Energy demand for materials in an international context.

PubMed

Worrell, Ernst; Carreon, Jesus Rosales

2017-06-13

Materials are everywhere and have determined society. The rapid increase in consumption of materials has led to an increase in the use of energy and release of greenhouse gas (GHG) emissions. Reducing emissions in material-producing industries is a key challenge. If all of industry switched to current best practices, the energy-efficiency improvement potential would be between 20% and 35% for most sectors. While these are considerable potentials, especially for sectors that have historically paid a lot of attention to energy-efficiency improvement, realization of these potentials under current 'business as usual' conditions is slow due to a large variety of barriers and limited efforts by industry and governments around the world. Importantly, the potentials are not sufficient to achieve the deep reductions in carbon emissions that will be necessary to stay within the climate boundaries as agreed in the 2015 Paris Conference of Parties. Other opportunities need to be included in the menu of options to mitigate GHG emissions. It is essential to develop integrated policies combining energy efficiency, renewable energy and material efficiency and material demand reduction, offering the most economically attractive way to realize deep reductions in carbon emissions.This article is part of the themed issue 'Material demand reduction'. © 2017 The Author(s).

Smoldering Remediation of Coal-Tar-Contaminated Soil: Pilot Field Tests of STAR.

PubMed

Scholes, Grant C; Gerhard, Jason I; Grant, Gavin P; Major, David W; Vidumsky, John E; Switzer, Christine; Torero, Jose L

2015-12-15

Self-sustaining treatment for active remediation (STAR) is an emerging, smoldering-based technology for nonaqueous-phase liquid (NAPL) remediation. This work presents the first in situ field evaluation of STAR. Pilot field tests were performed at 3.0 m (shallow test) and 7.9 m (deep test) below ground surface within distinct lithological units contaminated with coal tar at a former industrial facility. Self-sustained smoldering (i.e., after the in-well ignition heater was terminated) was demonstrated below the water table for the first time. The outward propagation of a NAPL smoldering front was mapped, and the NAPL destruction rate was quantified in real time. A total of 3700 kg of coal tar over 12 days in the shallow test and 860 kg over 11 days in the deep test was destroyed; less than 2% of total mass removed was volatilized. Self-sustaining propagation was relatively uniform radially outward in the deep test, achieving a radius of influence of 3.7 m; strong permeability contrasts and installed barriers influenced the front propagation geometry in the shallow test. Reductions in soil hydrocarbon concentrations of 99.3% and 97.3% were achieved in the shallow and deep tests, respectively. Overall, this provides the first field evaluation of STAR and demonstrates that it is effective in situ and under a variety of conditions and provides the information necessary for designing the full-scale site treatment.

Deep-Sea Bacterium Shewanella piezotolerans WP3 Has Two Dimethyl Sulfoxide Reductases in Distinct Subcellular Locations

PubMed Central

Xiong, Lei; Jian, Huahua

2017-01-01

ABSTRACT Dimethyl sulfoxide (DMSO) acts as a substantial sink for dimethyl sulfide (DMS) in deep waters and is therefore considered a potential electron acceptor supporting abyssal ecosystems. Shewanella piezotolerans WP3 was isolated from west Pacific deep-sea sediments, and two functional DMSO respiratory subsystems are essential for maximum growth of WP3 under in situ conditions (4°C/20 MPa). However, the relationship between these two subsystems and the electron transport pathway underlying DMSO reduction by WP3 remain unknown. In this study, both DMSO reductases (type I and type VI) in WP3 were found to be functionally independent despite their close evolutionary relationship. Moreover, immunogold labeling of DMSO reductase subunits revealed that the type I DMSO reductase was localized on the outer leaflet of the outer membrane, whereas the type VI DMSO reductase was located within the periplasmic space. CymA, a cytoplasmic membrane-bound tetraheme c-type cytochrome, served as a preferential electron transport protein for the type I and type VI DMSO reductases, in which type VI accepted electrons from CymA in a DmsE- and DmsF-independent manner. Based on these results, we proposed a core electron transport model of DMSO reduction in the deep-sea bacterium S. piezotolerans WP3. These results collectively suggest that the possession of two sets of DMSO reductases with distinct subcellular localizations may be an adaptive strategy for WP3 to achieve maximum DMSO utilization in deep-sea environments. IMPORTANCE As the dominant methylated sulfur compound in deep oceanic water, dimethyl sulfoxide (DMSO) has been suggested to play an important role in the marine biogeochemical cycle of the volatile anti-greenhouse gas dimethyl sulfide (DMS). Two sets of DMSO respiratory systems in the deep-sea bacterium Shewanella piezotolerans WP3 have previously been identified to mediate DMSO reduction under in situ conditions (4°C/20 MPa). Here, we report that the two DMSO reductases (type I and type VI) in WP3 have distinct subcellular localizations, in which type I DMSO reductase is localized to the exterior surface of the outer membrane and type VI DMSO reductase resides in the periplasmic space. A core electron transport model of DMSO reduction in WP3 was constructed based on genetic and physiological data. These results will contribute to a comprehensive understanding of the adaptation mechanisms of anaerobic respiratory systems in benthic microorganisms. PMID:28687647

Non-invasive therapy of wrinkles and lax skin using a novel multisource phase-controlled radio frequency system.

PubMed

Elman, Monica; Vider, Itzhak; Harth, Yoram; Gottfried, Varda; Shemer, Avner

2010-04-01

Abstract The last few years have shown an increased demand for non-invasive skin tightening to improve body contour. Since light (lasers or intense pulsed light sources) has a limited ability to penetrate deep into the tissue, radio frequency (RF) modalities were introduced for the reduction of lax skin to achieve skin tightening and body circumference reduction. This study presents the use of the novel 3DEEP technology for body contouring. 3DEEP is a next generation RF technology that provides targeted heating to deeper skin layers without pain or other local or systemic side effects associated with the use of the earlier generation RF systems available today. The study included 30 treatment areas on 23 healthy volunteers at two sites. The treatment protocol included four weekly and two bi-weekly (n= 6) treatments on different body areas. Results were evaluated by standardized photography and by circumference measurements at the treatment area, and were compared to changes in body weight. Significant improvement could be observed in wrinkles and skin laxity, and in the appearance of stretch marks and cellulite. Some changes appeared as early as after a single treatment. Circumference changes of up to 4.3 cm were measured.

Deep linear autoencoder and patch clustering-based unified one-dimensional coding of image and video

NASA Astrophysics Data System (ADS)

Li, Honggui

2017-09-01

This paper proposes a unified one-dimensional (1-D) coding framework of image and video, which depends on deep learning neural network and image patch clustering. First, an improved K-means clustering algorithm for image patches is employed to obtain the compact inputs of deep artificial neural network. Second, for the purpose of best reconstructing original image patches, deep linear autoencoder (DLA), a linear version of the classical deep nonlinear autoencoder, is introduced to achieve the 1-D representation of image blocks. Under the circumstances of 1-D representation, DLA is capable of attaining zero reconstruction error, which is impossible for the classical nonlinear dimensionality reduction methods. Third, a unified 1-D coding infrastructure for image, intraframe, interframe, multiview video, three-dimensional (3-D) video, and multiview 3-D video is built by incorporating different categories of videos into the inputs of patch clustering algorithm. Finally, it is shown in the results of simulation experiments that the proposed methods can simultaneously gain higher compression ratio and peak signal-to-noise ratio than those of the state-of-the-art methods in the situation of low bitrate transmission.

Investigation of a Passive, Temporal, Neutron Monitoring System that Functions within the Confines of Start I

DTIC Science & Technology

2003-03-01

was appreciated and their expertise was invaluable. I would also like to thank laboratory technician, Mr. Eric Taylor, whose assistance, skill...Sagdeev, “Detecting Nuclear Warheads,” in Reversing the Arms Race: How to Achieve and Verify Deep Reductions in the Nuclear Arsenals. Ed. F. von ... Hippel and R.Z. Sagdeev. New York: Gordon and Breach Science Publishers, 1990 7) Brigman, Charles J. Introduction To The Physics of Nuclear Weapon

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs) can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications. PMID:29375284

Strut Shaping of 34m Beam Waveguide Antenna for Reductions in Near-Field RF and Noise Temperature

NASA Technical Reports Server (NTRS)

Khayatian, Behrouz; Hoppe, Daniel J.; Britcliffe, Michael J.; Gama, Eric

2012-01-01

Strut shaping of NASA's Deep Space Network (DSN) 34m Beam Waveguide (BWG) antenna has been implemented to reduce near-field RF exposure while improving the antenna noise temperature. Strut shaping was achieved by introducing an RF shield that does not compromise the structural integrity of the existing antenna. Reduction in the RF near-field level will compensate for the planned transmit power increase of the antenna from 20 kW to 80 kW while satisfying safety requirements for RF exposure. Measured antenna noise temperature was also improved by as much as 1.5 K for the low elevation angles and 0.5 K in other areas.

Vehicle Color Recognition with Vehicle-Color Saliency Detection and Dual-Orientational Dimensionality Reduction of CNN Deep Features

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Li, Jiafeng; Zhuo, Li; Zhang, Hui; Li, Xiaoguang

2017-12-01

Color is one of the most stable attributes of vehicles and often used as a valuable cue in some important applications. Various complex environmental factors, such as illumination, weather, noise and etc., result in the visual characteristics of the vehicle color being obvious diversity. Vehicle color recognition in complex environments has been a challenging task. The state-of-the-arts methods roughly take the whole image for color recognition, but many parts of the images such as car windows; wheels and background contain no color information, which will have negative impact on the recognition accuracy. In this paper, a novel vehicle color recognition method using local vehicle-color saliency detection and dual-orientational dimensionality reduction of convolutional neural network (CNN) deep features has been proposed. The novelty of the proposed method includes two parts: (1) a local vehicle-color saliency detection method has been proposed to determine the vehicle color region of the vehicle image and exclude the influence of non-color regions on the recognition accuracy; (2) dual-orientational dimensionality reduction strategy has been designed to greatly reduce the dimensionality of deep features that are learnt from CNN, which will greatly mitigate the storage and computational burden of the subsequent processing, while improving the recognition accuracy. Furthermore, linear support vector machine is adopted as the classifier to train the dimensionality reduced features to obtain the recognition model. The experimental results on public dataset demonstrate that the proposed method can achieve superior recognition performance over the state-of-the-arts methods.

Deep Energy Retrofits - Eleven California Case Studies

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

Less, Brennan; Fisher, Jeremy; Walker, Iain

2012-10-01

This research documents and demonstrates viable approaches using existing materials, tools and technologies in owner-conducted deep energy retrofits (DERs). These retrofits are meant to reduce energy use by 70% or more, and include extensive upgrades to the building enclosure, heating, cooling and hot water equipment, and often incorporate appliance and lighting upgrades as well as the addition of renewable energy. In this report, 11 Northern California (IECC climate zone 3) DER case studies are described and analyzed in detail, including building diagnostic tests and end-use energy monitoring results. All projects recognized the need to improve the home and its systemsmore » approximately to current building code-levels, and then pursued deeper energy reductions through either enhanced technology/ building enclosure measures, or through occupant conservation efforts, both of which achieved impressive energy performance and reductions. The beyond-code incremental DER costs averaged $25,910 for the six homes where cost data were available. DERs were affordable when these incremental costs were financed as part of a remodel, averaging a $30 per month increase in the net-cost of home ownership.« less

Task- and self-related pathways to deep learning: the mediating role of achievement goals, classroom attentiveness, and group participation.

PubMed

Lau, Shun; Liem, Arief Darmanegara; Nie, Youyan

2008-12-01

The expectancy-value and achievement goal theories are arguably the two most dominant theories of achievement motivation in the contemporary literature. However, very few studies have examined how the constructs derived from both theories are related to deep learning. Moreover, although there is evidence demonstrating the links between achievement goals and deep learning, little research has examined the mediating processes involved. The aims of this research were to: (a) investigate the role of task- and self-related beliefs (task value and self-efficacy) as well as achievement goals in predicting deep learning in mathematics and (b) examine how classroom attentiveness and group participation mediated the relations between achievement goals and deep learning. The sample comprised 1,476 Grade-9 students from 39 schools in Singapore. Students' self-efficacy, task value, achievement goals, classroom attentiveness, group participation, and deep learning in mathematics were assessed by a self-reported questionnaire administered on-line. Structural equation modelling was performed to test the hypothesized model linking these variables. Task value was predictive of task-related achievement goals whereas self-efficacy was predictive of task-approach, performance-approach, and performance-avoidance goals. Achievement goals were found to fully mediate the relations between task value and self-efficacy on the one hand, and classroom attentiveness, group participation, and deep learning on the other. Classroom attentiveness and group participation partially mediated the relations between achievement goal adoption and deep learning. The findings suggest that (a) task- and self-related pathways are two possible routes through which students could be motivated to learn and (b) like task-approach goals, performance-approach goals could lead to adaptive processes and outcomes.

A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.

PubMed

Jin, Hongsheng; Li, Zongyao; Tong, Ruofeng; Lin, Lanfen

2018-05-01

The automatic detection of pulmonary nodules using CT scans improves the efficiency of lung cancer diagnosis, and false-positive reduction plays a significant role in the detection. In this paper, we focus on the false-positive reduction task and propose an effective method for this task. We construct a deep 3D residual CNN (convolution neural network) to reduce false-positive nodules from candidate nodules. The proposed network is much deeper than the traditional 3D CNNs used in medical image processing. Specifically, in the network, we design a spatial pooling and cropping (SPC) layer to extract multilevel contextual information of CT data. Moreover, we employ an online hard sample selection strategy in the training process to make the network better fit hard samples (e.g., nodules with irregular shapes). Our method is evaluated on 888 CT scans from the dataset of the LUNA16 Challenge. The free-response receiver operating characteristic (FROC) curve shows that the proposed method achieves a high detection performance. Our experiments confirm that our method is robust and that the SPC layer helps increase the prediction accuracy. Additionally, the proposed method can easily be extended to other 3D object detection tasks in medical image processing. © 2018 American Association of Physicists in Medicine.

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

Veysey, Jason; Octaviano, Claudia; Calvin, Katherine

Mexico’s climate policy sets ambitious national greenhouse gas (GHG) emission reduction targets—30% versus a business-as-usual baseline by 2020, 50% versus 2000 by 2050. However, these goals are at odds with recent energy and emission trends in the country. Both energy use and GHG emissions in Mexico have grown substantially over the last two decades. Here, we investigate how Mexico might reverse current trends and reach its mitigation targets by exploring results from energy system and economic models involved in the CLIMACAP-LAMP project. To meet Mexico’s emission reduction targets, all modeling groups agree that decarbonization of electricity is needed, along withmore » changes in the transport sector, either to more efficient vehicles or a combination of more efficient vehicles and lower carbon fuels. These measures reduce GHG emissions as well as emissions of other air pollutants. The models find different energy supply pathways, with some solutions based on renewable energy and others relying on biomass or fossil fuels with carbon capture and storage. The economy-wide costs of deep mitigation could range from 2% to 4% of GDP in 2030, and from 7% to 15% of GDP in 2050. Our results suggest that Mexico has some flexibility in designing deep mitigation strategies, and that technological options could allow Mexico to achieve its emission reduction targets, albeit at a cost to the country.« less

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.« less

Strut Shaping of 34m Beam Waveguide Antenna for Reductions in Near-Field RF and Noise Temeperature

NASA Technical Reports Server (NTRS)

Khayatian, Behrouz; Hoppe, Daniel J.; Britcliffe, Michael J.; Gama, Eric

2012-01-01

Struts shaping of the NASA's Deep Space Network (DSN) 34m Beam Waveguide (BWG) antenna has been implemented to reduce near-field RF exposure while improving the antenna noise temperature. Strut shaping was achieved by introducing an RF shield that does not compromise the structural integrity of the existing structure. Reduction in the RF near-field exposure will compensate for the planned transmit power increase of the antenna from 20 kW to 80 kW while satisfying safety requirements for RF exposure. Antenna noise temperature was also improved by as much as 1.5 K for the low elevation angles and 0.5 K in other areas. Both reductions of RF near-field exposure and antenna noise temperature were verified through measurements and agree very well with calculated results.

X-Divertor Geometries for Deeper Detachment Without Degrading the DIII-D H-Mode

NASA Astrophysics Data System (ADS)

Covele, Brent; Kotschenreuther, M. T.; Valanju, P. M.; Mahajan, S. M.; Leonard, A. W.; Hyatt, A. W.; McLean, A. G.; Thomas, D. M.; Guo, H. Y.; Watkins, J. G.; Makowski, M. A.; Hill, D. N.

2015-11-01

Recent DIII-D experiments comparing the standard divertor (SD) and X-Divertor (XD) geometries show heat and particle flux reduction at the divertor target plate. The XD features large poloidal flux expansion, increased connection length, and poloidal field line flaring, quantified by the Divertor Index. Both SD and XD were pushed deep into detachment with increased gas puffing, until core energy confinement and pedestal pressure were substantially reduced. As expected, outboard target heat fluxes are significantly reduced in the XD compared to the SD under similar upstream plasma conditions, even at low Greenwald fraction. The high-triangularity (floor) XD cases show larger reduction in temperature, heat, and particle flux relative to the SD in all cases, while low-triangularity (shelf) XD cases show more modest reductions over the SD. Consequently, heat flux reduction and divertor detachment may be achieved in the XD with less gas puffing and higher pedestal pressures. Further causative analysis, as well as detailed modeling with SOLPS, is underway. These initial experiments suggest the XD as a promising candidate to achieve divertor heat flux control compatible with robust H-mode operation. Work supported by US DOE under DE-FC02-04ER54698, DE-AC52-07NA27344, DE-FG02-04ER54754, and DE-FG02-04ER54742.

Deep learning methods for CT image-domain metal artifact reduction

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Shan, Hongming; Claus, Bernhard; Jin, Yannan; De Man, Bruno; Wang, Ge

2017-09-01

Artifacts resulting from metal objects have been a persistent problem in CT images over the last four decades. A common approach to overcome their effects is to replace corrupt projection data with values synthesized from an interpolation scheme or by reprojection of a prior image. State-of-the-art correction methods, such as the interpolation- and normalization-based algorithm NMAR, often do not produce clinically satisfactory results. Residual image artifacts remain in challenging cases and even new artifacts can be introduced by the interpolation scheme. Metal artifacts continue to be a major impediment, particularly in radiation and proton therapy planning as well as orthopedic imaging. A new solution to the long-standing metal artifact reduction (MAR) problem is deep learning, which has been successfully applied to medical image processing and analysis tasks. In this study, we combine a convolutional neural network (CNN) with the state-of-the-art NMAR algorithm to reduce metal streaks in critical image regions. Training data was synthesized from CT simulation scans of a phantom derived from real patient images. The CNN is able to map metal-corrupted images to artifact-free monoenergetic images to achieve additional correction on top of NMAR for improved image quality. Our results indicate that deep learning is a novel tool to address CT reconstruction challenges, and may enable more accurate tumor volume estimation for radiation therapy planning.

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

Deep learning methods to guide CT image reconstruction and reduce metal artifacts

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Zhou, Ye; Zhang, Junping; Wang, Ge

2017-03-01

The rapidly-rising field of machine learning, including deep learning, has inspired applications across many disciplines. In medical imaging, deep learning has been primarily used for image processing and analysis. In this paper, we integrate a convolutional neural network (CNN) into the computed tomography (CT) image reconstruction process. Our first task is to monitor the quality of CT images during iterative reconstruction and decide when to stop the process according to an intelligent numerical observer instead of using a traditional stopping rule, such as a fixed error threshold or a maximum number of iterations. After training on ground truth images, the CNN was successful in guiding an iterative reconstruction process to yield high-quality images. Our second task is to improve a sinogram to correct for artifacts caused by metal objects. A large number of interpolation and normalization-based schemes were introduced for metal artifact reduction (MAR) over the past four decades. The NMAR algorithm is considered a state-of-the-art method, although residual errors often remain in the reconstructed images, especially in cases of multiple metal objects. Here we merge NMAR with deep learning in the projection domain to achieve additional correction in critical image regions. Our results indicate that deep learning can be a viable tool to address CT reconstruction challenges.

Treatment of deep underlying reticular veins by Nd:Yag laser and IPL source.

PubMed

Colaiuda, S; Colaiuda, F; Gasparotti, M

2000-10-01

The purpose of this paper is to estimate the efficacy of Nd:Yag laser and IPL combined action for the treatment of deep (up to 5 mm) and large (up to 3 mm in diameter) reticular varicosity of the lower extremity. A group of 38 subjects (2 male and 36 female) aged from 34 to 65 years were treated for deep reticular varicosity of the legs. All patients underwent various clinical analyses in order to evaluate and exclude pre-existing cardiovascular pathology, coagulation disorders as well as pathology due to saphena incontinence. Also, for the first three months they underwent ambulatory specialistic treatments at 21-days intertreatment interval. A reduction of venous network of 80-90% after 2 treatment sessions with Nd:Yag laser was obtained in 84% of subjects. Successive 3 treatment sessions with IPL have achieved complete vanishing of the treated venous network in 36 patients (95%). A combined action of Nd:Yag laser and IPL has demonstrated its particular efficacy in non-invasive treatment of deep and extensive reticolar varicosity of the lower extremity, considering also that it is well tolerated by patients and applicable in each single case on out patient basis.

Deep-learning-based classification of FDG-PET data for Alzheimer's disease categories

NASA Astrophysics Data System (ADS)

Singh, Shibani; Srivastava, Anant; Mi, Liang; Caselli, Richard J.; Chen, Kewei; Goradia, Dhruman; Reiman, Eric M.; Wang, Yalin

2017-11-01

Fluorodeoxyglucose (FDG) positron emission tomography (PET) measures the decline in the regional cerebral metabolic rate for glucose, offering a reliable metabolic biomarker even on presymptomatic Alzheimer's disease (AD) patients. PET scans provide functional information that is unique and unavailable using other types of imaging. However, the computational efficacy of FDG-PET data alone, for the classification of various Alzheimers Diagnostic categories, has not been well studied. This motivates us to correctly discriminate various AD Diagnostic categories using FDG-PET data. Deep learning has improved state-of-the-art classification accuracies in the areas of speech, signal, image, video, text mining and recognition. We propose novel methods that involve probabilistic principal component analysis on max-pooled data and mean-pooled data for dimensionality reduction, and multilayer feed forward neural network which performs binary classification. Our experimental dataset consists of baseline data of subjects including 186 cognitively unimpaired (CU) subjects, 336 mild cognitive impairment (MCI) subjects with 158 Late MCI and 178 Early MCI, and 146 AD patients from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We measured F1-measure, precision, recall, negative and positive predictive values with a 10-fold cross validation scheme. Our results indicate that our designed classifiers achieve competitive results while max pooling achieves better classification performance compared to mean-pooled features. Our deep model based research may advance FDG-PET analysis by demonstrating their potential as an effective imaging biomarker of AD.

Automatic lung nodule graph cuts segmentation with deep learning false positive reduction

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Tseng, Tzu-Liang Bill; Qian, Wei

2017-03-01

To automatic detect lung nodules from CT images, we designed a two stage computer aided detection (CAD) system. The first stage is graph cuts segmentation to identify and segment the nodule candidates, and the second stage is convolutional neural network for false positive reduction. The dataset contains 595 CT cases randomly selected from Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI) and the 305 pulmonary nodules achieved diagnosis consensus by all four experienced radiologists were our detection targets. Consider each slice as an individual sample, 2844 nodules were included in our database. The graph cuts segmentation was conducted in a two-dimension manner, 2733 lung nodule ROIs are successfully identified and segmented. With a false positive reduction by a seven-layer convolutional neural network, 2535 nodules remain detected while the false positive dropped to 31.6%. The average F-measure of segmented lung nodule tissue is 0.8501.

Effects of Reduction Osteotomy on Gap Balancing During Total Knee Arthroplasty for Severe Varus Deformity.

PubMed

Niki, Yasuo; Harato, Kengo; Nagai, Katsuya; Suda, Yasunori; Nakamura, Masaya; Matsumoto, Morio

2015-12-01

This study aimed to assess the effects of down-sizing and lateralizing of the tibial component (reduction osteotomy) on gap balancing in TKA, and the clinical feasibility of an uncemented modular trabecular metal tibial tray in this technique. Reduction osteotomy was performed for 39 knees of 36 patients with knee OA with a mean tibiofemoral angle of 21° varus. In 20 knees, appropriate gap balance was achieved by release of the deep medial collateral ligament alone. Flexion gap imbalance could be reduced by approximately 1.7° and 2.8° for 4-mm osteotomy and 8-mm osteotomy, respectively. Within the first postoperative year, clinically-stable tibial component subsidence was observed in 9 knees, but it was not progressive, and the clinical results were excellent at a mean follow-up of 3.3 years. Copyright © 2015 Elsevier Inc. All rights reserved.

Formability of dual-phase steels in deep drawing of rectangular parts: Influence of blank thickness and die radius

NASA Astrophysics Data System (ADS)

López, Ana María Camacho; Regueras, José María Gutiérrez

2017-10-01

The new goals of automotive industry related with environment concerns, the reduction of fuel emissions and the security requirements have driven up to new designs which main objective is reducing weight. It can be achieved through new materials such as nano-structured materials, fibre-reinforced composites or steels with higher strength, among others. Into the last group, the Advance High Strength Steels (AHSS) and particularly, dual-phase steels are in a predominant situation. However, despite of their special characteristics, they present issues related to their manufacturability such as springback, splits and cracks, among others. This work is focused on the deep drawing processof rectangular shapes, a very usual forming operation that allows manufacturing several automotive parts like oil pans, cases, etc. Two of the main parameters in this process which affect directly to the characteristics of final product are blank thickness (t) and die radius (Rd). Influence of t and Rd on the formability of dual-phase steels has been analysed considering values typically used in industrial manufacturing for a wide range of dual-phase steels using finite element modelling and simulation; concretely, the influence of these parameters in the percentage of thickness reduction pt(%), a quite important value for manufactured parts by deep drawing operations, which affects to its integrity and its service behaviour. Modified Morh Coulomb criteria (MMC) has been used in order to obtain Fracture Forming Limit Diagrams (FFLD) which take into account an important failure mode in dual-phase steels: shear fracture. Finally, a relation between thickness reduction percentage and studied parameters has been established fordual-phase steels, obtaining a collection of equations based on Design of Experiments (D.O.E) technique, which can be useful in order to predict approximate results.

Reducing greenhouse gas emissions for climate stabilization: framing regional options.

PubMed

Olabisi, Laura Schmitt; Reich, Peter B; Johnson, Kris A; Kapuscinski, Anne R; Su, Sangwon H; Wilson, Elizabeth J

2009-03-15

The Intergovernmental Panel on Climate Change (IPCC) has stated that stabilizing atmospheric CO2 concentrations will require reduction of global greenhouse gas (GHG) emissions by as much as 80% by 2050. Subnational efforts to cut emissions will inform policy development nationally and globally. We projected GHG mitigation strategies for Minnesota, which has adopted a strategic goal of 80% emissions reduction by 2050. A portfolio of conservation strategies, including electricity conservation, increased vehicle fleet fuel efficiency, and reduced vehicle miles traveled, is likely the most cost-effective option for Minnesota and could reduce emissions by 18% below 2005 levels. An 80% GHG reduction would require complete decarbonization of the electricity and transportation sectors, combined with carbon capture and sequestration at power plants, or deep cuts in other relatively more intransigent GHG-emitting sectors. In order to achieve ambitious GHG reduction goals, policymakers should promote aggressive conservation efforts, which would probably have negative net costs, while phasing in alternative fuels to replace coal and motor gasoline over the long-term.

Deep facial analysis: A new phase I epilepsy evaluation using computer vision.

PubMed

Ahmedt-Aristizabal, David; Fookes, Clinton; Nguyen, Kien; Denman, Simon; Sridharan, Sridha; Dionisio, Sasha

2018-05-01

Semiology observation and characterization play a major role in the presurgical evaluation of epilepsy. However, the interpretation of patient movements has subjective and intrinsic challenges. In this paper, we develop approaches to attempt to automatically extract and classify semiological patterns from facial expressions. We address limitations of existing computer-based analytical approaches of epilepsy monitoring, where facial movements have largely been ignored. This is an area that has seen limited advances in the literature. Inspired by recent advances in deep learning, we propose two deep learning models, landmark-based and region-based, to quantitatively identify changes in facial semiology in patients with mesial temporal lobe epilepsy (MTLE) from spontaneous expressions during phase I monitoring. A dataset has been collected from the Mater Advanced Epilepsy Unit (Brisbane, Australia) and is used to evaluate our proposed approach. Our experiments show that a landmark-based approach achieves promising results in analyzing facial semiology, where movements can be effectively marked and tracked when there is a frontal face on visualization. However, the region-based counterpart with spatiotemporal features achieves more accurate results when confronted with extreme head positions. A multifold cross-validation of the region-based approach exhibited an average test accuracy of 95.19% and an average AUC of 0.98 of the ROC curve. Conversely, a leave-one-subject-out cross-validation scheme for the same approach reveals a reduction in accuracy for the model as it is affected by data limitations and achieves an average test accuracy of 50.85%. Overall, the proposed deep learning models have shown promise in quantifying ictal facial movements in patients with MTLE. In turn, this may serve to enhance the automated presurgical epilepsy evaluation by allowing for standardization, mitigating bias, and assessing key features. The computer-aided diagnosis may help to support clinical decision-making and prevent erroneous localization and surgery. Copyright © 2018 Elsevier Inc. All rights reserved.

Pathways to Mexico’s climate change mitigation targets: A multi-model analysis

DOE PAGES

Veysey, Jason; Octaviano, Claudia; Calvin, Katherine; ...

2015-04-25

Mexico’s climate policy sets ambitious national greenhouse gas (GHG) emission reduction targets—30% versus a business-as-usual baseline by 2020, 50% versus 2000 by 2050. However, these goals are at odds with recent energy and emission trends in the country. Both energy use and GHG emissions in Mexico have grown substantially over the last two decades. Here, we investigate how Mexico might reverse current trends and reach its mitigation targets by exploring results from energy system and economic models involved in the CLIMACAP-LAMP project. To meet Mexico’s emission reduction targets, all modeling groups agree that decarbonization of electricity is needed, along withmore » changes in the transport sector, either to more efficient vehicles or a combination of more efficient vehicles and lower carbon fuels. These measures reduce GHG emissions as well as emissions of other air pollutants. The models find different energy supply pathways, with some solutions based on renewable energy and others relying on biomass or fossil fuels with carbon capture and storage. The economy-wide costs of deep mitigation could range from 2% to 4% of GDP in 2030, and from 7% to 15% of GDP in 2050. Our results suggest that Mexico has some flexibility in designing deep mitigation strategies, and that technological options could allow Mexico to achieve its emission reduction targets, albeit at a cost to the country.« less

Deep vein thrombus formation induced by flow reduction in mice is determined by venous side branches.

PubMed

Brandt, Moritz; Schönfelder, Tanja; Schwenk, Melanie; Becker, Christian; Jäckel, Sven; Reinhardt, Christoph; Stark, Konstantin; Massberg, Steffen; Münzel, Thomas; von Brühl, Marie-Luise; Wenzel, Philip

2014-01-01

Interaction between vascular wall abnormalities, inflammatory leukocytes, platelets, coagulation factors and hemorheology in the pathogenesis of deep vein thrombosis (DVT) is incompletely understood, requiring well defined animal models of human disease. We subjected male C57BL/6 mice to ligation of the inferior vena cava (IVC) as a flow reduction model to induce DVT. Thrombus size and weight were analyzed macroscopically and sonographically by B-mode, pulse wave (pw) Doppler and power Doppler imaging (PDI) using high frequency ultrasound. Thrombus size varied substantially between individual procedures and mice, irrespective of the flow reduction achieved by the ligature. Interestingly, PDI accurately predicted thrombus size in a very robust fashion (r2 = 0.9734, p < 0.0001). Distance of the insertion of side branches from the ligature significantly determines thrombus weight (r2 = 0.5597, p < 0.0001) and length (r2 = 0.5441, p < 0.0001) in the IVC, regardless of the flow measured by pw-Doppler with distances <1.5 mm drastically impairing thrombus formation. Occlusion of side branches prior to ligation of IVC did not increase thrombus size, probably due to patent side branches inaccessible to surgery. Venous side branches influence thrombus size in experimental DVT and might therefore prevent thrombus formation. This renders vessel anatomy and hemorheology important determinants in mouse models of DVT, which should be controlled for.

Sulfate Reduction and Sulfide Biomineralization By Deep-Sea Hydrothermal Vent Microorganisms

NASA Astrophysics Data System (ADS)

Picard, A.; Gartman, A.; Clarke, D. R.; Girguis, P. R.

2014-12-01

Deep-sea hydrothermal vents are characterized by steep temperature and chemical gradients and moderate pressures. At these sites, mesophilic sulfate-reducing bacteria thrive, however their significance for the formation of sulfide minerals is unknown. In this study we investigated sulfate reduction and sulfide biomineralization by the deep-sea bacterium Desulfovibrio hydrothermalis isolated from a deep-sea vent chimney at the Grandbonum vent site (13°N, East Pacific Rise, 2600 m water depth) [1]. Sulfate reduction rates were determined as a function of pressure and temperature. Biomineralization of sulfide minerals in the presence of various metal concentrations was characterized using light and electron microscopy and optical spectroscopy. We seek to better understand the significance of biological sulfate reduction in deep-sea hydrothermal environments, to characterize the steps in sulfide mineral nucleation and growth, and identify the interactions between cells and minerals. [1] D. Alazard, S. Dukan, A. Urios, F. Verhe, N. Bouabida, F. Morel, P. Thomas, J.L. Garcia and B. Ollivier, Desulfovibrio hydrothermalis sp. nov., a novel sulfate-reducing bacterium isolated from hydrothermal vents, Int. J. Syst. Evol. Microbiol., 53 (2003) 173-178.

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.

Effects of Plasma Hydrogenation on Trapping Properties of Dislocations in Heteroepitaxial InP/GaAs

NASA Technical Reports Server (NTRS)

Ringel, S. A.; Chatterjee, B.

1994-01-01

In previous work, we have demonstrated the effectiveness of a post-growth hydrogen plasma treatment for passivating the electrical activity of dislocations in metalorganic chemical vapor deposition (MOCVD) grown InP on GaAs substrates by a more than two order of magnitude reduction in deep level concentration and an improvement in reverse bias leakage current by a factor of approx. 20. These results make plasma hydrogenation an extremely promising technique for achieving high efficiency large area and light weight heteroepitaxial InP solar cells for space applications. In this work we investigate the carrier trapping process by dislocations in heteroepitaxial InP/GaAs and the role of hydrogen passivation on this process. It is shown that the charge trapping kinetics of dislocations after hydrogen passivation are significantly altered, approaching point defect-like behavior consistent with a transformation from a high concentration of dislocation-related defect bands within the InP bandgap to a low concentration of individual deep levels after hydrogen passivation. It is further shown that the "apparent" activation energies of dislocation related deep levels, before and after passivation, reduce by approx. 70 meV as DLTS fill pulse times are increased from 1 usec. to 1 msec. A model is proposed which explains these effects based on a reduction of Coulombic interaction between individual core sites along the dislocation cores by hydrogen incorporation. Knowledge of the trapping properties in these specific structures is important to develop optimum, low loss heteroepitaxial InP cells.

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.

The inhibition of marine nitrification by ocean disposal of carbon dioxide.

PubMed

Huesemann, Michael H; Skillman, Ann D; Crecelius, Eric A

2002-02-01

In an attempt to reduce the threat of global warming, it has been proposed that the rise of atmospheric carbon dioxide concentrations be reduced by the ocean disposal of CO2 from the flue gases of fossil fuel-fired power plants. The release of large amounts of CO2 into mid or deep ocean waters will result in large plumes of acidified seawater with pH values ranging from 6 to 8. In an effort to determine whether these CO2-induced pH changes have any effect on marine nitrification processes, surficial (euphotic zone) and deep (aphotic zone) seawater samples were sparged with CO2 for varying time durations to achieve a specified pH reduction, and the rate of microbial ammonia oxidation was measured spectrophotometrically as a function of pH using an inhibitor technique. For both seawater samples taken from either the euphotic or aphotic zone, the nitrification rates dropped drastically with decreasing pH. Relative to nitrification rates in the original seawater at pH 8, nitrification rates were reduced by ca. 50% at pH 7 and more than 90% at pH 6.5. Nitrification was essentially completely inhibited at pH 6. These findings suggest that the disposal of CO2 into mid or deep oceans will most likely result in a drastic reduction of ammonia oxidation rates within the pH plume and the concomitant accumulation of ammonia instead of nitrate. It is unlikely that ammonia will reach the high concentration levels at which marine aquatic organisms are known to be negatively affected. However, if the ammonia-rich seawater from inside the pH plume is upwelled into the euphotic zone, it is likely that changes in phytoplankton abundance and community structure will occur. Finally, the large-scale inhibition of nitrification and the subsequent reduction of nitrite and nitrate concentrations could also result in a decrease of denitrification rates which, in turn, could lead to the buildup of nitrogen and unpredictable eutrophication phenomena. Clearly, more research on the environmental effects of ocean disposal of CO2 is needed to determine whether the potential costs related to marine ecosystem disturbance and disruption can be justified in terms of the perceived benefits that may be achieved by temporarily delaying global warming.

Cough event classification by pretrained deep neural network.

PubMed

Liu, Jia-Ming; You, Mingyu; Wang, Zheng; Li, Guo-Zheng; Xu, Xianghuai; Qiu, Zhongmin

2015-01-01

Cough is an essential symptom in respiratory diseases. In the measurement of cough severity, an accurate and objective cough monitor is expected by respiratory disease society. This paper aims to introduce a better performed algorithm, pretrained deep neural network (DNN), to the cough classification problem, which is a key step in the cough monitor. The deep neural network models are built from two steps, pretrain and fine-tuning, followed by a Hidden Markov Model (HMM) decoder to capture tamporal information of the audio signals. By unsupervised pretraining a deep belief network, a good initialization for a deep neural network is learned. Then the fine-tuning step is a back propogation tuning the neural network so that it can predict the observation probability associated with each HMM states, where the HMM states are originally achieved by force-alignment with a Gaussian Mixture Model Hidden Markov Model (GMM-HMM) on the training samples. Three cough HMMs and one noncough HMM are employed to model coughs and noncoughs respectively. The final decision is made based on viterbi decoding algorihtm that generates the most likely HMM sequence for each sample. A sample is labeled as cough if a cough HMM is found in the sequence. The experiments were conducted on a dataset that was collected from 22 patients with respiratory diseases. Patient dependent (PD) and patient independent (PI) experimental settings were used to evaluate the models. Five criteria, sensitivity, specificity, F1, macro average and micro average are shown to depict different aspects of the models. From overall evaluation criteria, the DNN based methods are superior to traditional GMM-HMM based method on F1 and micro average with maximal 14% and 11% error reduction in PD and 7% and 10% in PI, meanwhile keep similar performances on macro average. They also surpass GMM-HMM model on specificity with maximal 14% error reduction on both PD and PI. In this paper, we tried pretrained deep neural network in cough classification problem. Our results showed that comparing with the conventional GMM-HMM framework, the HMM-DNN could get better overall performance on cough classification task.

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Noé, Frank

2018-06-01

Inspired by the success of deep learning techniques in the physical and chemical sciences, we apply a modification of an autoencoder type deep neural network to the task of dimension reduction of molecular dynamics data. We can show that our time-lagged autoencoder reliably finds low-dimensional embeddings for high-dimensional feature spaces which capture the slow dynamics of the underlying stochastic processes—beyond the capabilities of linear dimension reduction techniques.

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…

Deep-convection events foster carbonate ion reduction in deep coral reefs

NASA Astrophysics Data System (ADS)

Perez, Fiz F.; Fontela, Marcos; Garcia-Ibañez, Maribel I.; Lherminier, Pascale; Zunino, Patricia; de la Paz, Mercedes; Padín, Xose A.; Alonso-Pérez, Fernando; Velo, Anton; Guallart, Elisa F.; Mercier, Herle

2017-04-01

Since millennial times, water mass circulation and deep-convection events have been transforming warm upper waters at high latitudes into cold and well-oxygenated deep waters. These processes have filled the deep North Atlantic Ocean with waters moderately saturated in calcium carbonate, thus promoting the growth of stony corals, which are hotspots of biodiversity. During the Anthropocene, the meridional circulation has been conveying cumulative amounts of more acidified waters with lower calcium carbonate saturation levels due to the incorporation of anthropogenic carbon dioxide, with very harsh conditions for deep cold-water corals projected by 2100. We evaluate the diminution of calcium carbonate saturation levels (aragonite form) due to the increase in anthropogenic carbon dioxide during the last two decades (2002-2016). We observe a strong decrease in the aragonite saturation levels concomitant with the reduction in the volume transport of aragonite-saturated waters. We estimate a 30-35% reduction in the transport of ion carbonate excess over the saturation levels with respect to the natural carbon cycle for the period 2002-2016. This reduction is associated with an increase in the downward transport of hydrogen ions. We also observe a heaving of the aragonite saturation horizons during the last 25 years, which is estimated at 6 m year-1 for the deep waters and 12-14 m year-1 for the intermediated waters. The harsh winters of 2015 and 2016 have fostered the fast addition of more acidified water into the lower layers of the North Atlantic through deep-convection events. In the future scenario of 2oC warming, the anthropogenic carbon dioxide in the water column would be double than today and the associated transport of hydrogen ions towards the bottom water would reduce the aragonite saturation levels to 60-80% with respect to preindustrial levels. This reduction in the aragonite saturation levels would suppose a strong diminution of the North Atlantic habitats where stony corals will be able to inhabit.

Cities’ Role in Mitigating United States Food System Greenhouse Gas Emissions

PubMed Central

2018-01-01

Current trends of urbanization, population growth, and economic development have made cities a focal point for mitigating global greenhouse gas (GHG) emissions. The substantial contribution of food consumption to climate change necessitates urban action to reduce the carbon intensity of the food system. While food system GHG mitigation strategies often focus on production, we argue that urban influence dominates this sector’s emissions and that consumers in cities must be the primary drivers of mitigation. We quantify life cycle GHG emissions of the United States food system through data collected from literature and government sources producing an estimated total of 3800 kg CO2e/capita in 2010, with cities directly influencing approximately two-thirds of food sector GHG emissions. We then assess the potential for cities to reduce emissions through selected measures; examples include up-scaling urban agriculture and home delivery of grocery options, which each may achieve emissions reductions on the order of 0.4 and ∼1% of this total, respectively. Meanwhile, changes in waste management practices and reduction of postdistribution food waste by 50% reduce total food sector emissions by 5 and 11%, respectively. Consideration of the scale of benefits achievable through policy goals can enable cities to formulate strategies that will assist in achieving deep long-term GHG emissions targets. PMID:29717606

Cities' Role in Mitigating United States Food System Greenhouse Gas Emissions.

PubMed

Mohareb, Eugene A; Heller, Martin C; Guthrie, Peter M

2018-05-15

Current trends of urbanization, population growth, and economic development have made cities a focal point for mitigating global greenhouse gas (GHG) emissions. The substantial contribution of food consumption to climate change necessitates urban action to reduce the carbon intensity of the food system. While food system GHG mitigation strategies often focus on production, we argue that urban influence dominates this sector's emissions and that consumers in cities must be the primary drivers of mitigation. We quantify life cycle GHG emissions of the United States food system through data collected from literature and government sources producing an estimated total of 3800 kg CO 2 e/capita in 2010, with cities directly influencing approximately two-thirds of food sector GHG emissions. We then assess the potential for cities to reduce emissions through selected measures; examples include up-scaling urban agriculture and home delivery of grocery options, which each may achieve emissions reductions on the order of 0.4 and ∼1% of this total, respectively. Meanwhile, changes in waste management practices and reduction of postdistribution food waste by 50% reduce total food sector emissions by 5 and 11%, respectively. Consideration of the scale of benefits achievable through policy goals can enable cities to formulate strategies that will assist in achieving deep long-term GHG emissions targets.

A class of invisible inhomogeneous media and the control of electromagnetic waves

NASA Astrophysics Data System (ADS)

Vial, B.; Liu, Y.; Horsley, S. A. R.; Philbin, T. G.; Hao, Y.

2016-12-01

We propose a general method to arbitrarily manipulate an electromagnetic wave propagating in a two-dimensional medium, without introducing any scattering. This leads to a whole class of isotropic spatially varying permittivity and permeability profiles that are invisible while shaping the field magnitude and/or phase. In addition, we propose a metamaterial structure working in the infrared that demonstrates deep subwavelength control of the electric field amplitude and strong reduction of the scattering. This work offers an alternative strategy to achieve invisibility with isotropic materials and paves the way for tailoring the propagation of light at the nanoscale.

Minimum number of spermatozoa required for normal fertility after deep intrauterine insemination in non-sedated sows.

PubMed

Martinez, E A; Vazquez, J M; Roca, J; Lucas, X; Gil, M A; Parrilla, I; Vazquez, J L; Day, B N

2002-01-01

A fibreoptic endoscope procedure for non-surgical deep intrauterine insemination in non-sedated sows has been reported. However, the endoscope is an expensive and fragile instrument, and is unsuitable for use under field conditions. The aim of this study was to determine the minimum number of spermatozoa required to maintain optimal fertility using a flexible catheter (1.8 m in length, 4 mm in diameter) for deep intrauterine insemination in 2-6 parity non-sedated sows. Crossbred sows were treated with eCG 24 h after weaning and with hCG 72 h later to induce oestrus. Deep intrauterine insemination was performed 36 h after hCG treatment in 117, 126, 60 and 69 sows with 15.0, 5.0, 2.5 or 1.0 x 10(7) spermatozoa in 10 ml, respectively. Weaned sows (n = 147) not treated with hormones and used for standard artificial insemination (AI) (two inseminations per oestrus with 3 x 10(9) spermatozoa in 100 ml) served as controls. The flexible catheter was passed successfully through the cervix into one uterine horn in 95.4% of the sows in an average of 3.7 +/- 0.09 min. Farrowing rates after deep intrauterine insemination with 15 or 5 x 10(7) spermatozoa did not differ from those of the control group (82.9, 76.2 and 83.0%, respectively), but a significant decrease (P < 0.001) was observed in sows inseminated with 2.5 or 1.0 x 10(7) spermatozoa (46.7 and 39.1%, respectively). In contrast, the number of spermatozoa inseminated did not affect prolificacy. Laparotomy revealed that the tip of the flexible catheter reached approximately the anterior third of the uterine horn. Although deep intrauterine insemination was performed in only one uterine horn, the percentages of embryos collected from the tip of both uterine horns 2 days after deep insemination were not significantly different. The results show that in comparison with standard AI, a 20-60-fold reduction in the number of spermatozoa inseminated and an 8-10-fold reduction in the dose volume can be achieved without decreasing fertility when semen is deposited non-surgically into the upper first third of one uterine horn.

Impact of Deepwater Horizon Spill on food supply to deep-sea benthos communities

USGS Publications Warehouse

Prouty, Nancy G.; Swarzenski, Pamela; Mienis, Furu; Duineveld, Gerald; Demopoulos, Amanda W.J.; Ross, Steve W.; Brooke, Sandra

2016-01-01

Deep-sea ecosystems encompass unique and often fragile communities that are sensitive to a variety of anthropogenic and natural impacts. After the 2010 Deepwater Horizon (DWH) oil spill, sampling efforts documented the acute impact of the spill on some deep-sea coral colonies. To investigate the impact of the DWH spill on quality and quantity of biomass delivered to the deep-sea, a suite of geochemical tracers (e.g., stable and radio-isotopes, lipid biomarkers, and compound specific isotopes) was measured from monthly sediment trap samples deployed near a high-density deep-coral site in the Viosca Knoll area of the north-central Gulf of Mexico prior to (Oct-2008 to Sept-2009) and after the spill (Oct-10 to Sept-11). Marine (e.g., autochthonous) sources of organic matter dominated the sediment traps in both years, however after the spill, there was a pronounced reduction in marinesourced OM, including a reduction in marine-sourced sterols and n-alkanes and a concomitant decrease in sediment trap organic carbon and pigment flux. Results from this study indicate a reduction in primary production and carbon export to the deep-sea in 2010-2011, at least 6-18 months after the spill started. Whereas satellite observations indicate an initial increase in phytoplankton biomass, results from this sediment trap study define a reduction in primary production and carbon export to the deep-sea community. In addition, a dilution from a low-14C carbon source (e.g., petrocarbon) was detected in the sediment trap samples after the spill, in conjunction with a change in the petrogenic composition. The data presented here fills a critical gap in our knowledge of biogeochemical processes and sub-acute impacts to the deep-sea that ensued after the 2010 DWH spill.

Anterior subcutaneous internal fixation for treatment of unstable pelvic fractures

PubMed Central

2014-01-01

Background Fractures of the pelvic ring including disruption of the posterior elements in high-energy trauma have both high morbidity and mortality rates. For some injury pattern part of the initial resuscitation includes either external fixation or plate fixation to close the pelvic ring and decrease blood loss. In certain situations – especially when associated with abdominal trauma and the need to perform laparotomies – both techniques may put the patient at risk of either pintract or deep plate infections. We describe an operative approach to percutaneously close and stabilize the pelvic ring using spinal implants as an internal fixator and report the results in a small series of patients treated with this technique during the resuscitation phase. Findings Four patients were treated by subcutaneous placement of an internal fixator. Screw fixation was carried out by minimally invasive placement of two supra-acetabular iliac screws. Afterwards, a subcutaneous transfixation rod was inserted and attached to the screws after reduction of the pelvic ring. All patients were allowed to fully weight-bear. No losses of reduction or deep infections occurred. Fracture healing was uneventful in all cases. Conclusion Minimally invasive fixation is an alternative technique to stabilize the pelvic ring. The clinical results illustrate that this technique is able to achieve good results in terms of maintenance of reduction the pelvic ring. Also, abdominal surgeries no longer put the patient at risk of infected pins or plates. PMID:24606833

Multimillennium changes in dissolved oxygen under global warming: results from an AOGCM and offline ocean biogeochemical model

NASA Astrophysics Data System (ADS)

Yamamoto, A.; Abe-Ouchi, A.; Shigemitsu, M.; Oka, A.; Takahashi, K.; Ohgaito, R.; Yamanaka, Y.

2016-12-01

Long-term oceanic oxygen change due to global warming is still unclear; most future projections (such as CMIP5) are only performed until 2100. Indeed, few previous studies using conceptual models project oxygen change in the next thousands of years, showing persistent global oxygen reduction by about 30% in the next 2000 years, even after atmospheric carbon dioxide stops rising. Yet, these models cannot sufficiently represent the ocean circulation change: the key driver of oxygen change. Moreover, considering serious effect oxygen reduction has on marine life and biogeochemical cycling, long-term oxygen change should be projected for higher validity. Therefore, we used a coupled atmosphere-ocean general circulation model (AOGCM) and an offline ocean biogeochemical model, investigating realistic long-term changes in oceanic oxygen concentration and ocean circulation. We integrated these models for 2000 years under atmospheric CO2 doubling and quadrupling. After global oxygen reduction in the first 500 years, oxygen concentration in deep ocean globally recovers and overshoots, despite surface oxygen decrease and weaker Atlantic Meridional Overturning Circulation. Deep ocean convection in the Weddell Sea recovers and overshoots, after initial cessation. Thus, enhanced deep convection and associated Antarctic Bottom Water supply oxygen-rich surface waters to deep ocean, resulting global deep ocean oxygenation. We conclude that the change in ocean circulation in the Southern Ocean potentially drives millennial-scale oxygenation in the deep ocean; contrary to past reported long-term oxygen reduction and general expectation. In presentation, we will discuss the mechanism of response of deep ocean convection in the Weddell Sea and show the volume changes of hypoxic waters.

Projected pH reductions by 2100 might put deep North Atlantic biodiversity at risk

NASA Astrophysics Data System (ADS)

Gehlen, M.; Séférian, R.; Jones, D. O. B.; Roy, T.; Roth, R.; Barry, J.; Bopp, L.; Doney, S. C.; Dunne, J. P.; Heinze, C.; Joos, F.; Orr, J. C.; Resplandy, L.; Segschneider, J.; Tjiputra, J.

2014-12-01

This study aims to evaluate the potential for impacts of ocean acidification on North Atlantic deep-sea ecosystems in response to IPCC AR5 Representative Concentration Pathways (RCPs). Deep-sea biota is likely highly vulnerable to changes in seawater chemistry and sensitive to moderate excursions in pH. Here we show, from seven fully coupled Earth system models, that for three out of four RCPs over 17% of the seafloor area below 500 m depth in the North Atlantic sector will experience pH reductions exceeding -0.2 units by 2100. Increased stratification in response to climate change partially alleviates the impact of ocean acidification on deep benthic environments. We report on major pH reductions over the deep North Atlantic seafloor (depth >500 m) and at important deep-sea features, such as seamounts and canyons. By 2100, and under the high CO2 scenario RCP8.5, pH reductions exceeding -0.2 (-0.3) units are projected in close to 23% (~15%) of North Atlantic deep-sea canyons and ~8% (3%) of seamounts - including seamounts proposed as sites of marine protected areas. The spatial pattern of impacts reflects the depth of the pH perturbation and does not scale linearly with atmospheric CO2 concentration. Impacts may cause negative changes of the same magnitude or exceeding the current target of 10% of preservation of marine biomes set by the convention on biological diversity, implying that ocean acidification may offset benefits from conservation/management strategies relying on the regulation of resource exploitation.

A patient-specific model of the biomechanics of hip reduction for neonatal Developmental Dysplasia of the Hip: Investigation of strategies for low to severe grades of Developmental Dysplasia of the Hip.

PubMed

Huayamave, Victor; Rose, Christopher; Serra, Sheila; Jones, Brendan; Divo, Eduardo; Moslehy, Faissal; Kassab, Alain J; Price, Charles T

2015-07-16

A physics-based computational model of neonatal Developmental Dysplasia of the Hip (DDH) following treatment with the Pavlik Harness (PV) was developed to obtain muscle force contribution in order to elucidate biomechanical factors influencing the reduction of dislocated hips. Clinical observation suggests that reduction occurs in deep sleep involving passive muscle action. Consequently, a set of five (5) adductor muscles were identified as mediators of reduction using the PV. A Fung/Hill-type model was used to characterize muscle response. Four grades (1-4) of dislocation were considered, with one (1) being a low subluxation and four (4) a severe dislocation. A three-dimensional model of the pelvis-femur lower limb of a representative 10 week-old female was generated based on CT-scans with the aid of anthropomorphic scaling of anatomical landmarks. The model was calibrated to achieve equilibrium at 90° flexion and 80° abduction. The hip was computationally dislocated according to the grade under investigation, the femur was restrained to move in an envelope consistent with PV restraints, and the dynamic response under passive muscle action and the effect of gravity was resolved. Model results with an anteversion angle of 50° show successful reduction Grades 1-3, while Grade 4 failed to reduce with the PV. These results are consistent with a previous study based on a simplified anatomically-consistent synthetic model and clinical reports of very low success of the PV for Grade 4. However our model indicated that it is possible to achieve reduction of Grade 4 dislocation by hyperflexion and the resultant external rotation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of plasma hydrogenation on trapping properties of dislocations in heteroepitaxial InP/GaAs

NASA Technical Reports Server (NTRS)

Ringel, S. A.; Chatterjee, B.

1994-01-01

In previous work, we have demonstrated the effectiveness of a post-growth hydrogen plasma treatment for passivating the electrical activity of dislocations in metalorganic chemical vapor deposition (MOCVD) grown InP on GaAs substrates by a more than two order of magnitude reduction in deep level concentration and an improvement in reverse bias leakage current by a factor of approximately 20. These results make plasma hydrogenation an extremely promising technique for achieving high efficiency large area and light weight heteroepitaxial InP solar cells for space applications. In this work we investigate the carrier trapping process by dislocations in heteroepitaxial InP/GaAs and the role of hydrogen passivation on this process. It is shown that the charge trapping kinetics of dislocations after hydrogen passivation are significantly altered, approaching point defect-like behavior consistent with a transformation from a high concentration of dislocation-related defect bands within the InP bandgap to a low concentration of individual dislocation related deep levels, before and after passivation. It is further shown that the 'apparent' activation energies of dislocation related deep levels, before and after passivation, reduce by approximately 70 meV as DLTS fill pulse times are increased from 1 microsecond to 1 millisecond. A model is proposed which explains these effects based on a reduction of Coulombic interaction between individual core sites along the dislocation cores by hydrogen incorporation. Knowledge of the trapping properties in these specific structures is important to develop optimum, low loss heteroepitaxial InP cells.

Acute multi-sgRNA knockdown of KEOPS complex genes reproduces the microcephaly phenotype of the stable knockout zebrafish model.

PubMed

Jobst-Schwan, Tilman; Schmidt, Johanna Magdalena; Schneider, Ronen; Hoogstraten, Charlotte A; Ullmann, Jeremy F P; Schapiro, David; Majmundar, Amar J; Kolb, Amy; Eddy, Kaitlyn; Shril, Shirlee; Braun, Daniela A; Poduri, Annapurna; Hildebrandt, Friedhelm

2018-01-01

Until recently, morpholino oligonucleotides have been widely employed in zebrafish as an acute and efficient loss-of-function assay. However, off-target effects and reproducibility issues when compared to stable knockout lines have compromised their further use. Here we employed an acute CRISPR/Cas approach using multiple single guide RNAs targeting simultaneously different positions in two exemplar genes (osgep or tprkb) to increase the likelihood of generating mutations on both alleles in the injected F0 generation and to achieve a similar effect as morpholinos but with the reproducibility of stable lines. This multi single guide RNA approach resulted in median likelihoods for at least one mutation on each allele of >99% and sgRNA specific insertion/deletion profiles as revealed by deep-sequencing. Immunoblot showed a significant reduction for Osgep and Tprkb proteins. For both genes, the acute multi-sgRNA knockout recapitulated the microcephaly phenotype and reduction in survival that we observed previously in stable knockout lines, though milder in the acute multi-sgRNA knockout. Finally, we quantify the degree of mutagenesis by deep sequencing, and provide a mathematical model to quantitate the chance for a biallelic loss-of-function mutation. Our findings can be generalized to acute and stable CRISPR/Cas targeting for any zebrafish gene of interest.

Seizure frequency reduction after posteromedial hypothalamus deep brain stimulation in drug-resistant epilepsy associated with intractable aggressive behavior.

PubMed

Benedetti-Isaac, Juan C; Torres-Zambrano, Martin; Vargas-Toscano, Andres; Perea-Castro, Esther; Alcalá-Cerra, Gabriel; Furlanetti, Luciano L; Reithmeier, Thomas; Tierney, Travis S; Anastasopoulos, Constantin; Fonoff, Erich T; Contreras Lopez, William Omar

2015-07-01

The aim of this study was to analyze the impact of deep brain stimulation (DBS) of the posteromedial hypothalamus (pHyp) on seizure frequency in patients with drug-resistant epilepsy (DRE) associated with intractable aggressive behavior (IAB). Data were collected retrospectively from nine patients, who received bilateral stereotactic pHyp-DBS for the treatment of medically intractable aggressive behavior, focusing on five patients who also had DRE. All patients were treated at the Colombian Center and Foundation of Epilepsy and Neurological Diseases-FIRE (Chapter of the International Bureau for Epilepsy), in Cartagena de Indias, Colombia from 2010 to 2014. Each case was evaluated previously by the institutional ethical committee, assessing the impact of aggressive behavior on the patient's family and social life, the humanitarian aspects of preserving the safety and physical integrity of caregivers, and the need to prevent self-harm. Epilepsy improvement was measured by a monthly seizure reduction percentage, comparing preoperative state and outcome. Additional response to epilepsy was defined by reduction of the antiepileptic drugs (AEDs). Aggressive behavior response was measured using the Overt Aggression Scale (OAS). All the patients with DRE associated with IAB presented a significant decrease of the rate of epileptic seizures after up to 4 years follow-up, achieving a general 89.6% average seizure reduction from the state before the surgery. Aggressiveness was significantly controlled, with evident improvement in the OAS, enhancing the quality of life of patients and families. In well-selected patients, DBS of the pHyp seems to be a safe and effective procedure for treatment of DRE associated with refractory aggressive behavior. Larger and prospective series are needed to define the pHyp as a target for DRE in different contexts. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Assessment of methods for methyl iodide emission reduction and pest control using a simulation model

NASA Astrophysics Data System (ADS)

Luo, Lifang; Ashworth, Daniel J.; Šimunek, Jirka; Xuan, Richeng; Yates, Scott R.

2013-02-01

The increasing registration of the fumigant methyl iodide within the USA has led to more concerns about its toxicity to workers and bystanders. Emission mitigation strategies are needed to protect the public and environmental health while providing effective pest control. The effectiveness of various methods on emissions reduction and pest control was assessed using a process-based mathematical model in this study. Firstly, comparisons between the simulated and laboratory measured emission fluxes and cumulative emissions were made for methyl iodide (MeI) under four emission reduction treatments: 1) control, 2) using soil with high organic matter content (HOM), 3) being covered by virtually impermeable film (VIF), and 4) irrigating soil surface following fumigation (Irrigation). Then the model was extended to simulate a broader range of emission reduction strategies for MeI, including 5) being covered by high density polyethylene (HDPE), 6) increasing injection depth from 30 cm to 46 cm (Deep), 7) HDPE + Deep, 8) adding a reagent at soil surface (Reagent), 9) Reagent + Irrigation, and 10) Reagent + HDPE. Furthermore, the survivability of three types of soil-borne pests (citrus nematodes [Tylenchulus semipenetrans], barnyard seeds [Echinochloa crus-galli], fungi [Fusarium oxysporum]) was also estimated for each scenario. Overall, the trend of the measured emission fluxes as well as total emission were reasonably reproduced by the model for treatments 1 through 4. Based on the numerical simulation, the ranking of effectiveness in total emission reduction was VIF (82.4%) > Reagent + HDPE (73.2%) > Reagent + Irrigation (43.0%) > Reagent (23.5%) > Deep + HDPE (19.3%) > HOM (17.6%) > Deep (13.0%) > Irrigation (11.9%) > HDPE (5.8%). The order for pest control efficacy suggests, VIF had the highest pest control efficacy, followed by Deep + HDPE, Irrigation, Reagent + Irrigation, HDPE, Deep, Reagent + HDPE, Reagent, and HOM. Therefore, VIF is the optimal method disregarding the cost of the film since it maximizes efficacy while minimizing volatility losses. Otherwise, the integrated methods such as Deep + HDPE and Reagent + Irrigation, are recommended.

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.

Projected pH reductions by 2100 might put deep North Atlantic biodiversity at risk

NASA Astrophysics Data System (ADS)

Gehlen, M.; Séférian, R.; Jones, D. O. B.; Roy, T.; Roth, R.; Barry, J.; Bopp, L.; Doney, S. C.; Dunne, J. P.; Heinze, C.; Joos, F.; Orr, J. C.; Resplandy, L.; Segschneider, J.; Tjiputra, J.

2014-06-01

This study aims at evaluating the potential for impacts of ocean acidification on North Atlantic deep-sea ecosystems in response to IPCC AR5 Representative Concentration Pathways (RCP). Deep-sea biota is likely highly vulnerable to changes in seawater chemistry and sensitive to moderate excursions in pH. Here we show, from seven fully-coupled Earth system models, that for three out of four RCPs over 17% of the seafloor area below 500 m depth in the North Atlantic sector will experience pH reductions exceeding -0.2 units by 2100. Increased stratification in response to climate change partially alleviates the impact of ocean acidification on deep benthic environment. We report major potential consequences of pH reductions for deep-sea biodiversity hotspots, such as seamounts and canyons. By 2100 and under the high CO2 scenario RCP8.5 pH reductions exceeding -0.2, (respectively -0.3) units are projected in close to 23% (~ 15%) of North Atlantic deep-sea canyons and ~ 8% (3%) of seamounts - including seamounts proposed as sites of marine protected areas. The spatial pattern of impacts reflects the depth of the pH perturbation and does not scale linearly with atmospheric CO2 concentration. Impacts may cause negative changes of the same magnitude or exceeding the current target of 10% of preservation of marine biomes set by the convention on biological diversity implying that ocean acidification may offset benefits from conservation/management strategies relying on the regulation of resource exploitation.

Advanced RF Front End Technology

NASA Technical Reports Server (NTRS)

Herman, M. I.; Valas, S.; Katehi, L. P. B.

2001-01-01

The ability to achieve low-mass low-cost micro/nanospacecraft for Deep Space exploration requires extensive miniaturization of all subsystems. The front end of the Telecommunication subsystem is an area in which major mass (factor of 10) and volume (factor of 100) reduction can be achieved via the development of new silicon based micromachined technology and devices. Major components that make up the front end include single-pole and double-throw switches, diplexer, and solid state power amplifier. JPL's Center For Space Microsystems - System On A Chip (SOAC) Program has addressed the challenges of front end miniaturization (switches and diplexers). Our objectives were to develop the main components that comprise a communication front end and enable integration in a single module that we refer to as a 'cube'. In this paper we will provide the latest status of our Microelectromechanical System (MEMS) switches and surface micromachined filter development. Based on the significant progress achieved we can begin to provide guidelines of the proper system insertion for these emerging technologies. Additional information is contained in the original extended abstract.

Super-resolution for asymmetric resolution of FIB-SEM 3D imaging using AI with deep learning.

PubMed

Hagita, Katsumi; Higuchi, Takeshi; Jinnai, Hiroshi

2018-04-12

Scanning electron microscopy equipped with a focused ion beam (FIB-SEM) is a promising three-dimensional (3D) imaging technique for nano- and meso-scale morphologies. In FIB-SEM, the specimen surface is stripped by an ion beam and imaged by an SEM installed orthogonally to the FIB. The lateral resolution is governed by the SEM, while the depth resolution, i.e., the FIB milling direction, is determined by the thickness of the stripped thin layer. In most cases, the lateral resolution is superior to the depth resolution; hence, asymmetric resolution is generated in the 3D image. Here, we propose a new approach based on an image-processing or deep-learning-based method for super-resolution of 3D images with such asymmetric resolution, so as to restore the depth resolution to achieve symmetric resolution. The deep-learning-based method learns from high-resolution sub-images obtained via SEM and recovers low-resolution sub-images parallel to the FIB milling direction. The 3D morphologies of polymeric nano-composites are used as test images, which are subjected to the deep-learning-based method as well as conventional methods. We find that the former yields superior restoration, particularly as the asymmetric resolution is increased. Our super-resolution approach for images having asymmetric resolution enables observation time reduction.

The interaction between short-term heat-treatment and the formability of an Al-Mg-Si alloy regarding deep drawing processes

NASA Astrophysics Data System (ADS)

Machhammer, M.; Sommitsch, C.

2016-11-01

Research conducted in recent years has shown that heat-treatable Al-Mg-Si alloys (6xxx) have great potential concerning the design of lightweight car bodies. Compared to conventional deep drawing steels the field of application is limited by a lower formability. In order to minimize the disadvantage of a lower drawability a short-term heat-treatment (SHT) can be applied before the forming process. The SHT, conducted in selected areas on the initial blank, leads to a local reduction of strength aiming at the decrease of critical stress during the deep drawing process. For the successful procedure of the SHT a solid knowledge about the crucial process parameters such as the design of the SHT layout, the SHT process time and the maximum SHT temperature are urgently required. It also should be noted that the storage time between the SHT and the forming processes affects the mechanical properties of the SHT area. In this paper, the effect of diverse SHT process parameters and various storage time-frames on the major and minor strain situation of a deep drawn part is discussed by the evaluation of the forming limit diagram. For the purpose of achieving short heating times and a homogenous temperature distribution a one side contact heating tool has been used for the heat treatment in this study.

50 CFR 229.37 - False Killer Whale Take Reduction Plan.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Hawaii Pelagic and Hawaii Insular stocks of false killer whales in the Hawaii-based deep-set and shallow... section have the following meanings: (1) Deep-set or Deep-setting has the same meaning as the definition... this title. (c) Gear requirements. (1) While deep-setting, the owner and operator of a vessel...

50 CFR 229.37 - False Killer Whale Take Reduction Plan.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Hawaii Pelagic and Hawaii Insular stocks of false killer whales in the Hawaii-based deep-set and shallow... section have the following meanings: (1) Deep-set or Deep-setting has the same meaning as the definition... this title. (c) Gear requirements. (1) While deep-setting, the owner and operator of a vessel...

Gas6 Promotes Inflammatory (CCR2hiCX3CR1lo) Monocyte Recruitment in Venous Thrombosis.

PubMed

Laurance, Sandrine; Bertin, François-René; Ebrahimian, Talin; Kassim, Yusra; Rys, Ryan N; Lehoux, Stéphanie; Lemarié, Catherine A; Blostein, Mark D

2017-07-01

Coagulation and inflammation are inter-related. Gas6 (growth arrest-specific 6) promotes venous thrombosis and participates to inflammation through endothelial-innate immune cell interactions. Innate immune cells can provide the initiating stimulus for venous thrombus development. We hypothesize that Gas6 promotes monocyte recruitment during venous thrombosis. Deep venous thrombosis was induced in wild-type and Gas6-deficient (-/-) mice using 5% FeCl 3 and flow reduction in the inferior vena cava. Total monocyte depletion was achieved by injection of clodronate before deep venous thrombosis. Inflammatory monocytes were depleted using an anti-C-C chemokine receptor type 2 (CCR2) antibody. Similarly, injection of an anti-chemokine ligand 2 (CCL2) antibody induced CCL2 depletion. Flow cytometry and immunofluorescence were used to characterize the monocytes recruited to the thrombus. In vivo, absence of Gas6 was associated with a reduction of monocyte recruitment in both deep venous thrombosis models. Global monocyte depletion by clodronate leads to smaller thrombi in wild-type mice. Compared with wild type, the thrombi from Gas6 -/- mice contain less inflammatory (CCR2 hi CX 3 CR1 lo ) monocytes, consistent with a Gas6-dependent recruitment of this monocyte subset. Correspondingly, selective depletion of CCR2 hi CX 3 CR1 lo monocytes reduced the formation of venous thrombi in wild-type mice demonstrating a predominant role of the inflammatory monocytes in thrombosis. In vitro, the expression of both CCR2 and CCL2 were Gas6 dependent in monocytes and endothelial cells, respectively, impacting monocyte migration. Moreover, Gas6-dependent CCL2 expression and monocyte migration were mediated via JNK (c-Jun N-terminal kinase). This study demonstrates that Gas6 specifically promotes the recruitment of inflammatory CCR2 hi CX 3 CR1 lo monocytes through the regulation of both CCR2 and CCL2 during deep venous thrombosis. © 2017 American Heart Association, Inc.

30 CFR 203.43 - To which production do I apply the RSV earned from qualified deep wells or qualified phase 1...

Code of Federal Regulations, 2011 CFR

2011-07-01

... INTERIOR MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.43 To... less than 200 meters deep, you began drilling an original deep well with a perforated interval the top...

Microbial Sulfate Reduction Potential in Coal-Bearing Sediments Down to ~2.5 km below the Seafloor off Shimokita Peninsula, Japan

PubMed Central

Glombitza, Clemens; Adhikari, Rishi R.; Riedinger, Natascha; Gilhooly, William P.; Hinrichs, Kai-Uwe; Inagaki, Fumio

2016-01-01

Sulfate reduction is the predominant anaerobic microbial process of organic matter mineralization in marine sediments, with recent studies revealing that sulfate reduction not only occurs in sulfate-rich sediments, but even extends to deeper, methanogenic sediments at very low background concentrations of sulfate. Using samples retrieved off the Shimokita Peninsula, Japan, during the Integrated Ocean Drilling Program (IODP) Expedition 337, we measured potential sulfate reduction rates by slurry incubations with 35S-labeled sulfate in deep methanogenic sediments between 1276.75 and 2456.75 meters below the seafloor. Potential sulfate reduction rates were generally extremely low (mostly below 0.1 pmol cm−3 d−1) but showed elevated values (up to 1.8 pmol cm−3 d−1) in a coal-bearing interval (Unit III). A measured increase in hydrogenase activity in the coal-bearing horizons coincided with this local increase in potential sulfate reduction rates. This paired enzymatic response suggests that hydrogen is a potentially important electron donor for sulfate reduction in the deep coalbed biosphere. By contrast, no stimulation of sulfate reduction rates was observed in treatments where methane was added as an electron donor. In the deep coalbeds, small amounts of sulfate might be provided by a cryptic sulfur cycle. The isotopically very heavy pyrites (δ34S = +43‰) found in this horizon is consistent with its formation via microbial sulfate reduction that has been continuously utilizing a small, increasingly 34S-enriched sulfate reservoir over geologic time scales. Although our results do not represent in-situ activity, and the sulfate reducers might only have persisted in a dormant, spore-like state, our findings show that organisms capable of sulfate reduction have survived in deep methanogenic sediments over more than 20 Ma. This highlights the ability of sulfate-reducers to persist over geological timespans even in sulfate-depleted environments. Our study moreover represents the deepest evidence of a potential for sulfate reduction in marine sediments to date. PMID:27761134

Microbial Sulfate Reduction Potential in Coal-Bearing Sediments Down to ~2.5 km below the Seafloor off Shimokita Peninsula, Japan.

PubMed

Glombitza, Clemens; Adhikari, Rishi R; Riedinger, Natascha; Gilhooly, William P; Hinrichs, Kai-Uwe; Inagaki, Fumio

2016-01-01

Sulfate reduction is the predominant anaerobic microbial process of organic matter mineralization in marine sediments, with recent studies revealing that sulfate reduction not only occurs in sulfate-rich sediments, but even extends to deeper, methanogenic sediments at very low background concentrations of sulfate. Using samples retrieved off the Shimokita Peninsula, Japan, during the Integrated Ocean Drilling Program (IODP) Expedition 337, we measured potential sulfate reduction rates by slurry incubations with 35 S-labeled sulfate in deep methanogenic sediments between 1276.75 and 2456.75 meters below the seafloor. Potential sulfate reduction rates were generally extremely low (mostly below 0.1 pmol cm -3 d -1 ) but showed elevated values (up to 1.8 pmol cm -3 d -1 ) in a coal-bearing interval (Unit III). A measured increase in hydrogenase activity in the coal-bearing horizons coincided with this local increase in potential sulfate reduction rates. This paired enzymatic response suggests that hydrogen is a potentially important electron donor for sulfate reduction in the deep coalbed biosphere. By contrast, no stimulation of sulfate reduction rates was observed in treatments where methane was added as an electron donor. In the deep coalbeds, small amounts of sulfate might be provided by a cryptic sulfur cycle. The isotopically very heavy pyrites (δ 34 S = +43‰) found in this horizon is consistent with its formation via microbial sulfate reduction that has been continuously utilizing a small, increasingly 34 S-enriched sulfate reservoir over geologic time scales. Although our results do not represent in-situ activity, and the sulfate reducers might only have persisted in a dormant, spore-like state, our findings show that organisms capable of sulfate reduction have survived in deep methanogenic sediments over more than 20 Ma. This highlights the ability of sulfate-reducers to persist over geological timespans even in sulfate-depleted environments. Our study moreover represents the deepest evidence of a potential for sulfate reduction in marine sediments to date.

Efficacy of two types of palliative sedation therapy defined using intervention protocols: proportional vs. deep sedation.

PubMed

Imai, Kengo; Morita, Tatsuya; Yokomichi, Naosuke; Mori, Masanori; Naito, Akemi Shirado; Tsukuura, Hiroaki; Yamauchi, Toshihiro; Kawaguchi, Takashi; Fukuta, Kaori; Inoue, Satoshi

2018-06-01

This study investigated the effect of two types of palliative sedation defined using intervention protocols: proportional and deep sedation. We retrospectively analyzed prospectively recorded data of consecutive cancer patients who received the continuous infusion of midazolam in a palliative care unit. Attending physicians chose the sedation protocol based on each patient's wish, symptom severity, prognosis, and refractoriness of suffering. The primary endpoint was a treatment goal achievement at 4 h: in proportional sedation, the achievement of symptom relief (Support Team Assessment Schedule (STAS) ≤ 1) and absence of agitation (modified Richmond Agitation-Sedation Scale (RASS) ≤ 0) and in deep sedation, the achievement of deep sedation (RASS ≤ - 4). Secondary endpoints included mean scores of STAS and RASS, deep sedation as a result, and adverse events. Among 398 patients who died during the period, 32 received proportional and 18 received deep sedation. The treatment goal achievement rate was 68.8% (22/32, 95% confidence interval 52.7-84.9) in the proportional sedation group vs. 83.3% (15/18, 66.1-100) in the deep sedation group. STAS decreased from 3.8 to 0.8 with proportional sedation at 4 h vs. 3.7 to 0.3 with deep sedation; RASS decreased from + 1.2 to - 1.7 vs. + 1.4 to - 3.7, respectively. Deep sedation was needed as a result in 31.3% (10/32) of the proportional sedation group. No fatal events that were considered as probably or definitely related to the intervention occurred. The two types of intervention protocol well reflected the treatment intention and expected outcomes. Further, large-scale cohort studies are promising.

Fusion of Deep Learning and Compressed Domain features for Content Based Image Retrieval.

PubMed

Liu, Peizhong; Guo, Jing-Ming; Wu, Chi-Yi; Cai, Danlin

2017-08-29

This paper presents an effective image retrieval method by combining high-level features from Convolutional Neural Network (CNN) model and low-level features from Dot-Diffused Block Truncation Coding (DDBTC). The low-level features, e.g., texture and color, are constructed by VQ-indexed histogram from DDBTC bitmap, maximum, and minimum quantizers. Conversely, high-level features from CNN can effectively capture human perception. With the fusion of the DDBTC and CNN features, the extended deep learning two-layer codebook features (DL-TLCF) is generated using the proposed two-layer codebook, dimension reduction, and similarity reweighting to improve the overall retrieval rate. Two metrics, average precision rate (APR) and average recall rate (ARR), are employed to examine various datasets. As documented in the experimental results, the proposed schemes can achieve superior performance compared to the state-of-the-art methods with either low- or high-level features in terms of the retrieval rate. Thus, it can be a strong candidate for various image retrieval related applications.

Deep learning methods for protein torsion angle prediction.

PubMed

Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

2017-09-18

Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

Task- and Self-Related Pathways to Deep Learning: The Mediating Role of Achievement Goals, Classroom Attentiveness, and Group Participation

ERIC Educational Resources Information Center

Lau, Shun; Liem, Arief Darmanegara; Nie, Youyan

2008-01-01

Background: The expectancy-value and achievement goal theories are arguably the two most dominant theories of achievement motivation in the contemporary literature. However, very few studies have examined how the constructs derived from both theories are related to deep learning. Moreover, although there is evidence demonstrating the links between…

Could US mayors achieve the entire US Paris climate target?

NASA Astrophysics Data System (ADS)

Gurney, K. R.; Huang, J.; Hutchins, M.; Liang, J.

2017-12-01

After the recent US Federal Administration announcement not to adhere to the Paris Accords, 359 mayors (and counting) in the US pledged to maintain their commitments, reducing emissions within their jurisdictions by 26-28% from their 2005 levels by the year 2025. While important, this leaves a large portion of the US landscape, and a large amount of US emissions, outside of the Paris commitment. With Federal US policy looking unlikely to change, could additional effort by US cities overcome the gap in national policy and achieve the equivalent US national Paris commitment? How many cities would be required and how deep would reductions need to be? Up until now, this question could not be reliably resolved due to lack of data at the urban scale. Here, we answer this question with new data - the Vulcan V3.0 FFCO2 emissions data product - through examination of the total US energy related CO2 emissions from cities. We find that the top 500 urban areas in the US could meet the national US commitment to the Paris Accords with a reduction of roughly 30% below their 2015 levels by the year 2025. This is driven by the share of US emissions emanating from cities, particularly the largest cohort. Indeed, as the number of urban areas taking on CO2 reduction targets grows, the less the reduction burden on any individual city. In this presentation, we provide an analysis of US urban CO2 emissions and US climate policy, accounting for varying definitions of urban areas, emitting sectors and the tradeoff between the number of policy-active cities and the CO2 reduction burden.

Is there a role for intramedullary nails in the treatment of simple pilon fractures? Rationale and preliminary results.

PubMed

Marcus, Matthew S; Yoon, Richard S; Langford, Joshua; Kubiak, Erik N; Morris, Andrew J; Koval, Kenneth J; Haidukewych, George J; Liporace, Frank A

2013-08-01

Certain patients with pilon fractures present with significant soft-tissue swelling or with a poor soft-tissue envelope typically not amenable to definitive fixation in the early time period. The objective of this study was to review the treatment of simple intra-articular fractures of the tibial plafond (Arbeitsgemeinschaft für Osteosynthesefragen/Orthopaedic Trauma Association (AO/OTA) type 43C1-C2) via intramedullary nailing (IMN) with the assessment of clinical and radiographic results and any associated complications. Retrospective clinical and radiological reviews of 31 patients sustaining AO/OTA type 43C distal tibial fractures treated with IMN were evaluated. Our main outcome measurement included achievable alignment in the immediate postoperative period and at the time of union along with complications or need for secondary procedures within the first year of follow-up. Seven patients were lost to follow-up. All the remaining patients achieved bony union at a mean union time of 14.1 ± 4.9 weeks with no evidence of malunion or malrotation. All patients were at full-weight-bearing status at 1-year follow-up. Complications were notable for one delayed union, one non-union, one patient with superficial wound drainage, two with deep infection, one with symptomatic hardware and one with deep vein thrombosis. Simple articular fractures of the tibial plafond (AO/OTA type 43C) treated via IMN can achieve excellent alignment and union rates with proper patient selection and surgical indication. One should not hesitate to use additional bone screws or plating options to help achieve better anatomic reduction. However, larger, prospective randomised trials comparing plating versus nailing, in experienced hands, are needed to completely delineate the utility of this treatment modality. Copyright © 2013 Elsevier Ltd. All rights reserved.

30 CFR 203.41 - If I have a qualified deep well or a qualified phase 1 ultra-deep well, what royalty relief would...

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.41 If I have... not . . . And if it later . . . Then your lease . . . (1) produced gas or oil from any deep well or...

30 CFR 203.40 - Which leases are eligible for royalty relief as a result of drilling a deep well or a phase 1...

Code of Federal Regulations, 2011 CFR

2011-07-01

... a result of drilling a deep well or a phase 1 ultra-deep well? 203.40 Section 203.40 Mineral... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.40 Which...

30 CFR 203.44 - What administrative steps must I take to use the royalty suspension volume?

Code of Federal Regulations, 2011 CFR

2011-07-01

... REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on... in writing of your intent to begin drilling operations on all deep wells and phase 1 ultra-deep wells...

Understanding the contribution of non-carbon dioxide gases in deep mitigation scenarios

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

Gernaat, David; Calvin, Katherine V.; Lucas, Paul

2015-07-01

The combined 2010 emissions of methane (CH4), nitrous oxide (N2O) and the fluorinated gasses (F-gas) account for about 20-30% of total emissions and about 30% of radiative forcing. At the moment, most studies looking at reaching ambitious climate targets project the emission of carbon dioxide (CO2) to be reduced to zero (or less) by the end of the century. As for non-CO2 gases, the mitigation potential seem to be more constrained, we find that by the end of the century in the current deep mitigation scenarios non-CO2 emissions could form the lion’s share of remaining greenhouse gas emissions. In ordermore » to support effective climate policy strategies, in this paper we provide a more in-depth look at the role of non-CO2¬ emission sources (CH4, N2O and F-gases) in achieving deep mitigation targets (radiative forcing target of 2.8 W/m2 in 2100). Specifically, we look at the sectorial mitigation potential and the remaining non-CO2 emissions. By including a set of different models, we provide some insights into the associated uncertainty. Most of the remaining methane emissions in 2100 in the climate mitigation scenario come from the livestock sector. Strong reductions are seen in the energy supply sector across all models. For N2O, less reduction potential is seen compared to methane and the sectoral differences are larger between the models. The paper shows that the assumptions on remaining non-CO2 emissions are critical for the feasibility of reaching ambitious climate targets and the associated costs.« less

To master or perform? Exploring relations between achievement goals and conceptual change learning.

PubMed

Ranellucci, John; Muis, Krista R; Duffy, Melissa; Wang, Xihui; Sampasivam, Lavanya; Franco, Gina M

2013-09-01

Research is needed to explore conceptual change in relation to achievement goal orientations and depth of processing. To address this need, we examined relations between achievement goals, use of deep versus shallow processing strategies, and conceptual change learning using a think-aloud protocol. Seventy-three undergraduate students were assessed on their prior knowledge and misconceptions about Newtonian mechanics, and then reported their achievement goals and participated in think-aloud protocols while reading Newtonian physics texts. A mastery-approach goal orientation positively predicted deep processing strategies, shallow processing strategies, and conceptual change. In contrast, a performance-approach goal orientation did not predict either of the processing strategies, but negatively predicted conceptual change. A performance-avoidance goal orientation negatively predicted deep processing strategies and conceptual change. Moreover, deep and shallow processing strategies positively predicted conceptual change as well as recall. Finally, both deep and shallow processing strategies mediated relations between mastery-approach goals and conceptual change. Results provide some support for Dole and Sinatra's (1998) Cognitive Reconstruction of Knowledge Model of conceptual change but also challenge specific facets with regard to the role of depth of processing in conceptual change. © 2012 The British Psychological Society.

Acute multi-sgRNA knockdown of KEOPS complex genes reproduces the microcephaly phenotype of the stable knockout zebrafish model

PubMed Central

Schneider, Ronen; Hoogstraten, Charlotte A.; Schapiro, David; Majmundar, Amar J.; Kolb, Amy; Eddy, Kaitlyn; Shril, Shirlee; Braun, Daniela A.; Poduri, Annapurna

2018-01-01

Until recently, morpholino oligonucleotides have been widely employed in zebrafish as an acute and efficient loss-of-function assay. However, off-target effects and reproducibility issues when compared to stable knockout lines have compromised their further use. Here we employed an acute CRISPR/Cas approach using multiple single guide RNAs targeting simultaneously different positions in two exemplar genes (osgep or tprkb) to increase the likelihood of generating mutations on both alleles in the injected F0 generation and to achieve a similar effect as morpholinos but with the reproducibility of stable lines. This multi single guide RNA approach resulted in median likelihoods for at least one mutation on each allele of >99% and sgRNA specific insertion/deletion profiles as revealed by deep-sequencing. Immunoblot showed a significant reduction for Osgep and Tprkb proteins. For both genes, the acute multi-sgRNA knockout recapitulated the microcephaly phenotype and reduction in survival that we observed previously in stable knockout lines, though milder in the acute multi-sgRNA knockout. Finally, we quantify the degree of mutagenesis by deep sequencing, and provide a mathematical model to quantitate the chance for a biallelic loss-of-function mutation. Our findings can be generalized to acute and stable CRISPR/Cas targeting for any zebrafish gene of interest. PMID:29346415

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.

Tunnel-injected sub-260 nm ultraviolet light emitting diodes

NASA Astrophysics Data System (ADS)

Zhang, Yuewei; Krishnamoorthy, Sriram; Akyol, Fatih; Bajaj, Sanyam; Allerman, Andrew A.; Moseley, Michael W.; Armstrong, Andrew M.; Rajan, Siddharth

2017-05-01

We report on tunnel-injected deep ultraviolet light emitting diodes (UV LEDs) configured with a polarization engineered Al0.75Ga0.25 N/In0.2Ga0.8 N tunnel junction structure. Tunnel-injected UV LED structure enables n-type contacts for both bottom and top contact layers. However, achieving Ohmic contact to wide bandgap n-AlGaN layers is challenging and typically requires high temperature contact metal annealing. In this work, we adopted a compositionally graded top contact layer for non-alloyed metal contact and obtained a low contact resistance of ρc = 4.8 × 10-5 Ω cm2 on n-Al0.75Ga0.25 N. We also observed a significant reduction in the forward operation voltage from 30.9 V to 19.2 V at 1 kA/cm2 by increasing the Mg doping concentration from 6.2 × 1018 cm-3 to 1.5 × 1019 cm-3. Non-equilibrium hole injection into wide bandgap Al0.75Ga0.25 N with Eg>5.2 eV was confirmed by light emission at 257 nm. This work demonstrates the feasibility of tunneling hole injection into deep UV LEDs and provides a structural design towards high power deep-UV emitters.

Integration of adaptive guided filtering, deep feature learning, and edge-detection techniques for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Gao, Bing

2017-11-01

The integration of an edge-preserving filtering technique in the classification of a hyperspectral image (HSI) has been proven effective in enhancing classification performance. This paper proposes an ensemble strategy for HSI classification using an edge-preserving filter along with a deep learning model and edge detection. First, an adaptive guided filter is applied to the original HSI to reduce the noise in degraded images and to extract powerful spectral-spatial features. Second, the extracted features are fed as input to a stacked sparse autoencoder to adaptively exploit more invariant and deep feature representations; then, a random forest classifier is applied to fine-tune the entire pretrained network and determine the classification output. Third, a Prewitt compass operator is further performed on the HSI to extract the edges of the first principal component after dimension reduction. Moreover, the regional growth rule is applied to the resulting edge logical image to determine the local region for each unlabeled pixel. Finally, the categories of the corresponding neighborhood samples are determined in the original classification map; then, the major voting mechanism is implemented to generate the final output. Extensive experiments proved that the proposed method achieves competitive performance compared with several traditional approaches.

The response of abyssal organisms to low pH conditions during a series of CO2-release experiments simulating deep-sea carbon sequestration

NASA Astrophysics Data System (ADS)

Barry, J. P.; Buck, K. R.; Lovera, C.; Brewer, P. G.; Seibel, B. A.; Drazen, J. C.; Tamburri, M. N.; Whaling, P. J.; Kuhnz, L.; Pane, E. F.

2013-08-01

The effects of low-pH, high-pCO2 conditions on deep-sea organisms were examined during four deep-sea CO2 release experiments simulating deep-ocean C sequestration by the direct injection of CO2 into the deep sea. We examined the survival of common deep-sea, benthic organisms (microbes; macrofauna, dominated by Polychaeta, Nematoda, Crustacea, Mollusca; megafauna, Echinodermata, Mollusca, Pisces) exposed to low-pH waters emanating as a dissolution plume from pools of liquid carbon dioxide released on the seabed during four abyssal CO2-release experiments. Microbial abundance in deep-sea sediments was unchanged in one experiment, but increased under environmental hypercapnia during another, where the microbial assemblage may have benefited indirectly from the negative impact of low-pH conditions on other taxa. Lower abyssal metazoans exhibited low survival rates near CO2 pools. No urchins or holothurians survived during 30-42 days of exposure to episodic, but severe environmental hypercapnia during one experiment (E1; pH reduced by as much as ca. 1.4 units). These large pH reductions also caused 75% mortality for the deep-sea amphipod, Haploops lodo, near CO2 pools. Survival under smaller pH reductions (ΔpH<0.4 units) in other experiments (E2, E3, E5) was higher for all taxa, including echinoderms. Gastropods, cephalopods, and fish were more tolerant than most other taxa. The gastropod Retimohnia sp. and octopus Benthoctopus sp. survived exposure to pH reductions that episodically reached -0.3 pH units. Ninety percent of abyssal zoarcids (Pachycara bulbiceps) survived exposure to pH changes reaching ca. -0.3 pH units during 30-42 day-long experiments.

Quantitative phase microscopy using deep neural networks

NASA Astrophysics Data System (ADS)

Li, Shuai; Sinha, Ayan; Lee, Justin; Barbastathis, George

2018-02-01

Deep learning has been proven to achieve ground-breaking accuracy in various tasks. In this paper, we implemented a deep neural network (DNN) to achieve phase retrieval in a wide-field microscope. Our DNN utilized the residual neural network (ResNet) architecture and was trained using the data generated by a phase SLM. The results showed that our DNN was able to reconstruct the profile of the phase target qualitatively. In the meantime, large error still existed, which indicated that our approach still need to be improved.

Effect of the antimicrobial photodynamic therapy on microorganism reduction in deep caries lesions: a systematic review and meta-analysis.

PubMed

Ornellas, Pâmela Oliveira; Antunes, Leonardo Dos Santos; Fontes, Karla Bianca Fernandes da Costa; Póvoa, Helvécio Cardoso Corrêa; Küchler, Erika Calvano; Iorio, Natalia Lopes Pontes; Antunes, Lívia Azeredo Alves

2016-09-01

This study aimed to perform a systematic review to assess the effectiveness of antimicrobial photodynamic therapy (aPDT) in the reduction of microorganisms in deep carious lesions. An electronic search was conducted in Pubmed, Web of Science, Scopus, Lilacs, and Cochrane Library, followed by a manual search. The MeSH terms, MeSH synonyms, related terms, and free terms were used in the search. As eligibility criteria, only clinical studies were included. Initially, 227 articles were identified in the electronic search, and 152 studies remained after analysis and exclusion of the duplicated studies; 6 remained after application of the eligibility criteria; and 3 additional studies were found in the manual search. After access to the full articles, three were excluded, leaving six for evaluation by the criteria of the Cochrane Collaboration’s tool for assessing risk of bias. Of these, five had some risk of punctuated bias. All results from the selected studies showed a significant reduction of microorganisms in deep carious lesions for both primary and permanent teeth. The meta-analysis demonstrated a significant reduction in microorganism counts in all analyses (p<0.00001). Based on these findings, there is scientific evidence emphasizing the effectiveness of aPDT in reducing microorganisms in deep carious lesions.

Effect of the antimicrobial photodynamic therapy on microorganism reduction in deep caries lesions: a systematic review and meta-analysis

NASA Astrophysics Data System (ADS)

Ornellas, Pâmela Oliveira; Antunes, Leonardo Santos; Fontes, Karla Bianca Fernandes da Costa; Póvoa, Helvécio Cardoso Corrêa; Küchler, Erika Calvano; Iorio, Natalia Lopes Pontes; Antunes, Lívia Azeredo Alves

2016-09-01

This study aimed to perform a systematic review to assess the effectiveness of antimicrobial photodynamic therapy (aPDT) in the reduction of microorganisms in deep carious lesions. An electronic search was conducted in Pubmed, Web of Science, Scopus, Lilacs, and Cochrane Library, followed by a manual search. The MeSH terms, MeSH synonyms, related terms, and free terms were used in the search. As eligibility criteria, only clinical studies were included. Initially, 227 articles were identified in the electronic search, and 152 studies remained after analysis and exclusion of the duplicated studies; 6 remained after application of the eligibility criteria; and 3 additional studies were found in the manual search. After access to the full articles, three were excluded, leaving six for evaluation by the criteria of the Cochrane Collaboration's tool for assessing risk of bias. Of these, five had some risk of punctuated bias. All results from the selected studies showed a significant reduction of microorganisms in deep carious lesions for both primary and permanent teeth. The meta-analysis demonstrated a significant reduction in microorganism counts in all analyses (p<0.00001). Based on these findings, there is scientific evidence emphasizing the effectiveness of aPDT in reducing microorganisms in deep carious lesions.

Plant Species Identification by Bi-channel Deep Convolutional Networks

NASA Astrophysics Data System (ADS)

He, Guiqing; Xia, Zhaoqiang; Zhang, Qiqi; Zhang, Haixi; Fan, Jianping

2018-04-01

Plant species identification achieves much attention recently as it has potential application in the environmental protection and human life. Although deep learning techniques can be directly applied for plant species identification, it still needs to be designed for this specific task to obtain the state-of-art performance. In this paper, a bi-channel deep learning framework is developed for identifying plant species. In the framework, two different sub-networks are fine-tuned over their pretrained models respectively. And then a stacking layer is used to fuse the output of two different sub-networks. We construct a plant dataset of Orchidaceae family for algorithm evaluation. Our experimental results have demonstrated that our bi-channel deep network can achieve very competitive performance on accuracy rates compared to the existing deep learning algorithm.

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...

30 CFR 203.31 - If I have a qualified phase 2 or qualified phase 3 ultra-deep well, what royalty relief would...

Code of Federal Regulations, 2011 CFR

2011-07-01

... INTERIOR MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra-Deep Wells on Leases Not Subject to Deep Water Royalty Relief § 203.31... applies if your lease: (i) Has produced gas or oil from a deep well with a perforated interval the top of...

Classification of breast MRI lesions using small-size training sets: comparison of deep learning approaches

NASA Astrophysics Data System (ADS)

Amit, Guy; Ben-Ari, Rami; Hadad, Omer; Monovich, Einat; Granot, Noa; Hashoul, Sharbell

2017-03-01

Diagnostic interpretation of breast MRI studies requires meticulous work and a high level of expertise. Computerized algorithms can assist radiologists by automatically characterizing the detected lesions. Deep learning approaches have shown promising results in natural image classification, but their applicability to medical imaging is limited by the shortage of large annotated training sets. In this work, we address automatic classification of breast MRI lesions using two different deep learning approaches. We propose a novel image representation for dynamic contrast enhanced (DCE) breast MRI lesions, which combines the morphological and kinetics information in a single multi-channel image. We compare two classification approaches for discriminating between benign and malignant lesions: training a designated convolutional neural network and using a pre-trained deep network to extract features for a shallow classifier. The domain-specific trained network provided higher classification accuracy, compared to the pre-trained model, with an area under the ROC curve of 0.91 versus 0.81, and an accuracy of 0.83 versus 0.71. Similar accuracy was achieved in classifying benign lesions, malignant lesions, and normal tissue images. The trained network was able to improve accuracy by using the multi-channel image representation, and was more robust to reductions in the size of the training set. A small-size convolutional neural network can learn to accurately classify findings in medical images using only a few hundred images from a few dozen patients. With sufficient data augmentation, such a network can be trained to outperform a pre-trained out-of-domain classifier. Developing domain-specific deep-learning models for medical imaging can facilitate technological advancements in computer-aided diagnosis.

Formability of paperboard during deep-drawing with local steam application

NASA Astrophysics Data System (ADS)

Franke, Wilken; Stein, Philipp; Dörsam, Sven; Groche, Peter

2018-05-01

The use of paperboard can significantly improve the environmental compatibility of everyday products such as packages. Nevertheless, most packages are currently made of plastics, since the three-dimensional shaping of paperboard is possible only to a limited extent. In order to increase the forming possibilities, deep drawing of cardboard has been intensively investigated for more than a decade. An improvement with regard to increased forming limits has been achieved by heating of the tool parts, which leads to a softening of paperboard constituents such as lignin. A further approach is the moistening of the samples, whereby the hydrogen bonds between the fibers are weakened and as a result an increase of the formability. It is expected that a combination of both parameter approaches will result in a significant increase in the forming capacity and in the shape accuracy. For this reason, a new tool concept is introduced within the scope of this work which makes it possible to moisten samples during the deep drawing process by means of steam supply. The conducted investigations show that spring-back in the preferred fiber direction can be reduced by 38 %. Orthogonal to the preferred fiber direction a reduction of spring back of up to 79 % is determined, which corresponds to a perfect shape. Moreover, it was determined that the steam duration and the initial moisture content have an influence on the final shape. In addition to the increased dimensional accuracy, an optimized wrinkle compression compared to conventional deep drawing is found. According to the results, it can be summarized that a steam application in the deep drawing of paperboard significantly improves the part quality.

Homoacetogenesis in Deep-Sea Chloroflexi, as Inferred by Single-Cell Genomics, Provides a Link to Reductive Dehalogenation in Terrestrial Dehalococcoidetes.

PubMed

Sewell, Holly L; Kaster, Anne-Kristin; Spormann, Alfred M

2017-12-19

The deep marine subsurface is one of the largest unexplored biospheres on Earth and is widely inhabited by members of the phylum Chloroflexi In this report, we investigated genomes of single cells obtained from deep-sea sediments of the Peruvian Margin, which are enriched in such Chloroflexi 16S rRNA gene sequence analysis placed two of these single-cell-derived genomes (DscP3 and Dsc4) in a clade of subphylum I Chloroflexi which were previously recovered from deep-sea sediment in the Okinawa Trough and a third (DscP2-2) as a member of the previously reported DscP2 population from Peruvian Margin site 1230. The presence of genes encoding enzymes of a complete Wood-Ljungdahl pathway, glycolysis/gluconeogenesis, a Rhodobacter nitrogen fixation (Rnf) complex, glyosyltransferases, and formate dehydrogenases in the single-cell genomes of DscP3 and Dsc4 and the presence of an NADH-dependent reduced ferredoxin:NADP oxidoreductase (Nfn) and Rnf in the genome of DscP2-2 imply a homoacetogenic lifestyle of these abundant marine Chloroflexi We also report here the first complete pathway for anaerobic benzoate oxidation to acetyl coenzyme A (CoA) in the phylum Chloroflexi (DscP3 and Dsc4), including a class I benzoyl-CoA reductase. Of remarkable evolutionary significance, we discovered a gene encoding a formate dehydrogenase (FdnI) with reciprocal closest identity to the formate dehydrogenase-like protein (complex iron-sulfur molybdoenzyme [CISM], DET0187) of terrestrial Dehalococcoides/Dehalogenimonas spp. This formate dehydrogenase-like protein has been shown to lack formate dehydrogenase activity in Dehalococcoides/Dehalogenimonas spp. and is instead hypothesized to couple HupL hydrogenase to a reductive dehalogenase in the catabolic reductive dehalogenation pathway. This finding of a close functional homologue provides an important missing link for understanding the origin and the metabolic core of terrestrial Dehalococcoides/Dehalogenimonas spp. and of reductive dehalogenation, as well as the biology of abundant deep-sea Chloroflexi IMPORTANCE The deep marine subsurface is one of the largest unexplored biospheres on Earth and is widely inhabited by members of the phylum Chloroflexi In this report, we investigated genomes of single cells obtained from deep-sea sediments and provide evidence for a homacetogenic lifestyle of these abundant marine Chloroflexi Moreover, genome signature and key metabolic genes indicate an evolutionary relationship between these deep-sea sediment microbes and terrestrial, reductively dehalogenating Dehalococcoides . Copyright © 2017 Sewell et al.

30 CFR 203.49 - May I substitute the deep gas drilling provisions in § 203.0 and §§ 203.40 through 203.47 for the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false May I substitute the deep gas drilling... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.49 May I...

The effect of deep-tissue massage therapy on blood pressure and heart rate.

PubMed

Kaye, Alan David; Kaye, Aaron J; Swinford, Jan; Baluch, Amir; Bawcom, Brad A; Lambert, Thomas J; Hoover, Jason M

2008-03-01

In the present study, we describe the effects of deep tissue massage on systolic, diastolic, and mean arterial blood pressure. The study involved 263 volunteers (12% males and 88% females), with an average age of 48.5. Overall muscle spasm/muscle strain was described as either moderate or severe for each patient. Baseline blood pressure and heart rate were measured via an automatic blood pressure cuff. Twenty-one (21) different soothing CDs played in the background as the deep tissue massage was performed over the course of the study. The massages were between 45 and 60 minutes in duration. The data were analyzed using analysis of variance with post-hoc Scheffe's F-test. Results of the present study demonstrated an average systolic pressure reduction of 10.4 mm Hg (p<0.06), a diastolic pressure reduction of 5.3 mm Hg (p<0.04), a mean arterial pressure reduction of 7.0 mm Hg (p<0.47), and an average heart rate reduction of 10.8 beats per minute (p<0.0003), respectively. Additional scientific research in this area is warranted.

Aligning Seminars with Bologna Requirements: Reciprocal Peer Tutoring, the Solo Taxonomy and Deep Learning

ERIC Educational Resources Information Center

Lueg, Rainer; Lueg, Klarissa; Lauridsen, Ole

2016-01-01

Changes in public policy, such as the Bologna Process, require students to be equipped with multifunctional competencies to master relevant tasks in unfamiliar situations. Achieving this goal might imply a change in many curricula toward deeper learning. As a didactical means to achieve deep learning results, the authors suggest reciprocal peer…

Sanders II type calcaneal fractures: a retrospective trial of percutaneous versus operative treatment.

PubMed

Wang, Ye-ming; Wei, Wan-fu

2015-02-01

The purpose of this study was to compare the clinical results of percutaneous reduction and Steinman pin fixation for Sanders II calcaneal fractures with those of operative management through an extensile lateral approach. Fifty-three patients treated with standard open reduction and internal fixation (ORIF group) and 54 patients who had undergone percutaneous reduction and Steinman pin fixation (CRIF group) were retrospectively reviewed. There were no differences between the groups regarding sex, age or fracture classification. Pain and functional outcome were evaluated with a visual analogue scale (VAS) and American Orthopaedic Foot and Ankle Society (AOFAS) scores. Wound complications and radiological results were compared. At a mean follow-up of 40.4 months (24 to 56 months), there were no differences between the two groups in mean AOFAS score, VAS score or radiologically determined variables. Two cases of deep infection and six of poor wound healing occurred in the ORIF group and none in the CRIF group. Subtalar and ankle motion was found to be better in the CRIF group. Percutaneous reduction and Steinman pin fixation minimizes complications and achieves functional outcomes comparable to those of the open techniques in patients with Sanders II calcaneal fractures. © 2015 Chinese Orthopaedic Association and Wiley Publishing Asia Pty Ltd.

Exploring the effects of dimensionality reduction in deep networks for force estimation in robotic-assisted surgery

NASA Astrophysics Data System (ADS)

Aviles, Angelica I.; Alsaleh, Samar; Sobrevilla, Pilar; Casals, Alicia

2016-03-01

Robotic-Assisted Surgery approach overcomes the limitations of the traditional laparoscopic and open surgeries. However, one of its major limitations is the lack of force feedback. Since there is no direct interaction between the surgeon and the tissue, there is no way of knowing how much force the surgeon is applying which can result in irreversible injuries. The use of force sensors is not practical since they impose different constraints. Thus, we make use of a neuro-visual approach to estimate the applied forces, in which the 3D shape recovery together with the geometry of motion are used as input to a deep network based on LSTM-RNN architecture. When deep networks are used in real time, pre-processing of data is a key factor to reduce complexity and improve the network performance. A common pre-processing step is dimensionality reduction which attempts to eliminate redundant and insignificant information by selecting a subset of relevant features to use in model construction. In this work, we show the effects of dimensionality reduction in a real-time application: estimating the applied force in Robotic-Assisted Surgeries. According to the results, we demonstrated positive effects of doing dimensionality reduction on deep networks including: faster training, improved network performance, and overfitting prevention. We also show a significant accuracy improvement, ranging from about 33% to 86%, over existing approaches related to force estimation.

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

Alternative pathways to the 1.5 °C target reduce the need for negative emission technologies

NASA Astrophysics Data System (ADS)

van Vuuren, Detlef P.; Stehfest, Elke; Gernaat, David E. H. J.; van den Berg, Maarten; Bijl, David L.; de Boer, Harmen Sytze; Daioglou, Vassilis; Doelman, Jonathan C.; Edelenbosch, Oreane Y.; Harmsen, Mathijs; Hof, Andries F.; van Sluisveld, Mariësse A. E.

2018-05-01

Mitigation scenarios that achieve the ambitious targets included in the Paris Agreement typically rely on greenhouse gas emission reductions combined with net carbon dioxide removal (CDR) from the atmosphere, mostly accomplished through large-scale application of bioenergy with carbon capture and storage, and afforestation. However, CDR strategies face several difficulties such as reliance on underground CO2 storage and competition for land with food production and biodiversity protection. The question arises whether alternative deep mitigation pathways exist. Here, using an integrated assessment model, we explore the impact of alternative pathways that include lifestyle change, additional reduction of non-CO2 greenhouse gases and more rapid electrification of energy demand based on renewable energy. Although these alternatives also face specific difficulties, they are found to significantly reduce the need for CDR, but not fully eliminate it. The alternatives offer a means to diversify transition pathways to meet the Paris Agreement targets, while simultaneously benefiting other sustainability goals.

Propellantless Propulsion Technologies for In-Space Transportation

NASA Technical Reports Server (NTRS)

Johnson, Les; Cook, Stephen (Technical Monitor)

2001-01-01

In order to implement the ambitious science and exploration missions planned over the next several decades, improvements in in-space transportation and propulsion technologies must be achieved. For robotic exploration and science missions, increased efficiencies of future propulsion systems are critical to reduce overall life-cycle costs. Future missions will require 2 to 3 times more total change in velocity over their mission lives than the NASA Solar Electric Technology Application Readiness (NSTAR) demonstration on the Deep Space 1 mission. Rendezvous and return missions will require similar investments in in-space propulsion systems. New opportunities to explore beyond the outer planets and to the stars will require unparalleled technology advancement and innovation. The Advanced Space Transportation Program (ASTP) is investing in technologies to achieve a factor of 10 reduction in the cost of Earth orbital transportation and a factor of 2 or 3 reduction in propulsion system mass and travel time for planetary missions within the next 15 years. Since more than 70% of projected launches over the next 10 years will require propulsion systems capable of attaining destinations beyond Low Earth Orbit, investment in in-space technologies will benefit a large percentage of future missions. Some of the most promising technologies for achieving these goals use the environment of space itself for energy and propulsion and are generically called, "propellantless" because they do not require on-board fuel to achieve thrust. An overview of the state-of-the-art in propellantless propulsion technologies such as solar and plasma sails, electrodynamic and momentum transfer tethers, and aeroassist and aerocapture will be described. Results of recent earth-based technology demonstrations and space tests will also be discussed.

A Meta-Analysis of Single-Family Deep Energy Retrofit Performance in the U.S.

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

Less, Brennan; Walker, Iain

2014-03-01

The current state of Deep Energy Retrofit (DER) performance in the U.S. has been assessed in 116 homes in the United States (US), using actual and simulated data gathered from the available domestic literature. Substantial airtightness reductions averaging 63% (n=48) were reported (two- to three-times more than in conventional retrofits), with average post-retrofit airtightness of 4.7 Air Changes per House at 50 Pascal (ACH50) (n=94). Yet, mechanical ventilation was not installed consistently. In order to avoid indoor air quality (IAQ) issues, all future DERs should comply with ASHRAE 62.2-2013 requirements or equivalent. Projects generally achieved good energy results, with averagemore » annual net-site and net-source energy savings of 47%±20% and 45%±24% (n=57 and n=35), respectively, and carbon emission reductions of 47%±22% (n=23). Net-energy reductions did not vary reliably with house age, airtightness, or reported project costs, but pre-retrofit energy usage was correlated with total reductions (MMBtu). Annual energy costs were reduced $1,283±$804 (n=31), from a pre-retrofit average of $2,738±$1,065 to $1,588±$561 post-retrofit (n=25 and n=39). The average reported incremental project cost was $40,420±$30,358 (n=59). When financed on a 30-year term, the median change in net-homeownership cost was only $1.00 per month, ranging from $149 in savings to an increase of $212 (mean=$15.67±$87.74; n=28), and almost half of the projects resulted in reductions in net-cost. The economic value of a DER may be much greater than is suggested by these net-costs, because DERs entail substantial non-energy benefits (NEBs), and retrofit measures may add value to a home at resale similarly to general remodeling, PV panel installation, and green/energy efficient home labels. These results provide estimates of the potential of DERs to address energy use in existing homes across climate zones that can be used in future estimates of the technical potential to reduce household energy use and greenhouse gas emissions through DERs.« less

Adaptive deep brain stimulation in advanced Parkinson disease.

PubMed

Little, Simon; Pogosyan, Alex; Neal, Spencer; Zavala, Baltazar; Zrinzo, Ludvic; Hariz, Marwan; Foltynie, Thomas; Limousin, Patricia; Ashkan, Keyoumars; FitzGerald, James; Green, Alexander L; Aziz, Tipu Z; Brown, Peter

2013-09-01

Brain-computer interfaces (BCIs) could potentially be used to interact with pathological brain signals to intervene and ameliorate their effects in disease states. Here, we provide proof-of-principle of this approach by using a BCI to interpret pathological brain activity in patients with advanced Parkinson disease (PD) and to use this feedback to control when therapeutic deep brain stimulation (DBS) is delivered. Our goal was to demonstrate that by personalizing and optimizing stimulation in real time, we could improve on both the efficacy and efficiency of conventional continuous DBS. We tested BCI-controlled adaptive DBS (aDBS) of the subthalamic nucleus in 8 PD patients. Feedback was provided by processing of the local field potentials recorded directly from the stimulation electrodes. The results were compared to no stimulation, conventional continuous stimulation (cDBS), and random intermittent stimulation. Both unblinded and blinded clinical assessments of motor effect were performed using the Unified Parkinson's Disease Rating Scale. Motor scores improved by 66% (unblinded) and 50% (blinded) during aDBS, which were 29% (p = 0.03) and 27% (p = 0.005) better than cDBS, respectively. These improvements were achieved with a 56% reduction in stimulation time compared to cDBS, and a corresponding reduction in energy requirements (p < 0.001). aDBS was also more effective than no stimulation and random intermittent stimulation. BCI-controlled DBS is tractable and can be more efficient and efficacious than conventional continuous neuromodulation for PD. Copyright © 2013 American Neurological Association.

DEWS (DEep White matter hyperintensity Segmentation framework): A fully automated pipeline for detecting small deep white matter hyperintensities in migraineurs.

PubMed

Park, Bo-Yong; Lee, Mi Ji; Lee, Seung-Hak; Cha, Jihoon; Chung, Chin-Sang; Kim, Sung Tae; Park, Hyunjin

2018-01-01

Migraineurs show an increased load of white matter hyperintensities (WMHs) and more rapid deep WMH progression. Previous methods for WMH segmentation have limited efficacy to detect small deep WMHs. We developed a new fully automated detection pipeline, DEWS (DEep White matter hyperintensity Segmentation framework), for small and superficially-located deep WMHs. A total of 148 non-elderly subjects with migraine were included in this study. The pipeline consists of three components: 1) white matter (WM) extraction, 2) WMH detection, and 3) false positive reduction. In WM extraction, we adjusted the WM mask to re-assign misclassified WMHs back to WM using many sequential low-level image processing steps. In WMH detection, the potential WMH clusters were detected using an intensity based threshold and region growing approach. For false positive reduction, the detected WMH clusters were classified into final WMHs and non-WMHs using the random forest (RF) classifier. Size, texture, and multi-scale deep features were used to train the RF classifier. DEWS successfully detected small deep WMHs with a high positive predictive value (PPV) of 0.98 and true positive rate (TPR) of 0.70 in the training and test sets. Similar performance of PPV (0.96) and TPR (0.68) was attained in the validation set. DEWS showed a superior performance in comparison with other methods. Our proposed pipeline is freely available online to help the research community in quantifying deep WMHs in non-elderly adults.

Endovascular treatment of iliofemoral deep vein thrombosis in pregnancy using US-guided percutaneous aspiration thrombectomy.

PubMed

Gedikoglu, Murat; Oguzkurt, Levent

2017-01-01

We aimed to describe ultrasonography (US)-guided percutaneous aspiration thrombectomy in pregnant women with iliofemoral deep vein thrombosis. This study included nine pregnant women with acute and subacute iliofemoral deep vein thrombosis, who were severe symptomatic cases with massive swelling and pain of the leg. Patients were excluded from the study if they had only femoropopliteal deep vein thrombosis or mild symptoms of deep vein thrombosis. US-guided percutaneous aspiration thrombectomy was applied to achieve thrombus removal and uninterrupted venous flow. The treatment was considered successful if there was adequate venous patency and symptomatic relief. Complete or significant thrombus removal and uninterrupted venous flow from the puncture site up to the iliac veins were achieved in all patients at first intervention. Complete relief of leg pain was achieved immediately in seven patients (77.8%). Two patients (22.2%) had a recurrence of thrombosis in the first week postintervention. One of them underwent a second intervention, where percutaneous aspiration thrombectomy was performed again with successful removal of thrombus and establishment of in line flow. Two patients were lost to follow-up after birth. None of the remaining seven patients had rethrombosis throughout the postpartum period. Symptomatic relief was detected clinically in these patients. Endovascular treatment with US-guided percutaneous aspiration thrombectomy can be considered as a safe and effective way to remove thrombus from the deep veins in pregnant women with acute and subacute iliofemoral deep vein thrombosis.

Endovascular treatment of iliofemoral deep vein thrombosis in pregnancy using US-guided percutaneous aspiration thrombectomy

PubMed Central

Gedikoglu, Murat; Oguzkurt, Levent

2017-01-01

PURPOSE We aimed to describe ultrasonography (US)-guided percutaneous aspiration thrombectomy in pregnant women with iliofemoral deep vein thrombosis. METHODS This study included nine pregnant women with acute and subacute iliofemoral deep vein thrombosis, who were severe symptomatic cases with massive swelling and pain of the leg. Patients were excluded from the study if they had only femoropopliteal deep vein thrombosis or mild symptoms of deep vein thrombosis. US-guided percutaneous aspiration thrombectomy was applied to achieve thrombus removal and uninterrupted venous flow. The treatment was considered successful if there was adequate venous patency and symptomatic relief. RESULTS Complete or significant thrombus removal and uninterrupted venous flow from the puncture site up to the iliac veins were achieved in all patients at first intervention. Complete relief of leg pain was achieved immediately in seven patients (77.8%). Two patients (22.2%) had a recurrence of thrombosis in the first week postintervention. One of them underwent a second intervention, where percutaneous aspiration thrombectomy was performed again with successful removal of thrombus and establishment of in line flow. Two patients were lost to follow-up after birth. None of the remaining seven patients had rethrombosis throughout the postpartum period. Symptomatic relief was detected clinically in these patients. CONCLUSION Endovascular treatment with US-guided percutaneous aspiration thrombectomy can be considered as a safe and effective way to remove thrombus from the deep veins in pregnant women with acute and subacute iliofemoral deep vein thrombosis. PMID:27801353

Microbial production and oxidation of methane in deep subsurface

NASA Astrophysics Data System (ADS)

Kotelnikova, Svetlana

2002-10-01

The goal of this review is to summarize present studies on microbial production and oxidation of methane in the deep subterranean environments. Methane is a long-living gas causing the "greenhouse" effect in the planet's atmosphere. Earlier, the deep "organic carbon poor" subsurface was not considered as a source of "biogenic" methane. Evidence of active methanogenesis and presence of viable methanogens including autotrophic organisms were obtained for some subsurface environments including water-flooded oil-fields, deep sandy aquifers, deep sea hydrothermal vents, the deep sediments and granitic groundwater at depths of 10 to 2000 m below sea level. As a rule, the deep subterranean microbial populations dwell at more or less oligotrophic conditions. Molecular hydrogen has been found in a variety of subsurface environments, where its concentrations were significantly higher than in the tested surface aquatic environments. Chemolithoautotrophic microorganisms from deep aquifers that could grow on hydrogen and carbon dioxide can act as primary producers of organic carbon, initiating heterotrophic food chains in the deep subterranean environments independent of photosynthesis. "Biogenic" methane has been found all over the world. On the basis of documented occurrences, gases in reservoirs and older sediments are similar and have the isotopic character of methane derived from CO 2 reduction. Groundwater representing the methanogenic end member are characterized by a relative depletion of dissolved organic carbon (DOC) in combination with an enrichment in 13C in inorganic carbon, which is consistent with the preferential reduction of 12CO 2 by autotrophic methanogens or acetogens. The isotopic composition of methane formed via CO 2 reduction is controlled by the δ13C of the original CO 2 substrate. Literature data shows that CH 4 as heavy as -40‰ or -50‰ can be produced by the microbial reduction of isotopically heavy CO 2. Produced methane may be oxidized microbially to carbon dioxide. Microbial methane oxidation is a biogeochemical process that limits the release of methane, a greenhouse gas from anaerobic environments. Anaerobic methane oxidation plays an important role in marine sediments. Similar processes may take place in deep subsurface and thus fuel the deep microbial community. Organisms or consortia responsible for anaerobic methane oxidation have not yet been cultured, although diverse aerobic methanotrophs have been isolated from a variety of underground niches. The presence of aerobic methanotrophs in the anoxic subsurface remains to be explained. The presence of methane in the deep subsurface have been shown all over the world. The flux of gases between the deep subsurface and the atmosphere is driven by the concentration gradient from depth to the atmosphere. However, methane is consumed by methanotrophs on the way of its evolution in oxidized environments and is transformed to organic form, available for further microbial processing. When the impact of subsurface environments to global warming is estimated, it is necessary to take into account the activity of methane-producing Archaea and methane-oxidizing biofilters in groundwater. Microbial production and oxidation of methane is involved in the carbon cycle in the deep subsurface environments.

Mirror coatings for large aperture UV optical infrared telescope optics

NASA Astrophysics Data System (ADS)

Balasubramanian, Kunjithapatham; Hennessy, John; Raouf, Nasrat; Nikzad, Shouleh; Del Hoyo, Javier; Quijada, Manuel

2017-09-01

Large space telescope concepts such as LUVOIR and HabEx aiming for observations from far UV to near IR require advanced coating technologies to enable efficient gathering of light with important spectral signatures including those in far UV region down to 90nm. Typical Aluminum mirrors protected with MgF2 fall short of the requirements below 120nm. New and improved coatings are sought to protect aluminum from oxidizing readily in normal environment causing severe absorption and reduction of reflectance in the deep UV. Choice of materials and the process of applying coatings present challenges. Here we present the progress achieved to date with experimental investigations of coatings at JPL and at GSFC and discuss the path forward to achieve high reflectance in the spectral region from 90 to 300nm without degrading performance in the visible and NIR regions taking into account durability concerns when the mirrors are exposed to normal laboratory environment as well as high humidity conditions. Reflectivity uniformity required on these mirrors is also discussed.

Learning Deep Representations for Ground to Aerial Geolocalization (Open Access)

DTIC Science & Technology

2015-10-15

proposed approach, Where-CNN, is inspired by deep learning success in face verification and achieves significant improvements over tra- ditional hand...crafted features and existing deep features learned from other large-scale databases. We show the ef- fectiveness of Where-CNN in finding matches

Role of Southern Ocean stratification in glacial atmospheric CO2 reduction

NASA Astrophysics Data System (ADS)

Kobayashi, H.; Oka, A.

2014-12-01

Paleoclimate proxy data at the glacial period shows high salinity of more than 37.0 psu in the deep South Atlantic. At the same time, data also indicate that the residence time of the water mass was more than 3000 years. These data implies that the stratification by salinity was stronger in the deep Southern Ocean (SO) in the Last Glacial Maximum (LGM). Previous studies using Ocean General Circulation Model (OGCM) fail to explain the low glacial atmospheric carbon dioxide (CO2) concentration at LGM. The reproducibility of salinity and water mass age is considered insufficient in these OGCMs, which may in turn affect the reproducibility of the atmospheric CO2concentration. In coarse-resolution OGCMs, The deep water is formed by unrealistic open-ocean deep convection in the SO. Considering these facts, we guessed previous studies using OGCM underestimated the salinity and water mass age at LGM. This study investigate the role of the enhanced stratification in the glacial SO on the variation of atmospheric CO2 concentration by using OGCM. In order to reproduce the recorded salinity of the deep water, relaxation of salinity toward value of recorded data is introduced in our OGCM simulations. It was found that deep water formation in East Antarctica is required for explaining the high salinity in the South Atlantic. In contrast, it is difficult to explain the glacial water mass age, even if we assume the situation vertical mixing is very weak in the SO. Contrary to previous estimate, the high salinity of the deep SO resulted in increase of Antarctic Bottom water (AABW) flow and decrease the residence time of carbon in the deep ocean, which increased atmospheric CO2 concentration. On the other hand, the weakening of the vertical mixing in the SO contributed to increase the vertical gradient of dissolved inorganic carbon (DIC), which decreased atmospheric CO2 concentration. Adding the contribution of the enhanced stratification in the glacial SO, we obtained larger reduction in atmospheric CO2 concentration than previous studies. However, we still fail to explain the full amplitude of recorded glacial reduction of atmospheric CO2 concentration. The carbonate compensation process, which is not incorporated in our simulations, might be required for further reduction in atmospheric CO2 concentration.

Extreme Environment Capable, Modular and Scalable Power Processing Unit for Solar Electric Propulsion

NASA Technical Reports Server (NTRS)

Carr, Gregory A.; Iannello, Christopher J.; Chen, Yuan; Hunter, Don J.; DelCastillo, Linda; Bradley, Arthur T.; Stell, Christopher; Mojarradi, Mohammad M.

2013-01-01

This paper is to present a concept of a modular and scalable High Temperature Boost (HTB) Power Processing Unit (PPU) capable of operating at temperatures beyond the standard military temperature range. The various extreme environments technologies are also described as the fundamental technology path to this concept. The proposed HTB PPU is intended for power processing in the area of space solar electric propulsion, where reduction of in-space mass and volume are desired, and sometimes even critical, to achieve the goals of future space flight missions. The concept of the HTB PPU can also be applied to other extreme environment applications, such as geothermal and petroleum deep-well drilling, where higher temperature operation is required.

Extreme Environment Capable, Modular and Scalable Power Processing Unit for Solar Electric Propulsion

NASA Technical Reports Server (NTRS)

Carr, Gregory A.; Iannello, Christopher J.; Chen, Yuan; Hunter, Don J.; Del Castillo, Linda; Bradley, Arthur T.; Stell, Christopher; Mojarradi, Mohammad M.

2013-01-01

This paper is to present a concept of a modular and scalable High Temperature Boost (HTB) Power Processing Unit (PPU) capable of operating at temperatures beyond the standard military temperature range. The various extreme environments technologies are also described as the fundamental technology path to this concept. The proposed HTB PPU is intended for power processing in the area of space solar electric propulsion, where the reduction of in-space mass and volume are desired, and sometimes even critical, to achieve the goals of future space flight missions. The concept of the HTB PPU can also be applied to other extreme environment applications, such as geothermal and petroleum deep-well drilling, where higher temperature operation is required.

Wavelength-modulated photocapacitance spectroscopy

NASA Technical Reports Server (NTRS)

Kamieniecki, E.; Lagowski, J.; Gatos, H. C.

1980-01-01

Derivative deep-level spectroscopy was achieved with wavelength-modulated photocapacitance employing MOS structures and Schottky barriers. The energy position and photoionization characteristics of deep levels of melt-grown GaAs and the Cr level in high-resistivity GaAs were determined. The advantages of this method over existing methods for deep-level spectroscopy are discussed.

Throughfall Reduction x Fertilization: Monitoring and Modeling the Effect on Deep Soil Water Usage in a Loblolly Pine Plantations of the Southeast US

NASA Astrophysics Data System (ADS)

Qi, J.; Markewitz, D.; Radcliffe, D. E.

2016-12-01

Forests in the southeastern U.S. are predicted to experience a moderate decrease in water availability that will result in soil water deficiency during the growing season. The potential impact of drier climate on the productivity of managed loblolly pine plantations in the Southeast US is uncertain. Access to water reserves in deep soil during drought periods helps the forest buffer the effects of water deficits. To better understand the potential impact of drought on deep soil hydrology, we studied the combined effects of throughfall reduction and soil fertility on soil hydrology to the depth of 3 m in a 10-year-old loblolly pine plantation by applying a throughfall reduction treatment (ambient versus 30% throughfall reduction) and a fertilization treatment (no fertilization versus fertilization). Fertilization lowered soil moisture for all depths and differences were significant at 30-60 cm and 300 cm. Throughfall reduction also lowered soil moisture for all depths and differences were significant in the surface soils (0-30 cm) and deep soils (below 2m). Fertilization significantly decreased 10-90 cm soil water when combined with throughfall reduction treatment. HYDRUS 1-D model was used to simulate changes in the vertical distribution of soil water and to enhance our understanding of hydrologic processes. The model was accurately calibrated using 914 days of data under ambient rainfall (R2=0.84 and RMSE = 0.04). Using data under throughfall reduction treatment, the model validation showed R2=0.67 and RMSE = 0.04, suggesting that this model captures the hydrological processes of this study site. The difference in the rates of simulated cumulative actual evapotranspiration between ambient and throughfall reduction were only 10%; however, water yield as lower boundary flux decreased 64%. These empirical and simulated results suggested that when evapotranspiration exceeded precipitation, the soil water in the upper 90 cm did not satisfy the demand for AET, soil below 90 cm constantly contribute to plant water uptake. With 30% less throughfall, the water in the 3 meter soil profile can satisfy the demand of evapotranspiration before water yield.

Active appearance model and deep learning for more accurate prostate segmentation on MRI

NASA Astrophysics Data System (ADS)

Cheng, Ruida; Roth, Holger R.; Lu, Le; Wang, Shijun; Turkbey, Baris; Gandler, William; McCreedy, Evan S.; Agarwal, Harsh K.; Choyke, Peter; Summers, Ronald M.; McAuliffe, Matthew J.

2016-03-01

Prostate segmentation on 3D MR images is a challenging task due to image artifacts, large inter-patient prostate shape and texture variability, and lack of a clear prostate boundary specifically at apex and base levels. We propose a supervised machine learning model that combines atlas based Active Appearance Model (AAM) with a Deep Learning model to segment the prostate on MR images. The performance of the segmentation method is evaluated on 20 unseen MR image datasets. The proposed method combining AAM and Deep Learning achieves a mean Dice Similarity Coefficient (DSC) of 0.925 for whole 3D MR images of the prostate using axial cross-sections. The proposed model utilizes the adaptive atlas-based AAM model and Deep Learning to achieve significant segmentation accuracy.

Imatinib dose reduction in patients with chronic myeloid leukemia in sustained deep molecular response.

PubMed

Cervantes, Francisco; Correa, Juan-Gonzalo; Pérez, Isabel; García-Gutiérrez, Valentín; Redondo, Sara; Colomer, Dolors; Jiménez-Velasco, Antonio; Steegmann, Juan-Luis; Sánchez-Guijo, Fermín; Ferrer-Marín, Francisca; Pereira, Arturo; Osorio, Santiago

2017-01-01

To determine whether a lower imatinib dose could minimize toxicity while maintaining the molecular response (MR), imatinib dose was reduced to 300 mg daily in 43 patients with chronic myeloid leukemia (CML) in sustained deep molecular response to first-line imatinib 400 mg daily. At the time of dose reduction, median duration of the deep response was 4.1 (interquartile range (IQR) 2.2-5.9) years; molecular response was MR 4 , MR 4.5 , and MR 5 of the international scale in 6, 28, and 9 patients, respectively. Toxicity grade was 1, 2, and 3 in 28, 8, and 1 patients, respectively; 6 patients underwent dose reduction without having side effects. With a median of 1.6 (IQR 0.7-3.2) years on imatinib 300 mg daily, only one patient lost the deep molecular response to MR 3 . At the last follow-up, response was MR 3 , MR 4 , MR 4.5 , and MR 5 in 1, 3, 9, and 30 patients, respectively. Toxicity improvement was observed in 23 (62.2 %) of the 37 patients with side effects, decreasing to grade 0 in 20 of them. All but one anemic patients improved (p = 0.01), the median Hb increase in this subgroup of patients being 1 g/dL. In CML patients with sustained deep response to the standard imatinib dose, reducing to 300 mg daily significantly improves tolerability and preserves efficacy.

Comparative analysis of hospital energy use: pacific northwest and scandinavia.

PubMed

Burpee, Heather; McDade, Erin

2014-01-01

This study aimed to establish the potential for significant energy reduction in hospitals in the United States by providing evidence of Scandinavian operational precedents with high Interior Environmental Quality (IEQ) and substantially lower energy profiles than comparable U.S. facilities. These facilities set important precedents for design teams seeking operational examples for achieving aggressive energy and interior environmental quality goals. This examination of operational hospitals is intended to offer hospital owners, designers, and building managers a strong case and concrete framework for strategies to achieve exceptionally high performing buildings. Energy efficient hospitals have the potential to significantly impact the U.S.'s overall energy profile, and key stakeholders in the hospital industry need specific, operationally grounded precedents in order to successfully implement informed energy reduction strategies. This study is an outgrowth of previous research evaluating high quality, low energy hospitals that serve as examples for new high performance hospital design, construction, and operation. Through extensive interviews, numerous site visits, the development of case studies, and data collection, this team has established thorough qualitative and quantitative analyses of several contemporary hospitals in Scandinavia and the Pacific Northwest. Many Scandinavian hospitals demonstrate a low energy profile, and when analyzed in comparison with U.S. hospitals, such Scandinavian precedents help define the framework required to make significant changes in the U.S. hospital building industry. Eight hospitals, four Scandinavian and four Pacific Northwest, were quantitatively compared using the Environmental Protection Agency's Portfolio Manager, allowing researchers to answer specific questions about the impact of energy source and architectural and mechanical strategies on energy efficiency in operational hospitals. Specific architectural, mechanical, and plant systems make these Scandinavian hospitals more energy efficient than their Pacific Northwest counterparts. More importantly, synergistic systems integration allows for their significant reductions in energy consumption. This quantitative comparison of operational Scandinavian and Pacific Northwest hospitals resulted in compelling evidence of the potential for deep energy savings in the U.S., and allowed researchers to outline specific strategies for achieving such reductions. © 2014 Vendome Group, LLC.

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

PubMed

Ouyang, Zhangyi; Liu, Feng; Zhao, Chenghui; Ren, Chao; An, Gaole; Mei, Chuan; Bo, Xiaochen; Shu, Wenjie

2018-04-16

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

De novo peptide sequencing by deep learning

PubMed Central

Tran, Ngoc Hieu; Zhang, Xianglilan; Xin, Lei; Shan, Baozhen; Li, Ming

2017-01-01

De novo peptide sequencing from tandem MS data is the key technology in proteomics for the characterization of proteins, especially for new sequences, such as mAbs. In this study, we propose a deep neural network model, DeepNovo, for de novo peptide sequencing. DeepNovo architecture combines recent advances in convolutional neural networks and recurrent neural networks to learn features of tandem mass spectra, fragment ions, and sequence patterns of peptides. The networks are further integrated with local dynamic programming to solve the complex optimization task of de novo sequencing. We evaluated the method on a wide variety of species and found that DeepNovo considerably outperformed state of the art methods, achieving 7.7–22.9% higher accuracy at the amino acid level and 38.1–64.0% higher accuracy at the peptide level. We further used DeepNovo to automatically reconstruct the complete sequences of antibody light and heavy chains of mouse, achieving 97.5–100% coverage and 97.2–99.5% accuracy, without assisting databases. Moreover, DeepNovo is retrainable to adapt to any sources of data and provides a complete end-to-end training and prediction solution to the de novo sequencing problem. Not only does our study extend the deep learning revolution to a new field, but it also shows an innovative approach in solving optimization problems by using deep learning and dynamic programming. PMID:28720701

Transportation Energy Futures Series: Alternative Fuel Infrastructure Expansion: Costs, Resources, Production Capacity, and Retail Availability for Low-Carbon Scenarios

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

Melaina, M. W.; Heath, G.; Sandor, D.

2013-04-01

Achieving the Department of Energy target of an 80% reduction in greenhouse gas emissions by 2050 depends on transportation-related strategies combining technology innovation, market adoption, and changes in consumer behavior. This study examines expanding low-carbon transportation fuel infrastructure to achieve deep GHG emissions reductions, with an emphasis on fuel production facilities and retail components serving light-duty vehicles. Three distinct low-carbon fuel supply scenarios are examined: Portfolio: Successful deployment of a range of advanced vehicle and fuel technologies; Combustion: Market dominance by hybridized internal combustion engine vehicles fueled by advanced biofuels and natural gas; Electrification: Market dominance by electric drive vehiclesmore » in the LDV sector, including battery electric, plug-in hybrid, and fuel cell vehicles, that are fueled by low-carbon electricity and hydrogen. A range of possible low-carbon fuel demand outcomes are explored in terms of the scale and scope of infrastructure expansion requirements and evaluated based on fuel costs, energy resource utilization, fuel production infrastructure expansion, and retail infrastructure expansion for LDVs. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored transportation-related strategies for abating GHGs and reducing petroleum dependence.« less

Achieving deep cuts in the carbon intensity of U.S. automobile transportation by 2050: complementary roles for electricity and biofuels.

PubMed

Scown, Corinne D; Taptich, Michael; Horvath, Arpad; McKone, Thomas E; Nazaroff, William W

2013-08-20

Passenger cars in the United States (U.S.) rely primarily on petroleum-derived fuels and contribute the majority of U.S. transportation-related greenhouse gas (GHG) emissions. Electricity and biofuels are two promising alternatives for reducing both the carbon intensity of automotive transportation and U.S. reliance on imported oil. However, as standalone solutions, the biofuels option is limited by land availability and the electricity option is limited by market adoption rates and technical challenges. This paper explores potential GHG emissions reductions attainable in the United States through 2050 with a county-level scenario analysis that combines ambitious plug-in hybrid electric vehicle (PHEV) adoption rates with scale-up of cellulosic ethanol production. With PHEVs achieving a 58% share of the passenger car fleet by 2050, phasing out most corn ethanol and limiting cellulosic ethanol feedstocks to sustainably produced crop residues and dedicated crops, we project that the United States could supply the liquid fuels needed for the automobile fleet with an average blend of 80% ethanol (by volume) and 20% gasoline. If electricity for PHEV charging could be supplied by a combination of renewables and natural-gas combined-cycle power plants, the carbon intensity of automotive transport would be 79 g CO2e per vehicle-kilometer traveled, a 71% reduction relative to 2013.

Comparing deep neural network and other machine learning algorithms for stroke prediction in a large-scale population-based electronic medical claims database.

PubMed

Chen-Ying Hung; Wei-Chen Chen; Po-Tsun Lai; Ching-Heng Lin; Chi-Chun Lee

2017-07-01

Electronic medical claims (EMCs) can be used to accurately predict the occurrence of a variety of diseases, which can contribute to precise medical interventions. While there is a growing interest in the application of machine learning (ML) techniques to address clinical problems, the use of deep-learning in healthcare have just gained attention recently. Deep learning, such as deep neural network (DNN), has achieved impressive results in the areas of speech recognition, computer vision, and natural language processing in recent years. However, deep learning is often difficult to comprehend due to the complexities in its framework. Furthermore, this method has not yet been demonstrated to achieve a better performance comparing to other conventional ML algorithms in disease prediction tasks using EMCs. In this study, we utilize a large population-based EMC database of around 800,000 patients to compare DNN with three other ML approaches for predicting 5-year stroke occurrence. The result shows that DNN and gradient boosting decision tree (GBDT) can result in similarly high prediction accuracies that are better compared to logistic regression (LR) and support vector machine (SVM) approaches. Meanwhile, DNN achieves optimal results by using lesser amounts of patient data when comparing to GBDT method.

30 CFR 203.30 - Which leases are eligible for royalty relief as a result of drilling a phase 2 or phase 3 ultra...

Code of Federal Regulations, 2011 CFR

2011-07-01

... a result of drilling a phase 2 or phase 3 ultra-deep well? 203.30 Section 203.30 Mineral Resources... REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra-Deep Wells on Leases Not Subject to Deep Water Royalty Relief § 203.30 Which leases...

30 CFR 203.34 - To which production may an RSV earned by qualified phase 2 and phase 3 ultra-deep wells on my...

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra-Deep Wells on Leases Not Subject to Deep Water Royalty Relief § 203.34 To which... lease, except as provided in paragraph (c) of § 203.33; (c) To any liquid hydrocarbon (oil and...

30 CFR 203.35 - What administrative steps must I take to use the RSV earned by a qualified phase 2 or phase 3...

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra-Deep Wells on Leases Not Subject to Deep Water Royalty Relief § 203.35 What... Development in writing of your intent to begin drilling operations on all your ultra-deep wells. (b) Before...

30 CFR 203.33 - To which production do I apply the RSV earned by qualified phase 2 and phase 3 ultra-deep wells...

Code of Federal Regulations, 2011 CFR

2011-07-01

... INTERIOR MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra-Deep Wells on Leases Not Subject to Deep Water Royalty Relief § 203.33... from qualified wells on or after May 18, 2007, reported on the Oil and Gas Operations Report, Part A...

Boosting compound-protein interaction prediction by deep learning.

PubMed

Tian, Kai; Shao, Mingyu; Wang, Yang; Guan, Jihong; Zhou, Shuigeng

2016-11-01

The identification of interactions between compounds and proteins plays an important role in network pharmacology and drug discovery. However, experimentally identifying compound-protein interactions (CPIs) is generally expensive and time-consuming, computational approaches are thus introduced. Among these, machine-learning based methods have achieved a considerable success. However, due to the nonlinear and imbalanced nature of biological data, many machine learning approaches have their own limitations. Recently, deep learning techniques show advantages over many state-of-the-art machine learning methods in some applications. In this study, we aim at improving the performance of CPI prediction based on deep learning, and propose a method called DL-CPI (the abbreviation of Deep Learning for Compound-Protein Interactions prediction), which employs deep neural network (DNN) to effectively learn the representations of compound-protein pairs. Extensive experiments show that DL-CPI can learn useful features of compound-protein pairs by a layerwise abstraction, and thus achieves better prediction performance than existing methods on both balanced and imbalanced datasets. Copyright © 2016 Elsevier Inc. All rights reserved.

Deep convolutional neural network based antenna selection in multiple-input multiple-output system

NASA Astrophysics Data System (ADS)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

Deep cooling of optically trapped atoms implemented by magnetic levitation without transverse confinement.

PubMed

Li, Chen; Zhou, Tianwei; Zhai, Yueyang; Xiang, Jinggang; Luan, Tian; Huang, Qi; Yang, Shifeng; Xiong, Wei; Chen, Xuzong

2017-05-01

We report a setup for the deep cooling of atoms in an optical trap. The deep cooling is implemented by eliminating the influence of gravity using specially constructed magnetic coils. Compared to the conventional method of generating a magnetic levitating force, the lower trap frequency achieved in our setup provides a lower limit of temperature and more freedoms to Bose gases with a simpler solution. A final temperature as low as ∼6nK is achieved in the optical trap, and the atomic density is decreased by nearly two orders of magnitude during the second stage of evaporative cooling. This deep cooling of optically trapped atoms holds promise for many applications, such as atomic interferometers, atomic gyroscopes, and magnetometers, as well as many basic scientific research directions, such as quantum simulations and atom optics.

Deep cooling of optically trapped atoms implemented by magnetic levitation without transverse confinement

NASA Astrophysics Data System (ADS)

Li, Chen; Zhou, Tianwei; Zhai, Yueyang; Xiang, Jinggang; Luan, Tian; Huang, Qi; Yang, Shifeng; Xiong, Wei; Chen, Xuzong

2017-05-01

We report a setup for the deep cooling of atoms in an optical trap. The deep cooling is implemented by eliminating the influence of gravity using specially constructed magnetic coils. Compared to the conventional method of generating a magnetic levitating force, the lower trap frequency achieved in our setup provides a lower limit of temperature and more freedoms to Bose gases with a simpler solution. A final temperature as low as ˜ 6 nK is achieved in the optical trap, and the atomic density is decreased by nearly two orders of magnitude during the second stage of evaporative cooling. This deep cooling of optically trapped atoms holds promise for many applications, such as atomic interferometers, atomic gyroscopes, and magnetometers, as well as many basic scientific research directions, such as quantum simulations and atom optics.

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

PubMed Central

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

2016-01-01

For many years, investigators have sought after high-resolution fluorescence imaging in centimeter-deep tissue because many interesting in vivo phenomena—such as the presence of immune system cells, tumor angiogenesis, and metastasis—may be located deep in tissue. Previously, we developed a new imaging technique to achieve high spatial resolution in sub-centimeter deep tissue phantoms named continuous-wave ultrasound-switchable fluorescence (CW-USF). The principle is to use a focused ultrasound wave to externally and locally switch on and off the fluorophore emission from a small volume (close to ultrasound focal volume). By making improvements in three aspects of this technique: excellent near-infrared USF contrast agents, a sensitive frequency-domain USF imaging system, and an effective signal processing algorithm, for the first time this study has achieved high spatial resolution (~ 900 μm) in 3-centimeter-deep tissue phantoms with high signal-to-noise ratio (SNR) and high sensitivity (3.4 picomoles of fluorophore in a volume of 68 nanoliters can be detected). We have achieved these results in both tissue-mimic phantoms and porcine muscle tissues. We have also demonstrated multi-color USF to image and distinguish two fluorophores with different wavelengths, which might be very useful for simultaneously imaging of multiple targets and observing their interactions in the future. This work has opened the door for future studies of high-resolution centimeter-deep tissue fluorescence imaging. PMID:27829050

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

PubMed

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

2016-01-01

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

Training Deep Spiking Neural Networks Using Backpropagation.

PubMed

Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

2016-01-01

Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

PubMed

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Structural damage detection using deep learning of ultrasonic guided waves

NASA Astrophysics Data System (ADS)

Melville, Joseph; Alguri, K. Supreet; Deemer, Chris; Harley, Joel B.

2018-04-01

Structural health monitoring using ultrasonic guided waves relies on accurate interpretation of guided wave propagation to distinguish damage state indicators. However, traditional physics based models do not provide an accurate representation, and classic data driven techniques, such as a support vector machine, are too simplistic to capture the complex nature of ultrasonic guide waves. To address this challenge, this paper uses a deep learning interpretation of ultrasonic guided waves to achieve fast, accurate, and automated structural damaged detection. To achieve this, full wavefield scans of thin metal plates are used, half from the undamaged state and half from the damaged state. This data is used to train our deep network to predict the damage state of a plate with 99.98% accuracy given signals from just 10 spatial locations on the plate, as compared to that of a support vector machine (SVM), which achieved a 62% accuracy.

Southern Ocean biogeochemical control of glacial/interglacial carbon dioxide change

NASA Astrophysics Data System (ADS)

Sigman, D. M.

2014-12-01

In the effort to explain the lower atmospheric CO2 concentrations observed during ice ages, two of the first hypotheses involved redistributing dissolved inorganic carbon (DIC) within the ocean. Broecker (1982) proposed a strengthening of the ocean's biological pump during ice ages, which increased the dissolved inorganic carbon gradient between the dark, voluminous ocean interior and the surface ocean's sun-lit, wind-mixed layer. Boyle (1988) proposed a deepening in the ocean interior's pool of DIC associated with organic carbon regeneration, with its concentration maximum shifting from intermediate to abyssal depths. While not irrefutable, evidence has arisen that these mechanisms can explain much of the ice age CO2 reduction and that both were activated by changes in the Southern Ocean. In the Antarctic Zone, reduced exchange of water between the surface and the underlying ocean sequestered more DIC in the ocean interior (the biological pump mechanism). Dust-borne iron fertilization of the Subantarctic surface lowered CO2 partly by the biological pump mechanism and partly by Boyle's carbon deepening. Each mechanism owes a part of its CO2 effect to a transient increase in seafloor calcium carbonate dissolution, which raised the ice age ocean's alkalinity, causing it to absorb more CO2. However, calcium carbonate cycling also sets limits on these mechanisms and their CO2 effects, such that the combination of Antarctic and Subantarctic changes is needed to achieve the full (80-100 ppm) ice age CO2 decline. Data suggest that these changes began at different phases in the development of the last ice age, 110 and 70 ka, respectively, explaining a 40 ppm CO2 drop at each time. We lack a robust understanding of the potential causes for both the implied reduction in Antarctic surface/deep exchange and the increase in Subantarctic dust supply during ice ages. Thus, even if the evidence for these Southern Ocean changes were to become incontrovertible, conceptual gaps stand in the way of a theory of glacial cycles that includes Southern Ocean-driven CO2 change. There are more compelling proposals for the causes of deglacial change, with a sharp reduction in North Atlantic deep water formation implicated as a trigger of increased surface/deep exchange in the Antarctic and the resulting release of CO2 to the atmosphere.

Fundamental Characteristics of Deep-UV Light-Emitting Diodes and Their Application To Control Foodborne Pathogens

PubMed Central

Shin, Joo-Yeon; Kim, Soo-Ji; Kim, Do-Kyun

2015-01-01

Low-pressure mercury UV (LP-UV) lamps have long been used for bacterial inactivation, but due to certain disadvantages, such as the possibility of mercury leakage, deep-UV-C light-emitting diodes (DUV-LEDs) for disinfection have recently been of great interest as an alternative. Therefore, in this study, we examined the basic spectral properties of DUV-LEDs and the effects of UV-C irradiation for inactivating foodborne pathogens, including Escherichia coli O157:H7, Salmonella enterica serovar Typhimurium, and Listeria monocytogenes, on solid media, as well as in water. As the temperature increased, DUV-LED light intensity decreased slightly, whereas LP-UV lamps showed increasing intensity until they reached a peak at around 30°C. As the irradiation dosage and temperature increased, E. coli O157:H7 and S. Typhimurium experienced 5- to 6-log-unit reductions. L. monocytogenes was reduced by over 5 log units at a dose of 1.67 mJ/cm2. At 90% relative humidity (RH), only E. coli O157:H7 experienced inactivation significantly greater than at 30 and 60% RH. In a water treatment study involving a continuous system, 6.38-, 5.81-, and 3.47-log-unit reductions were achieved in E. coli O157:H7, S. Typhimurium, and L. monocytogenes, respectively, at 0.5 liter per minute (LPM) and 200 mW output power. The results of this study suggest that the use of DUV-LEDs may compensate for the drawbacks of using LP-UV lamps to inactivate foodborne pathogens. PMID:26162872

30 CFR 203.42 - What conditions and limitations apply to royalty relief for deep wells and phase 1 ultra-deep wells?

Code of Federal Regulations, 2011 CFR

2011-07-01

... MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling... has produced gas or oil from a well with a perforated interval the top of which is 18,000 feet TVD SS or deeper, your lease cannot earn an RSV under § 203.41 as a result of drilling any subsequent deep...

Rationale and motivating factors for treatment-free remission in chronic myeloid leukemia.

PubMed

Caldemeyer, Lauren; Akard, Luke P

2016-12-01

With BCR-ABL1 tyrosine kinase inhibitors (TKIs), such as imatinib, nilotinib, dasatinib, bosutinib, and ponatinib, many patients with chronic myeloid leukemia in chronic phase (CML-CP) can expect to live near-normal life spans. Current treatment recommendations of the National Comprehensive Cancer Network and the European LeukemiaNet state that patients with CML-CP should remain on TKI therapy indefinitely. However, there is increasing evidence from clinical trials that some patients with sustained deep molecular responses may be able to achieve treatment-free remission (TFR), whereby they can suspend TKI therapy without losing previously achieved responses. With many patients achieving deep molecular responses to TKI therapy, there is growing interest in whether such patients can achieve TFR. In addition, adverse events (AEs) with long-term TKI therapy, including both the potential for later-emerging AEs and chronic, low-grade AEs, represent a major motivator for oncologists and their patients to investigate the feasibility of TFR. In this review, we provide an overview of data from TFR clinical trials, discuss the importance of achieving a deep molecular response to TKI treatment, and consider potential reasons for investigating TFR following TKI therapy.

COTS-Based Fault Tolerance in Deep Space: Qualitative and Quantitative Analyses of a Bus Network Architecture

NASA Technical Reports Server (NTRS)

Tai, Ann T.; Chau, Savio N.; Alkalai, Leon

2000-01-01

Using COTS products, standards and intellectual properties (IPs) for all the system and component interfaces is a crucial step toward significant reduction of both system cost and development cost as the COTS interfaces enable other COTS products and IPs to be readily accommodated by the target system architecture. With respect to the long-term survivable systems for deep-space missions, the major challenge for us is, under stringent power and mass constraints, to achieve ultra-high reliability of the system comprising COTS products and standards that are not developed for mission-critical applications. The spirit of our solution is to exploit the pertinent standard features of a COTS product to circumvent its shortcomings, though these standard features may not be originally designed for highly reliable systems. In this paper, we discuss our experiences and findings on the design of an IEEE 1394 compliant fault-tolerant COTS-based bus architecture. We first derive and qualitatively analyze a -'stacktree topology" that not only complies with IEEE 1394 but also enables the implementation of a fault-tolerant bus architecture without node redundancy. We then present a quantitative evaluation that demonstrates significant reliability improvement from the COTS-based fault tolerance.

Precision pointing compensation for DSN antennas with optical distance measuring sensors

NASA Technical Reports Server (NTRS)

Scheid, R. E.

1989-01-01

The pointing control loops of Deep Space Network (DSN) antennas do not account for unmodeled deflections of the primary and secondary reflectors. As a result, structural distortions due to unpredictable environmental loads can result in uncompensated boresight shifts which degrade pointing accuracy. The design proposed here can provide real-time bias commands to the pointing control system to compensate for environmental effects on pointing performance. The bias commands can be computed in real time from optically measured deflections at a number of points on the primary and secondary reflectors. Computer simulations with a reduced-order finite-element model of a DSN antenna validate the concept and lead to a proposed design by which a ten-to-one reduction in pointing uncertainty can be achieved under nominal uncertainty conditions.

Improved memory characteristics by NH3-nitrided GdO as charge storage layer for nonvolatile memory applications

NASA Astrophysics Data System (ADS)

Liu, L.; Xu, J. P.; Ji, F.; Chen, J. X.; Lai, P. T.

2012-07-01

Charge-trapping memory capacitor with nitrided gadolinium oxide (GdO) as charge storage layer (CSL) is fabricated, and the influence of post-deposition annealing in NH3 on its memory characteristics is investigated. Transmission electron microscopy, x-ray photoelectron spectroscopy, and x-ray diffraction are used to analyze the cross-section and interface quality, composition, and crystallinity of the stack gate dielectric, respectively. It is found that nitrogen incorporation can improve the memory window and achieve a good trade-off among the memory properties due to NH3-annealing-induced reasonable distribution profile of a large quantity of deep-level bulk traps created in the nitrided GdO film and reduction of shallow traps near the CSL/SiO2 interface.

30 CFR 203.32 - What other requirements or restrictions apply to royalty relief for a qualified phase 2 or phase...

Code of Federal Regulations, 2010 CFR

2010-07-01

... REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra-Deep Wells on... qualified ultra-deep well is a directional well (either an original well or a sidetrack) drilled across a...

A double-blind, randomized trial of deep repetitive transcranial magnetic stimulation (rTMS) for autism spectrum disorder.

PubMed

Enticott, Peter G; Fitzgibbon, Bernadette M; Kennedy, Hayley A; Arnold, Sara L; Elliot, David; Peachey, Amy; Zangen, Abraham; Fitzgerald, Paul B

2014-01-01

Biomedical treatment options for autism spectrum disorder (ASD) are extremely limited. Repetitive transcranial magnetic stimulation (rTMS) is a safe and efficacious technique when targeting specific areas of cortical dysfunction in major depressive disorder, and a similar approach could yield therapeutic benefits in ASD, if applied to relevant cortical regions. The aim of this study was to examine whether deep rTMS to bilateral dorsomedial prefrontal cortex improves social relating in ASD. 28 adults diagnosed with either autistic disorder (high-functioning) or Asperger's disorder completed a prospective, double-blind, randomized, placebo-controlled design with 2 weeks of daily weekday treatment. This involved deep rTMS to bilateral dorsomedial prefrontal cortex (5 Hz, 10-s train duration, 20-s inter-train interval) for 15 min (1500 pulses per session) using a HAUT-Coil. The sham rTMS coil was encased in the same helmet of the active deep rTMS coil, but no effective field was delivered into the brain. Assessments were conducted before, after, and one month following treatment. Participants in the active condition showed a near significant reduction in self-reported social relating symptoms from pre-treatment to one month follow-up, and a significant reduction in social relating symptoms (relative to sham participants) for both post-treatment assessments. Those in the active condition also showed a reduction in self-oriented anxiety during difficult and emotional social situations from pre-treatment to one month follow-up. There were no changes for those in the sham condition. Deep rTMS to bilateral dorsomedial prefrontal cortex yielded a reduction in social relating impairment and socially-related anxiety. Further research in this area should employ extended rTMS protocols that approximate those used in depression in an attempt to replicate and amplify the clinical response. Copyright © 2014 Elsevier Inc. All rights reserved.

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.;

DEEP: a general computational framework for predicting enhancers

PubMed Central

Kleftogiannis, Dimitrios; Kalnis, Panos; Bajic, Vladimir B.

2015-01-01

Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/. PMID:25378307

DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks.

PubMed

Li, Chao; Wang, Xinggang; Liu, Wenyu; Latecki, Longin Jan

2018-04-01

Mitotic count is a critical predictor of tumor aggressiveness in the breast cancer diagnosis. Nowadays mitosis counting is mainly performed by pathologists manually, which is extremely arduous and time-consuming. In this paper, we propose an accurate method for detecting the mitotic cells from histopathological slides using a novel multi-stage deep learning framework. Our method consists of a deep segmentation network for generating mitosis region when only a weak label is given (i.e., only the centroid pixel of mitosis is annotated), an elaborately designed deep detection network for localizing mitosis by using contextual region information, and a deep verification network for improving detection accuracy by removing false positives. We validate the proposed deep learning method on two widely used Mitosis Detection in Breast Cancer Histological Images (MITOSIS) datasets. Experimental results show that we can achieve the highest F-score on the MITOSIS dataset from ICPR 2012 grand challenge merely using the deep detection network. For the ICPR 2014 MITOSIS dataset that only provides the centroid location of mitosis, we employ the segmentation model to estimate the bounding box annotation for training the deep detection network. We also apply the verification model to eliminate some false positives produced from the detection model. By fusing scores of the detection and verification models, we achieve the state-of-the-art results. Moreover, our method is very fast with GPU computing, which makes it feasible for clinical practice. Copyright © 2018 Elsevier B.V. All rights reserved.

Interpretable Deep Models for ICU Outcome Prediction

PubMed Central

Che, Zhengping; Purushotham, Sanjay; Khemani, Robinder; Liu, Yan

2016-01-01

Exponential surge in health care data, such as longitudinal data from electronic health records (EHR), sensor data from intensive care unit (ICU), etc., is providing new opportunities to discover meaningful data-driven characteristics and patterns ofdiseases. Recently, deep learning models have been employedfor many computational phenotyping and healthcare prediction tasks to achieve state-of-the-art performance. However, deep models lack interpretability which is crucial for wide adoption in medical research and clinical decision-making. In this paper, we introduce a simple yet powerful knowledge-distillation approach called interpretable mimic learning, which uses gradient boosting trees to learn interpretable models and at the same time achieves strong prediction performance as deep learning models. Experiment results on Pediatric ICU dataset for acute lung injury (ALI) show that our proposed method not only outperforms state-of-the-art approaches for morality and ventilator free days prediction tasks but can also provide interpretable models to clinicians. PMID:28269832

Study of Colloidal Gold Synthesis Using Turkevich Method

NASA Astrophysics Data System (ADS)

Rohiman, Asep; Anshori, Isa; Surawijaya, Akhmadi; Idris, Irman

2011-12-01

The synthesis of colloidal gold or Au-nanoparticles (Au-NPs) by reduction of chloroauric acid (HAuCl4) with sodium citrate was done using Turkevich method. We prepare HAuCl4 solution by dissolving gold wires (99.99%) into aqua regia solution. To initiate the Au-NPs synthesis 0.17 ml of 1 % chloroauric acid solution was heated to the boiling point and then 10 ml of 1 % sodium citrate was added to the boiling solution with a constant stirring in order to maintain a homogenous solution. A color of faint gray was observed in the solution approximately one minute and in a period of 2-3 minutes later, it further darkened to deep wine and red color. It showed that the gold solution has reduced to Au-NPs. The effect of process temperature on the size of Au-NPs prepared by sodium citrate reduction has also been investigated. With increasing temperature of Au-NPs synthesis, smaller-size Au-NPs were obtained. The higher temperatures shorten the time needed to achieve activation energy for reduction process. The resulting Au-NPs has been characterized by scanning Electron Microscope (SEM), showing the size of Au-NPs average diameter is ˜20-27 nm. The resulting colloidal gold will be used as catalyst for Si nanowires growth using VLS method.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease

NASA Astrophysics Data System (ADS)

Gorzelic, P.; Schiff, S. J.; Sinha, A.

2013-04-01

Objective. To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). Approach. A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. Main Results. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Significance. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease.

PubMed

Gorzelic, P; Schiff, S J; Sinha, A

2013-04-01

To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Hello World Deep Learning in Medical Imaging.

PubMed

Lakhani, Paras; Gray, Daniel L; Pett, Carl R; Nagy, Paul; Shih, George

2018-05-03

There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

LOFAR 150-MHz observations of the Boötes field: catalogue and source counts

NASA Astrophysics Data System (ADS)

Williams, W. L.; van Weeren, R. J.; Röttgering, H. J. A.; Best, P.; Dijkema, T. J.; de Gasperin, F.; Hardcastle, M. J.; Heald, G.; Prandoni, I.; Sabater, J.; Shimwell, T. W.; Tasse, C.; van Bemmel, I. M.; Brüggen, M.; Brunetti, G.; Conway, J. E.; Enßlin, T.; Engels, D.; Falcke, H.; Ferrari, C.; Haverkorn, M.; Jackson, N.; Jarvis, M. J.; Kapińska, A. D.; Mahony, E. K.; Miley, G. K.; Morabito, L. K.; Morganti, R.; Orrú, E.; Retana-Montenegro, E.; Sridhar, S. S.; Toribio, M. C.; White, G. J.; Wise, M. W.; Zwart, J. T. L.

2016-08-01

We present the first wide area (19 deg2), deep (≈120-150 μJy beam-1), high-resolution (5.6 × 7.4 arcsec) LOFAR High Band Antenna image of the Boötes field made at 130-169 MHz. This image is at least an order of magnitude deeper and 3-5 times higher in angular resolution than previously achieved for this field at low frequencies. The observations and data reduction, which includes full direction-dependent calibration, are described here. We present a radio source catalogue containing 6 276 sources detected over an area of 19 deg2, with a peak flux density threshold of 5σ. As the first thorough test of the facet calibration strategy, introduced by van Weeren et al., we investigate the flux and positional accuracy of the catalogue. We present differential source counts that reach an order of magnitude deeper in flux density than previously achieved at these low frequencies, and show flattening at 150-MHz flux densities below 10 mJy associated with the rise of the low flux density star-forming galaxies and radio-quiet AGN.

Use of a "small-bubble technique" to increase the success of Anwar's "big-bubble technique" for deep lamellar keratoplasty with complete baring of Descemet's membrane.

PubMed

Parthasarathy, Anand; Por, Yong Ming; Tan, Donald T H

2007-10-01

To describe a quick and simple "small-bubble" technique to immediately determine the success of attaining complete Descemet's membrane (DM) separation from corneal stroma through Anwar's "big-bubble" technique of deep anterior lamellar keratoplasty (DALK) for complete stromal removal. A partial trephination was followed by a lamellar dissection of the anterior stroma. Deep stromal air injection was then attempted to achieve the big bubble to help separate the stroma from the DM. To confirm that a big bubble had been achieved, a small air bubble was injected into the anterior chamber (AC) through a limbal paracentesis. If the small bubble is then seen at the corneal periphery, it confirms that the big-bubble separation of DM was successful because the convex nature of the bubble will cause it to protrude posteriorly, forcing the small AC bubble to the periphery. If the small AC bubble is not seen in the corneal periphery, this means that it is present in the centre, beneath the opaque corneal stroma, and therefore the big bubble has not been achieved. We used the small-bubble technique to confirm the presence of the big bubble in three (one keratoconus, one interstitial keratitis and one dense corneal scar) out of 41 patients who underwent DALK. The small-bubble technique confirmed that the big bubble was achieved in the eye of all three patients. Complete stromal removal with baring of the DM was achieved, and postoperatively all three eyes achieved best corrected vision of 6/6. The small-bubble technique can be a useful surgical tool for corneal surgeons attempting lamellar keratoplasty using the big-bubble technique. It helps in confirming the separation of DM from the deep stroma, which is important in achieving total stromal replacement. It will help to make the transition to lamellar keratoplasty smoother, enhance corneal graft success and improve visual outcomes in patients.

Tsunami Speed Variations in Density-stratified Compressible Global Oceans

NASA Astrophysics Data System (ADS)

Watada, S.

2013-12-01

Recent tsunami observations in the deep ocean have accumulated unequivocal evidence that tsunami traveltime delays compared with the linear long-wave tsunami simulations occur during tsunami propagation in the deep ocean. The delay is up to 2% of the tsunami traveltime. Watada et al. [2013] investigated the cause of the delay using the normal mode theory of tsunamis and attributed the delay to the compressibility of seawater, the elasticity of the solid earth, and the gravitational potential change associated with mass motion during the passage of tsunamis. Tsunami speed variations in the deep ocean caused by seawater density stratification is investigated using a newly developed propagator matrix method that is applicable to seawater with depth-variable sound speeds and density gradients. For a 4-km deep ocean, the total tsunami speed reduction is 0.45% compared with incompressible homogeneous seawater; two thirds of the reduction is due to elastic energy stored in the water and one third is due to water density stratification mainly by hydrostatic compression. Tsunami speeds are computed for global ocean density and sound speed profiles and characteristic structures are discussed. Tsunami speed reductions are proportional to ocean depth with small variations, except for in warm Mediterranean seas. The impacts of seawater compressibility and the elasticity effect of the solid earth on tsunami traveltime should be included for precise modeling of trans-oceanic tsunamis. Data locations where a vertical ocean profile deeper than 2500 m is available in World Ocean Atlas 2009. The dark gray area indicates the Pacific Ocean defined in WOA09. a) Tsunami speed variations. Red, gray and black bars represent global, Pacific, and Mediterranean Sea, respectively. b) Regression lines of the tsunami velocity reduction for all oceans. c)Vertical ocean profiles at grid points indicated by the stars in Figure 1.

Deep space communication - A one billion mile noisy channel

NASA Technical Reports Server (NTRS)

Smith, J. G.

1982-01-01

Deep space exploration is concerned with the study of natural phenomena in the solar system with the aid of measurements made at spacecraft on deep space missions. Deep space communication refers to communication between earth and spacecraft in deep space. The Deep Space Network is an earth-based facility employed for deep space communication. It includes a network of large tracking antennas located at various positions around the earth. The goals and achievements of deep space exploration over the past 20 years are discussed along with the broad functional requirements of deep space missions. Attention is given to the differences in space loss between communication satellites and deep space vehicles, effects of the long round-trip light time on spacecraft autonomy, requirements for the use of massive nuclear power plants on spacecraft at large distances from the sun, and the kinds of scientific return provided by a deep space mission. Problems concerning a deep space link of one billion miles are also explored.

The Deep Space Gateway: The Next Stepping Stone to Mars

NASA Astrophysics Data System (ADS)

Cassady, R. J.; Carberry, C.; Cichan, T.

2018-02-01

Human missions to Mars will benefit from precursor missions such as the Deep Space Gateway (DSG) that achieve important science and human health and safety milestones. The DSG can perform lunar science and prepare for future Mars mission science.

Exploring the Function Space of Deep-Learning Machines

NASA Astrophysics Data System (ADS)

Li, Bo; Saad, David

2018-06-01

The function space of deep-learning machines is investigated by studying growth in the entropy of functions of a given error with respect to a reference function, realized by a deep-learning machine. Using physics-inspired methods we study both sparsely and densely connected architectures to discover a layerwise convergence of candidate functions, marked by a corresponding reduction in entropy when approaching the reference function, gain insight into the importance of having a large number of layers, and observe phase transitions as the error increases.

New Propulsion Technologies For Exploration of the Solar System and Beyond

NASA Technical Reports Server (NTRS)

Johnson, Les; Cook, Stephen (Technical Monitor)

2001-01-01

In order to implement the ambitious science and exploration missions planned over the next several decades, improvements in in-space transportation and propulsion technologies must be achieved. For robotic exploration and science missions, increased efficiencies of future propulsion systems are critical to reduce overall life-cycle costs. Future missions will require 2 to 3 times more total change in velocity over their mission lives than the NASA Solar Electric Technology Application Readiness (NSTAR) demonstration on the Deep Space 1 mission. Rendezvous and return missions will require similar investments in in-space propulsion systems. New opportunities to explore beyond the outer planets and to the stars will require unparalleled technology advancement and innovation. The Advanced Space Transportation Program (ASTP) is investing in technologies to achieve a factor of 10 reduction in the cost of Earth orbital transportation and a factor of 2 reduction in propulsion system mass and travel time for planetary missions within the next 15 years. Since more than 70% of projected launches over the next 10 years will require propulsion systems capable of attaining destinations beyond Low Earth Orbit, investment in in-space technologies will benefit a large percentage of future missions. The ASTP technology portfolio includes many advanced propulsion systems. From the next generation ion propulsion system operating in the 5 - 10 kW range, to fission-powered multi-kilowatt systems, substantial advances in spacecraft propulsion performance are anticipated. Some of the most promising technologies for achieving these goals use the environment of space itself for energy and propulsion and are generically called, "propellantless" because they do not require on-board fuel to achieve thrust. An overview of the state-of-the-art in propellantless propulsion technologies such as solar and plasma sails, electrodynamic and momentum transfer tethers, and aeroassist and aerocapture will also be described. Results of recent earth-based technology demonstrations and space tests for many of these new propulsion technologies will be discussed.

Anti-scar Treatment for Deep Partial-thickness Burn Wounds

DTIC Science & Technology

2017-10-01

fibrosis will be correlated with scar reduction. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Unclassified 18. NUMBER...treatment will be optimized and molecular markers of inflammation, angiogenesis, wound healing, and fibrosis will be correlated with scar reduction

The effects of deep network topology on mortality prediction.

PubMed

Hao Du; Ghassemi, Mohammad M; Mengling Feng

2016-08-01

Deep learning has achieved remarkable results in the areas of computer vision, speech recognition, natural language processing and most recently, even playing Go. The application of deep-learning to problems in healthcare, however, has gained attention only in recent years, and it's ultimate place at the bedside remains a topic of skeptical discussion. While there is a growing academic interest in the application of Machine Learning (ML) techniques to clinical problems, many in the clinical community see little incentive to upgrade from simpler methods, such as logistic regression, to deep learning. Logistic regression, after all, provides odds ratios, p-values and confidence intervals that allow for ease of interpretation, while deep nets are often seen as `black-boxes' which are difficult to understand and, as of yet, have not demonstrated performance levels far exceeding their simpler counterparts. If deep learning is to ever take a place at the bedside, it will require studies which (1) showcase the performance of deep-learning methods relative to other approaches and (2) interpret the relationships between network structure, model performance, features and outcomes. We have chosen these two requirements as the goal of this study. In our investigation, we utilized a publicly available EMR dataset of over 32,000 intensive care unit patients and trained a Deep Belief Network (DBN) to predict patient mortality at discharge. Utilizing an evolutionary algorithm, we demonstrate automated topology selection for DBNs. We demonstrate that with the correct topology selection, DBNs can achieve better prediction performance compared to several bench-marking methods.

Deglacial 'ping-pong' between East Asian Monsoon, North Pacific Meridional Overturning Circulation, and sediment dynamics along the deep northern South China Sea margin

NASA Astrophysics Data System (ADS)

Sarnthein, M.

2011-12-01

On the basis of marine and speleothem paleoclimate records it is widely accepted that the East Asian summer monsoon was strongly reduced during Heinrich stadial 1 (HS-1) such as during preceding stadials. Accordingly, Eastern Asia suffered from severe aridity from 17.4 - 14.7 ka, when all great Asian rivers from the Mekong in the south up to the Amur in the north almost ceased flowing into the Western Pacific. Today, the modern freshwater input of these rivers sums up to approx. 0.165 Sverdrups (in addition to the river discharge from Canada and Alaska), a flow possibly similar to the meltwater outbreaks that induced Atlantic Heinrich stadials. The East Asian freshwater feeds the Kuroshio/Oyashio Currents which act as "rain gutter" and finally discharge the freshwater up to the subarctic North Pacific (sensu Emile-Geay, et al., 2003). Indeed, the great reduction in both the fluvial freshwater discharge and the direct monsoon precipitation over the N.W. Pacific during HS-1 matched a significant rise in sea surface salinity in the subarctic North Pacific. Most important, it was precisely coeval with a thousand-year long pulse of North Pacific deep-water convection down to >3600 m water depth. This event obviously reflects a direct response to the great reduction in East Asian monsoon precipitation and is inferred from a major reduction of planktic reservoir ages from 1150 to 300 yr in the northwest Pacific and in particular, from an abrupt reduction of benthic ventilation ages by 1500 yr and a prominent minimum in bottom water alkalinity inferred from minimum delta11B, that suggests intensive vertical downmixing. The ventilated North Pacific deep waters, in turn, probably formed a western boundary current per analogy to that along the modern West Atlantic margin and finally entered the South China Sea with a lag of centuries. Today the track of the Pacific inflow can be traced along the northern margin of the South China Sea near 2000 m water depth by means of erosional furrows that reflect winnowing and/or erosion. The great deglacial incursion of North Pacific deep waters is reflected by a prominent reduction in deep-water ventilation ages and a maximum in CaCO3 preservation that leads to an aragonite spike. Near the end of previous glacial terminations II, III, and V (i.e., in the context of Heinrich stadials associated) the deglacial incursion pulses of North Pacific Deep Water probably resulted in major erosional hiatuses found at ODP Site 1144 to the south of HongKong, which each may finally be traced back to a short-term dramatic reduction in East Asian monsoon moisture during deglacial Heinrich events as ultimate driver of short-term convection events in the N.W. Pacific. Ref.: Emile-Geay, J., et al., 2003, Warren revisited: Atmospheric freshwater fluxes and 'Why is no deep water formed in the North Pacific.' - JGR 108, C6, 3178, doi:10.1029/2001JC001058.

Effect of dry large-scale vertical motions on initial MJO convective onset

NASA Astrophysics Data System (ADS)

Powell, Scott W.; Houze, Robert A.

2015-05-01

Anomalies of eastward propagating large-scale vertical motion with ~30 day variability at Addu City, Maldives, move into the Indian Ocean from the west and are implicated in Madden-Julian Oscillation (MJO) convective onset. Using ground-based radar and large-scale forcing data derived from a sounding array, typical profiles of environmental heating, moisture sink, vertical motion, moisture advection, and Eulerian moisture tendency are computed for periods prior to those during which deep convection is prevalent and those during which moderately deep cumulonimbi do not form into deep clouds. Convection with 3-7 km tops is ubiquitous but present in greater numbers when tropospheric moistening occurs below 600 hPa. Vertical eddy convergence of moisture in shallow to moderately deep clouds is likely responsible for moistening during a 3-7 day long transition period between suppressed and active MJO conditions, although moistening via evaporation of cloud condensate detrained into the environment of such clouds may also be important. Reduction in large-scale subsidence, associated with a vertical velocity structure that travels with a dry eastward propagating zonal wavenumbers 1-1.5 structure in zonal wind, drives a steepening of the lapse rate below 700 hPa, which supports an increase in moderately deep moist convection. As the moderately deep cumulonimbi moisten the lower troposphere, more deep convection develops, which itself moistens the upper troposphere. Reduction in large-scale subsidence associated with the eastward propagating feature reinforces the upper tropospheric moistening, helping to then rapidly make the environment conducive to formation of large stratiform precipitation regions, whose heating is critical for MJO maintenance.

Root growth and water relations of oak and birch seedlings.

PubMed

Osonubi, O; Davies, W J

1981-01-01

First year seedlings of English oak (Quercus Cobur) and silver birch (Betula pendula) were subjected to pressure-volume analysis to investigate the water potential components and cell wall properties of single leaves. It was hoped that this rapid-drying technique would differentiate between reductions in plant solute potential resulting from dehydration and the effects of solute accumulation.Comparison of results from these experiments with those of slow drying treatments (over a number of days) with plants growing in tubes of soil, indicated that some solute accumulation may have occurred in drying oak leaves. High leaf turgor and leaf conductance were maintained for a significant period of the drying cycle. Roots of well-watered oak plants extended deep into the soil profile, and possibly as a result of solute regulation and therefore turgor maintenance, root growth of unwatered plants was greater than that of their well-watered counterparts. This was particularly the case deep in the profile. As a result of deep root penetration, water deep in the soil core was used by oak plants to maintain plant turgor, and quite low soil water potentials were recorded in the lower soil segments.Root growth of well-watered birch seedlings was prolific but roots of both well-watered and unwatered plants were restricted to the upper part of the profile. Root growth of unwatered plants was reduced despite the existence of high soil water potentials deep in the profile. Shallow rooting birch seedlings were unable to use this water.Pressure-volume analysis indicated that significant reductions of water potential, which are required for water uptake from drying soil, would occur in oak with only a small reduction in plant water content compared to the situation in birch. This was a result of the low solute potential in oak leaves combined with a high modulus of elasticity of cell walls. Deep rooting of oak seedlings, combined with these characteristics, which will be particularly important when soil deep in the profile begins to dry, mean that this species may be comparatively successful when growing on dry sites.

Reduction of atherothrombotic burden before stent deployment in non-ST elevation acute coronary syndromes: Reduction of myocardial necrosis achieved with nose-dive manual thrombus aspiration (REMNANT) trial. A volumetric intravascular ultrasound study.

PubMed

Zimarino, Marco; Angeramo, Francesca; Prasad, Abhiram; Ruggieri, Benedetta; Malatesta, Sara; Prati, Francesco; Buttitta, Fiamma; De Caterina, Raffaele

2016-11-01

To test whether thrombus aspiration (TA) reduces the atherosclerotic burden in culprit lesions and "facilitate" percutaneous coronary intervention with stent (S-PCI) among patients with non-ST elevation acute coronary syndromes (NSTE-ACS). Evidence on the effects of TA adjunctive to S-PCI in NSTE-ACS is limited and controversial. TA was defined "aggressive" when using 7F devices or a catheter/artery ratio >0.6, "conservative" with 6F, and a catheter/artery ratio ≤0.6. Angiography and intravascular ultrasound (IVUS) were performed at baseline, after TA and after stent deployment. TA was accomplished in 61/76 patients (80%) with NSTE-ACS. The aspirated material was red thrombus in 23% and plaque fragments in 49% of cases. Compared with baseline, TA was associated with an 82% increase in minimal lumen diameter and a 15% reduction in diameter stenosis (P < 0.001 for both). After TA, IVUS documented a 24 and 16% increase in minimal lumen area and lumen volume, respectively (P < 0.001 for both), a 7% decrease in area stenosis through an 11% reduction of plaque + media volume (P < 0.001). When compared with "conservative", an "aggressive" TA was associated with a more pronounced reduction in percent area stenosis (P < 0.05) and an increase in percent stent expansion (P < 0.001). The plaque + media volume reduction after TA was correlated with stent expansion (r = 0.261, P = 0.046). Manual TA reduces atherothrombotic burden in culprit lesions of NSTE-ACS patients before S-PCI and, when deep plaque removal is obtained, TA optimizes subsequent stent expansion. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Advanced Technologies to Improve Closure of Life Support Systems

NASA Technical Reports Server (NTRS)

Barta, Daniel J.

2016-01-01

As NASA looks beyond the International Space Station toward long-duration, deep space missions away from Earth, the current practice of supplying consumables and spares will not be practical nor affordable. New approaches are sought for life support and habitation systems that will reduce dependency on Earth and increase mission sustainability. To reduce launch mass, further closure of Environmental Control and Life Support Systems (ECLSS) beyond the current capability of the ISS will be required. Areas of particular interest include achieving higher degrees of recycling within Atmosphere Revitalization, Water Recovery and Waste Management Systems. NASA is currently investigating advanced carbon dioxide reduction processes that surpass the level of oxygen recovery available from the Sabatier Carbon Dioxide Reduction Assembly (CRA) on the ISS. Candidate technologies will potentially improve the recovery of oxygen from about 50% (for the CRA) to as much as 100% for technologies who's end product is solid carbon. Improving the efficiency of water recycling and recovery can be achieved by the addition of advanced technologies to recover water from brines and solid wastes. Bioregenerative technologies may be utilized for water reclaimation and also for the production of food. Use of higher plants will simultaneously benefit atmosphere revitalization and water recovery through photosynthesis and transpiration. The level at which bioregenerative technologies are utilized will depend on their comparative requirements for spacecraft resources including mass, power, volume, heat rejection, crew time and reliability. Planetary protection requirements will need to be considered for missions to other solar system bodies.

Effectiveness of bridge V.A.C. dressings in the treatment of diabetic foot ulcers

PubMed Central

Nather, Aziz; Hong, Ng Yau; Lin, Wong Keng; Sakharam, Joshi Abhijit

2011-01-01

Objectives This is a prospective study of the clinical efficacy of the V.A.C. Granufoam Bridge Dressing for the treatment of diabetic foot ulcers. Materials and methods Five consecutive patients with diabetic foot ulcers were treated with V.A.C. Granufoam Bridge Dressings and studied over a period of 22–48 days. The indications for treatment included diabetic patients with open ray amputation wounds and wounds post-drainage for abscess with exposed deep structures. Clinical outcome was measured in terms of reduction in wound dimensions, presence of wound granulation, microbial clearance, and development of wound complications. Results Our results showed that with V.A.C. therapy, wound healing occurred in all patients. The number of dressings required ranged from 8 to 10. The baseline average wound size was 23.1 cm2. Wound areas shrunk by 18.4–41.7%. All subjects achieved 100% wound bed granulation with an average length of treatment of 33 days. Microbial clearance was achieved in all cases. All wounds healed by secondary intention in one case and four cases required split-thickness skin grafting. Conclusion The V.A.C. Granufoam Bridge Dressing is effective in the treatment of diabetic foot ulcers. It promotes reduction of wound area, wound bed granulation, and microbial clearance. By allowing placement of the suction pad outside the foot, it allowed patients to wear protective shoes and to walk non-weight bearing with crutches during V.A.C. therapy. PMID:22396825

Deep aquifer as driver for mineral authigenesis in Gulf of Alaska sediments (IODP Expedition 341, Site U1417)

NASA Astrophysics Data System (ADS)

Zindorf, Mark; März, Christian; Wagner, Thomas; Strauss, Harald; Gulick, Sean P. S.; Jaeger, John M.; LeVay, Leah J.

2016-04-01

Bacterial sulphate reduction plays a key role in authigenic mineral formation in marine sediments. Usually, decomposition of organic matter follows a sequence of microbial metabolic pathways, where microbial sulphate reduction leads to sulphate depletion deeper in the sediment. When sulphate is consumed completely from the pore waters, methanogenesis commences. The contact of sulphate- and methane-containing pore waters is a well-defined biogeochemical boundary (the sulphate-methane transition zone, SMTZ). Here authigenic pyrite, barite and carbonates form. Pyrite formation is directly driven by bacterial sulphate reduction since pyrite precipitates from produced hydrogen sulphide. Barite and carbonate formation are secondary effects resulting from changes of the chemical milieu due to microbial activity. However, this mineral authigenesis is ultimately linked to abiotic processes that determine the living conditions for microorganisms. At IODP Site U1417 in the Gulf of Alaska, a remarkable diagenetic pattern has been observed: Between sulphate depletion and methane enrichment, a ~250 m wide gap exists. Consequently, no SMTZ can be found under present conditions, but enrichments of pyrite indicate that such zones have existed in the past. Solid layers consisting of authigenic carbonate-cemented sand were partly recovered right above the methane production zone, likely preventing continued upward methane diffusion. At the bottom of the sediment succession, the lower boundary of the methanogenic zone is constrained by sulphate-rich pore waters that appear to originate from a deeper source. Here, a well-established SMTZ exists, but in reversed order (sulphate diffusing up, methane diffusing down). Sulphur isotopes of pyrite reveal that sulphate reduction here does not occur under closed system conditions. This indicates that a deep aquifer is actively recharging the deep sulphate pool. Similar deep SMTZs have been found at other sites, yet mostly in geologically active environments such as ridge flanks or above subduction zones. Therefore Site U1417, in a relatively inactive intraplate environment, represents a so far under-sampled geochemical setting. Calculated accumulation times for authigenic minerals in the deep SMTZ are on the same order of magnitude as the onset of subduction-related bending of the Pacific Plate, suggesting that both processes are linked. Plate bending could create fractures in the overlying sediments allowing seawater to penetrate and recharge a deep aquifer. Our study provides insights into a newly discovered geological process suitable for delivering sulphate-rich water deep into the sediments and installing diagenetically active environments where microbial activity would otherwise be very limited.

Interference-Fit Life Factors for Ball Bearings

NASA Technical Reports Server (NTRS)

Oswald, Fred B.; Zaretsky, Erwin V.; Poplawski, Joseph V.

2010-01-01

The effect of hoop stresses on the rolling-element fatigue life of angular-contact and deep-groove ball bearings was determined for common inner-ring interference fits at the ABEC-5 tolerance level. The analysis was applied to over 1150 bearing configurations and load cases. Hoop stresses were superimposed on the Hertzian principal stresses created by the applied bearing load to calculate the inner-race maximum shearing stress. The resulting fatigue life of the bearing was recalculated through a series of equations. The reduction in the fatigue life is presented as life factors that are applied to the unfactored bearing life. The life factors found in this study ranged from 1.00 (no life reduction)--where there was no net interface pressure--to a worst case of 0.38 (a 62-percent life reduction). For a given interference fit, the reduction in life is different for angular-contact and deep-groove ball bearings. Interference fits also affect the maximum Hertz stress-life relation. Experimental data of Czyzewski, showing the effect of interference fit on rolling-element fatigue life, were reanalyzed to determine the shear stress-life exponent. The Czyzewski data shear stress-life exponent c equals 8.77, compared with the assumed value of 9. Results are presented as tables and charts of life factors for angular-contact and deep-groove ball bearings with light, normal, and heavy loads and interference fits ranging from extremely light to extremely heavy.

Low-complexity object detection with deep convolutional neural network for embedded systems

NASA Astrophysics Data System (ADS)

Tripathi, Subarna; Kang, Byeongkeun; Dane, Gokce; Nguyen, Truong

2017-09-01

We investigate low-complexity convolutional neural networks (CNNs) for object detection for embedded vision applications. It is well-known that consolidation of an embedded system for CNN-based object detection is more challenging due to computation and memory requirement comparing with problems like image classification. To achieve these requirements, we design and develop an end-to-end TensorFlow (TF)-based fully-convolutional deep neural network for generic object detection task inspired by one of the fastest framework, YOLO.1 The proposed network predicts the localization of every object by regressing the coordinates of the corresponding bounding box as in YOLO. Hence, the network is able to detect any objects without any limitations in the size of the objects. However, unlike YOLO, all the layers in the proposed network is fully-convolutional. Thus, it is able to take input images of any size. We pick face detection as an use case. We evaluate the proposed model for face detection on FDDB dataset and Widerface dataset. As another use case of generic object detection, we evaluate its performance on PASCAL VOC dataset. The experimental results demonstrate that the proposed network can predict object instances of different sizes and poses in a single frame. Moreover, the results show that the proposed method achieves comparative accuracy comparing with the state-of-the-art CNN-based object detection methods while reducing the model size by 3× and memory-BW by 3 - 4× comparing with one of the best real-time CNN-based object detectors, YOLO. Our 8-bit fixed-point TF-model provides additional 4× memory reduction while keeping the accuracy nearly as good as the floating-point model. Moreover, the fixed- point model is capable of achieving 20× faster inference speed comparing with the floating-point model. Thus, the proposed method is promising for embedded implementations.

VUV lithography

DOEpatents

George, Edward V.; Oster, Yale; Mundinger, David C.

1990-01-01

Deep UV projection lithography can be performed using an e-beam pumped solid excimer UV source, a mask, and a UV reduction camera. The UV source produces deep UV radiation in the range 1700-1300A using xenon, krypton or argon; shorter wavelengths of 850-650A can be obtained using neon or helium. A thin solid layer of the gas is formed on a cryogenically cooled plate and bombarded with an e-beam to cause fluorescence. The UV reduction camera utilizes multilayer mirrors having high reflectivity at the UV wavelength and images the mask onto a resist coated substrate at a preselected demagnification. The mask can be formed integrally with the source as an emitting mask.

ESO Advanced Data Products for the Virtual Observatory

NASA Astrophysics Data System (ADS)

Retzlaff, J.; Delmotte, N.; Rite, C.; Rosati, P.; Slijkhuis, R.; Vandame, B.

2006-07-01

Advanced Data Products, that is, completely reduced, fully characterized science-ready data sets, play a crucial role for the success of the Virtual Observatory as a whole. We report on on-going work at ESO towards the creation and publication of Advanced Data Products in compliance with present VO standards on resource metadata. The new deep NIR multi-color mosaic of the GOODS/CDF-S region is used to showcase different aspects of the entire process: data reduction employing our MVM-based reduction pipeline, calibration and data characterization procedures, standardization of metadata content, and, finally, a prospect of the scientific potential illustrated by new results on deep galaxy number counts.

Early Intervention in Psychosis

PubMed Central

McGorry, Patrick D.

2015-01-01

Abstract Early intervention for potentially serious disorder is a fundamental feature of healthcare across the spectrum of physical illness. It has been a major factor in the reductions in morbidity and mortality that have been achieved in some of the non-communicable diseases, notably cancer and cardiovascular disease. Over the past two decades, an international collaborative effort has been mounted to build the evidence and the capacity for early intervention in the psychotic disorders, notably schizophrenia, where for so long deep pessimism had reigned. The origins and rapid development of early intervention in psychosis are described from a personal and Australian perspective. This uniquely evidence-informed, evidence-building and cost-effective reform provides a blueprint and launch pad to radically change the wider landscape of mental health care and dissolve many of the barriers that have constrained progress for so long. PMID:25919380

Nanostructured silicon membranes for control of molecular transport.

PubMed

Srijanto, Bernadeta R; Retterer, Scott T; Fowlkes, Jason D; Doktycz, Mitchel J

2010-11-01

A membrane that allows selective transport of molecular species requires precise engineering on the nanoscale. Membrane permeability can be tuned by controlling the physical structure and surface chemistry of the pores. Here, a combination of electron beam and optical lithography, along with cryogenic deep reactive ion etching, has been used to fabricate silicon membranes that are physically robust, have uniform pore sizes, and are directly integrated into a microfluidic network. Additional reductions in pore size were achieved using plasma enhanced chemical vapor deposition and atomic layer deposition of silicon dioxide to coat membrane surfaces. Cross sectioning of the membranes using focused ion beam milling was used to determine the physical shape of the membrane pores before and after coating. Functional characterization of the membranes was performed by using quantitative fluorescence microscopy to document the transport of molecular species across the membrane.

Deep-sea vent chemoautotrophs: diversity, biochemistry and ecological significance.

PubMed

Nakagawa, Satoshi; Takai, Ken

2008-07-01

Deep-sea vents support productive ecosystems driven primarily by chemoautotrophs. Chemoautotrophs are organisms that are able to fix inorganic carbon using a chemical energy obtained through the oxidation of reduced compounds. Following the discovery of deep-sea vent ecosystems in 1977, there has been an increasing knowledge that deep-sea vent chemoautotrophs display remarkable physiological and phylogenetic diversity. Cultivation-dependent and -independent studies have led to an emerging view that the majority of deep-sea vent chemoautotrophs have the ability to derive energy from a variety of redox couples other than the conventional sulfur-oxygen couple, and fix inorganic carbon via the reductive tricarboxylic acid cycle. In addition, recent genomic, metagenomic and postgenomic studies have considerably accelerated the comprehensive understanding of molecular mechanisms of deep-sea vent chemoautotrophy, even in yet uncultivable endosymbionts of vent fauna. Genomic analysis also suggested that there are previously unrecognized evolutionary links between deep-sea vent chemoautotrophs and important human/animal pathogens. This review summarizes chemoautotrophy in deep-sea vents, highlighting recent biochemical and genomic discoveries.

A Non-Invasive Deep Tissue PH Monitor.

DTIC Science & Technology

1995-08-11

disturbances in acid-base regulation may have serious effects on metabolic activity, circulation, and the central nervous system. Currently, acid-base...to tissue ischemia than is arterial pH. Consequently, a non-invasive deep tissue pH monitor has enormous value as a mechanism for rapid and effective ...achieved, and improve our understanding of what physical effects are important to successful non-invasive deep tissue pH monitoring. This last statement

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 sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction.

PubMed

Deng, Lei; Fan, Chao; Zeng, Zhiwen

2017-12-28

Direct prediction of the three-dimensional (3D) structures of proteins from one-dimensional (1D) sequences is a challenging problem. Significant structural characteristics such as solvent accessibility and contact number are essential for deriving restrains in modeling protein folding and protein 3D structure. Thus, accurately predicting these features is a critical step for 3D protein structure building. In this study, we present DeepSacon, a computational method that can effectively predict protein solvent accessibility and contact number by using a deep neural network, which is built based on stacked autoencoder and a dropout method. The results demonstrate that our proposed DeepSacon achieves a significant improvement in the prediction quality compared with the state-of-the-art methods. We obtain 0.70 three-state accuracy for solvent accessibility, 0.33 15-state accuracy and 0.74 Pearson Correlation Coefficient (PCC) for the contact number on the 5729 monomeric soluble globular protein dataset. We also evaluate the performance on the CASP11 benchmark dataset, DeepSacon achieves 0.68 three-state accuracy and 0.69 PCC for solvent accessibility and contact number, respectively. We have shown that DeepSacon can reliably predict solvent accessibility and contact number with stacked sparse autoencoder and a dropout approach.

Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks.

PubMed

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2018-06-13

Deep learning has been increasingly used to solve a number of problems with state-of-the-art performance in a wide variety of fields. In biology, deep learning can be applied to reduce feature extraction time and achieve high levels of performance. In our present work, we apply deep learning via two-dimensional convolutional neural networks and position-specific scoring matrices to classify Rab protein molecules, which are main regulators in membrane trafficking for transferring proteins and other macromolecules throughout the cell. The functional loss of specific Rab molecular functions has been implicated in a variety of human diseases, e.g., choroideremia, intellectual disabilities, cancer. Therefore, creating a precise model for classifying Rabs is crucial in helping biologists understand the molecular functions of Rabs and design drug targets according to such specific human disease information. We constructed a robust deep neural network for classifying Rabs that achieved an accuracy of 99%, 99.5%, 96.3%, and 97.6% for each of four specific molecular functions. Our approach demonstrates superior performance to traditional artificial neural networks. Therefore, from our proposed study, we provide both an effective tool for classifying Rab proteins and a basis for further research that can improve the performance of biological modeling using deep neural networks. Copyright © 2018 Elsevier Inc. All rights reserved.

Fast and low power Michelson interferometer thermo-optical switch on SOI.

PubMed

Song, Junfeng; Fang, Q; Tao, S H; Liow, T Y; Yu, M B; Lo, G Q; Kwong, D L

2008-09-29

We designed and fabricated silicon-on-insulator based Michelson interferometer (MI) thermo-optical switches with deep etched trenches for heat-isolation. Switch power was reduced approximately 20% for the switch with deep etched trenches, and the MI saved approximately 50% power than that of the Mach-Zehnder interferometer. 10.6 mW switch power, approximately 42 micros switch time for the MI with deep trenches, 13.14 mW switch power and approximately 34 micros switch time for the MI without deep trenches were achieved.

Effects of cooking on levels of PCBs in the fillets of winter flounder (Pseudopleuronectes americanus)

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

Poston, T.M.; Durell, G.S.; Koczwara, G.

1995-08-01

The Pacific Northwest Laboratory and Battelle Ocean Sciences performed a study to determine the effect of cooking on polychlorinated biphenyl (PCB) levels in the fillets of winter flounder (Pseudopleuronectes americanus). Broiling, pan frying, and deep frying in oil were tested on fillets from 21 fish collected from New Bedford Harbor, Massachusetts, on February 21, 1991. The evaluation involved estimating the change in PCB concentrations using a mass-balance approach that factored the change in fillet weight resulting from cooking with the changes in PCB concentration expressed on a precooked wet-weight basis. Deep frying in oil resulted in a 47% reduction inmore » total PCB levels in fillet tissue. Additionally, deep frying caused a 40% reduction in fillet mass. Pan frying and broiling resulted in statistically in insignificant increases in total PCB levels of 15% and 17%, respectively. Fillet mass reductions resulting from pan frying and broiling were 7% and 15%, respectively. The effects of cooking on 18 individual congeners generally paralleled the results observed for total PCB. All 18 congeners were significantly reduced by deep frying. Congener Cl{sub 2}(08) also was significantly reduced by either pan frying. Congeners Cl{sub 5}(105) and Cl{sub 5}(118) showed apparent significant increases in concentrations following pan frying. Congeners Cl{sub 5}(105), Cl{sub 5}(118), and C1{sub 6}(138) showed significant increases in concentration following broiling.« less

The molecular origin of a loading-induced black layer in the deep region of articular cartilage at the magic angle

PubMed Central

Wang, Nian; Kahn, David; Badar, Farid; Xia, Yang

2014-01-01

Purpose To investigate the molecular origin of an unusual low-intensity layer in the deep region of articular cartilage as seen in MRI when the tissue is imaged under compression and oriented at the magic angle. Materials and Methods Microscopic MRI (μMRI) T2 and T1ρ experiments were carried out for both native and degraded (treated with trypsin) 18 specimens. The glycosaminoglycan (GAG) concentrations in the specimens were quantified by both sodium ICP-OES and μMRI Gd(DTPA)2--contrast methods. The mechanical modulus of the specimens was also measured. Results Native tissue shows no load-induced layer, while the trypsin-degraded tissue shows clearly the low-intensity line at the deep part of tissue. The GAG reductions are confirmed by the sodium ICP-OES (from 81.7 ± 5.4 mg/ml to 9.2 ± 3.4 mg/ml), MRI GAG quantification (from 72.4 ± 6.7 mg/ml to 11.2 ± 2.9 mg/ml). The modulus reduction is confirmed by biomechanics (from 4.3 ± 0.7 MPa to 0.3 ± 0.1 MPa). Conclusion Both T2 and T1ρ profiles in native and degraded cartilage show strongly strain-, depth-, and angle-dependent using high resolution MRI. The GAG reduction is responsible for the visualization of a low-intensity layer in deep cartilage when it is loaded and orientated at 55°. PMID:24833266

Effects of peripheral cooling on intention tremor in multiple sclerosis

PubMed Central

Feys, P; Helsen, W; Liu, X; Mooren, D; Albrecht, H; Nuttin, B; Ketelaer, P

2005-01-01

Objective: To investigate the effect of peripheral sustained cooling on intention tremor in patients with multiple sclerosis (MS). MS induced upper limb intention tremor affects many functional activities and is extremely difficult to treat. Materials/Methods: Deep (18°C) and moderate (25°C) cooling interventions were applied for 15 minutes to 23 and 11 tremor arms of patients with MS, respectively. Deep and moderate cooling reduced skin temperature at the elbow by 13.5°C and 7°C, respectively. Evaluations of physiological variables, the finger tapping test, and a wrist step tracking task were performed before and up to 30 minutes after cooling. Results: The heart rate and the central body temperature remained unchanged throughout. Both cooling interventions reduced overall tremor amplitude and frequency proportional to cooling intensity. Tremor reduction persisted during the 30 minute post cooling evaluation period. Nerve conduction velocity was decreased after deep cooling, but this does not fully explain the reduction in tremor amplitude or the effects of moderate cooling. Cooling did not substantially hamper voluntary movement control required for accurate performance of the step tracking task. However, changes in the mechanical properties of muscles may have contributed to the tremor amplitude reduction. Conclusions: Cooling induced tremor reduction is probably caused by a combination of decreased nerve conduction velocity, changed muscle properties, and reduced muscle spindle activity. Tremor reduction is thought to relate to decreased long loop stretch reflexes, because muscle spindle discharge is temperature dependent. These findings are clinically important because applying peripheral cooling might enable patients to perform functional activities more efficiently. PMID:15716530

Fundamental Characteristics of Deep-UV Light-Emitting Diodes and Their Application To Control Foodborne Pathogens.

PubMed

Shin, Joo-Yeon; Kim, Soo-Ji; Kim, Do-Kyun; Kang, Dong-Hyun

2016-01-01

Low-pressure mercury UV (LP-UV) lamps have long been used for bacterial inactivation, but due to certain disadvantages, such as the possibility of mercury leakage, deep-UV-C light-emitting diodes (DUV-LEDs) for disinfection have recently been of great interest as an alternative. Therefore, in this study, we examined the basic spectral properties of DUV-LEDs and the effects of UV-C irradiation for inactivating foodborne pathogens, including Escherichia coli O157:H7, Salmonella enterica serovar Typhimurium, and Listeria monocytogenes, on solid media, as well as in water. As the temperature increased, DUV-LED light intensity decreased slightly, whereas LP-UV lamps showed increasing intensity until they reached a peak at around 30°C. As the irradiation dosage and temperature increased, E. coli O157:H7 and S. Typhimurium experienced 5- to 6-log-unit reductions. L. monocytogenes was reduced by over 5 log units at a dose of 1.67 mJ/cm(2). At 90% relative humidity (RH), only E. coli O157:H7 experienced inactivation significantly greater than at 30 and 60% RH. In a water treatment study involving a continuous system, 6.38-, 5.81-, and 3.47-log-unit reductions were achieved in E. coli O157:H7, S. Typhimurium, and L. monocytogenes, respectively, at 0.5 liter per minute (LPM) and 200 mW output power. The results of this study suggest that the use of DUV-LEDs may compensate for the drawbacks of using LP-UV lamps to inactivate foodborne pathogens. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Global Lunar Topography from the Deep Space Gateway for Science and Exploration

NASA Astrophysics Data System (ADS)

Archinal, B.; Gaddis, L.; Kirk, R.; Edmundson, K.; Stone, T.; Portree, D.; Keszthelyi, L.

2018-02-01

The Deep Space Gateway, in low lunar orbit, could be used to achieve a long standing goal of lunar science, collecting stereo images in two months to make a complete, uniform, high resolution, known accuracy, global topographic model of the Moon.

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.

Sensitivity of simulated deep ocean natural radiocarbon to gas exchange velocity and historical atmospheric Δ14C variations

NASA Astrophysics Data System (ADS)

Wagner, Hannes; Koeve, Wolfgang; Kriest, Iris; Oschlies, Andreas

2015-04-01

Simulated deep ocean natural radiocarbon is frequently used to assess model performance of deep ocean ventilation in Ocean General Circulation Models (OGCMs). It has been shown to be sensitive to a variety of model parameters, such as the mixing parameterization, convection scheme and vertical resolution. Here we use three different ocean models (MIT2.8, ECCO, UVic) to evaluate the sensitivity of simulated deep ocean natural radiocarbon to two other factors, while keeping the model physics constant: (1) the gas exchange velocity and (2) historic variations in atmospheric Δ^1^4C boundary conditions. We find that simulated natural Δ^1^4C decreases by 14-20 ‰ throughout the deep ocean and consistently in all three models, if the gas exchange velocity is lowered by 30 % with respect to the OCMIP-2 protocol, to become more consistent with newer estimates of the oceans uptake of bomb derived ^1^4C. Simulated deep ocean natural Δ^1^4C furthermore decreases by 3-9 ‰ throughout the deep Pacific, Indian and Southern Oceans and consistently in all three models, if the models are forced with the observed atmospheric Δ^1^4C history, instead of an often made pragmatic assumption of a constant atmospheric Δ^1^4C value of zero. Applying both improvements (gas exchange reduction, as well as atmospheric Δ^1^4C history implementation) concomitantly and accounting for the present uncertainty in gas exchange velocity estimates (between 10 and 40 % reduction with respect to the OCMIP-2 protocol) simulated deep ocean Δ^1^4C decreases by 10-30 ‰ throughout the deep Pacific, Indian and Southern Ocean. This translates to a ^1^4C-age increase of 100-300 years and indicates, that models, which in former assessments (based on the OCMIP-2 protocol) had been identified to have an accurate deep ocean ventilation, should now be regarded as rather having a bit too sluggish a ventilation. Models, which on the other hand had been identified to have a bit too fast a deep ocean ventilation, should now be regarded as rather having a more accurate ventilation.

Nd-glass laser for deep-penetration welding and hardening

NASA Astrophysics Data System (ADS)

Kayukov, Serguei V.; Yaresko, Sergey I.; Mikheyev, Pavel A.

2000-04-01

Pulsed Nd-glass lasers usually have low beam quality (200 - 300 mm-mrad), and are used only for surface hardening of metals. However, high pulse energy make them feasible for deep penetration welding if their beam quality could be improved. We investigated beam properties of Nd-glass laser with unstable resonator with semitransparent output coupler (URSOC). We had found that beam divergence of the laser with URSOC was an order of magnitude smaller than that of the laser with stable resonator. The achieved beam quality (40 - 50 mm-mrad) permitted to perform deep penetration welding with the aspect ratio of approximately 8. For beam divergence of 3 mrad melt depth of 6.3 mm was achieved with the ratio of depth to pulse energy of 0.27 mm/J.

An analysis and demonstration of clock synchronization by VLBI. [Very Long Baseline Interferometry for Deep Space Net

NASA Technical Reports Server (NTRS)

Hurd, W. J.

1974-01-01

A prototype of a semi-real time system for synchronizing the Deep Space Net station clocks by radio interferometry was successfully demonstrated on August 30, 1972. The system utilized an approximate maximum likelihood estimation procedure for processing the data, thereby achieving essentially optimum time sync estimates for a given amount of data, or equivalently, minimizing the amount of data required for reliable estimation. Synchronization accuracies as good as 100 ns rms were achieved between Deep Space Stations 11 and 12, both at Goldstone, Calif. The accuracy can be improved by increasing the system bandwidth until the fundamental limitations due to baseline and source position uncertainties and atmospheric effects are reached. These limitations are under 10 ns for transcontinental baselines.

Homoacetogenesis in Deep-Sea Chloroflexi, as Inferred by Single-Cell Genomics, Provides a Link to Reductive Dehalogenation in Terrestrial Dehalococcoidetes

PubMed Central

Sewell, Holly L.; Kaster, Anne-Kristin

2017-01-01

ABSTRACT The deep marine subsurface is one of the largest unexplored biospheres on Earth and is widely inhabited by members of the phylum Chloroflexi. In this report, we investigated genomes of single cells obtained from deep-sea sediments of the Peruvian Margin, which are enriched in such Chloroflexi. 16S rRNA gene sequence analysis placed two of these single-cell-derived genomes (DscP3 and Dsc4) in a clade of subphylum I Chloroflexi which were previously recovered from deep-sea sediment in the Okinawa Trough and a third (DscP2-2) as a member of the previously reported DscP2 population from Peruvian Margin site 1230. The presence of genes encoding enzymes of a complete Wood-Ljungdahl pathway, glycolysis/gluconeogenesis, a Rhodobacter nitrogen fixation (Rnf) complex, glyosyltransferases, and formate dehydrogenases in the single-cell genomes of DscP3 and Dsc4 and the presence of an NADH-dependent reduced ferredoxin:NADP oxidoreductase (Nfn) and Rnf in the genome of DscP2-2 imply a homoacetogenic lifestyle of these abundant marine Chloroflexi. We also report here the first complete pathway for anaerobic benzoate oxidation to acetyl coenzyme A (CoA) in the phylum Chloroflexi (DscP3 and Dsc4), including a class I benzoyl-CoA reductase. Of remarkable evolutionary significance, we discovered a gene encoding a formate dehydrogenase (FdnI) with reciprocal closest identity to the formate dehydrogenase-like protein (complex iron-sulfur molybdoenzyme [CISM], DET0187) of terrestrial Dehalococcoides/Dehalogenimonas spp. This formate dehydrogenase-like protein has been shown to lack formate dehydrogenase activity in Dehalococcoides/Dehalogenimonas spp. and is instead hypothesized to couple HupL hydrogenase to a reductive dehalogenase in the catabolic reductive dehalogenation pathway. This finding of a close functional homologue provides an important missing link for understanding the origin and the metabolic core of terrestrial Dehalococcoides/Dehalogenimonas spp. and of reductive dehalogenation, as well as the biology of abundant deep-sea Chloroflexi. PMID:29259088

Derivation of habitat-specific dissolved oxygen criteria for Chesapeake Bay and its tidal tributaries

USGS Publications Warehouse

Batiuk, Richard A.; Breitburg, Denise L.; Diaz, Robert J.; Cronin, Thomas M.; Secor, David H.; Thursby, Glen

2009-01-01

The Chesapeake 2000 Agreement committed its state and federal signatories to “define the water quality conditions necessary to protect aquatic living resources” in the Chesapeake Bay (USA) and its tidal tributaries. Hypoxia is one of the key water quality issues addressed as a result of the above Agreement. This paper summarizes the protection goals and specific criteria intended to achieve those goals for addressing hypoxia. The criteria take into account the variety of Bay habitats and the tendency towards low dissolved oxygen in some areas of the Bay. Stressful dissolved oxygen conditions were characterized for a diverse array of living resources of the Chesapeake Bay by different aquatic habitats: migratory fish spawning and nursery, shallow-water, open-water, deep-water, and deep-channel. The dissolved oxygen criteria derived for each of these habitats are intended to protect against adverse effects on survival, growth, reproduction and behavior. The criteria accommodate both spatial and temporal aspects of low oxygen events, and have been adopted into the Chesapeake Bay states – Maryland, Virginia, and Delaware – and the District of Columbia's water quality standards regulations. These criteria, now in the form of state regulatory standards, are driving an array of land-based and wastewater pollution reduction actions across the six-watershed.

Radiofrequency Lesions through Deep Brain Stimulation Electrodes in Movement Disorders: Case Report and Review of the Literature.

PubMed

Pérez-Suárez, Javier; Torres Díaz, Cristina V; López Manzanares, Lydia; Navas García, Marta; Pastor, Jesús; Barrio Fernández, Patricia; G de Sola, Rafael

2017-01-01

Although there are few reports of radiofrequency lesions performed through deep brain stimulation (DBS) electrodes in patients with movement disorders, experience with this method is scarce. We present 2 patients who had been previously treated with DBS of subthalamic nuclei (STN) and the ventral intermediate (VIM) nucleus of the thalamus for Parkinson's disease and essential tremor, respectively, and underwent a radiofrequency lesion through their DBS electrodes after developing a hardware infection. The authors conduct a review of the literature regarding this method. Both patients had a good clinical outcome after 20 and 8 months, respectively, as assessed by a reduction in Fahn-Tolosa-Marin Scale and Unified Parkinson's Disease Rating Scale scores. The second patient underwent a second DBS system implantation surgery after his radiofrequency treatment to optimize his management, achieving optimal clinical control with lower current and drug requirements than before the radiofrequency intervention. No adverse effects were observed. Radiofrequency lesions through DBS electrodes allow the creation of small and localized lesions. Its effectiveness and low-risk profile, in addition to its low cost, make this procedure suitable and a possible alternative in the therapeutic repertoire for the surgical treatment of movement disorders. © 2017 S. Karger AG, Basel.

[Surgical management of deep infiltrating endometriosis with bowel involvement and urinary tract involvement].

PubMed

Bendifallah, Sofiane; Ballester, Marcos; Darai, Emile

2017-12-01

Endometriosis is a benign pathology that affects 3% of the general population and about 10% of women of reproductive age. Three anatomoclinical entities are described: peritoneal, ovarian (endometrioma) and deep endometriosis characterized by the infiltration of anatomical structures or organs beyond the peritoneum. Laparoscopic surgery should be performed, as this is associated with a reduction in postoperative complications, length of hospitalization and convalescence. Several surgical techniques allow the removal of deep endometriosis with colorectal involvement: rectal shaving, anterior discoid resection, segmental resection. Deep endometriosis surgery with colorectal involvement is a source of postoperative complications: anastomotic fistula, rectovaginal fistula, intestinal occlusion, digestive haemorrhage, urinary fistula, deep pelvic abscess. Involvement of the urinary tract by endometriosis affects approximately 1% of patients with endometriosis. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Reproducible deep-inspiration breath-hold irradiation with forward intensity-modulated radiotherapy for left-sided breast cancer significantly reduces cardiac radiation exposure compared to inverse intensity-modulated radiotherapy.

PubMed

Bolukbasi, Yasemin; Saglam, Yucel; Selek, Ugur; Topkan, Erkan; Kataria, Anglina; Unal, Zeynep; Alpan, Vildan

2014-01-01

To investigate the objective utility of our clinical routine of reproducible deep-inspiration breath-hold irradiation for left-sided breast cancer patients on reducing cardiac exposure. Free-breathing and reproducible deep-inspiration breath-hold scans were evaluated for our 10 consecutive left-sided breast cancer patients treated with reproducible deep-inspiration breath-hold. The study was based on the adjuvant dose of 50 Gy in 25 fractions of 2 Gy/fraction. Both inverse and forward intensity-modulated radiotherapy plans were generated for each computed tomography dataset. Reproducible deep-inspiration breath-hold plans with forward intensity-modulated radiotherapy significantly spared the heart and left anterior descending artery compared to generated free-breathing plans based on mean doses - free-breathing vs reproducible deep-inspiration breath-hold, left ventricle (296.1 vs 94.5 cGy, P = 0.005), right ventricle (158.3 vs 59.2 cGy, P = 0.005), left anterior descending artery (171.1 vs 78.1 cGy, P = 0.005), and whole heart (173.9 vs 66 cGy, P = 0.005), heart V20 (2.2% vs 0%, P = 0.007) and heart V10 (4.2% vs 0.3%, P = 0.007) - whereas they revealed no additional burden on the ipsilateral lung. Reproducible deep-inspiration breath-hold and free-breathing plans with inverse intensity-modulated radiotherapy provided similar organ at risk sparing by reducing the mean doses to the left ventricle, left anterior descending artery, heart, V10-V20 of the heart and right ventricle. However, forward intensity-modulated radiotherapy showed significant reduction in doses to the left ventricle, left anterior descending artery, heart, right ventricle, and contralateral breast (mean dose, 248.9 to 12.3 cGy, P = 0.005). The mean doses for free-breathing vs reproducible deep-inspiration breath-hold of the proximal left anterior descending artery were 1.78 vs 1.08 Gy and of the distal left anterior descending artery were 8.11 vs 3.89 Gy, whereas mean distances to the 50 Gy isodose line of the proximal left anterior descending artery were 6.6 vs 3.3 cm and of the distal left anterior descending artery were 7.4 vs 4.1 cm, with forward intensity-modulated radiotherapy. Overall reduction in mean doses to proximal and distal left anterior descending artery with deep-inspiration breath-hold irradiation was 39% (P = 0.02) and 52% (P = 0.002), respectively. We found a significant reduction of radiation exposure to the contralateral breast, left and right ventricles, as well as of proximal and especially distal left anterior descending artery with the deep-inspiration breath-hold technique with forward intensity-modulated radiotherapy planning.

Single cell genomic study of dehalogenating Chloroflexi from deep sea sediments of Peruvian Margin

NASA Astrophysics Data System (ADS)

Spormann, A.; Kaster, A.; Meyer-Blackwell, K.; Biddle, J.

2012-12-01

Dehalogenating Chloroflexi, such as Dehalococcoidites (Dhc), are members of the rare biosphere of deep sea sediments but were originally discovered as the key microbes mediating reductive dehalogenation of the prevalent groundwater contaminants tetrachloroethene and trichloroethene to ethene. Dhc are slow growing, highly niche adapted microbes that are specialized to organohalide respiration as the sole mode of energy conservation. These strictly anaerobic microbes depend on a supporting microbial community to mitigate electron donor and cofactor requirements among other factors. Molecular and genomic studies on the key enzymes for energy conservation, reductive dehalogenases, have provided evidence for rapid adaptive evolution in terrestrial environments. However, the metabolic life style of Dhc in the absence of anthropogenic contaminants, such as in pristine deep sea sediments, is still unknown. In order to provide fundamental insights into life style, genomic population structure and evolution of Dhc, we analyzed a non-contaminated deep sea sediment sample of the Peru Margin 1230 site collected 6 mbf by a metagenomic and single cell genomic. We present for the first time single cell genomic data on dehalogenating Chloroflexi, a significant microbial population in the poorly understood oligotrophic marine sub-surface environments.

Single cell genomic study of dehalogenating Chloroflexi in deep sea sediments of Peru Margin 1230

NASA Astrophysics Data System (ADS)

Kaster, A.; Meyer-Blackwell, K.; Biddle, J.; Spormann, A.

2012-12-01

Dehalogenating Chloroflexi, such as Dehalococcoidites (Dhc), are members of the rare biosphere of deep sea sediments but were originally discovered as the key microbes mediating reductive dehalogenation of the prevalent groundwater contaminants tetrachloroethene and trichloroethene to ethene. Dhc are slow growing, highly niche adapted microbes that are specialized to organohalide respiration as the sole mode of energy conservation. They are strictly anaerobic microbes that depend on a supporting microbial community for electron donor and cofactor requirements among other factors. Molecular and genomic studies on the key enzymes for energy conservation, reductive dehalogenases, have provided evidence for rapid adaptive evolution in terrestrial environments. However, the metabolic life style of Dhc in the absence of anthropogenic contaminants, such as in pristine deep sea sediments, is still unknown. In order to provide fundamental insights into life style, genomic population structure and evolution of Dhc, we analyzed a non-contaminated deep sea sediment sample of the Peru Margin 1230 site collected 6 mbsf by a metagenomic and single cell genomic approach. We present for the first time single cell genomic data on dehalogenating Chloroflexi, a significant microbial population in the poorly understood oligotrophic marine sub-surface environment.

Prevention of deep vein thrombosis and pulmonary embolism. [/sup 125/I

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

Le Quesne, L.P.

1978-03-01

The development of the /sup 125/I-fibrinogen technic in the diagnosis of postoperative deep vein thrombosis provides a valuable tool for the study of the condition itself and of the efficacy of prophylactic measures. These measures may be divided into two groups: the antistasis regimes and the antithrombotic regimes. Published reports based on the /sup 125/I-fibrinogen technic are critically reviewed. Although many regimes cause a significant diminution in the incidence of isotopically detected deep vein thrombosis, 90% of which are confined to the calf, this does not necessarily imply a similar diminution in the incidence of major pulmonary emboli, most ofmore » which arise from thrombi in the proximal segment of the lower limb veins. The origin of these proximal thrombi, with particular reference to their relationship to calf thrombi, is discussed. The reported studies of the influence of antithrombotic regimes on the incidence of pulmonary embolism are reviewed. It is concluded that a reduction in the incidence of isotopically detected deep vein thrombosis is probably accompanied by a significant reduction in the incidence of major pulmonary embolism, but further studies are required.« less

A novel application of deep learning for single-lead ECG classification.

PubMed

Mathews, Sherin M; Kambhamettu, Chandra; Barner, Kenneth E

2018-06-04

Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with cardiac abnormalities. In this paper, a novel approach based on deep learning methodology is proposed for the classification of single-lead electrocardiogram (ECG) signals. We demonstrate the application of the Restricted Boltzmann Machine (RBM) and deep belief networks (DBN) for ECG classification following detection of ventricular and supraventricular heartbeats using single-lead ECG. The effectiveness of this proposed algorithm is illustrated using real ECG signals from the widely-used MIT-BIH database. Simulation results demonstrate that with a suitable choice of parameters, RBM and DBN can achieve high average recognition accuracies of ventricular ectopic beats (93.63%) and of supraventricular ectopic beats (95.57%) at a low sampling rate of 114 Hz. Experimental results indicate that classifiers built into this deep learning-based framework achieved state-of-the art performance models at lower sampling rates and simple features when compared to traditional methods. Further, employing features extracted at a sampling rate of 114 Hz when combined with deep learning provided enough discriminatory power for the classification task. This performance is comparable to that of traditional methods and uses a much lower sampling rate and simpler features. Thus, our proposed deep neural network algorithm demonstrates that deep learning-based methods offer accurate ECG classification and could potentially be extended to other physiological signal classifications, such as those in arterial blood pressure (ABP), nerve conduction (EMG), and heart rate variability (HRV) studies. Copyright © 2018. Published by Elsevier Ltd.

Reductive dechlorination of chlorinated ethenes under oxidation-reduction conditions and potentiometric surfaces in two trichloroethene-contaminated zones at the Double Eagle and Fourth Street Superfund sites in Oklahoma City, Oklahoma

USGS Publications Warehouse

Braun, Christopher L.

2004-01-01

The Double Eagle Refining Superfund site and the Fourth Street Abandoned Refinery Superfund site are in northeast Oklahoma City, Oklahoma, adjacent to one another. The Double Eagle facility became a Superfund site on the basis of contamination from lead and volatile organic compounds; the Fourth Street facility on the basis of volatile organic compounds, pesticides, and acid-base neutral compounds. The study documented in this report was done to investigate whether reductive dechlorination of chlorinated ethenes under oxidation-reduction conditions is occurring in two zones of the Garber-Wellington aquifer (shallow zone 30–60 to 75 feet below land surface, deep zone 75 to 160 feet below land surface) at the sites; and to construct potentiometric surfaces of the two water-yielding zones to determine the directions of groundwater flow at the sites. The presence in some wells of intermediate products of reductive dechlorination, dichloroethene and vinyl chloride, is an indication that reductive dechlorination of trichloroethene is occurring. Dissolved oxygen concentrations (less than 0.5 milligram per liter) indicate that consumption of dissolved oxygen likely had occurred in the oxygen-reducing microbial process associated with reductive dechlorination. Concentrations of nitrate and nitrite nitrogen (generally less than 2.0 and 0.06 milligrams per liter, respectively) indicate that nitrate reduction probably is not a key process in either aquifer zone. Concentrations of ferrous iron greater than 1.00 milligram per liter in the majority of wells sampled indicate that iron reduction is probable. Concentrations of sulfide less than 0.05 milligram per liter in all wells indicate that sulfate reduction probably is not a key process in either zone. The presence of methane in ground water is an indication of strongly reducing conditions that facilitate reductive dechlorination. Methane was detected in all but one well. In the shallow zone in the eastern part of the study area, ground water flowing from the northwest and south coalesces in a potentiometric trough, then moves westward and ultimately northwestward. In the western part of the study area, ground water in the shallow zone flows northwest. In the deep zone in the eastern part of the study area, ground water generally flows northwestward; and in the western part of the study area, ground water in the deep zone generally flows northward.

Deep brain stimulation, histone deacetylase inhibitors and glutamatergic drugs rescue resistance to fear extinction in a genetic mouse model

PubMed Central

Whittle, Nigel; Schmuckermair, Claudia; Gunduz Cinar, Ozge; Hauschild, Markus; Ferraguti, Francesco; Holmes, Andrew; Singewald, Nicolas

2013-01-01

Anxiety disorders are characterized by persistent, excessive fear. Therapeutic interventions that reverse deficits in fear extinction represent a tractable approach to treating these disorders. We previously reported that 129S1/SvImJ (S1) mice show no extinction learning following normal fear conditioning. We now demonstrate that weak fear conditioning does permit fear reduction during massed extinction training in S1 mice, but reveals specific deficiency in extinction memory consolidation/retrieval. Rescue of this impaired extinction consolidation/retrieval was achieved with d-cycloserine (N-methly-d-aspartate partial agonist) or MS-275 (histone deacetylase (HDAC) inhibitor), applied after extinction training. We next examined the ability of different drugs and non-pharmacological manipulations to rescue the extreme fear extinction deficit in S1 following normal fear conditioning with the ultimate aim to produce low fear levels in extinction retrieval tests. Results showed that deep brain stimulation (DBS) by applying high frequency stimulation to the nucleus accumbens (ventral striatum) during extinction training, indeed significantly reduced fear during extinction retrieval compared to sham stimulation controls. Rescue of both impaired extinction acquisition and deficient extinction consolidation/retrieval was achieved with prior extinction training administration of valproic acid (a GABAergic enhancer and HDAC inhibitor) or AMN082 [metabotropic glutamate receptor 7 (mGlu7) agonist], while MS-275 or PEPA (AMPA receptor potentiator) failed to affect extinction acquisition in S1 mice. Collectively, these data identify potential beneficial effects of DBS and various drug treatments, including those with HDAC inhibiting or mGlu7 agonism properties, as adjuncts to overcome treatment resistance in exposure-based therapies. This article is part of a Special Issue entitled ‘Cognitive Enhancers’. PMID:22722028

Countdown to Drawdown: an initial overview of exponential scaling of potential societal tipping points for deep decarbonization of global energy infrastructure by 2050

NASA Astrophysics Data System (ADS)

McCaffrey, Mark; Bhowmik, Avit

2017-04-01

The 194 signatories to the Paris Agreement range in size from small island nations (Tuvalu, less than 10,000 people) to massive states (India and China, which between them have 2.6 billion people). Their cultural backgrounds, political, economic and social systems vary widely. What they all share is an agreement for climate stabilisation at 1.5-2˚ C. A roadmap outlining potential exponential transitions towards a carbon-free economy may benefit from a logarithmic "powers of ten" framework that sets aside backgrounds and systems to examine the relative population concentration scales-from the individual (100) to local/neighborhood (103) to the national/transnational scales (108) and ultimately the global population of around 10 billion anticipated in 2050 (1010). What are the related targets and indicators for successful engagement at each level for rapid and radical reductions of carbon emissions and concentrations? What are the possible interventions and barriers that may be applied at different levels of population concentration? What "drawdown" strategies are most appropriate for different scales? Could focusing demonstrations of clean energy and sustainable practices on the local/neighborhood to urban scale (103-104) provide a leverage that has not been achieved at more complex national and transnational scales? Ultimately, backgrounds and systems are important factors in the equation, but the "powers of 10" scaling framework may provide a compass to assist in identifying the challenges, opportunities and related thresholds and tipping points for achieving deep decarbonization and transformation of the global energy infrastructure at every level of society over the next thirty-three years.

Automated variance reduction for MCNP using deterministic methods.

PubMed

Sweezy, J; Brown, F; Booth, T; Chiaramonte, J; Preeg, B

2005-01-01

In order to reduce the user's time and the computer time needed to solve deep penetration problems, an automated variance reduction capability has been developed for the MCNP Monte Carlo transport code. This new variance reduction capability developed for MCNP5 employs the PARTISN multigroup discrete ordinates code to generate mesh-based weight windows. The technique of using deterministic methods to generate importance maps has been widely used to increase the efficiency of deep penetration Monte Carlo calculations. The application of this method in MCNP uses the existing mesh-based weight window feature to translate the MCNP geometry into geometry suitable for PARTISN. The adjoint flux, which is calculated with PARTISN, is used to generate mesh-based weight windows for MCNP. Additionally, the MCNP source energy spectrum can be biased based on the adjoint energy spectrum at the source location. This method can also use angle-dependent weight windows.

A comparison of impact force reduction by polymer materials used for mouthguard fabrication.

PubMed

Gawlak, Dominika; Mańka-Malara, Katarzyna; Mierzwińska-Nastalska, Elżbieta; Gieleta, Roman; Kamiński, Tomasz; Łuniewska, Magdalena

2017-01-01

The essential function of mouthguards is protection against the effects of injuries sustained during sports activities. This purpose will be successfully achieved if appropriate materials ensuring sufficient reduction of the injury force are used for mouthguard fabrication. The objective of the study was to investigate the force reduction capability of selected materials as well as to identify which material reduces the impact force to the highest degree. The material for the study were samples of polymers (6 samples in total), obtained during the process of deep pressing (2 samples), flasking (3 samples) and thermal injection (1 sample), which were tested for impact force damping using an impact device - Charpy impact hammer. The control group comprised of the ceramic material samples subjected to the hammer impact. The statistical analysis applied in this study were one-way Welch ANOVA with post-hoc Games-Howell pairwise comparisons. The test materials reduced the impact force of the impact hammer to varying degrees. The greatest damping capability was demonstrated for the following materials: Impak with 1:1 powder-to-liquid weight ratio polymerized with the conventional flasking technique, and Corflex Orthodontic used in the thermal injection technique of mouthguard fabrication. Impak with 1:1 weight ratio and Corflex Orthodontic should be recommended for the fabrication of mouthguards since they demonstrated the most advantageous damping properties.

Highly Stable and Tunable Chemical Doping of Multilayer WS2 Field Effect Transistor: Reduction in Contact Resistance.

PubMed

Khalil, Hafiz M W; Khan, Muhammad Farooq; Eom, Jonghwa; Noh, Hwayong

2015-10-28

The development of low resistance contacts to 2D transition-metal dichalcogenides (TMDs) is still a big challenge for the future generation field effect transistors (FETs) and optoelectronic devices. Here, we report a chemical doping technique to achieve low contact resistance by keeping the intrinsic properties of few layers WS2. The transfer length method has been used to investigate the effect of chemical doping on contact resistance. After doping, the contact resistance (Rc) of multilayer (ML) WS2 has been reduced to 0.9 kΩ·μm. The significant reduction of the Rc is mainly due to the high electron doping density, thus a reduction in Schottky barrier height, which limits the device performance. The threshold voltage of ML-WS2 FETs confirms a negative shift upon the chemical doping, as further confirmed from the positions of E(1)2g and A1g peaks in Raman spectra. The n-doped samples possess a high drain current of 65 μA/μm, with an on/off ratio of 1.05 × 10(6) and a field effect mobility of 34.7 cm(2)/(V·s) at room temperature. Furthermore, the photoelectric properties of doped WS2 flakes were also measured under deep ultraviolet light. The potential of using LiF doping in contact engineering of TMDs opens new ways to improve the device performance.

Depth of Information Processing and Memory for Medical Facts.

ERIC Educational Resources Information Center

Slade, Peter D.; Onion, Carl W. R.

1995-01-01

The current emphasis in medical education is on engaging learners in deep processing of information to achieve better understanding of the subject matter. Traditional approaches aimed for memorization of medical facts; however, a good memory for medical facts is still essential in clinical practice. This study demonstrates that deep information…

VUV lithography

DOEpatents

George, E.V.; Oster, Y.; Mundinger, D.C.

1990-12-25

Deep UV projection lithography can be performed using an e-beam pumped solid excimer UV source, a mask, and a UV reduction camera. The UV source produces deep UV radiation in the range 1,700--1,300A using xenon, krypton or argon; shorter wavelengths of 850--650A can be obtained using neon or helium. A thin solid layer of the gas is formed on a cryogenically cooled plate and bombarded with an e-beam to cause fluorescence. The UV reduction camera utilizes multilayer mirrors having high reflectivity at the UV wavelength and images the mask onto a resist coated substrate at a preselected demagnification. The mask can be formed integrally with the source as an emitting mask. 6 figs.

40 CFR 440.33 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 440.33 Section 440.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... reduction attainable by the application of the best available technology economically achievable (BAT... reduction attainable by the application of the best available technology economically achievable (BAT): (a...

Assessment of MCRM Boost Assist from Orbit for Deep Space Missions

NASA Technical Reports Server (NTRS)

2000-01-01

Report provides results of analysis for the beamed energy driven MHD Chemical Rocket Motor (MCRM) for application to boost from orbit to escape for deep space and interplanetary missions. Parametric analyses were performed in the mission to determine operating regime for which the MCRM provides significant propulsion performance enhancement. Analysis of the MHD accelerator was performed numerical computational methods to determine design and operational features necessary to achieve Isp on the order of 2,000 to 3,000 seconds. Algorithms were developed to scale weights for the accelerator and power supply. Significant improvement in propulsion system performance can be achieved with the beamed energy driven MCRM. The limiting factor on achievable vehicle acceleration is the specific power of the rectenna.

Persistent staphylococcal bacteremia in an intravenous drug abuser.

PubMed

Barg, N L; Supena, R B; Fekety, R

1986-02-01

A patient with methicillin-resistant Staphylococcus aureus bacteremia received vancomycin (MIC = 0.8 microgram/ml, MBC = 15 micrograms/ml) and heparin simultaneously through the same intravenous line to treat a septic deep venous thrombosis. Bacteremia persisted for 7 days. Bacteremia terminated when the simultaneous infusion of heparin and vancomycin through the same line was stopped. This suggested that an interaction between vancomycin and heparin may have occurred, which resulted in a reduction in vancomycin activity. To test for such an interaction, mixtures of heparin and vancomycin in various concentrations were made and tested for antimicrobial activity against the organisms in the patient. A precipitate formed at the concentrations achieved in the intravenous lines, and when the vancomycin concentrations were measured by bioassay, a 50 to 60% reduction in activity was noted. In contrast, when these solutions were prepared and mixed at microgram concentrations, a precipitate was no longer observed, and antimicrobial activity was not reduced. Heparin appeared to interact unfavorably with vancomycin at the concentrations in the intravenous lines when these drugs were administered simultaneously to patients. This may be the cause of poor therapeutic responses to vancomycin in some patients, especially those infected with tolerant organisms.

Deep kernel learning method for SAR image target recognition

NASA Astrophysics Data System (ADS)

Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

2017-10-01

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

How to improve healthcare? Identify, nurture and embed individuals and teams with "deep smarts".

PubMed

Eljiz, Kathy; Greenfield, David; Molineux, John; Sloan, Terry

2018-03-19

Purpose Unlocking and transferring skills and capabilities in individuals to the teams they work within, and across, is the key to positive organisational development and improved patient care. Using the "deep smarts" model, the purpose of this paper is to examine these issues. Design/methodology/approach The "deep smarts" model is described, reviewed and proposed as a way of transferring knowledge and capabilities within healthcare organisations. Findings Effective healthcare delivery is achieved through, and continues to require, integrative care involving numerous, dispersed service providers. In the space of overlapping organisational boundaries, there is a need for "deep smarts" people who act as "boundary spanners". These are critical integrative, networking roles employing clinical, organisational and people skills across multiple settings. Research limitations/implications Studies evaluating the barriers and enablers to the application of the deep smarts model and 13 knowledge development strategies proposed are required. Such future research will empirically and contemporary ground our understanding of organisational development in modern complex healthcare settings. Practical implications An organisation with "deep smarts" people - in managerial, auxiliary and clinical positions - has a greater capacity for integration and achieving improved patient-centred care. Originality/value In total, 13 developmental strategies, to transfer individual capabilities into organisational capability, are proposed. These strategies are applicable to different contexts and challenges faced by individuals and teams in complex healthcare organisations.

Realization of Chinese word segmentation based on deep learning method

NASA Astrophysics Data System (ADS)

Wang, Xuefei; Wang, Mingjiang; Zhang, Qiquan

2017-08-01

In recent years, with the rapid development of deep learning, it has been widely used in the field of natural language processing. In this paper, I use the method of deep learning to achieve Chinese word segmentation, with large-scale corpus, eliminating the need to construct additional manual characteristics. In the process of Chinese word segmentation, the first step is to deal with the corpus, use word2vec to get word embedding of the corpus, each character is 50. After the word is embedded, the word embedding feature is fed to the bidirectional LSTM, add a linear layer to the hidden layer of the output, and then add a CRF to get the model implemented in this paper. Experimental results show that the method used in the 2014 People's Daily corpus to achieve a satisfactory accuracy.

Preliminary evidence for validity of the Bahasa Indonesian version of Study Process Questionnaire.

PubMed

Liem, Arief Darmanegara; Prasetya, Paulus Hidajat

2007-02-01

This study provides preliminary evidence for the validity of the Bahasa Indonesian version of the Study Process Questionnaire (BI-SPQ) from a sample of 147 psychology students (22 men and 125 women; M age = 21.8 yr., SD = 1.3). The internal consistency alpha of the BI-SPQ subscales were found to range from .46 (Surface Strategy) to .77 (Deep Strategy), with a median of .67. Principal component analysis indicated a two-factor solution, where the Deep and Achieving subscales loaded onto Factor 1 and the Surface subscales loaded on Factor 2. Students' GPAs were associated negatively with Surface Motive (r = -.24) and were associated positively with Deep and Achieving Motives (rs = .20). Further studies with larger samples involving students majoring in other disciplines are needed to provide further evidence of the validity of the BI-SPQ.

Morningness-eveningness preferences, learning approach and academic achievement of undergraduate medical students.

PubMed

Akram, Nimra; Khan, Naheed; Ameen, Mehreen; Mahmood, Shahmeera; Shamim, Komal; Amin, Marium; Rana, Qurrat Ul Ain

2018-05-15

Several studies have focused on determining the effect of chronotype and learning approach on academic achievement separately indicating that morning types have an academic advantage over the evening types and so have the deep learners over the surface learners. But, surprisingly none have assessed the possible relationship between chronotype and learning approach. So, the current study aimed to evaluate this association and their individual influence on academic performance as indicated by the Cumulative Grade Point Average (CGPA) as well as the effect of their interaction on academic performance. The study included 345 undergraduate medical students who responded to reduced Morningness-Eveningness Questionnaire and Biggs Revised Two-Factor Study Process Questionnaire. Morning types indulged in deep learning while evening types in surface learning. Morning and evening types did not differ on academic performance but deep learners had better academic outcomes than their counterparts. The interaction between chronotype and learning approach was significant on determining academic achievement. Our findings gave the impression that chronotype could have an impact on academic performance not directly but indirectly through learning approaches.

Optimisation of insect cell growth in deep-well blocks: development of a high-throughput insect cell expression screen.

PubMed

Bahia, Daljit; Cheung, Robert; Buchs, Mirjam; Geisse, Sabine; Hunt, Ian

2005-01-01

This report describes a method to culture insects cells in 24 deep-well blocks for the routine small-scale optimisation of baculovirus-mediated protein expression experiments. Miniaturisation of this process provides the necessary reduction in terms of resource allocation, reagents, and labour to allow extensive and rapid optimisation of expression conditions, with the concomitant reduction in lead-time before commencement of large-scale bioreactor experiments. This therefore greatly simplifies the optimisation process and allows the use of liquid handling robotics in much of the initial optimisation stages of the process, thereby greatly increasing the throughput of the laboratory. We present several examples of the use of deep-well block expression studies in the optimisation of therapeutically relevant protein targets. We also discuss how the enhanced throughput offered by this approach can be adapted to robotic handling systems and the implications this has on the capacity to conduct multi-parallel protein expression studies.

The Impact of the Aerosol Direct Radiative Forcing on Deep Convection and Air Quality in the Pearl River Delta Region

NASA Astrophysics Data System (ADS)

Liu, Z.; Yim, Steve H. L.; Wang, C.; Lau, N. C.

2018-05-01

Literature has reported the remarkable aerosol impact on low-level cloud by direct radiative forcing (DRF). Impacts on middle-upper troposphere cloud are not yet fully understood, even though this knowledge is important for regions with a large spatial heterogeneity of emissions and aerosol concentration. We assess the aerosol DRF and its cloud response in June (with strong convection) in Pearl River Delta region for 2008-2012 at cloud-resolving scale using an air quality-climate coupled model. Aerosols suppress deep convection by increasing atmospheric stability leading to less evaporation from the ground. The relative humidity is reduced in middle-upper troposphere due to induced reduction in both evaporation from the ground and upward motion. The cloud reduction offsets 20% of the aerosol DRF. The weaker vertical mixing further increases surface aerosol concentration by up to 2.90 μg/m3. These findings indicate the aerosol DRF impact on deep convection and in turn regional air quality.

Comparative Single-Cell Genomics of Chloroflexi from the Okinawa Trough Deep-Subsurface Biosphere.

PubMed

Fullerton, Heather; Moyer, Craig L

2016-05-15

Chloroflexi small-subunit (SSU) rRNA gene sequences are frequently recovered from subseafloor environments, but the metabolic potential of the phylum is poorly understood. The phylum Chloroflexi is represented by isolates with diverse metabolic strategies, including anoxic phototrophy, fermentation, and reductive dehalogenation; therefore, function cannot be attributed to these organisms based solely on phylogeny. Single-cell genomics can provide metabolic insights into uncultured organisms, like the deep-subsurface Chloroflexi Nine SSU rRNA gene sequences were identified from single-cell sorts of whole-round core material collected from the Okinawa Trough at Iheya North hydrothermal field as part of Integrated Ocean Drilling Program (IODP) expedition 331 (Deep Hot Biosphere). Previous studies of subsurface Chloroflexi single amplified genomes (SAGs) suggested heterotrophic or lithotrophic metabolisms and provided no evidence for growth by reductive dehalogenation. Our nine Chloroflexi SAGs (seven of which are from the order Anaerolineales) indicate that, in addition to genes for the Wood-Ljungdahl pathway, exogenous carbon sources can be actively transported into cells. At least one subunit for pyruvate ferredoxin oxidoreductase was found in four of the Chloroflexi SAGs. This protein can provide a link between the Wood-Ljungdahl pathway and other carbon anabolic pathways. Finally, one of the seven Anaerolineales SAGs contains a distinct reductive dehalogenase homologous (rdhA) gene. Through the use of single amplified genomes (SAGs), we have extended the metabolic potential of an understudied group of subsurface microbes, the Chloroflexi These microbes are frequently detected in the subsurface biosphere, though their metabolic capabilities have remained elusive. In contrast to previously examined Chloroflexi SAGs, our genomes (several are from the order Anaerolineales) were recovered from a hydrothermally driven system and therefore provide a unique window into the metabolic potential of this type of habitat. In addition, a reductive dehalogenase gene (rdhA) has been directly linked to marine subsurface Chloroflexi, suggesting that reductive dehalogenation is not limited to the class Dehalococcoidia This discovery expands the nutrient-cycling and metabolic potential present within the deep subsurface and provides functional gene information relating to this enigmatic group. Copyright © 2016 Fullerton and Moyer.

Survival and transfer of murine norovirus 1, a surrogate for human noroviruses, during the production process of deep-frozen onions and spinach.

PubMed

Baert, Leen; Uyttendaele, Mieke; Vermeersch, Mattias; Van Coillie, Els; Debevere, Johan

2008-08-01

The reduction of murine norovirus 1 (MNV-1) on onions and spinach by washing was investigated as was the risk of contamination during the washing procedure. To decontaminate wash water, the industrial sanitizer peracetic acid (PAA) was added to the water, and the survival of MNV-1 was determined. In contrast to onions, spinach undergoes a heat treatment before freezing. Therefore, the resistance of MNV-1 to blanching of spinach was examined. MNV-1 genomic copies were detected with a real-time reverse transcription PCR assay in PAA-treated water and blanched spinach, and PFUs (representing infectious MNV-1 units) were determined with a plaque assay. A < or = 1-log reduction in MNV-1 PFUs was achieved by washing onion bulbs and spinach leaves. More than 3 log PFU of MNV-1 was transmitted to onion bulbs and spinach leaves when these vegetables were washed in water containing approximately 5 log PFU/ml. No decline of MNV-1 occurred in used industrial spinach wash water after 6 days at room temperature. A concentration of 20 ppm of PAA in demineralized water (pH 4.13) and in potable water (pH 7.70) resulted in reductions of 2.88 +/- 0.25 and 2.41 +/- 0.18 log PFU, respectively, after 5 min of exposure, but no decrease in number of genomic copies was observed. No reduction of MNV-1 PFUs was observed on frozen onions or spinach during storage for 6 months. Blanching spinach (80 degrees C for 1 min) resulted in at least 2.44-log reductions of infectious MNV-1, but many genomic copies were still present.

Biogeochemical Signals from Deep Microbial Life in Terrestrial Crust

PubMed Central

Fukuda, Akari; Komatsu, Daisuke D.; Hirota, Akinari; Watanabe, Katsuaki; Togo, Yoko; Morikawa, Noritoshi; Hagiwara, Hiroki; Aosai, Daisuke; Iwatsuki, Teruki; Tsunogai, Urumu; Nagao, Seiya; Ito, Kazumasa; Mizuno, Takashi

2014-01-01

In contrast to the deep subseafloor biosphere, a volumetrically vast and stable habitat for microbial life in the terrestrial crust remains poorly explored. For the long-term sustainability of a crustal biome, high-energy fluxes derived from hydrothermal circulation and water radiolysis in uranium-enriched rocks are seemingly essential. However, the crustal habitability depending on a low supply of energy is unknown. We present multi-isotopic evidence of microbially mediated sulfate reduction in a granitic aquifer, a representative of the terrestrial crust habitat. Deep meteoric groundwater was collected from underground boreholes drilled into Cretaceous Toki granite (central Japan). A large sulfur isotopic fractionation of 20–60‰ diagnostic to microbial sulfate reduction is associated with the investigated groundwater containing sulfate below 0.2 mM. In contrast, a small carbon isotopic fractionation (<30‰) is not indicative of methanogenesis. Except for 2011, the concentrations of H2 ranged mostly from 1 to 5 nM, which is also consistent with an aquifer where a terminal electron accepting process is dominantly controlled by ongoing sulfate reduction. High isotopic ratios of mantle-derived 3He relative to radiogenic 4He in groundwater and the flux of H2 along adjacent faults suggest that, in addition to low concentrations of organic matter (<70 µM), H2 from deeper sources might partly fuel metabolic activities. Our results demonstrate that the deep biosphere in the terrestrial crust is metabolically active and playing a crucial role in the formation of reducing groundwater even under low-energy fluxes. PMID:25517230

CO2 storage capacity estimation: Methodology and gaps

USGS Publications Warehouse

Bachu, S.; Bonijoly, D.; Bradshaw, J.; Burruss, R.; Holloway, S.; Christensen, N.P.; Mathiassen, O.M.

2007-01-01

Implementation of CO2 capture and geological storage (CCGS) technology at the scale needed to achieve a significant and meaningful reduction in CO2 emissions requires knowledge of the available CO2 storage capacity. CO2 storage capacity assessments may be conducted at various scales-in decreasing order of size and increasing order of resolution: country, basin, regional, local and site-specific. Estimation of the CO2 storage capacity in depleted oil and gas reservoirs is straightforward and is based on recoverable reserves, reservoir properties and in situ CO2 characteristics. In the case of CO2-EOR, the CO2 storage capacity can be roughly evaluated on the basis of worldwide field experience or more accurately through numerical simulations. Determination of the theoretical CO2 storage capacity in coal beds is based on coal thickness and CO2 adsorption isotherms, and recovery and completion factors. Evaluation of the CO2 storage capacity in deep saline aquifers is very complex because four trapping mechanisms that act at different rates are involved and, at times, all mechanisms may be operating simultaneously. The level of detail and resolution required in the data make reliable and accurate estimation of CO2 storage capacity in deep saline aquifers practical only at the local and site-specific scales. This paper follows a previous one on issues and development of standards for CO2 storage capacity estimation, and provides a clear set of definitions and methodologies for the assessment of CO2 storage capacity in geological media. Notwithstanding the defined methodologies suggested for estimating CO2 storage capacity, major challenges lie ahead because of lack of data, particularly for coal beds and deep saline aquifers, lack of knowledge about the coefficients that reduce storage capacity from theoretical to effective and to practical, and lack of knowledge about the interplay between various trapping mechanisms at work in deep saline aquifers. ?? 2007 Elsevier Ltd. All rights reserved.

Phase dependent modulation of tremor amplitude in essential tremor through thalamic stimulation

PubMed Central

Cagnan, Hayriye; Brittain, John-Stuart; Little, Simon; Foltynie, Thomas; Limousin, Patricia; Zrinzo, Ludvic; Hariz, Marwan; Joint, Carole; Fitzgerald, James; Green, Alexander L.; Aziz, Tipu

2013-01-01

High frequency deep brain stimulation of the thalamus can help ameliorate severe essential tremor. Here we explore how the efficacy, efficiency and selectivity of thalamic deep brain stimulation might be improved in this condition. We started from the hypothesis that the effects of electrical stimulation on essential tremor may be phase dependent, and that, in particular, there are tremor phases at which stimuli preferentially lead to a reduction in the amplitude of tremor. The latter could be exploited to improve deep brain stimulation, particularly if tremor suppression could be reinforced by cumulative effects. Accordingly, we stimulated 10 patients with essential tremor and thalamic electrodes, while recording tremor amplitude and phase. Stimulation near the postural tremor frequency entrained tremor. Tremor amplitude was also modulated depending on the phase at which stimulation pulses were delivered in the tremor cycle. Stimuli in one half of the tremor cycle reduced median tremor amplitude by ∼10%, while those in the opposite half of the tremor cycle increased tremor amplitude by a similar amount. At optimal phase alignment tremor suppression reached 27%. Moreover, tremor amplitude showed a non-linear increase in the degree of suppression with successive stimuli; tremor suppression was increased threefold if a stimulus was preceded by four stimuli with a similar phase relationship with respect to the tremor, suggesting cumulative, possibly plastic, effects. The present results pave the way for a stimulation system that tracks tremor phase to control when deep brain stimulation pulses are delivered to treat essential tremor. This would allow treatment effects to be maximized by focussing stimulation on the optimal phase for suppression and by ensuring that this is repeated over many cycles so as to harness cumulative effects. Such a system might potentially achieve tremor control with far less power demand and greater specificity than current high frequency stimulation approaches, and may lower the risk for tolerance and rebound. PMID:24038075

30 CFR 203.45 - If I drill a certified unsuccessful well, what royalty relief will my lease earn?

Code of Federal Regulations, 2011 CFR

2011-07-01

... REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Deep Gas Wells on Leases Not Subject to Deep Water Royalty Relief § 203.45 If I drill a certified unsuccessful well, what... 30 Mineral Resources 2 2011-07-01 2011-07-01 false If I drill a certified unsuccessful well, what...

30 CFR 203.32 - What other requirements or restrictions apply to royalty relief for a qualified phase 2 or phase...

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra-Deep Wells on Leases Not Subject to Deep Water Royalty Relief § 203.32 What... (either an original well or a sidetrack) drilled across a lease line, then either: (1) The lease with the...

Dental treatment in patients with severe gag reflex using propofol-remifentanil intravenous sedation

PubMed Central

Shin, Sooil

2017-01-01

Patients with severe gag reflex (SGR) have difficulty getting the treatment they require in local clinics, and many tend to postpone the start of their treatment. To address this problem, dentists have used behavioral techniques and/or pharmacological techniques for treatment. Among the pharmacological methods available, propofol IV sedation is preferred over general anesthesia because it is a simpler procedure. Propofol in combination with remifentanil is characterized by stable sedative effects and quick recovery, leading to a deep sedation. Remifentanil acts to reduce the pain caused by lipid-soluble propofol on injection. The synergistic effects of propofol-remifentanil include reduction in the total amount of drug required to achieve a desired sedation level and anti-emetic effects. In this case report, we outline how the use of propofol-remifentanil IV sedation enabled us to successfully complete a wide range of dental treatments in a patient with SGR. PMID:28879331

The Keys to Successful Extended Missions

NASA Technical Reports Server (NTRS)

Seal, David A.; Manor-Chapman, Emily A.

2012-01-01

Many of NASA's successful missions of robotic exploration have gone on to highly productive mission extensions, from Voyager, Magellan, Ulysses, and Galileo, to the Mars Exploration Rovers Spirit and Opportunity, a variety of Mars orbiters, Spitzer, Deep Impact / EPOXI, and Cassini. These missions delivered not only a high science return during their prime science phase, but a wealth of opportunities during their extensions at a low incremental cost to the program. The success of such mission extensions can be traced to demonstration of new and unique science achievable during the extension; reduction in cost without significant increase in risk to spacecraft health; close inclusion of the science community and approval authorities in planning; intelligent design during the development and prime operations phase; and well crafted and conveyed extension proposals. This paper discusses lessons learned collected from a variety of project leaders which can be applied by current and future missions to maximize their chances of approval and success.

3D Reconfigurable MPSoC for Unmanned Spacecraft Navigation

NASA Astrophysics Data System (ADS)

Dekoulis, George

2016-07-01

This paper describes the design of a new lightweight spacecraft navigation system for unmanned space missions. The system addresses the demands for more efficient autonomous navigation in the near-Earth environment or deep space. The proposed instrumentation is directly suitable for unmanned systems operation and testing of new airborne prototypes for remote sensing applications. The system features a new sensor technology and significant improvements over existing solutions. Fluxgate type sensors have been traditionally used in unmanned defense systems such as target drones, guided missiles, rockets and satellites, however, the guidance sensors' configurations exhibit lower specifications than the presented solution. The current implementation is based on a recently developed material in a reengineered optimum sensor configuration for unprecedented low-power consumption. The new sensor's performance characteristics qualify it for spacecraft navigation applications. A major advantage of the system is the efficiency in redundancy reduction achieved in terms of both hardware and software requirements.

Treatment effectiveness of brain-computer interface training for patients with focal hand dystonia: A double-case study.

PubMed

Hashimoto, Yasunari; Ota, Tetsuo; Mukaino, Masahiko; Ushiba, Junichi

2013-01-01

Neuronal mechanism underlying dystonia is poorly understood. Dystonia can be treated with botulinum toxin injections or deep brain stimulation but these methods are not available for every patient therefore we need to consider other methods Our study aimed to develop a novel rehabilitation training using brain-computer interface system that decreases neural overexcitation in the sensorimotor cortex by bypassing brain and external world without the normal neuromuscular pathway. To achieve this purpose, we recorded electroencephalograms (10 channels) and forearm electromyograms (3 channels) from 2 patients with the diagnosis of writer's cramp and healthy control participants as a preliminary experiment. The patients were trained to control amplitude of their electroencephalographic signal using feedback from the brain-computer interface for 1 hour a day and then continued the training twice a month. After the 5-month training, a patient clearly showed reduction of dystonic movement during writing.

Propulsion and Cryogenics Advanced Development (PCAD) Project Propulsion Technologies for the Lunar Lander

NASA Technical Reports Server (NTRS)

Klem, Mark D.; Smith, Timothy D.

2008-01-01

The Propulsion and Cryogenics Advanced Development (PCAD) Project in the Exploration Technology Development Program is developing technologies as risk mitigation for Orion and the Lunar Lander. An integrated main and reaction control propulsion system has been identified as a candidate for the Lunar Lander Ascent Module. The propellants used in this integrated system are Liquid Oxygen (LOX)/Liquid Methane (LCH4) propellants. A deep throttle pump fed Liquid Oxygen (LOX)/Liquid Hydrogen (LH2) engine system has been identified for the Lunar Lander Descent Vehicle. The propellant combination and architecture of these propulsion systems are novel and would require risk reduction prior to detailed design and development. The PCAD Project addresses the technology requirements to obtain relevant and necessary test data to further the technology maturity of propulsion hardware utilizing these propellants. This plan and achievements to date will be presented.

Dental treatment in patients with severe gag reflex using propofol-remifentanil intravenous sedation.

PubMed

Shin, Sooil; Kim, Seungoh

2017-03-01

Patients with severe gag reflex (SGR) have difficulty getting the treatment they require in local clinics, and many tend to postpone the start of their treatment. To address this problem, dentists have used behavioral techniques and/or pharmacological techniques for treatment. Among the pharmacological methods available, propofol IV sedation is preferred over general anesthesia because it is a simpler procedure. Propofol in combination with remifentanil is characterized by stable sedative effects and quick recovery, leading to a deep sedation. Remifentanil acts to reduce the pain caused by lipid-soluble propofol on injection. The synergistic effects of propofol-remifentanil include reduction in the total amount of drug required to achieve a desired sedation level and anti-emetic effects. In this case report, we outline how the use of propofol-remifentanil IV sedation enabled us to successfully complete a wide range of dental treatments in a patient with SGR.

Technology Requirements For a Square-Meter, Arcsecond-Resolution Telescope for X-Rays: The SMART-X Mission

NASA Technical Reports Server (NTRS)

Schwartz, Daniel A.; Allured, Ryan; Bookbinder, Jay; Cotroneo, Vincenzo; Forman, William; Freeman, Mark; McMuldroch, Stuart; Reid, Paul; Tananbaum, Harvey; Vikhlinin, Alexey;

Deep Knowledge: A Strategy for University Budgetary Cuts

ERIC Educational Resources Information Center

Reynolds, Douglas B.

2016-01-01

During and after the Financial Crisis of 2008, many institutions of higher learning have had revenue and budgetary reductions, forcing them to make severe university budget cuts and university reductions in force. Often the university cuts are preceded by a process of evaluation of academic programs where institutions determine what they stand for…

New coding advances for deep space communications

NASA Technical Reports Server (NTRS)

Yuen, Joseph H.

1987-01-01

Advances made in error-correction coding for deep space communications are described. The code believed to be the best is a (15, 1/6) convolutional code, with maximum likelihood decoding; when it is concatenated with a 10-bit Reed-Solomon code, it achieves a bit error rate of 10 to the -6th, at a bit SNR of 0.42 dB. This code outperforms the Voyager code by 2.11 dB. The use of source statics in decoding convolutionally encoded Voyager images from the Uranus encounter is investigated, and it is found that a 2 dB decoding gain can be achieved.

Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.

PubMed

Sun, Wenqing; Zheng, Bin; Qian, Wei

2017-10-01

This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand-crafted features. All of the 1018 cases were acquired from Lung Image Database Consortium (LIDC) public lung cancer database. The nodules were segmented according to four radiologists' markings, and 13,668 samples were generated by rotating every slice of nodule images. Three multichannel ROI based deep structured algorithms were designed and implemented in this study: convolutional neural network (CNN), deep belief network (DBN), and stacked denoising autoencoder (SDAE). For the comparison purpose, we also implemented a CADx system using hand-crafted features including density features, texture features and morphological features. The performance of every scheme was evaluated by using a 10-fold cross-validation method and an assessment index of the area under the receiver operating characteristic curve (AUC). The observed highest area under the curve (AUC) was 0.899±0.018 achieved by CNN, which was significantly higher than traditional CADx with the AUC=0.848±0.026. The results from DBN was also slightly higher than CADx, while SDAE was slightly lower. By visualizing the automatic generated features, we found some meaningful detectors like curvy stroke detectors from deep structured schemes. The study results showed the deep structured algorithms with automatically generated features can achieve desirable performance in lung nodule diagnosis. With well-tuned parameters and large enough dataset, the deep learning algorithms can have better performance than current popular CADx. We believe the deep learning algorithms with similar data preprocessing procedure can be used in other medical image analysis areas as well. Copyright © 2017. Published by Elsevier Ltd.

To Master or Perform? Exploring Relations between Achievement Goals and Conceptual Change Learning

ERIC Educational Resources Information Center

Ranellucci, John; Muis, Krista R.; Duffy, Melissa; Wang, Xihui; Sampasivam, Lavanya; Franco, Gina M.

2013-01-01

Background: Research is needed to explore conceptual change in relation to achievement goal orientations and depth of processing. Aims: To address this need, we examined relations between achievement goals, use of deep versus shallow processing strategies, and conceptual change learning using a think-aloud protocol. Sample and Method:…

Precipitation Estimation from the ARM Distributed Radar Network during the MC3E Campaign

DOE PAGES

Giangrande, Scott E.; Collis, Scott; Theisen, Adam K.; ...

2014-09-12

This study presents radar-based precipitation estimates collected during the two-month DOE ARM - NASA Midlatitude Continental Convective Clouds Experiment (MC3E). Emphasis is on the usefulness of radar observations from the C-band and X-band scanning ARM precipitation radars (CSAPR, XSAPR) for rainfall estimation products to distances within 100 km of the Oklahoma SGP facility. A dense collection of collocated ARM, NASA GPM and nearby surface Oklahoma Mesonet gauge records are consulted to evaluate potential ARM radar-based hourly rainfall products and campaign optimized methods over individual gauge and areal characterizations. Rainfall products are evaluated against the performance of the regional operational NWSmore » NEXRAD S-band radar polarimetric product. Results indicate that the ARM C-band system may achieve similar point and areal-gauge bias and root mean square (rms) error performance to the NEXRAD standard for the variety of MC3E deep convective events sampled when capitalizing on differential phase measurements. The best campaign rainfall performance was achieved when applying radar relations capitalizing on estimates of the specific attenuation from the CSAPR system. The ARM X-band systems only demonstrate solid capabilities as compared to NEXRAD standards for hourly point and areal rainfall accumulations under 10 mm. Here, all methods exhibit a factor of 1.5 to 2.5 reduction in rms errors for areal accumulations over a 15 km2 NASA dense network housing 16 sites having collocated bucket gauges, with the higher error reductions best associated with polarimetric methods.« less

Precipitation Estimation from the ARM Distributed Radar Network during the MC3E Campaign

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

Giangrande, Scott E.; Collis, Scott; Theisen, Adam K.

This study presents radar-based precipitation estimates collected during the two-month DOE ARM - NASA Midlatitude Continental Convective Clouds Experiment (MC3E). Emphasis is on the usefulness of radar observations from the C-band and X-band scanning ARM precipitation radars (CSAPR, XSAPR) for rainfall estimation products to distances within 100 km of the Oklahoma SGP facility. A dense collection of collocated ARM, NASA GPM and nearby surface Oklahoma Mesonet gauge records are consulted to evaluate potential ARM radar-based hourly rainfall products and campaign optimized methods over individual gauge and areal characterizations. Rainfall products are evaluated against the performance of the regional operational NWSmore » NEXRAD S-band radar polarimetric product. Results indicate that the ARM C-band system may achieve similar point and areal-gauge bias and root mean square (rms) error performance to the NEXRAD standard for the variety of MC3E deep convective events sampled when capitalizing on differential phase measurements. The best campaign rainfall performance was achieved when applying radar relations capitalizing on estimates of the specific attenuation from the CSAPR system. The ARM X-band systems only demonstrate solid capabilities as compared to NEXRAD standards for hourly point and areal rainfall accumulations under 10 mm. Here, all methods exhibit a factor of 1.5 to 2.5 reduction in rms errors for areal accumulations over a 15 km2 NASA dense network housing 16 sites having collocated bucket gauges, with the higher error reductions best associated with polarimetric methods.« less

Periosteal infusion of bupivacaine/morphine post sternal fracture: a new analgesic technique.

PubMed

Duncan, Michael A; McNicholas, Walter; O'Keeffe, Declan; O'Reilly, Maeve

2002-01-01

Sternal fracture pain is severe and is difficult to alleviate due to the forces acting on the chest wall during respiration. We describe a continuous infusion regional analgesic technique for pain due to sternal fracture. A 47-year-old woman presented with a spontaneous sternal fracture, precluding effective coughing. Diclofenac and increasing doses of opioids did not give adequate pain relief and led to opioid toxicity. Two brief periods of analgesia were achieved with deep subcutaneous infiltration of bupivacaine. An epidural catheter was positioned periosteally, and an infusion of bupivacaine was commenced at 5 mL/h, achieving long-lasting analgesia. The bupivacaine concentration was reduced in a stepwise fashion from 0.5% to 0.25% and was changed to levobupivacaine after 3 days. Adding morphine (5 mg/60 mL levobupivicaine) permitted a reduction in infusion rate. The catheter was removed after 14 days because a local infection developed that resolved uneventfully with antibiotic therapy. Continuous infusion of local anesthetic and opioid to a sternal fracture site using a periosteally positioned catheter led to successful analgesia and hence improved respiratory function. Clinicians should consider placing a periosteal catheter when pain associated with sternal fracture cannot be adequately controlled with conventional methods.

Ground Source Geothermal District Heating and Cooling System

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

Lowe, James William

2016-10-21

Ball State University converted its campus from a coal-fired steam boiler district heating system to a ground source heat pump geothermal district system that produces simultaneously hot water for heating and chilled water for cooling. This system will include the installation of 3,600 four hundred feet deep vertical closed loop boreholes making it the largest ground source geothermal district system in the country. The boreholes will act as heat exchangers and transfer heat by virtue of the earth’s ability to maintain an average temperature of 55 degree Fahrenheit. With growing international concern for global warming and the need to reducemore » worldwide carbon dioxide loading of the atmosphere geothermal is poised to provide the means to help reduce carbon dioxide emissions. The shift from burning coal to utilizing ground source geothermal will increase electrical consumption but an overall decrease in energy use and reduction in carbon dioxide output will be achieved. This achievement is a result of coupling the ground source geothermal boreholes with large heat pump chiller technology. The system provides the thermodynamic means to move large amounts of energy with limited energy input. Ball State University: http://cms.bsu.edu/About/Geothermal.aspx« less

Remote In-Space Manufacturing Applied with the Science of Interplanetary Supply Chain Modeling for Deep Space Gateway Application

NASA Astrophysics Data System (ADS)

Galluzzi, M. C.

2018-02-01

Three goals can be achieved by 2030: 1. NASA will have the capability for remote on-demand 3d printing of critical hardware using regolith material as feedstock, 2. Logistics footprint reduced by 35%, 3. Deep Space Gateway will become 75% self-sustaining.

Relations between Goals, Self-Efficacy, Critical Thinking and Deep Processing Strategies: A Path Analysis

ERIC Educational Resources Information Center

Phan, Huy Phuong

2009-01-01

Research exploring students' academic learning has recently amalgamated different motivational theories within one conceptual framework. The inclusion of achievement goals, self-efficacy, deep processing and critical thinking has been cited in a number of studies. This article discusses two empirical studies that examined these four theoretical…

The Test of Economic Literacy and an Evaluation of the DEEP System.

ERIC Educational Resources Information Center

Soper, John C.; Brenneke, Judith Staley

1981-01-01

Compares traditional and recent tests used to measure economic literacy at the secondary school level. Suggests that the new Test of Economic Literacy provides a badly needed replacement for previous tests such as the TEL and relates how the Developmental Economic Education Program (DEEP) affects academic achievement in economics. (Author/DB)

Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification.

PubMed

Sladojevic, Srdjan; Arsenovic, Marko; Anderla, Andras; Culibrk, Dubravko; Stefanovic, Darko

2016-01-01

The latest generation of convolutional neural networks (CNNs) has achieved impressive results in the field of image classification. This paper is concerned with a new approach to the development of plant disease recognition model, based on leaf image classification, by the use of deep convolutional networks. Novel way of training and the methodology used facilitate a quick and easy system implementation in practice. The developed model is able to recognize 13 different types of plant diseases out of healthy leaves, with the ability to distinguish plant leaves from their surroundings. According to our knowledge, this method for plant disease recognition has been proposed for the first time. All essential steps required for implementing this disease recognition model are fully described throughout the paper, starting from gathering images in order to create a database, assessed by agricultural experts. Caffe, a deep learning framework developed by Berkley Vision and Learning Centre, was used to perform the deep CNN training. The experimental results on the developed model achieved precision between 91% and 98%, for separate class tests, on average 96.3%.

Highly Efficient Solution-Processed Deep-Red Organic Light-Emitting Diodes Based on an Exciplex Host Composed of a Hole Transporter and a Bipolar Host.

PubMed

Huang, Manli; Jiang, Bei; Xie, Guohua; Yang, Chuluo

2017-10-19

With the aim to achieve highly efficient deep-red emission, we introduced an exciplex forming cohost, 4,4',4″-tris(3-methylphenylphenylamino)triphenylamine (m-MTDATA): 2,5-bis(2-(9H-carbazol-9-yl)phenyl)-1,3,4-oxadiazole (o-CzOXD) (1:1). Due to the efficient triplet up-conversion processes upon the exciplex forming cohost, excellent performances of the devices were achieved with deep-red emission. Using the heteroleptic iridium complexes as the guest dopants, the solution-processed deep-red phosphorescent organic light-emitting diodes (PhOLEDs) with the iridium(III) bis(6-(4-(tert-butyl)phenyl)phenanthridine)acetylacetonate [(TP-BQ) 2 Ir(acac)]-based phosphorescent emitter exhibited an electroluminescent peak at 656 nm and a maximum external quantum efficiency (EQE) of 11.9%, which is 6.6 times that of the device based on the guest emitter doped in the polymer-based cohost. The unique exciplex with a typical hole transporter and a bipolar material is ideal and universal for hosting the red PhOLEDs and tremendously improves the device performances.

Electrically driven deep ultraviolet MgZnO lasers at room temperature

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

Suja, Mohammad; Bashar, Sunayna Binte; Debnath, Bishwajit

Semiconductor lasers in the deep ultraviolet (UV) range have numerous potential applications ranging from water purification and medical diagnosis to high-density data storage and flexible displays. Nevertheless, very little success was achieved in the realization of electrically driven deep UV semiconductor lasers to date. Here, we report the fabrication and characterization of deep UV MgZnO semiconductor lasers. These lasers are operated with continuous current mode at room temperature and the shortest wavelength reaches 284 nm. The wide bandgap MgZnO thin films with various Mg mole fractions were grown on c-sapphire substrate using radio-frequency plasma assisted molecular beam epitaxy. Metal-semiconductor-metal (MSM)more » random laser devices were fabricated using lithography and metallization processes. Besides the demonstration of scalable emission wavelength, very low threshold current densities of 29-33 A/cm 2 are achieved. Furthermore, numerical modeling reveals that impact ionization process is responsible for the generation of hole carriers in the MgZnO MSM devices. The interaction of electrons and holes leads to radiative excitonic recombination and subsequent coherent random lasing.« less

Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification

PubMed Central

Sladojevic, Srdjan; Arsenovic, Marko; Culibrk, Dubravko; Stefanovic, Darko

2016-01-01

The latest generation of convolutional neural networks (CNNs) has achieved impressive results in the field of image classification. This paper is concerned with a new approach to the development of plant disease recognition model, based on leaf image classification, by the use of deep convolutional networks. Novel way of training and the methodology used facilitate a quick and easy system implementation in practice. The developed model is able to recognize 13 different types of plant diseases out of healthy leaves, with the ability to distinguish plant leaves from their surroundings. According to our knowledge, this method for plant disease recognition has been proposed for the first time. All essential steps required for implementing this disease recognition model are fully described throughout the paper, starting from gathering images in order to create a database, assessed by agricultural experts. Caffe, a deep learning framework developed by Berkley Vision and Learning Centre, was used to perform the deep CNN training. The experimental results on the developed model achieved precision between 91% and 98%, for separate class tests, on average 96.3%. PMID:27418923

Electrically driven deep ultraviolet MgZnO lasers at room temperature

DOE PAGES

Suja, Mohammad; Bashar, Sunayna Binte; Debnath, Bishwajit; ...

2017-06-01

Semiconductor lasers in the deep ultraviolet (UV) range have numerous potential applications ranging from water purification and medical diagnosis to high-density data storage and flexible displays. Nevertheless, very little success was achieved in the realization of electrically driven deep UV semiconductor lasers to date. Here, we report the fabrication and characterization of deep UV MgZnO semiconductor lasers. These lasers are operated with continuous current mode at room temperature and the shortest wavelength reaches 284 nm. The wide bandgap MgZnO thin films with various Mg mole fractions were grown on c-sapphire substrate using radio-frequency plasma assisted molecular beam epitaxy. Metal-semiconductor-metal (MSM)more » random laser devices were fabricated using lithography and metallization processes. Besides the demonstration of scalable emission wavelength, very low threshold current densities of 29-33 A/cm 2 are achieved. Furthermore, numerical modeling reveals that impact ionization process is responsible for the generation of hole carriers in the MgZnO MSM devices. The interaction of electrons and holes leads to radiative excitonic recombination and subsequent coherent random lasing.« less

Mercury on a landscape scale—Balancing regional export with wildlife health

USGS Publications Warehouse

Marvin-DiPasquale, Mark C.; Windham-Myers, Lisamarie; Fleck, Jacob A.; Ackerman, Joshua T.; Eagles-Smith, Collin A.; McQuillen, Harry

2018-06-26

The Cosumnes River watershed requires a 57–64 percent reduction in loads to meet the new Delta methylmercury (MeHg) total maximum daily load allocation, established by the Central Valley Regional Water Quality Control Board. Because there are no large point sources of MeHg in the watershed, the focus of MeHg load reductions will fall upon non-point sources, particularly the expansive wetlands considered to be a primary source of MeHg in the region. Few management practices have been implemented and tested in order to meet load reductions in managed wetlands, but recent efforts have shown promise. This project examines a treatment approach to reduce MeHg loads to the Sacramento-San Joaquin River Delta by creating open-water deep cells with a small footprint at the downstream end of wetlands to promote net demethylation of MeHg and to minimize MeHg and Hg loads exiting wetlands at the Cosumnes River Preserve. Specifically, the deep cells were were located immediately up gradient of the wetland’s outflow weir and were deep enough (75–91 centimeter depth) to be vegetation-free. The topographic and hydrologic structure of each treatment wetland was modified to include open-water deep cells so that the removal of aqueous MeHg might be enhanced through (1) particle settling, (2) photo-degradation, and (3) benthic microbial demethylation. These deep cells were, therefore, expected to clean MeHg from surface water prior to its discharge to the Cosumnes River and the downstream Delta.Our goal was to test whether the implementation of the deep cells within wetlands would minimize MeHg and total Hg export. Further, we sought to test whether continuous flow-through hydrology, would lower MeHg concentrations in resident biota, compared to traditional wetland management operations. The dominant practice in seasonal wetlands management is the “fill-and-maintain” approach, in which wetlands are filled with water and the water levels maintained without substantial draining until drawdown. Our approach was to create and characterize replicate treatment wetland complexes, in conjunction with monitoring of hydrologic, biologic, and chemical indicators of MeHg exposure for two full annual cycles within winter-spring flooded seasonal wetlands. In addition to the creation of deep cells within treatment wetlands, hydrology was manipulated so that there was a constant flow-through of water, while the control wetlands utilized the fill-and-maintain approach. Specifically, the treatment wetlands were maintained in a flow-through manner, while the control wetlands were maintained in a fill-and-maintain manner from September through May, to test the hypothesis that the flow of water through the seasonal wetland can lower fish bioaccumulation through dilution of MeHg-concentrated water within the wetland by constant inflows of water into the wetland.The major tasks of this study included: (1) field design and implementation, (2) water and wetland management, (3) hydrologic monitoring and water quality sampling, (4) MeHg export and load estimates, (5) caged fish experiments for examining MeHg bioaccumulation, (6) site and process characterization to improve understanding and transferability of results, (7) adaptive management, transferability, and outreach, and (8) reporting of results and conclusions. This report summarizes the key findings of this study, which focuses on MeHg load estimates from control and treatment wetlands, quantification of three MeHg removal mechanisms (particulate settling, benthic demethylation, and photo-demethylation) in the deep cells within the treatment wetlands, and MeHg bioaccumulation in wetland fishes.Key findings include:Over two years of study, mean whole-water MeHg load decreased 37 percent in deep cells, when comparing inlet of check weir flows to outlet.Of the 37 percent MeHg load removed within the deep cell, photodegradation accounted for 7 percent and particle flux to the benthos accounted for 24 percent of the mass removed, with the remaining 6 percent apparent MeHg loss unexplained.Benthic MeHg degradation did not appear to be a major MeHg removal process in the deep cells, as changes in the ambient MeHg pool over 7-day bottle incubations showed that the surface sediment exhibited net MeHg production in the majority (87 percent) of incubation experiments. In only 13 percent of the incubations (3 out of 24) was net MeHg degradation observed.Estimates of benthic diffusive flux of MeHg across the sediment/water interface were small relative to particulate flux and variable (positive or negative), suggesting this is likely a minor term in the overall MeHg budget within the deep cells.Although the deep cells served as net MeHg sink overall, MeHg export from the flow-through treatment wetlands (shallow and deep combined) exceeded export from the fill-and-maintain managed control wetlands, because of the differences in hydrologic management between the two wetland types.Shallow wetlands under flow-through conditions generated a net export of MeHg.Most of the annual MeHg export from the treatment wetlands occurred within the first 3 months of flood up (September to November), shortly after hydrologic management began.Despite the effectiveness of the deep cell in lowering MeHg export concentrations, total mercury (THg) concentration did not decrease in biosentinel fish (Gambusia affinis, Mosquitofish) between the deep cell inlet and outlet.Mosquitofish THg concentrations were higher in treatment wetlands than in control wetlands during the first year of study, likely because of an associated increase in MeHg availability immediately following wetland construction activities. Mosquitofish THg concentrations declined in the treatment wetlands during the second year of study, and fish THg concentrations in treatment wetlands were no different from those in the control.Similarly, the increased hydrologic flow rates in the treatment wetlands did not lower fish THg concentrations nor aqueous MeHg concentrations in the shallow cells, suggesting that MeHg flux from the sediment to water column exceeded the flow-through flushing rate in the shallow portion of the treatment wetlands.Reductions in MeHg concentrations of surface water and fish may require higher flow rates than used in the study to achieve the region’s regulatory goals. However, the flow rates necessary may not be feasible for these managed wetlands because of limited water supply and the associated costs for water and pumping.The use of deep cells in seasonal wetlands were effective in lowering MeHg exports under continuous water flow-through hydrology. However, fill-and-maintain hydrology had lower exports overall, because of a single major drainage event at the end of the flood season.Future studies focused on limiting MeHg export should consider combining deep cells with the fill-and-maintain or fill-and-trickle hydrologic management approach.

Text feature extraction based on deep learning: a review.

PubMed

Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

2017-01-01

Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

Sensorless adaptive optics for isoSTED nanoscopy

NASA Astrophysics Data System (ADS)

Antonello, Jacopo; Hao, Xiang; Allgeyer, Edward S.; Bewersdorf, Joerg; Rittscher, Jens; Booth, Martin J.

2018-02-01

The presence of aberrations is a major concern when using fluorescence microscopy to image deep inside tissue. Aberrations due to refractive index mismatch and heterogeneity of the specimen under investigation cause severe reduction in the amount of fluorescence emission that is collected by the microscope. Furthermore, aberrations adversely affect the resolution, leading to loss of fine detail in the acquired images. These phenomena are particularly troublesome for super-resolution microscopy techniques such as isotropic stimulated-emission-depletion microscopy (isoSTED), which relies on accurate control of the shape and co-alignment of multiple excitation and depletion foci to operate as expected and to achieve the super-resolution effect. Aberrations can be suppressed by implementing sensorless adaptive optics techniques, whereby aberration correction is achieved by maximising a certain image quality metric. In confocal microscopy for example, one can employ the total image brightness as an image quality metric. Aberration correction is subsequently achieved by iteratively changing the settings of a wavefront corrector device until the metric is maximised. This simplistic approach has limited applicability to isoSTED microscopy where, due to the complex interplay between the excitation and depletion foci, maximising the total image brightness can lead to introducing aberrations in the depletion foci. In this work we first consider the effects that different aberration modes have on isoSTED microscopes. We then propose an iterative, wavelet-based aberration correction algorithm and evaluate its benefits.

The effect of some heat treatment parameters on the dimensional stability of AISI D2

NASA Astrophysics Data System (ADS)

Surberg, Cord Henrik; Stratton, Paul; Lingenhöle, Klaus

2008-01-01

The tool steel AISI D2 is usually processed by vacuum hardening followed by multiple tempering cycles. It has been suggested that a deep cold treatment in between the hardening and tempering processes could reduce processing time and improve the final properties and dimensional stability. Hardened blocks were then subjected to various combinations of single and multiple tempering steps (520 and 540 °C) and deep cold treatments (-90, -120 and -150 °C). The greatest dimensional stability was achieved by deep cold treatments at the lowest temperature used and was independent of the deep cold treatment time.

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

PubMed

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.

PubMed

Jones, David T; Kandathil, Shaun M

2018-04-26

In addition to substitution frequency data from protein sequence alignments, many state-of-the-art methods for contact prediction rely on additional sources of information, or features, of protein sequences in order to predict residue-residue contacts, such as solvent accessibility, predicted secondary structure, and scores from other contact prediction methods. It is unclear how much of this information is needed to achieve state-of-the-art results. Here, we show that using deep neural network models, simple alignment statistics contain sufficient information to achieve state-of-the-art precision. Our prediction method, DeepCov, uses fully convolutional neural networks operating on amino-acid pair frequency or covariance data derived directly from sequence alignments, without using global statistical methods such as sparse inverse covariance or pseudolikelihood estimation. Comparisons against CCMpred and MetaPSICOV2 show that using pairwise covariance data calculated from raw alignments as input allows us to match or exceed the performance of both of these methods. Almost all of the achieved precision is obtained when considering relatively local windows (around 15 residues) around any member of a given residue pairing; larger window sizes have comparable performance. Assessment on a set of shallow sequence alignments (fewer than 160 effective sequences) indicates that the new method is substantially more precise than CCMpred and MetaPSICOV2 in this regime, suggesting that improved precision is attainable on smaller sequence families. Overall, the performance of DeepCov is competitive with the state of the art, and our results demonstrate that global models, which employ features from all parts of the input alignment when predicting individual contacts, are not strictly needed in order to attain precise contact predictions. DeepCov is freely available at https://github.com/psipred/DeepCov. d.t.jones@ucl.ac.uk.

Spatially explicit estimates of forest carbon emissions, mitigation costs and REDD+ opportunities in Indonesia

NASA Astrophysics Data System (ADS)

Graham, Victoria; Laurance, Susan G.; Grech, Alana; Venter, Oscar

2017-04-01

Carbon emissions from the conversion and degradation of tropical forests contribute to anthropogenic climate change. Implementing programs to reduce emissions from tropical forest loss in Southeast Asia are perceived to be expensive due to high opportunity costs of avoided deforestation. However, these costs are not representative of all REDD+ opportunities as they are typically based on average costs across large land areas and are primarily for reducing deforestation from oil palm or pulp concessions. As mitigation costs and carbon benefits can vary according to site characteristics, spatially-explicit information should be used to assess cost-effectiveness and to guide the allocation of scarce REDD+ resources. We analyzed the cost-effectiveness of the following REDD+ strategies in Indonesia, one of the world’s largest sources of carbon emissions from deforestation: halting additional deforestation in protected areas, timber and oil palm concessions, reforesting degraded land and employing reduced-impact logging techniques in logging concessions. We discover that when spatial variation in costs and benefits is considered, low-cost options emerged even for the two most expensive strategies: protecting forests from conversion to oil palm and timber plantations. To achieve a low emissions reduction target of 25%, we suggest funding should target deforestation in protected areas, and oil palm and timber concessions to maximize emissions reductions at the lowest cumulative cost. Low-cost opportunities for reducing emissions from oil palm are where concessions have been granted on deep peat deposits or unproductive land. To achieve a high emissions reduction target of 75%, funding is allocated across all strategies, emphasizing that no single strategy can reduce emissions cost-effectively across all of Indonesia. These findings demonstrate that by using a spatially-targeted approach to identify high priority locations for reducing emissions from deforestation and forest degradation, REDD+ resources can be allocated cost-effectively across Indonesia.

Do deep convolutional neural networks really need to be deep when applied for remote scene classification?

NASA Astrophysics Data System (ADS)

Luo, Chang; Wang, Jie; Feng, Gang; Xu, Suhui; Wang, Shiqiang

2017-10-01

Deep convolutional neural networks (CNNs) have been widely used to obtain high-level representation in various computer vision tasks. However, for remote scene classification, there are not sufficient images to train a very deep CNN from scratch. From two viewpoints of generalization power, we propose two promising kinds of deep CNNs for remote scenes and try to find whether deep CNNs need to be deep for remote scene classification. First, we transfer successful pretrained deep CNNs to remote scenes based on the theory that depth of CNNs brings the generalization power by learning available hypothesis for finite data samples. Second, according to the opposite viewpoint that generalization power of deep CNNs comes from massive memorization and shallow CNNs with enough neural nodes have perfect finite sample expressivity, we design a lightweight deep CNN (LDCNN) for remote scene classification. With five well-known pretrained deep CNNs, experimental results on two independent remote-sensing datasets demonstrate that transferred deep CNNs can achieve state-of-the-art results in an unsupervised setting. However, because of its shallow architecture, LDCNN cannot obtain satisfactory performance, regardless of whether in an unsupervised, semisupervised, or supervised setting. CNNs really need depth to obtain general features for remote scenes. This paper also provides baseline for applying deep CNNs to other remote sensing tasks.

30 CFR 203.33 - To which production do I apply the RSV earned by qualified phase 2 and phase 3 ultra-deep wells...

Code of Federal Regulations, 2010 CFR

2010-07-01

... RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and Sulfur General Royalty Relief for Drilling Ultra... after May 18, 2007, reported on the Oil and Gas Operations Report, Part A (OGOR-A) for your lease under... the unitized portion of lease A (drilled after the ultra-deep well on the non-unitized portion of that...

Deep level defects in dilute GaAsBi alloys grown under intense UV illumination

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

Mooney, P. M.; Tarun, Marianne; Beaton, D. A.

2016-07-21

Dilute GaAs1-xBix alloys exhibiting narrow band edge photoluminescence (PL) were recently grown by molecular beam epitaxy (MBE) with the growth surface illuminated by intense UV radiation. To investigate whether the improved optical quality of these films results from a reduction in the concentration of deep level defects, p+/n and n+/p junction diodes were fabricated on both the illuminated and dark areas of several samples. Deep Level Transient Spectroscopy (DLTS) measurements show that the illuminated and dark areas of both the n- and p-type GaAs1-xBix epi-layers have similar concentrations of near mid-gap electron and hole traps, in the 1015 cm-3 range.more » Thus the improved PL spectra cannot be explained by a reduction in non-radiative recombination at deep level defects. We note that carrier freeze-out above 35 K is significantly reduced in the illuminated areas of the p-type GaAs1-xBix layers compared to the dark areas, allowing the first DLTS measurements of defect energy levels close to the valence band edge. These defect levels may account for differences in the PL spectra from the illuminated and dark areas of un-doped layers with a similar Bi fraction.« less

Ultra-Deep Drilling Cost Reduction; Design and Fabrication of an Ultra-Deep Drilling Simulator (UDS)

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

Lindstrom, Jason

2010-01-31

Ultra-deep drilling, below about 20,000 ft (6,096 m), is extremely expensive and limits the recovery of hydrocarbons at these depths. Unfortunately, rock breakage and cuttings removal under these conditions is not understood. To better understand and thus reduce cost at these conditions an ultra-deep single cutter drilling simulator (UDS) capable of drill cutter and mud tests to sustained pressure and temperature of 30,000 psi (207 MPa) and 482 °F (250 °C), respectively, was designed and manufactured at TerraTek, a Schlumberger company, in cooperation with the Department of Energy’s National Energy Technology Laboratory. UDS testing under ultra-deep drilling conditions offers anmore » economical alternative to high day rates and can prove or disprove the viability of a particular drilling technique or fluid to provide opportunity for future domestic energy needs.« less

Thermal performance trials on the habitability of private bushfire shelters: part 1

NASA Astrophysics Data System (ADS)

Taylor, Nigel A. S.; Haberley, Benjamin J.; Hoyle, David J. R.

2015-08-01

This communication is the first of two in which specifications for private bushfire shelters were evaluated during human trials. The purpose of this investigation (series 1) was to test the hypothesis that shelters capable of maintaining the internal environment at, or below, a modified discomfort index of 39 °C would prevent a deep-body temperature elevation of >2 °C. This was tested over 96 trials during which eight men and eight women were exposed at rest (60 min) to three regulated shelter conditions satisfying that standard: 40 °C and 70 % relative humidity, 45 °C and 50 % relative humidity and 50 °C and 30 % relative humidity. Subjects were tested twice in each condition following exercise- and heat-induced dehydration (2 % body mass reduction) and pre-heating to each of two deep-body thermal states (37.5 and 38.5 °C). Participants presented well rested and euhydrated, and pre-treatments successfully achieved the thermal and hydration targets prior to exposure. Auditory canal temperatures declined as exposures commenced, with subsequent rises of >0.5 °C not evident within any trial. However, each increment in air temperature elicited a significant elevation in the respective within-trial mean auditory canal temperature (37.4, 37.7 and 37.9 °C) and heart rate (103, 116 and 122 beats.min-1) when subjects were moderately hyperthermic (all P < 0.05). Nevertheless, on average, subjects successfully defended deep-body temperature at levels significantly below those associated with heat illness, and it was concluded that this thermal specification for bushfire shelters appeared adequate, providing the physical characteristics of the internal air remained stable.

Operative treatment of early infection after internal fixation of limb fractures (exclusive of severe open fractures).

PubMed

Bonnevialle, P

2017-02-01

Early infection after open reduction and internal fixation (ORIF) of a limb bone is defined as bacteriologically documented, deep and/or superficial surgical-site infection (SSI) diagnosed within 6months after the surgical procedure. This interval is arbitrarily considered sufficient to obtain fracture healing. The treatment of early infection after ORIF should be decided by a multidisciplinary team. The principles are the same as for revision arthroplasty. Superficial SSIs should be differentiated from deep SSIs, based on the results of bacteriological specimens collected using flawless technique. A turning point in the local microbial ecology occurs around the third or fourth week, when a biofilm develops around metallic implants. This biofilm protects the bacteria. The treatment relies on both non-operative and operative measures, which are selected based on the time to occurrence of the infection, condition of the soft tissues, and stage of bone healing. Both the surgical strategy and the antibiotic regimen should be determined during a multidisciplinary discussion. When treating superficial SSIs after ORIF, soft-tissue management is the main challenge. The treatment differs according to whether the hardware is covered or exposed. Defects in the skin and/or fascia can be managed using reliable reconstructive surgery techniques, either immediately or after a brief period of vacuum-assisted closure. In deep SSIs, deciding whether to leave or to remove the hardware is difficult. If the hardware is removed, the fracture site can be stabilised provisionally using either external fixation or a cement rod. Once infection control is achieved, several measures can be taken to stimulate bone healing before the end of the classical 6-month interval. If the hardware was removed, then internal fixation must be performed once the infection is eradicated. Copyright © 2016. Published by Elsevier Masson SAS.

Thermal performance trials on the habitability of private bushfire shelters: part 1.

PubMed

Taylor, Nigel A S; Haberley, Benjamin J; Hoyle, David J R

2015-08-01

This communication is the first of two in which specifications for private bushfire shelters were evaluated during human trials. The purpose of this investigation (series 1) was to test the hypothesis that shelters capable of maintaining the internal environment at, or below, a modified discomfort index of 39 °C would prevent a deep-body temperature elevation of >2 °C. This was tested over 96 trials during which eight men and eight women were exposed at rest (60 min) to three regulated shelter conditions satisfying that standard: 40 °C and 70 % relative humidity, 45 °C and 50 % relative humidity and 50 °C and 30 % relative humidity. Subjects were tested twice in each condition following exercise- and heat-induced dehydration (2 % body mass reduction) and pre-heating to each of two deep-body thermal states (37.5 and 38.5 °C). Participants presented well rested and euhydrated, and pre-treatments successfully achieved the thermal and hydration targets prior to exposure. Auditory canal temperatures declined as exposures commenced, with subsequent rises of >0.5 °C not evident within any trial. However, each increment in air temperature elicited a significant elevation in the respective within-trial mean auditory canal temperature (37.4, 37.7 and 37.9 °C) and heart rate (103, 116 and 122 beats.min(-1)) when subjects were moderately hyperthermic (all P < 0.05). Nevertheless, on average, subjects successfully defended deep-body temperature at levels significantly below those associated with heat illness, and it was concluded that this thermal specification for bushfire shelters appeared adequate, providing the physical characteristics of the internal air remained stable.

Outpatient treatment of deep venous thrombosis in diverse inner-city patients.

PubMed

Dunn, A S; Schechter, C; Gotlin, A; Vomvolakis, D; Jacobs, E; Sacks, H S; Coller, B

2001-04-15

We sought to describe the development and outcomes of a hospital-based program designed to provide safe and effective outpatient treatment to a diverse group of patients with acute deep venous thrombosis. Patients enrolled in the program were usually discharged on the day of or the day after presentation. Low- molecular-weight heparin was administered for a minimum of 5 days and warfarin was given for a minimum of 3 months. The hospital provided low-molecular-weight heparin free of charge to patients. Patients received daily home nursing visits to monitor the prothrombin time, assess compliance, and detect complications. The inpatient and outpatient records of the first 89 consecutive patients enrolled in the program were reviewed. Patients were observed for a 3-month period after enrollment. The median length of stay was 1 day. Low-molecular-weight heparin was administered for a mean (+/- standard deviation [SD]) of 4.7 +/- 2.4 days at home. Recurrent thromboembolism was noted in 1 patient (1%), major bleeding in 2 patients (2%), and minor bleeding in 2 patients (2%). No patients died or developed thrombocytopenia. Assuming that patients would have been hospitalized for the duration of treatment with low-molecular-weight heparin, the program eliminated a mean of 4.7 days of hospitalization, with an estimated reduction of $1,645 in total health care costs per patient. This hospital-based program to provide outpatient treatment of deep venous thrombosis to a diverse group of inner-city patients achieved a low incidence of adverse events and substantial health care cost savings. Specific strategies, including providing low-molecular-weight heparin free of charge and daily home nursing visits, can be utilized to facilitate access to outpatient treatment and ensure high-quality care.

Deep transcranial magnetic stimulation for the treatment of auditory hallucinations: a preliminary open-label study

PubMed Central

2011-01-01

Background Schizophrenia is a chronic and disabling disease that presents with delusions and hallucinations. Auditory hallucinations are usually expressed as voices speaking to or about the patient. Previous studies have examined the effect of repetitive transcranial magnetic stimulation (TMS) over the temporoparietal cortex on auditory hallucinations in schizophrenic patients. Our aim was to explore the potential effect of deep TMS, using the H coil over the same brain region on auditory hallucinations. Patients and methods Eight schizophrenic patients with refractory auditory hallucinations were recruited, mainly from Beer Ya'akov Mental Health Institution (Tel Aviv university, Israel) ambulatory clinics, as well as from other hospitals outpatient populations. Low-frequency deep TMS was applied for 10 min (600 pulses per session) to the left temporoparietal cortex for either 10 or 20 sessions. Deep TMS was applied using Brainsway's H1 coil apparatus. Patients were evaluated using the Auditory Hallucinations Rating Scale (AHRS) as well as the Scale for the Assessment of Positive Symptoms scores (SAPS), Clinical Global Impressions (CGI) scale, and the Scale for Assessment of Negative Symptoms (SANS). Results This preliminary study demonstrated a significant improvement in AHRS score (an average reduction of 31.7% ± 32.2%) and to a lesser extent improvement in SAPS results (an average reduction of 16.5% ± 20.3%). Conclusions In this study, we have demonstrated the potential of deep TMS treatment over the temporoparietal cortex as an add-on treatment for chronic auditory hallucinations in schizophrenic patients. Larger samples in a double-blind sham-controlled design are now being preformed to evaluate the effectiveness of deep TMS treatment for auditory hallucinations. Trial registration This trial is registered with clinicaltrials.gov (identifier: NCT00564096). PMID:21303566

Deep Reductions in Greenhouse Gas Emissions from the California Transportation Sector: Dynamics in Vehicle Fleet and Energy Supply Transitions to Achieve 80% Reduction in Emissions from 1990 Levels by 2050

NASA Astrophysics Data System (ADS)

Leighty, Wayne Waterman

California's "80in50" target for reducing greenhouse gas emissions to 80 percent below 1990 levels by the year 2050 is based on climate science rather than technical feasibility of mitigation. As such, it raises four fundamental questions: is this magnitude of reduction in greenhouse gas emissions possible, what energy system transitions over the next 40 years are necessary, can intermediate policy goals be met on the pathway toward 2050, and does the path of transition matter for the objective of climate change mitigation? Scenarios for meeting the 80in50 goal in the transportation sector are modelled. Specifically, earlier work defining low carbon transport scenarios for the year 2050 is refined by incorporating new information about biofuel supply. Then transition paths for meeting 80in50 scenarios are modelled for the light-duty vehicle sub-sector, with important implications for the timing of action, rate of change, and cumulative greenhouse gas emissions. One aspect of these transitions -- development in the California wind industry to supply low-carbon electricity for plug-in electric vehicles -- is examined in detail. In general, the range of feasible scenarios for meeting the 80in50 target is narrow enough that several common themes are apparent: electrification of light-duty vehicles must occur; continued improvements in vehicle efficiency must be applied to improving fuel economy; and energy carriers must de-carbonize to less than half of the carbon intensity of gasoline and diesel. Reaching the 80in50 goal will require broad success in travel demand reduction, fuel economy improvements and low-carbon fuel supply, since there is little opportunity to increase emission reductions in one area if we experience failure in another. Although six scenarios for meeting the 80in50 target are defined, only one also meets the intermediate target of reducing greenhouse gas emissions to 1990 levels by the year 2020. Furthermore, the transition path taken to reach any one of these scenarios can differ in cumulative emissions by more than 25 percent. Since cumulative emissions are the salient factor for climate change mitigation and the likelihood of success is an important consideration, initiating action immediately to begin the transitions indicated for achieving the 80in50 goal is found to be prudent.

Supporting Lower-Achieving Seven- and Eight-Year-Old Children with Place Value Understandings

ERIC Educational Resources Information Center

Bailey, Judy

2015-01-01

Children can sometimes appear to understand a concept such as place value without really having a deep understanding. Judy Bailey stresses the importance of listening carefully to children to identify their current understandings and then building on them systematically, using a range of materials, to promote a deep conceptual understanding. This…

Deep feature representation with stacked sparse auto-encoder and convolutional neural network for hyperspectral imaging-based detection of cucumber defects

USDA-ARS?s Scientific Manuscript database

It is challenging to achieve rapid and accurate processing of large amounts of hyperspectral image data. This research was aimed to develop a novel classification method by employing deep feature representation with the stacked sparse auto-encoder (SSAE) and the SSAE combined with convolutional neur...

Are Deep Strategic Learners Better Suited to PBL? A Preliminary Study

ERIC Educational Resources Information Center

Papinczak, Tracey

2009-01-01

The aim of this study was to determine if medical students categorised as having deep and strategic approaches to their learning find problem-based learning (PBL) enjoyable and supportive of their learning, and achieve well in the first-year course. Quantitative and qualitative data were gathered from first-year medical students (N = 213). All…

Diverse Assessment and Active Student Engagement Sustain Deep Learning: A Comparative Study of Outcomes in Two Parallel Introductory Biochemistry Courses

ERIC Educational Resources Information Center

Bevan, Samantha J.; Chan, Cecilia W. L.; Tanner, Julian A.

2014-01-01

Although there is increasing evidence for a relationship between courses that emphasize student engagement and achievement of student deep learning, there is a paucity of quantitative comparative studies in a biochemistry and molecular biology context. Here, we present a pedagogical study in two contrasting parallel biochemistry introductory…

Contributions of Academic Language, Perspective Taking, and Complex Reasoning to Deep Reading Comprehension

ERIC Educational Resources Information Center

LaRusso, Maria; Kim, Ha Yeon; Selman, Robert; Uccelli, Paola; Dawson, Theo; Jones, Stephanie; Donovan, Suzanne; Snow, Catherine

2016-01-01

"Deep reading comprehension" refers to the process required to succeed at tasks defined by the Common Core State Literacy Standards, as well as to achieve proficiency on the more challenging reading tasks in the Program for International Student Assessment (PISA) framework. The purpose of this study was to test the hypothesis that three…

Deep Learning in Distance Education: Are We Achieving the Goal?

ERIC Educational Resources Information Center

Shearer, Rick L.; Gregg, Andrea; Joo, K. P.

2015-01-01

As educators, one of our goals is to help students arrive at deeper levels of learning. However, how is this accomplished, especially in online courses? This design-based research study explored the concept of deep learning through a series of design changes in a graduate education course. A key question that emerged was through what learning…

Reduction Mammoplasty: A Comparison Between Operations Performed by Plastic Surgery and General Surgery.

PubMed

Kordahi, Anthony M; Hoppe, Ian C; Lee, Edward S

2015-01-01

Reduction mammoplasty is an often-performed procedure by plastic surgeons and increasingly by general surgeons. The question has been posed in both general surgical literature and plastic surgical literature as to whether this procedure should remain the domain of surgical specialists. Some general surgeons are trained in breast reductions, whereas all plastic surgeons receive training in this procedure. The National Surgical Quality Improvement Project provides a unique opportunity to compare the 2 surgical specialties in an unbiased manner in terms of preoperative comorbidities and 30-day postoperative complications. The National Surgical Quality Improvement Project database was queried for the years 2005-2012. Patients were identified as having undergone a reduction mammoplasty by Current Procedural Terminology codes. RESULTS were refined to include only females with an International Classification of Diseases, Ninth Revision, code of 611.1 (hypertrophy of breasts). Information was collected regarding age, surgical specialty performing procedure, body mass index, and other preoperative variables. The outcomes utilized were presence of superficial surgical site infection, presence of deep surgical site infection, presence of wound dehiscence, postoperative respiratory compromise, pulmonary embolism, deep vein thrombosis, perioperative transfusion, operative time, reintubation, reoperation, and length of hospital stay. During this time period, there were 6239 reduction mammaplasties performed within the National Surgical Quality Improvement Project database: 339 by general surgery and 5900 by plastic surgery. No statistical differences were detected between the 2 groups with regard to superficial wound infections, deep wound infections, organ space infections, or wound dehiscence. There were no significant differences noted between within groups with regard to systemic postoperative complications. Patients undergoing a procedure by general surgery were more likely to experience a failure of skin flaps, necessitating a return to the operative room (P < .05). Operative time was longer in procedures performed by general surgery (P < .05). Several important differences appear to exist between reduction mammaplasties performed by general surgery and plastic surgery. A focused training in reduction mammoplasty appears to be beneficial to the patient. The limitations of this study include a lack of long-term follow-up with regard to aesthetic outcome, nipple malposition, nipple sensation, and late wound sequelae.

Explaining Achievement in Higher Education

ERIC Educational Resources Information Center

Jansen, Ellen P. W. A.; Bruinsma, Marjon

2005-01-01

This research project investigated the relationship between students' pre-entry characteristics, perceptions of the learning environment, reported work discipline, the use of deep information processing strategies, and academic achievement. Ability measured by grade-point average in pre-university education was the most important predictor of…

Microbial redox processes in deep subsurface environments and the potential application of (per)chlorate in oil reservoirs

PubMed Central

Liebensteiner, Martin G.; Tsesmetzis, Nicolas; Stams, Alfons J. M.; Lomans, Bartholomeus P.

2014-01-01

The ability of microorganisms to thrive under oxygen-free conditions in subsurface environments relies on the enzymatic reduction of oxidized elements, such as sulfate, ferric iron, or CO2, coupled to the oxidation of inorganic or organic compounds. A broad phylogenetic and functional diversity of microorganisms from subsurface environments has been described using isolation-based and advanced molecular ecological techniques. The physiological groups reviewed here comprise iron-, manganese-, and nitrate-reducing microorganisms. In the context of recent findings also the potential of chlorate and perchlorate [jointly termed (per)chlorate] reduction in oil reservoirs will be discussed. Special attention is given to elevated temperatures that are predominant in the deep subsurface. Microbial reduction of (per)chlorate is a thermodynamically favorable redox process, also at high temperature. However, knowledge about (per)chlorate reduction at elevated temperatures is still scarce and restricted to members of the Firmicutes and the archaeon Archaeoglobus fulgidus. By analyzing the diversity and phylogenetic distribution of functional genes in (meta)genome databases and combining this knowledge with extrapolations to earlier-made physiological observations we speculate on the potential of (per)chlorate reduction in the subsurface and more precisely oil fields. In addition, the application of (per)chlorate for bioremediation, souring control, and microbial enhanced oil recovery are addressed. PMID:25225493

Towards deep learning with segregated dendrites

PubMed Central

Guerguiev, Jordan; Lillicrap, Timothy P

2017-01-01

Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning algorithm that utilizes multi-compartment neurons might help us to understand how the neocortex optimizes cost functions. Like neocortical pyramidal neurons, neurons in our model receive sensory information and higher-order feedback in electrotonically segregated compartments. Thanks to this segregation, neurons in different layers of the network can coordinate synaptic weight updates. As a result, the network learns to categorize images better than a single layer network. Furthermore, we show that our algorithm takes advantage of multilayer architectures to identify useful higher-order representations—the hallmark of deep learning. This work demonstrates that deep learning can be achieved using segregated dendritic compartments, which may help to explain the morphology of neocortical pyramidal neurons. PMID:29205151

Towards deep learning with segregated dendrites.

PubMed

Guerguiev, Jordan; Lillicrap, Timothy P; Richards, Blake A

2017-12-05

Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning algorithm that utilizes multi-compartment neurons might help us to understand how the neocortex optimizes cost functions. Like neocortical pyramidal neurons, neurons in our model receive sensory information and higher-order feedback in electrotonically segregated compartments. Thanks to this segregation, neurons in different layers of the network can coordinate synaptic weight updates. As a result, the network learns to categorize images better than a single layer network. Furthermore, we show that our algorithm takes advantage of multilayer architectures to identify useful higher-order representations-the hallmark of deep learning. This work demonstrates that deep learning can be achieved using segregated dendritic compartments, which may help to explain the morphology of neocortical pyramidal neurons.

Bag-of-visual-phrases and hierarchical deep models for traffic sign detection and recognition in mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yu, Yongtao; Li, Jonathan; Wen, Chenglu; Guan, Haiyan; Luo, Huan; Wang, Cheng

2016-03-01

This paper presents a novel algorithm for detection and recognition of traffic signs in mobile laser scanning (MLS) data for intelligent transportation-related applications. The traffic sign detection task is accomplished based on 3-D point clouds by using bag-of-visual-phrases representations; whereas the recognition task is achieved based on 2-D images by using a Gaussian-Bernoulli deep Boltzmann machine-based hierarchical classifier. To exploit high-order feature encodings of feature regions, a deep Boltzmann machine-based feature encoder is constructed. For detecting traffic signs in 3-D point clouds, the proposed algorithm achieves an average recall, precision, quality, and F-score of 0.956, 0.946, 0.907, and 0.951, respectively, on the four selected MLS datasets. For on-image traffic sign recognition, a recognition accuracy of 97.54% is achieved by using the proposed hierarchical classifier. Comparative studies with the existing traffic sign detection and recognition methods demonstrate that our algorithm obtains promising, reliable, and high performance in both detecting traffic signs in 3-D point clouds and recognizing traffic signs on 2-D images.

Factors affecting the achievement of Japanese-style deep knee flexion after total knee arthroplasty using posterior-stabilized prosthesis with high-flex knee design.

PubMed

Niki, Yasuo; Takeda, Yuki; Harato, Kengo; Suda, Yasunori

2015-11-01

Achievement of very deep knee flexion after total knee arthroplasty (TKA) can play a critical role in the satisfaction of patients who demand a floor-sitting lifestyle and engage in high-flexion daily activities (e.g., seiza-sitting). Seiza-sitting is characterized by the knees flexed >145º and feet turned sole upwards underneath the buttocks with the tibia internally rotated. The present study investigated factors affecting the achievement of seiza-sitting after TKA using posterior-stabilized total knee prosthesis with high-flex knee design. Subjects comprised 32 patients who underwent TKA with high-flex knee prosthesis and achieved seiza-sitting (knee flexion >145º) postoperatively. Another 32 patients served as controls who were capable of knee flexion >145º preoperatively, but failed to achieve seiza-sitting postoperatively. Accuracy of femoral and tibial component positions was assessed in terms of deviation from the ideal position using a two-dimensional to three-dimensional matching technique. Accuracies of the component position, posterior condylar offset ratio and intraoperative gap length were compared between the two groups. The proportion of patients with >3º internally rotated tibial component was significantly higher in patients who failed at seiza-sitting (41 %) than among patients who achieved it (13 %, p = 0.021). Comparison of intraoperative gap length between patient groups revealed that gap length at 135º flexion was significantly larger in patients who achieved seiza-sitting (4.2 ± 0.4 mm) than in patients who failed at it (2.7 ± 0.4 mm, p = 0.007). Conversely, no significant differences in gap inclination were seen between the groups. From the perspective of surgical factors, accurate implant positioning, particularly rotational alignment of the tibial component, and maintenance of a sufficient joint gap at 135º flexion appear to represent critical factors for achieving >145º of deep knee flexion after TKA.

Setup for in situ deep level transient spectroscopy of semiconductors during swift heavy ion irradiation.

PubMed

Kumar, Sandeep; Kumar, Sugam; Katharria, Y S; Safvan, C P; Kanjilal, D

2008-05-01

A computerized system for in situ deep level characterization during irradiation in semiconductors has been set up and tested in the beam line for materials science studies of the 15 MV Pelletron accelerator at the Inter-University Accelerator Centre, New Delhi. This is a new facility for in situ irradiation-induced deep level studies, available in the beam line of an accelerator laboratory. It is based on the well-known deep level transient spectroscopy (DLTS) technique. High versatility for data manipulation is achieved through multifunction data acquisition card and LABVIEW. In situ DLTS studies of deep levels produced by impact of 100 MeV Si ions on Aun-Si(100) Schottky barrier diode are presented to illustrate performance of the automated DLTS facility in the beam line.

Deep lamellar keratoplasty on air with lyophilised tissue.

PubMed Central

Chau, G K; Dilly, S A; Sheard, C E; Rostron, C K

1992-01-01

Deep lamellar keratoplasty on air involves injecting air into the corneal stroma to expand it to several times its normal thickness. This method is designed to facilitate dissection of the deep stroma and reduce the risk of perforation of Descemet's membrane when carrying out deep lamellar keratoplasty. We have modified the technique by using prelathed freeze-dried donor tissue and report our results in a series of patients with corneal stromal scarring owing to a variety of corneal problems, namely, keratoconus, pterygium, and herpes zoster ophthalmicus. All patients achieved best corrected postoperative visual acuity of 6/12 or better without problems associated with graft failure or rejection. Histopathological examination of corneal tissue following air injection showed surgical emphysema within the cornea and separation of deep stromal fibres from the underlying Descemet's membrane. Images PMID:1477037

Preparation of porous lead from shape-controlled PbO bulk by in situ electrochemical reduction in ChCl-EG deep eutectic solvent

NASA Astrophysics Data System (ADS)

Ru, Juanjian; Hua, Yixin; Xu, Cunying; Li, Jian; Li, Yan; Wang, Ding; Zhou, Zhongren; Gong, Kai

2015-12-01

Porous lead with different shapes was firstly prepared from controlled geometries of solid PbO bulk by in situ electrochemical reduction in choline chloride-ethylene glycol deep eutectic solvents at cell voltage 2.5 V and 353 K. The electrochemical behavior of PbO powders on cavity microelectrode was investigated by cyclic voltammetry. It is indicated that solid PbO can be directly reduced to metal in the solvent and a nucleation loop is apparent. Constant voltage electrolysis demonstrates that PbO pellet can be completely converted to metal for 13 h, and the current efficiency and specific energy consumption are about 87.79% and 736.82 kWh t-1, respectively. With the electro-deoxidation progress on the pellet surface, the reduction rate reaches the fastest and decreases along the distance from surface to inner center. The morphologies of metallic products are porous and mainly consisted of uniform particles which connect with each other by finer strip-shaped grains to remain the geometry and macro size constant perfectly. In addition, an empirical model of the electro-deoxidation process from spherical PbO bulk to porous lead is also proposed. These findings provide a novel and simple route for the preparation of porous metals from oxide precursors in deep eutectic solvents at room temperature.

Transcriptional analysis of sulfate reducing and chemolithoautotrophic sulfur oxidizing bacteria in the deep subseafloor.

PubMed

Orsi, William D; Barker Jørgensen, Bo; Biddle, Jennifer F

2016-08-01

Sulfate reducing bacteria (SRB) oxidize a significant proportion of subseafloor organic carbon, but their metabolic activities and subsistence mechanisms are poorly understood. Here, we report in depth phylogenetic and metabolic analyses of SRB transcripts in the Peru Margin subseafloor and interpret these results in the context of sulfate reduction activity in the sediment. Relative abundance of overall SRB gene transcripts declines strongly whereas relative abundance of ribosomal protein transcripts from sulfate reducing δ-Proteobacteria peak at 90 m below seafloor (mbsf) within a deep sulfate methane transition zone. This coincides with isotopically heavy δ(34) S values of pore water sulfate (70‰), indicating active subseafloor microbial sulfate reduction. Within the shallow sulfate reduction zone (0-5 mbsf), a transcript encoding the beta subunit of dissimilatory sulfite reductase (dsrB) was related to Desulfitobacterium dehalogenans and environmental sequences from Aarhus Bay (Denmark). At 159 mbsf we discovered a transcript encoding the reversely operating dissimilatory sulfite reductase α-subunit (rdsrA), with basal phylogenetic relation to the chemolithoautotrophic SUP05 Group II clade. A diversity of SRB transcripts involved in cellular maintenance point toward potential subsistence mechanisms under low-energy over long time periods, and provide a detailed new picture of SRB activities underlying sulfur cycling in the deep subseafloor. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Regional patterns of grey matter atrophy and magnetisation transfer ratio abnormalities in multiple sclerosis clinical subgroups: a voxel-based analysis study.

PubMed

Mallik, Shahrukh; Muhlert, Nils; Samson, Rebecca S; Sethi, Varun; Wheeler-Kingshott, Claudia A M; Miller, David H; Chard, Declan T

2015-04-01

In multiple sclerosis (MS), demyelination and neuro-axonal loss occur in the brain grey matter (GM). We used magnetic resonance imaging (MRI) measures of GM magnetisation transfer ratio (MTR) and volume to assess the regional localisation of reduced MTR (reflecting demyelination) and atrophy (reflecting neuro-axonal loss) in relapsing-remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS). A total of 98 people with MS (51 RRMS, 28 SPMS, 19 PPMS) and 29 controls had T1-weighted volumetric and magnetisation transfer scans. SPM8 was used to undertake voxel-based analysis (VBA) of GM tissue volumes and MTR. MS subgroups were compared with controls, adjusting for age and gender. A voxel-by-voxel basis correlation analysis between MTR and volume within each subject group was performed, using biological parametric mapping. MTR reduction was more extensive than atrophy. RRMS and SPMS patients showed proportionately more atrophy in the deep GM. SPMS and PPMS patients showed proportionately greater cortical MTR reduction. RRMS patients demonstrated the most correlation of MTR reduction and atrophy in deep GM. In SPMS and PPMS patients, there was less extensive correlation. These results suggest that in the deep GM of RRMS patients, demyelination and neuro-axonal loss may be linked, while in SPMS and PPMS patients, neuro-axonal loss and demyelination may occur mostly independently. © The Author(s), 2014.

Postoperative shoulder pain after laparoscopic hysterectomy with deep neuromuscular blockade and low-pressure pneumoperitoneum: A randomised controlled trial.

PubMed

Madsen, Matias V; Istre, Olav; Staehr-Rye, Anne K; Springborg, Henrik H; Rosenberg, Jacob; Lund, Jørgen; Gätke, Mona R

2016-05-01

Postoperative shoulder pain remains a significant problem after laparoscopy. Pneumoperitoneum with insufflation of carbon dioxide (CO2) is thought to be the most important cause. Reduction of pneumoperitoneum pressure may, however, compromise surgical visualisation. Recent studies indicate that the use of deep neuromuscular blockade (NMB) improves surgical conditions during a low-pressure pneumoperitoneum (8 mmHg). The aim of this study was to investigate whether low-pressure pneumoperitoneum (8 mmHg) and deep NMB (posttetanic count 0 to 1) compared with standard-pressure pneumoperitoneum (12 mmHg) and moderate NMB (single bolus of rocuronium 0.3 mg kg with spontaneous recovery) would reduce the incidence of shoulder pain and improve recovery after laparoscopic hysterectomy. A randomised, controlled, double-blinded study. Private hospital in Denmark. Ninety-nine patients. Randomisation to either deep NMB and 8 mmHg pneumoperitoneum (Group 8-Deep) or moderate NMB and 12 mmHg pneumoperitoneum (Group 12-Mod). Pain was assessed on a visual analogue scale (VAS) for 14 postoperative days. The primary endpoint was the incidence of shoulder pain during 14 postoperative days. Secondary endpoints included area under curve VAS scores for shoulder, abdominal, incisional and overall pain during 4 and 14 postoperative days; opioid consumption; incidence of nausea and vomiting; antiemetic consumption; time to recovery of activities of daily living; length of hospital stay; and duration of surgery. Shoulder pain occurred in 14 of 49 patients (28.6%) in Group 8-Deep compared with 30 of 50 (60%) patients in Group 12-Mod. Absolute risk reduction was 0.31 (95% confidence interval 0.12 to 0.48; P = 0.002). There were no differences in any secondary endpoints including area under the curve for VAS scores. Deep NMB and low-pressure pneumoperitoneum (8 mmHg) reduced the incidence of shoulder pain after laparoscopic hysterectomy in comparison to moderate NMB and standard-pressure pneumoperitoneum (12 mmHg). Clinicaltrials.gov identifier: NCT01722097.

Quality of sex life in endometriosis patients with deep dyspareunia before and after laparoscopic treatment.

PubMed

Lukic, A; Di Properzio, M; De Carlo, S; Nobili, F; Schimberni, M; Bianchi, P; Prestigiacomo, C; Moscarini, M; Caserta, D

2016-03-01

The present work aims at showing how dyspareunia linked to endometriosis can affect the life of fertile age women and how surgical treatment of endometriosis can relieve painful symptoms and consequently improve sex and social life. From a cohort of 320 women with a clinical and instrumental diagnosis of pelvic endometriosis, 67 patients were selected. These patients had deep dyspareunia that underwent laparoscopic surgical treatment. All the patients had filled out a pre- and post-surgery questionnaire. Six months after laparoscopic treatment, a significant reduction of dyspareunia was recorded, per VAS scores. A statistically significant improvement in sex life was observed between the pre- and post-surgical condition: in particular, an increased number of coituses and of non-difficult coituses, a higher number of patients who declared that pain did not negatively affect sexual pleasure and of patients achieving orgasm. The quality of the sex life in patients with endometriosis and dyspareunia showed significant improvement 6 months after laparoscopic treatment. In view of the diagnostic delay characterizing this disease and confirmed by our results, it is essential to involve a multidisciplinary team to assess all the signs and symptoms of endometriosis that may appear in a women of fertile age. This clinical approach is able to ensure a treatment that is as personalized as possible and an appropriate follow-up also with the objective of preserving reproductive performance.

Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network

NASA Astrophysics Data System (ADS)

Laloy, Eric; Hérault, Romain; Lee, John; Jacques, Diederik; Linde, Niklas

2017-12-01

Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational autoencoder type to construct a parametric low-dimensional base model parameterization of complex binary geological media. For inversion purposes, it has the attractive feature that random draws from an uncorrelated standard normal distribution yield model realizations with spatial characteristics that are in agreement with the training set. In comparison with the most commonly used parametric representations in probabilistic inversion, we find that our dimensionality reduction (DR) approach outperforms principle component analysis (PCA), optimization-PCA (OPCA) and discrete cosine transform (DCT) DR techniques for unconditional geostatistical simulation of a channelized prior model. For the considered examples, important compression ratios (200-500) are achieved. Given that the construction of our parameterization requires a training set of several tens of thousands of prior model realizations, our DR approach is more suited for probabilistic (or deterministic) inversion than for unconditional (or point-conditioned) geostatistical simulation. Probabilistic inversions of 2D steady-state and 3D transient hydraulic tomography data are used to demonstrate the DR-based inversion. For the 2D case study, the performance is superior compared to current state-of-the-art multiple-point statistics inversion by sequential geostatistical resampling (SGR). Inversion results for the 3D application are also encouraging.

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

Cramton, Karen; Peters, Katherine

With $10 million in funding from the U.S. Department of Energy's (DOE) Better Buildings Neighborhood Program, the NH Better Buildings program was established as an initiative that initially empowered the three “Beacon Communities” of Berlin, Nashua and Plymouth to achieve transformative energy savings and reductions in fossil fuel use and greenhouse gases through deep energy retrofits and complementary sustainable energy solutions. The program also enabled those Communities to provide leadership to other communities around the state as “beacons” of energy efficiency. The goal of the program was to reduce energy use by a minimum of 15% through energy efficiency upgradesmore » in residential and commercial buildings in the communities. The program expanded statewide in April 2012 by issuing a competitive solicitation for additional commercial projects non-profit, and municipal energy efficiency projects from any community in the state, and a partnership with the state’s utility-run, ratepayer-funded residential Home Performance with ENERGY STAR® (HPwES) program. The NH Better Buildings program was administered by the New Hampshire Office of Energy and Planning (OEP) and managed by the NH Community Development Finance Authority (CDFA). The program started in July 2010 and the last projects funded with American Reinvestment and Recovery Act (ARRA) funds were completed in August 2013. The program will continue after the American Recovery and Reinvestment Act program period as a Revolving Loan Fund, enabling low-interest financing for deep energy retrofits into the future.« less

Evaluation of a Progressive Mobility Protocol in Postoperative Cardiothoracic Surgical Patients.

PubMed

Floyd, Shawn; Craig, Sarah W; Topley, Darla; Tullmann, Dorothy

2016-01-01

Cardiothoracic surgical patients are at high risk for complications related to immobility, such as increased intensive care and hospital length of stay, intensive care unit readmission, pressure ulcer development, and deep vein thrombosis/pulmonary embolus. A progressive mobility protocol was started in the thoracic cardiovascular intensive care unit in a rural academic medical center. The purpose of the progressive mobility protocol was to increase mobilization of postoperative patients and decrease complications related to immobility in this unique patient population. A matched-pairs design was used to compare a randomly selected sample of the preintervention group (n = 30) to a matched postintervention group (n = 30). The analysis compared outcomes including intensive care unit and hospital length of stay, intensive care unit readmission occurrence, pressure ulcer prevalence, and deep vein thrombosis/pulmonary embolism prevalence between the 2 groups. Although this comparison does not achieve statistical significance (P < .05) for any of the outcomes measured, it does show clinical significance in a reduction in hospital length of stay, intensive care unit days, in intensive care unit readmission rate, and a decline in pressure ulcer prevalence, which is the overall goal of progressive mobility. This study has implications for nursing, hospital administration, and therapy services with regard to staffing and cost savings related to fewer complications of immobility. Future studies with a larger sample size and other populations are warranted.

The effect of ocean alkalinity and carbon transfer on deep-sea carbonate ion concentration during the past five glacial cycles

NASA Astrophysics Data System (ADS)

Kerr, Joanna; Rickaby, Rosalind; Yu, Jimin; Elderfield, Henry; Sadekov, Aleksey Yu.

2017-08-01

Glacial-interglacial deep Indo-Pacific carbonate ion concentration ([CO32-]) changes were mainly driven by two mechanisms that operated on different timescales: 1) a long-term increase during glaciation caused by a carbonate deposition reduction on shelves (i.e., the coral reef hypothesis), and 2) transient carbonate compensation responses to deep ocean carbon storage changes. To investigate these mechanisms, we have used benthic foraminiferal B/Ca to reconstruct deep-water [CO32-] in cores from the deep Indian and Equatorial Pacific Oceans during the past five glacial cycles. Based on our reconstructions, we suggest that the shelf-to-basin shift of carbonate deposition raised deep-water [CO32-], on average, by 7.3 ± 0.5 (SE) μmol/kg during glaciations. Oceanic carbon reorganisations during major climatic transitions caused deep-water [CO32-] deviations away from the long-term trend, and carbonate compensation processes subsequently acted to restore the ocean carbonate system to new steady state conditions. Deep-water [CO32-] showed similar patterns to sediment carbonate content (%CaCO3) records on glacial-interglacial timescales, suggesting that past seafloor %CaCO3 variations were dominated by deep-water carbonate preservation changes at our studied sites.

Radio Model-free Noise Reduction of Radio Transmissions with Convolutional Autoencoders

DTIC Science & Technology

2016-09-01

Encoder-Decoder Architecture for Image Segmentation .” Cornell University Library. Computing Research Repository (CoRR). abs/1511.00561. 2. Anthony J. Bell...Aaron C Courville, and Pascal Vincent. 2012. “Unsupervised Feature Learning and Deep Learning : A Review and New Perspectives.” Cornell University...Linux Journal 122(June):1–4. 5. Francois Chollet. 2015.“Keras: Deep Learning Library for TensorFlow and Theano.” Available online at https://github.com

Quantum neuromorphic hardware for quantum artificial intelligence

NASA Astrophysics Data System (ADS)

Prati, Enrico

2017-08-01

The development of machine learning methods based on deep learning boosted the field of artificial intelligence towards unprecedented achievements and application in several fields. Such prominent results were made in parallel with the first successful demonstrations of fault tolerant hardware for quantum information processing. To which extent deep learning can take advantage of the existence of a hardware based on qubits behaving as a universal quantum computer is an open question under investigation. Here I review the convergence between the two fields towards implementation of advanced quantum algorithms, including quantum deep learning.

An adaptive deep learning approach for PPG-based identification.

PubMed

Jindal, V; Birjandtalab, J; Pouyan, M Baran; Nourani, M

2016-08-01

Wearable biosensors have become increasingly popular in healthcare due to their capabilities for low cost and long term biosignal monitoring. This paper presents a novel two-stage technique to offer biometric identification using these biosensors through Deep Belief Networks and Restricted Boltzman Machines. Our identification approach improves robustness in current monitoring procedures within clinical, e-health and fitness environments using Photoplethysmography (PPG) signals through deep learning classification models. The approach is tested on TROIKA dataset using 10-fold cross validation and achieved an accuracy of 96.1%.

Deep Bleeder Acoustic Coagulation (DBAC)-part II: in vivo testing of a research prototype system.

PubMed

Sekins, K Michael; Barnes, Stephen R; Fan, Liexiang; Hopple, Jerry D; Hsu, Stephen J; Kook, John; Lee, Chi-Yin; Maleke, Caroline; Zeng, Xiaozheng Jenny; Moreau-Gobard, Romain; Ahiekpor-Dravi, Alexis; Funka-Lea, Gareth; Eaton, John; Wong, Keith; Keneman, Scott; Mitchell, Stuart B; Dunmire, Barbrina; Kucewicz, John C; Clubb, Fred J; Miller, Matthew W; Crum, Lawrence A

2015-01-01

Deep Bleeder Acoustic Coagulation (DBAC) is an ultrasound image-guided high-intensity focused ultrasound (HIFU) method proposed to automatically detect and localize (D&L) and treat deep, bleeding, combat wounds in the limbs of soldiers. A prototype DBAC system consisting of an applicator and control unit was developed for testing on animals. To enhance control, and thus safety, of the ultimate human DBAC autonomous product system, a thermal coagulation strategy that minimized cavitation, boiling, and non-linear behaviors was used. The in vivo DBAC applicator design had four therapy tiles (Tx) and two 3D (volume) imaging probes (Ix) and was configured to be compatible with a porcine limb bleeder model developed in this research. The DBAC applicator was evaluated under quantitative test conditions (e.g., bleeder depths, flow rates, treatment time limits, and dose exposure time limits) in an in vivo study (final exam) comprising 12 bleeder treatments in three swine. To quantify blood flow rates, the "bleeder" targets were intact arterial branches, i.e., the superficial femoral artery (SFA) and a deep femoral artery (DFA). D&L identified, characterized, and targeted bleeders. The therapy sequence selected Tx arrays and determined the acoustic power and Tx beam steering, focus, and scan patterns. The user interface commands consisted of two buttons: "Start D&L" and "Start Therapy." Targeting accuracy was assessed by necropsy and histologic exams and efficacy (vessel coagulative occlusion) by angiography and histology. The D&L process (Part I article, J Ther Ultrasound, 2015 (this issue)) executed fully in all cases in under 5 min and targeting evaluation showed 11 of 12 thermal lesions centered on the correct vessel subsection, with minimal damage to adjacent structures. The automated therapy sequence also executed properly, with select manual steps. Because the dose exposure time limit (t dose ≤ 30 s) was associated with nonefficacious treatment, 60-s dosing and dual-dosing was also pursued. Thrombogenic evidence (blood clotting) and collagen denaturation (vessel shrinkage) were found in necropsy and histologically in all targeted SFAs. Acute SFA reductions in blood flow (20-30 %) were achieved in one subject, and one partial and one complete vessel occlusion were confirmed angiographically. The complete occlusion case was achieved with a dual dose (90 s total exposure) with focal intensity ≈500 W/cm(2) (spatial average, temporal average). While not meeting all in vivo objectives, the overall performance of the DBAC applicator was positive. In particular, D&L automation workflow was verified during each of the tests, with processing times well under specified (10 min) limits, and all bleeder branches were detected and localized. Further, gross necropsy and tissue examination confirmed that the HIFU thermal lesions were coincident with the target vessel locations in over 90 % of the multi-array dosing treatments. The SFA/DFA bleeder models selected, and the protocols used, were the most suitable practical model options for the given DBAC anatomical and bleeder requirements. The animal models were imperfect in some challenging aspects, including requiring tissue-mimicking material (TMM) standoffs to achieve deep target depths, thereby introducing device-tissue motion, with resultant imaging artifacts. The model "bleeders" involved intact vessels, which are subject to less efficient heating and coagulation cascade behaviors than true puncture injuries.

The contribution of transport policies to the mitigation potential and cost of 2 °C and 1.5 °C goals

NASA Astrophysics Data System (ADS)

Zhang, Runsen; Fujimori, Shinichiro; Hanaoka, Tatsuya

2018-05-01

The transport sector contributes around a quarter of global CO2 emissions; thus, low-carbon transport policies are required to achieve the 2 °C and 1.5 °C targets. In this paper, representative transport policy scenarios are structured with the aim of achieving a better understanding of the interaction between the transport sector and the macroeconomy. To accomplish this, the Asia–Pacific Integrated Model/Transport (AIM/Transport) model, coupled with a computable general equilibrium model (AIM/CGE), is used to simulate the potential for different transport policy interventions to reduce emissions and cost over the period 2005–2100. The results show that deep decarbonization in the transport sector can be achieved by implementing transport policies such as energy efficiency improvements, vehicle technology innovations particularly the deployment of electric vehicles, public transport developments, and increasing the car occupancy rate. Technological transformations such as vehicle technological innovations and energy efficiency improvements provide the most significant reduction potential. The key finding is that low-carbon transport policies can reduce the carbon price, gross domestic product loss rate, and welfare loss rate generated by climate mitigation policies to limit global warming to 2 °C and 1.5 °C. Interestingly, the contribution of transport policies is more effective for stringent climate change targets in the 1.5 °C scenario, which implies that the stronger the mitigation intensity, the more transport specific policy is required. The transport sector requires attention to achieve the goal of stringent climate change mitigation.

Initial Response to Program, Program Participation, and Weight Reduction Among 375 MOVE! Participants, Augusta, Georgia, 2008-2010.

PubMed

Garvin, Jane T; Hardy, Dale; Xu, Hongyan

2016-04-21

Obesity management guidelines specify initial goals for participation and weight reduction for the first 6 months of a weight-reduction intervention, but guidelines do not specify when to assess early response and make adjustments. We aimed to determine whether very early or early weight reduction in the weight-reduction program MOVE! predicted later participation or achievement of weight-reduction goals. Using clinical data from 375 MOVE! participants enrolled from July 2008 through May 2010, we examined program participation and weight reduction. Very early response was defined as achieving a weight reduction of 0.5% or more at week 2, and early response was defined as achieving weight reduction of 1.0% or more at week 4. Success, or achievement of weight-reduction goal, at 6 months, 1 year, and 2 years was defined as a weight reduction of 5% or more. Participation was assessed according to the number of sessions attended within the first 6 months of program enrollment; attendance of 14 or more sessions was classified as high-intensity participation. Very early responders were more than 5 times as likely (odds ratio [OR] = 5.46; 95% confidence interval [CI], 1.69-17.71; P = .005) and early responders were more than 10 times as likely (OR = 10.76; 95% CI, 2.64-43.80; P = .001) to achieve the 6-month weight-reduction goal as participants who were not very early responders or early responders, respectively. Early responders were almost 7 times as likely to achieve the 1-year weight-reduction goal (OR = 6.96; 95% CI, 1.85-26.13; P = .004). Neither very early nor early response predicted participation, high-intensity participation, or success at 2 years. This research supports the predictive value of very early response and early response to MOVE! on weight-reduction success at 6 months; early response also predicted 1-year success, suggesting that the 2-week point may be an ideal time to assess initial response and make intervention adjustments.

Initial Response to Program, Program Participation, and Weight Reduction Among 375 MOVE! Participants, Augusta, Georgia, 2008–2010

PubMed Central

Hardy, Dale; Xu, Hongyan

2016-01-01

Introduction Obesity management guidelines specify initial goals for participation and weight reduction for the first 6 months of a weight-reduction intervention, but guidelines do not specify when to assess early response and make adjustments. We aimed to determine whether very early or early weight reduction in the weight-reduction program MOVE! predicted later participation or achievement of weight-reduction goals. Methods Using clinical data from 375 MOVE! participants enrolled from July 2008 through May 2010, we examined program participation and weight reduction. Very early response was defined as achieving a weight reduction of 0.5% or more at week 2, and early response was defined as achieving weight reduction of 1.0% or more at week 4. Success, or achievement of weight-reduction goal, at 6 months, 1 year, and 2 years was defined as a weight reduction of 5% or more. Participation was assessed according to the number of sessions attended within the first 6 months of program enrollment; attendance of 14 or more sessions was classified as high-intensity participation. Results Very early responders were more than 5 times as likely (odds ratio [OR] = 5.46; 95% confidence interval [CI], 1.69–17.71; P = .005) and early responders were more than 10 times as likely (OR = 10.76; 95% CI, 2.64–43.80; P = .001) to achieve the 6-month weight-reduction goal as participants who were not very early responders or early responders, respectively. Early responders were almost 7 times as likely to achieve the 1-year weight-reduction goal (OR = 6.96; 95% CI, 1.85–26.13; P = .004). Neither very early nor early response predicted participation, high-intensity participation, or success at 2 years. Conclusion This research supports the predictive value of very early response and early response to MOVE! on weight-reduction success at 6 months; early response also predicted 1-year success, suggesting that the 2-week point may be an ideal time to assess initial response and make intervention adjustments. PMID:27103265

Distribution of microbial methanogenesis, methane oxidation, and sulfate reduction in a high-temperature subduction system of the Nankai Trough off Cape Muroto (IODP Expedition 370 T-Limit, Site C0023)

NASA Astrophysics Data System (ADS)

Treude, T.; Kallmeyer, J.; Beulig, F.; Glombitza, C.; Schubert, F.; Krause, S.; Heuer, V.; Inagaki, F.; Morono, Y.

2017-12-01

The aim of the IODP Expedition 370 is to explore the temperature limit of the deep biosphere in a sub-seafloor environment located in the Nankai Trough, where in-situ sediment temperature increases from 2°C at the seafloor to about 120°C at the 1.2 km deep sediment/basement interface. Our study focuses on the exploration of potential microbial methanogenesis, anaerobic oxidation of methane (AOM), and sulfate reduction in sediments from different depths (from ca. 200 to 1170 mbsf) exposed to several temperature settings in the laboratory (40, 60, 75/80 and 95°C). The drill site, which features a décollement between ca. 758-796 mbsf, includes a sulfate-poor methanogenic zone from approx. 400 to 600 mbsf, followed by a deep methane-sulfate transition zone between approx. 600 to 800 m, which transitions into a deep sulfate-rich zone. Potential microbial activity of hydrogenotrophic methanogenesis, AOM, and sulfate reduction was determined in incubations of sediment slurries produced from whole-round cores with H2-added artificial seawater medium using radioisotope techniques (14C-bicarbonate, 14C-methane, and 35S-sulfate, respectively). Preliminary results revealed two peaks of methanogenesis activity with rates in the order of 0.2 to 0.5 pmol g-1dw d-1. One peak was located within the methane-rich zone passing into the methane-sulfate transition zone (60 to 80°C incubations), while the second peak occurred close to the basement (below 1000 mbsf, 95°C incubation). Sulfate reduction activity was generally highest above 400 mbsf ( 1000 pmol cm-3 d-1, 40°C incubation). Below 400 mbsf, rates declined to levels between 0.1 and 10 pmol cm-3 d-1 (60-95 °C incubations) without a clear trend and continued until close to the bottom of the core. The results point to potentially thermophilic and hypothermophilic microorganisms that exist under very low energy conditions. Samples from AOM incubations are currently being processed and preliminary results will be presented at the meeting as well as the results for sulfate reduction incubations with methane and acetate amendments.

Examining Learning Approaches of Science Student Teachers According to the Class Level and Gender

ERIC Educational Resources Information Center

Tural Dincer, Guner; Akdeniz, Ali Riza

2008-01-01

There are many factors influence the level of students' achievement in education. Studies show that one of these factors is "learning approach of a student". Research findings generally have identified two approaches of learning: deep and surface. When a student uses the deep approach, he/she has an intrinsic interest in subject matter and is…

Intervertebral disc detection in X-ray images using faster R-CNN.

PubMed

Ruhan Sa; Owens, William; Wiegand, Raymond; Studin, Mark; Capoferri, Donald; Barooha, Kenneth; Greaux, Alexander; Rattray, Robert; Hutton, Adam; Cintineo, John; Chaudhary, Vipin

2017-07-01

Automatic identification of specific osseous landmarks on the spinal radiograph can be used to automate calculations for correcting ligament instability and injury, which affect 75% of patients injured in motor vehicle accidents. In this work, we propose to use deep learning based object detection method as the first step towards identifying landmark points in lateral lumbar X-ray images. The significant breakthrough of deep learning technology has made it a prevailing choice for perception based applications, however, the lack of large annotated training dataset has brought challenges to utilizing the technology in medical image processing field. In this work, we propose to fine tune a deep network, Faster-RCNN, a state-of-the-art deep detection network in natural image domain, using small annotated clinical datasets. In the experiment we show that, by using only 81 lateral lumbar X-Ray training images, one can achieve much better performance compared to traditional sliding window detection method on hand crafted features. Furthermore, we fine-tuned the network using 974 training images and tested on 108 images, which achieved average precision of 0.905 with average computation time of 3 second per image, which greatly outperformed traditional methods in terms of accuracy and efficiency.

Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients

NASA Astrophysics Data System (ADS)

Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J.

2018-02-01

Predicting mutation/loss of alpha-thalassemia/mental retardation syndrome X-linked (ATRX) gene utilizing MR imaging is of high importance since it is a predictor of response and prognosis in brain tumors. In this study, we compare a deep neural network approach based on a residual deep neural network (ResNet) architecture and one based on a classical machine learning approach and evaluate their ability in predicting ATRX mutation status without the need for a distinct tumor segmentation step. We found that the ResNet50 (50 layers) architecture, pre trained on ImageNet data was the best performing model, achieving an accuracy of 0.91 for the test set (classification of a slice as no tumor, ATRX mutated, or mutated) in terms of f1 score in a test set of 35 cases. The SVM classifier achieved 0.63 for differentiating the Flair signal abnormality regions from the test patients based on their mutation status. We report a method that alleviates the need for extensive preprocessing and acts as a proof of concept that deep neural network architectures can be used to predict molecular biomarkers from routine medical images.

Design and Analysis of a Flexible, Reliable Deep Space Life Support System

NASA Technical Reports Server (NTRS)

Jones, Harry W.

2012-01-01

This report describes a flexible, reliable, deep space life support system design approach that uses either storage or recycling or both together. The design goal is to provide the needed life support performance with the required ultra reliability for the minimum Equivalent System Mass (ESM). Recycling life support systems used with multiple redundancy can have sufficient reliability for deep space missions but they usually do not save mass compared to mixed storage and recycling systems. The best deep space life support system design uses water recycling with sufficient water storage to prevent loss of crew if recycling fails. Since the amount of water needed for crew survival is a small part of the total water requirement, the required amount of stored water is significantly less than the total to be consumed. Water recycling with water, oxygen, and carbon dioxide removal material storage can achieve the high reliability of full storage systems with only half the mass of full storage and with less mass than the highly redundant recycling systems needed to achieve acceptable reliability. Improved recycling systems with lower mass and higher reliability could perform better than systems using storage.

Manifestations of drag reduction by polymer additives in decaying, homogeneous, isotropic turbulence.

PubMed

Perlekar, Prasad; Mitra, Dhrubaditya; Pandit, Rahul

2006-12-31

The existence of drag reduction by polymer additives, well established for wall-bounded turbulent flows, is controversial in homogeneous, isotropic turbulence. To settle this controversy, we carry out a high-resolution direct numerical simulation of decaying, homogeneous, isotropic turbulence with polymer additives. Our study reveals clear manifestations of drag-reduction-type phenomena: On the addition of polymers to the turbulent fluid, we obtain a reduction in the energy-dissipation rate, a significant modification of the fluid energy spectrum especially in the deep-dissipation range, a suppression of small-scale intermittency, and a decrease in small-scale vorticity filaments.

DRREP: deep ridge regressed epitope predictor.

PubMed

Sher, Gene; Zhi, Degui; Zhang, Shaojie

2017-10-03

The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been numerous advancements and improvements in epitope prediction, on average the best benchmark prediction accuracies are still only around 60%. New machine learning algorithms have arisen within the domain of deep learning, text mining, and convolutional networks. This paper presents a novel analytically trained and string kernel using deep neural network, which is tailored for continuous epitope prediction, called: Deep Ridge Regressed Epitope Predictor (DRREP). DRREP was tested on long protein sequences from the following datasets: SARS, Pellequer, HIV, AntiJen, and SEQ194. DRREP was compared to numerous state of the art epitope predictors, including the most recently published predictors called LBtope and DMNLBE. Using area under ROC curve (AUC), DRREP achieved a performance improvement over the best performing predictors on SARS (13.7%), HIV (8.9%), Pellequer (1.5%), and SEQ194 (3.1%), with its performance being matched only on the AntiJen dataset, by the LBtope predictor, where both DRREP and LBtope achieved an AUC of 0.702. DRREP is an analytically trained deep neural network, thus capable of learning in a single step through regression. By combining the features of deep learning, string kernels, and convolutional networks, the system is able to perform residue-by-residue prediction of continues epitopes with higher accuracy than the current state of the art predictors.

Limitations of Reliability for Long-Endurance Human Spaceflight

NASA Technical Reports Server (NTRS)

Owens, Andrew C.; de Weck, Olivier L.

2016-01-01

Long-endurance human spaceflight - such as missions to Mars or its moons - will present a never-before-seen maintenance logistics challenge. Crews will be in space for longer and be farther way from Earth than ever before. Resupply and abort options will be heavily constrained, and will have timescales much longer than current and past experience. Spare parts and/or redundant systems will have to be included to reduce risk. However, the high cost of transportation means that this risk reduction must be achieved while also minimizing mass. The concept of increasing system and component reliability is commonly discussed as a means to reduce risk and mass by reducing the probability that components will fail during a mission. While increased reliability can reduce maintenance logistics mass requirements, the rate of mass reduction decreases over time. In addition, reliability growth requires increased test time and cost. This paper assesses trends in test time requirements, cost, and maintenance logistics mass savings as a function of increase in Mean Time Between Failures (MTBF) for some or all of the components in a system. In general, reliability growth results in superlinear growth in test time requirements, exponential growth in cost, and sublinear benefits (in terms of logistics mass saved). These trends indicate that it is unlikely that reliability growth alone will be a cost-effective approach to maintenance logistics mass reduction and risk mitigation for long-endurance missions. This paper discusses these trends as well as other options to reduce logistics mass such as direct reduction of part mass, commonality, or In-Space Manufacturing (ISM). Overall, it is likely that some combination of all available options - including reliability growth - will be required to reduce mass and mitigate risk for future deep space missions.

Reduction of cardiac and pulmonary complication probabilities after breathing adapted radiotherapy for breast cancer

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

Korreman, Stine S.; Pedersen, Anders N.; Aarup, Lasse Rye

Purpose: Substantial reductions of cardio-pulmonary radiation doses can be achieved using voluntary deep inspiration breath-hold (DIBH) or free breathing inspiration gating (IG) in radiotherapy after conserving surgery for breast cancer. The purpose of this study is to evaluate the radiobiological implications of such dosimetric benefits. Methods and Materials: Patients from previously reported studies were pooled for a total of 33 patients. All patients underwent DIBH and free breathing (FB) scans, and 17 patients underwent an additional IG scan. Tangential conformal treatment plans covering the remaining breast, internal mammary, and periclavicular nodes were optimized for each scan, prescription dose 48 Gy.more » Normal tissue complication probabilities were calculated using the relative seriality model for the heart, and the model proposed by Burman et al. for the lung. Results: Previous computed tomography studies showed that both voluntary DIBH and IG provided reduction of the lung V{sub 5} (relative volume receiving more than 50% of prescription dose) on the order of 30-40%, and a 80-90% reduction of the heart V{sub 5} for left-sided cancers. Corresponding pneumonitis probability of 28.1% (range, 0.7-95.6%) for FB could be reduced to 2.6% (range, 0.1-40.1%) for IG, and 4.3% (range, 0.1-59%) for DIBH. The cardiac mortality probability could be reduced from 4.8% (range, 0.1-23.4%) in FB to 0.5% (range, 0.1-2.6%) for IG and 0.1% (range, 0-3.0%) for DIBH. Conclusions: Remarkable potential is shown for simple voluntary DIBH and free breathing IG to reduce the risk of both cardiac mortality and pneumonitis for the common technique of adjuvant tangential breast irradiation.« less

In Situ Scanning Tunneling Microscopy Topography Changes of Gold (111) in Aqueous Sulfuric Acid Produced by Electrochemical Surface Oxidation and Reduction and Relaxation Phenomena

NASA Astrophysics Data System (ADS)

Pasquale, M. A.; Nieto, F. J. Rodríguez; Arvia, A. J.

The electrochemical formation and reduction of O-layers on gold (111) films in 1 m sulfuric acid under different potentiodynamic routines are investigated utilizing in situ scanning tunneling microscopy. The surface dynamics is interpreted considering the anodic and cathodic reaction pathways recently proposed complemented with concurrent relaxation phenomena occurring after gold (111) lattice mild disruption (one gold atom deep) and moderate disruption (several atoms deep). The dynamics of both oxidized and reduced gold topographies depends on the potentiodynamic routine utilized to form OH/O surface species. The topography resulting from a mild oxidative disruption is dominated by quasi-2D holes and hillocks of the order of 5 nm, involving about 500-600 gold atoms each, and their coalescence. A cooperative turnover process at the O-layer, in which the anion ad-layer and interfacial water play a key role, determines the oxidized surface topography. The reduction of these O-layers results in gold clusters, their features depending on the applied potential routine. A moderate oxidative disruption produces a surface topography of hillocks and holes several gold atoms high and deep, respectively. The subsequent reduction leads to a spinodal gold pattern. Concurrent coalescence appears to be the result of an Ostwald ripening that involves the surface diffusion of both gold atoms and clusters. These processes produce an increase in surface roughness and an incipient gold faceting. The dynamics of different topographies can be qualitatively explained employing the arguments from colloidal science theory. For 1.1 V ≤ E ≅ Epzc weak electrostatic repulsions favor gold atom/cluster coalescence, whereas for E < Epzc the attenuated electrostatic repulsions among gold surfaces stabilize small clusters over the substrate producing string-like patterns.

Effect of deep injection on field-scale emissions of 1,3-dichloropropene and chloropicrin from bare soil

NASA Astrophysics Data System (ADS)

Yates, S. R.; Ashworth, D. J.; Zheng, W.; Knuteson, J.; van Wesenbeeck, I. J.

2016-07-01

Fumigating soil is important for the production of many high-value vegetable, fruit, and tree crops, but fumigants are toxic pesticides with relatively high volatility, which can lead to significant atmospheric emissions. A field experiment was conducted to measure emissions and subsurface diffusion of a mixture of 1,3-dichloropropene (1,3-D) and chloropicrin after shank injection to bare soil at 61 cm depth (i.e., deep injection). Three on-field methods, the aerodynamic (ADM), integrated horizontal flux (IHF), and theoretical profile shape (TPS) methods, were used to obtain fumigant flux density and cumulative emission values. Two air dispersion models (CALPUFF and ISCST3) were also used to back-calculate the flux density using air concentration measurements surrounding the fumigated field. Emissions were continuously measured for 16 days and the daily peak emission rates for the five methods ranged from 13 to 33 μg m-2 s-1 for 1,3-D and 0.22-3.2 μg m-2 s-1 for chloropicrin. Total 1,3-D mass lost to the atmosphere was approximately 23-41 kg ha-1, or 15-27% of the applied active ingredient and total mass loss of chloropicrin was <2%. Based on the five methods, deep injection reduced total emissions by approximately 2-24% compared to standard fumigation practices where fumigant injection is at 46 cm depth. Given the relatively wide range in emission-reduction percentages, a fumigant diffusion model was used to predict the percentage reduction in emissions by injecting at 61 cm, which yielded a 21% reduction in emissions. Significant reductions in emissions of 1,3-D and chloropicrin are possible by injecting soil fumigants deeper in soil.

30 CFR 203.60 - Who may apply for royalty relief on a case-by-case basis in deep water in the Gulf of Mexico or...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Who may apply for royalty relief on a case-by-case basis in deep water in the Gulf of Mexico or offshore of Alaska? 203.60 Section 203.60 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE INTERIOR MINERALS REVENUE MANAGEMENT RELIEF OR REDUCTION IN ROYALTY RATES OCS Oil, Gas, and...

Policy Implications of Deep Decarbonization in the United States

NASA Astrophysics Data System (ADS)

Williams, J.

2015-12-01

Independent research teams from sixteen of the largest greenhouse gas (GHG) emitting countries have participated in a collaborative two-year project developing emission reduction scenarios for their own countries consistent with limiting anthropogenic warming to 2 C or less. This talk discusses the policy implications of the work done by the Deep Decarbonization Pathways Project (DDPP) at the US federal and international levels, including new ways of informing decision makers about the requirements of an energy system transformation.

A metagenomic window into carbon metabolism at 3 km depth in Precambrian continental crust

PubMed Central

Magnabosco, Cara; Ryan, Kathleen; Lau, Maggie C Y; Kuloyo, Olukayode; Sherwood Lollar, Barbara; Kieft, Thomas L; van Heerden, Esta; Onstott, Tullis C

2016-01-01

Subsurface microbial communities comprise a significant fraction of the global prokaryotic biomass; however, the carbon metabolisms that support the deep biosphere have been relatively unexplored. In order to determine the predominant carbon metabolisms within a 3-km deep fracture fluid system accessed via the Tau Tona gold mine (Witwatersrand Basin, South Africa), metagenomic and thermodynamic analyses were combined. Within our system of study, the energy-conserving reductive acetyl-CoA (Wood-Ljungdahl) pathway was found to be the most abundant carbon fixation pathway identified in the metagenome. Carbon monoxide dehydrogenase genes that have the potential to participate in (1) both autotrophic and heterotrophic metabolisms through the reversible oxidization of CO and subsequent transfer of electrons for sulfate reduction, (2) direct utilization of H2 and (3) methanogenesis were identified. The most abundant members of the metagenome belonged to Euryarchaeota (22%) and Firmicutes (57%)—by far, the highest relative abundance of Euryarchaeota yet reported from deep fracture fluids in South Africa and one of only five Firmicutes-dominated deep fracture fluids identified in the region. Importantly, by combining the metagenomics data and thermodynamic modeling of this study with previously published isotopic and community composition data from the South African subsurface, we are able to demonstrate that Firmicutes-dominated communities are associated with a particular hydrogeologic environment, specifically the older, more saline and more reducing waters. PMID:26325359

Bitumen recovery from oil sands using deep eutectic solvent and its aqueous solutions

NASA Astrophysics Data System (ADS)

Pulati, Nuerxida

Oil sands compose a significant proportion of the world's known oil reserves. Oil sands are also known as tar sands and bituminous sands, are complex mixtures of sand, clays, water and bitumen, which is "heavy" and highly viscous oil. The extraction and separation of bitumen from oil sands requires significant amount of energy and large quantities of water and poses several environmental challenges. Bitumen can be successfully separated from oil sands using imidazolium based ionic liquids and nonpolar solvents, however, ionic liquids are expensive and toxic. In this thesis, the ionic liquid alternatives- deep eutectic solvent, were investigated. Oil sands separation can be successfully achieved by using deep eutectic solvents DES (choline chloride and urea) and nonpolar solvent naphtha in different types of oil sands, including Canadian ("water-wet"), Utah ("oil-wet") and low grade Kentucky oil sands. The separation quality depends on oil sands type, including bitumen and fine content, and separation condition, such as solvent ratio, temperature, mixing time and mechanical centrifuge. This separation claims to the DES ability to form ion /charge layering on mineral surface, which results in reduction of adhesion forces between bitumen and minerals and promote their separation. Addition of water to DES can reduce DES viscosity. DES water mixture as a media, oil sands separation can be achieved. However, concentration at about 50 % or higher might be required to obtain a clear separation. And the separation efficiency is oil sands sample dependent. The highest bitumen extraction yield happened at 75% DES-water solution for Utah oil sands samples, and at 50 60% DES-water solutions for Alberta oil sands samples. Force curves were measured using Atomic Force Microscopy new technique, PeakForce Tapping Quantitative Nanomechanical Mapping (PFTQNM). The results demonstrate that, by adding DES, the adhesion force between bitumen and silica and dissipation energy will decrease comparing to DI water. At higher concentration DES solution (>80%DES), the amount of decrease can be up to 80-90%. In lower concentration, at about 50% decrease was observed. The results provide fundamental insights into the mechanism of bitumen separation from oil sands. The reduction of adhesion force between bitumen and minerals (silica) in DES media is the main reason which facilitates the separation between them, which by means existence of DES will favor bitumen and minerals separation. Comparing to other techniques, DES based separation is environmentally compatible and economically viable. The separation can easily happen at room temperature. Choline chloride and urea are biodegradable, environmentally compatible, accessible in large scale and easily prepared by mixing and heating (<80 °C). Further improvement is needed regarding to separation quality and efficiency, either in the direction of developing better separation techniques or by looking for chemical additives which can improve separation and reduce environmental side-effects.

High-resolution velocimetry in energetic tidal currents using a convergent-beam acoustic Doppler profiler

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

Sellar, Brian; Harding, Samuel F.; Richmond, Marshall C.

An array of convergent acoustic Doppler velocimeters has been developed and tested for the high resolution measurement of three-dimensional tidal flow velocities in an energetic tidal site. This configuration has been developed to increase spatial resolution of velocity measurements in comparison to conventional acoustic Doppler profilers (ADPs) which characteristically use diverging acoustic beams emanating from a single instrument. This is achieved using converging acoustic beams with a sample volume at the focal point of 0.03 m 3. The array is also able to simultaneously measure three-dimensional velocity components in a profile throughout the water column, and as such is referredmore » to herein as a converging-beam acoustic Doppler profiler (CADP). Mid-depth profiling is achieved through integration of the sensor platform with the operational Alstom 1MW DeepGen-IV Tidal Turbine. This proof-of-concept paper outlines system configuration and comparison to measurements provided by co-installed reference instrumentation. Comparison of CADP to standard ADP velocity measurements reveals a mean difference of 8 mm/s, standard deviation of 18 mm/s, and order-of-magnitude reduction in realizable length-scale. CADP focal point measurements compared to a proximal single-beam reference show peak cross-correlation coefficient of 0.96 over 4.0 s averaging period and a 47% reduction in Doppler noise. The dual functionality of the CADP as a profiling instrument with a high resolution focal point make this configuration a unique and valuable advancement in underwater velocimetry enabling improved turbulence, resource and structural loading quantification and validation of numerical simulations. Alternative modes of operation have been implemented including noise-reducing bi-static sampling. Since waves are simultaneously measured it is expected that derivatives of this system will be a powerful tool in wave-current interaction studies.« less

Single-Stage Resection of Type II Constriction Rings in Limbs on the Basis of Histologic and Magnetic Resonance Imaging Observations: A Retrospective Study of 21 Consecutive Patients.

PubMed

Jiang, Yongkang; Mao, Hailei; Yang, Xi; Zhou, Shengbo; Ni, Feng; Xu, Qiming; Wang, Bin

2016-07-01

The purpose of this study was to determine the feasibility of single-stage resection for type II congenital constriction rings by means of histologic examination of resected specimens and imaging examination of affected extremities, and to evaluate the appearance and function of the extremities after single-stage surgery. The features of the skin on the constriction rings and the subcutaneous tissues were identified through continuous sectioning, hematoxylin and eosin staining, and immunohistologic staining of specimens of type II constriction rings obtained by means of surgery. The relationship between the constriction rings and the deep main blood vessels was evaluated using magnetic resonance imaging. Single-stage resection of the constriction band, reduction of the fascial flap, and triangular flap-plasty were performed for 21 patients. The appearance, lymphedema, and movement of the extremities were compared before and after the operation. Type II constriction rings in the extremities had normal full-layer skin structures. Collagen was found deposited densely at the base of the grooves, but the normal subcutaneous tissue space remained, and the vital nerves and blood vessels were unaffected. Complete resection of the constriction rings was achieved in all 21 patients, and lymphedema subsided 2 months after the operation. No episode of recurrence was found, and limb function was not affected at 26-month follow-up. Type II congenital constriction rings in limbs possess normal subcutaneous tissue spaces. A single-stage operation, which includes complete resection of the rings, fascial flap reduction, and triangular flap-plasty, could achieve a satisfactory appearance and good function. Therapeutic, III.

A Novel Technique for Closed Reduction and Fixation of Paediatric Calcaneal Fracture Dislocation Injuries

PubMed Central

Faroug, Radwane; Stirling, Paul; Ali, Farhan

2013-01-01

Paediatric calcaneal fractures are rare injuries usually managed conservatively or with open reduction and internal fixation (ORIF). Closed reduction was previously thought to be impossible, and very few cases are reported in the literature. We report a new technique for closed reduction using Ilizarov half-rings. We report successful closed reduction and screwless fixation of an extra-articular calcaneal fracture dislocation in a 7-year-old boy. Reduction was achieved using two Ilizarov half-ring frames arranged perpendicular to each other, enabling simultaneous application of longitudinal and rotational traction. Anatomical reduction was achieved with restored angles of Bohler and Gissane. Two K-wires were the definitive fixation. Bony union with good functional outcome and minimal pain was achieved at eight-weeks follow up. ORIF of calcaneal fractures provides good functional outcome but is associated with high rates of malunion and postoperative pain. Preservation of the unique soft tissue envelope surrounding the calcaneus reduces the risk of infection. Closed reduction prevents distortion of these tissues and may lead to faster healing and mobilisation. Closed reduction and screwless fixation of paediatric calcaneal fractures is an achievable management option. Our technique has preserved the soft tissue envelope surrounding the calcaneus, has avoided retained metalwork related complications, and has resulted in a good functional outcome. PMID:23819090

Chronic sleep reduction is associated with academic achievement and study concentration in higher education students.

PubMed

van der Heijden, Kristiaan B; Vermeulen, Marije C M; Donjacour, Claire E H M; Gordijn, Marijke C M; Hamburger, Hans L; Meijer, Anne M; van Rijn, Karin J; Vlak, Monique; Weysen, Tim

2018-04-01

Inadequate sleep impairs cognitive function and has been associated with worse academic achievement in higher education students; however, studies that control for relevant background factors and include knowledge on sleep hygiene are scarce. This study examined the association of chronic sleep reduction (i.e. symptoms of chronic sleep reduction such as shortness of sleep, sleepiness and irritation), subjective sleep quality and sleep hygiene knowledge with academic achievement (grades and study credits) and study concentration among 1378 higher education students (71% female, mean age 21.73 years, SD = 3.22) in the Netherlands. Demographic, health, lifestyle and study behaviour characteristics were included as covariates in hierarchical regression analyses. After controlling for significant covariates, only chronic sleep reduction remained a significant predictor of lower grades (last exam, average in current academic year). Better sleep quality and sleep hygiene knowledge were associated with better academic achievement, but significance was lost after controlling for covariates, except for a remaining positive association between sleep hygiene beliefs and grades in the current academic year. Moreover, better sleep quality and lower scores on chronic sleep reduction were associated with better study concentration after controlling for significant covariates. To conclude, chronic sleep reduction is associated with academic achievement and study concentration in higher education students. Inadequate sleep hygiene knowledge is moderately associated with worse academic achievement. Future research should investigate whether sleep hygiene interventions improve academic achievement in students of higher education. © 2017 European Sleep Research Society.

Deep molecular responses for treatment-free remission in chronic myeloid leukemia.

PubMed

Dulucq, Stéphanie; Mahon, Francois-Xavier

2016-09-01

Several clinical trials have demonstrated that some patients with chronic myeloid leukemia in chronic phase (CML-CP) who achieve sustained deep molecular responses on tyrosine kinase inhibitor (TKI) therapy can safely suspend therapy and attempt treatment-free remission (TFR). Many TFR studies to date have enrolled imatinib-treated patients; however, the feasibility of TFR following nilotinib or dasatinib has also been demonstrated. In this review, we discuss available data from TFR trials and what these data reveal about the molecular biology of TFR. With an increasing number of ongoing TFR clinical trials, TFR may become an achievable goal for patients with CML-CP. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Deep sub-wavelength ultrasonic imaging

NASA Astrophysics Data System (ADS)

Amireddy, Kiran Kumar; Balasubramaniam, Krishnan; Rajagopal, Prabhu

2018-04-01

There is much interest in improving the resolution of ultrasonic inspection, which suffers from large wavelengths typically in the range of millimeters, due to low value of speed of sound in solid media. The authors are interested in achieving this through holey structured metamaterial lenses, and have recently demonstrated an experimental subwavelength resolution of λ/25. However the previous work was in through-transmission mode with reception using Laser Doppler Vibrometer (LDV), which may not be suitable for practical applications. This paper discusses the use of optimized holey structured metalens to achieve a deep sub-wavelength imaging up to λ/18 in through-transmission mode, but using commercially available piezoelectric ultrasonic transducers for both generation and reception of ultrasound.

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning.

PubMed

Teng, Haotian; Cao, Minh Duc; Hall, Michael B; Duarte, Tania; Wang, Sheng; Coin, Lachlan J M

2018-05-01

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

Particle Swarm Optimization for Programming Deep Brain Stimulation Arrays

PubMed Central

Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

2017-01-01

Objective Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main Results The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (≤9.2%) and ROA (≤1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n=3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of <1% between approaches. Significance The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts. PMID:28068291

Particle swarm optimization for programming deep brain stimulation arrays

NASA Astrophysics Data System (ADS)

Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

2017-02-01

Objective. Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main results. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of  <1% between approaches. Significance. The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.

Use of the 37-38 GHz and 40-40.5 GHz Ka-bands for Deep Space Communications

NASA Technical Reports Server (NTRS)

Morabito, David; Hastrup, Rolf

2004-01-01

This paper covers a wide variety of issues associated with the implementation and use of these frequency bands for deep space communications. Performance issues, such as ground station pointing stability, ground antenna gain, antenna pattern, and propagation effects such as due to atmospheric, charged-particle and space loss at 37 GHz, will be addressed in comparison to the 32 GHz Ka-band deep space allocation. Issues with the use of and competition for this spectrum also will be covered. The state of the hardware developed (or proposed) for operating in this frequency band will be covered from the standpoint of the prospects for achieving higher data rates that could be accommodated in the available bandwidth. Hardware areas to be explored include modulators, digital-to-analog converters, filters, power amplifiers, receivers, and antennas. The potential users of the frequency band will be explored as well as their anticipated methods to achieve the potential high data rates and the implications of the competition for bandwidth.

Nuclear Thermal Rocket - Arc Jet Integrated System Model

NASA Technical Reports Server (NTRS)

Taylor, Brian D.; Emrich, William

2016-01-01

In the post-shuttle era, space exploration is moving into a new regime. Commercial space flight is in development and is planned to take on much of the low earth orbit space flight missions. With the development of a heavy lift launch vehicle, the Space Launch, System, NASA has become focused on deep space exploration. Exploration into deep space has traditionally been done with robotic probes. More ambitious missions such as manned missions to asteroids and Mars will require significant technology development. Propulsion system performance is tied to the achievability of these missions and the requirements of other developing technologies that will be required. Nuclear thermal propulsion offers a significant improvement over chemical propulsion while still achieving high levels of thrust. Opportunities exist; however, to build upon what would be considered a standard nuclear thermal engine to attain improved performance, thus further enabling deep space missions. This paper discuss the modeling of a nuclear thermal system integrated with an arc jet to further augment performance. The performance predictions and systems impacts are discussed.

Analysis of automatic repeat request methods for deep-space downlinks

NASA Technical Reports Server (NTRS)

Pollara, F.; Ekroot, L.

1995-01-01

Automatic repeat request (ARQ) methods cannot increase the capacity of a memoryless channel. However, they can be used to decrease the complexity of the channel-coding system to achieve essentially error-free transmission and to reduce link margins when the channel characteristics are poorly predictable. This article considers ARQ methods on a power-limited channel (e.g., the deep-space channel), where it is important to minimize the total power needed to transmit the data, as opposed to a bandwidth-limited channel (e.g., terrestrial data links), where the spectral efficiency or the total required transmission time is the most relevant performance measure. In the analysis, we compare the performance of three reference concatenated coded systems used in actual deep-space missions to that obtainable by ARQ methods using the same codes, in terms of required power, time to transmit with a given number of retransmissions, and achievable probability of word error. The ultimate limits of ARQ with an arbitrary number of retransmissions are also derived.

Motivation, Cognitive Processing and Achievement in Higher Education

ERIC Educational Resources Information Center

Bruinsma, Marjon

2004-01-01

This study investigated the question of whether a student's expectancy, values and negative affect influenced their deep information processing approach and achievement at the end of the first and second academic year. Five hundred and sixty-five first-year students completed a self-report questionnaire on three different occasions. The…

A Model of Metacognition, Achievement Goal Orientation, Learning Style and Self-Efficacy

ERIC Educational Resources Information Center

Coutinho, Savia A.; Neuman, George

2008-01-01

Structural equation modelling was used to test a model integrating achievement goal orientation, learning style, self-efficacy and metacognition into a single framework that explained and predicted variation in performance. Self-efficacy was the strongest predictor of performance. Metacognition was a weak predictor of performance. Deep processing…

Exploring Students' Reflective Thinking Practice, Deep Processing Strategies, Effort, and Achievement Goal Orientations

ERIC Educational Resources Information Center

Phan, Huy Phuong

2009-01-01

Recent research indicates that study processing strategies, effort, reflective thinking practice, and achievement goals are important factors contributing to the prediction of students' academic success. Very few studies have combined these theoretical orientations within one conceptual model. This study tested a conceptual model that included, in…

The Effect of Personal and School-Wide Goals on Deep Processing Strategies of At-Risk, Not At-Risk and Special Education Students.

ERIC Educational Resources Information Center

Anderman, Eric M.

Middle school students (N=712) were surveyed about their achievement goals and cognitive processing strategies. Results suggest that academically at-risk students use deep strategies less and are less learning focused than not at-risk and special education students. Special education and at-risk students tended to be more ability-focused than not…

Articulatory Closure Proficiency in Patients with Parkinson's Disease Following Deep Brain Stimulation of the Subthalamic Nucleus and Caudal Zona Incerta

ERIC Educational Resources Information Center

Karlsson, Fredrik; Olofsson, Katarina; Blomstedt, Patric; Linder, Jan; Nordh, Erik; van Doorn, Jan

2014-01-01

Purpose: The present study aimed at comparing the effects of deep brain stimulation (DBS) treatment of the subthalamic nucleus (STN) and the caudal zona incerta (cZi) on the proficiency in achieving oral closure and release during plosive production of people with Parkinson's disease. Method: Nineteen patients participated preoperatively and…

Fluid Management of and Flame Spread Across Liquid Pools

NASA Technical Reports Server (NTRS)

Ross, H. D.; Miller, F. J.

2001-01-01

The goal of our research on flame spread across pools of liquid fuel remains the quantitative identification of the mechanisms that control the rate and nature of flame spread when the initial temperature of the liquid pool is below the fuel's flash point temperature. As described in, four microgravity (mu-g) sounding rocket flights examined the effect of forced opposed airflow over a 2.5 cm deep x 2 cm wide x 30 cm long pool of 1-butanol. Among many unexpected findings, it was observed that the flame spread is much slower and steadier than in 1g where flame spread has a pulsating character. Our numerical model, restricted to two dimensions, had predicted faster, pulsating flame spread in mu-g. In a test designed to achieve a more 2-D experiment, our investigation of a shallow, wide pool (2 mm deep x 78 mm wide x 30 cm long) was unsuccessful in mu-g, due to an unexpectedly long time required to fill the tray. As such, the most recent Spread Across Liquids (SAL) sounding rocket experiment had two principal objectives: 1) determine if pulsating flame spread in deep fuel trays would occur under the conditions that a state-of-the-art computational combustion code and short-duration drop tower tests predict; and 2) determine if a long, rectangular, shallow fuel tray could achieve a visibly flat liquid surface across the whole tray without spillage in the mu-g time allotted. If the second objective was met, the shallow tray was to be ignited to determine the nature of flame spread in mu-g for this geometry. For the first time in the experiment series, two fuel trays - one deep (30 cm long x 2 cm wide x 25 mm deep) and one shallow (same length and width, but 2 mm deep)-- were flown. By doing two independent experiments in a single flight, a significant cost savings was realized. In parallel, the computational objective was to modify the code to improve agreement with earlier results. This last objective was achieved by modifying the fuel mass diffusivity and adding a parameter to correct for radiative and lateral heat loss.

40 CFR 418.73 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... representing the degree of effluent reduction attainable by the application of the best available technology... effluent reduction attainable by the application of the best available technology economically achievable... subpart after application of the best available technology economically achievable: There shall be no...

40 CFR 424.53 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... technology economically achievable: There shall be no discharge of process waste water pollutants to... representing the degree of effluent reduction attainable by the application of the best available technology... reduction attainable by the application of the best available technology economically achievable. The...

40 CFR 440.113 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2014 CFR

2014-07-01

... degree of effluent reduction attainable by the application of the best available technology economically... attainable by the application of the best available technology economically achievable (BAT). Except as... reduction attainable by the application of the best available technology economically achievable (BAT): (a...

40 CFR 440.113 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2012 CFR

2012-07-01

... degree of effluent reduction attainable by the application of the best available technology economically... attainable by the application of the best available technology economically achievable (BAT). Except as... reduction attainable by the application of the best available technology economically achievable (BAT): (a...

Compact Deep-Space Optical Communications Transceiver

NASA Technical Reports Server (NTRS)

Roberts, W. Thomas; Charles, Jeffrey R.

2009-01-01

Deep space optical communication transceivers must be very efficient receivers and transmitters of optical communication signals. For deep space missions, communication systems require high performance well beyond the scope of mere power efficiency, demanding maximum performance in relation to the precious and limited mass, volume, and power allocated. This paper describes the opto-mechanical design of a compact, efficient, functional brassboard deep space transceiver that is capable of achieving megabyte-per-second rates at Mars ranges. The special features embodied to enhance the system operability and functionality, and to reduce the mass and volume of the system are detailed. System tests and performance characteristics are described in detail. Finally, lessons learned in the implementation of the brassboard design and suggestions for improvements appropriate for a flight prototype are covered.

Salvaging deep anterior lamellar keratoplasty with microbubble incision technique in failed "big bubble" cases: an update study.

PubMed

Banerjee, Sanjib; Li, He J; Tsaousis, Konstantinos T; Tabin, Geoffrey C

2016-11-04

To report the achievement rate of bare Descemet membrane (DM) dissection with the help of microbubble incision technique in eyes with failed big bubble formation and to investigate the mechanism of the microbubble rescue technique through ex vivo imaging of human cadaver corneas. This retrospective clinical study included 80 eyes of 80 patients that underwent deep anterior lamellar keratoplasty (DALK). In 22/80 (27.5%) cases, big bubble dissection failed. After puncturing the microbubbles, viscodissection helped to achieve separation of DM from the remaining stroma. In addition, an ex vivo study with human cadaver cornea specimens, gross photography, and anterior segment optical coherence tomography imaging was accomplished ex vivo to explore the mechanism of this method. Microbubble dissection technique led to successful DALK in 19 of 22 cases of failed big bubble. Microperforation occurred in 3 eyes. Deep anterior lamellar keratoplasty was completed without any complications in 2 out of the 3 eyes with microperforation. In 1 eye, conversion to penetrating keratoplasty was required. Microbubble-guided viscodissection achieved 95.4% (21/22) success in exposing bare DM in failed big-bubble cases of DALK. Anterior segment optical coherence tomography imaging results of cadaver eyes showed where these microbubbles were concentrated and their related size. Microbubble-guided DALK should be considered an effective rescue technique in achieving bare DM in eyes with failed big bubble. Our ex vivo experiment illustrated the possible alterations in cornea anatomy during this technique.

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.

Warming combined with more extreme precipitation regimes modifies the water sources used by trees.

PubMed

Grossiord, Charlotte; Sevanto, Sanna; Dawson, Todd E; Adams, Henry D; Collins, Adam D; Dickman, Lee T; Newman, Brent D; Stockton, Elizabeth A; McDowell, Nate G

2017-01-01

The persistence of vegetation under climate change will depend on a plant's capacity to exploit water resources. We analyzed water source dynamics in piñon pine and juniper trees subjected to precipitation reduction, atmospheric warming, and to both simultaneously. Piñon and juniper exhibited different and opposite shifts in water uptake depth in response to experimental stress and background climate over 3 yr. During a dry summer, juniper responded to warming with a shift to shallow water sources, whereas piñon pine responded to precipitation reduction with a shift to deeper sources in autumn. In normal and wet summers, both species responded to precipitation reduction, but juniper increased deep water uptake and piñon increased shallow water uptake. Shifts in the utilization of water sources were associated with reduced stomatal conductance and photosynthesis, suggesting that belowground compensation in response to warming and water reduction did not alleviate stress impacts for gas exchange. We have demonstrated that predicted climate change could modify water sources of trees. Warming impairs juniper uptake of deep sources during extended dry periods. Precipitation reduction alters the uptake of shallow sources following extended droughts for piñon. Shifts in water sources may not compensate for climate change impacts on tree physiology. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Bundles to prevent ventilator-associated pneumonia: how valuable are they?

PubMed

Wip, Charity; Napolitano, Lena

2009-04-01

To review the value of care bundles to prevent ventilator-associated pneumonia (VAP). The Ventilator Bundle contains four components, elevation of the head of the bed to 30-45 degrees, daily 'sedation vacation' and daily assessment of readiness to extubate, peptic ulcer disease prophylaxis, and deep venous thrombosis prophylaxis, aimed to improve outcome in mechanically ventilated patients, but not all are associated with VAP prevention. Daily spontaneous awakening and breathing trials are associated with early liberation from mechanical ventilation and VAP reduction. Although a small prospective, randomized clinical study documented that the semirecumbent position was associated with a significant reduction in VAP, more recent studies have documented that the semirecumbent position is difficult to maintain in mechanically ventilated patients and may not impact VAP reduction. Prophylaxis for peptic ulcer disease and deep venous thrombosis do not directly impact VAP reduction. Other methods to reduce VAP, such as oral care and hygiene, chlorhexidine in the posterior pharynx, and specialized endotracheal tubes (continuous aspiration of subglottic secretions, silver-coated), should be considered for inclusion in a revised Ventilator Bundle more specifically aimed at VAP prevention. The Ventilator Bundle is an effective method to reduce VAP rates in ICUs. The ventilator bundle should be modified and expanded to include specific processes of care that have been definitively demonstrated to be effective in VAP reduction or a specific VAP bundle created to focus on VAP prevention.

Linear-array based full-view high-resolution photoacoustic computed tomography of whole mouse brain functions in vivo

NASA Astrophysics Data System (ADS)

Li, Lei; Zhang, Pengfei; Wang, Lihong V.

2018-02-01

Photoacoustic computed tomography (PACT) is a non-invasive imaging technique offering high contrast, high resolution, and deep penetration in biological tissues. We report a photoacoustic computed tomography (PACT) system equipped with a high frequency linear array for anatomical and functional imaging of the mouse whole brain. The linear array was rotationally scanned in the coronal plane to achieve the full-view coverage. We investigated spontaneous neural activities in the deep brain by monitoring the hemodynamics and observed strong interhemispherical correlations between contralateral regions, both in the cortical layer and in the deep regions.

Species abundance, sexual encounter and bioluminescent signalling in the deep sea.

PubMed Central

Herring, P J

2000-01-01

The problems faced by deep-sea animals in achieving sexual and other encounters require sensory and effector systems the synergy of which can span the often very substantial distances that separate individuals. Bioluminescent systems provide one of the links between individuals, and the sexual dimorphism of some photophores suggests that they are employed to attract a mate. However, nearest-neighbour values for many deep-sea animals put them beyond the effective range of bioluminescent signals and it is therefore likely that these signals are employed at intermediate ranges, once an initial contact (perhaps olfactory) has been made. PMID:11079413

Reducing GHG emissions in the United States' transportation sector

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

Das, Sujit; Andress, David A; Nguyen, Tien

Reducing GHG emissions in the U.S. transportation sector requires both the use of highly efficient propulsion systems and low carbon fuels. This study compares reduction potentials that might be achieved in 2060 for several advanced options including biofuels, hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), and fuel cell electric vehicles (FCEV), assuming that technical and cost reduction targets are met and necessary fueling infrastructures are built. The study quantifies the extent of the reductions that can be achieved through increasing engine efficiency and transitioning to low-carbon fuels separately. Decarbonizing the fuels is essential for achieving large reductions inmore » GHG emissions, and the study quantifies the reductions that can be achieved over a range of fuel carbon intensities. Although renewables will play a vital role, some combination of coal gasification with carbon capture and sequestration, and/or nuclear energy will likely be needed to enable very large reductions in carbon intensities for hydrogen and electricity. Biomass supply constraints do not allow major carbon emission reductions from biofuels alone; the value of biomass is that it can be combined with other solutions to help achieve significant results. Compared with gasoline, natural gas provides 20% reduction in GHG emissions in internal combustion engines and up to 50% reduction when used as a feedstock for producing hydrogen or electricity, making it a good transition fuel for electric propulsion drive trains. The material in this paper can be useful information to many other countries, including developing countries because of a common factor: the difficulty of finding sustainable, low-carbon, cost-competitive substitutes for petroleum fuels.« less

Ceramic Spheres—A Novel Solution to Deep Sea Buoyancy Modules

PubMed Central

Jiang, Bo; Blugan, Gurdial; Sturzenegger, Philip N.; Gonzenbach, Urs T.; Misson, Michael; Thornberry, John; Stenerud, Runar; Cartlidge, David; Kuebler, Jakob

2016-01-01

Ceramic-based hollow spheres are considered a great driving force for many applications such as offshore buoyancy modules due to their large diameter to wall thickness ratio and uniform wall thickness geometric features. We have developed such thin-walled hollow spheres made of alumina using slip casting and sintering processes. A diameter as large as 50 mm with a wall thickness of 0.5–1.0 mm has been successfully achieved in these spheres. Their material and structural properties were examined by a series of characterization tools. Particularly, the feasibility of these spheres was investigated with respect to its application for deep sea (>3000 m) buoyancy modules. These spheres, sintered at 1600 °C and with 1.0 mm of wall thickness, have achieved buoyancy of more than 54%. As the sphere’s wall thickness was reduced (e.g., 0.5 mm), their buoyancy reached 72%. The mechanical performance of such spheres has shown a hydrostatic failure pressure above 150 MPa, corresponding to a rating depth below sea level of 5000 m considering a safety factor of 3. The developed alumina-based ceramic spheres are feasible for low cost and scaled-up production and show great potential at depths greater than those achievable by the current deep-sea buoyancy module technologies. PMID:28773651

Coarse-to-fine deep neural network for fast pedestrian detection

NASA Astrophysics Data System (ADS)

Li, Yaobin; Yang, Xinmei; Cao, Lijun

2017-11-01

Pedestrian detection belongs to a category of object detection is a key issue in the field of video surveillance and automatic driving. Although recent object detection methods, such as Fast/Faster RCNN, have achieved excellent performance, it is difficult to meet real-time requirements and limits the application in real scenarios. A coarse-to-fine deep neural network for fast pedestrian detection is proposed in this paper. Two-stage approach is presented to realize fine trade-off between accuracy and speed. In the coarse stage, we train a fast deep convolution neural network to generate most pedestrian candidates at the cost of a number of false positives. The detector can cover the majority of scales, sizes, and occlusions of pedestrians. After that, a classification network is introduced to refine the pedestrian candidates generated from the previous stage. Refining through classification network, most of false detections will be excluded easily and the final pedestrian predictions with bounding box and confidence score are produced. Competitive results have been achieved on INRIA dataset in terms of accuracy, especially the method can achieve real-time detection that is faster than the previous leading methods. The effectiveness of coarse-to-fine approach to detect pedestrians is verified, and the accuracy and stability are also improved.

SPRUCE Deep Peat Heating Manipulations: in situ Methods to Characterize the Response of Deep Peat to Warming

NASA Astrophysics Data System (ADS)

Hanson, P. J.; Riggs, J. S.; Barbier, C. N.; Nettles, W. R., IV; Phillips, J. R.; Hook, L.

2014-12-01

Deep soil heating infrastructure was completed in 2014 for a peatland whole-ecosystem warming study that will include air warming starting in 2015 (SPRUCE; http://mnspruce.ornl.gov). In June 2014, we initiated deep soil heating to test the responsiveness of deep peat carbon stocks, microbial communities and biogeochemical cycling processes to heating at 4 warming levels (+2.25, +4.5, +6.75 and +9 °C; 2 replicate plots) compared to fully-constructed control plots (+0 °C; 2 replicate plots). The warming treatments were deployed over eight 113 m2 areas using circular arrays of low-wattage (W) electrical resistance heaters. Perimeter heating was achieved by an exterior circle of 48 100W heaters that apply heat from the surface to a depth of 3 meters. Heating within the study area was accomplished utilizing three zones of 100W "deep only" heaters: an intermediate circle of 12 units, an interior circle of 6 units and one unit placed at the plot center. Heating elements inside the study area apply heat only from -2 to -3 m to keep active heater surfaces away from measured peat volumes. With an average peat depth of 2.5 meters this system was able to warm approximately 113 of the 282 m3 of peat within each target plot. In the absence of the air warming cap, in situ deep peat heating is only effective at sustaining warming in the deep peat layers. Warming levels at depth were achieved over a 25-day (+ 2.25 °C) to a 60-day (+9 °C) period depending on the target treatment temperatures in agreement with a priori energy balance model simulations. Homogeneous temperature distributions between heaters at a given depth interval continued to develop after these targets were reached. Biological and biogeochemical responses to these manipulations are being actively assessed. After one month of transient heating, data for ground-level surface flux of CO2 and CH4 had not shown changes from deep peat heating, but they continue to be tracked and will be summarized in this and related talks.

HIFU Hemostasis of Liver Injuries Enhanced by Ultrasound Contrast Agents

NASA Astrophysics Data System (ADS)

Zderic, Vesna; Vaezy, Shahram; Brayman, Andrew A.; Matula, Thomas J.; O'Keefe, Grant E.; Crum, Lawrence A.

2005-03-01

Our objective was to investigate whether High-Intensity Focused Ultrasound (HIFU) hemostasis can be achieved faster in the presence of ultrasound contrast agents (UCA). Incisions (3 cm long and 0.5 cm deep) were made in surgically exposed rabbit liver. Optison at a concentration of 0.18 ml/kg was injected into the mesenteric vein, immediately before the incision was made. The HIFU applicator (frequency of 5.5 MHz, and intensity of 3,700 W/cm2) was scanned manually over the incision (at an approximate rate of 1 mm/s) until hemostasis was achieved. The times to complete hemostasis were measured and normalized with the initial blood loss. The hemostasis times were 59±23 s in the presence of Optison and 70±23 s without Optison. The presence of Optison produced a 37% reduction in the normalized hemostasis times (p<0.05). Optison also provided faster (by 34%) formation of the coagulum seal over the lesion. Gross observations showed that the lesion size did not change due to the presence of Optison. Histological analysis showed that lesions consisted of an area of coagulation necrosis in vicinity of the incision, occasionally surrounded by a congestion zone filled with blood. Our results suggest the potential utility of microbubble contrast agents for increasing efficiency of HIFU hemostasis of internal organ injuries.

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

PubMed

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2017-09-05

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

North Atlantic Deep Water Production during the Last Glacial Maximum

PubMed Central

Howe, Jacob N. W.; Piotrowski, Alexander M.; Noble, Taryn L.; Mulitza, Stefan; Chiessi, Cristiano M.; Bayon, Germain

2016-01-01

Changes in deep ocean ventilation are commonly invoked as the primary cause of lower glacial atmospheric CO2. The water mass structure of the glacial deep Atlantic Ocean and the mechanism by which it may have sequestered carbon remain elusive. Here we present neodymium isotope measurements from cores throughout the Atlantic that reveal glacial–interglacial changes in water mass distributions. These results demonstrate the sustained production of North Atlantic Deep Water under glacial conditions, indicating that southern-sourced waters were not as spatially extensive during the Last Glacial Maximum as previously believed. We demonstrate that the depleted glacial δ13C values in the deep Atlantic Ocean cannot be explained solely by water mass source changes. A greater amount of respired carbon, therefore, must have been stored in the abyssal Atlantic during the Last Glacial Maximum. We infer that this was achieved by a sluggish deep overturning cell, comprised of well-mixed northern- and southern-sourced waters. PMID:27256826

Current evidence supporting mucosal healing and deep remission as important treatment goals for inflammatory bowel disease.

PubMed

Pineton de Chambrun, Guillaume; Blanc, Pierre; Peyrin-Biroulet, Laurent

2016-08-01

Mucosal healing (MH) is now considered as a major treatment goal in clinical trials and clinical practice for patients with inflammatory bowel disease (IBD). MH is associated with sustained clinical remission, steroid-free remission, and reduced rates of hospitalization and surgery. There is a well-known disconnect between clinical symptoms and mucosal lesions that is more pronounced in CD. More stringent therapeutic goals have been discussed recently such as deep remission defined as clinical remission associated with MH. Recent international guidelines from the IOIBD recommended deep remission as a treatment goal in clinical practice. However there is no validated definition of deep remission in IBD. Also, the efficacy of available drugs to induce and maintain deep remission in IBD is poorly known. Finally, whether deep remission is the best way to modify the course of IBD and whether it should be achieved before considering drug de-escalation have to be formally evaluated in upcoming disease-modification trials.

Effects of internal phosphorus loadings and food-web structure on the recovery of a deep lake from eutrophication

USGS Publications Warehouse

Lepori, Fabio; Roberts, James J.

2017-01-01

We used monitoring data from Lake Lugano (Switzerland and Italy) to assess key ecosystem responses to three decades of nutrient management (1983–2014). We investigated whether reductions in external phosphorus loadings (Lext) caused declines in lake phosphorus concentrations (P) and phytoplankton biomass (Chl a), as assumed by the predictive models that underpinned the management plan. Additionally, we examined the hypothesis that deep lakes respond quickly to Lext reductions. During the study period, nutrient management reduced Lext by approximately a half. However, the effects of such reduction on P and Chl a were complex. Far from the scenarios predicted by classic nutrient-management approaches, the responses of P and Chl a did not only reflect changes in Lext, but also variation in internal P loadings (Lint) and food-web structure. In turn, Lint varied depending on basin morphometry and climatic effects, whereas food-web structure varied due to apparently stochastic events of colonization and near-extinction of key species. Our results highlight the complexity of the trajectory of deep-lake ecosystems undergoing nutrient management. From an applied standpoint, they also suggest that [i] the recovery of warm monomictic lakes may be slower than expected due to the development of Lint, and that [ii] classic P and Chl a models based on Lext may be useful in nutrient management programs only if their predictions are used as starting points within adaptive frameworks.

Regional patterns of grey matter atrophy and magnetisation transfer ratio abnormalities in multiple sclerosis clinical subgroups: A voxel-based analysis study

PubMed Central

Muhlert, Nils; Samson, Rebecca S; Sethi, Varun; Wheeler-Kingshott, Claudia AM; Miller, David H; Chard, Declan T

2015-01-01

Background: In multiple sclerosis (MS), demyelination and neuro-axonal loss occur in the brain grey matter (GM). We used magnetic resonance imaging (MRI) measures of GM magnetisation transfer ratio (MTR) and volume to assess the regional localisation of reduced MTR (reflecting demyelination) and atrophy (reflecting neuro-axonal loss) in relapsing–remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS). Methods: A total of 98 people with MS (51 RRMS, 28 SPMS, 19 PPMS) and 29 controls had T1-weighted volumetric and magnetisation transfer scans. SPM8 was used to undertake voxel-based analysis (VBA) of GM tissue volumes and MTR. MS subgroups were compared with controls, adjusting for age and gender. A voxel-by-voxel basis correlation analysis between MTR and volume within each subject group was performed, using biological parametric mapping. Results: MTR reduction was more extensive than atrophy. RRMS and SPMS patients showed proportionately more atrophy in the deep GM. SPMS and PPMS patients showed proportionately greater cortical MTR reduction. RRMS patients demonstrated the most correlation of MTR reduction and atrophy in deep GM. In SPMS and PPMS patients, there was less extensive correlation. Conclusions: These results suggest that in the deep GM of RRMS patients, demyelination and neuro-axonal loss may be linked, while in SPMS and PPMS patients, neuro-axonal loss and demyelination may occur mostly independently. PMID:25145689

Rechargeable internal neural stimulators--is there a problem with efficacy?

PubMed

Harries, Anwen M; Major, Shannon; Sandhu, Mandeep; Honey, Christopher R

2012-01-01

With the advent of rechargeable internal neural stimulators (rINS) for deep brain stimulation, our aim was to survey patient satisfaction and clinical efficacy in an early cohort of patients receiving this new technology. This is an observational study on nine patients with rINS. All patients had initially received non-rechargeable INS with established efficacy of their deep brain stimulation system for either dystonia or pain. Patient satisfaction and efficacy with their rINS were established by completion of a questionnaire, a quality of life assessment (SF-36), and calculation of the total electrical energy delivered (TEED) by the rINS. A reduction in efficacy of their rINS was noticed in 22% of patients. In 78% of patients, there was a problem with recharging their rINS because of poor contact. Two patients (22%) felt that recharging the rINS interfered with their lives and it was a daily reminder that they had a deep brain stimulator system in situ. Eight out of nine patients (89%), however, would recommend to other patients to have an rINS. Most patients were happy with their rechargeable internal neural stimulator. A reduction in efficacy was noticed in 22% of patients, which is similar to the proportion of patients noticing a reduction in efficacy when replacing with a non-rechargeable system. Thus, all patients require close monitoring post-replacement of rINS, in case possible adjustment of parameters is required. © 2011 International Neuromodulation Society.

7 CFR 12.23 - Conservation plans and conservation systems.

Code of Federal Regulations, 2011 CFR

2011-01-01

... in the field office technical guide are designed to achieve substantial reductions in soil erosion..., 1985, the measurement of erosion reduction achieved by applying a conservation plan or system shall be... in paragraph (b) which the conservation system or plan was designed to achieve. It is the...

40 CFR 430.94 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 430.94 Section 430.94 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... reduction attainable by the application of the best available technology economically achievable (BAT... economically achievable (BAT). Non-continuous dischargers shall not be subject to the maximum day mass...

40 CFR 429.143 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 429.143 Section 429.143 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... reduction attainable by the application of the best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT): There shall be...

40 CFR 430.24 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 430.24 Section 430.24 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... effluent reduction attainable by the application of best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT). (a) Except as...

40 CFR 429.123 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 429.123 Section 429.123 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... reduction attainable by the application of the best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT): There shall be...

40 CFR 471.62 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 471.62 Section 471.62 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... reduction attainable by the application of the best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT): (a) Rolling...

40 CFR 471.82 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 471.82 Section 471.82 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... reduction attainable by the application of the best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT): (a) Rolling...

40 CFR 429.123 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2014 CFR

2014-07-01

... achievable (BAT). 429.123 Section 429.123 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... reduction attainable by the application of the best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT): There shall be...

40 CFR 440.113 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 440.113 Section 440.113 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... attainable by the application of the best available technology economically achievable (BAT). Except as... reduction attainable by the application of the best available technology economically achievable (BAT): (a...

40 CFR 471.22 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 471.22 Section 471.22 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... reduction attainable by the application of the best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT): (a) Rolling...

40 CFR 430.94 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2014 CFR

2014-07-01

... achievable (BAT). 430.94 Section 430.94 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... reduction attainable by the application of the best available technology economically achievable (BAT... economically achievable (BAT). Non-continuous dischargers shall not be subject to the maximum day mass...

40 CFR 429.143 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2014 CFR

2014-07-01

... achievable (BAT). 429.143 Section 429.143 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... reduction attainable by the application of the best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT): There shall be...

40 CFR 471.72 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 471.72 Section 471.72 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... reduction attainable by the application of the best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT): (a) Extrusion...

40 CFR 430.24 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2014 CFR

2014-07-01

... achievable (BAT). 430.24 Section 430.24 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... effluent reduction attainable by the application of best available technology economically achievable (BAT... attainable by the application of the best available technology economically achievable (BAT). (a) Except as...

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.

High efficiency blue and white phosphorescent organic light emitting devices

NASA Astrophysics Data System (ADS)

Eom, Sang-Hyun

Organic light-emitting devices (OLEDs) have important applications in full-color flat-panel displays and as solid-state lighting sources. Achieving high efficiency deep-blue phosphorescent OLEDs (PHOLEDs) is necessary for high performance full-color displays and white light sources with a high color rendering index (CRI); however it is more challenging compared to the longer wavelength light emissions such as green and red due to the higher energy excitations for the deep-blue emitter as well as the weak photopic response of deep-blue emission. This thesis details several effective strategies to enhancing efficiencies of deep-blue PHOLEDs based on iridium(III) bis(4',6'-difluorophenylpyridinato)tetrakis(1-pyrazolyl)borate (FIr6), which are further employed to demonstrate high efficiency white OLEDs by combining the deep-blue emitter with green and red emitters. First, we have employed 1,1-bis-(di-4-tolylaminophenyl) cyclohexane (TAPC) as the hole transporting material to enhance electron and triplet exciton confinement in Fir6-based PHOLEDs, which increased external quantum efficiency up to 18 %. Second, dual-emissive-layer (D-EML) structures consisting of an N,N -dicarbazolyl-3,5-benzene (mCP) layer doped with 4 wt % FIr6 and a p-bis (triphenylsilyly)benzene (UGH2) layer doped with 25 wt % FIr6 was employed to maximize exciton generation in the emissive layer. Combined with the p-i-n device structure, high power efficiencies of (25 +/- 2) lm/W at 100 cd/m2 and (20 +/- 2) lm/W at 1000 cd/m 2 were achieved. Moreover, the peak external quantum efficiency of (20 +/- 1) % was achieved by employing tris[3-(3-pyridyl)mesityl]borane (3TPYMB) as the electron transporting material, which further improves the exciton confinement in the emissive layer. With Cs2CO3 doping in the 3TPYMB layer to greatly increase its electrical conductivity, a peak power efficiency up to (36 +/- 2) lm/W from the deep-blue PHOLED was achieved, which also maintains Commission Internationale de L'Eclairage (CIE) coordinates of (0.16, 0.28). High efficiency white PHOLEDs are also demonstrated by incorporating green and red phosphorescent emitters together with the deep-blue emitter FIr6. Similar to the FIr6-only devices, the D-EML structure with high triplet energy charge transport materials leads to a maximum external quantum efficiency of (19 +/- 1) %. Using the p-i-n device structure, a peak power efficiency of (40 +/- 2) lm/W and (36 +/- 2) lm/W at 100 cd/m2 were achieved, and the white PHOLED possesses a CRI of 79 and CIE coordinates of (0.37, 0.40). The limited light extraction from the planar-type OLEDs is also one of the remaining challenges to the OLED efficiency. Here we have developed a simple soft lithography technique to fabricate a transparent, close-packed hemispherical microlens arrays. The application of such microlens arrays to the glass surface of the large-area fluorescent OLEDs enhanced the light extraction efficiency up to (70 +/- 7)%. It is also shown that the light extraction efficiency of the OLEDs is affected by microlens contact angle, OLEDs size, and detailed layer structure of the OLEDs.

Inactivation of Heat Adapted and Chlorine Adapted Listeria Monocytogenes ATCC 7644 on Tomatoes Using Sodium Dodecyl Sulphate, Levulinic Acid and Sodium Hypochlorite Solution.

PubMed

Ijabadeniyi, Oluwatosin Ademola; Mnyandu, Elizabeth

2017-04-13

The effectiveness of sodium dodecyl sulphate (SDS), sodium hypochlorite solution and levulinic acid in reducing the survival of heat adapted and chlorine adapted Listeria monocytogenes ATCC 7644 was evaluated. The results against heat adapted L. monocytognes revealed that sodium hypochlorite solution was the least effective, achieving log reduction of 2.75, 2.94 and 3.97 log colony forming unit (CFU)/mL for 1, 3 and 5 minutes, respectively. SDS was able to achieve 8 log reduction for both heat adapted and chlorine adapted bacteria. When used against chlorine adapted L. monocytogenes sodium hypochlorite solution achieved log reduction of 2.76, 2.93 and 3.65 log CFU/mL for 1, 3 and 5 minutes, respectively. Using levulinic acid on heat adapted bacteria achieved log reduction of 3.07, 2.78 and 4.97 log CFU/mL for 1, 3, 5 minutes, respectively. On chlorine adapted bacteria levulinic acid achieved log reduction of 2.77, 3.07 and 5.21 log CFU/mL for 1, 3 and 5 minutes, respectively. Using a mixture of 0.05% SDS and 0.5% levulinic acid on heat adapted bacteria achieved log reduction of 3.13, 3.32 and 4.79 log CFU/mL for 1, 3 and 5 minutes while on chlorine adapted bacteria it achieved 3.20, 3.33 and 5.66 log CFU/mL, respectively. Increasing contact time also increased log reduction for both test pathogens. A storage period of up to 72 hours resulted in progressive log reduction for both test pathogens. Results also revealed that there was a significant difference (P≤0.05) among contact times, storage times and sanitizers. Findings from this study can be used to select suitable sanitizers and contact times for heat and chlorine adapted L. monocytogenes in the fresh produce industry.

Antarctic Glaciation during the Tertiary Recorded in Sub-Antarctic Deep-Sea Cores.

PubMed

Margolis, S V; Kennett, J P

1970-12-04

Study of 18 Cenozoic South Pacific deep-sea cores indicates an association of glacially derived ice-rafted sands and relatively low planktonic foraminiferal diversity with cooling of the Southern Ocean during the Lower Eocene, upper Middle Eocene, and Oligocene. Increased species diversity and reduction or absence of ice-rafted sands in Lower and Middle Miocene cores indicate a warming trend that ended in the Upper Miocene. Antarctic continental glaciation appears to have prevailed throughout much of the Cenozoic.

Deep anistropic shell program for tire analysis

NASA Technical Reports Server (NTRS)

Andersen, C. M.

1981-01-01

A finite element program was constructed to model the mechanical response of a tire, treated as a deep anisotropic shell, to specified static loads. The program is based on a Sanders Budiansky type shell theory with the effects of transverse shear deformation and bending-extensional coupling included. A displacement formulation is used together with a total Lagrangian description of the deformation. Sixteen-node quadrilateral elements with bicubic shape functions are employed. The Noor basis reduction technique and various type of symmetry considerations serve to improve the computational efficiency.

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.

MusiteDeep: a deep-learning framework for general and kinase-specific phosphorylation site prediction.

PubMed

Wang, Duolin; Zeng, Shuai; Xu, Chunhui; Qiu, Wangren; Liang, Yanchun; Joshi, Trupti; Xu, Dong

2017-12-15

Computational methods for phosphorylation site prediction play important roles in protein function studies and experimental design. Most existing methods are based on feature extraction, which may result in incomplete or biased features. Deep learning as the cutting-edge machine learning method has the ability to automatically discover complex representations of phosphorylation patterns from the raw sequences, and hence it provides a powerful tool for improvement of phosphorylation site prediction. We present MusiteDeep, the first deep-learning framework for predicting general and kinase-specific phosphorylation sites. MusiteDeep takes raw sequence data as input and uses convolutional neural networks with a novel two-dimensional attention mechanism. It achieves over a 50% relative improvement in the area under the precision-recall curve in general phosphorylation site prediction and obtains competitive results in kinase-specific prediction compared to other well-known tools on the benchmark data. MusiteDeep is provided as an open-source tool available at https://github.com/duolinwang/MusiteDeep. xudong@missouri.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

PubMed

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors.

PubMed

Kawahito, Shoji; Seo, Min-Woong

2016-11-06

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e - rms ) when compared with the CMS gain of two (2.4 e - rms ), or 16 (1.1 e - rms ).

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors

PubMed Central

Kawahito, Shoji; Seo, Min-Woong

2016-01-01

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e−rms) when compared with the CMS gain of two (2.4 e−rms), or 16 (1.1 e−rms). PMID:27827972

Classification of ECG beats using deep belief network and active learning.

PubMed

G, Sayantan; T, Kien P; V, Kadambari K

2018-04-12

A new semi-supervised approach based on deep learning and active learning for classification of electrocardiogram signals (ECG) is proposed. The objective of the proposed work is to model a scientific method for classification of cardiac irregularities using electrocardiogram beats. The model follows the Association for the Advancement of medical instrumentation (AAMI) standards and consists of three phases. In phase I, feature representation of ECG is learnt using Gaussian-Bernoulli deep belief network followed by a linear support vector machine (SVM) training in the consecutive phase. It yields three deep models which are based on AAMI-defined classes, namely N, V, S, and F. In the last phase, a query generator is introduced to interact with the expert to label few beats to improve accuracy and sensitivity. The proposed approach depicts significant improvement in accuracy with minimal queries posed to the expert and fast online training as tested on the MIT-BIH Arrhythmia Database and the MIT-BIH Supra-ventricular Arrhythmia Database (SVDB). With 100 queries labeled by the expert in phase III, the method achieves an accuracy of 99.5% in "S" versus all classifications (SVEB) and 99.4% accuracy in "V " versus all classifications (VEB) on MIT-BIH Arrhythmia Database. In a similar manner, it is attributed that an accuracy of 97.5% for SVEB and 98.6% for VEB on SVDB database is achieved respectively. Graphical Abstract Reply- Deep belief network augmented by active learning for efficient prediction of arrhythmia.

Surgical treatment of intra-articular calcaneal fractures.

PubMed

Stapleton, John J; Zgonis, Thomas

2014-10-01

Most intra-articular calcaneal fractures are a result of high-energy trauma. The operative management of calcaneal fractures has been based on achieving anatomic reduction and minimizing complications of the compromised soft tissue envelope. The traditional extensile lateral approach offers advantages of achieving adequate fracture reduction with the risk of wound-healing complications and infection. Limited open reduction and internal fixation techniques with or without using external fixation focuses on achieving fracture reduction with less risk of wound complications but higher risk of malunion. This article discusses key points of operative management for various intra-articular calcaneal fracture patterns and clinical presentations. Copyright © 2014 Elsevier Inc. All rights reserved.

Near-Term Actions to Address Long-Term Climate Risk

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2014-12-01

Addressing climate change requires effective long-term policy making, which occurs when reflecting on potential events decades or more in the future causes policy makers to choose near-term actions different than those they would otherwise pursue. Contrary to some expectations, policy makers do sometimes make such long-term decisions, but not as commonly and successfully as climate change may require. In recent years however, the new capabilities of analytic decision support tools, combined with improved understanding of cognitive and organizational behaviors, has significantly improved the methods available for organizations to manage longer-term climate risks. In particular, these tools allow decision makers to understand what near-term actions consistently contribute to achieving both short- and long-term societal goals, even in the face of deep uncertainty regarding the long-term future. This talk will describe applications of these approaches for infrastructure, water, and flood risk management planning, as well as studies of how near-term choices about policy architectures can affect long-term greenhouse gas emission reduction pathways.

Development of Database for Accident Analysis in Indian Mines

NASA Astrophysics Data System (ADS)

Tripathy, Debi Prasad; Guru Raghavendra Reddy, K.

2016-10-01

Mining is a hazardous industry and high accident rates associated with underground mining is a cause of deep concern. Technological developments notwithstanding, rate of fatal accidents and reportable incidents have not shown corresponding levels of decline. This paper argues that adoption of appropriate safety standards by both mine management and the government may result in appreciable reduction in accident frequency. This can be achieved by using the technology in improving the working conditions, sensitising workers and managers about causes and prevention of accidents. Inputs required for a detailed analysis of an accident include information on location, time, type, cost of accident, victim, nature of injury, personal and environmental factors etc. Such information can be generated from data available in the standard coded accident report form. This paper presents a web based application for accident analysis in Indian mines during 2001-2013. An accident database (SafeStat) prototype based on Intranet of the TCP/IP agreement, as developed by the authors, is also discussed.

Comparison and interactions between the long-term pursuit of energy independence and climate policies

NASA Astrophysics Data System (ADS)

Jewell, Jessica; Vinichenko, Vadim; McCollum, David; Bauer, Nico; Riahi, Keywan; Aboumahboub, Tino; Fricko, Oliver; Harmsen, Mathijs; Kober, Tom; Krey, Volker; Marangoni, Giacomo; Tavoni, Massimo; van Vuuren, Detlef P.; van der Zwaan, Bob; Cherp, Aleh

2016-06-01

Ensuring energy security and mitigating climate change are key energy policy priorities. The recent Intergovernmental Panel on Climate Change Working Group III report emphasized that climate policies can deliver energy security as a co-benefit, in large part through reducing energy imports. Using five state-of-the-art global energy-economy models and eight long-term scenarios, we show that although deep cuts in greenhouse gas emissions would reduce energy imports, the reverse is not true: ambitious policies constraining energy imports would have an insignificant impact on climate change. Restricting imports of all fuels would lower twenty-first-century emissions by only 2-15% against the Baseline scenario as compared with a 70% reduction in a 450 stabilization scenario. Restricting only oil imports would have virtually no impact on emissions. The modelled energy independence targets could be achieved at policy costs comparable to those of existing climate pledges but a fraction of the cost of limiting global warming to 2 ∘C.

Goal-directed-perfusion in neonatal aortic arch surgery.

PubMed

Cesnjevar, Robert Anton; Purbojo, Ariawan; Muench, Frank; Juengert, Joerg; Rueffer, André

2016-07-01

Reduction of mortality and morbidity in congenital cardiac surgery has always been and remains a major target for the complete team involved. As operative techniques are more and more standardized and refined, surgical risk and associated complication rates have constantly been reduced to an acceptable level but are both still present. Aortic arch surgery in neonates seems to be of particular interest, because perfusion techniques differ widely among institutions and an ideal form of a so called "total body perfusion (TBP)" is somewhat difficult to achieve. Thus concepts of deep hypothermic circulatory arrest (DHCA), regional cerebral perfusion (RCP/with cardioplegic cardiac arrest or on the perfused beating heart) and TBP exist in parallel and all carry an individual risk for organ damage related to perfusion management, chosen core temperature and time on bypass. Patient safety relies more and more on adequate end organ perfusion on cardiopulmonary bypass, especially sensitive organs like the brain, heart, kidney, liver and the gut, whereby on adequate tissue protection, temperature management and oxygen delivery should be visualized and monitored.

[Effectiveness of intermittent pneumatic compression (IPC) on thrombosis prophylaxis: a systematic literature review].

PubMed

Rohrer, Ottilia; Eicher, Manuela

2006-06-01

Despite changes in patient demographics and short-ened length of hospital stay deep vein thrombosis (DVT) remains a major health care problem which may lead to a variety of other high risk complications. Current treatment guidelines focus on preventive measures. Beside drug therapy, physical measures executed by nursing professionals exist, the outcomes of which are discussed controversially. Based on 25 studies that were found in MEDLINE and the Cochrane library, this systematic literature review identifies the effectiveness of intermittent pneumatic compression (IPC) on thrombosis prophylaxis. In almost all medical settings IPC contributes to a significant reduction of the incidence of DVT. At the same time, IPC has minimal negative side effects and is also cost effective. Correct application of IPC and patient compliance are essential to achieve its effectiveness. An increased awareness within the healthcare team in identifying the risk for and implementing measures against DVT is needed. Guidelines need to be developed in order to improve the effectiveness of thrombosis prophylaxis with the implementation of IPC.

Implications of Deep Decarbonization for Carbon Cycle Science

NASA Astrophysics Data System (ADS)

Jones, A. D.; Williams, J.; Torn, M. S.

2016-12-01

The energy-system transformations required to achieve deep decarbonization in the United States, defined as a reduction of greenhouse gas emissions of 80% or more below 1990 levels by 2050, have profound implications for carbon cycle science, particularly with respect to 4 key objectives: understanding and enhancing the terrestrial carbon sink, using bioenergy sustainably, controlling non-CO2 GHGs, and emissions monitoring and verification. (1) As a source of mitigation, the terrestrial carbon sink is pivotal but uncertain, and changes in the expected sink may significantly affect the overall cost of mitigation. Yet the dynamics of the sink under changing climatic conditions, and the potential to protect and enhance the sink through land management, are poorly understood. Policy urgently requires an integrative research program that links basic science knowledge to land management practices. (2) Biomass resources can fill critical energy needs in a deeply decarbonized system, but current understanding of sustainability and lifecycle carbon aspects is limited. Mitigation policy needs better understanding of the sustainable amount, types, and cost of bioenergy feedstocks, their interactions with other land uses, and more efficient and reliable monitoring of embedded carbon. (3) As CO2 emissions from energy decrease under deep decarbonization, the relative share of non-CO2 GHGs grows larger and their mitigation more important. Because the sources tend to be distributed, variable, and uncertain, they have been under-researched. Policy needs a better understanding of mitigation priorities and costs, informed by deeper research in key areas such as fugitive CH4, fertilizer-derived N2O, and industrial F-gases. (4) The M&V challenge under deep decarbonization changes with a steep decrease in the combustion CO2 sources due to widespread electrification, while a greater share of CO2 releases is net-carbon-neutral. Similarly, gas pipelines may carry an increasing share of methane from biogenic or other net carbon-neutral sources. Improved lifecycle analysis will be needed to verify carbon neutrality, while the signal-to-noise challenge for attributing CO2 to fossil or biogenic fuels becomes more challenging.

[Arthroscopy-guided fracture management. Ankle joint and calcaneus].

PubMed

Schoepp, C; Rixen, D

2013-04-01

Arthroscopic fracture management of the ankle and calcaneus requires a differentiated approach. The aim is to minimize surgical soft tissue damage and to visualize anatomical fracture reduction arthroscopically. Moreover, additional cartilage damage can be detected and treated. The arthroscopic approach is limited by deep impressions of the joint surface needing cancellous bone grafting, by multiple fracture lines on the articular side and by high-grade soft tissue damage. An alternative to the minimally invasive arthroscopic approach is open arthroscopic reduction in conventional osteosynthesis. This facilitates correct assessment of surgical reduction of complex calcaneal fractures, otherwise remaining non-anatomical reduction might not be fluoroscopically detected during surgery.

Clinical use of photodynamic antimicrobial chemotherapy for the treatment of deep carious lesions

NASA Astrophysics Data System (ADS)

Guglielmi, Camila De Almeida B.; Simionato, Maria Regina L.; Ramalho, Karen Müller; Imparato, José Carlos P.; Pinheiro, Sérgio Luiz; Luz, Maria A. A. C.

2011-08-01

The purpose of this study was to assess photodynamic antimicrobial chemotherapy (PACT) via irradiation, using a low power laser associated with a photosensitization dye, as an alternative to remove cariogenic microorganisms by drilling. Remaining dentinal samples in deep carious lesions on permanent molars (n = 26) were treated with 0.01% methylene blue dye and irradiated with a low power laser (InGaAIP - indium gallium aluminum phosphide; λ = 660 nm; 100 mW; 320 Jcm-2 90 s; 9J). Samples of dentin from the pulpal wall region were collected with a micropunch before and immediately after PACT and kept in a transport medium for microbiological analysis. Samples were cultured in plates of Brucella blood agar, Mitis Salivarius Bacitracin agar and Rogosa SL agar to determine the total viable bacteria, mutans streptococci and Lactobacillus spp. counts, respectively. After incubation, colony-forming units were counted and microbial reduction was calculated for each group of bacteria. PACT led to statistically significant reductions in mutans streptococci (1.38 log), Lactobacillus spp. (0.93 log), and total viable bacteria (0.91 log). This therapy may be an appropriate approach for the treatment of deep carious lesions using minimally invasive procedures.

Microbial diversity in Cenozoic sediments recovered from the Lomonosov Ridge in the Central Arctic basin.

PubMed

Forschner, Stephanie R; Sheffer, Roberta; Rowley, David C; Smith, David C

2009-03-01

The current understanding of microbes inhabiting deeply buried marine sediments is based largely on samples collected from continental shelves in tropical and temperate latitudes. The geographical range of marine subsurface coring was expanded during the Integrated Ocean Drilling Program Arctic Coring Expedition (IODP ACEX). This expedition to the ice-covered central Arctic Ocean successfully cored the entire 428 m sediment stack on the Lomonosov Ridge during August and September 2004. The recovered cores vary from siliciclastic sediment low in organic carbon (< 0.2%) to organic rich ( approximately 3%) black sediments that rapidly accumulated in the early middle Eocene. Three geochemical environments were characterized based on chemical analyses of porewater: an upper ammonium oxidation zone, a carbonate dissolution zone and a deep (> 200 m below sea floor) sulfate reduction zone. The diversity of microbes within each zone was assessed using 16S rRNA phylogenetic markers. Bacterial 16S rRNA genes were successfully amplified from each of the biogeochemical zones, while archaea was only amplified from the deep sulfate reduction zone. The microbial communities at each zone are phylogenetically different and are most closely related to those from other deep subsurface environments.

DEEP U BAND AND R IMAGING OF GOODS-SOUTH: OBSERVATIONS, DATA REDUCTION AND FIRST RESULTS ,

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

Nonino, M.; Cristiani, S.; Vanzella, E.

2009-08-01

We present deep imaging in the U band covering an area of 630 arcmin{sup 2} centered on the southern field of the Great Observatories Origins Deep Survey (GOODS). The data were obtained with the VIMOS instrument at the European Southern Observatory (ESO) Very Large Telescope. The final images reach a magnitude limit U {sub lim} {approx} 29.8 (AB, 1{sigma}, in a 1'' radius aperture), and have good image quality, with full width at half-maximum {approx}0.''8. They are significantly deeper than previous U-band images available for the GOODS fields, and better match the sensitivity of other multiwavelength GOODS photometry. The deepermore » U-band data yield significantly improved photometric redshifts, especially in key redshift ranges such as 2 < z < 4, and deeper color-selected galaxy samples, e.g., Lyman break galaxies at z {approx} 3. We also present the co-addition of archival ESO VIMOS R-band data, with R {sub lim} {approx} 29 (AB, 1{sigma}, 1'' radius aperture), and image quality {approx}0.''75. We discuss the strategies for the observations and data reduction, and present the first results from the analysis of the co-added images.« less

Characterizations of geothermal springs along the Moxi deep fault in the western Sichuan plateau, China

NASA Astrophysics Data System (ADS)

Qi, Jihong; Xu, Mo; An, Chengjiao; Wu, Mingliang; Zhang, Yunhui; Li, Xiao; Zhang, Qiang; Lu, Guoping

2017-02-01

Abundant geothermal springs occur along the Moxi fault located in western Sichuan Province (the eastern edge of the Qinghai-Tibet plateau), highlighted by geothermal water outflow with an unusually high temperature of 218 °C at 21.5 MPa from a 2010-m borehole in Laoyulin, Kangding. Earthquake activity occurs relatively more frequently in the region and is considered to be related to the strong hydrothermal activity. Geothermal waters hosted by a deep fault may provide evidence regarding the deep underground; their aqueous chemistry and isotopic information can indicate the mechanism of thermal springs. Cyclical variations of geothermal water outflows are thought to work under the effect of solid earth tides and can contribute to understanding conditions and processes in underground geo-environments. This paper studies the origin and variations of the geothermal spring group controlled by the Moxi fault and discusses conditions in the deep ground. Flow variation monitoring of a series of parameters was performed to study the geothermal responses to solid tides. Geothermal reservoir temperatures are evaluated with Na-K-Mg data. The abundant sulfite content, dissolved oxygen (DO) and oxidation-reduction potential (ORP) data are discussed to study the oxidation-reduction states. Strontium isotopes are used to trace the water source. The results demonstrate that geothermal water could flow quickly through the Moxi fault the depth of the geothermal reservoir influences the thermal reservoir temperature, where supercritical hot water is mixed with circulating groundwater and can reach 380 °C. To the southward along the fault, the circulation of geothermal waters becomes shallower, and the waters may have reacted with metamorphic rock to some extent. Our results provide a conceptual deep heat source model for geothermal flow and the reservoir characteristics of the Moxi fault and indicate that the faulting may well connect the deep heat source to shallower depths. The approach of hot spring variation research also has potential benefits for earthquake monitoring and prediction.

Rates and extent of microbial debromination in the deep subseafloor biosphere

NASA Astrophysics Data System (ADS)

Berg, R. D.; Solomon, E. A.; Morris, R. M.

2013-12-01

Recent genomic and porewater geochemical data suggest that reductive dehalogenation of a wide range of halogenated organic compounds could represent an important energy source for deep subseafloor microbial communities. At continental slope sites worldwide, there is a remarkably linear relationship between porewater profiles of ammonium and bromide, indicating that the factors controlling the distribution and rates of dehalogenation have the potential to influence carbon and nitrogen cycling in the deep subsurface biosphere. Though this metabolic pathway could play an important role in the cycling of otherwise refractory pools of carbon and nitrogen in marine sediments and provide energy to microbial communities in the deep subsurface biosphere, the rates and extent of dehalogenation in marine sediments are poorly constrained. Here we report net reaction rate profiles of debromination activity in continental slope sediments, calculated from numerical modeling of porewater bromide profiles from several margins worldwide. The reaction rate profiles indicate three common zones of debromination activity in slope sediments: 1) low rates of debromination, and a potential bromine sink, in the upper sediment column correlating to the sulfate reduction zone, with net bromide removal rates from -3.6 x 10^-2 to -4.85 x 10^-1 μmol m^-2 yr^-1, 2) high rates of debromination from the sulfate-methane transition zone to ~40-100 mbsf, with net bromide release rates between 7.1 x 10^-2 to 3.9 x 10^-1 μmol m^-2 yr^-1, and 3) an inflection point at ~40-100 mbsf, below which net rates of debromination decrease by an order of magnitude and at several sites are indistinguishable from zero. These results indicate that dehalogenating activity is widely distributed in marine sediments, providing energy to fuel deep subseafloor microbial communities, with potentially important consequences for the global bromine and nitrogen cycles.

Numerical-experimental investigation of load paths in DP800 dual phase steel during Nakajima test

NASA Astrophysics Data System (ADS)

Bergs, Thomas; Nick, Matthias; Feuerhack, Andreas; Trauth, Daniel; Klocke, Fritz

2018-05-01

Fuel efficiency requirements demand lightweight construction of vehicle body parts. The usage of advanced high strength steels permits a reduction of sheet thickness while still maintaining the overall strength required for crash safety. However, damage, internal defects (voids, inclusions, micro fractures), microstructural defects (varying grain size distribution, precipitates on grain boundaries, anisotropy) and surface defects (micro fractures, grooves) act as a concentration point for stress and consequently as an initiation point for failure both during deep drawing and in service. Considering damage evolution in the design of car body deep drawing processes allows for a further reduction in material usage and therefore body weight. Preliminary research has shown that a modification of load paths in forming processes can help mitigate the effects of damage on the material. This paper investigates the load paths in Nakajima tests of a DP800 dual phase steel to research damage in deep drawing processes. Investigation is done via a finite element model using experimentally validated material data for a DP800 dual phase steel. Numerical simulation allows for the investigation of load paths with respect to stress states, strain rates and temperature evolution, which cannot be easily observed in physical experiments. Stress triaxiality and the Lode parameter are used to describe the stress states. Their evolution during the Nakajima tests serves as an indicator for damage evolution. The large variety of sheet metal forming specific load paths in Nakajima tests allows a comprehensive evaluation of damage for deep drawing. The results of the numerical simulation conducted in this project and further physical experiments will later be used to calibrate a damage model for simulation of deep drawing processes.

Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

PubMed

Terunuma, Toshiyuki; Tokui, Aoi; Sakae, Takeji

2018-03-01

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tracking should be performed by controlling "importance recognition": the understanding that soft-tissue is an important tracking feature and bone structure is unimportant. We propose a new real-time tumor-contouring method that uses deep learning with importance recognition control. The novelty of the proposed method is the combination of the devised random overlay method and supervised deep learning to induce the recognition of structures in tumor contouring as important or unimportant. This method can be used for tumor contouring because it uses deep learning to perform image segmentation. Our results from a simulated fluoroscopy model showed accurate tracking of a low-visibility tumor with an error of approximately 1 mm, even if enhanced bone structure acted as an obstacle. A high similarity of approximately 0.95 on the Jaccard index was observed between the segmented and ground truth tumor regions. A short processing time of 25 ms was achieved. The results of this simulated fluoroscopy model support the feasibility of robust real-time tumor contouring with fluoroscopy. Further studies using clinical fluoroscopy are highly anticipated.

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

King, M. P.; Kaplar, R. J.; Dickerson, J. R.

Electrical performance and characterization of deep levels in vertical GaN P-i-N diodes grown on low threading dislocation density (~10 4 –10 6 cm –2) bulk GaN substrates are investigated. The lightly doped n drift region of these devices is observed to be highly compensated by several prominent deep levels detected using deep level optical spectroscopy at E c-2.13, 2.92, and 3.2 eV. A combination of steady-state photocapacitance and lighted capacitance-voltage profiling indicates the concentrations of these deep levels to be N t = 3 × 10 12, 2 × 10 15, and 5 × 10 14 cm –3, respectively. Themore » E c-2.92 eV level is observed to be the primary compensating defect in as-grown n-type metal-organic chemical vapor deposition GaN, indicating this level acts as a limiting factor for achieving controllably low doping. The device blocking voltage should increase if compensating defects reduce the free carrier concentration of the n drift region. Understanding the incorporation of as-grown and native defects in thick n-GaN is essential for enabling large V BD in the next-generation wide-bandgap power semiconductor devices. Furthermore, controlling the as-grown defects induced by epitaxial growth conditions is critical to achieve blocking voltage capability above 5 kV.« less

Student Learning Approaches in the UAE: The Case for the Achieving Domain

ERIC Educational Resources Information Center

McLaughlin, James; Durrant, Philip

2017-01-01

The deep versus surface learning approach dichotomy has dominated recent research in student learning approach dimensions. However, the achievement dimension may differ in importance in non-Western and vocational tertiary settings. The aim was to assess how Emirati tertiary students could be characterized in terms of their learning approaches. The…

The Relationships among Middle School Students' Motivational Orientations, Learning Strategies, and Academic Achievement

ERIC Educational Resources Information Center

McClintic-Gilbert, Megan S.; Corpus, Jennifer Henderlong; Wormington, Stephanie V.; Haimovitz, Kyla

2013-01-01

The present study examined the extent to which middle school students' (N = 90) learning strategies mediated the relationship between their motivational orientations and academic achievement. Survey data revealed that higher degrees of intrinsic motivation predicted the use of both deep and surface learning strategies, whereas higher degrees of…

Lasing and Longitudinal Cavity Modes in Photo-Pumped Deep Ultraviolet AlGaN Heterostructures

DTIC Science & Technology

2013-04-29

of the structures were intentionally doped. The AlGaN composition was determined by triple -axis high-resolution X-ray diffraction measurements. Cross...threshold can be achieved on single crystal AlN substrates. This achievement serves as a starting point towards realizing electrically pumped sub-300 nm UV

Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies

ERIC Educational Resources Information Center

Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; vom Hofe, Rudolf

2013-01-01

This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10;…

[Perceptions of classroom goal structures, personal achievement goal orientations, and learning strategies].

PubMed

Miki, Kaori; Yamauchi, Hirotsugu

2005-08-01

We examined the relations among students' perceptions of classroom goal structures (mastery and performance goal structures), students' achievement goal orientations (mastery, performance, and work-avoidance goals), and learning strategies (deep processing, surface processing and self-handicapping strategies). Participants were 323 5th and 6th grade students in elementary schools. The results from structural equation modeling indicated that perceptions of classroom mastery goal structures were associated with students' mastery goal orientations, which were in turn related positively to the deep processing strategies and academic achievement. Perceptions of classroom performance goal stractures proved associated with work avoidance-goal orientations, which were positively related to the surface processing and self-handicapping strategies. Two types of goal structures had a positive relation with students' performance goal orientations, which had significant positive effects on academic achievement. The results of this study suggest that elementary school students' perceptions of mastery goal structures are related to adaptive patterns of learning more than perceptions of performance goal structures are. The role of perceptions of classroom goal structure in promoting students' goal orientations and learning strategies is discussed.

Modelled ocean changes at the Plio-Pleistocene transition driven by Antarctic ice advance

PubMed Central

Hill, Daniel J.; Bolton, Kevin P.; Haywood, Alan M.

2017-01-01

The Earth underwent a major transition from the warm climates of the Pliocene to the Pleistocene ice ages between 3.2 and 2.6 million years ago. The intensification of Northern Hemisphere Glaciation is the most obvious result of the Plio-Pleistocene transition. However, recent data show that the ocean also underwent a significant change, with the convergence of deep water mass properties in the North Pacific and North Atlantic Ocean. Here we show that the lack of coastal ice in the Pacific sector of Antarctica leads to major reductions in Pacific Ocean overturning and the loss of the modern North Pacific Deep Water (NPDW) mass in climate models of the warmest periods of the Pliocene. These results potentially explain the convergence of global deep water mass properties at the Plio-Pleistocene transition, as Circumpolar Deep Water (CDW) became the common source. PMID:28252023

Isolation of Geobacter species from diverse sedimentary environments

USGS Publications Warehouse

Coaxes, J.D.; Phillips, E.J.P.; Lonergan, D.J.; Jenter, H.; Lovley, D.R.

1996-01-01

In an attempt to better understand the microorganisms responsible for Fe(III) reduction in sedimentary environments, Fe(III)-reducing microorganisms were enriched for and isolated from freshwater aquatic sediments, a pristine deep aquifer, and a petroleum-contaminated shallow aquifer. Enrichments were initiated with acetate or toluene as the electron donor and Fe(III) as the electron acceptor. Isolations were made with acetate or benzoate. Five new strains which could obtain energy for growth by dissimilatory Fe(III) reduction were isolated. All five isolates are gram- negative strict anaerobes which grow with acetate as the electron donor and Fe(III) as the electron acceptor. Analysis of the 16S rRNA sequence of the isolated organisms demonstrated that they all belonged to the genus Geobacter in the delta subdivision of the Proteobacteria. Unlike the type strain, Geobacter metallireducens, three of the five isolates could use H2 as an electron donor fur Fe(III) reduction. The deep subsurface isolate is the first Fe(III) reducer shown to completely oxidize lactate to carbon dioxide, while one of the freshwater sediment isolates is only the second Fe(III) reducer known that can oxidize toluene. The isolation of these organisms demonstrates that Geobacter species are widely distributed in a diversity of sedimentary environments in which Fe(III) reduction is an important process.

40 CFR 415.113 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... economically achievable (BAT). 415.113 Section 415.113 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.113 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... economically achievable (BAT). 415.113 Section 415.113 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 425.33 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2014 CFR

2014-07-01

... achievable (BAT). 425.33 Section 425.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT): The...

40 CFR 415.663 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... economically achievable (BAT). 415.663 Section 415.663 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.203 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... economically achievable (BAT). 415.203 Section 415.203 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.203 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... economically achievable (BAT). 415.203 Section 415.203 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.673 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... economically achievable (BAT). 415.673 Section 415.673 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32 any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.653 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... economically achievable (BAT). 415.653 Section 415.653 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT): The...

40 CFR 415.343 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... economically achievable (BAT). 415.343 Section 415.343 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT): The...

40 CFR 425.33 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). 425.33 Section 425.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT): The...

40 CFR 415.663 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... economically achievable (BAT). 415.663 Section 415.663 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.423 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... economically achievable (BAT). 415.423 Section 415.423 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.653 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... economically achievable (BAT). 415.653 Section 415.653 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT): The...

40 CFR 415.343 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... economically achievable (BAT). 415.343 Section 415.343 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT): The...

40 CFR 415.673 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... economically achievable (BAT). 415.673 Section 415.673 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32 any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.663 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... economically achievable (BAT). 415.663 Section 415.663 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.203 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... economically achievable (BAT). 415.203 Section 415.203 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.423 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... economically achievable (BAT). 415.423 Section 415.423 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.343 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... economically achievable (BAT). 415.343 Section 415.343 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT): The...

40 CFR 415.673 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... economically achievable (BAT). 415.673 Section 415.673 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32 any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.113 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... economically achievable (BAT). 415.113 Section 415.113 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

40 CFR 415.653 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... economically achievable (BAT). 415.653 Section 415.653 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT): The...

40 CFR 415.423 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... economically achievable (BAT). 415.423 Section 415.423 Protection of Environment ENVIRONMENTAL PROTECTION... achievable (BAT). Except as provided in 40 CFR 125.30 through 125.32, any existing point source subject to... reduction attainable by the application of the best available technology economically achievable (BAT...

Posterior distraction reduction and occipitocervical fixation for the treatment of basilar invagination and atlantoaxial dislocation.

PubMed

Meng, Yang; Chen, Hua; Lou, Jigang; Rong, Xin; Wang, Beiyu; Deng, Yuxiao; Ding, Chen; Hong, Ying; Liu, Hao

2016-01-01

To introduce a novel distraction technique for the treatment of basilar invagination (BI) and atlantoaxial dislocation (AAD) via a posterior-only approach. Twenty-one consecutive patients with BI and AAD who underwent posterior distraction reduction and occipitocervical fixation between January 2009 and June 2013 were enrolled in the present study. This novel distraction technique included two steps. First, the distraction between the occipitocervical junction of the rod (OCJR) and the occipital screws was performed to achieve horizontal and partial vertical reduction. Secondly, the distraction was performed between the C2 screws and OCJR to achieve complete vertical reduction. The pre- and postoperative JOA score, the extent of reduction, the fusion status, and the complications were recorded and analyzed. The mean follow-up was 18.3 months with a range of 10-32 months. No patient incurred neurovascular injury during surgery. The mean JOA score at the last follow-up (15.4) showed significant improvement (P<0.01) compared with the pre-operative parameters (11.2). Complete horizontal reduction was achieved in 18 patients (85.7%), and complete vertical reduction was achieved in 17 patients (80.9%). The rest patients are all received greater than 50% horizontal and vertical reduction. Solid fusion was achieved in 20 patients (95.2%). Mild dysphagia was observed in two patients. One patient suffered from postoperative fever and pulmonary infection. This novel distraction technique may provide satisfactory reduction via a posterior-only approach without exposure of the C1/2 facet joint. Therefore, it is a safe and effective method for the treatment of BI with AAD. Copyright © 2015 Elsevier B.V. All rights reserved.

Deep-Sea Carbonate Accumulation and Surface Ocean Saturation State in the Aftermath of the Cretaceous-Paleogene extinction

NASA Astrophysics Data System (ADS)

Pruss, S. B.; Higgins, J. A.; Bush, A. M.; Leckie, R. M.; Deeg, C.; Getzin, B. L.

2016-12-01

The role of the K-Pg extinction on biogeochemical cycling has been intensively studied in recent years. However, it remains unknown how extinctions in marine pelagic calcifiers impacted carbon cycling in the ocean. Low accumulation rates of microfossils in the aftermath of the extinction have been attributed to lowered production, which triggered a reduction in carbonate delivery to the seafloor. Interestingly, although microfossil abundance is lower and foraminifera are significantly smaller than in the latest Cretaceous, carbonate accumulated on the seafloor in the earliest Paleogene even in areas that should have been below the CCD. One such deep-water site in the South Pacific (U1370) was cored during IODP Expedition 329 in November 2010. We examined 16 samples from an anomalous carbonate layer provisionally assigned to lower Paleocene planktonic foraminiferal Zones P1a and P1b that preserves benthic and planktonic foraminifera. Carbon isotope values of the benthic species Nuttalies orealis range from 1.45 to 1.95‰ VPDB in the 16 samples. The planktonic species Parasubbotina pseudobulloides was only abundant enough for analysis in 4 samples, and these values range from 1.41 to 1.91‰ VPDB. We note, as others have, that no carbon isotope gradient existed between the benthic and planktonic foraminifera during the deposition of this carbonate layer, perhaps due to reduced primary production and/or export of organic carbon. The presence of this carbonate layer in the deep ocean and its preservation of a collapsed isotopic gradient are both consistent with a reduction in the surface-to-deep water gradient in carbonate saturation state during the unusual oceanographic conditions that followed the extinction. We speculate that this was associated with a sustained reduction in surface ocean saturation state with adverse consequences for neritic carbonate producers in the aftermath of the K-T extinction.

Multiple sulfur isotope records at the end-Guadalupian (Permian) at Chaotian, China: Implications for a role of bioturbation in the Phanerozoic sulfur cycle

NASA Astrophysics Data System (ADS)

Saitoh, Masafumi; Ueno, Yuichiro; Matsu'ura, Fumihiro; Kawamura, Tetsuya; Isozaki, Yukio; Yao, Jianxin; Ji, Zhansheng; Yoshida, Naohiro

2017-03-01

A recent study on quadruple sulfur isotopes (32S, 33S, 34S, and 36S) of sedimentary pyrite suggested that the end-Guadalupian extinction was caused by shoaling of the sulfidic deep-water. This scenario is based on the assumption that sulfur isotopic compositions of pyrite from hosting sediments were controlled by benthos activities, thus by the redox conditions of the sedimentary environments. Nonetheless, the relationship between the sulfur isotope records and redox conditions, reconstructed from litho- and bio-facies, are poorly known. In order to examine the effect of bioturbation in sediments, quadruple sulfur isotopic compositions of sedimentary pyrite from the end-Guadalupian succession in Chaotian, South China, were analyzed. Black mudstones of deep-water facies immediately below the extinction horizon have consistently high Δ33S values of ca. +0.079‰, clearly suggesting a sulfate reduction in the anoxic water column. Our new data are consistent with the emergence of a sulfidic deep-water mass prior to the end-Guadalupian extinction; the upwelling of the toxic deep-water may have contributed to the extinction. In contrast, shallow-marine bioclastic limestones with burrows deposited under oxic conditions have negative Δ33S values. This anomalous isotopic signal indicates the mixing of two distinct types of pyrite; one generated during the sulfate reduction in an open system and the other in a closed system. We interpret that bioturbation supplied sulfate in the sediments and promoted sulfate reduction and in-situ sulfide precipitation within the sediments. The negative Δ33S values of oxic sediments in Chaotian are inconsistent with the previous model and demonstrate that the sedimentary sulfur cycle associated with bioturbation was more complicated than previously thought. Our study also implies that, more generally, the role of bioturbation in increasing seawater sulfate concentration in the Phanerozoic may have been overestimated in the previous studies, because bioturbation may have enhanced sulfide burial or sulfur output from the oceans.

Using the Deep Space Atomic Clock for Navigation and Science.

PubMed

Ely, Todd A; Burt, Eric A; Prestage, John D; Seubert, Jill M; Tjoelker, Robert L

2018-06-01

Routine use of one-way radiometric tracking for deep space navigation and radio science is not possible today because spacecraft frequency and time references that use state-of-the-art ultrastable oscillators introduce errors from their intrinsic drift and instability on timescales past 100 s. The Deep Space Atomic Clock (DSAC), currently under development as a NASA Technology Demonstration Mission, is an advanced prototype of a space-flight suitable, mercury-ion atomic clock that can provide an unprecedented frequency and time stability in a space-qualified clock. Indeed, the ground-based results of the DSAC space demonstration unit have already achieved an Allan deviation of at one day; space performance on this order will enable the use of one-way radiometric signals for deep space navigation and radio science.

Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

PubMed

Li, Zhixi; He, Yifan; Keel, Stuart; Meng, Wei; Chang, Robert T; He, Mingguang

2018-03-02

To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs. A deep learning system for the classification of GON was developed for automated classification of GON on color fundus photographs. We retrospectively included 48 116 fundus photographs for the development and validation of a deep learning algorithm. This study recruited 21 trained ophthalmologists to classify the photographs. Referable GON was defined as vertical cup-to-disc ratio of 0.7 or more and other typical changes of GON. The reference standard was made until 3 graders achieved agreement. A separate validation dataset of 8000 fully gradable fundus photographs was used to assess the performance of this algorithm. The area under receiver operator characteristic curve (AUC) with sensitivity and specificity was applied to evaluate the efficacy of the deep learning algorithm detecting referable GON. In the validation dataset, this deep learning system achieved an AUC of 0.986 with sensitivity of 95.6% and specificity of 92.0%. The most common reasons for false-negative grading (n = 87) were GON with coexisting eye conditions (n = 44 [50.6%]), including pathologic or high myopia (n = 37 [42.6%]), diabetic retinopathy (n = 4 [4.6%]), and age-related macular degeneration (n = 3 [3.4%]). The leading reason for false-positive results (n = 480) was having other eye conditions (n = 458 [95.4%]), mainly including physiologic cupping (n = 267 [55.6%]). Misclassification as false-positive results amidst a normal-appearing fundus occurred in only 22 eyes (4.6%). A deep learning system can detect referable GON with high sensitivity and specificity. Coexistence of high or pathologic myopia is the most common cause resulting in false-negative results. Physiologic cupping and pathologic myopia were the most common reasons for false-positive results. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Integrated piezoelectric actuators in deep drawing tools to reduce the try-out

NASA Astrophysics Data System (ADS)

Neugebauer, Reimund; Mainda, Patrick; Kerschner, Matthias; Drossel, Welf-Guntram; Roscher, Hans-Jürgen

2011-05-01

Tool making is a very time consuming and expensive operation because many iteration loops are used to manually adjust tool components during the try-out process. That means that trying out deep drawing tools is 30% of the total costs. This is the reason why an active deep drawing tool was developed at the Fraunhofer Institute for Machine Tools and Forming Technology IWU in cooperation with Audi and Volkswagen to reduce the costs and production rates. The main difference between the active and conventional deep drawing tools is using piezoelectric actuators to control the forming process. The active tool idea, which is the main subject of this research, will be presented as well as the findings of experiments with the custom-built deep drawing tool. This experimental tool was designed according to production requirements and has been equipped with piezoelectric actuators that allow active pressure distribution on the sheet metal flange. The disposed piezoelectric elements are similar to those being used in piezo injector systems for modern diesel engines. In order to achieve the required force, the actuators are combined in a cluster that is embedded in the die of the deep drawing tool. One main objective of this work, i.e. reducing the time-consuming try-out-period, has been achieved with the experimental tool which means that the actuators were used to set static pressure distribution between the blankholder and die. We will present the findings of our analysis and the advantages of the active system over a conventional deep drawing tool. In addition to the ability of changing the static pressure distribution, the piezoelectric actuator can also be used to generate a dynamic pressure distribution during the forming process. As a result the active tool has the potential to expand the forming constraints to make it possible to manage forming restrictions caused by light weight materials in future.

Dynamic Geospatial Modeling of the Building Stock to Project Urban Energy Demand.

PubMed

Breunig, Hanna Marie; Huntington, Tyler; Jin, Ling; Robinson, Alastair; Scown, Corinne Donahue

2018-06-26

In the United States, buildings account for more than 40 percent of total energy consumption, and the evolution of the urban form will impact the effectiveness of strategies to reduce energy use and mitigate emissions. This paper presents a broadly applicable approach for modeling future commercial, residential, and industrial floorspace, thermal consumption (heating and cooling), and associated GHG emissions at the tax assessor land parcel level. The approach accounts for changing building standards and retrofitting, climate change, and trends in housing and industry. We demonstrate the automated workflow for California, and project building stock, thermal energy consumption, and associated GHG emissions out to 2050. Our results suggest that if buildings in California have long lifespans, and minimal energy efficiency improvements compared to building codes reflective of 2008, then the state will face a 20% or higher increase in thermal energy consumption by 2050. Baseline annual GHG emissions associated with thermal energy consumption in the modeled building stock in 2016 is 34% below 1990 levels (110 Mt CO2eq/y).While the 2020 targets for the reduction of GHG emissions set by the California Senate Bill 350 have already been met, none of our scenarios achieve >80% reduction from 1990 levels by 2050, despite assuming an 86% reduction in electricity carbon intensity in our "Low Carbon" scenario. The results highlight the challenge California faces in meeting its new energy efficiency targets unless the State's building stock undergoes timely and strategic turnover, paired with deep retrofitting of existing buildings and natural gas equipment.

Megasessions: Efficacy of Fewer, Longer Treatment Sessions for Fat Reduction in Noninvasive Body Contouring Using a Radiofrequency Based Device.

PubMed

Duncan, Diane

2017-05-01

While the field of noninvasive body contouring is booming, many patients still note a lesser result than they might achieve with a single session of liposuction or dermolipectomy. The duration of a noninvasive fat reduction treatment series can be daunting. Patients have questioned the worth of these procedures when the expected benefit is modest and the time they devote to the project is significant. An eight-patient mini-study was performed to see if two or three "megasessions" could be substituted for eight weekly sessions of bipolar radiofrequency based fat reduction treatments. Patients were randomized into a two session or three session group by drawing straws. The device used was the BodyFX bipolar RF device by InMode. This device employs a suction coupled vacuum that heats a section of skin and soft tissue in the treatment region and delivers a high voltage pulse. Each patient was treated for 2 hours per session, using the Body FX, more superficial Mini FX, and the Deep FX device in an effort to treat on a multilevel basis. Preoperative 2D and 3D Vectra photos were taken, and were repeated at 1 month and 3 months post-treatment. Volumetric analysis and patient assessment showed similar results with a two or three treatment "megasession" protocol when compared with the traditional protocol of eight weekly sessions. While the cohort number was not statistically significant, the photographs and measurements are compelling enough to warrant further investigation into this treatment protocol.

J Drugs Dermatol. 2017;16(5):478-480.

Class Size Reduction in Practice: Investigating the Influence of the Elementary School Principal

ERIC Educational Resources Information Center

Burch, Patricia; Theoharis, George; Rauscher, Erica

2010-01-01

Class size reduction (CSR) has emerged as a very popular, if not highly controversial, policy approach for reducing the achievement gap. This article reports on findings from an implementation study of class size reduction policy in Wisconsin entitled the Student Achievement Guarantee in Education (SAGE). Drawing on case studies of nine schools,…

A Model of Carbon Capture and Storage with Demonstration of Global Warming Potential and Fossil Fuel Resource Use Efficiency

NASA Astrophysics Data System (ADS)

Suebsiri, Jitsopa

Increasing greenhouse gas concentration in the atmosphere influences global climate change even though the level of impact is still unclear. Carbon dioxide capture and storage (CCS) is increasingly seen as an important component of broadly based greenhouse gas reduction measures. Although the other greenhouse gases are more potent, the sheer volume of CO 2 makes it dominant in term of its effect in the atmosphere. To understand the implications, CCS activities should be studied from a full life cycle perspective. This thesis outlines the successful achievement of the objectives of this study in conducting life cycle assessment (LCA), reviewing the carbon dioxide implications only, combining two energy systems, coal-fired electrical generations and CO2 used for enhanced oil recovery (EOR). LCA is the primary approach used in this study to create a tool for CCS environmental evaluation. The Boundary Dam Power Station (BDPS) and the Weyburn-Midale CO 2 EOR Project in Saskatchewan, Canada, are studied and adopted as case scenarios to find the potential for effective application of CCS in both energy systems. This study demonstrates two levels of retrofitting of the BDPS, retrofit of unit 3 or retrofit of all units, combined with three options for CO 2 geological storage: deep saline aquifer, CO2 EOR, and a combination of deep saline aquifer storage and CO2 EOR. Energy output is considered the product of combining these two energy resources (coal and oil). Gigajoules (GJ) are used as the fundamental unit of measurement in comparing the combined energy types. The application of this tool effectively demonstrates the results of application of a CCS system concerning global warming potential (GWP) and fossil fuel resource use efficiency. Other environmental impacts could be analyzed with this tool as well. In addition, the results demonstrate that the GWP reduction is directly related to resource use efficiency. This means the lower the GWP of CCS, the lower resource use efficiency as well. Three processes, coal mining, power production including CO2 capture unit operation, and crude oil usage, must be included when the GWP of CCS is calculated. Moreover, the results from the sensitivity analysis of power generation efficiency present not only a significant reduction of GWP, but also a competitive solution for improving or at least preventing the decrease of fossil fuel resource use efficiency when CCS is applied.

Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks.

PubMed

Kim, D H; MacKinnon, T

2018-05-01

To identify the extent to which transfer learning from deep convolutional neural networks (CNNs), pre-trained on non-medical images, can be used for automated fracture detection on plain radiographs. The top layer of the Inception v3 network was re-trained using lateral wrist radiographs to produce a model for the classification of new studies as either "fracture" or "no fracture". The model was trained on a total of 11,112 images, after an eightfold data augmentation technique, from an initial set of 1,389 radiographs (695 "fracture" and 694 "no fracture"). The training data set was split 80:10:10 into training, validation, and test groups, respectively. An additional 100 wrist radiographs, comprising 50 "fracture" and 50 "no fracture" images, were used for final testing and statistical analysis. The area under the receiver operator characteristic curve (AUC) for this test was 0.954. Setting the diagnostic cut-off at a threshold designed to maximise both sensitivity and specificity resulted in values of 0.9 and 0.88, respectively. The AUC scores for this test were comparable to state-of-the-art providing proof of concept for transfer learning from CNNs in fracture detection on plain radiographs. This was achieved using only a moderate sample size. This technique is largely transferable, and therefore, has many potential applications in medical imaging, which may lead to significant improvements in workflow productivity and in clinical risk reduction. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

New Hampshire Better Buildings - Final Report

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

Cramton, Karen; Peters, Katherine

2014-11-01

With $10 million in funding from the U.S. Department of Energy's (DOE) Better Buildings Neighborhood Program, the NH Better Buildings program was established as an initiative that initially empowered the three “Beacon Communities” of Berlin, Nashua and Plymouth to achieve transformative energy savings and reductions in fossil fuel use and greenhouse gases through deep energy retrofits and complementary sustainable energy solutions. The program also enabled those Communities to provide leadership to other communities around the state as “beacons” of energy efficiency. The goal of the program was to reduce energy use by a minimum of 15% through energy efficiency upgradesmore » in residential and commercial buildings in the communities. The program expanded statewide in April 2012 by issuing a competitive solicitation for additional commercial projects non-profit, and municipal energy efficiency projects from any community in the state, and a partnership with the state’s utility-run, ratepayer-funded residential Home Performance with ENERGY STAR® (HPwES) program. The NH Better Buildings program was administered by the New Hampshire Office of Energy and Planning (OEP) and managed by the NH Community Development Finance Authority (CDFA). The program started in July 2010 and the last projects funded with American Reinvestment and Recovery Act (ARRA) funds were completed in August 2013. The program will continue after the American Recovery and Reinvestment Act program period as a Revolving Loan Fund, enabling low-interest financing for deep energy retrofits into the future.« less

Nonlinear Inference in Partially Observed Physical Systems and Deep Neural Networks

NASA Astrophysics Data System (ADS)

Rozdeba, Paul J.

The problem of model state and parameter estimation is a significant challenge in nonlinear systems. Due to practical considerations of experimental design, it is often the case that physical systems are partially observed, meaning that data is only available for a subset of the degrees of freedom required to fully model the observed system's behaviors and, ultimately, predict future observations. Estimation in this context is highly complicated by the presence of chaos, stochasticity, and measurement noise in dynamical systems. One of the aims of this dissertation is to simultaneously analyze state and parameter estimation in as a regularized inverse problem, where the introduction of a model makes it possible to reverse the forward problem of partial, noisy observation; and as a statistical inference problem using data assimilation to transfer information from measurements to the model states and parameters. Ultimately these two formulations achieve the same goal. Similar aspects that appear in both are highlighted as a means for better understanding the structure of the nonlinear inference problem. An alternative approach to data assimilation that uses model reduction is then examined as a way to eliminate unresolved nonlinear gating variables from neuron models. In this formulation, only measured variables enter into the model, and the resulting errors are themselves modeled by nonlinear stochastic processes with memory. Finally, variational annealing, a data assimilation method previously applied to dynamical systems, is introduced as a potentially useful tool for understanding deep neural network training in machine learning by exploiting similarities between the two problems.

Effective photodynamic therapy against microbial populations in human deep tissue abscess aspirates

PubMed Central

Haidaris, Constantine G.; Foster, Thomas H.; Waldman, David L.; Mathes, Edward J.; McNamara, JoAnne; Curran, Timothy

2014-01-01

Background and Objective The primary therapy for deep tissue abscesses is drainage accompanied by systemic antimicrobial treatment. However, the long antibiotic course required increases the probability of acquired resistance, and the high incidence of polymicrobial infections in abscesses complicates treatment choices. Photodynamic therapy (PDT) is effective against multiple classes of organisms, including those displaying drug resistance, and may serve as a useful adjunct to the standard of care by reduction of abscess microbial burden following drainage. Study Design/Materials and Methods Aspirates were obtained from 32 patients who underwent image-guided percutaneous drainage of the abscess cavity. The majority of the specimens (24/32) were abdominal, with the remainder from liver and lung. Conventional microbiological techniques and nucleotide sequence analysis of rRNA gene fragments were used to characterize microbial populations from abscess aspirates. We evaluated the sensitivity of microorganisms to methylene blue-sensitized PDT in vitro both within the context of an abscess aspirate and as individual isolates. Results Most isolates were bacterial, with the fungus Candida tropicalis also isolated from two specimens. We examined the sensitivity of these microorganisms to methylene blue-PDT. Complete elimination of culturable microorganisms was achieved in three different aspirates, and significant killing (p < 0.0001) was observed in all individual microbial isolates tested compared to controls. Conclusions These results and the technical feasibility of advancing optical fibers through catheters at the time of drainage motivate further work on including PDT as a therapeutic option during abscess treatment. PMID:23996629

Effective photodynamic therapy against microbial populations in human deep tissue abscess aspirates.

PubMed

Haidaris, Constantine G; Foster, Thomas H; Waldman, David L; Mathes, Edward J; McNamara, Joanne; Curran, Timothy

2013-10-01

The primary therapy for deep tissue abscesses is drainage accompanied by systemic antimicrobial treatment. However, the long antibiotic course required increases the probability of acquired resistance, and the high incidence of polymicrobial infections in abscesses complicates treatment choices. Photodynamic therapy (PDT) is effective against multiple classes of organisms, including those displaying drug resistance, and may serve as a useful adjunct to the standard of care by reduction of abscess microbial burden following drainage. Aspirates were obtained from 32 patients who underwent image-guided percutaneous drainage of the abscess cavity. The majority of the specimens (24/32) were abdominal, with the remainder from liver and lung. Conventional microbiological techniques and nucleotide sequence analysis of rRNA gene fragments were used to characterize microbial populations from abscess aspirates. We evaluated the sensitivity of microorganisms to methylene blue-sensitized PDT in vitro both within the context of an abscess aspirate and as individual isolates. Most isolates were bacterial, with the fungus Candida tropicalis also isolated from two specimens. We examined the sensitivity of these microorganisms to methylene blue-PDT. Complete elimination of culturable microorganisms was achieved in three different aspirates, and significant killing (P < 0.0001) was observed in all individual microbial isolates tested compared to controls. These results and the technical feasibility of advancing optical fibers through catheters at the time of drainage motivate further work on including PDT as a therapeutic option during abscess treatment. © 2013 Wiley Periodicals, Inc.

40 CFR 430.84 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2013 CFR

2013-07-01

... achievable (BAT). [Reserved] 430.84 Section 430.84 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... effluent reduction attainable by the application of best available technology economically achievable (BAT...

40 CFR 430.84 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2014 CFR

2014-07-01

... achievable (BAT). [Reserved] 430.84 Section 430.84 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... effluent reduction attainable by the application of best available technology economically achievable (BAT...

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

Software Graphics Processing Unit (sGPU) for Deep Space Applications

NASA Technical Reports Server (NTRS)

McCabe, Mary; Salazar, George; Steele, Glen

2015-01-01

A graphics processing capability will be required for deep space missions and must include a range of applications, from safety-critical vehicle health status to telemedicine for crew health. However, preliminary radiation testing of commercial graphics processing cards suggest they cannot operate in the deep space radiation environment. Investigation into an Software Graphics Processing Unit (sGPU)comprised of commercial-equivalent radiation hardened/tolerant single board computers, field programmable gate arrays, and safety-critical display software shows promising results. Preliminary performance of approximately 30 frames per second (FPS) has been achieved. Use of multi-core processors may provide a significant increase in performance.

Bathyal sea urchins of the Bahamas, with notes on covering behavior in deep sea echinoids (Echinodermata: Echinoidea)

NASA Astrophysics Data System (ADS)

Pawson, David L.; Pawson, Doris J.

2013-08-01

In a survey of the bathyal echinoderms of the Bahama Islands region using manned submersibles, approximately 200 species of echinoderms were encountered and documented; 33 species were echinoids, most of them widespread in the general Caribbean area. Three species were found to exhibit covering behavior, the piling of debris on the upper surface of the body. Active covering is common in at least 20 species of shallow-water echinoids, but it has been reliably documented previously only once in deep-sea habitats. Images of covered deep-sea species, and other species of related interest, are provided. Some of the reasons adduced in the past for covering in shallow-water species, such as reduction of incident light intensity, physical camouflage, ballast in turbulent water, protection from desiccation, presumably do not apply in bathyal species. The main reasons for covering in deep, dark, environments are as yet unknown. Some covering behavior in the deep sea may be related to protection of the genital pores, ocular plates, or madreporite. Covering in some deep-sea species may also be merely a tactile reflex action, as some authors have suggested for shallow-water species.

Technology Development for a Stirling Radioisotope Power System for Deep Space Missions

NASA Technical Reports Server (NTRS)

Thieme, Lanny G.; Qiu, Songgang; White, Maurice A.

2000-01-01

NASA Glenn Research Center and the Department of Energy (DOE) are developing a Stirling convertor for an advanced radioisotope power system to provide spacecraft on-board electric power for NASA deep space missions. NASA Glenn is addressing key technology issues through the use of two NASA Phase 2 SBIRs with Stirling Technology Company (STC) of Kennewick, WA. Under the first SBIR, STC demonstrated a 40 to 50 fold reduction in vibrations, compared to an unbalanced convertor, with a synchronous connection of two thermodynamically independent free-piston Stirling convertors. The second SBIR is for the development of an Adaptive Vibration Reduction System (AVRS) that will essentially eliminate vibrations over a mission lifetime, even in the unlikely event of a failed convertor. This paper discusses the status and results for these two SBIR projects and also presents results for characterizing the friction factor of high-porosity random fiber regenerators that are being used for this application.

A Systematic Review of Behavioral Interventions to Reduce Condomless Sex and Increase HIV Testing for Latino MSM.

PubMed

Pérez, Ashley; Santamaria, E Karina; Operario, Don

2017-12-15

Latino men who have sex with men (MSM) in the United States are disproportionately affected by HIV, and there have been calls to improve availability of culturally sensitive HIV prevention programs for this population. This article provides a systematic review of intervention programs to reduce condomless sex and/or increase HIV testing among Latino MSM. We searched four electronic databases using a systematic review protocol, screened 1777 unique records, and identified ten interventions analyzing data from 2871 Latino MSM. Four studies reported reductions in condomless anal intercourse, and one reported reductions in number of sexual partners. All studies incorporated surface structure cultural features such as bilingual study recruitment, but the incorporation of deep structure cultural features, such as machismo and sexual silence, was lacking. There is a need for rigorously designed interventions that incorporate deep structure cultural features in order to reduce HIV among Latino MSM.

Oak Forest Responses to Episodic-Seasonal-Drought, Chronic Multi-year Precipitation Change and Acute Drought Manipulations in a Region With Deep Soils and High Precipitation

NASA Astrophysics Data System (ADS)

Hanson, Paul J.; Wullschleger, Stan D.; Todd, Donald E.; Auge, Robert M.; Froberg, Mats; Johnson, Dale W.

2010-05-01

Implications of episodic-seasonal drought (extremely dry late summers), chronic multi-year precipitation manipulations (±33 percent over 12 years) and acute drought (-100 percent over 3 years) were evaluated for the response of vegetation and biogeochemical cycles for an upland-oak forest. The Quercus-Acer forest is located in eastern Tennessee on deep acidic soils with mean annual temperatures of 14.2 °C and abundant precipitation (1352 mm y-1). The multi-year observations and chronic manipulations were conducted from 1993 through 2005 using understory throughfall collection troughs and redistribution gutters and pipes. Acute manipulations of dominant canopy trees (Quercus prinus; Liriodendron tulipifera) were conducted from 2003 through 2005 using full understory tents. Regional and severe late-summer droughts were produced reduced stand water use and photosynthetic carbon gain as expected. Likewise, seedlings and saplings exhibited reduced survival and cumulative growth reductions. Conversely, multi-year chronic increases or decreases in precipitation and associated soil water deficits did not reduce large tree basal area growth for the tree species present. The resilience of canopy trees to chronic-change was the result of a disconnect between carbon allocation to tree growth (an early-season phenomenon) and late-season drought occurrence. Acute precipitation exclusion from the largest canopy trees also produced limited physiological responses and minimal cumulative growth reductions. Lateral root water sources were removed through trenching and could not explain the lack of response to extreme soil drying. Therefore, deep rooting the primary mechanism for large-tree resilience to severe drought. Extensive trench-based assessments of rooting depth suggested that ‘deep' water supplies were being obtained from limited numbers of deep fine roots. Observations of carbon stocks in organic horizons demonstrated accumulation with precipitation reductions and drying, but no change in mineral soil carbon pools attributable to changing precipitation. Measured changes in nitrogen and other element pools suggested that long term immobilization of elements with chronic drying would lead to reduced growth, but that deep rooting access to the key base cations would moderate such effects by providing a source of minerals to be cycled in near surface soils. Cumulative changes in canopy foliar production were evident over time showing sustained or even increased production with chronic drying. This unexpected response is hypothesized to result from the retention of nutrients in highly-rooted surface horizons made available for plant uptake during spring mineralization.

Russian Policy on Methane Emissions in the Oil and Gas Sector: A Case Study in Opportunities and Challenges in Reducing Short-Lived Forcers

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

Evans, Meredydd; Roshchanka, Volha

2014-08-04

This paper uses Russian policy in the oil and gas sector as a case study in assessing options and challenges for scaling-up emission reductions. We examine the challenges to achieving large-scale emission reductions, successes that companies have achieved to date, how Russia has sought to influence methane emissions through its environmental fine system, and options for helping companies achieve large-scale emission reductions in the future through simpler and clearer incentives.

Wastewater recycling and heat reclamation at the Red Lion Central Laundry, Portland, Oregon

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

Garlick, T.F.; Halverson, M.A.; Ledbetter, M.R.

1996-09-01

This report discusses water, energy, and cost savings that can be achieved in a commercial laundry through the use of a wastewater recycling and heat recovery system. Cost savings are achieved through reductions in water use, reduction in sewage charges, reductions in water heating energy, and potential reductions in water treatment chemicals. This report provides an economic analysis of the impact of capital investment, daily consumption, and local utility rates on the payback period.

Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation

NASA Astrophysics Data System (ADS)

Gaonkar, Bilwaj; Hovda, David; Martin, Neil; Macyszyn, Luke

2016-03-01

Deep Learning, refers to large set of neural network based algorithms, have emerged as promising machine- learning tools in the general imaging and computer vision domains. Convolutional neural networks (CNNs), a specific class of deep learning algorithms, have been extremely effective in object recognition and localization in natural images. A characteristic feature of CNNs, is the use of a locally connected multi layer topology that is inspired by the animal visual cortex (the most powerful vision system in existence). While CNNs, perform admirably in object identification and localization tasks, typically require training on extremely large datasets. Unfortunately, in medical image analysis, large datasets are either unavailable or are extremely expensive to obtain. Further, the primary tasks in medical imaging are organ identification and segmentation from 3D scans, which are different from the standard computer vision tasks of object recognition. Thus, in order to translate the advantages of deep learning to medical image analysis, there is a need to develop deep network topologies and training methodologies, that are geared towards medical imaging related tasks and can work in a setting where dataset sizes are relatively small. In this paper, we present a technique for stacked supervised training of deep feed forward neural networks for segmenting organs from medical scans. Each `neural network layer' in the stack is trained to identify a sub region of the original image, that contains the organ of interest. By layering several such stacks together a very deep neural network is constructed. Such a network can be used to identify extremely small regions of interest in extremely large images, inspite of a lack of clear contrast in the signal or easily identifiable shape characteristics. What is even more intriguing is that the network stack achieves accurate segmentation even when it is trained on a single image with manually labelled ground truth. We validate this approach,using a publicly available head and neck CT dataset. We also show that a deep neural network of similar depth, if trained directly using backpropagation, cannot acheive the tasks achieved using our layer wise training paradigm.

Subconjunctival PRGF Fibrin Membrane as an Adjuvant to Nonpenetrating Deep Sclerectomy: A 2-Year Pilot Study.

PubMed

Rodríguez-Agirretxe, Iñaki; Freire, Vanesa; Muruzabal, Francisco; Orive, Gorka; Anitua, Eduardo; Díez-Feijóo, Elio; Acera, Arantxa

2018-01-01

To evaluate the potential role of the autologous PRGF (plasma rich in growth factors) fibrin membrane in tissue regeneration after glaucoma filtering surgery. Ten patients with medically uncontrolled primary open-angle glaucoma underwent nonpenetrating deep sclerectomy and were treated with PRGF fibrin membrane as adjuvant. Intraocular pressure reduction was the primary outcome. This variable was measured preoperatively and also at each follow-up visit. Secondary outcomes included the number of antiglaucoma medications, anterior segment optical coherence tomography bleb examination, photographic bleb evaluation, and subjective clinical symptomatology evaluation. The surgical technique showed a significant reduction (p < 0.05) in intraocular pressure in relation to preoperative values at each time of the study, decreasing from 23.3 ± 6.4 to 15.2 ± 4.6 mm Hg at 2 years. Furthermore, the number of antiglaucoma medications consumed showed a significant reduction at the end point of the study compared with the preoperative situation. Optical coherence tomography and photographic filtering bleb variables experienced a progressive reduction during the follow-up. Subjective symptoms showed a reduction from 8.3 ± 4.5 to 4.2 ± 5.3 at 2 years. PRGF-Endoret treatment could promote ocular surface regeneration after glaucoma surgery, enhancing the surgery success rates and reducing the need for postoperative medications. It is important to highlight that this is a preliminary study and some large clinical studies are necessary to verify these results. © 2017 S. Karger AG, Basel.

Emotions, Self-Regulated Learning, and Achievement in Mathematics: A Growth Curve Analysis

ERIC Educational Resources Information Center

Ahmed, Wondimu; van der Werf, Greetje; Kuyper, Hans; Minnaert, Alexander

2013-01-01

The purpose of the current study was twofold: (a) to investigate the developmental trends of 4 academic emotions (anxiety, boredom, enjoyment, and pride) and (b) to examine whether changes in emotions are linked to the changes in students' self-regulatory strategies (shallow, deep, and meta-cognitive) and achievement in mathematics. Four hundred…

An Examination of the Interrelationships between Self-Esteem, Others' Expectations, Family Support, Learning Approaches and Academic Achievement

ERIC Educational Resources Information Center

Roman, Sergio; Cuestas, Pedro J.; Fenollar, Pedro

2008-01-01

The current research represents an initial step into the analysis of the effect of self-esteem, others' (peers and teachers) expectations and family support on academic achievement through learning approaches (deep processing, surface processing and effort). Data were gathered from 553 university students from different faculties of a Spanish…

Academic Self-Concept and Learning Strategies: Direction of Effect on Student Academic Achievement

ERIC Educational Resources Information Center

McInerney, Dennis M.; Cheng, Rebecca Wing-yi; Mok, Magdalena Mo Ching; Lam, Amy Kwok Hap

2012-01-01

This study examined the prediction of academic self-concept (English and Mathematics) and learning strategies (deep and surface), and their direction of effect, on academic achievement (English and Mathematics) of 8,354 students from 16 secondary schools in Hong Kong. Two competing models were tested to ascertain the direction of effect: Model A…

SXDF-UDS-CANDELS-ALMA 1.5 arcmin2 deep survey

NASA Astrophysics Data System (ADS)

Kohno, Kotaro; Tamura, Yoichi; Yamaguchi, Yuki; Umehata, Hideki; Rujopakarn, Wiphu; Lee, Minju; Motohara, Kentaro; Makiya, Ryu; Izumi, Takuma; Ivison, Rob; Ikarashi, Soh; Tadaki, Ken-ichi; Kodama, Tadayuki; Hatsukade, Bunyo; Yabe, Kiyoto; Hayashi, Masao; Iono, Daisuke; Matsuda, Yuichi; Nakanishi, Kouichiro; Kawabe, Ryohei; Wilson, Grant; Yun, Min S.; Hughes, David; Caputi, Karina; Dunlop, James

2015-08-01

We have conducted 1.1 mm ALMA observations of a contiguous 105″ × 50″ or 1.5 arcmin2 window (achieved by 19 point mosaic) in the SXDF-UDS-CANDELS. We achieved a 5σ sensitivity of 0.28 mJy, giving a flat sensus of dusty star-forming galaxies with LIR ~6 × 1011 L⊙ (if Tdust = 40 K) or SFR ~100 M⊙ yr-1 up to z~10 thanks to the negative K-correction at this wavelength. We detect 5 brightest sources (S/N>6) and 18 low-significant sources (5 > S/N > 4; they may contain spurious detections, though) in the field. We find that these discrete sources are responsible for a faint filamentary emission seen in low-resolution (~30″) heavily confused AzTEC 1.1mm and SPIRE 0.5mm images. One of the 5 brightest ALMA sources is very dark in deep WFC3 and HAWK-I NIR images as well as VLA 1.4 GHz images, demonstrating that deep ALMA imaging can unveil new obscured star-forming galaxy population.

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.

Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status.

PubMed

Korfiatis, Panagiotis; Kline, Timothy L; Lachance, Daniel H; Parney, Ian F; Buckner, Jan C; Erickson, Bradley J

2017-10-01

Predicting methylation of the O6-methylguanine methyltransferase (MGMT) gene status utilizing MRI imaging is of high importance since it is a predictor of response and prognosis in brain tumors. In this study, we compare three different residual deep neural network (ResNet) architectures to evaluate their ability in predicting MGMT methylation status without the need for a distinct tumor segmentation step. We found that the ResNet50 (50 layers) architecture was the best performing model, achieving an accuracy of 94.90% (+/- 3.92%) for the test set (classification of a slice as no tumor, methylated MGMT, or non-methylated). ResNet34 (34 layers) achieved 80.72% (+/- 13.61%) while ResNet18 (18 layers) accuracy was 76.75% (+/- 20.67%). ResNet50 performance was statistically significantly better than both ResNet18 and ResNet34 architectures (p < 0.001). We report a method that alleviates the need of extensive preprocessing and acts as a proof of concept that deep neural architectures can be used to predict molecular biomarkers from routine medical images.

Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era.

PubMed

Jing, Yankang; Bian, Yuemin; Hu, Ziheng; Wang, Lirong; Xie, Xiang-Qun Sean

2018-03-30

Over the last decade, deep learning (DL) methods have been extremely successful and widely used to develop artificial intelligence (AI) in almost every domain, especially after it achieved its proud record on computational Go. Compared to traditional machine learning (ML) algorithms, DL methods still have a long way to go to achieve recognition in small molecular drug discovery and development. And there is still lots of work to do for the popularization and application of DL for research purpose, e.g., for small molecule drug research and development. In this review, we mainly discussed several most powerful and mainstream architectures, including the convolutional neural network (CNN), recurrent neural network (RNN), and deep auto-encoder networks (DAENs), for supervised learning and nonsupervised learning; summarized most of the representative applications in small molecule drug design; and briefly introduced how DL methods were used in those applications. The discussion for the pros and cons of DL methods as well as the main challenges we need to tackle were also emphasized.

Distributed deep learning networks among institutions for medical imaging.

PubMed

Chang, Ken; Balachandar, Niranjan; Lam, Carson; Yi, Darvin; Brown, James; Beers, Andrew; Rosen, Bruce; Rubin, Daniel L; Kalpathy-Cramer, Jayashree

2018-03-29

Deep learning has become a promising approach for automated support for clinical diagnosis. When medical data samples are limited, collaboration among multiple institutions is necessary to achieve high algorithm performance. However, sharing patient data often has limitations due to technical, legal, or ethical concerns. In this study, we propose methods of distributing deep learning models as an attractive alternative to sharing patient data. We simulate the distribution of deep learning models across 4 institutions using various training heuristics and compare the results with a deep learning model trained on centrally hosted patient data. The training heuristics investigated include ensembling single institution models, single weight transfer, and cyclical weight transfer. We evaluated these approaches for image classification in 3 independent image collections (retinal fundus photos, mammography, and ImageNet). We find that cyclical weight transfer resulted in a performance that was comparable to that of centrally hosted patient data. We also found that there is an improvement in the performance of cyclical weight transfer heuristic with a high frequency of weight transfer. We show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study.

DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations.

PubMed

Yuan, Yuchen; Shi, Yi; Li, Changyang; Kim, Jinman; Cai, Weidong; Han, Zeguang; Feng, David Dagan

2016-12-23

With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer types/subtypes, which may contribute to more accurate somatic point mutation based cancer classification (SMCC). However in existing SMCC methods, issues like high data sparsity, small volume of sample size, and the application of simple linear classifiers, are major obstacles in improving the classification performance. To address the obstacles in existing SMCC studies, we propose DeepGene, an advanced deep neural network (DNN) based classifier, that consists of three steps: firstly, the clustered gene filtering (CGF) concentrates the gene data by mutation occurrence frequency, filtering out the majority of irrelevant genes; secondly, the indexed sparsity reduction (ISR) converts the gene data into indexes of its non-zero elements, thereby significantly suppressing the impact of data sparsity; finally, the data after CGF and ISR is fed into a DNN classifier, which extracts high-level features for accurate classification. Experimental results on our curated TCGA-DeepGene dataset, which is a reformulated subset of the TCGA dataset containing 12 selected types of cancer, show that CGF, ISR and DNN all contribute in improving the overall classification performance. We further compare DeepGene with three widely adopted classifiers and demonstrate that DeepGene has at least 24% performance improvement in terms of testing accuracy. Based on deep learning and somatic point mutation data, we devise DeepGene, an advanced cancer type classifier, which addresses the obstacles in existing SMCC studies. Experiments indicate that DeepGene outperforms three widely adopted existing classifiers, which is mainly attributed to its deep learning module that is able to extract the high level features between combinatorial somatic point mutations and cancer types.

Depth as an organizer of fish assemblages in floodplain lakes

USGS Publications Warehouse

Miranda, L.E.

2011-01-01

Depth reduction is a natural process in floodplain lakes, but in many basins has been accelerated by anthropogenic disturbances. A diverse set of 42 floodplain lakes in the Yazoo River Basin (Mississippi, USA) was examined to test the hypothesis of whether depth reduction was a key determinant of water quality and fish assemblage structure. Single and multiple variable analyses were applied to 10 commonly monitored water variables and 54 fish species. Results showed strong associations between depth and water characteristics, and between depth and fish assemblages. Deep lakes provided less variable environments, clearer water, and a wider range of microhabitats than shallow lakes. The greater environmental stability was reflected by the dominant species in the assemblages, which included a broader representation of large-body species, species less tolerant of extreme water quality, and more predators. Stability in deep lakes was further reflected by reduced among-lake variability in taxa representation. Fish assemblages in shallow lakes were more variable than deep lakes, and commonly dominated by opportunistic species that have early maturity, extended breeding seasons, small adult size, and short lifespan. Depth is a causal factor that drives many physical and chemical variables that contribute to organizing fish assemblages in floodplain lakes. Thus, correlations between fish and water transparency, temperature, oxygen, trophic state, habitat structure, and other environmental descriptors may ultimately be totally or partly regulated by depth. In basins undergoing rapid anthropogenic modifications, local changes forced by depth reductions may be expected to eliminate species available from the regional pool and could have considerable ecological implications. ?? 2010 Springer Basel AG (outside the USA).

Starvation and recovery in the deep-sea methanotroph Methyloprofundus sedimenti.

PubMed

Tavormina, Patricia L; Kellermann, Matthias Y; Antony, Chakkiath Paul; Tocheva, Elitza I; Dalleska, Nathan F; Jensen, Ashley J; Valentine, David L; Hinrichs, Kai-Uwe; Jensen, Grant J; Dubilier, Nicole; Orphan, Victoria J

2017-01-01

In the deep ocean, the conversion of methane into derived carbon and energy drives the establishment of diverse faunal communities. Yet specific biological mechanisms underlying the introduction of methane-derived carbon into the food web remain poorly described, due to a lack of cultured representative deep-sea methanotrophic prokaryotes. Here, the response of the deep-sea aerobic methanotroph Methyloprofundus sedimenti to methane starvation and recovery was characterized. By combining lipid analysis, RNA analysis, and electron cryotomography, it was shown that M. sedimenti undergoes discrete cellular shifts in response to methane starvation, including changes in headgroup-specific fatty acid saturation levels, and reductions in cytoplasmic storage granules. Methane starvation is associated with a significant increase in the abundance of gene transcripts pertinent to methane oxidation. Methane reintroduction to starved cells stimulates a rapid, transient extracellular accumulation of methanol, revealing a way in which methane-derived carbon may be routed to community members. This study provides new understanding of methanotrophic responses to methane starvation and recovery, and lays the initial groundwork to develop Methyloprofundus as a model chemosynthesizing bacterium from the deep sea. © 2016 John Wiley & Sons Ltd.

The reduction in fatigue crack growth resistance of dentin with depth.

PubMed

Ivancik, J; Neerchal, N K; Romberg, E; Arola, D

2011-08-01

The fatigue crack growth resistance of dentin was characterized as a function of depth from the dentino-enamel junction. Compact tension (CT) specimens were prepared from the crowns of third molars in the deep, middle, and peripheral dentin. The microstructure was quantified in terms of the average tubule dimensions and density. Fatigue cracks were grown in-plane with the tubules and characterized in terms of the initiation and growth responses. Deep dentin exhibited the lowest resistance to the initiation of fatigue crack growth, as indicated by the stress intensity threshold (ΔK(th) ≈ 0.8 MPa•m(0.5)) and the highest incremental fatigue crack growth rate (over 1000 times that in peripheral dentin). Cracks in deep dentin underwent incremental extension under cyclic stresses that were 40% lower than those required in peripheral dentin. The average fatigue crack growth rates increased significantly with tubule density, indicating the importance of microstructure on the potential for tooth fracture. Molars with deep restorations are more likely to suffer from the cracked-tooth syndrome, because of the lower fatigue crack growth resistance of deep dentin.

Transmission in near-infrared optical windows for deep brain imaging.

PubMed

Shi, Lingyan; Sordillo, Laura A; Rodríguez-Contreras, Adrián; Alfano, Robert

2016-01-01

Near-infrared (NIR) radiation has been employed using one- and two-photon excitation of fluorescence imaging at wavelengths 650-950 nm (optical window I) for deep brain imaging; however, longer wavelengths in NIR have been overlooked due to a lack of suitable NIR-low band gap semiconductor imaging detectors and/or femtosecond laser sources. This research introduces three new optical windows in NIR and demonstrates their potential for deep brain tissue imaging. The transmittances are measured in rat brain tissue in the second (II, 1,100-1,350 nm), third (III, 1,600-1,870 nm), and fourth (IV, centered at 2,200 nm) NIR optical tissue windows. The relationship between transmission and tissue thickness is measured and compared with the theory. Due to a reduction in scattering and minimal absorption, window III is shown to be the best for deep brain imaging, and windows II and IV show similar but better potential for deep imaging than window I. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction

PubMed Central

Spencer, Matt; Eickholt, Jesse; Cheng, Jianlin

2014-01-01

Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80% and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test data set of 198 proteins, achieving a Q3 accuracy of 80.7% and a Sov accuracy of 74.2%. PMID:25750595

WFIRST: Science from Deep Field Surveys

NASA Astrophysics Data System (ADS)

Koekemoer, Anton M.; Foley, Ryan; WFIRST Deep Field Working Group

2018-06-01

WFIRST will enable deep field imaging across much larger areas than those previously obtained with Hubble, opening up completely new areas of parameter space for extragalactic deep fields including cosmology, supernova and galaxy evolution science. The instantaneous field of view of the Wide Field Instrument (WFI) is about 0.3 square degrees, which would for example yield an Ultra Deep Field (UDF) reaching similar depths at visible and near-infrared wavelengths to that obtained with Hubble, over an area about 100-200 times larger, for a comparable investment in time. Moreover, wider fields on scales of 10-20 square degrees could achieve depths comparable to large HST surveys at medium depths such as GOODS and CANDELS, and would enable multi-epoch supernova science that could be matched in area to LSST Deep Drilling fields or other large survey areas. Such fields may benefit from being placed on locations in the sky that have ancillary multi-band imaging or spectroscopy from other facilities, from the ground or in space. The WFIRST Deep Fields Working Group has been examining the science considerations for various types of deep fields that may be obtained with WFIRST, and present here a summary of the various properties of different locations in the sky that may be considered for future deep fields with WFIRST.

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

PubMed

Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

2015-01-01

Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80 percent and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

WFIRST: Science from Deep Field Surveys

NASA Astrophysics Data System (ADS)

Koekemoer, Anton; Foley, Ryan; WFIRST Deep Field Working Group

2018-01-01

WFIRST will enable deep field imaging across much larger areas than those previously obtained with Hubble, opening up completely new areas of parameter space for extragalactic deep fields including cosmology, supernova and galaxy evolution science. The instantaneous field of view of the Wide Field Instrument (WFI) is about 0.3 square degrees, which would for example yield an Ultra Deep Field (UDF) reaching similar depths at visible and near-infrared wavelengths to that obtained with Hubble, over an area about 100-200 times larger, for a comparable investment in time. Moreover, wider fields on scales of 10-20 square degrees could achieve depths comparable to large HST surveys at medium depths such as GOODS and CANDELS, and would enable multi-epoch supernova science that could be matched in area to LSST Deep Drilling fields or other large survey areas. Such fields may benefit from being placed on locations in the sky that have ancillary multi-band imaging or spectroscopy from other facilities, from the ground or in space. The WFIRST Deep Fields Working Group has been examining the science considerations for various types of deep fields that may be obtained with WFIRST, and present here a summary of the various properties of different locations in the sky that may be considered for future deep fields with WFIRST.

A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

NASA Astrophysics Data System (ADS)

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

2018-02-01

In recent years, intelligent fault diagnosis algorithms using machine learning technique have achieved much success. However, due to the fact that in real world industrial applications, the working load is changing all the time and noise from the working environment is inevitable, degradation of the performance of intelligent fault diagnosis methods is very serious. In this paper, a new model based on deep learning is proposed to address the problem. Our contributions of include: First, we proposed an end-to-end method that takes raw temporal signals as inputs and thus doesn't need any time consuming denoising preprocessing. The model can achieve pretty high accuracy under noisy environment. Second, the model does not rely on any domain adaptation algorithm or require information of the target domain. It can achieve high accuracy when working load is changed. To understand the proposed model, we will visualize the learned features, and try to analyze the reasons behind the high performance of the model.

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.

Bi-telescopic, deep, simultaneous meteor observations

NASA Technical Reports Server (NTRS)

Taff, L. G.

1986-01-01

A statistical summary is presented of 10 hours of observing sporadic meteors and two meteor showers using the Experimental Test System of the Lincoln Laboratory. The observatory is briefly described along with the real-time and post-processing hardware, the analysis, and the data reduction. The principal observational results are given for the sporadic meteor zenithal hourly rates. The unique properties of the observatory include twin telescopes to allow the discrimination of meteors by parallax, deep limiting magnitude, good time resolution, and sophisticated real-time and post-observing video processing.

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

PubMed

Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

2018-04-01

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

The Retrenchment Knife

ERIC Educational Resources Information Center

Dozier, John M.

1976-01-01

Horizontal vs. vertical cuts, that is the key question. Faculties favor the horizontal (put us all in the same boat), but the deep vertical cut (e.g. staff and program reduction) is, the author argues, most likely to cure an institutional illness. (Editor/JT)

The influence of biopreparations on the reduction of energy consumption and CO2 emissions in shallow and deep soil tillage.

PubMed

Naujokienė, Vilma; Šarauskis, Egidijus; Lekavičienė, Kristina; Adamavičienė, Aida; Buragienė, Sidona; Kriaučiūnienė, Zita

2018-06-01

The application of innovation in agriculture technologies is very important for increasing the efficiency of agricultural production, ensuring the high productivity of plants, production quality, farm profitability, the positive balance of used energy, and the requirements of environmental protection. Therefore, it is a scientific problem that solid and soil surfaces covered with plant residue have a negative impact on the work, traction resistance, energy consumption, and environmental pollution of tillage machines. The objective of this work was to determine the dependence of the reduction of energy consumption and CO 2 gas emissions on different biopreparations. Experimental research was carried out in a control (SC1) and seven different biopreparations using scenarios (SC2-SC8) using bacterial and non-bacterial biopreparations in different consistencies (with essential and mineral oils, extracts of various grasses and sea algae, phosphorus, potassium, humic and gibberellic acids, copper, zinc, manganese, iron, and calcium), estimating discing and plowing as the energy consumption parameters of shallow and deep soil tillage machines, respectively. CO 2 emissions were determined by evaluating soil characteristics (such as hardness, total porosity and density). Meteorological conditions such average daily temperatures (2015-20.3 °C; 2016-16.90 °C) and precipitations (2015-6.9 mm; 2016-114.9 mm) during the month strongly influenced different results in 2015 and 2016. Substantial differences between the averages of energy consumption identified in approximately 62% of biological preparation combinations created usage scenarios. Experimental research established that crop field treatments with biological preparations at the beginning of vegetation could reduce the energy consumption of shallow tillage machines by up to approximately 23%, whereas the energy consumption of deep tillage could be reduced by up to approximately 19.2% compared with the control treatment. The experimental research results reveal the reduction of CO 2 emissions in shallow tillage to approximately 20.14% (and that in deep tillage to approximately 19.16%) when works were performed by different biological preparation usage scenarios. This experimental research demonstrates the efficient use of the special adaptation of a new biotechnological method for the reduction of the energy consumption and CO 2 gas emissions of agricultural machinery. Copyright © 2018 Elsevier B.V. All rights reserved.

Advanced Life Support Technologies and Scenarios

NASA Technical Reports Server (NTRS)

Barta, Daniel J.

2011-01-01

As NASA looks beyond the International Space Station toward long-duration, deep space missions away from Earth, the current practice of supplying consumables and spares will not be practical nor affordable. New approaches are sought for life support and habitation systems that will reduce dependency on Earth and increase mission sustainability. To reduce launch mass, further closure of Environmental Control and Life Support Systems (ECLSS) beyond the current capability of the ISS will be required. Areas of particular interest include achieving higher degrees of recycling within Atmosphere Revitalization, Water Recovery and Waste Management Systems. NASA is currently investigating advanced carbon dioxide reduction processes that surpass the level of oxygen recovery available from the Sabatier Carbon Dioxide Reduction Assembly (CRA) on the ISS. Improving the efficiency of the recovery of water from spacecraft solid and liquid wastes is possible through use of emerging technologies such as the heat melt compactor and brine dewatering systems. Another significant consumable is that of food. Food production systems based on higher plants may not only contribute significantly to the diet, but also contribute to atmosphere revitalization, water purification and waste utilization. Bioreactors may be potentially utilized for wastewater and solid waste management. The level at which bioregenerative technologies are utilized will depend on their comparative requirements for spacecraft resources including mass, power, volume, heat rejection, crew time and reliability. Planetary protection requirements will need to be considered for missions to other solar system bodies.

Clean Air Act, TRI drive emission reduction

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

Heller, K.

1994-06-22

When asked to rank priority environmental engineering projects, many chemical firms put emissions reduction first. The chief motivators are the need to comply with rules governing major sources of hazardous air pollutants (HAPS) under the Clean Air Act Amendments of 1990 (CAA), along with the need to reduce the volumes of chemicals on EPA`s Toxics Release Inventory (TRI). Deep-welling of toxics is getting special attention as the practice adds considerably to TRI numbers. {open_quotes}We want to eliminate our air toxics so that we can get entirely out of the [CAA] Maximum Achievable Control Technology (MACT) requirements,{close_quotes} says Thomas Zosel, manager/pollutionmore » prevention programs for 3M (St. Paul, MN). He estimates that 3M`s 1993 total research expenditures for environmental improvements were at least $200 million, out of an annual research budget of a little more than $1 billion. And, he says, the spending level is not expected to drop. Among its many efforts, 3M is striving to move away from solvents in all of its processes. To help reach that goal, the company developed a {open_quotes}waste measurement metric{close_quotes} that calculates the wastes produced by each of the company`s 50 operating divisions. In the case of Magic Tape, the company eliminated solvent emission by switching to a water-based adhesive that does not require a solvent.« less

Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature.

PubMed

Li, Yuankun; Xu, Tingfa; Deng, Honggao; Shi, Guokai; Guo, Jie

2018-02-23

Although correlation filter (CF)-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN) to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios.

A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition

PubMed Central

Saez, Yago; Baldominos, Alejandro; Isasi, Pedro

2016-01-01

Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called “deep learning”, which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google’s TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population), a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO) cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees). However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data), deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and facilitates cold starts and big data processing of physical activity records. PMID:28042838

A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition.

PubMed

Saez, Yago; Baldominos, Alejandro; Isasi, Pedro

2016-12-30

Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called "deep learning", which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google's TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population), a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO) cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees). However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data), deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and facilitates cold starts and big data processing of physical activity records.

ACTIVIS: Visual Exploration of Industry-Scale Deep Neural Network Models.

PubMed

Kahng, Minsuk; Andrews, Pierre Y; Kalro, Aditya; Polo Chau, Duen Horng

2017-08-30

While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ACTIVIS, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance- and subset-level. ACTIVIS has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ACTIVIS may work with different models.

Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

NASA Astrophysics Data System (ADS)

Ma, Ling; Lu, Guolan; Wang, Dongsheng; Wang, Xu; Chen, Zhuo Georgia; Muller, Susan; Chen, Amy; Fei, Baowei

2017-03-01

Hyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-guided surgery. HSI acquires high-resolution images at hundreds of spectral bands, providing big data to differentiating different types of tissue. We proposed a deep learning based method for the detection of head and neck cancer with hyperspectral images. Since the deep learning algorithm can learn the feature hierarchically, the learned features are more discriminative and concise than the handcrafted features. In this study, we adopt convolutional neural networks (CNN) to learn the deep feature of pixels for classifying each pixel into tumor or normal tissue. We evaluated our proposed classification method on the dataset containing hyperspectral images from 12 tumor-bearing mice. Experimental results show that our method achieved an average accuracy of 91.36%. The preliminary study demonstrated that our deep learning method can be applied to hyperspectral images for detecting head and neck tumors in animal models.

NEEDLE KNIFE SPHINCTEROTOMY - THE CHRIS HANI BARAGWANATH ACADEMIC HOSPITAL EXPERIENCE.

PubMed

Thomson, J T; Smith, M D; Omoshoro-Jones, J A O; Devar, J D; Khan, Z K; Jugmohan, B J

2017-06-01

Deep biliary cannulation is essential in performing a therapeutic ERCP. Cannulation can be enhanced through the utilization of a pre-cut by means of a needle knife sphincterotomy. Retrospective analysis of the Chris Hani Baragwanath Academic Hospital's ERCP database was performed. All ERCPs performed with the aid of a needle knife were identified and analysed for successful and unsuccessful deep biliary cannulation. 2830 ERCPs were performed during the study period. 369 (13%) required needle knife sphincterotomies and successful deep biliary cannulation was achieved in 229 (62%) of these patients. Repeat ERCPs were performed on 125 (34%) patients. 61 (49%) of the repeat ERCPs were performed because of previously failed cannulation. 34 (56%) of these repeat ERCPs resulted in successful deep biliary cannulation at re-attempt. 99% of successful cannulations at repeat ERCP had had a needle knife sphincterotomy at the first ERCP. Needle knife sphincterotomy improves deep biliary cannulation at initial ERCP and subsequent ERCPs with low incidences of complications.

Action-Driven Visual Object Tracking With Deep Reinforcement Learning.

PubMed

Yun, Sangdoo; Choi, Jongwon; Yoo, Youngjoon; Yun, Kimin; Choi, Jin Young

2018-06-01

In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning. The use of RL enables even partially labeled data to be successfully utilized for semisupervised learning. Through the evaluation of the object tracking benchmark data set, the proposed tracker is validated to achieve a competitive performance at three times the speed of existing deep network-based trackers. The fast version of the proposed method, which operates in real time on graphics processing unit, outperforms the state-of-the-art real-time trackers with an accuracy improvement of more than 8%.

Speech reconstruction using a deep partially supervised neural network.

PubMed

McLoughlin, Ian; Li, Jingjie; Song, Yan; Sharifzadeh, Hamid R

2017-08-01

Statistical speech reconstruction for larynx-related dysphonia has achieved good performance using Gaussian mixture models and, more recently, restricted Boltzmann machine arrays; however, deep neural network (DNN)-based systems have been hampered by the limited amount of training data available from individual voice-loss patients. The authors propose a novel DNN structure that allows a partially supervised training approach on spectral features from smaller data sets, yielding very good results compared with the current state-of-the-art.

Experimental studies on nonpenetrating filtration surgery using the CO2 laser.

PubMed

Assia, Ehud I; Rotenstreich, Yigal; Barequet, Irina S; Apple, David J; Rosner, Mordechai; Belkin, Michael

2007-06-01

This study evaluated the use of a CO2 laser for performing deep sclerectomy in nonpenetrating filtration surgery. Three experimental models were performed: enucleated sheep and cow eyes (n=18) to determine optimal irradiation parameters, live rabbit eyes (n=20) to test feasibility, and cadaver eyes (40 procedures in 20 eyes) to study effects in human eyes tissue. After a half-thickness scleral flap was created, deep sclerectomy was performed by CO2 laser applications on the scleral bed down to the trabeculo-Descemet's membrane. Fluid percolation was repeatedly achieved without penetration in sheep and cow eyes using scanned laser energy of 5-10 W at a pulse duration of 200 micros and a working distance of 35 cm. In live rabbits, deep sclerectomy was achieved without perforation in 19/20 eyes. Intraocular pressure was significantly decreased on the first postoperative day (10.3+/-5.1 mmHg lower, on average, than in the nonoperated fellow eye; P<0.001), and this persisted for 21 days. Operations on all cadaver eyes resulted in effective fluid percolation. Penetration of the scleral wall occurred in five cases only after repeated laser applications with high energy. Histologically, a thin sclerocorneal intact wall was demonstrated at the sclerectomy bed. Collateral tissue damage did not extend beyond 100 microm, and adjacent structures remained unharmed. CO2 laser-assisted deep sclerectomy is a feasible and apparently safe procedure.

Identification of the primary compensating defect level responsible for determining blocking voltage of vertical GaN power diodes

DOE PAGES

King, M. P.; Kaplar, R. J.; Dickerson, J. R.; ...

2016-10-31

Electrical performance and characterization of deep levels in vertical GaN P-i-N diodes grown on low threading dislocation density (~10 4 –10 6 cm –2) bulk GaN substrates are investigated. The lightly doped n drift region of these devices is observed to be highly compensated by several prominent deep levels detected using deep level optical spectroscopy at E c-2.13, 2.92, and 3.2 eV. A combination of steady-state photocapacitance and lighted capacitance-voltage profiling indicates the concentrations of these deep levels to be N t = 3 × 10 12, 2 × 10 15, and 5 × 10 14 cm –3, respectively. Themore » E c-2.92 eV level is observed to be the primary compensating defect in as-grown n-type metal-organic chemical vapor deposition GaN, indicating this level acts as a limiting factor for achieving controllably low doping. The device blocking voltage should increase if compensating defects reduce the free carrier concentration of the n drift region. Understanding the incorporation of as-grown and native defects in thick n-GaN is essential for enabling large V BD in the next-generation wide-bandgap power semiconductor devices. Furthermore, controlling the as-grown defects induced by epitaxial growth conditions is critical to achieve blocking voltage capability above 5 kV.« less

That sinking feeling: Suspended sediments can prevent the ascent of coral egg bundles

PubMed Central

Ricardo, Gerard F.; Jones, Ross J.; Negri, Andrew P.; Stocker, Roman

2016-01-01

Spawning synchrony represents a common reproductive strategy in sessile marine organisms and for broadcast spawning corals, buoyancy of egg-sperm bundles is critical to maximise fertilisation at the ocean surface. Here we demonstrate a novel threat to coral reproduction whereby buoyant egg-sperm bundles intercept and are “ballasted” by sediment grains on their journey to the ocean surface, preventing them from reaching the ocean surface and greatly reducing egg-sperm encounter rates. Empirical observations of this mechanism are successfully captured by a mathematical model that predicts the reduction in ascent probability and egg-sperm encounters as a function of sediment load. When applied to 15 m deep reefs, the model predicts that 10% and 50% reductions in egg-sperm encounters occur at 35 mg L−1 and 87 mg L−1 suspended sediment concentrations, respectively, and for a 5 m deep reef a 10% reduction occurs at 106 mg L−1. These concentrations are commonly associated with sediment plumes from dredging or natural resuspension events. The potential for sediments to sink coral gametes highlights the need to carefully manage the timing of turbidity-generating human activities near reefs during spawning periods. PMID:26898352

That sinking feeling: Suspended sediments can prevent the ascent of coral egg bundles.

PubMed

Ricardo, Gerard F; Jones, Ross J; Negri, Andrew P; Stocker, Roman

2016-02-22

Spawning synchrony represents a common reproductive strategy in sessile marine organisms and for broadcast spawning corals, buoyancy of egg-sperm bundles is critical to maximise fertilisation at the ocean surface. Here we demonstrate a novel threat to coral reproduction whereby buoyant egg-sperm bundles intercept and are "ballasted" by sediment grains on their journey to the ocean surface, preventing them from reaching the ocean surface and greatly reducing egg-sperm encounter rates. Empirical observations of this mechanism are successfully captured by a mathematical model that predicts the reduction in ascent probability and egg-sperm encounters as a function of sediment load. When applied to 15 m deep reefs, the model predicts that 10% and 50% reductions in egg-sperm encounters occur at 35 mg L(-1) and 87 mg L(-1) suspended sediment concentrations, respectively, and for a 5 m deep reef a 10% reduction occurs at 106 mg L(-1). These concentrations are commonly associated with sediment plumes from dredging or natural resuspension events. The potential for sediments to sink coral gametes highlights the need to carefully manage the timing of turbidity-generating human activities near reefs during spawning periods.

ANI/MAELU engineering inspection criteria 8.3 ALARA

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

Schneider, L.

1995-03-01

The purpose of this criteria section is to provide guidelines for programs whose intent is to achieve occupational doses and doses to members of the public that are as low as is reasonably achievable (ALARA). The success that has been achieved by applying ALARA concepts at nuclear power plants is clearly illustrated by the major reductions in the annual cumulative dose to workers at many sites over the last few years. This success is the combined result of the general maturity of the nuclear industry, the intensive study of dose reduction practices by industry groups, and the successful sharing ofmore » experience and practices among plants. Source term reduction should be used as a primary ALARA mechanism. Methods which should be considered include: satellite and cobalt reduction, chemistry control, decontamination, submicron filters, zinc addition, hot spot reduction and permanent or temporary shielding.« less