3 range due to the deep activation energy, lower solubility, and compensation from defects, therefore, limiting doping efficiency to about 1%. Herein, we report an enhanced doping efficiency up to ˜10% in GaN by a periodic doping, metal modulation epitaxy growth technique. The hole concentrations grown by periodically modulating Ga atoms and Mg dopants were over ˜1.5×1019cm-3.

Sleep Quality Prediction From Wearable Data Using Deep Learning.

PubMed

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 sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional logistic regression (0.6463). Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep. ©Aarti Sathyanarayana, Shafiq Joty, Luis Fernandez-Luque, Ferda Ofli, Jaideep Srivastava, Ahmed Elmagarmid, Teresa Arora, Shahrad Taheri. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 04.11.2016.

Sleep Quality Prediction From Wearable Data Using Deep Learning

PubMed Central

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

2016-01-01

Background 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. Objective 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. Methods 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). Results 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 linear regression. CNN had the highest specificity and sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional linear regression (0.6463). Conclusions Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep. PMID:27815231

New ultra deep blue emitters based on chrysene chromophores

NASA Astrophysics Data System (ADS)

Shin, Hwangyu; Kang, Seokwoo; Jung, Hyocheol; Lee, Hayoon; Lee, Jaehyun; Kim, Beomjin; Park, Jongwook

2016-09-01

Chrysene, which has a wide band gap, was selected as an emission core to develop and study new materials that emit ultra-deep-blue light with high efficiency. Six compounds introducing various side groups were designed and synthesized: 6, 12-bis(30,50-diphenylphenyl)chrysene (TP-C-TP), 6-(30,50-diphenylphenyl)-12-(3,5-diphenylbiphenyl-400-yl)chrysene (TP-C-TPB) and 6,12-bis(300,500-diphenylbiphenyl-40-yl)chrysene (TPB-C-TPB), which contained bulky aromatic si de groups; and N,N,N0 ,N0-tetraphenyl-chrysene-6,12-diamine (DPA-C-DPA), [12-(4-diphenylamino-phenyl)-chrysene-6-yl]-diphenylamine(DPA-C-TPA) and 6,12-bis[4-(diphenylamino)phenyl]chrysene (TPA-C-TPA), which contained aromatic amine groups, were designed to afford improved hole injection properties. The synthesized materials showed maxi mum absorption wavelengths at 342-402 nm in the film state and exhibited deep-blue photoluminescence (PL) emission s at 417-464 nm. The use of TP-C-TPB in a non-doped organic light emitting diode (OLED) device resulted in ultra-deep-blue emission with an external quantum efficiency (EQE) of 4.02% and Commission Internationale de L'Eclairage coo rdinates (CIE x, y) of (0.154, 0.042) through effective control of the internal conjugation length and suppression of the p -p* stacking. The use of TPA-C-TPA, which includes an aromatic amine side group, afforded an excellent EQE of 4.83 % and excellent color coordinates CIE x, y of (0.147, 0.077).

Defect-Reduction Mechanism for Improving Radiative Efficiency in InGaN/GaN Light-Emitting Diodes using InGaN Underlayers

DOE PAGES

Armstrong, Andrew M.; Bryant, Benjamin N.; Crawford, Mary H.; ...

2015-04-01

The influence of a dilute In xGa 1-xN (x~0.03) underlayer (UL) grown below a single In 0.16Ga 0.84N quantum well (SQW), within a light-emitting diode(LED), on the radiative efficiency and deep level defect properties was studied using differential carrier lifetime (DCL) measurements and deep level optical spectroscopy (DLOS). DCL measurements found that inclusion of the UL significantly improved LED radiative efficiency. At low current densities, the non-radiative recombination rate of the LED with an UL was found to be 3.9 times lower than theLED without an UL, while the radiative recombination rates were nearly identical. This, then, suggests that themore » improved radiative efficiency resulted from reduced non-radiative defect concentration within the SQW. DLOS measurement found the same type of defects in the InGaN SQWs with and without ULs. However, lighted capacitance-voltage measurements of the LEDs revealed a 3.4 times reduction in a SQW-related near-mid-gap defect state for the LED with an UL. Furthermore, quantitative agreement in the reduction of both the non-radiative recombination rate (3.9×) and deep level density (3.4×) upon insertion of an UL corroborates deep level defect reduction as the mechanism for improved LED efficiency.« less

Heavy Mg-doping of (Al,Ga)N films for potential applications in deep ultraviolet light-emitting structures

NASA Astrophysics Data System (ADS)

Liang, Y. H.; Towe, E.

2018-03-01

Doping of high aluminum-containing (Al,Ga)N thin films has remained a challenging problem that has hindered progress in the development of deep ultraviolet light-emitters. This paper reports on the synthesis and use of heavily doped (Al,Ga)N films in deep ultraviolet (˜274 nm) light-emitting structures; these structures were synthesized by molecular beam epitaxy under liquid-metal growth conditions that facilitate the incorporation of extremely high density of Mg dopant impurities (up to 5 × 1019 cm-3) into aluminum-rich (Al,Ga)N thin films. Prototypical light-emitting diode structures incorporating Al0.7Ga0.3N films doped with Mg impurities that ionize to give free hole carrier concentrations of up to 6 × 1017 cm-3 exhibit external quantum efficiencies of up 0.56%; this is an improvement from previous devices made from molecular beam epitaxy-grown materials. This improvement is believed to be due to the high hole carrier concentration enabled by the relatively low activation energy of 220 meV compared to the expected values of 408-507 meV for Al0.7Ga0.3N films.

Inclusion of the fitness sharing technique in an evolutionary algorithm to analyze the fitness landscape of the genetic code adaptability.

PubMed

Santos, José; Monteagudo, Ángel

2017-03-27

The canonical code, although prevailing in complex genomes, is not universal. It was shown the canonical genetic code superior robustness compared to random codes, but it is not clearly determined how it evolved towards its current form. The error minimization theory considers the minimization of point mutation adverse effect as the main selection factor in the evolution of the code. We have used simulated evolution in a computer to search for optimized codes, which helps to obtain information about the optimization level of the canonical code in its evolution. A genetic algorithm searches for efficient codes in a fitness landscape that corresponds with the adaptability of possible hypothetical genetic codes. The lower the effects of errors or mutations in the codon bases of a hypothetical code, the more efficient or optimal is that code. The inclusion of the fitness sharing technique in the evolutionary algorithm allows the extent to which the canonical genetic code is in an area corresponding to a deep local minimum to be easily determined, even in the high dimensional spaces considered. The analyses show that the canonical code is not in a deep local minimum and that the fitness landscape is not a multimodal fitness landscape with deep and separated peaks. Moreover, the canonical code is clearly far away from the areas of higher fitness in the landscape. Given the non-presence of deep local minima in the landscape, although the code could evolve and different forces could shape its structure, the fitness landscape nature considered in the error minimization theory does not explain why the canonical code ended its evolution in a location which is not an area of a localized deep minimum of the huge fitness landscape.

TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutions.

PubMed

Heinrich, Mattias P; Blendowski, Max; Oktay, Ozan

2018-05-30

Deep convolutional neural networks (DCNN) are currently ubiquitous in medical imaging. While their versatility and high-quality results for common image analysis tasks including segmentation, localisation and prediction is astonishing, the large representational power comes at the cost of highly demanding computational effort. This limits their practical applications for image-guided interventions and diagnostic (point-of-care) support using mobile devices without graphics processing units (GPU). We propose a new scheme that approximates both trainable weights and neural activations in deep networks by ternary values and tackles the open question of backpropagation when dealing with non-differentiable functions. Our solution enables the removal of the expensive floating-point matrix multiplications throughout any convolutional neural network and replaces them by energy- and time-preserving binary operators and population counts. We evaluate our approach for the segmentation of the pancreas in CT. Here, our ternary approximation within a fully convolutional network leads to more than 90% memory reductions and high accuracy (without any post-processing) with a Dice overlap of 71.0% that comes close to the one obtained when using networks with high-precision weights and activations. We further provide a concept for sub-second inference without GPUs and demonstrate significant improvements in comparison with binary quantisation and without our proposed ternary hyperbolic tangent continuation. We present a key enabling technique for highly efficient DCNN inference without GPUs that will help to bring the advances of deep learning to practical clinical applications. It has also great promise for improving accuracies in large-scale medical data retrieval.

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

PubMed Central

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. PMID:28680387

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

PubMed

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.

Nonlinear analysis and control of an aircraft in the neighbourhood of deep stall

NASA Astrophysics Data System (ADS)

Kolb, Sébastien; Hétru, Laurent; Faure, Thierry M.; Montagnier, Olivier

2017-01-01

When an aircraft is locked in a stable equilibrium at high angle-of-attack, we have to do with the so-called deep stall which is a very dangerous situation. Airplanes with T-tail are mainly concerned with this phenomenon since the wake of the main wing flows over the horizontal tail and renders it ineffective but other aircrafts such as fighters can also be affected. First the phase portrait and bifurcation diagram are determined and characterized (with three equilibria in a deep stall prone configuration). It allows to diagnose the configurations of aircrafts susceptible to deep stall and also to point out the different types of time evolutions. Several techniques are used in order to determine the basin of attraction of the stable equilibrium at high angle-of-attack. They are based on the calculation of the stable manifold of the saddle-point equilibrium at medium angle-of-attack. Then several ways are explored in order to try to recover from deep stall. They exploits static features (such as curves of pitching moment versus angle-of-attack for full pitch down and full pitch up elevators) or dynamic aspects (excitation of the eigenmodes and improvement of the aerodynamic efficiency of the tail). Finally, some properties of a deep stall prone aircraft are pointed out and some control tools are also implemented. We try also to apply this mathematical results in a concrete situation by taking into account the captors specificities or by estimating the relevant variables thanks to other available information.

GaN ultraviolet p-i-n photodetectors with enhanced deep ultraviolet quantum efficiency

NASA Astrophysics Data System (ADS)

Wang, Guosheng; Xie, Feng; Wang, Jun; Guo, Jin

2017-10-01

GaN ultraviolet (UV) p-i-n photodetectors (PDs) with a thin p-AlGaN/GaN contact layer are designed and fabricated. The PD exhibits a low dark current density of˜7 nA/cm2 under -5 V, and a zero-bias peak responsivity of ˜0.16 A/W at 360 nm, which corresponds to a maximum quantum efficiency of 55%. It is found that, in the wavelength range between 250 and 365 nm, the PD with thin p-AlGaN/GaN contact layer exhibits enhanced quantum efficiency especially in a deep-UV wavelength range, than that of the control PD with conventional thin p-GaN contact layer. The improved quantum efficiency of the PD with thin p-AlGaN/GaN contact layer in the deep-UV wavelength range is mainly attributed to minority carrier reflecting properties of thin p-AlGaN/GaN heterojunction which could reduce the surface recombination loss of photon-generated carriers and improve light current collection efficiency.

High Efficiency Ka-Band Solid State Power Amplifier Waveguide Power Combiner

NASA Technical Reports Server (NTRS)

Wintucky, Edwin G.; Simons, Rainee N.; Chevalier, Christine T.; Freeman, Jon C.

2010-01-01

A novel Ka-band high efficiency asymmetric waveguide four-port combiner for coherent combining of two Monolithic Microwave Integrated Circuit (MMIC) Solid State Power Amplifiers (SSPAs) having unequal outputs has been successfully designed, fabricated and characterized over the NASA deep space frequency band from 31.8 to 32.3 GHz. The measured combiner efficiency is greater than 90 percent, the return loss greater than 18 dB and input port isolation greater than 22 dB. The manufactured combiner was designed for an input power ratio of 2:1 but can be custom designed for any arbitrary power ratio. Applications considered are NASA s space communications systems needing 6 to 10 W of radio frequency (RF) power. This Technical Memorandum (TM) is an expanded version of the article recently published in Institute of Engineering and Technology (IET) Electronics Letters.

Investigation of surface finishing of carbon based coated tools for dry deep drawing of aluminium alloys

NASA Astrophysics Data System (ADS)

Steiner, J.; Andreas, K.; Merklein, M.

2016-11-01

Global trends like growing environmental awareness and demand for resource efficiency motivate an abandonment of lubricants in metal forming. However, dry forming evokes increased friction and wear. Especially, dry deep drawing of aluminum alloys leads to intensive interaction between tool and workpiece due to its high adhesion tendency. One approach to improve the tribological behavior is the application of carbon based coatings. These coatings are characterized by high wear resistance. In order to investigate the potential of carbon based coatings for dry deep drawing, friction and wear behavior of different coating compositions are evaluated in strip drawing tests. This setup is used to model the tribological conditions in the flange area of deep drawing operations. The tribological behavior of tetrahedral amorphous (ta-C) and hydrogenated amorphous carbon coatings with and without tungsten modification (a-C:H:W, a-C:H) is investigated. The influence of tool topography is analyzed by applying different surface finishing. The results show reduced friction with decreased roughness for coated tools. Besides tool topography the coating type determines the tribological conditions. Smooth tools with ta-C and a-C:H coatings reveal low friction and prevent adhesive wear. In contrast, smooth a-C:H:W coated tools only lead to slight improvement compared to rough, uncoated specimen.

Targeted Mesoporous Iron Oxide Nanoparticles-Encapsulated Perfluorohexane and a Hydrophobic Drug for Deep Tumor Penetration and Therapy.

PubMed

Su, Yu-Lin; Fang, Jen-Hung; Liao, Chia-Ying; Lin, Chein-Ting; Li, Yun-Ting; Hu, Shang-Hsiu

2015-01-01

A magneto-responsive energy/drug carrier that enhances deep tumor penetration with a porous nano-composite is constructed by using a tumor-targeted lactoferrin (Lf) bio-gate as a cap on mesoporous iron oxide nanoparticles (MIONs). With a large payload of a gas-generated molecule, perfluorohexane (PFH), and a hydrophobic anti-cancer drug, paclitaxel (PTX), Lf-MIONs can simultaneously perform bursting gas generation and on-demand drug release upon high-frequency magnetic field (MF) exposure. Biocompatible PFH was chosen and encapsulated in MIONs due to its favorable phase transition temperature (56 °C) and its hydrophobicity. After a short-duration MF treatment induces heat generation, the local pressure increase via the gasifying of the PFH embedded in MION can substantially rupture the three-dimensional tumor spheroids in vitro as well as enhance drug and carrier penetration. As the MF treatment duration increases, Lf-MIONs entering the tumor spheroids provide an intense heat and burst-like drug release, leading to superior drug delivery and deep tumor thermo-chemo-therapy. With their high efficiency for targeting tumors, Lf-MIONs/PTX-PFH suppressed subcutaneous tumors in 16 days after a single MF exposure. This work presents the first study of using MF-induced PFH gasification as a deep tumor-penetrating agent for drug delivery.

Targeted Mesoporous Iron Oxide Nanoparticles-Encapsulated Perfluorohexane and a Hydrophobic Drug for Deep Tumor Penetration and Therapy

PubMed Central

Su, Yu-Lin; Fang, Jen-Hung; Liao, Chia-Ying; Lin, Chein-Ting; Li, Yun-Ting; Hu, Shang-Hsiu

2015-01-01

A magneto-responsive energy/drug carrier that enhances deep tumor penetration with a porous nano-composite is constructed by using a tumor-targeted lactoferrin (Lf) bio-gate as a cap on mesoporous iron oxide nanoparticles (MIONs). With a large payload of a gas-generated molecule, perfluorohexane (PFH), and a hydrophobic anti-cancer drug, paclitaxel (PTX), Lf-MIONs can simultaneously perform bursting gas generation and on-demand drug release upon high-frequency magnetic field (MF) exposure. Biocompatible PFH was chosen and encapsulated in MIONs due to its favorable phase transition temperature (56 °C) and its hydrophobicity. After a short-duration MF treatment induces heat generation, the local pressure increase via the gasifying of the PFH embedded in MION can substantially rupture the three-dimensional tumor spheroids in vitro as well as enhance drug and carrier penetration. As the MF treatment duration increases, Lf-MIONs entering the tumor spheroids provide an intense heat and burst-like drug release, leading to superior drug delivery and deep tumor thermo-chemo-therapy. With their high efficiency for targeting tumors, Lf-MIONs/PTX-PFH suppressed subcutaneous tumors in 16 days after a single MF exposure. This work presents the first study of using MF-induced PFH gasification as a deep tumor-penetrating agent for drug delivery. PMID:26379789

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

PubMed Central

Zhang, Wei; Peng, Gaoliang; Li, Chuanhao; Chen, Yuanhang; Zhang, Zhujun

2017-01-01

Intelligent fault diagnosis techniques have replaced time-consuming and unreliable human analysis, increasing the efficiency of fault diagnosis. Deep learning models can improve the accuracy of intelligent fault diagnosis with the help of their multilayer nonlinear mapping ability. This paper proposes a novel method named Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN). The proposed method uses raw vibration signals as input (data augmentation is used to generate more inputs), and uses the wide kernels in the first convolutional layer for extracting features and suppressing high frequency noise. Small convolutional kernels in the preceding layers are used for multilayer nonlinear mapping. AdaBN is implemented to improve the domain adaptation ability of the model. The proposed model addresses the problem that currently, the accuracy of CNN applied to fault diagnosis is not very high. WDCNN can not only achieve 100% classification accuracy on normal signals, but also outperform the state-of-the-art DNN model which is based on frequency features under different working load and noisy environment conditions. PMID:28241451

A bright cyan-excitable orange fluorescent protein facilitates dual-emission microscopy and enhances bioluminescence imaging in vivo

PubMed Central

Chu, Jun; Oh, Young-Hee; Sens, Alex; Ataie, Niloufar; Dana, Hod; Macklin, John J.; Laviv, Tal; Welf, Erik S.; Dean, Kevin M.; Zhang, Feijie; Kim, Benjamin B.; Tang, Clement Tran; Hu, Michelle; Baird, Michelle A.; Davidson, Michael W.; Kay, Mark A.; Fiolka, Reto; Yasuda, Ryohei; Kim, Douglas S.; Ng, Ho-Leung; Lin, Michael Z.

2016-01-01

Orange-red fluorescent proteins (FPs) are widely used in biomedical research for multiplexed epifluorescence microscopy with GFP-based probes, but their different excitation requirements make multiplexing with new advanced microscopy methods difficult. Separately, orange-red FPs are useful for deep-tissue imaging in mammals due to the relative tissue transmissibility of orange-red light, but their dependence on illumination limits their sensitivity as reporters in deep tissues. Here we describe CyOFP1, a bright engineered orange-red FP that is excitable by cyan light. We show that CyOFP1 enables single-excitation multiplexed imaging with GFP-based probes in single-photon and two-photon microscopy, including time-lapse imaging in light-sheet systems. CyOFP1 also serves as an efficient acceptor for resonance energy transfer from the highly catalytic blue-emitting luciferase NanoLuc. An optimized fusion of CyOFP1 and NanoLuc, called Antares, functions as a highly sensitive bioluminescent reporter in vivo, producing substantially brighter signals from deep tissues than firefly luciferase and other bioluminescent proteins. PMID:27240196

The Biological Deep Sea Hydrothermal Vent as a Model to Study Carbon Dioxide Capturing Enzymes

PubMed Central

Minic, Zoran; Thongbam, Premila D.

2011-01-01

Deep sea hydrothermal vents are located along the mid-ocean ridge system, near volcanically active areas, where tectonic plates are moving away from each other. Sea water penetrates the fissures of the volcanic bed and is heated by magma. This heated sea water rises to the surface dissolving large amounts of minerals which provide a source of energy and nutrients to chemoautotrophic organisms. Although this environment is characterized by extreme conditions (high temperature, high pressure, chemical toxicity, acidic pH and absence of photosynthesis) a diversity of microorganisms and many animal species are specially adapted to this hostile environment. These organisms have developed a very efficient metabolism for the assimilation of inorganic CO2 from the external environment. In order to develop technology for the capture of carbon dioxide to reduce greenhouse gases in the atmosphere, enzymes involved in CO2 fixation and assimilation might be very useful. This review describes some current research concerning CO2 fixation and assimilation in the deep sea environment and possible biotechnological application of enzymes for carbon dioxide capture. PMID:21673885

The biological deep sea hydrothermal vent as a model to study carbon dioxide capturing enzymes.

PubMed

Minic, Zoran; Thongbam, Premila D

2011-01-01

Deep sea hydrothermal vents are located along the mid-ocean ridge system, near volcanically active areas, where tectonic plates are moving away from each other. Sea water penetrates the fissures of the volcanic bed and is heated by magma. This heated sea water rises to the surface dissolving large amounts of minerals which provide a source of energy and nutrients to chemoautotrophic organisms. Although this environment is characterized by extreme conditions (high temperature, high pressure, chemical toxicity, acidic pH and absence of photosynthesis) a diversity of microorganisms and many animal species are specially adapted to this hostile environment. These organisms have developed a very efficient metabolism for the assimilation of inorganic CO₂ from the external environment. In order to develop technology for the capture of carbon dioxide to reduce greenhouse gases in the atmosphere, enzymes involved in CO₂ fixation and assimilation might be very useful. This review describes some current research concerning CO₂ fixation and assimilation in the deep sea environment and possible biotechnological application of enzymes for carbon dioxide capture.

Benzobisoxazole cruciforms: A tunable, cross-conjugated platform for the generation of deep blue OLED materials

DOE PAGES

Chavez, III, Ramiro; Cai, Min; Tlach, Brian; ...

2016-01-20

Four new cross-conjugated small molecules based on a central benzo[1,2-d:4,5-d']bisoxazole moiety possessing semi-independently tunable HOMO and LUMO levels were synthesized and the properties of these materials were evaluated experimentally and theoretically. The molecules were thermally stable with 5% weight loss occurring well above 350 °C. The cruciforms all exhibited blue emission in solution ranging from 433–450 nm. Host–guest OLEDs fabricated from various concentrations of these materials using the small molecule host 4,4'-bis(9-carbazolyl)-biphenyl (CBP) exhibited deep blue-emission with Commission Internationale de L'Eclairage (CIE) coordinates of (0.15 ≤ x ≤ 0.17, 0.05 ≤ y ≤ 0.11), and maximum luminance efficiencies as highmore » as ~2 cd A–1. Lastly, these results demonstrate the potential of benzobisoxazole cruciforms as emitters for developing high-performance deep blue OLEDs.« less

Deep magnetic capture of magnetically loaded cells for spatially targeted therapeutics.

PubMed

Huang, Zheyong; Pei, Ning; Wang, Yanyan; Xie, Xinxing; Sun, Aijun; Shen, Li; Zhang, Shuning; Liu, Xuebo; Zou, Yunzeng; Qian, Juying; Ge, Junbo

2010-03-01

Magnetic targeting has recently demonstrated potential in promoting magnetically loaded cell delivery to target lesion, but its application is limited by magnetic attenuation. For deep magnetic capture of cells for spatial targeting therapeutics, we designed a magnetic pole, in which the magnetic field density can be focused at a distance from the pole. As flowing through a tube served as a model of blood vessels, the magnetically loaded mesenchymal stem cells (MagMSCs) were highly enriched at the site distance from the magnetic pole. The cell capture efficiency was positively influenced by the magnetic flux density, and inversely influenced by the flow velocity, and well-fitted with the deductive value by theoretical considerations. It appeared to us that the spatially-focused property of the magnetic apparatus promises a new deep targeting strategy to promote homing and engraftment for cellular therapy. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Adolescents with greater mental toughness show higher sleep efficiency, more deep sleep and fewer awakenings after sleep onset.

PubMed

Brand, Serge; Gerber, Markus; Kalak, Nadeem; Kirov, Roumen; Lemola, Sakari; Clough, Peter J; Pühse, Uwe; Holsboer-Trachsler, Edith

2014-01-01

Mental toughness (MT) is understood as the display of confidence, commitment, challenge, and control. Mental toughness is associated with resilience against stress. However, research has not yet focused on the relation between MT and objective sleep. The aim of the present study was therefore to explore the extent to which greater MT is associated with objectively assessed sleep among adolescents. A total of 92 adolescents (35% females; mean age, 18.92 years) completed the Mental Toughness Questionnaire. Participants were split into groups of high and low mental toughness. Objective sleep was recorded via sleep electroencephalograms and subjective sleep was assessed via a questionnaire. Compared with participants with low MT, participants with high MT had higher sleep efficiency, a lower number of awakenings after sleep onset, less light sleep, and more deep sleep. They also reported lower daytime sleepiness. Adolescents reporting higher MT also had objectively better sleep, as recorded via sleep electroencephalograms. A bidirectional association between MT and sleep seems likely; therefore, among adolescence, improving sleep should increase MT, and improving MT should increase sleep. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

A clinical decision rule and D-dimer testing to rule out upper extremity deep vein thrombosis in high-risk patients.

PubMed

van Es, Nick; Bleker, Suzanne M; Di Nisio, Marcello; Kleinjan, Ankie; Beyer-Westendorf, Jan; Camporese, Giuseppe; Kamphuisen, Pieter W; Büller, Harry R; Bossuyt, Patrick M

2016-12-01

In a management study, a diagnostic algorithm consisting of a clinical decision rule, D-dimer, and ultrasonography was shown to safely exclude upper extremity deep vein thrombosis (UEDVT). Efficiency may be lower in high-risk subgroups: those with a central venous catheter or pacemaker, inpatients, cancer, and elderly patients. Data of 406 patients with suspected UEDVT enrolled in a prospective management study were used for the present analysis. The aim was to evaluate the efficiency of the algorithm in subgroups, defined as the proportion of patients in whom imaging could be safely withheld based on the combination of a decision rule result indicating "UEDVT unlikely" and a normal D-dimer result. The strategy excluded UEDVT in 87 of 406 patients (21%); ultrasonography was withheld in these patients and none developed UEDVT during 3months of follow-up. In contrast, ultrasonography could be withheld in only 4 of 92 patients with a catheter or pacemaker (4.3%; 95% CI: 1.7% to 11%) and in 4 of 83 inpatients (4.8%; 95% CI: 1.9% to 12%). The efficiency was 11% in patients with cancer and 13% in those older than 75years. Although the combination of a decision rule and D-dimer testing is safe in excluding UEDVT in the overall population of patients with suspected UEDVT, its efficiency appears limited in some subgroups, in particular those with a central venous catheter or pacemaker, and inpatients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of electrode gap and electric current on chlorine generation of electrolyzed deep ocean water.

PubMed

Hsu, Guoo-Shyng Wang; Hsu, Shun-Yao

2018-04-01

Electrolyzed water is a sustainable disinfectant, which can comply with food safety regulations and is environmental friendly. A two-factor central composite design was adopted for studying the effects of electrode gap and electric current on chlorine generation efficiency of electrolyzed deep ocean water. Deep ocean water was electrolyzed in a glass electrolyzing cell equipped with platinum-plated titanium anode and cathode in a constant-current operation mode. Results showed that current density, chlorine concentration, and electrolyte temperature increased with electric current, while electric efficiency decreased with electric current and electrode gap. An electrode gap of less than 11.7 mm, and a low electric current appeared to be a more energy efficient design and operation condition for the electrolysis system. Copyright © 2017. Published by Elsevier B.V.

Separation of the isomers of benzene poly(carboxylic acid)s by quaternary ammonium salt via formation of deep eutectic solvents.

PubMed

Hou, Yucui; Li, Jian; Ren, Shuhang; Niu, Muge; Wu, Weize

2014-11-26

Because of similar properties and very low volatility, isomers of benzene poly(carboxylic acid)s (BPCAs) are very difficult to separate. In this work, we found that isomers of BPCAs could be separated efficiently by quaternary ammonium salts (QASs) via formation of deep eutectic solvents (DESs). Three kinds of QASs were used to separate the isomers of BPCAs, including the isomers of benzene tricarboxylic acids (trimellitic acid, trimesic acid, and hemimellitic acid) and the isomers of benzene dicarboxylic acids (phthalic acid and isophthalic acid). Among the QASs, tetraethylammonium chloride was found to have the best performance, which could completely separate BPCA isomers in methyl ethyl ketone solutions. It was found that the hydrogen bond forming between QAS and BPCA results in the selective separation of BPCA isomers. QAS in DES was regenerated effectively by the antisolvent method, and the regenerated QAS was reused four times with the same high efficiency.

Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras

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

Cui, Yonggang; Thomas, Maikael A.

We propose the development of proven deep learning algorithms to flag objects and events of interest in Next Generation Surveillance System (NGSS) surveillance to make IAEA image review more efficient. Video surveillance is one of the core monitoring technologies used by the IAEA Department of Safeguards when implementing safeguards at nuclear facilities worldwide. The current image review software GARS has limited automated functions, such as scene-change detection, black image detection and missing scene analysis, but struggles with highly cluttered backgrounds. A cutting-edge algorithm to be developed in this project will enable efficient and effective searches in images and video streamsmore » by identifying and tracking safeguards relevant objects and detect anomalies in their vicinity. In this project, we will develop the algorithm, test it with the IAEA surveillance cameras and data sets collected at simulated nuclear facilities at BNL and SNL, and implement it in a software program for potential integration into the IAEA’s IRAP (Integrated Review and Analysis Program).« less

AlGaN-based deep ultraviolet light-emitting diodes grown on nano-patterned sapphire substrates with significant improvement in internal quantum efficiency

NASA Astrophysics Data System (ADS)

Dong, Peng; Yan, Jianchang; Zhang, Yun; Wang, Junxi; Zeng, Jianping; Geng, Chong; Cong, Peipei; Sun, Lili; Wei, Tongbo; Zhao, Lixia; Yan, Qingfeng; He, Chenguang; Qin, Zhixin; Li, Jinmin

2014-06-01

We report high-performance AlGaN-based deep ultraviolet light-emitting diodes grown on nano-patterned sapphire substrates (NPSS) using metal-organic chemical vapor deposition. By nanoscale epitaxial lateral overgrowth on NPSS, 4-μm AlN buffer layer has shown strain relaxation and a coalescence thickness of only 2.5 μm. The full widths at half-maximum of X-ray diffraction (002) and (102) ω-scan rocking curves of AlN on NPSS are only 69.4 and 319.1 arcsec. The threading dislocation density in AlGaN-based multi-quantum wells, which are grown on this AlN/NPSS template with a light-emitting wavelength at 283 nm at room temperature, is reduced by 33% compared with that on flat sapphire substrate indicated by atomic force microscopy measurements, and the internal quantum efficiency increases from 30% to 43% revealed by temperature-dependent photoluminescent measurement.

Investigation of miniaturized radioisotope thermionic power generation for general use

NASA Astrophysics Data System (ADS)

Duzik, Adam J.; Choi, Sang H.

2016-04-01

Radioisotope thermoelectric generators (RTGs) running off the radioisotope Pu238 are the current standard in deep space probe power supplies. While reliable, these generators are very inefficient, operating at only ~7% efficiency. As an alternative, more efficient radioisotope thermionic emission generators (RTIGs) are being explored. Like RTGs, current RTIGs concepts use exotic materials for the emitter, limiting applicability to space and other niche applications. The high demand for long-lasting mobile power sources would be satisfied if RTIGs could be produced inexpensively. This work focuses on exposing several common materials, such as Al, stainless steel, W, Si, and Cu, to elevated temperatures under vacuum to determine the efficiency of each material as inexpensive replacements for thermoelectric materials.

Management and Accountability Procedures: DEEP - The New Mexico State Facilitator.

ERIC Educational Resources Information Center

New Mexico Univ., Albuquerque. Coll. of Education.

Presented is a description of how DEEP (Developmental Economic Education Program) monitors activity and achievements to ensure that objectives are met effectively and efficiently, and that evidence of achievement is available for reports. The purposes of DEEP management and accountability procedures are: (1) to maintain both long term and short…

76 FR 50171 - Notice of Intent To Prepare an Environmental Impact Statement for the Henrys Fork Salinity...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-12

... following methods: Government-wide rulemaking Web site: http://www.regulations.gov . Follow the instructions... irrigation system improvements outlined in this plan will provide more efficient use of this water. Deep... reduction of excess deep percolation passing below the plant root zone. Deep percolation of irrigation water...

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

PubMed

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.

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

PubMed

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.

Improved transition path sampling methods for simulation of rare events

NASA Astrophysics Data System (ADS)

Chopra, Manan; Malshe, Rohit; Reddy, Allam S.; de Pablo, J. J.

2008-04-01

The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations.

Synthesis and Photovoltaic Properties of a Copolymer based on thieno [2, 3-f] benzofuran and thienopyrroledione

NASA Astrophysics Data System (ADS)

Gao, Yueyue; Yang, Yulin; Zhang, Yong

2017-12-01

A novel donor-acceptor type conjugated polymer PTBFTPD based on two-dimensional (2D) conjugated alkylthienyl substituted thieno[2,3-f]benzofuran (TBF) and thienopyrroledione (TPD) unit, was synthesized and applied as donor material for bulk heterojunction solar cells. The novol polymer possesses a narrow bandgap of 1.83 eV, a deep HOMO energy level (-5.64 eV) and a closer π-π stacking. After conventional devices were fabricated using PTBFTPD as donor blending with PC70BM as acceptor, a power conversion efficiency (PCE) of 4.33% with a high open circuit voltage (Voc) of 1.09 V was obtained. The result indicates the promising potential of thieno [2, 3-f] benzofuran unit for high efficient polymer solar cells with a high voltage.

Metagenomic analysis of a desulphurisation system used to treat biogas from vinasse methanisation.

PubMed

Dias, Marcela França; Colturato, Luis Felipe; de Oliveira, João Paulo; Leite, Laura Rabelo; Oliveira, Guilherme; Chernicharo, Carlos Augusto; de Araújo, Juliana Calabria

2016-04-01

We investigated the response of microbial community to changes in H2S loading rate in a microaerated desulphurisation system treating biogas from vinasse methanisation. H2S removal efficiency was high, and both COD and DO seemed to be important parameters to biomass activity. DGGE analysis retrieved sequences of sulphide-oxidising bacteria (SOB), such as Thioalkalimicrobium sp. Deep sequencing analysis revealed that the microbial community was complex and remained constant throughout the experiment. Most sequences belonged to Firmicutes and Proteobacteria, and, to a lesser extent, Bacteroidetes, Chloroflexi, and Synergistetes. Despite the high sulphide removal efficiency, the abundance of the taxa of SOB was low, and was negatively affected by the high sulphide loading rate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structural Analyses of Stirling Power Convertor Heater Head for Long-Term Reliability, Durability, and Performance

NASA Technical Reports Server (NTRS)

Halford, Gary R.; Shah, Ashwin; Arya, Vinod K.; Krause, David L.; Bartolotta, Paul A.

2002-01-01

Deep-space missions require onboard electric power systems with reliable design lifetimes of up to 10 yr and beyond. A high-efficiency Stirling radioisotope power system is a likely candidate for future deep-space missions and Mars rover applications. To ensure ample durability, the structurally critical heater head of the Stirling power convertor has undergone extensive computational analyses of operating temperatures (up to 650 C), stresses, and creep resistance of the thin-walled Inconel 718 bill of material. Durability predictions are presented in terms of the probability of survival. A benchmark structural testing program has commenced to support the analyses. This report presents the current status of durability assessments.

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

Renner, J.; Farbin, A.; Vidal, J. Muñoz

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 usemore » of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.« less

Three-dimensional assembly of tissue-engineered cartilage constructs results in cartilaginous tissue formation without retainment of zonal characteristics.

PubMed

Schuurman, W; Harimulyo, E B; Gawlitta, D; Woodfield, T B F; Dhert, W J A; van Weeren, P R; Malda, J

2016-04-01

Articular cartilage has limited regenerative capabilities. Chondrocytes from different layers of cartilage have specific properties, and regenerative approaches using zonal chondrocytes may yield better replication of the architecture of native cartilage than when using a single cell population. To obtain high seeding efficiency while still mimicking zonal architecture, cell pellets of expanded deep zone and superficial zone equine chondrocytes were seeded and cultured in two layers on poly(ethylene glycol)-terephthalate-poly(butylene terephthalate) (PEGT-PBT) scaffolds. Scaffolds seeded with cell pellets consisting of a 1:1 mixture of both cell sources served as controls. Parallel to this, pellets of superficial or deep zone chondrocytes, and combinations of the two cell populations, were cultured without the scaffold. Pellet cultures of zonal chondrocytes in scaffolds resulted in a high seeding efficiency and abundant cartilaginous tissue formation, containing collagen type II and glycosaminoglycans (GAGs) in all groups, irrespective of the donor (n = 3), zonal population or stratified scaffold-seeding approach used. However, whereas total GAG production was similar, the constructs retained significantly more GAG compared to pellet cultures, in which a high percentage of the produced GAGs were secreted into the culture medium. Immunohistochemistry for zonal markers did not show any differences between the conditions. We conclude that spatially defined pellet culture in 3D scaffolds is associated with high seeding efficiency and supports cartilaginous tissue formation, but did not result in the maintenance or restoration of the original zonal phenotype. The use of pellet-assembled constructs leads to a better retainment of newly produced GAGs than the use of pellet cultures alone. Copyright © 2013 John Wiley & Sons, Ltd.

Quick acquisition and recognition method for the beacon in deep space optical communications.

PubMed

Wang, Qiang; Liu, Yuefei; Ma, Jing; Tan, Liying; Yu, Siyuan; Li, Changjiang

2016-12-01

In deep space optical communications, it is very difficult to acquire the beacon given the long communication distance. Acquisition efficiency is essential for establishing and holding the optical communication link. Here we proposed a quick acquisition and recognition method for the beacon in deep optical communications based on the characteristics of the deep optical link. To identify the beacon from the background light efficiently, we utilized the maximum similarity between the collecting image and the reference image for accurate recognition and acquisition of the beacon in the area of uncertainty. First, the collecting image and the reference image were processed by Fourier-Mellin. Second, image sampling and image matching were applied for the accurate positioning of the beacon. Finally, the field programmable gate array (FPGA)-based system was used to verify and realize this method. The experimental results showed that the acquisition time for the beacon was as fast as 8.1s. Future application of this method in the system design of deep optical communication will be beneficial.

DeepSynergy: predicting anti-cancer drug synergy with Deep Learning

PubMed Central

Preuer, Kristina; Lewis, Richard P I; Hochreiter, Sepp; Bender, Andreas; Bulusu, Krishna C; Klambauer, Günter

2018-01-01

Abstract Motivation While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerged as a time- and cost-efficient way to prioritize combinations to test, based on recently available large-scale combination screening data. Recently, Deep Learning has had an impact in many research areas by achieving new state-of-the-art model performance. However, Deep Learning has not yet been applied to drug synergy prediction, which is the approach we present here, termed DeepSynergy. DeepSynergy uses chemical and genomic information as input information, a normalization strategy to account for input data heterogeneity, and conical layers to model drug synergies. Results DeepSynergy was compared to other machine learning methods such as Gradient Boosting Machines, Random Forests, Support Vector Machines and Elastic Nets on the largest publicly available synergy dataset with respect to mean squared error. DeepSynergy significantly outperformed the other methods with an improvement of 7.2% over the second best method at the prediction of novel drug combinations within the space of explored drugs and cell lines. At this task, the mean Pearson correlation coefficient between the measured and the predicted values of DeepSynergy was 0.73. Applying DeepSynergy for classification of these novel drug combinations resulted in a high predictive performance of an AUC of 0.90. Furthermore, we found that all compared methods exhibit low predictive performance when extrapolating to unexplored drugs or cell lines, which we suggest is due to limitations in the size and diversity of the dataset. We envision that DeepSynergy could be a valuable tool for selecting novel synergistic drug combinations. Availability and implementation DeepSynergy is available via www.bioinf.jku.at/software/DeepSynergy. Contact klambauer@bioinf.jku.at Supplementary information Supplementary data are available at Bioinformatics online. PMID:29253077

Growth and characterization of β-Ga2O3 thin films by molecular beam epitaxy for deep-UV photodetectors

NASA Astrophysics Data System (ADS)

Ghose, Susmita; Rahman, Shafiqur; Hong, Liang; Rojas-Ramirez, Juan Salvador; Jin, Hanbyul; Park, Kibog; Klie, Robert; Droopad, Ravi

2017-09-01

The growth of high quality epitaxial beta-gallium oxide (β-Ga2O3) using a compound source by molecular beam epitaxy has been demonstrated on c-plane sapphire (Al2O3) substrates. The compound source provides oxidized gallium molecules in addition to oxygen when heated from an iridium crucible in a high temperature effusion cell enabling a lower heat of formation for the growth of Ga2O3, resulting in a more efficient growth process. This source also enabled the growth of crystalline β-Ga2O3 without the need for additional oxygen. The influence of the substrate temperatures on the crystal structure and quality, chemical bonding, surface morphology, and optical properties has been systematically evaluated by x-ray diffraction, scanning transmission electron microscopy, x-ray photoelectron spectroscopy, atomic force microscopy, spectroscopic ellipsometry, and UV-vis spectroscopy. Under optimized growth conditions, all films exhibited pure (" separators="|2 ¯01 ) oriented β-Ga2O3 thin films with six-fold rotational symmetry when grown on a sapphire substrate. The thin films demonstrated significant absorption in the deep-ultraviolet (UV) region with an optical bandgap around 5.0 eV and a refractive index of 1.9. A deep-UV photodetector fabricated on the high quality β-Ga2O3 thin film exhibits high resistance and small dark current (4.25 nA) with expected photoresponse for 254 nm UV light irradiation suggesting that the material grown using the compound source is a potential candidate for deep-ultraviolet photodetectors.

Deep Packet/Flow Analysis using GPUs

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

Gong, Qian; Wu, Wenji; DeMar, Phil

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. Sincemore » 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.« less

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

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

Yan Haojing; Finkelstein, Steven L.; Huang, Kuang-Han

One key goal of the Hubble Space Telescope Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey is to track galaxy evolution back to z Almost-Equal-To 8. Its two-tiered ''wide and deep'' strategy bridges significant gaps in existing near-infrared surveys. Here we report on z Almost-Equal-To 8 galaxy candidates selected as F105W-band dropouts in one of its deep fields, which covers 50.1 arcmin{sup 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 < 26.2 mag, and are >1 mag brighter than any previously known F105W-dropouts.more » We derive constraints on the bright end of the rest-frame ultraviolet luminosity function of galaxies at z Almost-Equal-To 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 Almost-Equal-To 8. Their derived stellar masses are on the order of a few Multiplication-Sign 10{sup 9} M{sub Sun }, from which we obtain the first measurement of the high-mass end of the galaxy stellar mass function at z Almost-Equal-To 8. The high number density of very luminous and very massive galaxies at z Almost-Equal-To 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.« less

Early diagenesis in the sediments of the Congo deep-sea fan dominated by massive terrigenous deposits: Part II - Iron-sulfur coupling

NASA Astrophysics Data System (ADS)

Taillefert, Martial; Beckler, Jordon S.; Cathalot, Cécile; Michalopoulos, Panagiotis; Corvaisier, Rudolph; Kiriazis, Nicole; Caprais, Jean-Claude; Pastor, Lucie; Rabouille, Christophe

2017-08-01

Deep-sea fans are well known depot centers for organic carbon that should promote sulfate reduction. At the same time, the high rates of deposition of unconsolidated metal oxides from terrigenous origin may also promote metal-reducing microbial activity. To investigate the eventual coupling between the iron and sulfur cycles in these environments, shallow sediment cores (< 50 cm) across various channels and levees in the Congo River deep-sea fan ( 5000 m) were profiled using a combination of geochemical methods. Interestingly, metal reduction dominated suboxic carbon remineralization processes in most of these sediments, while dissolved sulfide was absent. In some 'hotspot' patches, however, sulfate reduction produced large sulfide concentrations which supported chemosynthetic-based benthic megafauna. These environments were characterized by sharp geochemical boundaries compared to the iron-rich background environment, suggesting that FeS precipitation efficiently titrated iron and sulfide from the pore waters. A companion study demonstrated that methanogenesis was active in the deep sediment layers of these patchy ecosystems, suggesting that sulfate reduction was promoted by alternative anaerobic processes. These highly reduced habitats could be fueled by discrete, excess inputs of highly labile natural organic matter from Congo River turbidites or by exhumation of buried sulfide during channel flank erosion and slumping. Sulfidic conditions may be maintained by the mineralization of decomposition products from local benthic macrofauna or bacterial symbionts or by the production of more crystalline Fe(III) oxide phases that are less thermodynamically favorable than sulfate reduction in these bioturbated sediments. Overall, the iron and sulfur biogeochemical cycling in this environment is unique and much more similar to a coastal ecosystem than a deep-sea environment.

Preliminary test results from a free-piston Stirling engine technology demonstration program to support advanced radioisotope space power applications

NASA Astrophysics Data System (ADS)

White, Maurice A.; Qiu, Songgang; Augenblick, Jack E.

2000-01-01

Free-piston Stirling engines offer a relatively mature, proven, long-life technology that is well-suited for advanced, high-efficiency radioisotope space power systems. Contracts from DOE and NASA are being conducted by Stirling Technology Company (STC) for the purpose of demonstrating the Stirling technology in a configuration and power level that is representative of an eventual space power system. The long-term objective is to develop a power system with an efficiency exceeding 20% that can function with a high degree of reliability for up to 15 years on deep space missions. The current technology demonstration convertors (TDC's) are completing shakedown testing and have recently demonstrated performance levels that are virtually identical to projections made during the preliminary design phase. This paper describes preliminary test results for power output, efficiency, and vibration levels. These early results demonstrate the ability of the free-piston Stirling technology to exceed objectives by approximately quadrupling the efficiency of conventional radioisotope thermoelectric generators (RTG's). .

(Nanotechnology Iniatitive) Multicolor Nanostructured High Efficiency Photovoltaic Devices

DTIC Science & Technology

2007-06-30

temperature reaches 520 °C, the surface of strained buffer layer starts to form some nanoholes and nanogrooves. The depth of these nanoholes and...nanogrooves is more than 3 nm. This indicates that the nanoholes and nanogrooves are formed not only just in the top GaAs (5 ML) layer, but also deep...segregated Sb or unstabled GaAsSb at high temperature during the InAs growth. As the InAs growth temperature decreases, the density of the nanoholes and

Combinatorial FSK modulation for power-efficient high-rate communications

NASA Technical Reports Server (NTRS)

Wagner, Paul K.; Budinger, James M.; Vanderaar, Mark J.

1991-01-01

Deep-space and satellite communications systems must be capable of conveying high-rate data accurately with low transmitter power, often through dispersive channels. A class of noncoherent Combinatorial Frequency Shift Keying (CFSK) modulation schemes is investigated which address these needs. The bit error rate performance of this class of modulation formats is analyzed and compared to the more traditional modulation types. Candidate modulator, demodulator, and digital signal processing (DSP) hardware structures are examined in detail. System-level issues are also discussed.

Building on prior knowledge without building it in.

PubMed

Hansen, Steven S; Lampinen, Andrew K; Suri, Gaurav; McClelland, James L

2017-01-01

Lake et al. propose that people rely on "start-up software," "causal models," and "intuitive theories" built using compositional representations to learn new tasks more efficiently than some deep neural network models. We highlight the many drawbacks of a commitment to compositional representations and describe our continuing effort to explore how the ability to build on prior knowledge and to learn new tasks efficiently could arise through learning in deep neural networks.

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.

PubMed

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.

Photosystem II efficiency of the palisade and spongy mesophyll in Quercus coccifera using adaxial/abaxial illumination and excitation light sources with wavelengths varying in penetration into the leaf tissue.

PubMed

Peguero-Pina, José Javier; Gil-Pelegrín, Eustaquio; Morales, Fermín

2009-01-01

The existence of major vertical gradients within the leaf is often overlooked in studies of photosynthesis. These gradients, which involve light heterogeneity, cell composition, and CO(2) concentration across the mesophyll, can generate differences in the maximum potential PSII efficiency (F (V)/F (M) or F (V)/F (P)) of the different cell layers. Evidence is presented for a step gradient of F (V)/F (P) ratios across the mesophyll, from the adaxial (palisade parenchyma, optimal efficiencies) to the abaxial (spongy parenchyma, sub-optimal efficiencies) side of Quercus coccifera leaves. For this purpose, light sources with different wavelengths that penetrate more or less deep within the leaf were employed, and measurements from the adaxial and abaxial sides were performed. To our knowledge, this is the first report where a low photosynthetic performance in the abaxial side of leaves is accompanied by impaired F (V)/F (P) ratios. This low photosynthetic efficiency of the abaxial side could be related to the occurrence of bundle sheath extensions, which facilitates the penetration of high light intensities deep within the mesophyll. Also, leaf morphology (twisted in shape) and orientation (with a marked angle from the horizontal plane) imply direct sunlight illumination of the abaxial side. The existence of cell layers within leaves with different photosynthetic efficiencies makes appropriate the evaluation of how light penetrates within the mesophyll when using Chl fluorescence or gas exchange techniques that use different wavelengths for excitation and/or for driving photosynthesis.

Full open-framework batteries for stationary energy storage

NASA Astrophysics Data System (ADS)

Pasta, Mauro; Wessells, Colin D.; Liu, Nian; Nelson, Johanna; McDowell, Matthew T.; Huggins, Robert A.; Toney, Michael F.; Cui, Yi

2014-01-01

New types of energy storage are needed in conjunction with the deployment of renewable energy sources and their integration with the electrical grid. We have recently introduced a family of cathodes involving the reversible insertion of cations into materials with the Prussian Blue open-framework crystal structure. Here we report a newly developed manganese hexacyanomanganate open-framework anode that has the same crystal structure. By combining it with the previously reported copper hexacyanoferrate cathode we demonstrate a safe, fast, inexpensive, long-cycle life aqueous electrolyte battery, which involves the insertion of sodium ions. This high rate, high efficiency cell shows a 96.7% round trip energy efficiency when cycled at a 5C rate and an 84.2% energy efficiency at a 50C rate. There is no measurable capacity loss after 1,000 deep-discharge cycles. Bulk quantities of the electrode materials can be produced by a room temperature chemical synthesis from earth-abundant precursors.

Full open-framework batteries for stationary energy storage.

PubMed

Pasta, Mauro; Wessells, Colin D; Liu, Nian; Nelson, Johanna; McDowell, Matthew T; Huggins, Robert A; Toney, Michael F; Cui, Yi

2014-01-01

New types of energy storage are needed in conjunction with the deployment of renewable energy sources and their integration with the electrical grid. We have recently introduced a family of cathodes involving the reversible insertion of cations into materials with the Prussian Blue open-framework crystal structure. Here we report a newly developed manganese hexacyanomanganate open-framework anode that has the same crystal structure. By combining it with the previously reported copper hexacyanoferrate cathode we demonstrate a safe, fast, inexpensive, long-cycle life aqueous electrolyte battery, which involves the insertion of sodium ions. This high rate, high efficiency cell shows a 96.7% round trip energy efficiency when cycled at a 5C rate and an 84.2% energy efficiency at a 50C rate. There is no measurable capacity loss after 1,000 deep-discharge cycles. Bulk quantities of the electrode materials can be produced by a room temperature chemical synthesis from earth-abundant precursors.

Polymeric and Molecular Materials for Advanced Organic Electronics

DTIC Science & Technology

2011-07-25

printable variants. All have excellent dielectric and insulating properties, a remarkable ability to minimize trapped charge between thin film transistor... trapped charge density, and hence the corresponding OTFT device performance. Under this program we first discovered that OTFT performance is...deep, high- density charge traps must be overcome for efficient FET operation, it has been postulated that in most OFETs, shallow lower-density (~10

A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices.

PubMed

Ravi, Daniele; Wong, Charence; Lo, Benny; Yang, Guang-Zhong

2017-01-01

The increasing popularity of wearable devices in recent years means that a diverse range of physiological and functional data can now be captured continuously for applications in sports, wellbeing, and healthcare. This wealth of information requires efficient methods of classification and analysis where deep learning is a promising technique for large-scale data analytics. While deep learning has been successful in implementations that utilize high-performance computing platforms, its use on low-power wearable devices is limited by resource constraints. In this paper, we propose a deep learning methodology, which combines features learned from inertial sensor data together with complementary information from a set of shallow features to enable accurate and real-time activity classification. The design of this combined method aims to overcome some of the limitations present in a typical deep learning framework where on-node computation is required. To optimize the proposed method for real-time on-node computation, spectral domain preprocessing is used before the data are passed onto the deep learning framework. The classification accuracy of our proposed deep learning approach is evaluated against state-of-the-art methods using both laboratory and real world activity datasets. Our results show the validity of the approach on different human activity datasets, outperforming other methods, including the two methods used within our combined pipeline. We also demonstrate that the computation times for the proposed method are consistent with the constraints of real-time on-node processing on smartphones and a wearable sensor platform.

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

PubMed

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.

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

PubMed Central

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

2015-01-01

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. PMID:25572661

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

NASA Astrophysics Data System (ADS)

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

2015-01-01

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.

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

PubMed

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.

International Space Station (ISS) Bacterial Filter Elements (BFEs): Filter Efficiency and Pressure Drop Testing of Returned Units

NASA Technical Reports Server (NTRS)

Green, Robert D.; Agui, Juan H.; Vijayakumar, R.; Berger, Gordon M.; Perry, Jay L.

2017-01-01

The air quality control equipment aboard the International Space Station (ISS) and future deep space exploration vehicles provide the vital function of maintaining a clean cabin environment for the crew and the hardware. This becomes a serious challenge in pressurized space compartments since no outside air ventilation is possible, and a larger particulate load is imposed on the filtration system due to lack of sedimentation. The ISS Environmental Control and Life Support (ECLS) system architecture in the U.S. Segment uses a distributed particulate filtration approach consisting of traditional High-Efficiency Particulate Air (HEPA) filters deployed at multiple locations in each U.S. Seg-ment module; these filters are referred to as Bacterial Filter Elements, or BFEs. In our previous work, we presented results of efficiency and pressure drop measurements for a sample set of two returned BFEs with a service life of 2.5 years. In this follow-on work, we present similar efficiency, pressure drop, and leak tests results for a larger sample set of six returned BFEs. The results of this work can aid the ISS Program in managing BFE logistics inventory through the stations planned lifetime as well as provide insight for managing filter element logistics for future exploration missions. These results also can provide meaningful guidance for particulate filter designs under consideration for future deep space exploration missions.

Filter Efficiency and Pressure Testing of Returned ISS Bacterial Filter Elements (BFEs)

NASA Technical Reports Server (NTRS)

Green, Robert D.; Agui, Juan H.; Berger, Gordon M.; Vijayakumar, R.; Perry, Jay L.

2017-01-01

The air quality control equipment aboard the International Space Station (ISS) and future deep space exploration vehicles provide the vital function of maintaining a clean cabin environment for the crew and the hardware. This becomes a serious challenge in pressurized space compartments since no outside air ventilation is possible, and a larger particulate load is imposed on the filtration system due to lack of sedimentation. The ISS Environmental Control and Life Support (ECLS) system architecture in the U.S. Segment uses a distributed particulate filtration approach consisting of traditional High-Efficiency Particulate Air (HEPA) filters deployed at multiple locations in each U.S. Seg-ment module; these filters are referred to as Bacterial Filter Elements, or BFEs. In our previous work, we presented results of efficiency and pressure drop measurements for a sample set of two returned BFEs with a service life of 2.5 years. In this follow-on work, we present similar efficiency, pressure drop, and leak tests results for a larger sample set of six returned BFEs. The results of this work can aid the ISS Program in managing BFE logistics inventory through the stations planned lifetime as well as provide insight for managing filter element logistics for future exploration missions. These results also can provide meaningful guidance for particulate filter designs under consideration for future deep space exploration missions.

Efficient Cleavage of Lignin–Carbohydrate Complexes and Ultrafast Extraction of Lignin Oligomers from Wood Biomass by Microwave‐Assisted Treatment with Deep Eutectic Solvent

PubMed Central

Liu, Yongzhuang; Chen, Wenshuai; Xia, Qinqin; Guo, Bingtuo; Wang, Qingwen; Liu, Shouxin; Liu, Yixing; Li, Jian

2017-01-01

Abstract Lignocellulosic biomass is an abundant and renewable resource for the production of biobased value‐added fuels, chemicals, and materials, but its effective exploitation by an energy‐efficient and environmentally friendly strategy remains a challenge. Herein, a facile approach for efficiently cleaving lignin–carbohydrate complexes and ultrafast fractionation of components from wood by microwave‐assisted treatment with deep eutectic solvent is reported. The solvent was composed of sustainable choline chloride and oxalic acid dihydrate, and showed a hydrogen‐bond acidity of 1.31. Efficient fractionation of lignocellulose with the solvent was realized by heating at 80 °C under 800 W microwave irradiation for 3 min. The extracted lignin showed a low molecular weight of 913, a low polydispersity of 1.25, and consisted of lignin oligomers with high purity (ca. 96 %), and thus shows potential in downstream production of aromatic chemicals. The other dissolved matter mainly comprised glucose, xylose, and hydroxymethylfurfural. The undissolved material was cellulose with crystal I structure and a crystallinity of approximately 75 %, which can be used for fabricating nanocellulose. Therefore, this work promotes an ultrafast lignin‐first biorefinery approach while simultaneously keeping the undissolved cellulose available for further utilization. This work is expected to contribute to improving the economics of overall biorefining of lignocellulosic biomass. PMID:28054749

Focused Crawling of the Deep Web Using Service Class Descriptions

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

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 thesemore » 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.« less

Real-time temperature feedback for nanoparticles based tumor thermal treatment (Conference Presentation)

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Tamir, Gil; Gannot, Israel

2017-02-01

Systemic hyperthermia therapy exploits the fact that cancer cells are more sensitive to elevated temperatures than healthy tissue. Systemic application of hyperthermia externally usually leads to low efficiency treatment. Recently, our group and others have proposed an antibody conjugated magnetic nanoparticles (MNPs) approach to overcome the limitation of systemic hyperthermia. MNPs can bind specifically to the tumor sites, thus delivering internal highly effective targeted hyperthermia. However, such internal mechanism requires more complicated controls and monitoring. This current work presents a deep tissue temperature monitoring method to control hyperthermia effectiveness and minimize collateral damage to surrounding tissues. A low-frequency narrowband modulation of the RF field used for MNP heating leads to the generation of diffused thermal waves which propagate to the tissue surface and captured by a thermal camera. A Fourier domain, analytical heat transfer model is used for temperature monitoring algorithm. The ill-posed thermal inverse problem is solved efficiently by iterating over the source power until both the amplitude and phase match the recorded thermal image sequence. The narrow bandwidth thermal stimulation enables acquiring deep signals with high SNR. We show that thermal transverse resolution improves as the stimulation frequency increases even slightly above DC, enabling better heat source transverse separation and margin identification in the case of distributed tumors. These results can be used as a part of an overall image and treat system for efficient detection of tumors, manipulation of MNPs and monitoring MNP based hyperthermia.

Particle fueling experiments with a series of pellets in LHD

NASA Astrophysics Data System (ADS)

Baldzuhn, J.; Damm, H.; Dinklage, A.; Sakamoto, R.; Motojima, G.; Yasuhara, R.; Ida, K.; Yamada, H.; LHD Experiment Group; Wendelstein 7-X Team

2018-03-01

Ice pellet injection is performed in the heliotron Large Helical Device (LHD). The pellets are injected in short series, with up to eight individual pellets. Parameter variations are performed for the pellet ice isotopes, the LHD magnetic configurations, the heating scenario, and some others. These experiments are performed in order to find out whether deeper fueling can be achieved with a series of pellets compared to single pellets. An increase of the fueling efficiency is expected since pre-cooling of the plasma by the first pellets within a series could aid deeper penetration of later pellets in the same series. In addition, these experiments show which boundary conditions must be fulfilled to optimize the technique. The high-field side injection of pellets, as proposed for deep fueling in a tokamak, will not be feasible with the same efficiency in a stellarator or heliotron because there the magnetic field gradient is smaller than in a tokamak of comparable size. Hence, too shallow pellet fueling, in particular in a large device or a fusion reactor, will be an issue that can be overcome only by extremely high pellet velocities, or other techniques that will have to be developed in the future. It turned out by our investigations that the fueling efficiency can be enhanced by the injection of a series of pellets to some extent. However, further investigations will be needed in order to optimize this approach for deep particle fueling.

Deep South Atlantic carbonate chemistry and increased interocean deep water exchange during last deglaciation

NASA Astrophysics Data System (ADS)

Yu, Jimin; Anderson, Robert F.; Jin, Zhangdong; Menviel, Laurie; Zhang, Fei; Ryerson, Fredrick J.; Rohling, Eelco J.

2014-04-01

Carbon release from the deep ocean at glacial terminations is a critical component of past climate change, but the underlying mechanisms remain poorly understood. We present a 28,000-year high-resolution record of carbonate ion concentration, a key parameter of the global carbon cycle, at 5-km water depth in the South Atlantic. We observe similar carbonate ion concentrations between the Last Glacial Maximum and the late Holocene, despite elevated concentrations in the glacial surface ocean. This strongly supports the importance of respiratory carbon accumulation in a stratified deep ocean for atmospheric CO2 reduction during the last ice age. After ˜9 μmol/kg decline during Heinrich Stadial 1, deep South Atlantic carbonate ion concentration rose by ˜24 μmol/kg from the onset of Bølling to Pre-boreal, likely caused by strengthening North Atlantic Deep Water formation (Bølling) or increased ventilation in the Southern Ocean (Younger Drays) or both (Pre-boreal). The ˜15 μmol/kg decline in deep water carbonate ion since ˜10 ka is consistent with extraction of alkalinity from seawater by deep-sea CaCO3 compensation and coral reef growth on continental shelves during the Holocene. Between 16,600 and 15,000 years ago, deep South Atlantic carbonate ion values converged with those at 3.4-km water depth in the western equatorial Pacific, as did carbon isotope and radiocarbon values. These observations suggest a period of enhanced lateral exchange of carbon between the deep South Atlantic and Pacific Oceans, probably due to an increased transfer of momentum from southern westerlies to the Southern Ocean. By spreading carbon-rich deep Pacific waters around Antarctica for upwelling, invigorated interocean deep water exchange would lead to more efficient CO2 degassing from the Southern Ocean, and thus to an atmospheric CO2 rise, during the early deglaciation.

Silicon solar cell characterization at low temperatures and low illumination as a function of particulate irradiation

NASA Technical Reports Server (NTRS)

Whitaker, A. F.; Little, S. A.; Peacock, C. L., Jr.

1983-01-01

Various configurations of back surface reflector silicon solar cells including small (2 x 2) cm and large (approx. 6 x 6) cm cells with conventional and wraparound contacts were subjected to 1 MeV electron irradiation and characterized under both Earth orbital and deep space conditions of temperatures and illuminations. Current-Voltage (I-V) data were generated from +65 C to -150 C and at incident illuminations from 135.3 mW/sq cm to 5.4 mW/sq cm for these cells. Degradation in cell performance which is manifested only under deep space conditions is emphasized. In addition, the effect of particle irradiation on the high temperature and high intensity and low temperature and low intensity performance of the cells is described. The cells with wraparound contacts were found to have lower efficiencies at Earth orbital conditions than the cells with conventional contacts.

Earth system feedback statistically extracted from the Indian Ocean deep-sea sediments recording Eocene hyperthermals.

PubMed

Yasukawa, Kazutaka; Nakamura, Kentaro; Fujinaga, Koichiro; Ikehara, Minoru; Kato, Yasuhiro

2017-09-12

Multiple transient global warming events occurred during the early Palaeogene. Although these events, called hyperthermals, have been reported from around the globe, geologic records for the Indian Ocean are limited. In addition, the recovery processes from relatively modest hyperthermals are less constrained than those from the severest and well-studied hothouse called the Palaeocene-Eocene Thermal Maximum. In this study, we constructed a new and high-resolution geochemical dataset of deep-sea sediments clearly recording multiple Eocene hyperthermals in the Indian Ocean. We then statistically analysed the high-dimensional data matrix and extracted independent components corresponding to the biogeochemical responses to the hyperthermals. The productivity feedback commonly controls and efficiently sequesters the excess carbon in the recovery phases of the hyperthermals via an enhanced biological pump, regardless of the magnitude of the events. Meanwhile, this negative feedback is independent of nannoplankton assemblage changes generally recognised in relatively large environmental perturbations.

Molecular imaging needles: dual-modality optical coherence tomography and fluorescence imaging of labeled antibodies deep in tissue

PubMed Central

Scolaro, Loretta; Lorenser, Dirk; Madore, Wendy-Julie; Kirk, Rodney W.; Kramer, Anne S.; Yeoh, George C.; Godbout, Nicolas; Sampson, David D.; Boudoux, Caroline; McLaughlin, Robert A.

2015-01-01

Molecular imaging using optical techniques provides insight into disease at the cellular level. In this paper, we report on a novel dual-modality probe capable of performing molecular imaging by combining simultaneous three-dimensional optical coherence tomography (OCT) and two-dimensional fluorescence imaging in a hypodermic needle. The probe, referred to as a molecular imaging (MI) needle, may be inserted tens of millimeters into tissue. The MI needle utilizes double-clad fiber to carry both imaging modalities, and is interfaced to a 1310-nm OCT system and a fluorescence imaging subsystem using an asymmetrical double-clad fiber coupler customized to achieve high fluorescence collection efficiency. We present, to the best of our knowledge, the first dual-modality OCT and fluorescence needle probe with sufficient sensitivity to image fluorescently labeled antibodies. Such probes enable high-resolution molecular imaging deep within tissue. PMID:26137379

Towards the development of continuous, organocatalytic, and stereoselective reactions in deep eutectic solvents

PubMed Central

Brenna, Davide; Massolo, Elisabetta; Puglisi, Alessandra; Rossi, Sergio; Celentano, Giuseppe; Capriati, Vito

2016-01-01

Different deep eutectic solvent (DES) mixtures were studied as reaction media for the continuous synthesis of enantiomerically enriched products by testing different experimental set-ups. L-Proline-catalysed cross-aldol reactions were efficiently performed in continuo, with high yield (99%), anti-stereoselectivity, and enantioselectivity (up to 97% ee). Moreover, using two different DES mixtures, the diastereoselectivity of the process could be tuned, thereby leading to the formation, under different experimental conditions, to both the syn- and the anti-isomer with very high enantioselectivity. The excess of cyclohexanone was recovered and reused, and the reaction could be run and the product isolated without the use of any organic solvent by a proper choice of DES components. The dramatic influence of the reaction media on the reaction rate and stereoselectivity of the process suggests that the intimate architecture of DESs deeply influences the reactivity of different species involved in the catalytic cycle. PMID:28144332

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study

PubMed Central

Hosseinyalamdary, Siavash

2018-01-01

Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy. PMID:29695119

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study.

PubMed

Hosseinyalamdary, Siavash

2018-04-24

Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy.

Electrical characterization and comparison of CIGS solar cells made with different structures and fabrication techniques

DOE PAGES

Garris, Rebekah L.; Johnston, Steven; Li, Jian V.; ...

2017-08-31

In a previous study, we reported on Cu(In,Ga)Se2-based (CIGS) solar cell samples collected from different research laboratories and industrial companies with the purpose of understanding the range of CIGS materials that can lead to high-quality and high-efficiency solar panels. Here, we report on electrical measurements of those same samples. Electron-beam induced current and time-resolved photoluminescence (TRPL) gave insights about the collection probability and the lifetime of carriers generated in each absorber. Capacitance and drive-level capacitance profiling revealed nonuniformity in carrier-density profiles. Admittance spectroscopy revealed small activation energies (= 0.03 eV) indicative of the inversion strength, larger activation energies (> 0.1more » eV) reflective of thermal activation of absorber conductivity and a deeper defect level. Deep-level transient spectroscopy (DLTS) probed deep hole-trapping defects and showed that all samples in this study had a majority-carrier defect with activation energy between 0.3 eV and 0.9 eV. Optical-DLTS revealed deep electron-trapping defects in several of the CIGS samples. This work focused on revealing similarities and differences between high-quality CIGS solar cells made with various structures and fabrication techniques.« less

Electrical characterization and comparison of CIGS solar cells made with different structures and fabrication techniques

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

Garris, Rebekah L.; Johnston, Steven; Li, Jian V.

In a previous study, we reported on Cu(In,Ga)Se2-based (CIGS) solar cell samples collected from different research laboratories and industrial companies with the purpose of understanding the range of CIGS materials that can lead to high-quality and high-efficiency solar panels. Here, we report on electrical measurements of those same samples. Electron-beam induced current and time-resolved photoluminescence (TRPL) gave insights about the collection probability and the lifetime of carriers generated in each absorber. Capacitance and drive-level capacitance profiling revealed nonuniformity in carrier-density profiles. Admittance spectroscopy revealed small activation energies (= 0.03 eV) indicative of the inversion strength, larger activation energies (> 0.1more » eV) reflective of thermal activation of absorber conductivity and a deeper defect level. Deep-level transient spectroscopy (DLTS) probed deep hole-trapping defects and showed that all samples in this study had a majority-carrier defect with activation energy between 0.3 eV and 0.9 eV. Optical-DLTS revealed deep electron-trapping defects in several of the CIGS samples. This work focused on revealing similarities and differences between high-quality CIGS solar cells made with various structures and fabrication techniques.« less

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

PubMed

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.

Retrofitting a 1960s Split-Level, Cold-Climate Home

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

Puttagunta, Srikanth

2015-07-13

National programs such as Home Performance with ENERGY STAR® and numerous other utility air-sealing programs have made homeowners aware of the benefits of energy-efficiency retrofits. Yet these programs tend to focus only on the low-hanging fruit: they recommend air sealing the thermal envelope and ductwork where accessible, switching to efficient lighting and low-flow fixtures, and improving the efficiency of mechanical systems (though insufficient funds or lack of knowledge to implement these improvements commonly prevent the implementation of these higher cost upgrades). At the other end of the spectrum, various utilities across the country are encouraging deep energy retrofit programs. Althoughmore » deep energy retrofits typically seek 50% energy savings, they are often quite costly and are most applicable to gut-rehab projects. A significant potential for lowering energy use in existing homes lies between the lowhanging fruit and deep energy retrofit approaches—retrofits that save approximately 30% in energy compared to the pre-retrofit conditions. The energy-efficiency measures need to be nonintrusive so the retrofit projects can be accomplished in occupied homes.« less

Existing Whole-House Solutions Case Study: Deep Energy Retrofit of 1910 House, Portland, Oregon

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

none,

2011-12-01

This case study lists project information, cost and energy efficiency performance data, energy efficiency measures and lessons learned for a 100-year-old home in Portland, Oregon, audited by Pacific Northwest National Laboratory for a deep energy retrofit. New HVAC and extensive insulation upgrades including rigid XPS and new siding over the old lead painted siding, and EPS on the basement walls and in cathedral ceiling helped bring HERS down to 68.

Fundamental performance differences between CMOS and CCD imagers: Part II

NASA Astrophysics Data System (ADS)

Janesick, James; Andrews, James; Tower, John; Grygon, Mark; Elliott, Tom; Cheng, John; Lesser, Michael; Pinter, Jeff

2007-09-01

A new class of CMOS imagers that compete with scientific CCDs is presented. The sensors are based on deep depletion backside illuminated technology to achieve high near infrared quantum efficiency and low pixel cross-talk. The imagers deliver very low read noise suitable for single photon counting - Fano-noise limited soft x-ray applications. Digital correlated double sampling signal processing necessary to achieve low read noise performance is analyzed and demonstrated for CMOS use. Detailed experimental data products generated by different pixel architectures (notably 3TPPD, 5TPPD and 6TPG designs) are presented including read noise, charge capacity, dynamic range, quantum efficiency, charge collection and transfer efficiency and dark current generation. Radiation damage data taken for the imagers is also reported.

Investigation of Miniaturized Radioisotope Thermionic Power Generation for General Use

NASA Technical Reports Server (NTRS)

Duzik, Adam J.; Choi, Sang H.

2016-01-01

Radioisotope thermoelectric generators (RTGs) running off the radioisotope Pu238 are the current standard in deep space probe power supplies. While reliable, these generators are very inefficient, operating at only approx.7% efficiency. As an alternative, more efficient radioisotope thermionic emission generators (RTIGs) are being explored. Like RTGs, current RTIGs concepts use exotic materials for the emitter, limiting applicability to space and other niche applications. The high demand for long-lasting mobile power sources would be satisfied if RTIGs could be produced inexpensively. This work focuses on exposing several common materials, such as Al, stainless steel, W, Si, and Cu, to elevated temperatures under vacuum to determine the efficiency of each material as inexpensive replacements for thermoelectric materials.

Investigating the Potential of Deep Neural Networks for Large-Scale Classification of Very High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Postadjian, T.; Le Bris, A.; Sahbi, H.; Mallet, C.

2017-05-01

Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification tasks including the automatic analysis of Very High Spatial Resolution (VHR) geospatial images. Most of the recent initiatives have focused on very high discrimination capacity combined with accurate object boundary retrieval. Therefore, current architectures are perfectly tailored for urban areas over restricted areas but not designed for large-scale purposes. This paper presents an end-to-end automatic processing chain, based on DCNNs, that aims at performing large-scale classification of VHR satellite images (here SPOT 6/7). Since this work assesses, through various experiments, the potential of DCNNs for country-scale VHR land-cover map generation, a simple yet effective architecture is proposed, efficiently discriminating the main classes of interest (namely buildings, roads, water, crops, vegetated areas) by exploiting existing VHR land-cover maps for training.

A Poor Relationship Between Sea Level and Deep-Water Sand Delivery

NASA Astrophysics Data System (ADS)

Harris, Ashley D.; Baumgardner, Sarah E.; Sun, Tao; Granjeon, Didier

2018-08-01

The most commonly cited control on delivery of sand to deep water is the rate of relative sea-level fall. The rapid rate of accommodation loss on the shelf causes sedimentation to shift basinward. Field and experimental numerical modeling studies have shown that deep-water sand delivery can occur during any stage of relative sea level position and across a large range of values of rate of relative sea-level change. However, these studies did not investigate the impact of sediment transport efficiency on the relationship between rate of relative sea-level change and deep-water sand delivery rate. We explore this relationship using a deterministic nonlinear diffusion-based numerical stratigraphic forward model. We vary across three orders of magnitude the diffusion coefficient value for marine settings, which controls sediment transport efficiency. We find that the rate of relative sea-level change can explain no more than 1% of the variability in deep-water sand delivery rates, regardless of sediment transport efficiency. Model results show a better correlation with relative sea level, with up to 55% of the variability in deep water sand delivery rates explained. The results presented here are consistent with studies of natural settings which suggest stochastic processes such as avulsion and slope failure, and interactions among such processes, may explain the remaining variance. Relative sea level is a better predictor of deep-water sand delivery than rate of relative sea-level change because it is the sea-level fall itself which promotes sand delivery, not the rate of the fall. We conclude that the poor relationship between sea level and sand delivery is not an artifact of the modeling parameters but is instead due to the inadequacy of relative sea level and the rate of relative sea-level change to fully describe the dimensional space in which depositional systems reside. Subsequently, sea level itself is unable to account for the interaction of multiple processes that contribute to sand delivery to deep water.

Mitigation of stimulated Raman scattering in high power fiber lasers using transmission gratings

NASA Astrophysics Data System (ADS)

Heck, Maximilian; Bock, Victor; Krämer, Ria G.; Richter, Daniel; Goebel, Thorsten A.; Matzdorf, Christian; Liem, Andreas; Schreiber, Thomas; Tünnermann, Andreas; Nolte, Stefan

2018-02-01

The average output power of fiber lasers have been scaled deep into the kW regime within the recent years. However a further scaling is limited due to nonlinear effects like stimulated Raman scattering (SRS). Using the special characteristics of femtosecond laser pulse written transmission fiber gratings, it is possible to realize a notch filter that mitigates efficiently this negative effect by coupling the Raman wavelength from the core into the cladding of the fiber. To the best of our knowledge, we realized for the first time highly efficient gratings in large mode area (LMA) fibers with cladding diameters up to 400 μm. The resonances show strong attenuation at design wavelength and simultaneously low out of band losses. A high power fiber amplifier with an implemented passive fiber grating is shown and its performance is carefully investigated.

Deep-Sea Nematodes Actively Colonise Sediments, Irrespective of the Presence of a Pulse of Organic Matter: Results from an In-Situ Experiment

PubMed Central

Guilini, Katja; Soltwedel, Thomas; van Oevelen, Dick; Vanreusel, Ann

2011-01-01

A colonisation experiment was performed in situ at 2500 m water depth at the Arctic deep-sea long-term observatory HAUSGARTEN to determine the response of deep-sea nematodes to disturbed, newly available patches, enriched with organic matter. Cylindrical tubes,laterally covered with a 500 µm mesh, were filled with azoic deep-sea sediment and 13C-labelled food sources (diatoms and bacteria). After 10 days of incubation the tubes were analysed for nematode response in terms of colonisation and uptake. Nematodes actively colonised the tubes,however with densities that only accounted for a maximum of 2.13% (51 ind.10 cm−2) of the ambient nematode assemblages. Densities did not differ according to the presence or absence of organic matter, nor according to the type of organic matter added. The fact that the organic matter did not function as an attractant to nematodes was confirmed by the absence of notable 13C assimilation by the colonising nematodes. Overall, colonisationappears to be a process that yields reproducible abundance and diversity patterns, with certain taxa showing more efficiency. Together with the high variability between the colonising nematode assemblages, this lends experimental support to the existence of a spatio-temporal mosaic that emerges from highly localised, partially stochastic community dynamics. PMID:21526147

Deep-space and near-Earth optical communications by coded orbital angular momentum (OAM) modulation.

PubMed

Djordjevic, Ivan B

2011-07-18

In order to achieve multi-gigabit transmission (projected for 2020) for the use in interplanetary communications, the usage of large number of time slots in pulse-position modulation (PPM), typically used in deep-space applications, is needed, which imposes stringent requirements on system design and implementation. As an alternative satisfying high-bandwidth demands of future interplanetary communications, while keeping the system cost and power consumption reasonably low, in this paper, we describe the use of orbital angular momentum (OAM) as an additional degree of freedom. The OAM is associated with azimuthal phase of the complex electric field. Because OAM eigenstates are orthogonal the can be used as basis functions for N-dimensional signaling. The OAM modulation and multiplexing can, therefore, be used, in combination with other degrees of freedom, to solve the high-bandwidth requirements of future deep-space and near-Earth optical communications. The main challenge for OAM deep-space communication represents the link between a spacecraft probe and the Earth station because in the presence of atmospheric turbulence the orthogonality between OAM states is no longer preserved. We will show that in combination with LDPC codes, the OAM-based modulation schemes can operate even under strong atmospheric turbulence regime. In addition, the spectral efficiency of proposed scheme is N2/log₂N times better than that of PPM.

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

PubMed

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.

Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory

PubMed Central

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. PMID:25780910

Project CONVERGE: Initial Results From the Mapping of Surface Currents in Palmer Deep

NASA Astrophysics Data System (ADS)

Statscewich, H.; Kohut, J. T.; Winsor, P.; Oliver, M. J.; Bernard, K. S.; Cimino, M. A.; Fraser, W.

2016-02-01

The Palmer Deep submarine canyon on the Western Antarctic Peninsula provides a conduit for upwelling of relatively warm, nutrient rich waters which enhance local primary production and support a food web productive enough to sustain a large top predator biomass. In an analysis of ten years of satellite-tagged penguins, Oliver et al. (2013) showed that circulation features associated with tidal flows may be a key driver of nearshore predator distributions. During diurnal tides, the penguins feed close to their breeding colonies and during semi-diurnal tides, the penguins make foraging trips to the more distant regions of Palmer Deep. It is hypothesized that convergent features act to concentrate primary producers and aggregate schools of krill that influence the behavior of predator species. The initial results from a six month deployment of a High Frequency Radar network in Palmer Deep are presented in an attempt to characterize and quantify convergent features. During a three month period from January through March 2015, we conducted in situ sampling consisting of multiple underwater glider deployments, small boat acoustic surveys of Antarctic krill, and penguin ARGOS-linked satellite telemetry and time-depth recorders (TDRs). The combination of real-time surface current maps with adaptive in situ sampling introduces High Frequency Radar to the Antarctic in a way that allows us to rigorously and efficiently test the influence of local tidal processes on top predator foraging ecology.

An Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer.

PubMed

Saha, Monjoy; Chakraborty, Chandan; Arun, Indu; Ahmed, Rosina; Chatterjee, Sanjoy

2017-06-12

Being a non-histone protein, Ki-67 is one of the essential biomarkers for the immunohistochemical assessment of proliferation rate in breast cancer screening and grading. The Ki-67 signature is always sensitive to radiotherapy and chemotherapy. Due to random morphological, color and intensity variations of cell nuclei (immunopositive and immunonegative), manual/subjective assessment of Ki-67 scoring is error-prone and time-consuming. Hence, several machine learning approaches have been reported; nevertheless, none of them had worked on deep learning based hotspots detection and proliferation scoring. In this article, we suggest an advanced deep learning model for computerized recognition of candidate hotspots and subsequent proliferation rate scoring by quantifying Ki-67 appearance in breast cancer immunohistochemical images. Unlike existing Ki-67 scoring techniques, our methodology uses Gamma mixture model (GMM) with Expectation-Maximization for seed point detection and patch selection and deep learning, comprises with decision layer, for hotspots detection and proliferation scoring. Experimental results provide 93% precision, 0.88% recall and 0.91% F-score value. The model performance has also been compared with the pathologists' manual annotations and recently published articles. In future, the proposed deep learning framework will be highly reliable and beneficial to the junior and senior pathologists for fast and efficient Ki-67 scoring.

Current crowding and self-heating effects in AlGaN-based flip-chip deep-ultraviolet light-emitting diodes

NASA Astrophysics Data System (ADS)

Hao, Guo-Dong; Taniguchi, Manabu; Tamari, Naoki; Inoue, Shin-ichiro

2018-01-01

We thoroughly explored the physical origin of the efficiency decrease with increasing injection current and current crowding effect in 280 nm AlGaN-based flip-chip deep-ultraviolet (DUV) light-emitting diodes (LEDs). The current spreading length was experimentally determined to be much smaller in DUV LEDs than that in conventional InGaN-based visible LEDs. The severe self-heating caused by the low power conversion efficiency of DUV LEDs should be mainly responsible for the considerable decrease of efficiency when current crowding is present. The wall-plug efficiency of the DUV LEDs was markedly enhanced by using a well-designed p-electrode pattern to improve the current distribution.

Tunnel-injected sub 290 nm ultra-violet light emitting diodes with 2.8% external quantum efficiency

NASA Astrophysics Data System (ADS)

Zhang, Yuewei; Jamal-Eddine, Zane; Akyol, Fatih; Bajaj, Sanyam; Johnson, Jared M.; Calderon, Gabriel; Allerman, Andrew A.; Moseley, Michael W.; Armstrong, Andrew M.; Hwang, Jinwoo; Rajan, Siddharth

2018-02-01

We report on the high efficiency tunnel-injected ultraviolet light emitting diodes (UV LEDs) emitting at 287 nm. Deep UV LED performance has been limited by the severe internal light absorption in the p-type contact layers and low electrical injection efficiency due to poor p-type conduction. In this work, a polarization engineered Al0.65Ga0.35N/In0.2Ga0.8N tunnel junction layer is adopted for non-equilibrium hole injection to replace the conventionally used direct p-type contact. A reverse-graded AlGaN contact layer is further introduced to realize a low resistance contact to the top n-AlGaN layer. This led to the demonstration of a low tunnel junction resistance of 1.9 × 10-3 Ω cm2 obtained at 1 kA/cm2. Light emission at 287 nm with an on-wafer peak external quantum efficiency of 2.8% and a wall-plug efficiency of 1.1% was achieved. The measured power density at 1 kA/cm2 was 54.4 W/cm2, confirming the efficient hole injection through interband tunneling. With the benefits of the minimized internal absorption and efficient hole injection, a tunnel-injected UV LED structure could enable future high efficiency UV emitters.

Global patterns of organic carbon export and sequestration in the ocean (Arne Richter Award for Outstanding Young Scientists)

NASA Astrophysics Data System (ADS)

Henson, S.; Sanders, R.; Madsen, E.; Le Moigne, F.; Quartly, G.

2012-04-01

A major term in the global carbon cycle is the ocean's biological carbon pump which is dominated by sinking of small organic particles from the surface ocean to its interior. Here we examine global patterns in particle export efficiency (PEeff), the proportion of primary production that is exported from the surface ocean, and transfer efficiency (Teff), the fraction of exported organic matter that reaches the deep ocean. This is achieved through extrapolating from in situ estimates of particulate organic carbon export to the global scale using satellite-derived data. Global scale estimates derived from satellite data show, in keeping with earlier studies, that PEeff is high at high latitudes and low at low latitudes, but that Teff is low at high latitudes and high at low latitudes. However, in contrast to the relationship observed for deep biomineral fluxes in previous studies, we find that Teff is strongly negatively correlated with opal export flux from the upper ocean, but uncorrelated with calcium carbonate export flux. We hypothesise that the underlying factor governing the spatial patterns observed in Teff is ecosystem function, specifically the degree of recycling occurring in the upper ocean, rather than the availability of calcium carbonate for ballasting. Finally, our estimate of global integrated carbon export is only 50% of previous estimates. The lack of consensus amongst different methodologies on the strength of the biological carbon pump emphasises that our knowledge of a major planetary carbon flux remains incomplete.

Development of high-efficiency solar cells on silicon web

NASA Technical Reports Server (NTRS)

Meier, D. L.

1986-01-01

Achievement of higher efficiency cells by directing efforts toward identifying carrier loss mechanisms; design of cell structures; and development of processing techniques are described. Use of techniques such as deep-level transient spectroscopy (DLTS), laser-beam-induced current (LBIC), and transmission electron microscopy (TEM) indicated that dislocations in web material rather than twin planes were primarily responsible for limiting diffusion lengths in the web. Lifetimes and cell efficiencies can be improved from 19 to 120 microns, and 8 to 10.3% (no AR), respectively, by implanting hydrogen at 1500 eV and a beam current density of 2.0 mA/sq cm. Some of the processing improvements included use of a double-layer AR coating (ZnS and MgF2) and an addition of an aluminum back surface reflectors. Cells of more than 16% efficiency were achieved.

Effects of electrode settings on chlorine generation efficiency of electrolyzing seawater.

PubMed

Hsu, Guoo-Shyng Wang; Hsia, Chih-Wei; Hsu, Shun-Yao

2015-12-01

Electrolyzed water has significant disinfection effects, can comply with food safety regulations, and is environmental friendly. We investigated the effects of immersion depth of electrodes, stirring, electrode size, and electrode gap on the properties and chlorine generation efficiency of electrolyzing seawater and its storage stability. Results indicated that temperature and oxidation-reduction potential (ORP) of the seawater increased gradually, whereas electrical conductivity decreased steadily in electrolysis. During the electrolysis process, pH values and electric currents also decreased slightly within small ranges. Additional stirring or immersing the electrodes deep under the seawater significantly increased current density without affecting its electric efficiency and current efficiency. Decreasing electrode size or increasing electrode gap decreased chlorine production and electric current of the process without affecting its electric efficiency and current efficiency. Less than 35% of chlorine in the electrolyzed seawater was lost in a 3-week storage period. The decrement trend leveled off after the 1 st week of storage. The electrolyzing system is a convenient and economical method for producing high-chlorine seawater, which will have high potential applications in agriculture, aquaculture, or food processing. Copyright © 2015. Published by Elsevier B.V.

Generalising better: Applying deep learning to integrate deleteriousness prediction scores for whole-exome SNV studies.

PubMed

Korvigo, Ilia; Afanasyev, Andrey; Romashchenko, Nikolay; Skoblov, Mikhail

2018-01-01

Many automatic classifiers were introduced to aid inference of phenotypical effects of uncategorised nsSNVs (nonsynonymous Single Nucleotide Variations) in theoretical and medical applications. Lately, several meta-estimators have been proposed that combine different predictors, such as PolyPhen and SIFT, to integrate more information in a single score. Although many advances have been made in feature design and machine learning algorithms used, the shortage of high-quality reference data along with the bias towards intensively studied in vitro models call for improved generalisation ability in order to further increase classification accuracy and handle records with insufficient data. Since a meta-estimator basically combines different scoring systems with highly complicated nonlinear relationships, we investigated how deep learning (supervised and unsupervised), which is particularly efficient at discovering hierarchies of features, can improve classification performance. While it is believed that one should only use deep learning for high-dimensional input spaces and other models (logistic regression, support vector machines, Bayesian classifiers, etc) for simpler inputs, we still believe that the ability of neural networks to discover intricate structure in highly heterogenous datasets can aid a meta-estimator. We compare the performance with various popular predictors, many of which are recommended by the American College of Medical Genetics and Genomics (ACMG), as well as available deep learning-based predictors. Thanks to hardware acceleration we were able to use a computationally expensive genetic algorithm to stochastically optimise hyper-parameters over many generations. Overfitting was hindered by noise injection and dropout, limiting coadaptation of hidden units. Although we stress that this work was not conceived as a tool comparison, but rather an exploration of the possibilities of deep learning application in ensemble scores, our results show that even relatively simple modern neural networks can significantly improve both prediction accuracy and coverage. We provide open-access to our finest model via the web-site: http://score.generesearch.ru/services/badmut/.

Trap Depth Engineering of SrSi2O2N2:Ln2+,Ln3+ (Ln2+ = Yb, Eu; Ln3+ = Dy, Ho, Er) Persistent Luminescence Materials for Information Storage Applications.

PubMed

Zhuang, Yixi; Lv, Ying; Wang, Le; Chen, Wenwei; Zhou, Tian-Liang; Takeda, Takashi; Hirosaki, Naoto; Xie, Rong-Jun

2018-01-17

Deep-trap persistent luminescence materials exhibit unique properties of energy storage and controllable photon release under additional stimulation, allowing for both wavelength and intensity multiplexing to realize high-capacity storage in the next-generation information storage system. However, the lack of suitable persistent luminescence materials with deep traps is the bottleneck of such storage technologies. In this study, we successfully developed a series of novel deep-trap persistent luminescence materials in the Ln 2+ /Ln 3+ -doped SrSi 2 O 2 N 2 system (Ln 2+ = Yb, Eu; Ln 3+ = Dy, Ho, Er) by applying the strategy of trap depth engineering. Interestingly, the trap depth can be tailored by selecting different codopants, and it monotonically increases from 0.90 to 1.18 eV in the order of Er, Ho, and Dy. This is well explained by the energy levels indicated in the host-referred binding energy scheme. The orange-red-emitting SrSi 2 O 2 N 2 :Yb,Dy and green-emitting SrSi 2 O 2 N 2 :Eu,Dy phosphors are demonstrated to be good candidates of information storage materials, which are attributed to their deep traps, narrow thermoluminescence glow bands, high emission efficiency, and excellent chemical stability. This work not only validates the suitability of deep-trap persistent luminescence materials in the information storage applications, but also broadens the avenue to explore such kinds of new materials for applications in anticounterfeiting and advanced displays.

Long term stable deep red light-emitting electrochemical cells based on an emissive, rigid cationic Ir(iii) complex

DOE PAGES

Namanga, Jude E.; Ruhr-Univ. Bochum, Bochum; Gerlitzki, Niels; ...

2017-02-17

Here, the new cationic iridium complex [Ir(bzq) 2(biq)][PF 6] (bzq = benzo[ h]quinolinato and biq = 2,2'-biquinoline) has been synthesized for application as an emitter in light emitting electrochemical cells (LECs). The molecular structure and crystal packing of this complex were established by single X-ray diffraction (SXRD). The electrochemical and photophysical properties of the complex were examined to determine the frontier orbital energies as well as the optical transitions that led to photoemission. The complex was found to emit at 644 nm and 662 nm for powder and thin films, respectively. A high powder photoluminescence quantum yield of 25% wasmore » determined, which is attributed to a reduction in vibrational modes of the complex due to the use of the rigid cyclometalated (C^N) bzq ligand. A LEC with [Ir(bzq) 2(biq)][PF 6] as the emitter was fabricated which showed a deep red emission (662 nm) with a luminance of 33.65 cd m –2, yielding a current efficiency of 0.33 cd A –1 and a power efficiency of 0.2 lm W –1. Most importantly, the LEC based on [Ir(bzq) 2(biq)][PF 6] demonstrated a lifetime of 280 hours which is among the longest device lifetimes reported for any deep red light emitting LEC.« less

Long term stable deep red light-emitting electrochemical cells based on an emissive, rigid cationic Ir(iii) complex

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

Namanga, Jude E.; Ruhr-Univ. Bochum, Bochum; Gerlitzki, Niels

Here, the new cationic iridium complex [Ir(bzq) 2(biq)][PF 6] (bzq = benzo[ h]quinolinato and biq = 2,2'-biquinoline) has been synthesized for application as an emitter in light emitting electrochemical cells (LECs). The molecular structure and crystal packing of this complex were established by single X-ray diffraction (SXRD). The electrochemical and photophysical properties of the complex were examined to determine the frontier orbital energies as well as the optical transitions that led to photoemission. The complex was found to emit at 644 nm and 662 nm for powder and thin films, respectively. A high powder photoluminescence quantum yield of 25% wasmore » determined, which is attributed to a reduction in vibrational modes of the complex due to the use of the rigid cyclometalated (C^N) bzq ligand. A LEC with [Ir(bzq) 2(biq)][PF 6] as the emitter was fabricated which showed a deep red emission (662 nm) with a luminance of 33.65 cd m –2, yielding a current efficiency of 0.33 cd A –1 and a power efficiency of 0.2 lm W –1. Most importantly, the LEC based on [Ir(bzq) 2(biq)][PF 6] demonstrated a lifetime of 280 hours which is among the longest device lifetimes reported for any deep red light emitting LEC.« less

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

NASA Astrophysics Data System (ADS)

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.

Deep Photoacoustic/Luminescence/Magnetic Resonance Multimodal Imaging in Living Subjects Using High-Efficiency Upconversion Nanocomposites.

PubMed

Liu, Yu; Kang, Ning; Lv, Jing; Zhou, Zijian; Zhao, Qingliang; Ma, Lingceng; Chen, Zhong; Ren, Lei; Nie, Liming

2016-08-01

A gadolinium-doped multi-shell upconversion nanoparticle under 800 nm excitation is synthesized with a 10-fold fluorescence-intensity enhancement over that under 980 nm. The nanoformulations exhibit excellent photoacoustic/luminescence/magnetic resonance tri-modal imaging capabilities, enabling visualization of tumor morphology and microvessel distribution at a new imaging depth. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High permeability cores to optimize the stimulation of deeply located brain regions using transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Salvador, R.; Miranda, P. C.; Roth, Y.; Zangen, A.

2009-05-01

Efficient stimulation of deeply located brain regions with transcranial magnetic stimulation (TMS) poses many challenges, arising from the fact that the induced field decays rapidly and becomes less focal with depth. We propose a new method to improve the efficiency of TMS of deep brain regions that combines high permeability cores, to increase focality and field intensity, with a coil specifically designed to induce a field that decays slowly with increasing depth. The performance of the proposed design was investigated using the finite element method to determine the total electric field induced by this coil/core arrangement on a realistically shaped homogeneous head model. The calculations show that the inclusion of the cores increases the field's magnitude by as much as 25% while also decreasing the field's decay with depth along specific directions. The focality, as measured by the area where the field's norm is greater than 1/\\sqrt 2 of its maximum value, is also improved by as much as 15% with some core arrangements. The coil's inductance is not significantly increased by the cores. These results show that the presence of the cores might make this specially designed coil even more suited for the effective stimulation of deep brain regions.

Ferrofluid of magnetic clay and menthol based deep eutectic solvent: Application in directly suspended droplet microextraction for enrichment of some emerging contaminant explosives in water and soil samples.

PubMed

Zarei, Ali Reza; Nedaei, Maryam; Ghorbanian, Sohrab Ali

2018-06-08

In this work, for the first time, ferrofluid of magnetic montmorillonite nanoclay and deep eutectic solvent was prepared and coupled with directly suspended droplet microextraction. Incorporation of ferrofluid in a miniaturized sample preparation technique resulted in achieving high extraction efficiency while developing a green analytical method. The prepared ferrofluid has strong sorbing properties and hydrophobic characteristics. In this method, a micro-droplet of ferrofluid was suspended into the vortex of a stirring aqueous solution and after completing the extraction process, was easily separated from the solution by a magnetic rod without any operational problems. The predominant experimental variables affecting the extraction efficiency of explosives were evaluated. Under optimal conditions, the limits of detection were in the range 0.22-0.91 μg L -1 . The enrichment factors were between 23 and 93 and the relative standard deviations were <10%. The relative recoveries were ranged from 88 to 104%. This method was successfully applied for the extraction and preconcentration of explosives in water and soil samples, followed their determination by high performance liquid chromatography with ultraviolet detection (HPLC-UV). Copyright © 2018 Elsevier B.V. All rights reserved.

Phased Retrofits in Existing Homes in Florida Phase I: Shallow and Deep Retrofits

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

D. Parker; Sutherland, K.; Chasar, D.

2016-02-01

The U.S. Department of Energy (DOE) Building America program, in collaboration with Florida Power and Light (FPL), conducted a phased residential energy-efficiency retrofit program. This research sought to establish impacts on annual energy and peak energy reductions from the technologies applied at two levels of retrofit - shallow and deep, with savings levels approaching the Building America program goals of reducing whole-house energy use by 40%. Under the Phased Deep Retrofit (PDR) project, we have installed phased, energy-efficiency retrofits in a sample of 56 existing, all-electric homes. End-use savings and economic evaluation results from the phased measure packages and singlemore » measures are summarized in this report.« less

A light and faster regional convolutional neural network for object detection in optical remote sensing images

NASA Astrophysics Data System (ADS)

Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

2018-07-01

Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

Field performance of self-siphon sediment cleansing set for sediment removal in deep CSO chamber.

PubMed

Zhou, Yongchao; Zhang, Yiping; Tang, Ping

2013-01-01

This paper presents a study of the self-siphon sediment cleansing set (SSCS), a system designed to remove sediment from the deep combined sewer overflow (CSO) chamber during dry-weather periods. In order to get a better understanding of the sediment removal effectiveness and operational conditions of the SSCS system, we carried out a full-scale field study and comparison analysis on the sediment depth changes in the deep CSO chambers under the conditions with and without the SSCS. The field investigation results demonstrated that the SSCS drains the dry-weather flow that accumulated for 50-57 min from the sewer channel to the intercepting system in about 10 min. It is estimated that the bed shear stress in the CSO chamber and sewer channel is improved almost 25 times on average. The SSCS acts to remove the near bed solids with high pollution load efficiently. Moreover, it cleans up not only the new sediment layer but also part of the previously accumulated sediment.

Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.

A Deep Space Power System Option Based on Synergistic Power Conversion Technologies

NASA Technical Reports Server (NTRS)

Schreiber, Jeffrey G.

2000-01-01

Deep space science missions have typically used radioisotope thermoelectric generator (RTG) power systems. The RTG power system has proven itself to be a rugged and highly reliable power system over many missions, however the thermal-to-electric conversion technology used was approximately 5% efficient. While the relatively low efficiency has some benefits in terms of system integration, there are compelling reasons why a more efficient conversion system should be pursued. The cost savings alone that are available as a result of the reduced isotope inventory are significant. The Advanced Radioisotope Power System (ARPS) project was established to fulfill this goal. Although it was not part of the ARPS project, Stirling conversion technology is being demonstrated with a low level of funding by both NASA and DOE. A power system with Stirling convertors. although intended for use with an isotope heat source. can be combined with other advanced technologies to provide a novel power system for deep space missions. An inflatable primary concentrator would be used in combination with a refractive secondary concentrator (RSC) as the heat source to power the system. The inflatable technology as a structure has made great progress for a variety of potential applications such as communications reflectors, radiators and solar arrays. The RSC has been pursued for use in solar thermal propulsion applications, and it's unique properties allow some advantageous system trades to be made. The power system proposed would completely eliminate the isotope heat source and could potentially provide power for science missions to planets as distant as Uranus. This paper will present the background and developmental status of the technologies and will then describe the power system being proposed.

Aromatically C6- and C9-Substituted Phenanthro[9,10-d]imidazole Blue Fluorophores: Structure-Property Relationship and Electroluminescent Application.

PubMed

Chen, Wen-Cheng; Yuan, Yi; Xiong, Yuan; Rogach, Andrey L; Tong, Qing-Xiao; Lee, Chun-Sing

2017-08-09

In this study, a series of aromatically substituted phenanthro[9,10-d]imidazole (PI) fluorophores at C6 and C9 (no. 6 and 9 carbon atoms) have been synthesized and systematically characterized by theoretical, thermal, photophysical, electrochemical, and electroluminescent (EL) studies. C6 and C9 modifications have positive influences on the thermal properties of the new materials. Theoretical calculations suggest that the C6 and the C9 positions of PI are electronically different. Theoretical and experimental evidences of intramolecular charge transfer (ICT) between two identical moieties attaching to the C6 and the C9 positions are observed. Photophysical properties of the fluorophores are greatly influenced by size and conjugation extent of the substituents as well as linking steric hindrance. It is found that the C6 and C9 positions afford moderate conjugated extension compared to the C2 modification. Moreover, ICT characteristics of the new fluorophores increase as the size of the substituted aromatic group, and are partially influenced by steric hindrance, with the anthracene and the pyrene derivatives having the strongest ICT excited properties. EL performances of the fluorophores were evaluated as host emitters or dopants in organic light-emitting devices (OLEDs). Most of the devices showed significantly improved efficiencies compared to the OLED using the nonmodified emitter. Among all the devices, a 5 wt % TPI-Py doped device exhibited excellent performances with an external quantum efficiency >5% at 1000 cd/m 2 and a deep-blue color index of (0.155, 0.065), which are comparable to the most advanced deep-blue devices. Our study can give useful information for designing C6/C9-modificated PI fluorophores and provide an efficient approach for constructing high-performance deep-blue OLEDs.

Acoustic communications for cabled seafloor observatories

NASA Astrophysics Data System (ADS)

Freitag, L.; Stojanovic, M.

2003-04-01

Cabled seafloor observatories will provide scientists with a continuous presence in both deep and shallow water. In the deep ocean, connecting sensors to seafloor nodes for power and data transfer will require cables and a highly-capable ROV, both of which are potentially expensive. For many applications where very high bandwidth is not required, and where a sensor is already designed to operate on battery power, the use of acoustic links should be considered. Acoustic links are particularly useful for large numbers of low-bandwidth sensors scattered over tens of square kilometers. Sensors used to monitor the chemistry and biology of vent fields are one example. Another important use for acoustic communication is monitoring of AUVs performing pre-programmed or adaptive sampling missions. A high data rate acoustic link with an AUV allows the observer on shore to direct the vehicle in real-time, providing for dynamic event response. Thus both fixed and mobile sensors motivate the development of observatory infrastructure that provides power-efficient, high bandwidth acoustic communication. A proposed system design that can provide the wireless infrastructure, and further examples of its use in networks such as NEPTUNE, are presented.

Cobalt dopant with deep redox potential for organometal halide hybrid solar cells.

PubMed

Koh, Teck Ming; Dharani, Sabba; Li, Hairong; Prabhakar, Rajiv Ramanujam; Mathews, Nripan; Grimsdale, Andrew C; Mhaisalkar, Subodh G

2014-07-01

In this work, we report a new cobalt(III) complex, tris[2-(1H-pyrazol-1-yl)pyrimidine]cobalt(III) tris[bis(trifluoromethylsulfonyl)imide] (MY11), with deep redox potential (1.27 V vs NHE) as dopant for 2,2',7,7'-tetrakis-(N,N-di-p-methoxyphenylamine)-9,9'-spirobifluorene (spiro-OMeTAD). This dopant possesses, to the best of our knowledge, the deepest redox potential among all cobalt-based dopants used in solar cell applications, allowing it to dope a wide range of hole-conductors. We demonstrate the tuning of redox potential of the Co dopant by incorporating pyrimidine moiety in the ligand. We characterize the optical and electrochemical properties of the newly synthesized dopant and show impressive spiro-to-spiro(+) conversion. Lastly, we fabricate high efficiency perovskite-based solar cells using MY11 as dopant for molecular hole-conductor, spiro-OMeTAD, to reveal the impact of this dopant in photovoltaic performance. An overall power conversion efficiency of 12% is achieved using MY11 as p-type dopant to spiro-OMeTAD. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Providing Multi-Page Data Extraction Services with XWRAPComposer

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

Liu, Ling; Zhang, Jianjun; Han, Wei

2008-04-30

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 Deepmore » 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 Deep Web 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.« less

Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

PubMed

Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

2017-10-01

While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

Efficient energy absorption of intense ps-laser pulse into nanowire target

NASA Astrophysics Data System (ADS)

Habara, H.; Honda, S.; Katayama, M.; Sakagami, H.; Nagai, K.; Tanaka, K. A.

2016-06-01

The interaction between ultra-intense laser light and vertically aligned carbon nanotubes is investigated to demonstrate efficient laser-energy absorption in the ps laser-pulse regime. Results indicate a clear enhancement of the energy conversion from laser to energetic electrons and a simultaneously small plasma expansion on the surface of the target. A two-dimensional plasma particle calculation exhibits a high absorption through laser propagation deep into the nanotube array, even for a dense array whose structure is much smaller than the laser wavelength. The propagation leads to the radial expansion of plasma perpendicular to the nanotubes rather than to the front side. These features may contribute to fast ignition in inertial confinement fusion and laser particle acceleration, both of which require high current and small surface plasma simultaneously.

Semiconductor-based narrow-line and high-brilliance 193-nm laser system for industrial applications

NASA Astrophysics Data System (ADS)

Opalevs, D.; Scholz, M.; Stuhler, J.; Gilfert, C.; Liu, L. J.; Wang, X. Y.; Vetter, A.; Kirner, R.; Scharf, T.; Noell, W.; Rockstuhl, C.; Li, R. K.; Chen, C. T.; Voelkel, R.; Leisching, P.

2018-02-01

We present a novel industrial-grade prototype version of a continuous-wave 193 nm laser system entirely based on solid state pump laser technology. Deep-ultraviolet emission is realized by frequency-quadrupling an amplified diode laser and up to 20 mW of optical power were generated using the nonlinear crystal KBBF. We demonstrate the lifetime of the laser system for different output power levels and environmental conditions. The high stability of our setup was proven in > 500 h measurements on a single spot, a crystal shifter multiplies the lifetime to match industrial requirements. This laser improves the relative intensity noise, brilliance, wall-plug efficiency and maintenance cost significantly. We discuss first lithographic experiments making use of this improvement in photon efficiency.

Online, efficient and precision laser profiling of bronze-bonded diamond grinding wheels based on a single-layer deep-cutting intermittent feeding method

NASA Astrophysics Data System (ADS)

Deng, Hui; Chen, Genyu; He, Jie; Zhou, Cong; Du, Han; Wang, Yanyi

2016-06-01

In this study, an online, efficient and precision laser profiling approach that is based on a single-layer deep-cutting intermittent feeding method is described. The effects of the laser cutting depth and the track-overlap ratio of the laser cutting on the efficiency, precision and quality of laser profiling were investigated. Experiments on the online profiling of bronze-bonded diamond grinding wheels were performed using a pulsed fiber laser. The results demonstrate that an increase in the laser cutting depth caused an increase in the material removal efficiency during the laser profiling process. However, the maximum laser profiling efficiency was only achieved when the laser cutting depth was equivalent to the initial surface contour error of the grinding wheel. In addition, the selection of relatively high track-overlap ratios of laser cutting for the profiling of grinding wheels was beneficial with respect to the increase in the precision of laser profiling, whereas the efficiency and quality of the laser profiling were not affected by the change in the track-overlap ratio. After optimized process parameters were employed for online laser profiling, the circular run-out error and the parallelism error of the grinding wheel surface decreased from 83.1 μm and 324.6 μm to 11.3 μm and 3.5 μm, respectively. The surface contour precision of the grinding wheel significantly improved. The highest surface contour precision for grinding wheels of the same type that can be theoretically achieved after laser profiling is completely dependent on the peak power density of the laser. The higher the laser peak power density is, the higher the surface contour precision of the grinding wheel after profiling.

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis

NASA Astrophysics Data System (ADS)

Litjens, Geert; Sánchez, Clara I.; Timofeeva, Nadya; Hermsen, Meyke; Nagtegaal, Iris; Kovacs, Iringo; Hulsbergen-van de Kaa, Christina; Bult, Peter; van Ginneken, Bram; van der Laak, Jeroen

2016-05-01

Pathologists face a substantial increase in workload and complexity of histopathologic cancer diagnosis due to the advent of personalized medicine. Therefore, diagnostic protocols have to focus equally on efficiency and accuracy. In this paper we introduce ‘deep learning’ as a technique to improve the objectivity and efficiency of histopathologic slide analysis. Through two examples, prostate cancer identification in biopsy specimens and breast cancer metastasis detection in sentinel lymph nodes, we show the potential of this new methodology to reduce the workload for pathologists, while at the same time increasing objectivity of diagnoses. We found that all slides containing prostate cancer and micro- and macro-metastases of breast cancer could be identified automatically while 30-40% of the slides containing benign and normal tissue could be excluded without the use of any additional immunohistochemical markers or human intervention. We conclude that ‘deep learning’ holds great promise to improve the efficacy of prostate cancer diagnosis and breast cancer staging.

Gait switches in deep-diving beaked whales: biomechanical strategies for long-duration dives.

PubMed

Martín López, Lucía Martina; Miller, Patrick J O; Aguilar de Soto, Natacha; Johnson, Mark

2015-05-01

Diving animals modulate their swimming gaits to promote locomotor efficiency and so enable longer, more productive dives. Beaked whales perform extremely long and deep foraging dives that probably exceed aerobic capacities for some species. Here, we use biomechanical data from suction-cup tags attached to three species of beaked whales (Mesoplodon densirostris, N=10; Ziphius cavirostris, N=9; and Hyperoodon ampullatus, N=2) to characterize their swimming gaits. In addition to continuous stroking and stroke-and-glide gaits described for other diving mammals, all whales produced occasional fluke-strokes with distinctly larger dorso-ventral acceleration, which we termed 'type-B' strokes. These high-power strokes occurred almost exclusively during deep dive ascents as part of a novel mixed gait. To quantify body rotations and specific acceleration generated during strokes we adapted a kinematic method combining data from two sensors in the tag. Body rotations estimated with high-rate magnetometer data were subtracted from accelerometer data to estimate the resulting surge and heave accelerations. Using this method, we show that stroke duration, rotation angle and acceleration were bi-modal for these species, with B-strokes having 76% of the duration, 52% larger body rotation and four times more surge than normal strokes. The additional acceleration of B-strokes did not lead to faster ascents, but rather enabled brief glides, which may improve the overall efficiency of this gait. Their occurrence towards the end of long dives leads us to propose that B-strokes may recruit fast-twitch fibres that comprise ∼80% of swimming muscles in Blainville's beaked whales, thus prolonging foraging time at depth. © 2015. Published by The Company of Biologists Ltd.

Wet scavenging of soluble gases in DC3 deep convective storms using WRF-Chem simulations and aircraft observations: DEEP CONVECTIVE WET SCAVENGING OF GASES

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

Bela, Megan M.; Barth, Mary C.; Toon, Owen B.

We examine wet scavenging of soluble trace gases in storms observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. We conduct high-resolution simulations with the Weather Research and Forecasting model with Chemistry (WRF-Chem) of a severe storm in Oklahoma. The model represents well the storm location, size, and structure as compared with Next Generation Weather Radar reflectivity, and simulated CO transport is consistent with aircraft observations. Scavenging efficiencies (SEs) between inflow and outflow of soluble species are calculated from aircraft measurements and model simulations. Using a simple wet scavenging scheme, we simulate the SE of each soluble speciesmore » within the error bars of the observations. The simulated SEs of all species except nitric acid (HNO3) are highly sensitive to the values specified for the fractions retained in ice when cloud water freezes. To reproduce the observations, we must assume zero ice retention for formaldehyde (CH2O) and hydrogen peroxide (H2O2) and complete retention for methyl hydrogen peroxide (CH3OOH) and sulfur dioxide (SO2), likely to compensate for the lack of aqueous chemistry in the model. We then compare scavenging efficiencies among storms that formed in Alabama and northeast Colorado and the Oklahoma storm. Significant differences in SEs are seen among storms and species. More scavenging of HNO3 and less removal of CH3OOH are seen in storms with higher maximum flash rates, an indication of more graupel mass. Graupel is associated with mixed-phase scavenging and lightning production of nitrogen oxides (NOx ), processes that may explain the observed differences in HNO3 and CH3OOH scavenging.« less

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Fakharuddin, Azhar; De Rossi, Francesca; Watson, Trystan M.; Schmidt-Mende, Lukas; Jose, Rajan

2016-09-01

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.

Numerical experiments of volcanic dominated rifts and passive margins

NASA Astrophysics Data System (ADS)

Korchinski, Megan; Teyssier, Christian; Rey, Patrice; Whitney, Donna; Mondy, Luke

2017-04-01

Continental rifting is driven by plate tectonic forces (passive rifting), thermal thinning of the lithosphere over a hotspot (active rifting), or a combination of the two. Successful rifts develop into passive margins where pre-drift stretching is accompanied by normal faulting, clastic sedimentation, and various degrees of magmatism. The structure of volcanic passive margins (VPM) differs substantially from margins that are dominated by sedimentation. VPMs are typically narrow, with a lower continental crust that is intruded by magma and can flow as a low-viscosity layer. To investigate the role of the deep crust in the early development of VPMs, we have developed a suite of 2D thermomechanical numerical experiments (Underworld code) in which the density and viscosity of the deep crust and the density of the rift basin fill are systematically varied. Our experiments show that, for a given rifting velocity, the viscosity of the deep crust and the density of the rift basin fill exert primary controls on early VPM development. The viscosity of the deep crust controls the degree to which the shallow crust undergoes localised faulting or distributed thinning. A weak deep crust localises rifting and is efficiently exhumed to the near-surface, whereas a strong deep crust distributes shallow crust extension and remains buried. A high density rift basin fill results in gravitational loading and increased subsidence rate in cases in which the viscosity of the deep crust is sufficiently low to allow that layer to be displaced by the sinking basin fill. At the limit, a low viscosity deep crust overlain by a thick basalt-dominated fill generates a gravitational instability, with a drip of cool basalt that sinks and ponds at the Moho. Experiment results indicate that the deep crust plays a critical role in the dynamic development of volcanic dominated rifts and passive margins. During rifting, the deep continental crust is heated and readily responds to solicitations of the shallow crust (rooting of normal faults, exhumation of the deep crust in normal fault footwalls). Gravitational instabilities caused by high density rift infill similar to those observed in our numerical experiments may be present in the Mesoproterozoic ( 1100 Ma) North American Midcontinent Rift System (MRS). The MRS is a failed rift that is filled with >20 km of dominantly basaltic volcanic deposits, and therefore represents an end member VPM (high density basin fill) where the initial structure of a pre-drift VPM is preserved. Magmatism occurred in two pulses over <15 Ma involving deep mantle melting first (>150 km), then shallow melting (40-70 km). Post-rift subsidence accumulated up to 10 km of clastic sediments in the center of the basin. Evidence of cool, dense rocks sinking into a low-viscosity deep crust as predicted in our numerical experiments may be present in the western arm of the MRS, where crustal density analyses suggest the presence of dense bodies (eclogite) at the base of the crust.

CMOS minimal array

NASA Astrophysics Data System (ADS)

Janesick, James; Cheng, John; Bishop, Jeanne; Andrews, James T.; Tower, John; Walker, Jeff; Grygon, Mark; Elliot, Tom

2006-08-01

A high performance prototype CMOS imager is introduced. Test data is reviewed for different array formats that utilize 3T photo diode, 5T pinned photo diode and 6T photo gate CMOS pixel architectures. The imager allows several readout modes including progressive scan, snap and windowed operation. The new imager is built on different silicon substrates including very high resistivity epitaxial wafers for deep depletion operation. Data products contained in this paper focus on sensor's read noise, charge capacity, charge transfer efficiency, thermal dark current, RTS dark spikes, QE, pixel cross- talk and on-chip analog circuitry performance.

Phase 2 Methyl Iodide Deep-Bed Adsorption Tests

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

Soelberg, Nick; Watson, Tony

2014-09-01

Nuclear fission produces fission products (FPs) and activation products, including iodine-129, which could evolve into used fuel reprocessing facility off-gas systems, and could require off-gas control to limit air emissions to levels within acceptable emission limits. Research, demonstrations, and some reprocessing plant experience have indicated that diatomic iodine can be captured with efficiencies high enough to meet regulatory requirements. Research on the capture of organic iodides has also been performed, but to a lesser extent. Several questions remain open regarding the capture of iodine bound in organic compounds. Deep-bed methyl iodide adsorption testing has progressed according to a multi-laboratory methylmore » iodide adsorption test plan. This report summarizes the second phase of methyl iodide adsorption work performed according to this test plan using the deep-bed iodine adsorption test system at the Idaho National Laboratory (INL), performed during the second half of Fiscal Year (FY) 2014. Test results continue to show that methyl iodide adsorption using AgZ can achieve total iodine decontamination factors (DFs, ratios of uncontrolled and controlled total iodine levels) above 1,000, until breakthrough occurred. However, mass transfer zone depths are deeper for methyl iodide adsorption compared to diatomic iodine (I2) adsorption. Methyl iodide DFs for the Ag Aerogel test adsorption efficiencies were less than 1,000, and the methyl iodide mass transfer zone depth exceeded 8 inches. Additional deep-bed testing and analyses are recommended to (a) expand the data base for methyl iodide adsorption under various conditions specified in the methyl iodide test plan, and (b) provide more data for evaluating organic iodide reactions and reaction byproducts for different potential adsorption conditions.« less

Scaling Deep Learning on GPU and Knights Landing clusters

DOE PAGES

You, Yang; Buluc, Aydin; Demmel, James

2017-09-26

The speed of deep neural networks training has become a big bottleneck of deep learning research and development. For example, training GoogleNet by ImageNet dataset on one Nvidia K20 GPU needs 21 days. To speed up the training process, the current deep learning systems heavily rely on the hardware accelerators. However, these accelerators have limited on-chip memory compared with CPUs. To handle large datasets, they need to fetch data from either CPU memory or remote processors. We use both self-hosted Intel Knights Landing (KNL) clusters and multi-GPU clusters as our target platforms. From an algorithm aspect, current distributed machine learningmore » systems are mainly designed for cloud systems. These methods are asynchronous because of the slow network and high fault-tolerance requirement on cloud systems. We focus on Elastic Averaging SGD (EASGD) to design algorithms for HPC clusters. Original EASGD used round-robin method for communication and updating. The communication is ordered by the machine rank ID, which is inefficient on HPC clusters. First, we redesign four efficient algorithms for HPC systems to improve EASGD's poor scaling on clusters. Async EASGD, Async MEASGD, and Hogwild EASGD are faster \\textcolor{black}{than} their existing counterparts (Async SGD, Async MSGD, and Hogwild SGD, resp.) in all the comparisons. Finally, we design Sync EASGD, which ties for the best performance among all the methods while being deterministic. In addition to the algorithmic improvements, we use some system-algorithm codesign techniques to scale up the algorithms. By reducing the percentage of communication from 87% to 14%, our Sync EASGD achieves 5.3x speedup over original EASGD on the same platform. We get 91.5% weak scaling efficiency on 4253 KNL cores, which is higher than the state-of-the-art implementation.« less

Scaling Deep Learning on GPU and Knights Landing clusters

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

You, Yang; Buluc, Aydin; Demmel, James

The speed of deep neural networks training has become a big bottleneck of deep learning research and development. For example, training GoogleNet by ImageNet dataset on one Nvidia K20 GPU needs 21 days. To speed up the training process, the current deep learning systems heavily rely on the hardware accelerators. However, these accelerators have limited on-chip memory compared with CPUs. To handle large datasets, they need to fetch data from either CPU memory or remote processors. We use both self-hosted Intel Knights Landing (KNL) clusters and multi-GPU clusters as our target platforms. From an algorithm aspect, current distributed machine learningmore » systems are mainly designed for cloud systems. These methods are asynchronous because of the slow network and high fault-tolerance requirement on cloud systems. We focus on Elastic Averaging SGD (EASGD) to design algorithms for HPC clusters. Original EASGD used round-robin method for communication and updating. The communication is ordered by the machine rank ID, which is inefficient on HPC clusters. First, we redesign four efficient algorithms for HPC systems to improve EASGD's poor scaling on clusters. Async EASGD, Async MEASGD, and Hogwild EASGD are faster \\textcolor{black}{than} their existing counterparts (Async SGD, Async MSGD, and Hogwild SGD, resp.) in all the comparisons. Finally, we design Sync EASGD, which ties for the best performance among all the methods while being deterministic. In addition to the algorithmic improvements, we use some system-algorithm codesign techniques to scale up the algorithms. By reducing the percentage of communication from 87% to 14%, our Sync EASGD achieves 5.3x speedup over original EASGD on the same platform. We get 91.5% weak scaling efficiency on 4253 KNL cores, which is higher than the state-of-the-art implementation.« less

Benthic Foraminifera, Food in the Deep Sea, and Limits to Bentho-Pelagic Coupling

NASA Astrophysics Data System (ADS)

Thomas, E.; Boscolo-Galazzo, F.; Arreguin-Rodrigu, G. J.; Ortiz, S.; Alegret, L.

2015-12-01

The deep-sea is the largest habitat on Earth, contains highly diverse biota, but is very little known. Many of its abundant benthic biota (e.g., nematodes) are not preserved in the fossil record. Calcareous and agglutinated benthic foraminifera (unicellular eukaryotes, Rhizaria; efficient dispersers) and ostracodes (Animalia, Crustacea; non-efficient dispersers) are the most common organisms providing a fossil record of deep-sea environments. Very little food is supplied to the deep-sea, because organic matter produced by photosynthesis is largely degraded before it arrives at the seafloor. Only a few % of organic matter is carried to the ocean bottom by 'marine snow', with its particle size and behavior in the water column controlled by surface ecosystem structure, including type of dominant primary producers (diatoms, cyanobacteria). Food supply and its seasonality are generally seen as the dominant control on benthic assemblages (combined with oxygenation), providing bentho-pelagic coupling between primary and benthic productivity. Benthic foraminiferal assemblages (composition and density) thus are used widely to estimate past productivity, especially during episodes of global climate change, ocean acidification, and mass extinction of primary producers. We show that some environmental circumstances may result in interrupting bentho-pelagic coupling, e.g. through lateral supply of organic matter along continental margins (adding more refractory organic matter), through trophic focusing and/or fine particle winnowing on seamounts (giving an advantage to suspension feeders), and through carbonate undersaturation (giving advantage to infaunal over epifaunal calcifyers). In addition, increased remineralization of organic matter combined with increased metabolic rates may cause assemblages to reflect more oligotrophic conditions at stable primary productivity during periods of global warming. As a result, benthic foraminiferal accumulation rates must be carefully evaluated before use as proxies for primary productivity.

In-Home Sleep Recordings in Military Veterans With Posttraumatic Stress Disorder Reveal Less REM and Deep Sleep <1 Hz.

PubMed

Onton, Julie A; Matthews, Scott C; Kang, Dae Y; Coleman, Todd P

2018-01-01

Veterans with posttraumatic stress disorder (PTSD) often report suboptimal sleep quality, often described as lack of restfulness for unknown reasons. These experiences are sometimes difficult to objectively quantify in sleep lab assessments. Here, we used a streamlined sleep assessment tool to record in-home 2-channel electroencephalogram (EEG) with concurrent collection of electrodermal activity (EDA) and acceleration. Data from a single forehead channel were transformed into a whole-night spectrogram, and sleep stages were classified using a fully automated algorithm. For this study, 71 control subjects and 60 military-related PTSD subjects were analyzed for percentage of time spent in Light, Hi Deep (1-3 Hz), Lo Deep (<1 Hz), and rapid eye movement (REM) sleep stages, as well as sleep efficiency and fragmentation. The results showed a significant tendency for PTSD sleepers to spend a smaller percentage of the night in REM ( p < 0.0001) and Lo Deep ( p = 0.001) sleep, while spending a larger percentage of the night in Hi Deep ( p < 0.0001) sleep. The percentage of combined Hi+Lo Deep sleep did not differ between groups. All sleepers usually showed EDA peaks during Lo, but not Hi, Deep sleep; however, PTSD sleepers were more likely to lack EDA peaks altogether, which usually coincided with a lack of Lo Deep sleep. Linear regressions with all subjects showed that a decreased percentage of REM sleep in PTSD sleepers was accounted for by age, prazosin, SSRIs and SNRIs ( p < 0.02), while decreased Lo Deep and increased Hi Deep in the PTSD group could not be accounted for by any factor in this study ( p < 0.005). Linear regression models with only the PTSD group showed that decreased REM correlated with self-reported depression, as measured with the Depression, Anxiety, and Stress Scales (DASS; p < 0.00001). DASS anxiety was associated with increased REM time ( p < 0.0001). This study shows altered sleep patterns in sleepers with PTSD that can be partially accounted for by age and medication use; however, differences in deep sleep related to PTSD could not be linked to any known factor. With several medications [prazosin, selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs); p < 0.03], as well as SSRIs were associated with less sleep efficiency (b = -3.3 ± 0.95; p = 0.0005) and more sleep fragmentation (b = -1.7 ± 0.51; p = 0.0009). Anti-psychotics were associated with less sleep efficiency (b = -4.9 ± 1.4; p = 0.0004). Sleep efficiency was negatively impacted by SSRIs, antipsychotic medications, and depression ( p < 0.008). Increased sleep fragmentation was associated with SSRIs, SNRIs, and anxiety ( p < 0.009), while prazosin and antipsychotic medications correlated with decreased sleep fragmentation ( p < 0.05).

In-Home Sleep Recordings in Military Veterans With Posttraumatic Stress Disorder Reveal Less REM and Deep Sleep <1 Hz

PubMed Central

Onton, Julie A.; Matthews, Scott C.; Kang, Dae Y.; Coleman, Todd P.

2018-01-01

Veterans with posttraumatic stress disorder (PTSD) often report suboptimal sleep quality, often described as lack of restfulness for unknown reasons. These experiences are sometimes difficult to objectively quantify in sleep lab assessments. Here, we used a streamlined sleep assessment tool to record in-home 2-channel electroencephalogram (EEG) with concurrent collection of electrodermal activity (EDA) and acceleration. Data from a single forehead channel were transformed into a whole-night spectrogram, and sleep stages were classified using a fully automated algorithm. For this study, 71 control subjects and 60 military-related PTSD subjects were analyzed for percentage of time spent in Light, Hi Deep (1–3 Hz), Lo Deep (<1 Hz), and rapid eye movement (REM) sleep stages, as well as sleep efficiency and fragmentation. The results showed a significant tendency for PTSD sleepers to spend a smaller percentage of the night in REM (p < 0.0001) and Lo Deep (p = 0.001) sleep, while spending a larger percentage of the night in Hi Deep (p < 0.0001) sleep. The percentage of combined Hi+Lo Deep sleep did not differ between groups. All sleepers usually showed EDA peaks during Lo, but not Hi, Deep sleep; however, PTSD sleepers were more likely to lack EDA peaks altogether, which usually coincided with a lack of Lo Deep sleep. Linear regressions with all subjects showed that a decreased percentage of REM sleep in PTSD sleepers was accounted for by age, prazosin, SSRIs and SNRIs (p < 0.02), while decreased Lo Deep and increased Hi Deep in the PTSD group could not be accounted for by any factor in this study (p < 0.005). Linear regression models with only the PTSD group showed that decreased REM correlated with self-reported depression, as measured with the Depression, Anxiety, and Stress Scales (DASS; p < 0.00001). DASS anxiety was associated with increased REM time (p < 0.0001). This study shows altered sleep patterns in sleepers with PTSD that can be partially accounted for by age and medication use; however, differences in deep sleep related to PTSD could not be linked to any known factor. With several medications [prazosin, selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs); p < 0.03], as well as SSRIs were associated with less sleep efficiency (b = -3.3 ± 0.95; p = 0.0005) and more sleep fragmentation (b = -1.7 ± 0.51; p = 0.0009). Anti-psychotics were associated with less sleep efficiency (b = -4.9 ± 1.4; p = 0.0004). Sleep efficiency was negatively impacted by SSRIs, antipsychotic medications, and depression (p < 0.008). Increased sleep fragmentation was associated with SSRIs, SNRIs, and anxiety (p < 0.009), while prazosin and antipsychotic medications correlated with decreased sleep fragmentation (p < 0.05). PMID:29867419

Maximizing fluorescence collection efficiency in multiphoton microscopy

PubMed Central

Zinter, Joseph P.; Levene, Michael J.

2011-01-01

Understanding fluorescence propagation through a multiphoton microscope is of critical importance in designing high performance systems capable of deep tissue imaging. Optical models of a scattering tissue sample and the Olympus 20X 0.95NA microscope objective were used to simulate fluorescence propagation as a function of imaging depth for physiologically relevant scattering parameters. The spatio-angular distribution of fluorescence at the objective back aperture derived from these simulations was used to design a simple, maximally efficient post-objective fluorescence collection system. Monte Carlo simulations corroborated by data from experimental tissue phantoms demonstrate collection efficiency improvements of 50% – 90% over conventional, non-optimized fluorescence collection geometries at large imaging depths. Imaging performance was verified by imaging layer V neurons in mouse cortex to a depth of 850 μm. PMID:21934897

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

PubMed Central

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. PMID:28222198

Efficient parallelization for AMR MHD multiphysics calculations; implementation in AstroBEAR

NASA Astrophysics Data System (ADS)

Carroll-Nellenback, Jonathan J.; Shroyer, Brandon; Frank, Adam; Ding, Chen

2013-03-01

Current adaptive mesh refinement (AMR) simulations require algorithms that are highly parallelized and manage memory efficiently. As compute engines grow larger, AMR simulations will require algorithms that achieve new levels of efficient parallelization and memory management. We have attempted to employ new techniques to achieve both of these goals. Patch or grid based AMR often employs ghost cells to decouple the hyperbolic advances of each grid on a given refinement level. This decoupling allows each grid to be advanced independently. In AstroBEAR we utilize this independence by threading the grid advances on each level with preference going to the finer level grids. This allows for global load balancing instead of level by level load balancing and allows for greater parallelization across both physical space and AMR level. Threading of level advances can also improve performance by interleaving communication with computation, especially in deep simulations with many levels of refinement. While we see improvements of up to 30% on deep simulations run on a few cores, the speedup is typically more modest (5-20%) for larger scale simulations. To improve memory management we have employed a distributed tree algorithm that requires processors to only store and communicate local sections of the AMR tree structure with neighboring processors. Using this distributed approach we are able to get reasonable scaling efficiency (>80%) out to 12288 cores and up to 8 levels of AMR - independent of the use of threading.

High Power MPD Thruster Development at the NASA Glenn Research Center

NASA Technical Reports Server (NTRS)

LaPointe, Michael R.; Mikellides, Pavlos G.; Reddy, Dhanireddy (Technical Monitor)

2001-01-01

Propulsion requirements for large platform orbit raising, cargo and piloted planetary missions, and robotic deep space exploration have rekindled interest in the development and deployment of high power electromagnetic thrusters. Magnetoplasmadynamic (MPD) thrusters can effectively process megawatts of power over a broad range of specific impulse values to meet these diverse in-space propulsion requirements. As NASA's lead center for electric propulsion, the Glenn Research Center has established an MW-class pulsed thruster test facility and is refurbishing a high-power steady-state facility to design, build, and test efficient gas-fed MPD thrusters. A complimentary numerical modeling effort based on the robust MACH2 code provides a well-balanced program of numerical analysis and experimental validation leading to improved high power MPD thruster performance. This paper reviews the current and planned experimental facilities and numerical modeling capabilities at the Glenn Research Center and outlines program plans for the development of new, efficient high power MPD thrusters.

Efficient generation of mouse models of human diseases via ABE- and BE-mediated base editing.

PubMed

Liu, Zhen; Lu, Zongyang; Yang, Guang; Huang, Shisheng; Li, Guanglei; Feng, Songjie; Liu, Yajing; Li, Jianan; Yu, Wenxia; Zhang, Yu; Chen, Jia; Sun, Qiang; Huang, Xingxu

2018-06-14

A recently developed adenine base editor (ABE) efficiently converts A to G and is potentially useful for clinical applications. However, its precision and efficiency in vivo remains to be addressed. Here we achieve A-to-G conversion in vivo at frequencies up to 100% by microinjection of ABE mRNA together with sgRNAs. We then generate mouse models harboring clinically relevant mutations at Ar and Hoxd13, which recapitulates respective clinical defects. Furthermore, we achieve both C-to-T and A-to-G base editing by using a combination of ABE and SaBE3, thus creating mouse model harboring multiple mutations. We also demonstrate the specificity of ABE by deep sequencing and whole-genome sequencing (WGS). Taken together, ABE is highly efficient and precise in vivo, making it feasible to model and potentially cure relevant genetic diseases.

Optical+Near-IR Bayesian Classification of Quasars

NASA Astrophysics Data System (ADS)

Mehta, Sajjan S.; Richards, G. T.; Myers, A. D.

2011-05-01

We describe the details of an optimal Bayesian classification of quasars with combined optical+near-IR photometry from the SDSS and UKIDSS LAS surveys. Using only deep co-added SDSS photometry from the "Stripe 82" region and requiring full four-band UKIDSS detections, we reliably identify 2665 quasar candidates with a computed efficiency in excess of 99%. Relaxing the data constraints to combinations of two-band detections yields up to 6424 candidates with minimal trade-off in completeness and efficiency. The completeness and efficiency of the sample are investigated with existing spectra from the SDSS, 2SLAQ, and AUS surveys in addition to recent single-slit observations from Palomar Observatory, which revealed 22 quasars from a subsample of 29 high-z candidates. SDSS-III/BOSS observations will allow further exploration of the completeness/efficiency of the sample over 2.2

Recovery of soil unicellular eukaryotes: an efficiency and activity analysis on the single cell level.

PubMed

Lentendu, Guillaume; Hübschmann, Thomas; Müller, Susann; Dunker, Susanne; Buscot, François; Wilhelm, Christian

2013-12-01

Eukaryotic unicellular organisms are an important part of the soil microbial community, but they are often neglected in soil functional microbial diversity analysis, principally due to the absence of specific investigation methods in the special soil environment. In this study we used a method based on high-density centrifugation to specifically isolate intact algal and yeast cells, with the aim to analyze them with flow cytometry and sort them for further molecular analysis such as deep sequencing. Recovery efficiency was tested at low abundance levels that fit those in natural environments (10(4) to 10(6) cells per g soil). Five algae and five yeast morphospecies isolated from soil were used for the testing. Recovery efficiency was between 1.5 to 43.16% and 2 to 30.2%, respectively, and was dependent on soil type for three of the algae. Control treatments without soil showed that the majority of cells were lost due to the method itself (58% and 55.8% respectively). However, the cell extraction technique did not much compromise cell vitality because a fluorescein di-acetate assay indicated high viability percentages (73.3% and 97.2% of cells, respectively). The low abundant algae and yeast morphospecies recovered from soil were cytometrically analyzed and sorted. Following, their DNA was isolated and amplified using specific primers. The developed workflow enables isolation and enrichment of intact autotrophic and heterotrophic soil unicellular eukaryotes from natural environments for subsequent application of deep sequencing technologies. Copyright © 2013 Elsevier B.V. All rights reserved.

Examination of the operator and compensator tank role in urban wastewater treatment using activated sludge method.

PubMed

Mokhtari Azar, Akbar; Ghadirpour Jelogir, Ali; Nabi Bidhendi, Gholam Reza; Zaredar, Narges

2011-04-01

No doubt, operator is one of the main fundaments in wastewater treatment plants. By identifying the inadequacies, the operator could be considered as an important key in treatment plant. Several methods are used for wastewater treatment that requires spending a lot of cost. However, all investments of treatment facilities are usable when the expected efficiency of the treatment plant was obtained. Using experienced operator, this goal is more easily accessible. In this research, the wastewater of an urban community contaminated with moderated, diluted and highly concentrated pollution has been treated using surface and deep aeration treatment method. Sampling of these pilots was performed during winter 2008 to summer 2009. The results indicate that all analyzed parameters were eliminated using activated sludge and surface aeration methods. However, in activated sludge and deep aeration methods in combination with suitable function of operator, more pollutants could be eliminated. Hence, existence of operator in wastewater treatment plants is the basic principle to achieve considered efficiency. Wastewater treatment system is not intelligent itself and that is the operator who can organize even an inefficient system by its continuous presence. The converse of this fact is also real. Despite the various units and appropriate design of wastewater treatment plant, without an operator, the studied process cannot be expected highly efficient. In places frequently affected by the shock of organic and hydraulic loads, the compensator tank is important to offset the wastewater treatment process. Finally, in regard to microbial parameters, existence of disinfection unit is very useful.

Photovoltaic pump systems

NASA Astrophysics Data System (ADS)

Klockgether, J.; Kiessling, K. P.

1983-09-01

Solar pump systems for the irrigation of fields and for water supply in regions with much sunshine are discussed. For surface water and sources with a hoisting depth of 12 m, a system with immersion pumps is used. For deep sources with larger hoisting depths, an underwater motor pump was developed. Both types of pump system meet the requirements of simple installation and manipulation, safe operation, maintenance free, and high efficiency reducing the number of solar cells needed.

An Efficient Strategy of Screening for Pathogens in Wild-Caught Ticks and Mosquitoes by Reusing Small RNA Deep Sequencing Data

PubMed Central

An, Xiaoping; Fan, Hang; Ma, Maijuan; Anderson, Benjamin D.; Jiang, Jiafu; Liu, Wei; Cao, Wuchun; Tong, Yigang

2014-01-01

This paper explored our hypothesis that sRNA (18∼30 bp) deep sequencing technique can be used as an efficient strategy to identify microorganisms other than viruses, such as prokaryotic and eukaryotic pathogens. In the study, the clean reads derived from the sRNA deep sequencing data of wild-caught ticks and mosquitoes were compared against the NCBI nucleotide collection (non-redundant nt database) using Blastn. The blast results were then analyzed with in-house Python scripts. An empirical formula was proposed to identify the putative pathogens. Results showed that not only viruses but also prokaryotic and eukaryotic species of interest can be screened out and were subsequently confirmed with experiments. Specially, a novel Rickettsia spp. was indicated to exist in Haemaphysalis longicornis ticks collected in Beijing. Our study demonstrated the reuse of sRNA deep sequencing data would have the potential to trace the origin of pathogens or discover novel agents of emerging/re-emerging infectious diseases. PMID:24618575

Designed Er(3+)-singly doped NaYF4 with double excitation bands for simultaneous deep macroscopic and microscopic upconverting bioimaging.

PubMed

Wen, Xuanyuan; Wang, Baoju; Wu, Ruitao; Li, Nana; He, Sailing; Zhan, Qiuqiang

2016-06-01

Simultaneous deep macroscopic imaging and microscopic imaging is in urgent demand, but is challenging to achieve experimentally due to the lack of proper fluorescent probes. Herein, we have designed and successfully synthesized simplex Er(3+)-doped upconversion nanoparticles (UCNPs) with double excitation bands for simultaneous deep macroscopic and microscopic imaging. The material structure and the excitation wavelength of Er(3+)-singly doped UCNPs were further optimized to enhance the upconversion emission efficiency. After optimization, we found that NaYF4:30%Er(3+)@NaYF4:2%Er(3+) could simultaneously achieve efficient two-photon excitation (2PE) macroscopic tissue imaging and three-photon excitation (3PE) deep microscopic when excited by 808 nm continuous wave (CW) and 1480 nm CW lasers, respectively. In vitro cell imaging and in vivo imaging have also been implemented to demonstrate the feasibility and potential of the proposed simplex Er(3+)-doped UCNPs as bioprobe.

Optical Spectroscopy of Distant Red Galaxies

NASA Astrophysics Data System (ADS)

Wuyts, Stijn; van Dokkum, Pieter G.; Franx, Marijn; Förster Schreiber, Natascha M.; Illingworth, Garth D.; Labbé, Ivo; Rudnick, Gregory

2009-11-01

We present optical spectroscopic follow-up of a sample of distant red galaxies (DRGs) with K tot s,Vega < 22.5, selected by (J - K)Vega>2.3, in the Hubble Deep Field South (HDFS), the MS 1054-03 field, and the Chandra Deep Field South (CDFS). Spectroscopic redshifts were obtained for 15 DRGs. Only two out of 15 DRGs are located at z < 2, suggesting a high efficiency to select high-redshift sources. From other spectroscopic surveys in the CDFS targeting intermediate to high-redshift populations selected with different criteria, we find spectroscopic redshifts for a further 30 DRGs. We use the sample of spectroscopically confirmed DRGs to establish the high quality (scatter in Δz/(1 + z) of ~0.05) of their photometric redshifts in the considered deep fields, as derived with EAZY. Combining the spectroscopic and photometric redshifts, we find that 74% of DRGs with K tot s,Vega < 22.5 lie at z>2. The combined spectroscopic and photometric sample is used to analyze the distinct intrinsic and observed properties of DRGs at z < 2 and z>2. In our photometric sample to K tot s,Vega < 22.5, low-redshift DRGs are brighter in Ks than high-redshift DRGs by 0.7 mag, and more extincted by 1.2 mag in AV . Our analysis shows that the DRG criterion selects galaxies with different properties at different redshifts. Such biases can be largely avoided by selecting galaxies based on their rest-frame properties, which requires very good multi-band photometry and high quality photometric redshifts.

Sleep and Breathing in High Altitude Pulmonary Edema Susceptible Subjects at 4,559 Meters

PubMed Central

Nussbaumer-Ochsner, Yvonne; Schuepfer, Nicole; Ursprung, Justyna; Siebenmann, Christoph; Maggiorini, Marco; Bloch, Konrad E.

2012-01-01

Study objectives: Susceptible subjects ascending rapidly to high altitude develop pulmonary edema (HAPE). We evaluated whether HAPE leads to sleep and breathing disturbances that are alleviated by dexamethasone. Design: Double-blind, randomized, placebo-controlled trial with open-label extension. Setting: One night in sleep laboratory at 490 m, 2 nights in mountain hut at 4,559 m. Participants: 21 HAPE susceptibles. Intervention: Dexamethasone 2 × 8 mg/d, either 24 h prior to ascent and at 4,559 m (dex-early), or started on day 2 at 4,559 m only (dex-late). Measurements: Polysomnography, questionnaires on sleep and acute mountain sickness. Results: Polysomnographies at 490 m were normal. In dex-late (n = 12) at 4,559 m, night 1 and 3, median oxygen saturation was 71% and 80%, apnea/hypopnea index 91.3/h and 9.6/h. In dex-early (n = 9), corresponding values were 78% and 79%, and 85.3/h and 52.3/h (P < 0.05 vs. 490 m, all instances). In dex-late, ascending from 490 m to 4,559 m (night 1), sleep efficiency decreased from 91% to 65%, slow wave sleep from 20% to 8% (P < 0.05, both instances). In dex-early, corresponding sleep efficiencies were 96% and 95%, slow wave sleep 18% and 9% (P < 0.05). From night 1 to 3, sleep efficiency remained unchanged in both groups while slow wave sleep increased to 20% in dex-late (P < 0.01). Compared to dex-early, initial AMS scores in dex-late were higher but improved during stay at altitude. Conclusions: HAPE susceptibles ascending rapidly to high altitude experience pronounced nocturnal hypoxemia, and reduced sleep efficiency and deep sleep. Dexamethasone taken before ascent prevents severe hypoxemia and sleep disturbances, while dexamethasone taken 24 h after arrival at 4,559 m increases oxygenation and deep sleep. Citation: Nussbaumer-Ochsner Y; Schuepfer N; Ursprung J; Siebenmann C; Maggiorini M; Bloch KE. Sleep and breathing in high altitude pulmonary edema susceptible subjects at 4,559 meters. SLEEP 2012;35(10):1413-1421. PMID:23024440

Nanoparticle-enhanced synergistic HIFU ablation and transarterial chemoembolization for efficient cancer therapy

NASA Astrophysics Data System (ADS)

You, Yufeng; Wang, Zhigang; Ran, Haitao; Zheng, Yuanyi; Wang, Dong; Xu, Jinshun; Wang, Zhibiao; Chen, Yu; Li, Pan

2016-02-01

High-intensity focused ultrasound (HIFU) is being generally explored as a non-invasive therapeutic modality to treat solid tumors. However, the clinical use of HIFU for large and deep tumor-ablation applications such as hepatocellular carcinoma (HCC) is currently entangled with long treatment duration and high operating energy. This critical issue can be potentially resolved by the introduction of HIFU synergistic agents (SAs). Traditional SAs such as microbubbles and microparticles face the problem of large size, short cycle time, damage to mononuclear phagocytic system and unsatisfactory targeting efficiency. In this work, we have developed a facile and versatile nanoparticle-based HIFU synergistic cancer surgery enhanced by transarterial chemoembolization for high-efficiency HCC treatment based on elaborately designed Fe3O4-PFH/PLGA nanocapsules. Multifunctional Fe3O4-PFH/PLGA nanocapsules were administrated into tumor tissues via transarterial injection combined with Lipiodol to achieve high tumor accumulation because transarterial chemoembolization by Lipiodol could block the blood vessels. The high synergistic HIFU ablation effect was successfully achieved against HCC tumors based on the phase-transformation performance of the perfluorohexane (PFH) inner core in the composite nanocapsules, as systematically demonstrated in VX2 liver tumor xenograft in rabbits. Multifunctional Fe3O4-PFH/PLGA nanocapsules were also demonstrated as efficient contrast agents for ultrasound, magnetic resonance and photoacoustic tri-modality imagings, potentially applicable for imaging-guided HIFU synergistic surgery. Therefore, the elaborate integration of traditional transarterial chemoembolization with recently developed nanoparticle-enhanced HIFU cancer surgery could efficiently enhance the HCC cancer treatment outcome, initiating a new and efficient therapeutic protocol/modality for clinic cancer treatment.

Zero-internal fields in nonpolar InGaN/GaN multi-quantum wells grown by the multi-buffer layer technique.

PubMed

Song, Hooyoung; Kim, Jin Soak; Kim, Eun Kyu; Seo, Yong Gon; Hwang, Sung-Min

2010-04-02

The potential of nonpolar a-plane InGaN/GaN multi-quantum wells (MQWs), which are free from a strong piezoelectric field, was demonstrated. An a-GaN template grown on an r-plane sapphire substrate by the multi-buffer layer technique showed high structural quality with an omega full width at half maximum value along the c-axis of 418 arcsec obtained from high-resolution x-ray diffraction analysis. From barrier analysis by deep level transient spectroscopy, it appeared that a-plane InGaN/GaN MQWs can solve the efficiency droop problem as they have a lower electron capture barrier than the c-plane sample. The peak shift of the temperature-dependent photoluminescence signal for the nonpolar InGaN/GaN MQWs was well fitted by Varshni's empirical equation with zero-internal fields. A high photoluminescence efficiency of 0.27 from this sample also showed that nonpolar MQWs can be the key factor to solve the efficiency limitation in conventional c-plane GaN based light emitting diodes.

Flat-plate solar array project process development area process research of non-CZ silicon material

NASA Technical Reports Server (NTRS)

1985-01-01

Three sets of samples were laser processed and then cell processed. The laser processing was carried out on P-type and N-type web at laser power levels from 0.5 joule/sq cm to 2.5 joule/sq cm. Six different liquid dopants were tested (3 phosphorus dopants, 2 boron dopants, 1 aluminum dopant). The laser processed web strips were fabricated into solar cells immediately after laser processing and after various annealing cycles. Spreading resistance measurements made on a number of these samples indicate that the N(+)P (phosphorus doped) junction is approx. 0.2 micrometers deep and suitable for solar cells. However, the P(+)N (or P(+)P) junction is very shallow ( 0.1 micrometers) with a low surface concentration and resulting high resistance. Due to this effect, the fabricated cells are of low efficiency. The maximum efficiency attained was 9.6% on P-type web after a 700 C anneal. The main reason for the low efficiency was a high series resistance in the cell due to a high resistance back contact.

Understanding the complex evolution of rapidly mutating viruses with deep sequencing: Beyond the analysis of viral diversity.

PubMed

Leung, Preston; Eltahla, Auda A; Lloyd, Andrew R; Bull, Rowena A; Luciani, Fabio

2017-07-15

With the advent of affordable deep sequencing technologies, detection of low frequency variants within genetically diverse viral populations can now be achieved with unprecedented depth and efficiency. The high-resolution data provided by next generation sequencing technologies is currently recognised as the gold standard in estimation of viral diversity. In the analysis of rapidly mutating viruses, longitudinal deep sequencing datasets from viral genomes during individual infection episodes, as well as at the epidemiological level during outbreaks, now allow for more sophisticated analyses such as statistical estimates of the impact of complex mutation patterns on the evolution of the viral populations both within and between hosts. These analyses are revealing more accurate descriptions of the evolutionary dynamics that underpin the rapid adaptation of these viruses to the host response, and to drug therapies. This review assesses recent developments in methods and provide informative research examples using deep sequencing data generated from rapidly mutating viruses infecting humans, particularly hepatitis C virus (HCV), human immunodeficiency virus (HIV), Ebola virus and influenza virus, to understand the evolution of viral genomes and to explore the relationship between viral mutations and the host adaptive immune response. Finally, we discuss limitations in current technologies, and future directions that take advantage of publically available large deep sequencing datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

Exploring geo-tagged photos for land cover validation with deep learning

NASA Astrophysics Data System (ADS)

Xing, Hanfa; Meng, Yuan; Wang, Zixuan; Fan, Kaixuan; Hou, Dongyang

2018-07-01

Land cover validation plays an important role in the process of generating and distributing land cover thematic maps, which is usually implemented by high cost of sample interpretation with remotely sensed images or field survey. With an increasing availability of geo-tagged landscape photos, the automatic photo recognition methodologies, e.g., deep learning, can be effectively utilised for land cover applications. However, they have hardly been utilised in validation processes, as challenges remain in sample selection and classification for highly heterogeneous photos. This study proposed an approach to employ geo-tagged photos for land cover validation by using the deep learning technology. The approach first identified photos automatically based on the VGG-16 network. Then, samples for validation were selected and further classified by considering photos distribution and classification probabilities. The implementations were conducted for the validation of the GlobeLand30 land cover product in a heterogeneous area, western California. Experimental results represented promises in land cover validation, given that GlobeLand30 showed an overall accuracy of 83.80% with classified samples, which was close to the validation result of 80.45% based on visual interpretation. Additionally, the performances of deep learning based on ResNet-50 and AlexNet were also quantified, revealing no substantial differences in final validation results. The proposed approach ensures geo-tagged photo quality, and supports the sample classification strategy by considering photo distribution, with accuracy improvement from 72.07% to 79.33% compared with solely considering the single nearest photo. Consequently, the presented approach proves the feasibility of deep learning technology on land cover information identification of geo-tagged photos, and has a great potential to support and improve the efficiency of land cover validation.

Novel Low-Cost, Low-Power Miniature Thermionic Cathode Developed for Microwave/Millimeter Wave Tube and Cathode Ray Tube Applications

NASA Technical Reports Server (NTRS)

Wintucky, Edwin G.

1999-01-01

A low cost, small size and mass, low heater power, durable high-performance barium dispenser thermionic cathode has been developed that offers significant advancements in the design, manufacture, and performance of the electron sources used in vacuum electronic devices--such as microwave (and millimeter wave) traveling-wave tubes (TWT's)--and in display devices such as high-brightness, high-resolution cathode ray tubes (CRT's). The lower cathode heater power and the reduced size and mass of the new cathode are expected to be especially beneficial in TWT's for deep space communications, where future missions are requiring smaller spacecraft, higher data transfer rates (higher frequencies and radiofrequency output power), and greater electrical efficiency. Also expected to benefit are TWT's for commercial and government communication satellites, for both low and geosynchronous Earth orbit, with additional benefits offered by lower cost and potentially higher cathode current loading. A particularly important TWT application is in the microwave power module (MPM), which is a hybrid microwave (or millimeter wave) amplifier consisting of a low-noise solid state driver, a vacuum power booster (small TWT), and an electronic power conditioner integrated into a single compact package. The attributes of compactness and potentially high electrical efficiency make the MPM very attractive for many commercial and government (civilian and defense) applications in communication and radar systems. The MPM is already finding application in defense electronic systems and is under development by NASA for deep space communications. However, for the MPM to become competitive and commercially successful, a major reduction in cost must be achieved.

The DEEP2 Galaxy Redshift Survey: Design, Observations, Data Reduction, and Redshifts

NASA Technical Reports Server (NTRS)

Newman, Jeffrey A.; Cooper, Michael C.; Davis, Marc; Faber, S. M.; Coil, Alison L; Guhathakurta, Puraga; Koo, David C.; Phillips, Andrew C.; Conroy, Charlie; Dutton, Aaron A.;

Efficient energy absorption of intense ps-laser pulse into nanowire target

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

Habara, H.; Honda, S.; Katayama, M.

The interaction between ultra-intense laser light and vertically aligned carbon nanotubes is investigated to demonstrate efficient laser-energy absorption in the ps laser-pulse regime. Results indicate a clear enhancement of the energy conversion from laser to energetic electrons and a simultaneously small plasma expansion on the surface of the target. A two-dimensional plasma particle calculation exhibits a high absorption through laser propagation deep into the nanotube array, even for a dense array whose structure is much smaller than the laser wavelength. The propagation leads to the radial expansion of plasma perpendicular to the nanotubes rather than to the front side. Thesemore » features may contribute to fast ignition in inertial confinement fusion and laser particle acceleration, both of which require high current and small surface plasma simultaneously.« less

An analytical model with flexible accuracy for deep submicron DCVSL cells

NASA Astrophysics Data System (ADS)

Valiollahi, Sepideh; Ardeshir, Gholamreza

2018-07-01

Differential cascoded voltage switch logic (DCVSL) cells are among the best candidates of circuit designers for a wide range of applications due to advantages such as low input capacitance, high switching speed, small area and noise-immunity; nevertheless, a proper model has not yet been developed to analyse them. This paper analyses deep submicron DCVSL cells based on a flexible accuracy-simplicity trade-off including the following key features: (1) the model is capable of producing closed-form expressions with an acceptable accuracy; (2) model equations can be solved numerically to offer higher accuracy; (3) the short-circuit currents occurring in high-low/low-high transitions are accounted in analysis and (4) the changes in the operating modes of transistors during transitions together with an efficient submicron I-V model, which incorporates the most important non-ideal short-channel effects, are considered. The accuracy of the proposed model is validated in IBM 0.13 µm CMOS technology through comparisons with the accurate physically based BSIM3 model. The maximum error caused by analytical solutions is below 10%, while this amount is below 7% for numerical solutions.

49 CFR 575.106 - Tire fuel efficiency consumer information program.

Code of Federal Regulations, 2013 CFR

2013-10-01

... tires, deep tread, winter-type snow tires, space-saver or temporary use spare tires, tires with nominal... deep tread, winter-type snow tires and limited production tires that it manufactures which are exempt... to have included in the database of information available to consumers on NHTSA's Web site. (ii...

49 CFR 575.106 - Tire fuel efficiency consumer information program.

Code of Federal Regulations, 2014 CFR

2014-10-01

... tires, deep tread, winter-type snow tires, space-saver or temporary use spare tires, tires with nominal... deep tread, winter-type snow tires and limited production tires that it manufactures which are exempt... to have included in the database of information available to consumers on NHTSA's Web site. (ii...

49 CFR 575.106 - Tire fuel efficiency consumer information program.

Code of Federal Regulations, 2012 CFR

2012-10-01

... tires, deep tread, winter-type snow tires, space-saver or temporary use spare tires, tires with nominal... deep tread, winter-type snow tires and limited production tires that it manufactures which are exempt... to have included in the database of information available to consumers on NHTSA's Web site. (ii...

A novel near-infrared nanomaterial with high quantum efficiency and its applications in real time in vivo imaging

NASA Astrophysics Data System (ADS)

Cui, X. X.; Fan, Q.; Shi, S. J.; Wen, W. H.; Chen, D. F.; Guo, H. T.; Xu, Y. T.; Gao, F.; Nie, R. Z.; Ford, Harold D.; Tang, Gordon H.; Hou, C. Q.; Peng, B.

2018-05-01

Fluorescence imaging signal is severely limited by the quantum efficiency and emission wavelength. To overcome these challenges, novel NIR-emitting K5NdLi2F10 nanoparticles under NIR excitation was introduced as fluorescence imaging probe for the first time. The photostability of K5NdLi2F10 nanoparticles in the water, phosphate buffer saline, fetal bovine serum and living mice was investigated. The fluorescence signal was detected with depths of 3.5 and 2.0 cm in phantom and pork tissue, respectively. Fluorescence spectrum with a significant signal-to-background ratio of 10:1 was captured in living mice. Moreover, clear NIR images were virtualized for the living mice after intravenous injection. The imaging ability of nanoparticles in tumor-beard mice were evaluated, the enrichment of K5NdLi2F10 nanoparticles in tumor site due to the enhanced permeability and retention effect was confirmed. The systematic studies of toxicity, bio-distribution and in-vivo dynamic imaging suggest that these materials give high biocompatibility and low toxicity. These NIR-emitting nanoparticles with high quantum efficiency, high penetration and low toxicity might facilitate tumor identification in deep tissues more sensitively.

A novel near-infrared nanomaterial with high quantum efficiency and its applications in real time in vivo imaging.

PubMed

Cui, X X; Fan, Q; Shi, S J; Wen, W H; Chen, D F; Guo, H T; Xu, Y T; Gao, F; Nie, R Z; Ford, Harold D; Tang, Gordon H; Hou, C Q; Peng, B

2018-05-18

Fluorescence imaging signal is severely limited by the quantum efficiency and emission wavelength. To overcome these challenges, novel NIR-emitting K 5 NdLi 2 F 10 nanoparticles under NIR excitation was introduced as fluorescence imaging probe for the first time. The photostability of K 5 NdLi 2 F 10 nanoparticles in the water, phosphate buffer saline, fetal bovine serum and living mice was investigated. The fluorescence signal was detected with depths of 3.5 and 2.0 cm in phantom and pork tissue, respectively. Fluorescence spectrum with a significant signal-to-background ratio of 10:1 was captured in living mice. Moreover, clear NIR images were virtualized for the living mice after intravenous injection. The imaging ability of nanoparticles in tumor-beard mice were evaluated, the enrichment of K 5 NdLi 2 F 10 nanoparticles in tumor site due to the enhanced permeability and retention effect was confirmed. The systematic studies of toxicity, bio-distribution and in-vivo dynamic imaging suggest that these materials give high biocompatibility and low toxicity. These NIR-emitting nanoparticles with high quantum efficiency, high penetration and low toxicity might facilitate tumor identification in deep tissues more sensitively.

Design considerations for the beamwaveguide retrofit of a ground antenna station

NASA Technical Reports Server (NTRS)

Veruttipong, T.; Withington, J.; Galindo-Israel, V.; Imbriale, W.; Bathker, D.

1987-01-01

A primary requirement of the NASA Deep Space Network (DSN) is to provide for optimal reception of very low signal levels. This requirement necessitates optimizing the antenna gain to the total system operating noise level quotient. Low overall system noise levels of 16 to 20 K are achieved by using cryogenically cooled preamplifiers closely coupled with an appropriately balanced antenna gain/spillover design. Additionally, high-power transmitters (up to 400 kW CW) are required for spacecraft emergency command and planetary radar experiments. The frequency bands allocated for deep space telemetry are narrow bands near 2.1 and 2.3 GHz (Ka-band), 7.1 and 8.4 GHz (X-band), and 32 and 34.5 GHz (Ka-band). In addition, planned operations for the Search for Extraterrestrial Intelligence (SETI) program require continuous low-noise receive coverage over the 1 to 10 GHz band. To summarize, DSN antennas must operate efficiently with low receive noise and high-power uplink over the 1 to 35 GHz band.

Human-level control through deep reinforcement learning.

PubMed

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.

Human-level control through deep reinforcement learning

NASA Astrophysics Data System (ADS)

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.

Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops.

PubMed

Wasson, A P; Richards, R A; Chatrath, R; Misra, S C; Prasad, S V Sai; Rebetzke, G J; Kirkegaard, J A; Christopher, J; Watt, M

2012-05-01

Wheat yields globally will depend increasingly on good management to conserve rainfall and new varieties that use water efficiently for grain production. Here we propose an approach for developing new varieties to make better use of deep stored water. We focus on water-limited wheat production in the summer-dominant rainfall regions of India and Australia, but the approach is generally applicable to other environments and root-based constraints. Use of stored deep water is valuable because it is more predictable than variable in-season rainfall and can be measured prior to sowing. Further, this moisture is converted into grain with twice the efficiently of in-season rainfall since it is taken up later in crop growth during the grain-filling period when the roots reach deeper layers. We propose that wheat varieties with a deeper root system, a redistribution of branch root density from the surface to depth, and with greater radial hydraulic conductivity at depth would have higher yields in rainfed systems where crops rely on deep water for grain fill. Developing selection systems for mature root system traits is challenging as there are limited high-throughput phenotyping methods for roots in the field, and there is a risk that traits selected in the lab on young plants will not translate into mature root system traits in the field. We give an example of a breeding programme that combines laboratory and field phenotyping with proof of concept evaluation of the trait at the beginning of the selection programme. This would greatly enhance confidence in a high-throughput laboratory or field screen, and avoid investment in screens without yield value. This approach requires careful selection of field sites and years that allow expression of deep roots and increased yield. It also requires careful selection and crossing of germplasm to allow comparison of root expression among genotypes that are similar for other traits, especially flowering time and disease and toxicity resistances. Such a programme with field and laboratory evaluation at the outset will speed up delivery of varieties with improved root systems for higher yield.

Non-restraining EEG Radiotelemetry: Epidural and Deep Intracerebral Stereotaxic EEG Electrode Placement.

PubMed

Papazoglou, Anna; Lundt, Andreas; Wormuth, Carola; Ehninger, Dan; Henseler, Christina; Soós, Julien; Broich, Karl; Weiergräber, Marco

2016-06-25

Implantable EEG radiotelemetry is of central relevance in the neurological characterization of transgenic mouse models of neuropsychiatric and neurodegenerative diseases as well as epilepsies. This powerful technique does not only provide valuable insights into the underlying pathophysiological mechanisms, i.e., the etiopathogenesis of CNS related diseases, it also facilitates the development of new translational, i.e., therapeutic approaches. Whereas competing techniques that make use of recorder systems used in jackets or tethered systems suffer from their unphysiological restraining to semi-restraining character, radiotelemetric EEG recordings overcome these disadvantages. Technically, implantable EEG radiotelemetry allows for precise and highly sensitive measurement of epidural and deep, intracerebral EEGs under various physiological and pathophysiological conditions. First, we present a detailed protocol of a straight forward, successful, quick and efficient technique for epidural (surface) EEG recordings resulting in high-quality electrocorticograms. Second, we demonstrate how to implant deep, intracerebral EEG electrodes, e.g., in the hippocampus (electrohippocampogram). For both approaches, a computerized 3D stereotaxic electrode implantation system is used. The radiofrequency transmitter itself is implanted into a subcutaneous pouch in both mice and rats. Special attention also has to be paid to pre-, peri- and postoperative treatment of the experimental animals. Preoperative preparation of mice and rats, suitable anesthesia as well as postoperative treatment and pain management are described in detail.

ChemTS: an efficient python library for de novo molecular generation.

PubMed

Yang, Xiufeng; Zhang, Jinzhe; Yoshizoe, Kazuki; Terayama, Kei; Tsuda, Koji

2017-01-01

Automatic design of organic materials requires black-box optimization in a vast chemical space. In conventional molecular design algorithms, a molecule is built as a combination of predetermined fragments. Recently, deep neural network models such as variational autoencoders and recurrent neural networks (RNNs) are shown to be effective in de novo design of molecules without any predetermined fragments. This paper presents a novel Python library ChemTS that explores the chemical space by combining Monte Carlo tree search and an RNN. In a benchmarking problem of optimizing the octanol-water partition coefficient and synthesizability, our algorithm showed superior efficiency in finding high-scoring molecules. ChemTS is available at https://github.com/tsudalab/ChemTS.

ChemTS: an efficient python library for de novo molecular generation

NASA Astrophysics Data System (ADS)

Yang, Xiufeng; Zhang, Jinzhe; Yoshizoe, Kazuki; Terayama, Kei; Tsuda, Koji

2017-12-01

Automatic design of organic materials requires black-box optimization in a vast chemical space. In conventional molecular design algorithms, a molecule is built as a combination of predetermined fragments. Recently, deep neural network models such as variational autoencoders and recurrent neural networks (RNNs) are shown to be effective in de novo design of molecules without any predetermined fragments. This paper presents a novel Python library ChemTS that explores the chemical space by combining Monte Carlo tree search and an RNN. In a benchmarking problem of optimizing the octanol-water partition coefficient and synthesizability, our algorithm showed superior efficiency in finding high-scoring molecules. ChemTS is available at https://github.com/tsudalab/ChemTS.

Micro-Welding of Copper Plate by Frequency Doubled Diode Pumped Pulsed Nd:YAG Laser

NASA Astrophysics Data System (ADS)

Nakashiba, Shin-Ichi; Okamoto, Yasuhiro; Sakagawa, Tomokazu; Takai, Sunao; Okada, Akira

A pulsed laser of 532 nm wavelength with ms range pulse duration was newly developed by second harmonic generation of diode pumped pulsed Nd:YAG laser. High electro-optical conversion efficiency more than 13% could be achieved, and 1.5 kW peak power green laser pulse was put in optical fiber of 100 μm in diameter. In micro- welding of 1.0 mm thickness copper plate, a keyhole welding was successfully performed by 1.0 kW peak power at spot diameter less than 200 μm. The frequency doubled pulsed laser improved the processing efficiency of copper welding, and narrow and deep weld bead was stably obtained.

Microwave Frequency Multiplier

NASA Astrophysics Data System (ADS)

Velazco, J. E.

2017-02-01

High-power microwave radiation is used in the Deep Space Network (DSN) and Goldstone Solar System Radar (GSSR) for uplink communications with spacecraft and for monitoring asteroids and space debris, respectively. Intense X-band (7.1 to 8.6 GHz) microwave signals are produced for these applications via klystron and traveling-wave microwave vacuum tubes. In order to achieve higher data rate communications with spacecraft, the DSN is planning to gradually furnish several of its deep space stations with uplink systems that employ Ka-band (34-GHz) radiation. Also, the next generation of planetary radar, such as Ka-Band Objects Observation and Monitoring (KaBOOM), is considering frequencies in the Ka-band range (34 to 36 GHz) in order to achieve higher target resolution. Current commercial Ka-band sources are limited to power levels that range from hundreds of watts up to a kilowatt and, at the high-power end, tend to suffer from poor reliability. In either case, there is a clear need for stable Ka-band sources that can produce kilowatts of power with high reliability. In this article, we present a new concept for high-power, high-frequency generation (including Ka-band) that we refer to as the microwave frequency multiplier (MFM). The MFM is a two-cavity vacuum tube concept where low-frequency (2 to 8 GHz) power is fed into the input cavity to modulate and accelerate an electron beam. In the second cavity, the modulated electron beam excites and amplifies high-power microwaves at a frequency that is a multiple integer of the input cavity's frequency. Frequency multiplication factors in the 4 to 10 range are being considered for the current application, although higher multiplication factors are feasible. This novel beam-wave interaction allows the MFM to produce high-power, high-frequency radiation with high efficiency. A key feature of the MFM is that it uses significantly larger cavities than its klystron counterparts, thus greatly reducing power density and arcing concerns. We present a theoretical analysis for the beam-wave interactions in the MFM's input and output cavities. We show the conditions required for successful frequency multiplication inside the output cavity. Computer simulations using the plasma physics code MAGIC show that 100 kW of Ka-band (32-GHz) output power can be produced using an 80-kW X-band (8-GHz) signal at the MFM's input. The associated MFM efficiency - from beam power to Ka-band power - is 83 percent. Thus, the overall klystron-MFM efficiency is 42 percent - assuming that a klystron with an efficiency of 50 percent delivers the input signal.

On the Hole Injection for III-Nitride Based Deep Ultraviolet Light-Emitting Diodes.

PubMed

Li, Luping; Zhang, Yonghui; Xu, Shu; Bi, Wengang; Zhang, Zi-Hui; Kuo, Hao-Chung

2017-10-24

The hole injection is one of the bottlenecks that strongly hinder the quantum efficiency and the optical power for deep ultraviolet light-emitting diodes (DUV LEDs) with the emission wavelength smaller than 360 nm. The hole injection efficiency for DUV LEDs is co-affected by the p-type ohmic contact, the p-type hole injection layer, the p-type electron blocking layer and the multiple quantum wells. In this report, we review a large diversity of advances that are currently adopted to increase the hole injection efficiency for DUV LEDs. Moreover, by disclosing the underlying device physics, the design strategies that we can follow have also been suggested to improve the hole injection for DUV LEDs.

On the Hole Injection for III-Nitride Based Deep Ultraviolet Light-Emitting Diodes

PubMed Central

Li, Luping; Zhang, Yonghui; Kuo, Hao-Chung

2017-01-01

The hole injection is one of the bottlenecks that strongly hinder the quantum efficiency and the optical power for deep ultraviolet light-emitting diodes (DUV LEDs) with the emission wavelength smaller than 360 nm. The hole injection efficiency for DUV LEDs is co-affected by the p-type ohmic contact, the p-type hole injection layer, the p-type electron blocking layer and the multiple quantum wells. In this report, we review a large diversity of advances that are currently adopted to increase the hole injection efficiency for DUV LEDs. Moreover, by disclosing the underlying device physics, the design strategies that we can follow have also been suggested to improve the hole injection for DUV LEDs. PMID:29073738

Multicolor Nanostructured High Efficiency Photovoltaic Devices

DTIC Science & Technology

2007-06-30

the surface of strained buffer layer starts to form some nanoholes and nanogrooves. The depth of these nanoholes and nanogrooves is more than 3 nm...This indicates that the nanoholes and nanogrooves are formed not only just in the top GaAs (5 ML) layer, but also deep in the strained GaAsSb buffer...temperature during the InAs growth. As the InAs growth temperature decreases, the density of the nanoholes and nanogrooves is significantly reduced

Theoretical evidence of charge transfer interaction between SO₂ and deep eutectic solvents formed by choline chloride and glycerol.

PubMed

Li, Hongping; Chang, Yonghui; Zhu, Wenshuai; Wang, Changwei; Wang, Chao; Yin, Sheng; Zhang, Ming; Li, Huaming

2015-11-21

The nature of the interaction between deep eutectic solvents (DESs), formed by ChCl and glycerol, and SO2 has been systematically investigated using the M06-2X density functional combined with cluster models. Block-localized wave function energy decomposition (BLW-ED) analysis shows that the interaction between SO2 and DESs is dominated by a charge transfer interaction. After this interaction, the SO2 molecule becomes negatively charged, whereas the ChCl-glycerol molecule is positively charged, which is the result of Lewis acid-base interaction. The current result affords a theoretical proof that it is highly useful and efficient to manipulate the Lewis acidity of absorbents for SO2 capture. Moreover, hydrogen bonding as well as electrostatic interactions may also contribute to the stability of the complex. Structure analysis shows that solvent molecules will adjust their geometries to interact with SO2. In addition, the structure of SO2 is barely changed after interaction. The interaction energy between different cluster models and SO2 ranges from -6.8 to -14.4 kcal mol(-1). It is found that the interaction energy is very sensitive to the solvent structure. The moderate interaction between ChCl-glycerol and SO2 is consistent with the concept that highly efficient solvents for SO2 absorption should not only be solvable but also regenerable.

Existing Whole-House Solutions Case Study: Retrofitting a 1960s Split-Level Cold-Climate Home

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

Puttagunta, S.

2015-08-01

National programs such as Home Performance with ENERGY STAR® and numerous other utility air sealing programs have brought awareness to homeowners of the benefits of energy efficiency retrofits. Yet, these programs tend to focus on the low-hanging fruit: air-sealing the thermal envelope and ductwork where accessible, switch to efficient lighting, and low-flow fixtures. At the other end of the spectrum, deep-energy retrofit programs are also being encouraged by various utilities across the country. While deep energy retrofits typically seek 50% energy savings, they are often quite costly and most applicable to gut-rehab projects. A significant potential for lowering energy usagemore » in existing homes lies between the low hanging fruit and deep energy retrofit approaches - retrofits that save approximately 30% in energy over the existing conditions.« less

Enhancing Spatial Resolution of Remotely Sensed Imagery Using Deep Learning

NASA Astrophysics Data System (ADS)

Beck, J. M.; Bridges, S.; Collins, C.; Rushing, J.; Graves, S. J.

2017-12-01

Researchers at the Information Technology and Systems Center at the University of Alabama in Huntsville are using Deep Learning with Convolutional Neural Networks (CNNs) to develop a method for enhancing the spatial resolutions of moderate resolution (10-60m) multispectral satellite imagery. This enhancement will effectively match the resolutions of imagery from multiple sensors to provide increased global temporal-spatial coverage for a variety of Earth science products. Our research is centered on using Deep Learning for automatically generating transformations for increasing the spatial resolution of remotely sensed images with different spatial, spectral, and temporal resolutions. One of the most important steps in using images from multiple sensors is to transform the different image layers into the same spatial resolution, preferably the highest spatial resolution, without compromising the spectral information. Recent advances in Deep Learning have shown that CNNs can be used to effectively and efficiently upscale or enhance the spatial resolution of multispectral images with the use of an auxiliary data source such as a high spatial resolution panchromatic image. In contrast, we are using both the spatial and spectral details inherent in low spatial resolution multispectral images for image enhancement without the use of a panchromatic image. This presentation will discuss how this technology will benefit many Earth Science applications that use remotely sensed images with moderate spatial resolutions.

Integrated Atmosphere Resource Recovery and Environmental Monitoring Technology Demonstration for Deep Space Exploration

NASA Technical Reports Server (NTRS)

Perry, Jay L.; Abney, Morgan B.; Knox, James C.; Parrish, Keith J.; Roman, Monserrate C.; Jan, Darrell L.

2012-01-01

Exploring the frontiers of deep space continues to be defined by the technological challenges presented by safely transporting a crew to and from destinations of scientific interest. Living and working on that frontier requires highly reliable and efficient life support systems that employ robust, proven process technologies. The International Space Station (ISS), including its environmental control and life support (ECLS) system, is the platform from which humanity's deep space exploration missions begin. The ISS ECLS system Atmosphere Revitalization (AR) subsystem and environmental monitoring (EM) technical architecture aboard the ISS is evaluated as the starting basis for a developmental effort being conducted by the National Aeronautics and Space Administration (NASA) via the Advanced Exploration Systems (AES) Atmosphere Resource Recovery and Environmental Monitoring (ARREM) Project.. An evolutionary approach is employed by the ARREM project to address the strengths and weaknesses of the ISS AR subsystem and EM equipment, core technologies, and operational approaches to reduce developmental risk, improve functional reliability, and lower lifecycle costs of an ISS-derived subsystem architecture suitable for use for crewed deep space exploration missions. The most promising technical approaches to an ISS-derived subsystem design architecture that incorporates promising core process technology upgrades will be matured through a series of integrated tests and architectural trade studies encompassing expected exploration mission requirements and constraints.

Inverse effects of Polyacrylamide (PAM) usage in furrow irrigation on advance time and deep percolation.

PubMed

Meral, Ramazan; Cemek, Bilal; Apan, Mehmet; Merdun, Hasan

2006-10-01

The positive effects of Polyacrylamide (PAM), which is used as a soil conditioner in furrow irrigation, on sediment transport, erosion, and infiltration have been investigated intensively in recent years. However, the effects of PAM have not been considered enough in irrigation system planning and design. As a result of increased infiltration because of PAM, advance time may be inversely affected and deep percolation increases. However, advance time in furrow irrigation is a crucial parameter in order to get high application efficiency. In this study, inverse effects of PAM were discussed, and as an alternative solution, the applicability of surge flow was investigated. PAM application significantly increased the advance time at the rates of 41.3-56.3% in the first irrigation. The application of surge flow with PAM removed this negative effect on advance time, where there was no statistically significant difference according to normal continuous flow (without PAM). PAM applications significantly increased the deep percolation, 80.3-117.1%. Surge flow with PAM had significantly positive effect on the deep percolation compared to continuous flow with PAM but not compared to normal continuous flow. These results suggested that irrigation planning should me made based on the new soil and flow conditions because of PAM usage, and surge flow can be a solution to these problems.

De Novo Deep Transcriptome Analysis of Medicinal Plants for Gene Discovery in Biosynthesis of Plant Natural Products.

PubMed

Han, R; Rai, A; Nakamura, M; Suzuki, H; Takahashi, H; Yamazaki, M; Saito, K

2016-01-01

Study on transcriptome, the entire pool of transcripts in an organism or single cells at certain physiological or pathological stage, is indispensable in unraveling the connection and regulation between DNA and protein. Before the advent of deep sequencing, microarray was the main approach to handle transcripts. Despite obvious shortcomings, including limited dynamic range and difficulties to compare the results from distinct experiments, microarray was widely applied. During the past decade, next-generation sequencing (NGS) has revolutionized our understanding of genomics in a fast, high-throughput, cost-effective, and tractable manner. By adopting NGS, efficiency and fruitful outcomes concerning the efforts to elucidate genes responsible for producing active compounds in medicinal plants were profoundly enhanced. The whole process involves steps, from the plant material sampling, to cDNA library preparation, to deep sequencing, and then bioinformatics takes over to assemble enormous-yet fragmentary-data from which to comb and extract information. The unprecedentedly rapid development of such technologies provides so many choices to facilitate the task, which can cause confusion when choosing the suitable methodology for specific purposes. Here, we review the general approaches for deep transcriptome analysis and then focus on their application in discovering biosynthetic pathways of medicinal plants that produce important secondary metabolites. © 2016 Elsevier Inc. All rights reserved.

Deep convolutional neural network for classifying Fusarium wilt of radish from unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Ha, Jin Gwan; Moon, Hyeonjoon; Kwak, Jin Tae; Hassan, Syed Ibrahim; Dang, Minh; Lee, O. New; Park, Han Yong

2017-10-01

Recently, unmanned aerial vehicles (UAVs) have gained much attention. In particular, there is a growing interest in utilizing UAVs for agricultural applications such as crop monitoring and management. We propose a computerized system that is capable of detecting Fusarium wilt of radish with high accuracy. The system adopts computer vision and machine learning techniques, including deep learning, to process the images captured by UAVs at low altitudes and to identify the infected radish. The whole radish field is first segmented into three distinctive regions (radish, bare ground, and mulching film) via a softmax classifier and K-means clustering. Then, the identified radish regions are further classified into healthy radish and Fusarium wilt of radish using a deep convolutional neural network (CNN). In identifying radish, bare ground, and mulching film from a radish field, we achieved an accuracy of ≥97.4%. In detecting Fusarium wilt of radish, the CNN obtained an accuracy of 93.3%. It also outperformed the standard machine learning algorithm, obtaining 82.9% accuracy. Therefore, UAVs equipped with computational techniques are promising tools for improving the quality and efficiency of agriculture today.

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

NASA Astrophysics Data System (ADS)

Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

2017-05-01

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

Preparation of Deep Sea Fish Oil-Based Nanostructured Lipid Carriers with Enhanced Cellular Uptake.

PubMed

Zhu, Qiu-Yun; Guissi, Fida; Yang, Ru-Ya; Wang, Qian; Wang, Ke; Chen, Dan; Han, Zhi-Hao; Ma, Yi; Zhang, Min; Gu, Yue-Qing

2015-12-01

Nanostructured lipid carriers (NLC) are a promising pharmaceutical delivery system with mean diameter less than 200 nm which are dispersed in an aqueous phase containing emulsifier(s), to increase the water solubility, stability and bioavailability of oil compounds. Herein we prepared a promising NLC with glyceryl monostearate (GMS) as the solid lipid template and deep sea fish oil as the liquid lipid template using melted-ultrasonic method. Fish oil-NLC had a mean size of 84.7 ± 2.6 nm and a zeta potential that ranged from -17.87 mV to -32.91 mV. The nanoparticles exhibited good stability for four weeks with a high encapsulation efficiency of 87.5 ± 5.2%. Afterwards, confocal laser scanning microscopy (CLSM) and flow cytometry (FCM) were used to investigate the contribution of Fish oil-NLC in enhancing fluorescein isothiocyanate (FITC) cellular uptake in comparison with free FITC. The results of this study indicated the possibility of this carrier to overcome the shortcomings of deep sea fish oil and to provide a novel bifunctional carrier with nutritional potential and drug delivery ability.

The impact on atmospheric CO2 of iron fertilization induced changes in the ocean's biological pump

NASA Astrophysics Data System (ADS)

Jin, X.; Gruber, N.; Frenzel, H.; Doney, S. C.; McWilliams, J. C.

2007-10-01

Using numerical simulations, we quantify the impact of changes in the ocean's biological pump on the air-sea balance of CO2 by fertilizing a small surface patch in the high-nutrient, low-chlorophyll region of the eastern tropical Pacific with iron. Decade-long fertilization experiments are conducted in a basin-scale, eddy-permitting coupled physical biogeochemical ecological model. In contrast to previous studies, we find that most of the dissolved inorganic carbon (DIC) removed from the euphotic zone by the enhanced biological export is replaced by uptake of CO2 from the atmosphere. Atmospheric uptake efficiencies, the ratio of the perturbation in air-sea CO2 flux to the perturbation in export flux across 100 m, are 0.75 to 0.93 in our patch size-scale experiments. The atmospheric uptake efficiency is insensitive to the duration of the experiment. The primary factor controlling the atmospheric uptake efficiency is the vertical distribution of the enhanced biological production. Iron fertilization at the surface tends to induce production anomalies primarily near the surface, leading to high efficiencies. In contrast, mechanisms that induce deep production anomalies (e.g. altered light availability) tend to have a low uptake efficiency, since most of the removed DIC is replaced by lateral and vertical transport and mixing. Despite high atmospheric uptake efficiencies, patch-scale iron fertilization of the ocean's biological pump tends to remove little CO2 from the atmosphere over the decadal timescale considered here.

The impact on atmospheric CO2 of iron fertilization induced changes in the ocean's biological pump

NASA Astrophysics Data System (ADS)

Jin, X.; Gruber, N.; Frenzel, H.; Doney, S. C.; McWilliams, J. C.

2008-03-01

Using numerical simulations, we quantify the impact of changes in the ocean's biological pump on the air-sea balance of CO2 by fertilizing a small surface patch in the high-nutrient, low-chlorophyll region of the eastern tropical Pacific with iron. Decade-long fertilization experiments are conducted in a basin-scale, eddy-permitting coupled physical/biogeochemical/ecological model. In contrast to previous studies, we find that most of the dissolved inorganic carbon (DIC) removed from the euphotic zone by the enhanced biological export is replaced by uptake of CO2 from the atmosphere. Atmospheric uptake efficiencies, the ratio of the perturbation in air-sea CO2 flux to the perturbation in export flux across 100 m, integrated over 10 years, are 0.75 to 0.93 in our patch size-scale experiments. The atmospheric uptake efficiency is insensitive to the duration of the experiment. The primary factor controlling the atmospheric uptake efficiency is the vertical distribution of the enhanced biological production and export. Iron fertilization at the surface tends to induce production anomalies primarily near the surface, leading to high efficiencies. In contrast, mechanisms that induce deep production anomalies (e.g. altered light availability) tend to have a low uptake efficiency, since most of the removed DIC is replaced by lateral and vertical transport and mixing. Despite high atmospheric uptake efficiencies, patch-scale iron fertilization of the ocean's biological pump tends to remove little CO2 from the atmosphere over the decadal timescale considered here.

Survey of Constellation-Era LOX/Methane Development Activities and Future Development Needs

NASA Technical Reports Server (NTRS)

Marshall, William M.; Stiegemeier, Benjamin; Greene, Sandra Elam; Hurlbert, Eric A.

2017-01-01

NASA formed the Constellation Program in 2005 to achieve the objectives of maintaining American presence in low-Earth orbit, returning to the moon for purposes of establishing an outpost, and laying the foundation to explore Mars and beyond in the first half of the 21st century. The Exploration Technology Development Program (ETDP) was formulated to address the technology needs to address Constellation architecture decisions. The Propellants and Cryogenic Advanced Development (PCAD) project was tasked with risk mitigation of specific propulsion related technologies to support ETDP. Propulsion systems were identified as critical technologies owing to the high gear-ratio of lunar Mars landers Cryogenic propellants offer performance advantage over storables (NTOMMH) Mass savings translate to greater payload capacity In-situ production of propellant an attractive feature; methane and oxygen identified as possible Martian in-situ propellants New technologies were required to meet more difficult missions High performance LOX/LH2 deep throttle descent engines High performance LOX/LCH4 ascent main and reaction control system (RCS) engines The PCAD project sought to provide those technologies through Reliable ignition pulse RCS Fast start High efficiency engines Stable deep throttling.

Highly Efficient Spectrally Stable Red Perovskite Light-Emitting Diodes.

PubMed

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.

Self-learning Monte Carlo with deep neural networks

NASA Astrophysics Data System (ADS)

Shen, Huitao; Liu, Junwei; Fu, Liang

2018-05-01

The self-learning Monte Carlo (SLMC) method is a general algorithm to speedup MC simulations. Its efficiency has been demonstrated in various systems by introducing an effective model to propose global moves in the configuration space. In this paper, we show that deep neural networks can be naturally incorporated into SLMC, and without any prior knowledge can learn the original model accurately and efficiently. Demonstrated in quantum impurity models, we reduce the complexity for a local update from O (β2) in Hirsch-Fye algorithm to O (β lnβ ) , which is a significant speedup especially for systems at low temperatures.

Underground Coal Gasification Research Program near Hanna, Carbon County, Wyoming: Environmental impact assessment

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

Not Available

In the fall of 1972, the Laramie Energy Research Center initiated an in situ coal gasification experiment in Hanna, Wyoming. The objective was to test the feasibility of underground gasification in a deep, thick seam of western subbituminous coal and, if feasible, to maximize gas heating value while sustaining stable gas production rates and achieving a high coal utilization efficiency. The coal seam was ignited on March 28, 1973, in a 30-foot seam 400 feet deep. The ''burn'' was maintained for a year, until March 22, 1974, when air injection was stopped. The combustion zone was extinguished by the naturalmore » influx of seam water in approximately three months. This report discusses the environmental inpacts of this program on the area and provides details of the program. 13 refs., 7 figs., 11 tabs.« less

I-V-T analysis of radiation damage in high efficiency Si solar cells

NASA Technical Reports Server (NTRS)

Banerjee, S.; Anderson, W. A.; Rao, B. B.

1985-01-01

A detailed analysis of current-voltage characteristics of N(+)-P/P solar cells indicate that there is a combination of different mechanisms which results in an enhancement in the dark current and in turn deteriorates the photovoltaic performance of the solar cells after 1 MeV e(-) irradiation. The increase in the dark current is due to three effects, i.e., bulk recombination, space charge recombination by deep traps and space charge recombination through shallow traps. It is shown that the increase in bulk recombination current is about 2 to 3 orders of magnitude whereas space charge recombination current due to shallow traps increases only by an order or so and no space charge recombination through deep traps was observed after irradiation. Thus, in order to improve the radiation hardness of these devices, bulk properties should be preserved.

Analysis of Variability in HIV-1 Subtype A Strains in Russia Suggests a Combination of Deep Sequencing and Multitarget RNA Interference for Silencing of the Virus.

PubMed

Kretova, Olga V; Chechetkin, Vladimir R; Fedoseeva, Daria M; Kravatsky, Yuri V; Sosin, Dmitri V; Alembekov, Ildar R; Gorbacheva, Maria A; Gashnikova, Natalya M; Tchurikov, Nickolai A

2017-02-01

Any method for silencing the activity of the HIV-1 retrovirus should tackle the extremely high variability of HIV-1 sequences and mutational escape. We studied sequence variability in the vicinity of selected RNA interference (RNAi) targets from isolates of HIV-1 subtype A in Russia, and we propose that using artificial RNAi is a potential alternative to traditional antiretroviral therapy. We prove that using multiple RNAi targets overcomes the variability in HIV-1 isolates. The optimal number of targets critically depends on the conservation of the target sequences. The total number of targets that are conserved with a probability of 0.7-0.8 should exceed at least 2. Combining deep sequencing and multitarget RNAi may provide an efficient approach to cure HIV/AIDS.

Toward On-Demand Deep Brain Stimulation Using Online Parkinson's Disease Prediction Driven by Dynamic Detection.

PubMed

Mohammed, Ameer; Zamani, Majid; Bayford, Richard; Demosthenous, Andreas

2017-12-01

In Parkinson's disease (PD), on-demand deep brain stimulation is required so that stimulation is regulated to reduce side effects resulting from continuous stimulation and PD exacerbation due to untimely stimulation. Also, the progressive nature of PD necessitates the use of dynamic detection schemes that can track the nonlinearities in PD. This paper proposes the use of dynamic feature extraction and dynamic pattern classification to achieve dynamic PD detection taking into account the demand for high accuracy, low computation, and real-time detection. The dynamic feature extraction and dynamic pattern classification are selected by evaluating a subset of feature extraction, dimensionality reduction, and classification algorithms that have been used in brain-machine interfaces. A novel dimensionality reduction technique, the maximum ratio method (MRM) is proposed, which provides the most efficient performance. In terms of accuracy and complexity for hardware implementation, a combination having discrete wavelet transform for feature extraction, MRM for dimensionality reduction, and dynamic k-nearest neighbor for classification was chosen as the most efficient. It achieves a classification accuracy of 99.29%, an F1-score of 97.90%, and a choice probability of 99.86%.

A deep survey of the X-ray binary populations in the SMC

NASA Astrophysics Data System (ADS)

Zezas, A.; Antoniou, V.

2017-10-01

The Small Magellanic Cloud (SMC) has been the subject of systematic X-ray surveys over the past two decades, which have yielded a rich population of high-mass X-ray binaries consisting predominantly of Be/X-ray binaries. We present results from our deep Chandra survey of the SMC which targeted regions with stellar populations ranging between ˜10-100 Myr. X-ray luminosities down to ˜3×10^{32} erg/s were reached, probing all active accreting binaries and extending well into the regime of quiescent accreting binaries and X-ray emitting normal stars. We measure the dependence of the formation efficiency of X-ray binaries on age. We also detect pulsations from 19 known and one new candidate pulsar. We construct the X-ray luminosity function in different regions of the SMC, which shows clear evidence for the propeller effect the centrifugal inhibition of accretion due to the interaction of the accretion flow with the pulsar's magnetic field. Finally we compare these results with predictions for the formation efficiency of X-ray binaries as a function of age from X-ray binary population synthesis models.

On the AlxGa1-xN/AlyGa1-yN/AlxGa1-xN (x>y) p-electron blocking layer to improve the hole injection for AlGaN based deep ultraviolet light-emitting diodes

NASA Astrophysics Data System (ADS)

Chu, Chunshuang; Tian, Kangkai; Fang, Mengqian; Zhang, Yonghui; Li, Luping; Bi, Wengang; Zhang, Zi-Hui

2018-01-01

This work proposes the [0001] oriented AlGaN-based deep ultraviolet (DUV) light-emitting diode (LED) possessing a specifically designed p-electron blocking layer (p-EBL) to achieve the high internal quantum efficiency. Both electrons and holes can be efficiently injected into the active region by adopting the Al0.60Ga0.40N/Al0.50Ga0.50N/Al0.60Ga0.40N structured p-EBL, in which a p-Al0.50Ga0.50N layer is embedded into the p-EBL. Moreover, the impact of different thicknesses for the p-Al0.50Ga0.50N insertion layer on the hole and electron injections has also been investigated. Compared with the DUV LED with the bulk p-Al0.60Ga0.40N as the EBL, the proposed LED architectures improve the light output power if the thickness of the p-Al0.50Ga0.50N insertion layer is properly designed.

Population-genomic variation within RNA viruses of the Western honey bee, Apis mellifera, inferred from deep sequencing

USDA-ARS?s Scientific Manuscript database

Deep sequencing of viruses isolated from infected hosts is an efficient way to measure population-genetic variation and can reveal patterns of dispersal and natural selection. In this study, we mined existing Illumina sequence reads to investigate single-nucleotide polymorphisms (SNPs) within two RN...

Toolkits and Libraries for Deep Learning.

PubMed

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.

Preliminary Design of Low-Thrust Interplanetary Missions

NASA Technical Reports Server (NTRS)

Sims, Jon A.; Flanagan, Steve N.

1997-01-01

For interplanetary missions, highly efficient electric propulsion systems can be used to increase the mass delivered to the destination and/or reduce the trip time over typical chemical propulsion systems. This technology is being demonstrated on the Deep Space 1 mission - part of NASA's New Millennium Program validating technologies which can lower the cost and risk and enhance the performance of future missions. With the successful demonstration on Deep Space 1, future missions can consider electric propulsion as a viable propulsion option. Electric propulsion systems, while highly efficient, produce only a small amount of thrust. As a result, the engines operate during a significant fraction of the trajectory. This characteristic makes it much more difficult to find optimal trajectories. The methods for optimizing low-thrust trajectories are typically categorized as either indirect, or direct. Indirect methods are based on calculus of variations, resulting in a two-point boundary value problem that is solved by satisfying terminal constraints and targeting conditions. These methods are subject to extreme sensitivity to the initial guess of the variables - some of which are not physically intuitive. Adding a gravity assist to the trajectory compounds the sensitivity. Direct methods parameterize the problem and use nonlinear programming techniques to optimize an objective function by adjusting a set of variables. A variety of methods of this type have been examined with varying results. These methods are subject to the limitations of the nonlinear programming techniques. In this paper we present a direct method intended to be used primarily for preliminary design of low-thrust interplanetary trajectories, including those with multiple gravity assists. Preliminary design implies a willingness to accept limited accuracy to achieve an efficient algorithm that executes quickly.

Fish Food in the Deep Sea: Revisiting the Role of Large Food-Falls

PubMed Central

Higgs, Nicholas D.; Gates, Andrew R.; Jones, Daniel O. B.

2014-01-01

The carcasses of large pelagic vertebrates that sink to the seafloor represent a bounty of food to the deep-sea benthos, but natural food-falls have been rarely observed. Here were report on the first observations of three large ‘fish-falls’ on the deep-sea floor: a whale shark (Rhincodon typus) and three mobulid rays (genus Mobula). These observations come from industrial remotely operated vehicle video surveys of the seafloor on the Angola continental margin. The carcasses supported moderate communities of scavenging fish (up to 50 individuals per carcass), mostly from the family Zoarcidae, which appeared to be resident on or around the remains. Based on a global dataset of scavenging rates, we estimate that the elasmobranch carcasses provided food for mobile scavengers over extended time periods from weeks to months. No evidence of whale-fall type communities was observed on or around the carcasses, with the exception of putative sulphide-oxidising bacterial mats that outlined one of the mobulid carcasses. Using best estimates of carcass mass, we calculate that the carcasses reported here represent an average supply of carbon to the local seafloor of 0.4 mg m−2d−1, equivalent to ∼4% of the normal particulate organic carbon flux. Rapid flux of high-quality labile organic carbon in fish carcasses increases the transfer efficiency of the biological pump of carbon from the surface oceans to the deep sea. We postulate that these food-falls are the result of a local concentration of large marine vertebrates, linked to the high surface primary productivity in the study area. PMID:24804731

WHATS-3: An improved flow-through multi-bottle fluid sampler for deep-sea geofluid research

NASA Astrophysics Data System (ADS)

Miyazaki, Junichi; Makabe, Akiko; Matsui, Yohei; Ebina, Naoya; Tsutsumi, Saki; Ishibashi, Jun-ichiro; Chen, Chong; Kaneko, Sho; Takai, Ken; Kawagucci, Shinsuke

2017-06-01

Deep-sea geofluid systems, such as hydrothermal vents and cold seeps, are key to understanding subseafloor environments of Earth. Fluid chemistry, especially, provides crucial information towards elucidating the physical, chemical and biological processes that occur in these ecosystems. To accurately assess fluid and gas properties of deep-sea geofluids, well-designed pressure-tight fluid samplers are indispensable and as such they are important assets of deep-sea geofluid research. Here, the development of a new flow-through, pressure-tight fluid sampler capable of four independent sampling events (two subsamples for liquid and gas analyses from each) is reported. This new sampler, named WHATS-3, is a new addition to the WHATS-series samplers and a major upgrade from the previous WHATS-2 sampler with improvements in sample number, valve operational time, physical robustness, and ease of maintenance. Routine laboratory-based pressure tests proved that it is suitable for operation up to 35 MPa pressure. Successful field tests of the new sampler were also carried out in five hydrothermal fields, two in Indian Ocean and three in Okinawa Trough (max. depth 3,300 m). Relations of Mg and major ion species demonstrated bimodal mixing trends between a hydrothermal fluid and seawater, confirming the high-quality of fluids sampled. The newly developed WHATS-3 sampler is well-balanced in sampling capability, field usability, and maintenance feasibility, and can serve as one of the best geofluid samplers available at present to conduct efficient research of deep-sea geofluid systems.

Her2Net: A Deep Framework for Semantic Segmentation and Classification of Cell Membranes and Nuclei in Breast Cancer Evaluation.

PubMed

Saha, Monjoy; Chakraborty, Chandan

2018-05-01

We present an efficient deep learning framework for identifying, segmenting, and classifying cell membranes and nuclei from human epidermal growth factor receptor-2 (HER2)-stained breast cancer images with minimal user intervention. This is a long-standing issue for pathologists because the manual quantification of HER2 is error-prone, costly, and time-consuming. Hence, we propose a deep learning-based HER2 deep neural network (Her2Net) to solve this issue. The convolutional and deconvolutional parts of the proposed Her2Net framework consisted mainly of multiple convolution layers, max-pooling layers, spatial pyramid pooling layers, deconvolution layers, up-sampling layers, and trapezoidal long short-term memory (TLSTM). A fully connected layer and a softmax layer were also used for classification and error estimation. Finally, HER2 scores were calculated based on the classification results. The main contribution of our proposed Her2Net framework includes the implementation of TLSTM and a deep learning framework for cell membrane and nucleus detection, segmentation, and classification and HER2 scoring. Our proposed Her2Net achieved 96.64% precision, 96.79% recall, 96.71% F-score, 93.08% negative predictive value, 98.33% accuracy, and a 6.84% false-positive rate. Our results demonstrate the high accuracy and wide applicability of the proposed Her2Net in the context of HER2 scoring for breast cancer evaluation.

282-nm AlGaN-based deep ultraviolet light-emitting diodes with improved performance on nano-patterned sapphire substrates

NASA Astrophysics Data System (ADS)

Dong, Peng; Yan, Jianchang; Wang, Junxi; Zhang, Yun; Geng, Chong; Wei, Tongbo; Cong, Peipei; Zhang, Yiyun; Zeng, Jianping; Tian, Yingdong; Sun, Lili; Yan, Qingfeng; Li, Jinmin; Fan, Shunfei; Qin, Zhixin

2013-06-01

We first report AlGaN-based deep ultraviolet light-emitting diodes (UV-LEDs) grown on nano-patterned sapphire substrates (NPSS) prepared through a nanosphere lithography technique. The AlN coalescence thickness on NPSS is only 3 μm due to AlN's nano-scaled lateral growth, which also leads to low dislocation densities in AlN and epi-layers above. On NPSS, the light-output power of a 282-nm UV-LED reaches 3.03 mW at 20 mA with external quantum efficiency of 3.45%, exhibiting 98% better performance than that on flat sapphire. Temperature-dependent photoluminescence reveals this significant enhancement to be a combination of higher internal quantum efficiency and higher light extraction efficiency.

Testing strong-segregation theory against self-consistent-field theory for block copolymer melts

NASA Astrophysics Data System (ADS)

Matsen, M. W.

2001-06-01

We introduce a highly efficient self-consistent-field theory (SCFT) method for examining the cylindrical and spherical block copolymer morphologies using a standard unit cell approximation (UCA). The method is used to calculate the classical diblock copolymer phase boundaries deep into the strong-segregation regime, where they can be compared with recent improvements to strong-segregation theory (SST). The comparison suggests a significant discrepancy between the two theories indicating that our understanding of strongly stretched polymer brushes is still incomplete.

The need for scientific software engineering in the pharmaceutical industry

NASA Astrophysics Data System (ADS)

Luty, Brock; Rose, Peter W.

2017-03-01

Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

The need for scientific software engineering in the pharmaceutical industry.

PubMed

Luty, Brock; Rose, Peter W

2017-03-01

Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

Optical Features of Efficient Europium(III) Complexes with β-Diketonato and Auxiliary Ligands and Mechanistic Investigation of Energy Transfer Process.

PubMed

Bala, Manju; Kumar, Satish; Taxak, V B; Boora, Priti; Khatkar, S P

2016-09-01

Two new europium (III) complexes have been synthesized with 1,3-[bis(4-methoxyphenyl)]propane-1,3-dionato (HBMPD) as main ligand and 2,2'-bipyridyl (bipy) or 1,10-phenanthroline (phen) as an auxiliary ligand. The main ligand HBMPD has been synthesized by ecofriendly microwave approach and complexes by solution precipitation method. The resulting materials are characterized by IR, (1)H-NMR, elemental analysis, X-ray diffraction, UV-visible and TG-DTG techniques. The photoluminescence (PL) spectroscopy depicts the detail analysis of photophysical properties of the complexes, their results show that the ligand interact with Eu (III) ion which act as antenna and transfers the absorbed energy to the central europium(III) ion via sensitization process efficiently. As a consequence of this interaction, these materials exhibit excellent luminescent intensity, long decay time (τ), high quantum efficiency (η) and Judd-Ofelt intensity parameter (Ω2). The CIE coordinates fall under the deep red region, matching well with the NTSC (National Television Standard Committee) standard. Hence, these highly efficient optical materials can be used as a red component in organic light emitting diodes (OLEDs) and full color flat panel displays.

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

PubMed

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.

Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing

NASA Astrophysics Data System (ADS)

Shao, Haidong; Jiang, Hongkai; Zhang, Haizhou; Duan, Wenjing; Liang, Tianchen; Wu, Shuaipeng

2018-02-01

The vibration signals collected from rolling bearing are usually complex and non-stationary with heavy background noise. Therefore, it is a great challenge to efficiently learn the representative fault features of the collected vibration signals. In this paper, a novel method called improved convolutional deep belief network (CDBN) with compressed sensing (CS) is developed for feature learning and fault diagnosis of rolling bearing. Firstly, CS is adopted for reducing the vibration data amount to improve analysis efficiency. Secondly, a new CDBN model is constructed with Gaussian visible units to enhance the feature learning ability for the compressed data. Finally, exponential moving average (EMA) technique is employed to improve the generalization performance of the constructed deep model. The developed method is applied to analyze the experimental rolling bearing vibration signals. The results confirm that the developed method is more effective than the traditional methods.

Electronics for Deep Space Cryogenic Applications

NASA Technical Reports Server (NTRS)

Patterson, R. L.; Hammond, A.; Dickman, J. E.; Gerber, S. S.; Elbuluk, M. E.; Overton, E.

2002-01-01

Deep space probes and planetary exploration missions require electrical power management and control systems that are capable of efficient and reliable operation in very cold temperature environments. Typically, in deep space probes, heating elements are used to keep the spacecraft electronics near room temperature. The utilization of power electronics designed for and operated at low temperature will contribute to increasing efficiency and improving reliability of space power systems. At NASA Glenn Research Center, commercial-off-the-shelf devices as well as developed components are being investigated for potential use at low temperatures. These devices include semiconductor switching devices, magnetics, and capacitors. Integrated circuits such as digital-to-analog and analog-to-digital converters, DC/DC converters, operational amplifiers, and oscillators are also being evaluated. In this paper, results will be presented for selected analog-to-digital converters, oscillators, DC/DC converters, and pulse width modulation (PWM) controllers.

Enhancing arsenic mitigation in Bangladesh: findings from institutional, psychological, and technical investigations.

PubMed

Johnston, Richard; Hug, Stephan J; Inauen, Jennifer; Khan, Nasreen I; Mosler, Hans-Joachim; Yang, Hong

2014-08-01

As part of a trans-disciplinary research project, a series of surveys and interventions were conducted in different arsenic-affected regions of rural Bangladesh. Surveys of institutional stakeholders identified deep tubewells and piped water systems as the most preferred options, and the same preferences were found in household surveys of populations at risk. Psychological surveys revealed that these two technologies were well-supported by potential users, with self-efficacy and social norms being the principal factors driving behavior change. The principal drawbacks of deep tubewells are that installation costs are too high for most families to own private wells, and that for various socio-cultural-religious reasons, people are not willing to walk long distances to access communal tubewells. In addition, water sector planners have reservations about greater exploitation of the deep aquifer, out of concern for current or future geogenic contamination. Groundwater models and field studies have shown that in the great majority of the affected areas, the risk of arsenic contamination of deep groundwater is small; salinity, iron, and manganese are more likely to pose problems. These constituents can in some cases be avoided by exploiting an intermediate depth aquifer of good chemical quality, which is hydraulically and geochemically separate from the arsenic-contaminated shallow aquifer. Deep tubewells represent a technically sound option throughout much of the arsenic-affected regions, and future mitigation programs should build on and accelerate construction of deep tubewells. Utilization of deep tubewells, however, could be improved by increasing the tubewell density (which requires stronger financial support) to reduce travel times, by considering water quality in a holistic way, and by accompanying tubewell installation with motivational interventions based on psychological factors. By combining findings from technical and social sciences, the efficiency and success of arsenic mitigation in general - and installation of deep tubewells in particular - can be significantly enhanced. Copyright © 2013 Elsevier B.V. All rights reserved.

The 32-GHz performance of the DSS-14 70-meter antenna: 1989 configuration

NASA Technical Reports Server (NTRS)

Gatti, M. S.; Klein, M. J.; Kuiper, T. B. H.

1989-01-01

The results of preliminary 32 GHz calibrations of the 70 meter antenna at Goldstone are presented. Measurements were done between March and July 1989 using Virgo A and Venus as the primary efficiency calibrators. The flux densites of theses radio sources at 32 GHz are not known with high accuracy, but were extrapolated from calibrated data at lower frequencies. The measured value of efficiency (0.35) agreed closely with the predicted value (0.32), and the results are very repeatable. Flux densities of secondary sources used in the observations were subsequently derived. These measurements were performed using a beamswitching radiometer that employed an uncooled high-electron mobility transistor (HEMT) low-noise amplifier. This system was installed primarily to determine the performance of the antenna in its 1989 configuration, but the experience will also aid in successful future calibration of the Deep Space Network (DSN) at this frequency.

Ge nanopillar solar cells epitaxially grown by metalorganic chemical vapor deposition

PubMed Central

Kim, Youngjo; Lam, Nguyen Dinh; Kim, Kangho; Park, Won-Kyu; Lee, Jaejin

2017-01-01

Radial junction solar cells with vertically aligned wire arrays have been widely studied to improve the power conversion efficiency. In this work, we report the first Ge nanopillar solar cell. Nanopillar arrays are selectively patterned on p-type Ge (100) substrates using nanosphere lithography and deep reactive ion etching processes. Nanoscale radial and planar junctions are realized by an n-type Ge emitter layer which is epitaxially grown by MOCVD using isobutylgermane. In situ epitaxial surface passivation is employed using an InGaP layer to avoid high surface recombination rates and Fermi level pinning. High quality n-ohmic contact is realized by protecting the top contact area during the nanopillar patterning. The short circuit current density and the power conversion efficiency of the Ge nanopillar solar cell are demonstrated to be improved up to 18 and 30%, respectively, compared to those of the Ge solar cell with a planar surface. PMID:28209964

Technology Assessment of Doe's 55-we Stirling Technology Demonstrator Convector (TDC)

NASA Technical Reports Server (NTRS)

Furlong, Richard; Shaltens, Richard

2000-01-01

The Department of Energy (DOE), Germantown, Maryland and the NASA Glenn Research Center (GRC), Cleveland, Ohio are developing a Stirling Convertor for an advanced radioisotope power system as a potential power source for spacecraft on-board electric power for NASA deep space science missions. The Stirling Convertor is being evaluated as an alternative high efficiency power source to replace Radioisotope Thermoelectric Generators (RTGs). Stirling Technology Company (STC), Kennewick, Washington, is developing the highly efficient, long life 55-We free-piston Stirling Convertor known as the Technology Demonstrator Convertor (TDC) under contract to DOE. GRC provides Stirling technology expertise under a Space Act Agreement with the DOE. Lockheed Martin Astronautics (LMA), Valley Forge, Pennsylvania is the current power system integrator for the Advanced Radioisotope Power System (ARPS) Project for the DOE. JPL is responsible for the Outer Planets/Solar Probe Project for NASA.

Detecting very low allele fraction variants using targeted DNA sequencing and a novel molecular barcode-aware variant caller.

PubMed

Xu, Chang; Nezami Ranjbar, Mohammad R; Wu, Zhong; DiCarlo, John; Wang, Yexun

2017-01-03

Detection of DNA mutations at very low allele fractions with high accuracy will significantly improve the effectiveness of precision medicine for cancer patients. To achieve this goal through next generation sequencing, researchers need a detection method that 1) captures rare mutation-containing DNA fragments efficiently in the mix of abundant wild-type DNA; 2) sequences the DNA library extensively to deep coverage; and 3) distinguishes low level true variants from amplification and sequencing errors with high accuracy. Targeted enrichment using PCR primers provides researchers with a convenient way to achieve deep sequencing for a small, yet most relevant region using benchtop sequencers. Molecular barcoding (or indexing) provides a unique solution for reducing sequencing artifacts analytically. Although different molecular barcoding schemes have been reported in recent literature, most variant calling has been done on limited targets, using simple custom scripts. The analytical performance of barcode-aware variant calling can be significantly improved by incorporating advanced statistical models. We present here a highly efficient, simple and scalable enrichment protocol that integrates molecular barcodes in multiplex PCR amplification. In addition, we developed smCounter, an open source, generic, barcode-aware variant caller based on a Bayesian probabilistic model. smCounter was optimized and benchmarked on two independent read sets with SNVs and indels at 5 and 1% allele fractions. Variants were called with very good sensitivity and specificity within coding regions. We demonstrated that we can accurately detect somatic mutations with allele fractions as low as 1% in coding regions using our enrichment protocol and variant caller.

Cold Helium Gas Pressurization For Spacecraft Cryogenic Propulsion Systems

NASA Technical Reports Server (NTRS)

Morehead, Robert L.; Atwell. Matthew J.; Hurlbert, Eric A.; Melcher, J. C.

2017-01-01

To reduce the dry mass of a spacecraft pressurization system, helium pressurant may be stored at low temperature and high pressure to increase mass in a given tank volume. Warming this gas through an engine heat exchanger prior to tank pressurization both increases the system efficiency and simplifies the designs of intermediate hardware such as regulators, valves, etc. since the gas is no longer cryogenic. If this type of cold helium pressurization system is used in conjunction with a cryogenic propellant, though, a loss in overall system efficiency can be expected due to heat transfer from the warm ullage gas to the cryogenic propellant which results in a specific volume loss for the pressurant, interpreted as the Collapse Factor. Future spacecraft with cryogenic propellants will likely have a cold helium system, with increasing collapse factor effects as vehicle sizes decrease. To determine the collapse factor effects and overall implementation strategies for a representative design point, a cold helium system was hotfire tested on the Integrated Cryogenic Propulsion Test Article (ICPTA) in a thermal vacuum environment at the NASA Glenn Research Center Plum Brook Station. The ICPTA vehicle is a small lander-sized spacecraft prototype built at NASA Johnson Space Center utilizing cryogenic liquid oxygen/liquid methane propellants and cryogenic helium gas as a pressurant to operate one 2,800lbf 5:1 throttling main engine, two 28lbf Reaction Control Engines (RCE), and two 7lbf RCEs (Figure 1). This vehicle was hotfire tested at a variety of environmental conditions at NASA Plum Brook, ranging from ambient temperature/simulated high altitude, deep thermal/high altitude, and deep thermal/high vacuum conditions. A detailed summary of the vehicle design and testing campaign may be found in Integrated Cryogenic Propulsion Test Article Thermal Vacuum Hotfire Testing, AIAA JPC 2017.

A focal plane detector design for a wide band Laue-lens telescope

NASA Astrophysics Data System (ADS)

Caroli, E.; Auricchio, N.; Bertuccio, G.; Budtz-Jørgensen, C.; Curado da Silva, R. M.; Del Sordo, S.; Frontera, F.; Quadrini, E.; Ubertini, P.; Ventura, G.

2006-06-01

The energy range above 50 keV is important for the study of many open problems in high energy astrophysics such as, non thermal mechanisms in SNR, the study of the high energy cut-offs in AGN spectra, and the detection of nuclear and annihilation lines. In the framework of the definition of a new mission concept for hard X and soft gamma ray (GRI- Gamma Ray Imager) for the next decade, the use of Laue lenses with broad energy band-passes from 100 to 1000 keV is under study. This kind of instruments will be used for deep study the hard X-ray continuum of celestial sources. This new telescope will require focal plane detectors with high detection efficiency over the entire operative range, an energy resolution of few keV at 500 keV and a sensitivity to linear polarization. We describe a possible configuration for the focal plane detector based on CdTe/CZT pixelated layers stacked together to achieve the required detection efficiency at high energy. Each layer can either operate as a separate position sensitive detector and a polarimeter or together with other layers in order to increase the overall full energy efficiency. We report on the current state of art in high Z spectrometers development and on some activities undergoing. Furthermore we describe the proposed focal plane option with the required resources and an analytical summary of the achievable performance in terms of efficiency and polarimetry.

A new approach for solving seismic tomography problems and assessing the uncertainty through the use of graph theory and direct methods

NASA Astrophysics Data System (ADS)

Bogiatzis, P.; Ishii, M.; Davis, T. A.

2016-12-01

Seismic tomography inverse problems are among the largest high-dimensional parameter estimation tasks in Earth science. We show how combinatorics and graph theory can be used to analyze the structure of such problems, and to effectively decompose them into smaller ones that can be solved efficiently by means of the least squares method. In combination with recent high performance direct sparse algorithms, this reduction in dimensionality allows for an efficient computation of the model resolution and covariance matrices using limited resources. Furthermore, we show that a new sparse singular value decomposition method can be used to obtain the complete spectrum of the singular values. This procedure provides the means for more objective regularization and further dimensionality reduction of the problem. We apply this methodology to a moderate size, non-linear seismic tomography problem to image the structure of the crust and the upper mantle beneath Japan using local deep earthquakes recorded by the High Sensitivity Seismograph Network stations.

High-directionality fiber-chip grating coupler with interleaved trenches and subwavelength index-matching structure.

PubMed

Benedikovic, Daniel; Alonso-Ramos, Carlos; Cheben, Pavel; Schmid, Jens H; Wang, Shurui; Xu, Dan-Xia; Lapointe, Jean; Janz, Siegfried; Halir, Robert; Ortega-Moñux, Alejandro; Wangüemert-Pérez, J Gonzalo; Molina-Fernández, Iñigo; Fédéli, Jean-Marc; Vivien, Laurent; Dado, Milan

2015-09-15

We present the first experimental demonstration of a new fiber-chip grating coupler concept that exploits the blazing effect by interleaving the standard full (220 nm) and shallow etch (70 nm) trenches in a 220 nm thick silicon layer. The high directionality is obtained by controlling the separation between the deep and shallow trenches to achieve constructive interference in the upward direction and destructive interference toward the silicon substrate. Utilizing this concept, the grating directionality can be maximized independent of the bottom oxide thickness. The coupler also includes a subwavelength-engineered index-matching region, designed to reduce the reflectivity at the interface between the injection waveguide and the grating. We report a measured fiber-chip coupling efficiency of -1.3  dB, the highest coupling efficiency achieved to date for a surface grating coupler in a 220 nm silicon-on-insulator platform fabricated in a conventional dual-etch process without high-index overlays or bottom mirrors.

Orbital Transfer Techniques for Round-Trip Mars Missions

NASA Technical Reports Server (NTRS)

Landau, Damon

2013-01-01

The human exploration of Phobos and Deimos or the retrieval of a surface sample launched to low-Mars orbit presents a highly constrained orbital transfer problem. In general, the plane of the target orbit will not be accessible from the arrival or departure interplanetary trajectories with an (energetically optimal) tangential burn at periapsis. The orbital design is further complicated by the addition of a high-energy parking orbit for the relatively massive Deep Space Vehicle to reduce propellant expenditure, while the crew transfers to and from the target orbit in a smaller Space Exploration Vehicle. The proposed strategy shifts the arrival and departure maneuvers away from periapsis so that the apsidal line of the parking orbit lies in the plane of the target orbit, permitting highly efficient plane change maneuvers at apoapsis of the elliptical parking orbit. An apsidal shift during the arrival or departure maneuver is approximately five times as efficient as maneuvering while in Mars orbit, thus significantly reducing the propellant necessary to transfer between the arrival, target, and departure orbits.

Study of relationships of material properties and high efficiency solar cell performance on material composition

NASA Technical Reports Server (NTRS)

Sah, C. T.

1983-01-01

The performance improvements obtainable from extending the traditionally thin back-surface-field (BSF) layer deep into the base of silicon solar cells under terrestrial solar illumination (AM1) are analyzed. This extended BSF cell is also known as the back-drift-field cell. About 100 silicon cells were analyzed, each with a different emitter or base dopant impurity distribution whose selection was based on physically anticipated improvements. The four principal performance parameters (the open-circuit voltage, the short-circuit current, the fill factor, and the maximum efficiency) are computed using a FORTRAN program, called Circuit Technique for Semiconductor-device Analysis, CTSA, which numerically solves the six Shockley Equations under AM1 solar illumination at 88.92 mW/cm, at an optimum cell thickness of 50 um. The results show that very significant performance improvements can be realized by extending the BSF layer thickness from 2 um (18% efficiency) to 40 um (20% efficiency).

Resource Efficient Metal and Material Recycling

NASA Astrophysics Data System (ADS)

Reuter, Markus A.; van Schaik, Antoinette

Metals enable sustainability through their use and their recyclability. However, various factors can affect the Resource Efficiency of Metal Processing and Recycling. Some typical factors that enable Resource Efficiency include and arranged under the drivers of sustainability: Environment (Maximize Resource Efficiency — Energy, Recyclates, Materials, Water, Sludges, Emissions, Land); Economic Feasibility (BAT & Recycling Systems Simulation / Digitalization, Product vis-à-vis Material Centric Recycling); and Social — Licence to Operate (Legislation, consumer, policy, theft, manual labour.). In order to realize this primary production has to be linked systemically with typical actors in the recycling chain such as Original Equipment Manufacturers (OEMs), Recyclers & Collection, Physical separation specialists as well as process metallurgical operations that produce high value metals, compounds and products that recycle back to products. This is best done with deep knowledge of multi-physics, technology, product & system design, process control, market, life cycle management, policy, to name a few. The combination of these will be discussed as Design for Sustainability (DfS) and Design for Recycling (DfR) applications.

[Research advances on regulating soil nitrogen loss by the type of nitrogen fertilizer and its application strategy.

PubMed

Zhou, Wei; Lyu, Teng Fei; Yang, Zhi Ping; Sun, Hong; Yang, Liang Jie; Chen, Yong; Ren, Wan Jun

2016-09-01

Unreasonable application of nitrogen fertilizer to cropland decreases nitrogen use efficiency of crop. A large amount of nitrogen loss to environment through runoff, leaching, ammonia volati-lization, nitrification-denitrification, etc., causes water and atmospheric pollution, poses serious environmental problems and threatens human health. The type of nitrogen fertilizer and its application rate, time, and method have significant effects on nitrogen loss. The primary reason for nitrogen loss is attributed to the supersaturated soil nitrogen concentration. Making full use of environmental nitrogen sources, reducing the application rate of chemical nitrogen fertilizers, applying deep placement fertilizing method, and applying organic fertilizers with chemical nitrogen fertilizers, are effective practices for reducing nitrogen loss and improving nitrogen use efficiency. It is suggested that deve-loping new high efficiency nitrogen fertilizers, enhancing nitrogen management, and strengthening the monitoring and use of environmental nitrogen sources are the powerful tools to decrease nitrogen application rate and increase efficiency of cropland.

3.1 W narrowband blue external cavity diode laser

NASA Astrophysics Data System (ADS)

Peng, Jue; Ren, Huaijin; Zhou, Kun; Li, Yi; Du, Weichuan; Gao, Songxin; Li, Ruijun; Liu, Jianping; Li, Deyao; Yang, Hui

2018-03-01

We reported a high-power narrowband blue diode laser which is suitable for subsequent nonlinear frequency conversion into the deep ultraviolet (DUV) spectral range. The laser is based on an external cavity diode laser (ECDL) system using a commercially available GaN-based high-power blue laser diode emitting at 448 nm. Longitudinal mode selection is realized by using a surface diffraction grating in Littrow configuration. The diffraction efficiency of the grating was optimized by controlling the polarization state of the laser beam incident on the grating. A maximum optical output power of 3.1 W in continuous-wave operation with a spectral width of 60 pm and a side-mode suppression ratio (SMSR) larger than 10 dB at 448.4 nm is achieved. Based on the experimental spectra and output powers, the theoretical efficiency and output power of the subsequent nonlinear frequency conversion were calculated according to the Boyd- Kleinman theory. The single-pass conversion efficiency and output power is expected to be 1.9×10-4 and 0.57 mW, respectively, at the 3.1 W output power of the ECDL. The high-power narrowband blue diode laser is very promising as pump source in the subsequent nonlinear frequency conversion.

InP Devices For Millimeter-Wave Monolithic Circuits

NASA Astrophysics Data System (ADS)

Binari, S. C.; Neidert, R. E.; Dietrich, H. B.

1989-11-01

High efficiency, mm-wave operation has been obtained from lateral transferred-electron devices (TEDs) designed with a high resistivity region located near the cathode contact. At 29.9 GHz, a CW power output of 29.1 mW with a conversion efficiency of 6.7% has been achieved with cavity-tuned discrete devices. This result represents the highest power output and efficiency of a lateral TED in this frequency range. The lateral devices also had a CW power output of 0.4 mW at 98.5 GHz and 0.9 mW at 75.2 GHz. In addition, a monolithic oscillator incorporating the lateral TED has been demonstrated at 79.9 GHz. InP Schottky-barrier diodes have been fabricated using selective MeV ion implantation into semi-insulating InP substrates. Using Si implantation with energies of up to 6.0 MeV, n+ layers as deep as 3 μm with peak carrier concentrations of 2 x 1018 cm-3 have been obtained. These devices have been evaluated as mixers and detectors at 94 GHz and have demonstrated a conversion loss of 7.6 dB and a zero-bias detector sensitivity as high as 400 mV/mW.

ChemTS: an efficient python library for de novo molecular generation

PubMed Central

Yang, Xiufeng; Zhang, Jinzhe; Yoshizoe, Kazuki; Terayama, Kei; Tsuda, Koji

2017-01-01

Abstract Automatic design of organic materials requires black-box optimization in a vast chemical space. In conventional molecular design algorithms, a molecule is built as a combination of predetermined fragments. Recently, deep neural network models such as variational autoencoders and recurrent neural networks (RNNs) are shown to be effective in de novo design of molecules without any predetermined fragments. This paper presents a novel Python library ChemTS that explores the chemical space by combining Monte Carlo tree search and an RNN. In a benchmarking problem of optimizing the octanol-water partition coefficient and synthesizability, our algorithm showed superior efficiency in finding high-scoring molecules. ChemTS is available at https://github.com/tsudalab/ChemTS. PMID:29435094

Gas-exfoliated porous monolayer boron nitride for enhanced aerobic oxidative desulfurization performance.

PubMed

Wu, Yingcheng; Wu, Peiwen; Chao, Yanhong; He, Jing; Li, Hongping; Lu, Linjie; Jiang, Wei; Zhang, Beibei; Li, Huaming; Zhu, Wenshuai

2018-01-12

Hexagonal boron nitride has been regarded to be an efficient catalyst in aerobic oxidation fields, but limited by the less-exposed active sites. In this contribution, we proposed a simple green liquid nitrogen gas exfoliation strategy for preparation of porous monolayer nanosheets (BN-1). Owing to the reduced layer numbers, decreased lateral sizes and artificially-constructed pores, increased exposure of active sites was expected, further contributed to an enhanced aerobic oxidative desulfurization (ODS) performance up to ∼98% of sulfur removal, achieving ultra-deep desulfurization. This work not only introduced an excellent catalyst for aerobic ODS, but also provided a strategy for construction of some other highly-efficient monolayer two-dimensional materials for enhanced catalytic performance.

Machine learning action parameters in lattice quantum chromodynamics

NASA Astrophysics Data System (ADS)

Shanahan, Phiala E.; Trewartha, Daniel; Detmold, William

2018-05-01

Numerical lattice quantum chromodynamics studies of the strong interaction are important in many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods promise improved efficiency of lattice calculations, and access to regions of parameter space that are currently computationally intractable, via multi-scale action-matching approaches that necessitate parametric regression of generated lattice datasets. The applicability of machine learning to this regression task is investigated, with deep neural networks found to provide an efficient solution even in cases where approaches such as principal component analysis fail. The high information content and complex symmetries inherent in lattice QCD datasets require custom neural network layers to be introduced and present opportunities for further development.

Gas-exfoliated porous monolayer boron nitride for enhanced aerobic oxidative desulfurization performance

NASA Astrophysics Data System (ADS)

Wu, Yingcheng; Wu, Peiwen; Chao, Yanhong; He, Jing; Li, Hongping; Lu, Linjie; Jiang, Wei; Zhang, Beibei; Li, Huaming; Zhu, Wenshuai

2018-01-01

Hexagonal boron nitride has been regarded to be an efficient catalyst in aerobic oxidation fields, but limited by the less-exposed active sites. In this contribution, we proposed a simple green liquid nitrogen gas exfoliation strategy for preparation of porous monolayer nanosheets (BN-1). Owing to the reduced layer numbers, decreased lateral sizes and artificially-constructed pores, increased exposure of active sites was expected, further contributed to an enhanced aerobic oxidative desulfurization (ODS) performance up to ˜98% of sulfur removal, achieving ultra-deep desulfurization. This work not only introduced an excellent catalyst for aerobic ODS, but also provided a strategy for construction of some other highly-efficient monolayer two-dimensional materials for enhanced catalytic performance.

Numerical Study of a 10 K Two Stage Pulse Tube Cryocooler with Precooling Inside the Pulse Tube

NASA Astrophysics Data System (ADS)

Xiaomin, Pang; Xiaotao, Wang; Wei, Dai; Jianyin, Hu; Ercang, Luo

2017-02-01

High efficiency cryocoolers working below 10 K have many applications such as cryo-pump, superconductor cooling and cryogenic electronics. This paper presents a thermally coupled two-stage pulse tube cryocooler system and its numeric analysis. The simulation results indicate that temperature distribution in the pulse tube has a significant impact on the system performance. So a precooling heat exchanger is put inside the second stage pulse tube for a deep investigation on its influence on the system performance. The influences of operating parameters such as precooling temperature, location of the precooling heat exchanger are discussed. Comparison of energy losses apparently show the advantages of the configuration which leads to an improvement on the efficiency. Finally, the cryocooler is predicted to be able to reach a relative Carnot efficiency of 10.7% at 10 K temperature.

Low-threshold voltage ultraviolet light-emitting diodes based on (Al,Ga)N metal-insulator-semiconductor structures

NASA Astrophysics Data System (ADS)

Liang, Yu-Han; Towe, Elias

2017-12-01

Al-rich III-nitride-based deep-ultraviolet (UV) (275-320 nm) light-emitting diodes are plagued with a low emission efficiency and high turn-on voltages. We report Al-rich (Al,Ga)N metal-insulator-semiconductor UV light-emitting Schottky diodes with low turn-on voltages of <3 V, which are about half those of typical (Al,Ga)N p-i-n diodes. Our devices use a thin AlN film as the insulator and an n-type Al0.58Ga0.42N film as the semiconductor. To improve the efficiency, we inserted a GaN quantum-well structure between the AlN insulator and the n-type Al x Ga1- x N semiconductor. The benefits of the quantum-well structure include the potential to tune the emission wavelength and the capability to confine carriers for more efficient radiative recombination.

Dye-Sensitized Core/Active Shell Upconversion Nanoparticles for Optogenetics and Bioimaging Applications

DOE PAGES

Wu, Xiang; Zhang, Yuanwei; Takle, Kendra; ...

2016-01-06

A near-infrared (NIR) dye-sensitized upconversion nanoparticles (UCNPs) can broaden the absorption range and boost upconversion efficiency of UCNPs. We achieved significantly enhanced upconversion luminescence in dye-sensitized core/active shell UCNPs via the doping of ytterbium ions (Yb 3+ ) in the UCNP shell, which bridged the energy transfer from the dye to the UCNP core. As a result, we synergized the two most practical upconversion booster effectors (dye-sensitizing and core/shell enhancement) to amplify upconversion efficiency. We also demonstrated two biomedical applications using these UCNPs. By using dye-sensitized core/active shell UCNP embedded poly(methyl methacrylate) polymer implantable systems, we successfully shifted the optogeneticmore » neuron excitation window to a biocompatible and deep tissue penetrable 800 nm wavelength. Furthermore, UCNPs were water-solubilized with Pluronic F127 with high upconversion efficiency and can be imaged in a mouse model.« less

ACS Data Handbook v.6.0

NASA Astrophysics Data System (ADS)

Gonzaga, S.; et al.

2011-03-01

ACS was designed to provide a deep, wide-field survey capability from the visible to near-IR using the Wide Field Camera (WFC), high resolution imaging from the near-UV to near-IR with the now-defunct High Resolution Camera (HRC), and solar-blind far-UV imaging using the Solar Blind Camera (SBC). The discovery efficiency of ACS's Wide Field Channel (i.e., the product of WFC's field of view and throughput) is 10 times greater than that of WFPC2. The failure of ACS's CCD electronics in January 2007 brought a temporary halt to CCD imaging until Servicing Mission 4 in May 2009, when WFC functionality was restored. Unfortunately, the high-resolution optical imaging capability of HRC was not recovered.

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images.

PubMed

Xu, Jun; Xiang, Lei; Liu, Qingshan; Gilmore, Hannah; Wu, Jianzhong; Tang, Jinghai; Madabhushi, Anant

2016-01-01

Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of breast cancer tissue specimens. The Nottingham Histologic Score system is highly correlated with the shape and appearance of breast cancer nuclei in histopathological images. However, automated nucleus detection is complicated by 1) the large number of nuclei and the size of high resolution digitized pathology images, and 2) the variability in size, shape, appearance, and texture of the individual nuclei. Recently there has been interest in the application of "Deep Learning" strategies for classification and analysis of big image data. Histopathology, given its size and complexity, represents an excellent use case for application of deep learning strategies. In this paper, a Stacked Sparse Autoencoder (SSAE), an instance of a deep learning strategy, is presented for efficient nuclei detection on high-resolution histopathological images of breast cancer. The SSAE learns high-level features from just pixel intensities alone in order to identify distinguishing features of nuclei. A sliding window operation is applied to each image in order to represent image patches via high-level features obtained via the auto-encoder, which are then subsequently fed to a classifier which categorizes each image patch as nuclear or non-nuclear. Across a cohort of 500 histopathological images (2200 × 2200) and approximately 3500 manually segmented individual nuclei serving as the groundtruth, SSAE was shown to have an improved F-measure 84.49% and an average area under Precision-Recall curve (AveP) 78.83%. The SSAE approach also out-performed nine other state of the art nuclear detection strategies.

Deep-etched sinusoidal polarizing beam splitter grating.

PubMed

Feng, Jijun; Zhou, Changhe; Cao, Hongchao; Lv, Peng

2010-04-01

A sinusoidal-shaped fused-silica grating as a highly efficient polarizing beam splitter (PBS) is investigated based on the simplified modal method. The grating structure depends mainly on the ratio of groove depth to grating period and the ratio of incident wavelength to grating period. These ratios can be used as a guideline for the grating design at different wavelengths. A sinusoidal-groove PBS grating is designed at a wavelength of 1310 nm under Littrow mounting, and the transmitted TM and TE polarized waves are mainly diffracted into the zeroth order and the -1st order, respectively. The grating profile is optimized by using rigorous coupled-wave analysis. The designed PBS grating is highly efficient (>95.98%) over the O-band wavelength range (1260-1360 nm) for both TE and TM polarizations. The sinusoidal grating can exhibit higher diffraction efficiency, larger extinction ratio, and less reflection loss than the rectangular-groove PBS grating. By applying wet etching technology on the rectangular grating, which was manufactured by holographic recording and inductively coupled plasma etching technology, the sinusoidal grating can be approximately fabricated. Experimental results are in agreement with theoretical values.

Highly Reflective Nonalloyed Ni/Ag/Pt Contact to Mg-Si Codoped p-GaN for Enhanced Efficiency of Light-Emitting Diodes.

PubMed

Oh, Munsik; Kim, Hyunsoo

2015-10-01

The authors report enhanced efficiency of GaN-based light-emitting diodes (LEDs) fabricated with highly reflective nonalloyed Ni/Ag/Pt contact. The Ni/Ag/Pt contact formed on the Mg-Si codoped p-GaN produced the low specific contact resistance of 7.9 x 10(-4) Ωcm2 under as-deposited condition, which is comparable to the reference reflector (annealed at 500 °C for 1 min in oxygen ambient). Current-voltage-temperature measurements and the secondary ion mass spectroscopy revealed that the ohmic mechanism of the nonalloyed Ni/Ag/Pt contact is due to the more generated deep-level states associated with Mg-Si codoping, which act as the efficient hopping centers for the carrier transport at the contact/p-GaN interface. Due to the absence of interfacial reaction, the nonalloyed Ni/Ag/Pt contact showed much higher optical reflectivity (93.4% at 450 nm) as compared to the annealed sample (57.7%), resulting in a 40.5% brighter light output power as compared to the reference LEDs.

Experimental Investigation of the Influence of Confining Stress on Hard Rock Fragmentation Using a Conical Pick

NASA Astrophysics Data System (ADS)

Li, Xibing; Wang, Shaofeng; Wang, Shanyong

2018-01-01

High geostress is a prominent condition in deep excavations and affects the cuttability of deep hard rock. This study aims to determine the influence of confining stress on hard rock fragmentation as applied by a conical pick. Using a true triaxial test apparatus, static and coupled static and dynamic loadings from pick forces were applied to end faces of cubic rock specimens to break them under biaxial, uniaxial and stress-free confining stress conditions. The cuttability indices (peak pick force, insertion depth and disturbance duration), failure patterns and fragment sizes were measured and compared to estimate the effects of confining stress. The results show that the rock cuttabilities decreased in order from rock breakages under stress-free conditions to uniaxial confining stress and then to biaxial confining stress. Under biaxial confining stress, only flake-shaped fragments were stripped from the rock surfaces under the requirements of large pick forces or disturbance durations. As the level of uniaxial confining stress increased, the peak pick force and the insertion depth initially increased and then decreased, and the failure patterns varied from splitting to partial splitting and then to rock bursts with decreasing average fragment sizes. Rock bursts will occur under elastic compression via ultra-high uniaxial confining stresses. There are two critical uniaxial confining stress levels, namely stress values at which peak pick forces begin to decrease and improve rock cuttability, and those at which rock bursts initially occur and cutting safety decreases. In particular, hard rock is easiest to split safely and efficiently under stress-free conditions. Moreover, coupled static preloading and dynamic disturbance can increase the efficiency of rock fragmentation with increasing preloading levels and disturbance amplitudes. The concluding remarks confirm hard rock cuttability using conical pick, which can improve the applicability of mechanical excavation in deep hard rock masses.

PHL 1092: A narrow-line quasar emerging from the darkness

NASA Astrophysics Data System (ADS)

Gallo, Luigi

2013-10-01

The radio quiet, narrow line quasar, PHL1092 exhibits the extreme behaviour associated with 1H0707 and IRAS13224, but at a high redshift (z=0.396) and with high luminosity (~10^45 erg/s). From a short, bright state observation of PHL1092 we discovered a super soft excess, possible relativistically broadened FeL and K emission, high radiative efficiency, and possible high velocity outflow. Follow up observations between 2008-10 caught the quasar in a deep minimum that could be attributed to disruption of the corona. We will monitor PHL1092 with Swift to catch the quasar emerging from its current low-flux state so that we can study the bright state of the AGN with a triggered 130ks XMM observation.

Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning.

PubMed

Norouzzadeh, Mohammad Sadegh; Nguyen, Anh; Kosmala, Margaret; Swanson, Alexandra; Palmer, Meredith S; Packer, Craig; Clune, Jeff

2018-06-19

Having accurate, detailed, and up-to-date information about the location and behavior of animals in the wild would improve our ability to study and conserve ecosystems. We investigate the ability to automatically, accurately, and inexpensively collect such data, which could help catalyze the transformation of many fields of ecology, wildlife biology, zoology, conservation biology, and animal behavior into "big data" sciences. Motion-sensor "camera traps" enable collecting wildlife pictures inexpensively, unobtrusively, and frequently. However, extracting information from these pictures remains an expensive, time-consuming, manual task. We demonstrate that such information can be automatically extracted by deep learning, a cutting-edge type of artificial intelligence. We train deep convolutional neural networks to identify, count, and describe the behaviors of 48 species in the 3.2 million-image Snapshot Serengeti dataset. Our deep neural networks automatically identify animals with >93.8% accuracy, and we expect that number to improve rapidly in years to come. More importantly, if our system classifies only images it is confident about, our system can automate animal identification for 99.3% of the data while still performing at the same 96.6% accuracy as that of crowdsourced teams of human volunteers, saving >8.4 y (i.e., >17,000 h at 40 h/wk) of human labeling effort on this 3.2 million-image dataset. Those efficiency gains highlight the importance of using deep neural networks to automate data extraction from camera-trap images, reducing a roadblock for this widely used technology. Our results suggest that deep learning could enable the inexpensive, unobtrusive, high-volume, and even real-time collection of a wealth of information about vast numbers of animals in the wild. Copyright © 2018 the Author(s). Published by PNAS.

A high-efficiency gas target setup for underground experiments, and redetermination of the branching ratio of the 189.5 keV 22Ne(p,γ)23Na resonance

NASA Astrophysics Data System (ADS)

Ferraro, F.; Takács, M. P.; Piatti, D.; Mossa, V.; Aliotta, M.; Bemmerer, D.; Best, A.; Boeltzig, A.; Broggini, C.; Bruno, C. G.; Caciolli, A.; Cavanna, F.; Chillery, T.; Ciani, G. F.; Corvisiero, P.; Csedreki, L.; Davinson, T.; Depalo, R.; D'Erasmo, G.; Di Leva, A.; Elekes, Z.; Fiore, E. M.; Formicola, A.; Fülöp, Zs.; Gervino, G.; Guglielmetti, A.; Gustavino, C.; Gyürky, Gy.; Imbriani, G.; Junker, M.; Kochanek, I.; Lugaro, M.; Marcucci, L. E.; Marigo, P.; Menegazzo, R.; Pantaleo, F. R.; Paticchio, V.; Perrino, R.; Prati, P.; Schiavulli, L.; Stöckel, K.; Straniero, O.; Szücs, T.; Trezzi, D.; Zavatarelli, S.

2018-03-01

The experimental study of nuclear reactions of astrophysical interest is greatly facilitated by a low-background, high-luminosity setup. The Laboratory for Underground Nuclear Astrophysics (LUNA) 400kV accelerator offers ultra-low cosmic-ray induced background due to its location deep underground in the Gran Sasso National Laboratory (INFN-LNGS), Italy, and high intensity, 250-500μA, proton and α ion beams. In order to fully exploit these features, a high-purity, recirculating gas target system for isotopically enriched gases is coupled to a high-efficiency, six-fold optically segmented bismuth germanate (BGO) γ-ray detector. The beam intensity is measured with a beam calorimeter with constant temperature gradient. Pressure and temperature measurements have been carried out at several positions along the beam path, and the resultant gas density profile has been determined. Calibrated γ-intensity standards and the well-known Ep = 278 keV 14N(p,γ)15O resonance were used to determine the γ-ray detection efficiency and to validate the simulation of the target and detector setup. As an example, the recently measured resonance at Ep = 189.5 keV in the 22Ne(p,γ)23Na reaction has been investigated with high statistics, and the γ-decay branching ratios of the resonance have been determined.

Physics of grain boundaries in polycrystalline photovoltaic semiconductors

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

Yan, Yanfa, E-mail: yanfa.yan@utoledo.edu; Yin, Wan-Jian; Wu, Yelong

2015-03-21

Thin-film solar cells based on polycrystalline Cu(In,Ga)Se{sub 2} (CIGS) and CdTe photovoltaic semiconductors have reached remarkable laboratory efficiencies. It is surprising that these thin-film polycrystalline solar cells can reach such high efficiencies despite containing a high density of grain boundaries (GBs), which would seem likely to be nonradiative recombination centers for photo-generated carriers. In this paper, we review our atomistic theoretical understanding of the physics of grain boundaries in CIGS and CdTe absorbers. We show that intrinsic GBs with dislocation cores exhibit deep gap states in both CIGS and CdTe. However, in each solar cell device, the GBs can bemore » chemically modified to improve their photovoltaic properties. In CIGS cells, GBs are found to be Cu-rich and contain O impurities. Density-functional theory calculations reveal that such chemical changes within GBs can remove most of the unwanted gap states. In CdTe cells, GBs are found to contain a high concentration of Cl atoms. Cl atoms donate electrons, creating n-type GBs between p-type CdTe grains, forming local p-n-p junctions along GBs. This leads to enhanced current collections. Therefore, chemical modification of GBs allows for high efficiency polycrystalline CIGS and CdTe thin-film solar cells.« less

Exploration of Ultralight Nanofiber Aerogels as Particle Filters: Capacity and Efficiency.

PubMed

Deuber, Fabian; Mousavi, Sara; Federer, Lukas; Hofer, Marco; Adlhart, Christian

2018-03-14

Ultralight nanofiber aerogels (NFAs) or nanofiber sponges are a truly three-dimensional derivative of the intrinsically flat electrospun nanofiber mats or membranes (NFMs). Here we investigated the potential of such materials for particle or aerosol filtration because particle filtration is a major application of NFMs. Ultralight NFAs were synthesized from electrospun nanofibers using a solid-templating technique. These materials had a tunable hierarchical cellular open-pore structure. We observed high filtration efficiencies of up to 99.999% at the most penetrating particle size. By tailoring the porosity of the NFAs through the processing parameters, we were able to adjust the number of permeated particles by a factor of 1000 and the pressure drop by a factor of 9. These NFAs acted as a deep-bed filter, and they were capable of handling high dust loadings without any indication of performance loss or an increase in the pressure drop. When the face velocity was increased from 0.75 to 6 cm s -1 , the filtration efficiency remained high within a factor of 1.1-10. Both characteristics were in contrast to the behavior of two commercial NFM particle filters, which showed significant increases in the pressure drop with the filtration time as well as a susceptibility against high face velocities by a factor of 105.

Physics of grain boundaries in polycrystalline photovoltaic semiconductors

DOE PAGES

Yan, Yanfa; Yin, Wan-Jian; Wu, Yelong; ...

2015-03-16

Thin-film solar cells based on polycrystalline Cu(In,Ga)Se 2 (CIGS) and CdTe photovoltaic semiconductors have reached remarkable laboratory efficiencies. It is surprising that these thin-film polycrystalline solar cells can reach such high efficiencies despite containing a high density of grain boundaries (GBs), which would seem likely to be nonradiative recombination centers for photo-generated carriers. In this study, we review our atomistic theoretical understanding of the physics of grain boundaries in CIGS and CdTe absorbers. We show that intrinsic GBs with dislocation cores exhibit deep gap states in both CIGS and CdTe. Although, in each solar cell device, the GBs can bemore » chemically modified to improve their photovoltaic properties. In CIGS cells, GBs are found to be Cu-rich and contain O impurities. Density-functional theory calculations reveal that such chemical changes within GBs can remove most of the unwanted gap states. In CdTe cells, GBs are found to contain a high concentration of Cl atoms. Cl atoms donate electrons, creating n-type GBs between p-type CdTe grains, forming local p-n-p junctions along GBs. This leads to enhanced current collections. In conclusion, chemical modification of GBs allows for high efficiency polycrystalline CIGS and CdTe thin-film solar cells.« less

DEEP: Database of Energy Efficiency Performance

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

Hong, Tianzhen; Piette, Mary; Lee, Sang Hoon

A database of energy efficiency performance (DEEP) is a presimulated database to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 10 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER [sic] prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones.more » DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air conditioning, plug loads, and domestic hot war. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center (NERSC) of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of the CEC PIER project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users' decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit.« less

The Evolution of Deep Ocean Chemistry and Respired Carbon in the Eastern Equatorial Pacific Over the Last Deglaciation

NASA Astrophysics Data System (ADS)

de la Fuente, Maria; Calvo, Eva; Skinner, Luke; Pelejero, Carles; Evans, David; Müller, Wolfgang; Povea, Patricia; Cacho, Isabel

2017-12-01

It has been shown that the deep Eastern Equatorial Pacific (EEP) region was poorly ventilated during the Last Glacial Maximum (LGM) relative to Holocene values. This finding suggests a more efficient biological pump, which indirectly supports the idea of increased carbon storage in the deep ocean contributing to lower atmospheric CO2 during the last glacial. However, proxies related to respired carbon are needed in order to directly test this proposition. Here we present Cibicides wuellerstorfi B/Ca ratios from Ocean Drilling Program Site 1240 measured by laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) as a proxy for deep water carbonate saturation state (Δ[CO32-], and therefore [CO32-]), along with δ13C measurements. In addition, the U/Ca ratio in foraminiferal coatings has been analyzed as an indicator of oxygenation changes. Our results show lower [CO32-], δ13C, and [O2] values during the LGM, which would be consistent with higher respired carbon levels in the deep EEP driven, at least in part, by reduced deep water ventilation. However, the difference between LGM and Holocene [CO32-] observed at our site is relatively small, in accordance with other records from across the Pacific, suggesting that a "counteracting" mechanism, such as seafloor carbonate dissolution, also played a role. If so, this mechanism would have increased average ocean alkalinity, allowing even more atmospheric CO2 to be "sequestered" by the ocean. Therefore, the deep Pacific Ocean very likely stored a significant amount of atmospheric CO2 during the LGM, specifically due to a more efficient biological carbon pump and also an increase in average ocean alkalinity.

Thermal ink-jet device using single-chip silicon microchannels

NASA Astrophysics Data System (ADS)

Wuu, DongSing; Cheng, Chen-Yue; Horng, RayHua; Chan, G. C.; Chiu, Sao-Ling; Wu, Yi-Yung

1998-06-01

We present a new method to fabricate silicon microfluidic channels by through-hole etching with subsequent planarization. The method is based on etching out the deep grooves through a perforated silicon carbide membrane, followed by sealing the membrane with plasma-enhanced chemical vapor deposition (PECVD). Low-pressure-chemical-vapor- deposited (LPCVD) polysilicon was used as a sacrificial layer to define the channel structure and only one etching step is required. This permits the realization of planarization after a very deep etching step in silicon and offers the possibility for film deposition, resist spinning and film patterning across deep grooves. The process technology was demonstrated on the fabrication of a monolithic silicon microchannel structure for thermal inkjet printing. The Ta-Al heater arrays are integrated on the top of each microchannel, which connect to a common on-chip front-end ink reservoir. The fabrication of this device requires six masks and no active nozzle-to-chip alignment. Moreover, the present micromachining process is compatible with the addition of on-chip circuitry for multiplexing the heater control signals. Heat transfer efficiency to the ink is enhanced by the high thermal conductivity of the silicon carbide in the channel ceiling, while the bulk silicon maintains high interchannel isolation. The fabricated inkjet devices show the droplet sizes of 20 - 50 micrometer in diameter with various channel dimensions and stable ejection of ink droplets more than 1 million.

Porosity evolution at the brittle-ductile transition in the continental crust: Implications for deep hydro-geothermal circulation.

PubMed

Violay, M; Heap, M J; Acosta, M; Madonna, C

2017-08-09

Recently, projects have been proposed to engineer deep geothermal reservoirs in the ductile crust. To examine their feasibility, we performed high-temperature (up to 1000 °C), high-pressure (130 MPa) triaxial experiments on granite (initially-intact and shock-cooled samples) in which we measured the evolution of porosity during deformation. Mechanical data and post-mortem microstuctural characterisation (X-ray computed tomography and scanning electron microscopy) indicate that (1) the failure mode was brittle up to 900 °C (shear fracture formation) but ductile at 1000 °C (no strain localisation); (2) only deformation up to 800 °C was dilatant; (3) deformation at 900 °C was brittle but associated with net compaction due to an increase in the efficiency of crystal plastic processes; (4) ductile deformation at 1000 °C was compactant; (5) thermally-shocking the granite did not influence strength or failure mode. Our data show that, while brittle behaviour increases porosity, porosity loss is associated with both ductile behaviour and transitional behaviour as the failure mode evolves from brittle to ductile. Extrapolating our data to geological strain rates suggests that the brittle-ductile transition occurs at a temperature of 400 ± 100 °C, and is associated with the limit of fluid circulation in the deep continental crust.

Comparison of fabrication methods for microstructured deep UV multimode waveguides based on fused silica

NASA Astrophysics Data System (ADS)

Elmlinger, Philipp; Schreivogel, Martin; Schmid, Marc; Kaiser, Myriam; Priester, Roman; Sonström, Patrick; Kneissl, Michael

2016-04-01

The suitability of materials for deep ultraviolet (DUV) waveguides concerning transmittance, fabrication, and coupling properties is investigated and a fused silica core/ambient air cladding waveguide system is presented. This high refractive index contrast system has far better coupling efficiency especially for divergent light sources like LEDs and also a significantly smaller critical bending radius compared to conventional waveguide systems, as simulated by ray-tracing simulations. For the fabrication of 300-ffm-thick multimode waveguides a hydrouoric (HF) acid based wet etch process is compared to selective laser etching (SLE). In order to fabricate thick waveguides out of 300-ffm-thick silica wafers by HF etching, two masking materials, LPCVD silicon nitride and LPCVD poly silicon, are investigated. Due to thermal stress, the silicon nitride deposited wafers show cracks and even break. Using poly silicon as a masking material, no cracks are observed and deep etching in 50 wt% HF acid up to 180 min is performed. While the masked and unmasked silica surface is almost unchanged in terms of roughness, notching defects occur at the remaining polysilicon edge leading to jagged sidewalls. Using SLE, waveguides with high contour accuracy are fabricated and the DUV guiding properties are successfully demonstrated with propagation losses between 0.6 and 0:8 dB=mm. These values are currently limited by sidewall scattering losses.

Deep Energy Retrofit Guidance for the Building America Solutions Center

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

Less, Brennan; Walker, Iain

2015-01-01

The U.S. DOE Building America program has established a research agenda targeting market-relevant strategies to achieve 40% reductions in existing home energy use by 2030. Deep Energy Retrofits (DERs) are part of the strategy to meet and exceed this goal. DERs are projects that create new, valuable assets from existing residences, by bringing homes into alignment with the expectations of the 21st century. Ideally, high energy using, dated homes that are failing to provide adequate modern services to their owners and occupants (e.g., comfortable temperatures, acceptable humidity, clean, healthy), are transformed through comprehensive upgrades to the building envelope, services andmore » miscellaneous loads into next generation high performance homes. These guidance documents provide information to aid in the broader market adoption of DERs. They are intended for inclusion in the online resource the Building America Solutions Center (BASC). This document is an assemblage of multiple entries in the BASC, each of which addresses a specific aspect of Deep Energy Retrofit best practices for projects targeting at least 50% energy reductions. The contents are based upon a review of actual DERs in the U.S., as well as a mixture of engineering judgment, published guidance from DOE research in technologies and DERs, simulations of cost-optimal DERs, Energy Star and Consortium for Energy Efficiency (CEE) product criteria, and energy codes.« less

The Deep-Sea and Sub-Seafloor Frontier initiative - a key to link EC research and international scientific ocean drilling

NASA Astrophysics Data System (ADS)

Kopf, A.

2009-04-01

The Deep-Sea and Sub-Seafloor Frontiers project, DS3F, represents the continuation of the DSF roadmap towards the sustainable management of oceanic resources on a European scale. It will develop strategies for sub-seafloor sampling to contribute to a better understanding of deep-sea and sub-seafloor processes by connecting marine research in life and geosciences, climate and environmental change, as well as socio-economic issues and policy building. We propose to establish a long-lived research approach that considers (i) the need for a sustainable management of the ocean, and particularly the deep sea with enhanced activity (fishery, hydrocarbon exploration), (ii) the necessity to unravel deep-seated geological processes that drive seafloor ecosystems, and (iii) the value of seabed archives for the reconstruction of paleo-environmental conditions and the improved prediction of future climate change. Sub-seafloor drilling and sampling can provide two key components in understanding how deep-sea ecosystems function at present, and how they will respond to global change: (a) an inventory of present subsurface processes and biospheres, and their links to surface ecosystems, including seafloor observation and baseline studies, and (b) a high resolution archive of past variations in environmental conditions and biodiversity. For both components, an international effort is needed to share knowledge, methods and technologies, including mission-specific platforms to increase the efficiency, coverage and accuracy of sub-seafloor sampling and exploration. The deep biosphere has been discovered only within the past two decades and comprises the last major frontier for biological exploration. We lack fundamental knowledge of composition, diversity, distribution and metabolism in sub-seafloor biological communities at Earth's extremes, and their repercussions on seafloor ecosystems and life in the deep sea. There is equally an emerging need to shed light on geodynamic processes fuelling biological activity, and how such processes tie into the emission of geofuels and the formation of hydrocarbons and other resources. In addition, geodynamic processes may be cause natural hazards such as earthquake slip, submarine landslides, or tsunamis with a profound effect for humans and ecosystems. Their governing principles and potential triggers are poorly understood and often related to the sub-seafloor environment. In summary, the three main research areas in the Integrated Ocean Drilling Program (IODP; see Initial Science Plan www.iodp.org/isp/), i.e. geodynamics, climate and deep biosphere, as well as the goals of DS3F show a strong overlap and suggest an emerging need to join forces. This will result in the most efficient use of sub-seafloor sampling techniques and existing marine infrastructure to study the geosystem and its effects on biosphere and marine ecosystems. The DS3F initiative aims at providing a comprehensive "white paper" for a sustainable use of the oceans, an European Maritime Policy, and a strong link between European mission-specific drilling projects including IODP, IMAGES, ESF-EuroMARC and EC campaigns.

Development of AlGaN-based deep-ultraviolet (DUV) LEDs focusing on the fluorine resin encapsulation and the prospect of the practical applications

NASA Astrophysics Data System (ADS)

Hirano, Akira; Nagasawa, Yosuke; Ippommatsu, Masamichi; Aosaki, Ko; Honda, Yoshio; Amano, Hiroshi; Akasaki, Isamu

2016-09-01

AlGaN-based LEDs are expected to be useful for sterilization, deodorization, photochemical applications such as UV curing and UV printing, medical applications such as phototherapy, and sensing. Today, it has become clear that efficient AlGaN-based LED dies are producible between 355 and 250 nm with an external quantum efficiency (EQE) of 3% on flat sapphire. These dies were realized on flat sapphire without using a special technique, i.e., reduction in threading dislocation density or light extraction enhancement techniques such as the use of a photonic crystal or a patterned sapphire substrate. Despite the limited light extraction efficiency of about 8% owing to light absorption at a thick p-GaN contact layer, high EQEs of approximately 6% has been reproducible between 300 and 280 nm without using special techniques. Moreover, an EQE of 3.9% has been shown at 271 nm, despite the smaller current injection efficiency (CIE). The high EQEs are thought to correspond to the high internal quantum efficiency (IQE), indicating a small room for improving IQE. Accordingly, resin encapsulation on a simple submount is strongly desired. Recently, we have succeeded in demonstrating fluorine resin encapsulation on a ceramic sheet (chip-on-board, COB) that is massproducible. Furthermore, the molecular structure of a resin with a durability of more than 10,000 h is explained in this paper from the photochemical viewpoint. Thus, the key technologies of AlGaN-based DUV-LEDs having an EQE of 10% within a reasonable production cost have been established. The achieved efficiency makes AlGaN-based DUVLEDs comparable to high-pressure mercury lamps.

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

Chavez, III, Ramiro; Cai, Min; Tlach, Brian

Four new cross-conjugated small molecules based on a central benzo[1,2-d:4,5-d']bisoxazole moiety possessing semi-independently tunable HOMO and LUMO levels were synthesized and the properties of these materials were evaluated experimentally and theoretically. The molecules were thermally stable with 5% weight loss occurring well above 350 °C. The cruciforms all exhibited blue emission in solution ranging from 433–450 nm. Host–guest OLEDs fabricated from various concentrations of these materials using the small molecule host 4,4'-bis(9-carbazolyl)-biphenyl (CBP) exhibited deep blue-emission with Commission Internationale de L'Eclairage (CIE) coordinates of (0.15 ≤ x ≤ 0.17, 0.05 ≤ y ≤ 0.11), and maximum luminance efficiencies as highmore » as ~2 cd A–1. Lastly, these results demonstrate the potential of benzobisoxazole cruciforms as emitters for developing high-performance deep blue OLEDs.« less

Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia.

PubMed

Ratnadurai-Giridharan, Shivakeshavan; Cheung, Chung C; Rubchinsky, Leonid L

2017-11-01

Conventional deep brain stimulation of basal ganglia uses high-frequency regular electrical pulses to treat Parkinsonian motor symptoms but has a series of limitations. Relatively new and not yet clinically tested, optogenetic stimulation is an effective experimental stimulation technique to affect pathological network dynamics. We compared the effects of electrical and optogenetic stimulation of the basal gangliaon the pathologicalParkinsonian rhythmic neural activity. We studied the network response to electrical stimulation and excitatory and inhibitory optogenetic stimulations. Different stimulations exhibit different interactions with pathological activity in the network. We studied these interactions for different network and stimulation parameter values. Optogenetic stimulation was found to be more efficient than electrical stimulation in suppressing pathological rhythmicity. Our findings indicate that optogenetic control of neural synchrony may be more efficacious than electrical control because of the different ways of how stimulations interact with network dynamics.

Isotopic studies of epigenetic features in metalliferous sediment, Atlantis II Deep, Red Sea

USGS Publications Warehouse

Zierenberg, Robert A.; Shanks, Wayne C.

1988-01-01

The unique depositional environment of the Atlantis II Deep brine pool in the Red Sea produces a stratiform metalliferous deposit of greater areal extent than deposits formed by buoyant-plume systems typical of the midocean ridges because of much more efficient metal entrapment. Isotopic analyses of strontium, sulfur, carbon, and oxygen from the metalliferous sediments indicate that three major sources contribute dissolved components to the hydrothermal system: seawater, Miocene evaporites, and rift-zone basalt. An areally restricted magnetite-hematite-pyroxene assemblage formed at high temperatures, possibly in response to hydrothermal convection initiated by intrusion of basalt into the metalliferous sediment. A correlation between smectite Fe/(Fe+Mg) ratios and oxygen isotope temperatures suggests that smectite is a potentially important chemical geothermometer, and confirms geochemical calculations indicating that Mg-rich smectite is more stable than Fe-rich smectite at elevated temperatures.

Laser processing of ceramics for microelectronics manufacturing

NASA Astrophysics Data System (ADS)

Sposili, Robert S.; Bovatsek, James; Patel, Rajesh

2017-03-01

Ceramic materials are used extensively in the microelectronics, semiconductor, and LED lighting industries because of their electrically insulating and thermally conductive properties, as well as for their high-temperature-service capabilities. However, their brittleness presents significant challenges for conventional machining processes. In this paper we report on a series of experiments that demonstrate and characterize the efficacy of pulsed nanosecond UV and green lasers in machining ceramics commonly used in microelectronics manufacturing, such as aluminum oxide (alumina) and aluminum nitride. With a series of laser pocket milling experiments, fundamental volume ablation rate and ablation efficiency data were generated. In addition, techniques for various industrial machining processes, such as shallow scribing and deep scribing, were developed and demonstrated. We demonstrate that lasers with higher average powers offer higher processing rates with the one exception of deep scribes in aluminum nitride, where a lower average power but higher pulse energy source outperformed a higher average power laser.

Detection of a possible superluminous supernova in the epoch of reionization

NASA Astrophysics Data System (ADS)

Mould, Jeremy; Abbott, Tim; Cooke, Jeff; Curtin, Chris; Katsiani, Antonios; Koekemoer, Anton; Tescari, Edoardo; Uddin, Syed; Wang, Lifan; Wyithe, Stuaet

2017-04-01

An interesting transient has been detected in one of our three Dark Energy Camera deep fields. Observations of these deep fields take advantage of the high red sensitivity of DECam on the Cerro Tololo Interamerican Observatory Blanco telescope. The survey includes the Y band with rest wavelength 1430{Å} at z = 6. Survey fields (the Prime field 0555-6130, the 16hr field 1600-75 and the SUDSS New Southern Field) are deeper in Y than other infrared surveys. They are circumpolar, allowing all night to be used efficiently, exploiting the moon tolerance of 1 micron observations to minimize conflict with the Dark Energy Survey. As an i-band dropout (meaning that the flux decrement shortward of Lyman alpha is in the i bandpass), the transient we report here is a supernova candidate with z 6, with a luminosity comparable to the brightest known current epoch superluminous supernova (i.e., 2 x 10^11 solar luminosities).

Limiting factors in the production of deep microstructures

NASA Astrophysics Data System (ADS)

Tolfree, David W. L.; O'Neill, William; Tunna, Leslie; Sutcliffe, Christopher

1999-10-01

Microsystems increasingly require precision deep microstructures that can be cost-effectively designed and manufactured. New products must be able to meet the demands of the rapidly growing markets for microfluidic, micro- optical and micromechanical devices in industrial sectors which include chemicals, pharmaceuticals, biosciences, medicine and food. The realization of such products, first requires an effective process to design and manufacture prototypes. Two process methods used for the fabrication of high aspect-ratio microstructures are based on X-ray beam lithography with electroforming processes and direct micromachining with a frequency multiplied Nd:YAG laser using nanosecond pulse widths. Factors which limit the efficiency and precision obtainable using such processes are important parameters when deciding on the best fabrication method to use. A basic microstructure with narrow channels suitable for a microfluidic mixer have been fabricated using both these techniques and comparisons made of the limitations and suitability of the processes in respect of fast prototyping and manufacture or working devices.

Deep Space Network and Lunar Network Communication Coverage of the Moon

NASA Technical Reports Server (NTRS)

Lee, Charles H.; Cheung, Kar-Ming

2006-01-01

In this article, we describe the communication coverage analysis for the lunar network and the Earth ground stations. The first part of this article focuses on the direct communication coverage of the Moon from the Earth's ground stations. In particular, we assess the coverage performance of the Moon based on the existing Deep Space Network (DSN) antennas and the complimentary coverage of other potential stations at Hartebeesthoek, South Africa and at Santiago, Chile. We also address the coverage sensitivity based on different DSN antenna scenarios and their capability to provide single and redundant coverage of the Moon. The second part of this article focuses on the framework of the constrained optimization scheme to seek a stable constellation six relay satellites in two planes that not only can provide continuous communication coverage to any users on the Moon surface, but can also deliver data throughput in a highly efficient manner.

Enhanced and green extraction polyphenols and furanocoumarins from Fig (Ficus carica L.) leaves using deep eutectic solvents.

PubMed

Wang, Tong; Jiao, Jiao; Gai, Qing-Yan; Wang, Peng; Guo, Na; Niu, Li-Li; Fu, Yu-Jie

2017-10-25

Nowadays, green extraction of bioactive compounds from medicinal plants has gained increasing attention. As green solvent, deep eutectic solvent (DES) have been highly rated to replace toxic organic solvents in extraction process. In present study, to simultaneous extraction five main bioactive compounds from fig leaves, DES was tailor-made. The tailor-made DES composed of a 3:3:3 molar ratio of glycerol, xylitol and D-(-)-Fructose showed enhanced extraction yields for five target compounds simultaneously compared with traditional methanol and non-tailor DESs. Then, the tailor-made DES based extraction methods have compared and microwave-assisted extraction was selected and optimized due to its high extraction yields with lower time consumption. The influencing parameters including extraction temperature, liquid-solid ratio, and extraction time were optimized using response surface methodology (RSM). Under optimal conditions the extraction yield of caffeoylmalic acid, psoralic acid-glucoside, rutin, psoralen and bergapten was 6.482mg/g, 16.34mg/g, 5.207mg/g, 15.22mg/g and 2.475mg/g, respectively. Macroporous resin D101 has been used to recovery target compounds with recovery yields of 79.2%, 83.4%, 85.5%, 81.2% and 75.3% for caffeoylmalic acid, psoralic acid-glucoside, rutin, psoralen and bergapten, respectively. The present study suggests that DESs are truly designer and efficient solvents and the method we developed was efficient and sustainable for extraction main compounds from Fig leaves.mg/g. Copyright © 2017 Elsevier B.V. All rights reserved.

The Sulu Sea as Carbon Dioxide Sink

NASA Astrophysics Data System (ADS)

Ferrera, C. M.; Jacinto, G. S.; Chen, C. T. A.

2016-12-01

The Sulu Sea, one of the marginal seas in the West Pacific and the largest internal sea in the Philippines, is characterized by its unique deep water ventilation pattern and high sediment organic carbon and CaCO3 content. Studies on the dissolved CO2 system in the Sulu Sea have remarkably shown that anthropogenic CO2 has already penetrated to the bottom of this 5km-deep basin, albeit limited to a dataset from a single station in December 1996. To further understand the role of this tropical marginal sea as CO2 sink and to assess its behavior as a CO2 sink during the 11-year period, water samples for dissolved CO2 parameters from two deep stations of high productivity and low productivity were collected in December 2007/January 2008 and were compared with the 1996 data. Results suggest that the surface waters in the low productivity region might have been acidifying at a rate of -0.0012 pH unit yr-1. Atmospheric CO2 increased at +1.9 ppmv yr-1 and seawater fCO2 at +3.30 μatm yr-1. Through deep water ventilation, anthropogenic CO2 has penetrated the water column thereby making the deeper waters a sink of anthropogenic CO2. But then the presence and dissolution of CaCO3 deposits at the sea floor and along the Sulu Sea slopes as a result of the reaction with this anthropogenic CO2 probably neutralizes the acidification at depths as shown by the increase in total alkalinity (+0.57 μmol kg-1 yr-1), and facilitates further uptake of CO2 from the atmosphere. Therefore, productivity at Sulu Sea surface waters results to sequestration of CO2 from the atmosphere to the sediment sink through organic carbon and CaCO3 deposits. While high temperature and low productivity surface waters make the Sulu Sea a source of CO2 to the atmosphere, ventilation patterns make the deep waters of the Sulu Sea an efficient sink for anthropogenic CO2. Given the larger area occupied by the CO2 sink deep waters compared to the CO2 source surface waters including an upwelling area, the Sulu Sea could possibly be a "net" CO2 sink, an important contribution to the otherwise underestimated inventory of CO2 from marginal seas.

Lead isotopes in North Pacific deep water - Implications for past changes in input sources and circulation patterns

USGS Publications Warehouse

van de Flierdt, T.; Frank, M.; Halliday, A.N.; Hein, J.R.; Hattendorf, B.; Gunther, D.; Kubik, P.W.

2003-01-01

The sources of non-anthropogenic Pb in seawater have been the subject of debate. Here we present Pb isotope time-series that indicate that the non-anthropogenic Pb budget of the northernmost Pacific Ocean has been governed by ocean circulation and riverine inputs, which in turn have ultimately been controlled by tectonic processes. Despite the fact that the investigated locations are situated within the Asian dust plume, and proximal to extensive arc volcanism, eolian contributions have had little impact. We have obtained the first high-resolution and high-precision Pb isotope time-series of North Pacific deep water from two ferromanganese crusts from the Gulf of Alaska in the NE Pacific Ocean, and from the Detroit Seamount in the NW Pacific Ocean. Both crusts were dated applying 10 Be/9Be ratios and yield continuous time-series for the past 13.5 and 9.6 Myr, respectively. Lead isotopes show a monotonic evolution in 206Pb/204Pb from low values in the Miocene (??? 18.57) to high values at present day (??? 18.84) in both crusts, even though they are separated by more than 3000 km along the Aleutian Arc. The variation exceeds the amplitude found in Equatorial Pacific deep water records by about three-fold. There also is a striking similarity in 207Pb/204Pb and 208Pb/ 204Pb ratios of the two crusts, indicating the existence of a local circulation cell in the sub-polar North Pacific, where efficient lateral mixing has taken place but only limited exchange (in terms of Pb) with deep water from the Equatorial Pacific has occurred. Both crusts display well-defined trends with age in Pb-Pb isotope mixing plots, which require the involvement of at least four distinct Pb sources for North Pacific deep water. The Pb isotope time-series reveal that eolian supplies (volcanic ash and continent-derived loess) have only been of minor importance for the dissolved Pb budget of marginal sites in the deep North Pacific over the past 6 Myr. The two predominant sources have been young volcanic arcs, one located in the northeastern part and one located in the northwestern part of the Pacific margin, from where material has been eroded and delivered to the ocean, most likely via riverine pathways. ?? 2003 Elsevier Science B.V. All rights reserved.

A Neutron Multiplicity Meter for Deep Underground Muon-Induced High Energy Neutron Measurements

NASA Astrophysics Data System (ADS)

Hennings-Yeomans, Raul; Akerib, Daniel

2007-04-01

The nature of dark matter is one of the most important outstanding issues in particle physics, cosmology and astrophysics. A leading hypothesis is that Weakly Interacting Massive Particles, or WIMPs, were produced in the early universe and make up the dark matter. WIMP searches must be performed underground to shield from cosmic rays, which produce secondary particles that could fake a WIMP signal. Nuclear recoils from fast neutrons in underground laboratories are one of the most challenging backgrounds to WIMP detection. We present, for the first time, the design of an instrument capable of measuring the high energy (>60,eV) muon-induced neutron flux deep underground. The instrument is based on applying the Gd-loaded liquid-scintillator technique to measure the rate of multiple low energy neutron events produced in a Pb target and from this measurement to infer the rate of high energy neutron events. This unique signature allows both for efficient tagging of neutron multiplicity events as well as rejection of random gamma backgrounds so effectively that typical low-background techniques are not required. We will also discuss the benefits of using a neutron multiplicity meter as a component of active shielding.

THE DEEP2 GALAXY REDSHIFT SURVEY: THE VORONOI-DELAUNAY METHOD CATALOG OF GALAXY GROUPS

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

Gerke, Brian F.; Newman, Jeffrey A.; Davis, Marc

2012-05-20

We present a public catalog of galaxy groups constructed from the spectroscopic sample of galaxies in the fourth data release from the Deep Extragalactic Evolutionary Probe 2 (DEEP2) Galaxy Redshift Survey, including the Extended Groth Strip (EGS). The catalog contains 1165 groups with two or more members in the EGS over the redshift range 0 < z < 1.5 and 1295 groups at z > 0.6 in the rest of DEEP2. Twenty-five percent of EGS galaxies and fourteen percent of high-z DEEP2 galaxies are assigned to galaxy groups. The groups were detected using the Voronoi-Delaunay method (VDM) after it hasmore » been optimized on mock DEEP2 catalogs following similar methods to those employed in Gerke et al. In the optimization effort, we have taken particular care to ensure that the mock catalogs resemble the data as closely as possible, and we have fine-tuned our methods separately on mocks constructed for the EGS and the rest of DEEP2. We have also probed the effect of the assumed cosmology on our inferred group-finding efficiency by performing our optimization on three different mock catalogs with different background cosmologies, finding large differences in the group-finding success we can achieve for these different mocks. Using the mock catalog whose background cosmology is most consistent with current data, we estimate that the DEEP2 group catalog is 72% complete and 61% pure (74% and 67% for the EGS) and that the group finder correctly classifies 70% of galaxies that truly belong to groups, with an additional 46% of interloper galaxies contaminating the catalog (66% and 43% for the EGS). We also confirm that the VDM catalog reconstructs the abundance of galaxy groups with velocity dispersions above {approx}300 km s{sup -1} to an accuracy better than the sample variance, and this successful reconstruction is not strongly dependent on cosmology. This makes the DEEP2 group catalog a promising probe of the growth of cosmic structure that can potentially be used for cosmological tests.« less

Variability of neodymium isotopes associated with planktonic foraminifera in the Pacific Ocean during the Holocene and Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Hu, Rong; Piotrowski, Alexander M.; Bostock, Helen C.; Crowhurst, Simon; Rennie, Victoria

2016-08-01

The deep Pacific Ocean holds the largest oceanic reservoir of carbon which may interchange with the atmosphere on climatologically important timescales. The circulation of the deep Pacific during the Last Glacial Maximum (LGM), however, is not well understood. Neodymium (Nd) isotopes of ferromanganese oxide coatings precipitated on planktonic foraminifera are a valuable proxy for deep ocean water mass reconstruction in paleoceanography. In this study, we present Nd isotope compositions (εNd) of planktonic foraminifera for the Holocene and the LGM obtained from 55 new sites widely distributed in the Pacific Ocean. The Holocene planktonic foraminiferal εNd results agree with the proximal seawater data, indicating that they provide a reliable record of modern bottom water Nd isotopes in the deep Pacific. There is a good correlation between foraminiferal εNd and seawater phosphate concentrations (R2 = 0.80), but poorer correlation with silicate (R2 = 0.37). Our interpretation is that the radiogenic Nd isotope is added to the deep open Pacific through particle release from the upper ocean during deep water mass advection and aging. The data thus also imply the Nd isotopes in the Pacific are not likely to be controlled by silicate cycling. In the North Pacific, the glacial Nd isotopic compositions are similar to the Holocene values, indicating that the Nd isotope composition of North Pacific Deep Water (NPDW) remained constant (-3.5 to -4). During the LGM, the southwest Pacific cores throughout the water column show higher εNd corroborating previous studies which suggested a reduced inflow of North Atlantic Deep Water to the Pacific. However, the western equatorial Pacific deep water does not record a corresponding radiogenic excursion, implying reduced radiogenic boundary inputs during the LGM probably due to a shorter duration of seawater-particle interaction in a stronger glacial deep boundary current. A significant negative glacial εNd excursion is evident in mid-depth (1-2 km) cores of the eastern equatorial Pacific (EEP) which may suggest a stronger influence of NPDW return flow to the core sites and decreased local input in the EEP. Taken together, our Nd records do not support a dynamically slower glacial Pacific overturning circulation, and imply that the increased carbon inventory of Pacific deep water might be due to poor high latitude air-sea exchange and increased biological pump efficiency in glacial times.

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

PubMed

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.

Dopantless Diodes for Efficient Mid/deep UV LEDs and Lasers - Topic 4.2 Optoelectronics

DTIC Science & Technology

2017-09-12

Week, Santa Barbara, CA, “Polarization hole engineering in deep- ultraviolet nanowire LEDs”, ATM Sarwar, Santino Carnevale, Thomas Kent, Brelon May...Electronic Materials Conference, Santa Barbara, California, “ Engineering the polarization hole doping of graded nanowire ultraviolet LEDs integrated on...Nanostructures for Optoelectronic and Magnetic Functionalities: Growth, Characterization and Engineering Publication Type: Thesis or Dissertation

Deep Filter Banks for Texture Recognition, Description, and Segmentation.

PubMed

Cimpoi, Mircea; Maji, Subhransu; Kokkinos, Iasonas; Vedaldi, Andrea

Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descriptors in an orderless manner have had a tremendous impact in diverse applications. In this paper we make several contributions to texture understanding. First, instead of focusing on texture instance and material category recognition, we propose a human-interpretable vocabulary of texture attributes to describe common texture patterns, complemented by a new describable texture dataset for benchmarking. Second, we look at the problem of recognizing materials and texture attributes in realistic imaging conditions, including when textures appear in clutter, developing corresponding benchmarks on top of the recently proposed OpenSurfaces dataset. Third, we revisit classic texture represenations, including bag-of-visual-words and the Fisher vectors, in the context of deep learning and show that these have excellent efficiency and generalization properties if the convolutional layers of a deep model are used as filter banks. We obtain in this manner state-of-the-art performance in numerous datasets well beyond textures, an efficient method to apply deep features to image regions, as well as benefit in transferring features from one domain to another.

Multi-label spacecraft electrical signal classification method based on DBN and random forest

PubMed Central

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data. PMID:28486479

Multi-label spacecraft electrical signal classification method based on DBN and random forest.

PubMed

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data.

Sterilization of Exopolysaccharides Produced by Deep-Sea Bacteria: Impact on Their Stability and Degradation

PubMed Central

Rederstorff, Emilie; Fatimi, Ahmed; Sinquin, Corinne; Ratiskol, Jacqueline; Merceron, Christophe; Vinatier, Claire; Weiss, Pierre; Colliec-Jouault, Sylvia

2011-01-01

Polysaccharides are highly heat-sensitive macromolecules, so high temperature treatments are greatly destructive and cause considerable damage, such as a great decrease in both viscosity and molecular weight of the polymer. The technical feasibility of the production of exopolysaccharides by deep-sea bacteria Vibrio diabolicus and Alteromonas infernus was previously demonstrated using a bioproduct manufacturing process. The objective of this study was to determine which sterilization method, other than heat sterilization, was the most appropriate for these marine exopolysaccharides and was in accordance with bioprocess engineering requirements. Chemical sterilization using low-temperature ethylene oxide and a mixture of ionized gases (plasmas) was compared to the sterilization methods using gamma and beta radiations. The changes to both the physical and chemical properties of the sterilized exopolysaccharides were analyzed. The use of ethylene oxide can be recommended for the sterilization of polysaccharides as a weak effect on both rheological and structural properties was observed. This low-temperature gas sterilizing process is very efficient, giving a good Sterility Assurance Level (SAL), and is also well suited to large-scale compound manufacturing in the pharmaceutical industry. PMID:21566796

Deep dewatering process of sludge by chemical conditioning and its potential influence on wastewater treatment plants.

PubMed

Wang, Shuo; Ma, Cong; Zhu, Yin; Yang, Yangkun; Du, Guocheng; Li, Ji

2018-06-15

FeCl 3 , quick lime, and cationic polyacrylamide (CPAM) were used for excess sludge conditioning from wastewater treatment plant (WWTP) and the dewatering performance by different chemical conditioners was investigated. Experimental results showed that FeCl 3 could make small and concentrated sludge particles. Furthermore, new mineral phase structures for building a dewatering framework were obtained by the addition of quick lime, and the coagulation capacity was enhanced by the formation of colloid hydroxyl polymer, which was induced due to the alkaline environment. In addition, the floc particle size significantly increased after the CPAM dosage. The bound water could be released with the stripping of tightly bound extracellular polymeric substance (EPS). Therefore, the dewatering performance and efficiencies were improved and subsequently the hypothetical sludge deep dewatering process was depicted in accordance with the variation of EPS. However, high-strength refractory organics in sludge filtrates caused by quick lime pyrolysis could lead to the unstable operation of the WWTP, because the relatively high concentrations of organic compounds with benzene were dominant in sludge dewatering filtrates.

Classification with an edge: Improving semantic image segmentation with boundary detection

NASA Astrophysics Data System (ADS)

Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

2018-01-01

We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

Video-rate functional photoacoustic microscopy at depths

NASA Astrophysics Data System (ADS)

Wang, Lidai; Maslov, Konstantin; Xing, Wenxin; Garcia-Uribe, Alejandro; Wang, Lihong V.

2012-10-01

We report the development of functional photoacoustic microscopy capable of video-rate high-resolution in vivo imaging in deep tissue. A lightweight photoacoustic probe is made of a single-element broadband ultrasound transducer, a compact photoacoustic beam combiner, and a bright-field light delivery system. Focused broadband ultrasound detection provides a 44-μm lateral resolution and a 28-μm axial resolution based on the envelope (a 15-μm axial resolution based on the raw RF signal). Due to the efficient bright-field light delivery, the system can image as deep as 4.8 mm in vivo using low excitation pulse energy (28 μJ per pulse, 0.35 mJ/cm2 on the skin surface). The photoacoustic probe is mounted on a fast-scanning voice-coil scanner to acquire 40 two-dimensional (2-D) B-scan images per second over a 9-mm range. High-resolution anatomical imaging is demonstrated in the mouse ear and brain. Via fast dual-wavelength switching, oxygen dynamics of mouse cardio-vasculature is imaged in realtime as well.

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

NASA Astrophysics Data System (ADS)

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 Lake Huron that resemble deep-sea seep and vent communities.

Meltwater routing and the Younger Dryas.

PubMed

Condron, Alan; Winsor, Peter

2012-12-04

The Younger Dryas--the last major cold episode on Earth--is generally considered to have been triggered by a meltwater flood into the North Atlantic. The prevailing hypothesis, proposed by Broecker et al. [1989 Nature 341:318-321] more than two decades ago, suggests that an abrupt rerouting of Lake Agassiz overflow through the Great Lakes and St. Lawrence Valley inhibited deep water formation in the subpolar North Atlantic and weakened the strength of the Atlantic Meridional Overturning Circulation (AMOC). More recently, Tarasov and Peltier [2005 Nature 435:662-665] showed that meltwater could have discharged into the Arctic Ocean via the Mackenzie Valley ~4,000 km northwest of the St. Lawrence outlet. Here we use a sophisticated, high-resolution, ocean sea-ice model to study the delivery of meltwater from the two drainage outlets to the deep water formation regions in the North Atlantic. Unlike the hypothesis of Broecker et al., freshwater from the St. Lawrence Valley advects into the subtropical gyre ~3,000 km south of the North Atlantic deep water formation regions and weakens the AMOC by <15%. In contrast, narrow coastal boundary currents efficiently deliver meltwater from the Mackenzie Valley to the deep water formation regions of the subpolar North Atlantic and weaken the AMOC by >30%. We conclude that meltwater discharge from the Arctic, rather than the St. Lawrence Valley, was more likely to have triggered the Younger Dryas cooling.

The Deep Impact Network Experiment Operations Center

NASA Technical Reports Server (NTRS)

Torgerson, J. Leigh; Clare, Loren; Wang, Shin-Ywan

2009-01-01

Delay/Disruption Tolerant Networking (DTN) promises solutions in solving space communications challenges arising from disconnections as orbiters lose line-of-sight with landers, long propagation delays over interplanetary links, and other phenomena. DTN has been identified as the basis for the future NASA space communications network backbone, and international standardization is progressing through both the Consultative Committee for Space Data Systems (CCSDS) and the Internet Engineering Task Force (IETF). JPL has developed an implementation of the DTN architecture, called the Interplanetary Overlay Network (ION). ION is specifically implemented for space use, including design for use in a real-time operating system environment and high processing efficiency. In order to raise the Technology Readiness Level of ION, the first deep space flight demonstration of DTN is underway, using the Deep Impact (DI) spacecraft. Called the Deep Impact Network (DINET), operations are planned for Fall 2008. An essential component of the DINET project is the Experiment Operations Center (EOC), which will generate and receive the test communications traffic as well as "out-of-DTN band" command and control of the DTN experiment, store DTN flight test information in a database, provide display systems for monitoring DTN operations status and statistics (e.g., bundle throughput), and support query and analyses of the data collected. This paper describes the DINET EOC and its value in the DTN flight experiment and potential for further DTN testing.

The diagnostic management of upper extremity deep vein thrombosis: A review of the literature.

PubMed

Kraaijpoel, Noémie; van Es, Nick; Porreca, Ettore; Büller, Harry R; Di Nisio, Marcello

2017-08-01

Upper extremity deep vein thrombosis (UEDVT) accounts for 4% to 10% of all cases of deep vein thrombosis. UEDVT may present with localized pain, erythema, and swelling of the arm, but may also be detected incidentally by diagnostic imaging tests performed for other reasons. Prompt and accurate diagnosis is crucial to prevent pulmonary embolism and long-term complications as the post-thrombotic syndrome of the arm. Unlike the diagnostic management of deep vein thrombosis (DVT) of the lower extremities, which is well established, the work-up of patients with clinically suspected UEDVT remains uncertain with limited evidence from studies of small size and poor methodological quality. Currently, only one prospective study evaluated the use of an algorithm, similar to the one used for DVT of the lower extremities, for the diagnostic workup of clinically suspected UEDVT. The algorithm combined clinical probability assessment, D-dimer testing and ultrasonography and appeared to safely and effectively exclude UEDVT. However, before recommending its use in routine clinical practice, external validation of this strategy and improvements of the efficiency are needed, especially in high-risk subgroups in whom the performance of the algorithm appeared to be suboptimal, such as hospitalized or cancer patients. In this review, we critically assess the accuracy and efficacy of current diagnostic tools and provide clinical guidance for the diagnostic management of clinically suspected UEDVT. Copyright © 2017 Elsevier Ltd. All rights reserved.

Learning from Past Classification Errors: Exploring Methods for Improving the Performance of a Deep Learning-based Building Extraction Model through Quantitative Analysis of Commission Errors for Optimal Sample Selection

NASA Astrophysics Data System (ADS)

Swan, B.; Laverdiere, M.; Yang, L.

2017-12-01

In the past five years, deep Convolutional Neural Networks (CNN) have been increasingly favored for computer vision applications due to their high accuracy and ability to generalize well in very complex problems; however, details of how they function and in turn how they may be optimized are still imperfectly understood. In particular, their complex and highly nonlinear network architecture, including many hidden layers and self-learned parameters, as well as their mathematical implications, presents open questions about how to effectively select training data. Without knowledge of the exact ways the model processes and transforms its inputs, intuition alone may fail as a guide to selecting highly relevant training samples. Working in the context of improving a CNN-based building extraction model used for the LandScan USA gridded population dataset, we have approached this problem by developing a semi-supervised, highly-scalable approach to select training samples from a dataset of identified commission errors. Due to the large scope this project, tens of thousands of potential samples could be derived from identified commission errors. To efficiently trim those samples down to a manageable and effective set for creating additional training sample, we statistically summarized the spectral characteristics of areas with rates of commission errors at the image tile level and grouped these tiles using affinity propagation. Highly representative members of each commission error cluster were then used to select sites for training sample creation. The model will be incrementally re-trained with the new training data to allow for an assessment of how the addition of different types of samples affects the model performance, such as precision and recall rates. By using quantitative analysis and data clustering techniques to select highly relevant training samples, we hope to improve model performance in a manner that is resource efficient, both in terms of training process and in sample creation.

Survey report of NOAA Ship McArthur II cruises AR-04-04, AR-05-05 and AR-06-03: habitat classification of side scan sonar imagery in support of deep-sea coral/sponge explorations at the Olympic Coast National Marine Sanctuary

USGS Publications Warehouse

Intelmann, Steven S.; Cochrane, Guy R.; Bowlby, C. Edward; Brancato, Mary Sue; Hyland, Jeffrey

2007-01-01

Habitat mapping and characterization has been defined as a high-priority management issue for the Olympic Coast National Marine Sanctuary (OCNMS), especially for poorly known deep-sea habitats that may be sensitive to anthropogenic disturbance. As a result, a team of scientists from OCNMS, National Centers for Coastal Ocean Science (NCCOS), and other partnering institutions initiated a series of surveys to assess the distribution of deep-sea coral/sponge assemblages within the sanctuary and to look for evidence of potential anthropogenic impacts in these critical habitats. Initial results indicated that remotely delineating areas of hard bottom substrate through acoustic sensing could be a useful tool to increase the efficiency and success of subsequent ROV-based surveys of the associated deep-sea fauna. Accordingly, side scan sonar surveys were conducted in May 2004, June 2005, and April 2006 aboard the NOAA Ship McArthur II to: (1) obtain additional imagery of the seafloor for broader habitat-mapping coverage of sanctuary waters, and (2) help delineate suitable deep-sea coral-sponge habitat, in areas of both high and low commercial-fishing activities, to serve as sites for surveying-in more detail using an ROV on subsequent cruises, Several regions of the sea floor throughout the OCNMS were surveyed and mosaicked at 1-meter pixel resolution. Imagery from the side scan sonar mapping efforts was integrated with other complementary data from a towed camera sled, ROVs, sedentary samples, and bathymetry records to describe geological and biological (where possible) aspects of habitat. Using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999), we created a preliminary map of various habitat polygon features for use in a geographical information system (GIS). This report provides a description of the mapping and groundtruthing efforts as well as results of the image classification procedure for each of the areas surveyed.

DEEP: A Database of Energy Efficiency Performance to Accelerate Energy Retrofitting of Commercial Buildings

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

Hoon Lee, Sang; Hong, Tianzhen; Sawaya, Geof

The paper presents a method and process to establish a database of energy efficiency performance (DEEP) to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 35 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER prototype buildings. The prototype buildings represent seven building types across six vintages of constructions andmore » 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and domestic hot water. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of an on-going project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users’ decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit. DEEP will be migrated into the DEnCity - DOE’s Energy City, which integrates large-scale energy data for multi-purpose, open, and dynamic database leveraging diverse source of existing simulation data.« less

A highly efficient and compact long pulse Nd:YAG rod laser with 540 J of pulse energy for welding application.

PubMed

Choubey, Ambar; Vishwakarma, S C; Misra, Pushkar; Jain, R K; Agrawal, D K; Arya, R; Upadhyaya, B N; Oak, S M

2013-07-01

We have developed an efficient and high average power flash lamp pumped long pulse Nd:YAG laser capable of generating 1 kW of average output power with maximum 540 J of single pulse energy and 20 kW of peak power. The laser pulse duration can be varied from 1 to 40 ms and repetition rate from 1 to 100 Hz. A compact and robust laser pump chamber and resonator was designed to achieve this high average and peak power. It was found that this laser system provides highest single pulse energy as compared to other long pulsed Nd:YAG laser systems of similar rating. A slope efficiency of 5.4% has been achieved, which is on higher side for typical lamp pumped solid-state lasers. This system will be highly useful in laser welding of materials such as aluminium and titanium. We have achieved 4 mm deep penetration welding of these metals under optimized conditions of output power, pulse energy, and pulse duration. The laser resonator was optimized to provide stable operation from single shot to 100 Hz of repetition rate. The beam quality factor was measured to be M(2) ~ 91 and pulse-to-pulse stability of ±3% for the multimode operation. The laser beam was efficiently coupled through an optical fiber of 600 μm core diameter and 0.22 numerical aperture with power transmission of 90%.

Deep learning for medical image segmentation - using the IBM TrueNorth neurosynaptic system

NASA Astrophysics Data System (ADS)

Moran, Steven; Gaonkar, Bilwaj; Whitehead, William; Wolk, Aidan; Macyszyn, Luke; Iyer, Subramanian S.

2018-03-01

Deep convolutional neural networks have found success in semantic image segmentation tasks in computer vision and medical imaging. These algorithms are executed on conventional von Neumann processor architectures or GPUs. This is suboptimal. Neuromorphic processors that replicate the structure of the brain are better-suited to train and execute deep learning models for image segmentation by relying on massively-parallel processing. However, given that they closely emulate the human brain, on-chip hardware and digital memory limitations also constrain them. Adapting deep learning models to execute image segmentation tasks on such chips, requires specialized training and validation. In this work, we demonstrate for the first-time, spinal image segmentation performed using a deep learning network implemented on neuromorphic hardware of the IBM TrueNorth Neurosynaptic System and validate the performance of our network by comparing it to human-generated segmentations of spinal vertebrae and disks. To achieve this on neuromorphic hardware, the training model constrains the coefficients of individual neurons to {-1,0,1} using the Energy Efficient Deep Neuromorphic (EEDN)1 networks training algorithm. Given the 1 million neurons and 256 million synapses, the scale and size of the neural network implemented by the IBM TrueNorth allows us to execute the requisite mapping between segmented images and non-uniform intensity MR images >20 times faster than on a GPU-accelerated network and using <0.1 W. This speed and efficiency implies that a trained neuromorphic chip can be deployed in intra-operative environments where real-time medical image segmentation is necessary.

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

NASA Astrophysics Data System (ADS)

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.

The effect of aerosol-derived changes in the warm phase on the properties of deep convective clouds

NASA Astrophysics Data System (ADS)

Chen, Qian; Koren, Ilan; Altaratz, Orit; Heiblum, Reuven; Dagan, Guy

2017-04-01

The aerosol impact on deep convective clouds starts in an increased number of cloud droplets in higher aerosol loading environment. This change drives many others, like enhanced condensational growth, delay in collision-coalescence and others. Since the warm processes serve as the initial and boundary conditions for the mixed and cold-phase processes in deep clouds, it is highly important to understand the aerosol effect on them. The weather research and forecasting model (WRF) with spectral bin microphysics was used to study a deep convective system over the Marshall Islands, during the Kwajalein Experiment (KWAJEX). Three simulations were conducted with aerosol concentrations of 100, 500 and 2000 cm-3, to reflect clean, semipolluted, and polluted conditions. The results of the clean run agreed well with the radar profiles and rain rate observations. The more polluted simulations resulted in larger total cloud mass, larger upper level cloud fraction and rain rates. There was an increased mass both below and above the zero temperature level. It indicates of more efficient growth processes both below and above the zero level. In addition the polluted runs showed an increased upward transport (across the zero level) of liquid water due to both stronger updrafts and larger droplet mobility. In this work we discuss the transport of cloud mass crossing the zero temperature level (in both directions) in order to gain a process level understanding of how aerosol effects on the warm processes affect the macro- and micro-properties of deep convective clouds.

White OLED devices and processes for lighting applications

NASA Astrophysics Data System (ADS)

Ide, Nobuhiro; Tsuji, Hiroya; Ito, Norihiro; Matsuhisa, Yuko; Houzumi, Shingo; Nishimori, Taisuke

2010-05-01

In these days, the basic performances of white OLEDs are dramatically improved and application of OLEDs to "Lighting" is expected to be true in the near future. We have developed various technologies for OLED lighting with the aid of the Japanese governmental project, "High-efficiency lighting based on the organic light-emitting mechanism." In this project, a white OLED with high efficiency (37 lm/W) and high quality emission characteristics (CRI of 95 with a small variation of chromaticity in different directions and chromaticity just on the black-body radiation curve) applicable to "Lighting" was realized by a two-unit structure with a fluorescent deep blue emissive unit and a phosphorescent green and red emissive unit. Half-decay lifetime of this white OLED at 1,000 cd/m2 was over 40,000 h. A heat radiative, thin encapsulation structure (less than 1 mm) realized a very stable emission at high luminance of over 3,000 cd/m2. A new deposition source with a hot-wall and a rate controllable valve was developed. Thickness uniformity within +/- 3% at high deposition rate of over 8 nm/s, high material utilization of over 70 %, and repeatable deposition rate controllability were confirmed.

Crystal growth and optical characteristics of beryllium-free polyphosphate, KLa(PO3)4, a possible deep-ultraviolet nonlinear optical crystal

NASA Astrophysics Data System (ADS)

Shan, Pai; Sun, Tongqing; Chen, Hong; Liu, Hongde; Chen, Shaolin; Liu, Xuanwen; Kong, Yongfa; Xu, Jingjun

2016-04-01

Deep-ultraviolet nonlinear optical crystals are of great importance as key materials in generating coherent light with wavelength below 200 nm through cascaded frequency conversion of solid-state lasers. However, the solely usable crystal in practice, KBe2BO3F2 (KBBF), is still commercially unavailable because of the high toxicity of beryllium-containing and the extreme difficulty of crystal growth. Here, we report the crystal growth and characteristics of an beryllium-free polyphosphate, KLa(PO3)4. Centimeter-sized single crystals have been easily obtained by the flux method and slow-cooling technique. The second-harmonic generation efficiency of KLa(PO3)4 powder is 0.7 times that of KH2PO4; moreover, the KLa(PO3)4 crystal is phase-matchable. Remarkably, the KLa(PO3)4 crystal exhibits an absorption edge of 162 nm, which is the shortest among phase-matchable phosphates so far. These attributes make KLa(PO3)4 a possible deep-ultraviolet nonlinear optical crystal. An analysis of the dipole moments of the polyhedra and theoretical calculations by density functional theory were made to elucidate the structure-properties relationships of KLa(PO3)4.

Ultra-wideband filtering of spoof surface plasmon polaritons using deep subwavelength planar structures

PubMed Central

Hu, Ming Zhe; Zhang, Hao Chi; Yin, Jia Yuan; Ding, Zhao; Liu, Jun Feng; Tang, Wen Xuan; Cui, Tie Jun

2016-01-01

Novel ultra-wideband filtering of spoof surface plasmon polaritons (SPPs) is proposed in the microwave frequency using deep subwavelength planar structures printed on thin and flexible dielectric substrate. The proposed planar SPPs waveguide is composed of two mirror-oriented metallic corrugated strips, which are further decorated with parallel-arranged slots in the main corrugated strips. This compound structure provides deep subwavelength field confinement as well as flexible parameters when employed as a plasmonic waveguide, which is potential to construct miniaturization. Using momentum and impedance matching technology, we achieve a smooth conversion between the proposed SPPs waveguide and the conventional transmission line. To verify the validity of the design, we fabricate a spoof SPPs filter, and the measured results illustrate excellent performance, in which the reflection coefficient is less than −10 dB within the −3 dB passband from 1.21 GHz to 7.21 GHz with the smallest insertion loss of 1.23 dB at 2.21 GHz, having very good agreements with numerical simulations. The ultra-wideband filter with low insertion loss and high transmission efficiency possesses great potential in modern communication systems. PMID:27883028