Study the effect of elevated dies temperature on aluminium and steel round deep drawing

NASA Astrophysics Data System (ADS)

Lean, Yeong Wei; Azuddin, M.

2016-02-01

Round deep drawing operation can only be realized by expensive multi-step production processes. To reduce the cost of processes while expecting an acceptable result, round deep drawing can be done at elevated temperature. There are 3 common problems which are fracture, wrinkling and earing of deep drawing a round cup. The main objective is to investigate the effect of dies temperature on aluminium and steel round deep drawing; with a sub-objective of eliminate fracture and reducing wrinkling effect. Experimental method is conducted with 3 different techniques on heating the die. The techniques are heating both upper and lower dies, heating only the upper dies, and heating only the lower dies. 4 different temperatures has been chosen throughout the experiment. The experimental result then will be compared with finite element analysis software. There is a positive result from steel material on heating both upper and lower dies, where the simulation result shows comparable as experimental result. Heating both upper and lower dies will be the best among 3 types of heating techniques.

Analysis of the Lankford coefficient evolution at different strain rates for AA6016-T4, DP800 and DC06

NASA Astrophysics Data System (ADS)

Lenzen, Matthias; Merklein, Marion

2017-10-01

In the automotive sector, a major challenge is the deep-drawing of modern lightweight sheet metals with limited formability. Thus, conventional material models lack in accuracy due to the complex material behavior. A current field of research takes into account the evolution of the Lankford coefficient. Today, changes in anisotropy under increasing degree of deformation are not considered. Only a consolidated average value of the Lankford coefficient is included in conventional material models. This leads to an increasing error in prediction of the flow behavior and therefore to an inaccurate prognosis of the forming behavior. To increase the accuracy of the prediction quality, the strain dependent Lankford coefficient should be respected, because the R-value has a direct effect on the contour of the associated flow rule. Further, the investigated materials show a more or less extinct rate dependency of the yield stress. For this reason, the rate dependency of the Lankford coefficient during uniaxial tension is focused within this contribution. To quantify the influence of strain rate on the Lankford coefficient, tensile tests are performed for three commonly used materials, the aluminum alloy AA6016-T4, the advanced high strength steel DP800 and the deep drawing steel DC06 at three different strain rates. The strain measurement is carried out by an optical strain measurement system. An evolution of the Lankford coefficient was observed for all investigated materials. Also, an influence of the deformation velocity on the anisotropy could be detected.

Improved process robustness by using closed loop control in deep drawing applications

NASA Astrophysics Data System (ADS)

Barthau, M.; Liewald, M.; Christian, Held

2017-09-01

The production of irregular shaped deep-drawing parts with high quality requirements, which are common in today’s automotive production, permanently challenges production processes. High requirements on lightweight construction of passenger car bodies following European regulations until 2020 have been massively increasing the use of high strength steels substantially for years and are also leading to bigger challenges in sheet metal part production. Of course, the more and more complex shapes of today’s car body shells also intensify the issue due to modern and future design criteria. The metal forming technology tries to meet these challenges by developing a highly sophisticated layout of deep drawing dies that consider part quality requirements, process robustness and controlled material flow during the deep or stretch drawing process phase. A new method for controlling material flow using a closed loop system was developed at the IFU Stuttgart. In contrast to previous approaches, this new method allows a control intervention during the deep-drawing stroke. The blank holder force around the outline of the drawn part is used as control variable. The closed loop is designed as trajectory follow up with feed forward control. The used command variable is the part-wall stress that is measured with a piezo-electric measuring pin. In this paper the used control loop will be described in detail. The experimental tool that was built for testing the new control approach is explained here with its features. A method for gaining the follow up trajectories from simulation will also be presented. Furthermore, experimental results considering the robustness of the deep drawing process and the gain in process performance with developed control loop will be shown. Finally, a new procedure for the industrial application of the new control method of deep drawing will be presented by using a new kind of active element to influence the local blank holder pressure onto part flange.

Investigation of holder pressure and size effects in micro deep drawing of rectangular work pieces driven by piezoelectric actuator.

PubMed

Aminzahed, Iman; Mashhadi, Mahmoud Mosavi; Sereshk, Mohammad Reza Vaziri

2017-02-01

Micro forming is a manufacturing process to fabricate micro parts with high quality and a cost effective manner. Deep drawing could be a favorable method for production of complicated parts in macro and micro sizes. In this paper piezoelectric actuator is used as a novel approach in the field of micro manufacturing. Also, in current work, investigations are conducted with four rectangular punches and blanks with various thicknesses. Blank holder pressure effects on thickness distributions, punch force, and springback are studied. According to the results of this work, increasing of blank holder pressure in scaled deep drawing, in contrast to thickness of drawn part, leads to decrease in the punch forces and springback. Furthermore, it is shown that in micro deep drawing, the effects of holder pressure on mentioned parameters can be ignored. Copyright © 2016 Elsevier B.V. All rights reserved.

Obtaining manufactured geometries of deep-drawn components through a model updating procedure using geometric shape parameters

NASA Astrophysics Data System (ADS)

Balla, Vamsi Krishna; Coox, Laurens; Deckers, Elke; Plyumers, Bert; Desmet, Wim; Marudachalam, Kannan

2018-01-01

The vibration response of a component or system can be predicted using the finite element method after ensuring numerical models represent realistic behaviour of the actual system under study. One of the methods to build high-fidelity finite element models is through a model updating procedure. In this work, a novel model updating method of deep-drawn components is demonstrated. Since the component is manufactured with a high draw ratio, significant deviations in both profile and thickness distributions occurred in the manufacturing process. A conventional model updating, involving Young's modulus, density and damping ratios, does not lead to a satisfactory match between simulated and experimental results. Hence a new model updating process is proposed, where geometry shape variables are incorporated, by carrying out morphing of the finite element model. This morphing process imitates the changes that occurred during the deep drawing process. An optimization procedure that uses the Global Response Surface Method (GRSM) algorithm to maximize diagonal terms of the Modal Assurance Criterion (MAC) matrix is presented. This optimization results in a more accurate finite element model. The advantage of the proposed methodology is that the CAD surface of the updated finite element model can be readily obtained after optimization. This CAD model can be used for carrying out analysis, as it represents the manufactured part more accurately. Hence, simulations performed using this updated model with an accurate geometry, will therefore yield more reliable results.

Modeling of the minimum variable blank holder force based on forming limit diagram (FLD) in deep drawing process

NASA Astrophysics Data System (ADS)

Candra, S.; Batan, I. M. L.; Berata, W.; Pramono, A. S.

2017-11-01

This paper presents the mathematical approach of minimum blank holder force to prevent wrinkling in deep drawing process of the cylindrical cup. Based on the maximum of minor-major strain ratio, the slab method was applied to determine the modeling of minimum variable blank holder force (VBHF) and it compared to FE simulation. The Tin steel sheet of T4-CA grade, with the thickness of 0.2 mm was used in this study. The modeling of minimum VBHF can be used as a simple reference to prevent wrinkling in deep drawing.

Process Simulation of Aluminium Sheet Metal Deep Drawing at Elevated Temperatures

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

Winklhofer, Johannes; Trattnig, Gernot; Lind, Christoph

Lightweight design is essential for an economic and environmentally friendly vehicle. Aluminium sheet metal is well known for its ability to improve the strength to weight ratio of lightweight structures. One disadvantage of aluminium is that it is less formable than steel. Therefore complex part geometries can only be realized by expensive multi-step production processes. One method for overcoming this disadvantage is deep drawing at elevated temperatures. In this way the formability of aluminium sheet metal can be improved significantly, and the number of necessary production steps can thereby be reduced. This paper introduces deep drawing of aluminium sheet metalmore » at elevated temperatures, a corresponding simulation method, a characteristic process and its optimization. The temperature and strain rate dependent material properties of a 5xxx series alloy and their modelling are discussed. A three dimensional thermomechanically coupled finite element deep drawing simulation model and its validation are presented. Based on the validated simulation model an optimised process strategy regarding formability, time and cost is introduced.« less

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Influence of asymmetrical drawing radius deviation in micro deep drawing

NASA Astrophysics Data System (ADS)

Heinrich, L.; Kobayashi, H.; Shimizu, T.; Yang, M.; Vollertsen, F.

2017-09-01

Nowadays, an increasing demand for small metal parts in electronic and automotive industries can be observed. Deep drawing is a well-suited technology for the production of such parts due to its excellent qualities for mass production. However, the downscaling of the forming process leads to new challenges in tooling and process design, such as high relative deviation of tool geometry or blank displacement compared to the macro scale. FEM simulation has been a widely-used tool to investigate the influence of symmetrical process deviations as for instance a global variance of the drawing radius. This study shows a different approach that allows to determine the impact of asymmetrical process deviations on micro deep drawing. In this particular case the impact of an asymmetrical drawing radius deviation and blank displacement on cup geometry deviation was investigated for different drawing ratios by experiments and FEM simulation. It was found that both variations result in an increasing cup height deviation. Nevertheless, with increasing drawing ratio a constant drawing radius deviation has an increasing impact, while blank displacement results in a decreasing offset of the cups geometry. This is explained by different mechanisms that result in an uneven cup geometry. While blank displacement leads to material surplus on one side of the cup, an unsymmetrical radius deviation on the other hand generates uneven stretching of the cups wall. This is intensified for higher drawing ratios. It can be concluded that the effect of uneven radius geometry proves to be of major importance for the production of accurately shaped micro cups and cannot be compensated by intentional blank displacement.

Experimental Investigations on Formability of Aluminum Tailor Friction Stir Welded Blanks in Deep Drawing Process

NASA Astrophysics Data System (ADS)

Kesharwani, R. K.; Panda, S. K.; Pal, S. K.

2015-02-01

In the present work, tailor friction stir welded blanks (TFSWBs) were fabricated successfully using 2.0-mm-thick AA5754-H22 and AA5052-H32 sheet metals with optimized tool design and process parameters. Taguchi L9 orthogonal array has been used to design the friction stir welding experiments, and the Grey relational analysis has been applied for the multi objective optimization in order to maximize the weld strength and total elongation reducing the surface roughness and energy consumption. The formability of the TFSWBs and parent materials was evaluated and compared in terms of limiting drawing ratio (LDR) using a conventional circular die. It was found that the formability of the TFSWBs was comparable with that of both the parent materials without failure in the weldment. A modified conical tractrix die (MCTD) was proposed to enhance the LDR of the TFSWBs. It was found that the formability was improved by 27% using the MCTD.

5. INTERIOR VIEW OF BASEMENT, LOOKING WEST. DEEP DRAW, HEAVY ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. INTERIOR VIEW OF BASEMENT, LOOKING WEST. DEEP DRAW, HEAVY PRESS MANUFACTURED BY E. W. BLISS CO., BROOKLYN, NEW YORK. PRESS #3-3/4 S, PATENTED BY E. W. BLISS CO., AUGUST 16, 1892, AND JANUARY 31, 1893. THIS PRESS DATES FROM CA. 1920. - Illinois Pure Aluminum Company, 109 Holmes Street, Lemont, Cook County, IL

Studies in Cup Drawing Behavior of Polymer Laminated Sheet Metal

NASA Astrophysics Data System (ADS)

Elnagmi, M.; Jain, M.; Bruhis, M.; Nielsen, K.

2011-08-01

Axisymmetric deep drawing behavior of a polymer laminated sheet metal (PLSM) is investigated using an axisymmetric cup drawing test. PLSMs are of interest as a replacement for painted finishes for automotive applications as they have the potential to achieve good quality long lasting and aesthetically appealing surfaces on stamped parts. However, there is limited understanding of PLSMs in automotive deep drawing situations to produce complex 3-D parts. The tests are carried out using well-controlled, laboratory-based, dual-action, servo-hydraulic forming presses under blank-holder force and punch displacement control conditions. An optical strain mapping system is used to measure the surface strains (and to construct 3D strain maps) from the film side of the deformed samples for a range of forming conditions. Deep drawing characteristics such as punch load versus punch displacement traces, strain distribution along the cup profile, flange wrinkling and fracture characteristics are experimentally assessed for stainless steel-plastic film laminated sheet materials. Also the effect of lamination pressure on wrinkling and delamination is investigated for a decorative pressure sensitive adhesive film affixed to the stainless steel sheet.

a Walk Through Earth's Time

NASA Astrophysics Data System (ADS)

Turrin, B. D.; Turrin, M.

2012-12-01

After "What is this rock?" the most common questions that is asked of Geologists is "How old is this rock/fossil?" For geologists considering ages back to millions of years is routine. Sorting and cataloguing events into temporal sequences is a natural tendency for all humans. In fact, it is an everyday activity for humans, i.e., keeping track of birthdays, anniversaries, appointments, meetings, AGU abstract deadlines etc… However, the time frames that are most familiar to the non scientist (seconds, minutes, hours, days, years) generally extend to only a few decades or at most centuries. Yet the vast length of time covered by Earth's history, 4.56 billion years, greatly exceeds these timeframes and thus is commonly referred to as "Deep Time". This is a challenging concept for most students to comprehend as it involves temporal and abstract thinking, yet it is key to their successful understanding of numerous geologic principles. We have developed an outdoor learning activity for general Introductory Earth Science courses that incorporates several scientific and geologic concepts such as: linear distance or stratigraphic thickness representing time, learning about major events in Earth's history and locating them in a scaled temporal framework, field mapping, abstract thinking, scaling and dimensional analysis, and the principles of radio isotopic dating. The only supplies needed are readily available in local hardware stores i.e. a 300 ft. surveyor's tape marked in feet, and tenths and hundredths of a foot, and the student's own introductory geology textbook. The exercise employs a variety of pedagogical learning modalities, including traditional lecture-based, the use of Art/Drawing, use of Visualization, Collaborative learning, and Kinesthetic and Experiential learning. Initially the students are exposed to the concept of "Deep Time" in a short conventional introductory lecture; this is followed by a 'field day'. Prior to the field exercise, students work with their textbook selecting events is Earth History that they find interesting. Using the textbook and online resources they then draw figures that represent these events. The drawing exercise reinforces the learning by having students visualize (imprinting an image) of these geologic events. Once the students have produced their drawings, the outdoor field exercise follows. Working collaboratively, the students measure and lay out a scaled linear model representing 4.56 billion years of geologic time. They then organize and place their drawings in the proper sequence on the temporal model that they have created. Once all the drawings are in place they are able to visualize the expanse of time in Earth's history. Through comparing results from a pre-test to those from a post-test we can show the gains in student understanding of Deep Time, a concept that is central to many of our geologic understandings.

Feedback control in deep drawing based on experimental datasets

NASA Astrophysics Data System (ADS)

Fischer, P.; Heingärtner, J.; Aichholzer, W.; Hortig, D.; Hora, P.

2017-09-01

In large-scale production of deep drawing parts, like in automotive industry, the effects of scattering material properties as well as warming of the tools have a significant impact on the drawing result. In the scope of the work, an approach is presented to minimize the influence of these effects on part quality by optically measuring the draw-in of each part and adjusting the settings of the press to keep the strain distribution, which is represented by the draw-in, inside a certain limit. For the design of the control algorithm, a design of experiments for in-line tests is used to quantify the influence of the blank holder force as well as the force distribution on the draw-in. The results of this experimental dataset are used to model the process behavior. Based on this model, a feedback control loop is designed. Finally, the performance of the control algorithm is validated in the production line.

Evaluation of the Kloswall longwall mining system

NASA Astrophysics Data System (ADS)

Guay, P. J.

1982-04-01

A new longwal mining system specifically designed to extract a very deep web (48 inches or deeper) from a longwall panel was studied. Productivity and cost analysis comparing the new mining system with a conventional longwall operation taking a 30 inch wide web is presented. It is shown that the new system will increase annual production and return on investment in most cases. Conceptual drawings and specifications for a high capacity three drum shearer and a unique shield type of roof support specifically designed for very wide web operation are reported. The advantages and problems associated with wide web mining in general and as they relate specifically to the equipment selected for the new mining system are discussed.

Analysis of earing behaviour in deep drawing of ASS 304 at elevated temperature

NASA Astrophysics Data System (ADS)

Gupta, Amit Kumar; Deole, Aditya; Kotkunde, Nitin; Singh, Swadesh Kumar; jella, Gangadhar

2016-08-01

Earing tendency in a deep drawn cup of circular blanks is one the most prominent characteristics observed due to anisotropy in a metal sheet. Such formation of uneven rim is mainly due to dissimilarity in yield stress as well as Lankford parameter (r- value) in different orientations. In this paper, an analytical function coupled with different yield functions viz., Hill 1948, Barlat 1989 and Barlat Yld 2000-2d has been used to provide an approximation of earing profile. In order to validate the results, material parameters for yield functions and hardening rule have been calibrated for ASS 304 at 250°C and deep drawing experiment is conducted to measure the earing profile. The predicted earing profiles based on analytical results have been validated using experimental earing profile. Based on this analysis, Barlat Yld 2000-2d has been observed to be a well suited yield model for deep drawing of ASS 304, which also confirms the reliability of analytical function for earing profile estimation.

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.

Enhancing observation by drawing: Alveolinids models by Manfred Reichel (1896-1984)

NASA Astrophysics Data System (ADS)

Leria, Maria

2017-04-01

Graphic representation is a fundamental tool in morphological studies, as paleontology. A paradigmatic example is the alveolinid drawings of Prof. Manfred Reichel (1896-1984). Thanks to these drawings his research on foraminifera, had an important impact on micropaleontology. Manfred Reichel studied Fine Arts, but later he began a scientific career on biological sciences and becoming a professor in micropaleontology, at the Geological and Paleontological Institute of the University of Basel, Switzerland. His background in art had a benefit in his scientific production, especially with the extremely complex foraminiferal structures. By means of illustrations, inspired by the French naturalists, he was able to solve the most complex internal architecture of forams. His drawings display foraminifera's internal 3D structure in such a comprehensible way that has not been improved using modern techniques. His work has been used by different generations of paleontologist to understand the internal architecture of forams and are still used today. The aim of this study is to analyze the process that Reichel followed to create some of his most representative drawings. This study is based on the examination of a selection of Reichel's drawings (n>40) held at the Natural History Museum in Basel. In addition, his family and students have been interviewed supplying useful information to understand how he applied his artistic skills to teach and research. This study illustrates the steps followed by Reichel in the creation of a drawing of alveolinid. The process represents the transformation of the morphological data from 2D images (polished rock sections) into a comprehensible 3D image. A description of the process of observation, comparison, sketches and studies, concluding with the final three-dimensional drawing is shown. The results show that that the classical convention in drawing is still and irreplaceable tool in natural sciences, because it allows to define aspects that cannot be equally appreciated shown by other means (text or photography). Drawing it can also be a scientific analytical tool with an artistic identity, we present an example where rigor is intrinsically linked to a high sensibility, and a deep knowledge of drawing that brings as a result a beautiful piece of art.

Effects of hypnosis and level of processing on repeated recall of line drawings.

PubMed

McKelvie, S J; Pullara, M

1988-07-01

Moderately susceptible subjects (N = 30) initially judged 30 line drawings of objects for pleasantness (deep processing) and 30 line drawings for visual complexity (shallow processing), after which they were given two immediate recall tests. Following a 48-hr delay, subjects were allocated randomly to hypnosis, simulation, or neutral control conditions and were tested four more times. Subjects produced more correct and incorrect responses over the six trials and gave a higher number of correct responses for deep items than for shallow items. Over the last four trials, hypnosis had no general facilitative effect relative to the other two treatments, but the effect of depth was strongest for hypnotized subjects, who recalled more deep items than did the controls. Finally, both hypnotized and simulating subjects rated their recall as more involuntary and their experimental treatment as more helpful than did the controls. Caution is urged in the forensic use of hypnosis as a retrieval device.

The drawing effect: Evidence for reliable and robust memory benefits in free recall.

PubMed

Wammes, Jeffrey D; Meade, Melissa E; Fernandes, Myra A

2016-01-01

In 7 free-recall experiments, the benefit of creating drawings of to-be-remembered information relative to writing was examined as a mnemonic strategy. In Experiments 1 and 2, participants were presented with a list of words and were asked to either draw or write out each. Drawn words were better recalled than written. Experiments 3-5 showed that the memory boost provided by drawing could not be explained by elaborative encoding (deep level of processing, LoP), visual imagery, or picture superiority, respectively. In Experiment 6, we explored potential limitations of the drawing effect, by reducing encoding time and increasing list length. Drawing, relative to writing, still benefited memory despite these constraints. In Experiment 7, the drawing effect was significant even when encoding trial types were compared in pure lists between participants, inconsistent with a distinctiveness account. Together these experiments indicate that drawing enhances memory relative to writing, across settings, instructions, and alternate encoding strategies, both within- and between-participants, and that a deep LoP, visual imagery, or picture superiority, alone or collectively, are not sufficient to explain the observed effect. We propose that drawing improves memory by encouraging a seamless integration of semantic, visual, and motor aspects of a memory trace.

Micro-hydromechanical deep drawing of metal cups with hydraulic pressure effects

NASA Astrophysics Data System (ADS)

Luo, Liang; Jiang, Zhengyi; Wei, Dongbin; Wang, Xiaogang; Zhou, Cunlong; Huang, Qingxue

2018-03-01

Micro-metal products have recently enjoyed high demand. In addition, metal microforming has drawn increasing attention due to its net-forming capability, batch manufacturing potential, high product quality, and relatively low equipment cost. Micro-hydromechanical deep drawing (MHDD), a typical microforming method, has been developed to take advantage of hydraulic force. With reduced dimensions, the hydraulic pressure development changes; accordingly, the lubrication condition changes from the macroscale to the microscale. A Voronoi-based finite element model is proposed in this paper to consider the change in lubrication in MHDD according to open and closed lubricant pocket theory. Simulation results agree with experimental results concerning drawing force. Changes in friction significantly affect the drawing process and the drawn cups. Moreover, defined wrinkle indexes have been shown to have a complex relationship with hydraulic pressure. High hydraulic pressure can increase the maximum drawing ratio (drawn cup height), whereas the surface finish represented by the wear is not linearly dependent on the hydraulic pressure due to the wrinkles.

Application of positron annihilation lifetime technique to the study of deep level transients in semiconductors

NASA Astrophysics Data System (ADS)

Deng, A. H.; Shan, Y. Y.; Fung, S.; Beling, C. D.

2002-03-01

Unlike its conventional applications in lattice defect characterization, positron annihilation lifetime technique was applied to study temperature-dependent deep level transients in semiconductors. Defect levels in the band gap can be determined as they are determined by conventional deep level transient spectroscopy (DLTS) studies. The promising advantage of this application of positron annihilation over the conventional DLTS is that it could further extract extra microstructure information of deep-level defects, such as whether a deep level defect is vacancy related or not. A demonstration of EL2 defect level transient study in GaAs was shown and the EL2 level of 0.82±0.02 eV was obtained by a standard Arrhenius analysis, similar to that in conventional DLTS studies.

Deep drawing of 304 L Steel Sheet using Vegetable oils as Forming Lubricants

NASA Astrophysics Data System (ADS)

Shashidhara, Y. M.; Jayaram, S. R.

2012-12-01

The study involves the evaluation of deep drawing process using two non edible oils, Pongam (Pongammia pinnata) and Jatropha (Jatropha carcass) as metal forming lubricants. Experiments are conducted on 304L steel sheets under the raw and modified oils with suitable punch and die on a hydraulic press of 200 ton capacity. The punch load, draw-in-length and wall thickness distribution for deep drawn cups are observed. The drawn cups are scanned using laser scanning technique and 3D models are generated using modeling package. The wall thickness profiles of cups at different sections (or height) are measured using CAD package. Among the two raw oils, the drawn cups under Jatropha oil, have uniform wall thickness profile compared to Pongam oil. Uneven flow of material and cup rupturing is observed under methyl esters of Pongam and Jatropha oil lubricated conditions. However, the results are observed under epoxidised Jatropha oil with uniform metal flow and wall thicknesses compared to mineral and other versions of vegetable oils.

Prediction of forming limit in hydro-mechanical deep drawing of steel sheets using ductile fracture criterion

NASA Astrophysics Data System (ADS)

Oh, S.-T.; Chang, H.-J.; Oh, K. H.; Han, H. N.

2006-04-01

It has been observed that the forming limit curve at fracture (FLCF) of steel sheets, with a relatively higher ductility limit have linear shapes, similar to those of a bulk forming process. In contrast, the FLCF of sheets with a relatively lower ductility limit have rather complex shapes approaching the forming limit curve at neck (FLCN) towards the equi-biaxial strain paths. In this study, the FLCFs of steel sheets were measured and compared with the fracture strains predicted from specific ductile fracture criteria, including a criterion suggested by the authors, which can accurately describe FLCFs with both linear and complex shapes. To predict the forming limit for hydro-mechanical deep drawing of steel sheets, the ductile fracture criteria were integrated into a finite element simulation. The simulation, results based on the criterion suggested by authors accurately predicted the experimetal, fracture limits of steel sheets for the hydro-mechanical deep drawing process.

Forming Limit Diagram of Titanium and Stainless Steel Alloys to Study the Formability of Hydro-Mechanical Deep Drawing Parts

NASA Astrophysics Data System (ADS)

Shirizly, A.

2005-08-01

The increase demand for stronger, lighter and economic sheet metal products, make the Hydromecanical deep drawing process lately more and more popular. The Hydromecanical process is used in almost all types of sheet metal parts from home appliances and kitchenware to automotive and aviation industries. Therefore, many common materials were tested and characterized by their ability to sustain large strains via the well known Forming Limit Diagram (FLD). The aim of this work is to examine the forming capability if the Hydromecanical process in production of hemisphere parts made of materials commonly used in the aviation and aerospace industries. Experimental procedures were carried out to assess their ductility through FLD and the Forming Limit Carve (FLC).Two type of material sheets were tested herewith for demonstrating the procedure: commercial pure titanium and stainless steel 316L. A numerical simulation of the Hydromecanical process was examined and compared to self made Hydromecanical deep drawing of hemispherical parts.

Application Of A New Semi-Empirical Model For Forming Limit Prediction Of Sheet Material Including Superposed Loads Of Bending And Shearing

NASA Astrophysics Data System (ADS)

Held, Christian; Liewald, Mathias; Schleich, Ralf; Sindel, Manfred

2010-06-01

The use of lightweight materials offers substantial strength and weight advantages in car body design. Unfortunately such kinds of sheet material are more susceptible to wrinkling, spring back and fracture during press shop operations. For characterization of capability of sheet material dedicated to deep drawing processes in the automotive industry, mainly Forming Limit Diagrams (FLD) are used. However, new investigations at the Institute for Metal Forming Technology have shown that High Strength Steel Sheet Material and Aluminum Alloys show increased formability in case of bending loads are superposed to stretching loads. Likewise, by superposing shearing on in plane uniaxial or biaxial tension formability changes because of materials crystallographic texture. Such mixed stress and strain conditions including bending and shearing effects can occur in deep-drawing processes of complex car body parts as well as subsequent forming operations like flanging. But changes in formability cannot be described by using the conventional FLC. Hence, for purpose of improvement of failure prediction in numerical simulation codes significant failure criteria for these strain conditions are missing. Considering such aspects in defining suitable failure criteria which is easy to implement into FEA a new semi-empirical model has been developed considering the effect of bending and shearing in sheet metals formability. This failure criterion consists of the combination of the so called cFLC (combined Forming Limit Curve), which considers superposed bending load conditions and the SFLC (Shear Forming Limit Curve), which again includes the effect of shearing on sheet metal's formability.

Photographic and drafting techniques simplify method of producing engineering drawings

NASA Technical Reports Server (NTRS)

Provisor, H.

1968-01-01

Combination of photographic and drafting techniques has been developed to simplify the preparation of three dimensional and dimetric engineering drawings. Conventional photographs can be converted to line drawings by making copy negatives on high contrast film.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson's disease.

PubMed

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M; Tan, Huiling; Brown, Peter

2017-04-01

Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson's disease, elevations in beta activity (13-35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson's disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could be more efficacious than conventional continuous deep brain stimulation in the treatment of Parkinson's disease, and helps inform how adaptive deep brain stimulation might best be delivered. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson’s disease

PubMed Central

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M.; Tan, Huiling

2017-01-01

Abstract Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson’s disease, elevations in beta activity (13–35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson’s disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could be more efficacious than conventional continuous deep brain stimulation in the treatment of Parkinson’s disease, and helps inform how adaptive deep brain stimulation might best be delivered. PMID:28334851

Design and Drawing for Production. Syllabus. Field Test Edition II.

ERIC Educational Resources Information Center

New York State Education Dept., Albany.

This syllabus, which replaces the New York State Education Department publication "Mechanical Drawing and Design," is intended for use in teaching a high school course in design and drawing for production. The materials included in the guide reflect a shift away from the conventional methods of teaching design and drawing to a greater…

Young Children's Human Figure Drawing: Cross-Sectional and Longitudinal Studies.

ERIC Educational Resources Information Center

Cox, M. V.; Parkin, C. E.

1986-01-01

This cross-sectional and longitudinal study investigated the development of human figure drawing in 42 children aged two to four years and eleven months. Drawings were categorized as scribbles, distinct forms, tadpoles, transitional, or conventional figures. Results suggest that young children draw the human figure in a tadpole form before they…

Does a conservative tibial cut in conventional total knee arthroplasty violate the deep medial collateral ligament?

PubMed

Maes, Michael; Luyckx, Thomas; Bellemans, Johan

2014-11-01

Based on the anatomy of the deep medial collateral ligament (MCL), it was hypothesized that at least part of its cross-sectional insertion area is jeopardized while performing a standard tibial cut in conventional total knee arthroplasty (TKA). The aim of this study was to determine whether it is anatomically possible to preserve the tibial deep MCL insertion during conventional TKA. Thirty-three unpaired cadaveric knee specimens were used for this study. Knees with severe varus/valgus deformity or damage to the medial structures of the knee were excluded. In the first part of the study, the dimensions of the tibial insertion of the deep MCL and its relationship to the joint line were recorded. Next, the cross-sectional area of the deep MCL insertion was determined using calibrated digital photographic analysis. In the second part, the effect of a standard 9-mm 3° sloped tibial cut on the structural integrity of the deep MCL cross-sectional insertion area was determined using conventional instrumentation. The proximal border of the deep MCL insertion site on the tibia was located on average 4.7 ± 1.2 mm distally to the joint line. After performing a standard 9-mm 3° sloped tibial cut, on average 54% of the deep MCL insertion area was resected. In 29% of the cases, the deep MCL insertion area was completely excised. The deep MCL cannot routinely be preserved in conventional TKA. The deep MCL insertion is at risk and may be jeopardized in case of a tibial cut 9 mm below the native joint line. As the deep MCL is a distinct medial stabilizer and plays an important role in rotational stability, this may have implications in future designs of both unicondylar and total knee arthroplasty, but further research is necessary.

Electro-thermo-mechanical coupling analysis of deep drawing with resistance heating for aluminum matrix composites sheet

NASA Astrophysics Data System (ADS)

Zhang, Kaifeng; Zhang, Tuoda; Wang, Bo

2013-05-01

Recently, electro-plastic forming to be a focus of attention in materials hot processing research area, because it is a sort of energy-saving, high efficient and green manufacturing technology. An electro-thermo-mechanical model can be adopted to carry out the sequence simulation of aluminum matrix composites sheet deep drawing via electro-thermal coupling and thermal-mechanical coupling method. The first step of process is resistance heating of sheet, then turn off the power, and the second step is deep drawing. Temperature distribution of SiCp/2024Al composite sheet by resistance heating and sheet deep drawing deformation were analyzed. During the simulation, effect of contact resistances, temperature coefficient of resistance for electrode material and SiCp/2024Al composite on temperature distribution were integrally considered. The simulation results demonstrate that Sicp/2024Al composite sheet can be rapidly heated to 400° in 30s using resistances heating and the sheet temperature can be controlled by adjusting the current density. Physical properties of the electrode materials can significantly affect the composite sheet temperature distribution. The temperature difference between the center and the side of the sheet is proportional to the thermal conductivity of the electrode, the principal cause of which is that the heat transfers from the sheet to the electrode. SiCp/2024Al thin-wall part can be intactly manufactured at strain rate of 0.08s-1 and the sheet thickness thinning rate is limited within 20%, which corresponds well to the experimental result.

Exploring the Relationship between Students' Understanding of Conventional Time and Deep (Geologic) Time

NASA Astrophysics Data System (ADS)

Cheek, Kim A.

2013-07-01

Many geologic processes occur in the context of geologic or deep time. Students of all ages demonstrate difficulty grasping this fundamental concept which impacts their ability to acquire other geoscience concepts. A concept of deep time requires the ability to sequence events on an immense temporal scale (succession) and to judge the durations of geologic processes based on the rates at which they occur. The twin concepts of succession and duration are the same ideas that underlie a concept of conventional time. If deep time is an extension of conventional time and not qualitatively different from it, students should display similar reasoning patterns when dealing with analogous tasks over disparate temporal periods. Thirty-five US students aged 13-24 years participated in individual task-based interviews to ascertain how they thought about succession and duration in conventional and deep time. This is the first attempt to explore this relationship in the same study in over 30 years. Most students successfully completed temporal succession tasks, but there was greater variability in responses on duration tasks. Conventional time concepts appear to impact how students reason about deep time. The application of spatial reasoning to temporal tasks sometimes leads to correct responses but in other instances does not. Implications for future research and teaching strategies are discussed.

Southern Ocean Deep-Convection as a Driver of Centennial-to-Millennial-Scale Climate Variability at Southern High Latitudes

NASA Astrophysics Data System (ADS)

Pedro, J. B.; Martin, T.; Steig, E. J.; Jochum, M.; Park, W.; Rasmussen, S.

2015-12-01

Antarctic Isotope Maxima (AIM) are centennial-to-millennial scale warming events observed in Antarctic ice core records from the last glacial period and deglaciation. Mounting evidence links AIM events to parallel variations in atmospheric CO2, Southern Ocean (SO) sea surface temperatures and Antarctic Bottom Water production. According to the prevailing view, AIM events are forced from the North Atlantic by melt-water discharge from ice sheets suppressing the production of North Atlantic Deep Water and associated northward heat transport in the Atlantic. However observations and model studies increasingly suggest that melt-water fluxes have the wrong timing to be invoked as such a trigger. Here, drawing on results form the Kiel Climate Model, we present an alternative hypothesis in which AIM events are forced via internal oscillations in SO deep-convection. The quasi-periodic timescale of deep-convection events is set by heat (buoyancy) accumulation at SO intermediate depths and stochastic variability in sea ice conditions and freshening at the surface. Massive heat release from the SO convective zone drives Antarctic and large-scale southern hemisphere warming via a two-stage process involving changes in the location of Southern Ocean fronts, in the strength and intensity of the Westerlies and in meridional ocean and atmospheric heat flux anomalies. The potential for AIM events to be driven by internal Southern Ocean processes and the identification of time-lags internal to the southern high latitudes challenges conventional views on the North Atlantic as the pacemaker of millennial-scale climate variability.

Deep drawability of Ti/resin/Ti laminated sheet

NASA Astrophysics Data System (ADS)

Hardada, Yasunroi; Hattori, Shuji

2017-10-01

Aiming to enhance functionality of titanium cup, the formability of titanium/resin/titanium laminated sheet by deep drawing was investigated. Although pure titanium has excellent corrosion resistance, the density of titanium is higher than that of light metals, such as aluminum and magnesium. Part of the titanium cup made of resin allows for weight reduction of the cup. Furthermore, the clad cup is more likely to have heat retention and protection against vibration characteristics. In the experiment, the materials were pure titanium and polycarbonate. The initial thickness of the sheet was 0.2 to 0.5 mm in thickness. A total plate thickness of the blank was 1.0 to 1.5 mm in thickness. The blank diameter is 70 mm. The laminated sheet was constituted by interposing resin between two titanium sheets. Each sheet in stacked condition was not joined each other. In the deep drawing process, the laminated sheet was employed and a flat sheet blank was formed into a circle by a punch. For the prevention of seizure in contact area between a drawing tool and titanium, titanium blank was treated by oxide coating. By this method, the fresh and clean titanium is not in direct contact with the die during the forming due to the existence of the oxide layer. The deep drawing was carried out to investigate the formability. The laminated sheet was successfully drawn without the cracks. The section of the drawn cup was observed to examine a formability of the resin sheet. The reduction rate of the thickness was less than 10%. It was found that the titanium/resin/titanium clad cup was successfully drawn.

Experimental study on titanium wire drawing with ultrasonic vibration.

PubMed

Liu, Shen; Shan, Xiaobiao; Guo, Kai; Yang, Yuancai; Xie, Tao

2018-02-01

Titanium and its alloys have been widely used in aerospace and biomedical industries, however, they are classified as difficult-to-machine materials. In this paper, ultrasonic vibration is imposed on the die to overcome the difficulties during conventional titanium wire drawing processes at the room temperature. Numerical simulations were performed to investigate the variation of axial stress within the contacting region and study the change of the drawing stress with several factors in terms of the longitudinal amplitude and frequency of the applied ultrasonic vibration, the diameter reduction ratio, and the drawing force. An experimental testing equipment was established to measure the drawing torque and rotational velocity of the coiler drum during the wire drawing process. The result indicates the drawing force increases with the growth of the drawing velocity and the reduction ratio, whether with or without vibrations. Application of either form of ultrasonic vibrations contributes to the further decrease of the drawing force, especially the longitudinal vibration with larger amplitude. SEM was employed to detect the surface morphology of the processed wires drawn under the three circumstances. The surface quality of the drawn wires with ultrasonic vibrations was apparently improved compared with those using conventional method. In addition, the longitudinal and torsional composite vibration was more effective for surface quality improvement than pure longitudinal vibration, however, at the cost of weakened drawing force reduction effect. Copyright © 2017 Elsevier B.V. All rights reserved.

Constitutive Behavior and Deep Drawability of Three Aluminum Alloys Under Different Temperatures and Deformation Speeds

NASA Astrophysics Data System (ADS)

Panicker, Sudhy S.; Prasad, K. Sajun; Basak, Shamik; Panda, Sushanta Kumar

2017-08-01

In the present work, uniaxial tensile tests were carried out to evaluate the stress-strain response of AA2014, AA5052 and AA6082 aluminum alloys at four temperatures: 303, 423, 523 and 623 K, and three strain rates: 0.0022, 0.022 and 0.22 s-1. It was found that the Cowper-Symonds model was not a robust constitutive model, and it failed to predict the flow behavior, particularly the thermal softening at higher temperatures. Subsequently, a comparative study was made on the capability of Johnson-Cook (JC), modified Zerilli-Armstrong (m-ZA), modified Arrhenius (m-ARR) and artificial neural network (ANN) for modeling the constitutive behavior of all the three aluminum alloys under the mentioned strain rates and temperatures. Also, the improvement in formability of the materials was evaluated at an elevated temperature of 623 K in terms of cup height and maximum safe strains by conducting cylindrical cup deep drawing experiments under two different punch speeds of 4 and 400 mm/min. The cup heights increased during warm deep drawing due to thermal softening and increase in failure strains. Also, a small reduction in cup height was observed when the punch speed increased from 4 to 400 mm/min at 623 K. Hence, it was suggested to use high-speed deformation at elevated temperature to reduce both punch load and cycle time during the deep drawing process.

Development of a Hybrid Deep Drawing Process to Reduce Springback of AHSS

NASA Astrophysics Data System (ADS)

Boskovic, Vladimir; Sommitsch, Christoph; Kicin, Mustafa

2017-09-01

In future, the steel manufacturers will strive for the implementation of Advanced High Strength Steels (AHSS) in the automotive industry to reduce mass and improve structural performance. A key challenge is the definition of optimal and cost effective processes as well as solutions to introduce complex steel products in cold forming. However, the application of these AHSS often leads to formability problems such as springback. One promising approach in order to minimize springback is the relaxation of stress through the targeted heating of materials in the radius area after the deep drawing process. In this study, experiments are conducted on a Dual Phase (DP) and TWining Induced Plasticity (TWIP) steel for the process feasibility study. This work analyses the influence of various heat treatment temperatures on the springback reduction of deep drawn AHSS.

Dynamic analysis of six-bar mechanical press for deep drawing

NASA Astrophysics Data System (ADS)

Mitsi, S.; Tsiafis, I.; Bouzakis, K. D.

2017-02-01

This paper analyzes the dynamical behavior of a six-bar linkage used in mechanical presses for metal forming such as deep drawing. In the under study mechanism, a four-bar linkage is connected to a slider through an articulated binary link. The motion of the six-bar linkage is studied by kinematic analysis developing an analytical method. Furthermore, using an iterative method and d’ Alembert’s principle, the joint forces and drive moment are evaluated considering joint frictions. The simulation results obtained with a MATLAB program are validated by comparing the theoretical values of the input moment with the ones obtained from the conservation of energy law.

Effect of Hydraulic Pressure on Warm Hydro Mechanical Deep Drawing of Magnesium Alloy Sheet

NASA Astrophysics Data System (ADS)

Liu, Wei; Wu, Linzhi; Yuan, Shijian

The uniaxial tensile test and hydraulic bulging test of AZ31 magnesium alloy sheets were applied to study the influence of temperature on the material properties and obtain the forming limit curves at different temperatures. Numerical simulations of warm hydro mechanical deep drawing were carried out to investigate the effect of hydraulic pressure on the formability of a cylindrical cup, and the simplified hydraulic pressure profiles were used to simulate the loading procedure of hydraulic pressure. The optimal hydraulic pressure at different temperatures were given and verified by experimental studies at temperature 100°C and 170V.

Source and transport of human enteric viruses in deep municipal water supply wells

USGS Publications Warehouse

Bradbury, Kenneth R.; Borchardt, Mark A.; Gotkowitz, Madeline; Spencer, Susan K.; Zhu, Jun; Hunt, Randall J.

2013-01-01

Until recently, few water utilities or researchers were aware of possible virus presence in deep aquifers and wells. During 2008 and 2009 we collected a time series of virus samples from six deep municipal water-supply wells. The wells range in depth from approximately 220 to 300 m and draw water from a sandstone aquifer. Three of these wells draw water from beneath a regional aquitard, and three draw water from both above and below the aquitard. We also sampled a local lake and untreated sewage as potential virus sources. Viruses were detected up to 61% of the time in each well sampled, and many groundwater samples were positive for virus infectivity. Lake samples contained viruses over 75% of the time. Virus concentrations and serotypes observed varied markedly with time in all samples. Sewage samples were all extremely high in virus concentration. Virus serotypes detected in sewage and groundwater were temporally correlated, suggesting very rapid virus transport, on the order of weeks, from the source(s) to wells. Adenovirus and enterovirus levels in the wells were associated with precipitation events. The most likely source of the viruses in the wells was leakage of untreated sewage from sanitary sewer pipes.

An incremental analysis of a deep drawing steel’s material behaviour undergoing the predeformation using drawbeads

NASA Astrophysics Data System (ADS)

Schmid, H.; Suttner, S.; Merklein, M.

2017-09-01

Nowadays lightweight design in metal forming processes leads to complex deep drawing geometries, which can cause multiple damages. Therefore, drawbeads are one way to regulate and control material flow during the forming process. Not only in research, but also in industrial practice, it could be determined that material is work hardened passing drawbead geometries. It particularly means when material is pre-deformed with tensile and alternating bending loads. This incident also gives the opportunity to utilize it in a reasonable way if examined properly. To investigate these findings, a process oriented and comprehensive analysis of the material behaviour during these forming operations is needed. In this paper, sheet metal strips are linearly drawn through a drawbead and stopped after passing the drawbead. Within this forming operation, the material undergoes non-linear straining before reaching the in-plane position again. Here, the process will be stopped to investigate a permanent strengthening local along the sheet thickness. Therefore, microhardness measurements are realized before and after passing the drawbead. Because of its common use and its wide known material data, a deep drawing steel DC will be used for these studies. Additionally, the strategy is applied to advanced high strength steel.

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

NASA Astrophysics Data System (ADS)

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

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

Enhancing Deep Learning: Lessons from the Introduction of Learning Teams in Management Education in France

ERIC Educational Resources Information Center

Borredon, Liz; Deffayet, Sylvie; Baker, Ann C.; Kolb, David

2011-01-01

Drawing from the reflective teaching and learning practices recommended in influential publications on learning styles, experiential learning, deep learning, and dialogue, the authors tested the concept of "learning teams" in the framework of a leadership program implemented for the first time in a top French management school…

Local laser-strengthening: Customizing the forming behavior of car body steel sheets

NASA Astrophysics Data System (ADS)

Wagner, M.; Jahn, A.; Beyer, E.; Balzani, D.

2018-05-01

Future trends in designing lightweight components especially for automotive applications increasingly require complex and delicate structures with highest possible level of capacity [1]. The manufacturing of metallic car body components is primarily realized by deep or stretch drawing. The forming process of especially cold rolled and large-sized components is typically characterized by inhomogeneous stress and strain distributions. As a result, the avoidance of undesirable deep drawing effects like earing and local necking is among the greatest challenges in forming complex car body structures [2]. Hence, a novel local laser-treatment approach with the objective of customizing the forming behavior of car body steel sheets is currently explored.

Ballistic parameters and trauma potential of pistol crossbows.

PubMed

Frank, Matthias; Schikorr, Wolfgang; Tesch, Ralf; Werner, Ronald; Hanisch, Steffen; Peters, Dieter; Ekkernkamp, Axel; Bockholdt, Britta; Seifert, Julia

2013-07-01

Hand-held pistol crossbows, which are smaller versions of conventional crossbows, have recently increased in popularity. Similar to conventional crossbows, life threatening injuries due to bolts discharged from pistol crossbows are reported in forensic and traumatological literature. While the ballistic background of conventional crossbows is comprehensively investigated, there are no investigations on the characteristic ballistic parameters (draw force, potential energy, recurve factor, kinetic energy, and efficiency) of pistol crossbows. Two hand-held pistol crossbows (Barnett Commando and Mini Cross Bow, rated draw force 362.9 N or 80 lbs) were tested. The maximum draw force was investigated using a dynamic tensile testing machine (TIRAtest 2705, TIRA GmbH). The potential energy was determined graphically by polynomial regression as area under the force-draw curve. External ballistic parameters of the bolts discharged from pistol crossbows were measured using a redundant ballistic speed measurement system (Dual-BMC 21a and Dual-LS 1000, Werner Mehl Kurzzeitmesstechnik). The average maximum draw force was 190.3 and 175.6 N for the Barnett and Mini Cross Bow, respectively. The corresponding total energy expended was 10.7 and 11 J, respectively. The recurve factor was calculated to be 0.705 and 1.044, respectively. Average bolt velocity was measured 43 up to 52 m/s. The efficiency was calculated up to 0.94. To conclude, this work provides the pending ballistic data on this special subgroup of crossbows which operate on a remarkable low kinetic energy level. Furthermore, it demonstrates that the nominal draw force pretended in the sales brochure is grossly exaggerated.

Prediction of thinning of the sheet metal in the program AutoForm and its experimental verification

NASA Astrophysics Data System (ADS)

Fedorko, M.; Urbánek, M.; Rund, M.

2017-02-01

The manufacture of press-formed parts often involves deep-drawing operations. Deep drawing, however, can be deemed an industrial branch in its own right. Today, many experimental as well as numerical methods are available for designing and optimizing deep drawing operations. The best option, however, is to combine both approaches. The present paper describes one such investigation. Here, measurements and numerical simulation were used for mapping the impact of anisotropy on thickness variation in a spherical-shaped drawn part of DC01 steel. Variation in sheet thickness was measured on spherical-shaped drawn parts of various geometries by means of two cameras, and evaluated with digital image correlation using the ARAMIS software from the company GOM. The forming experiment was carried out on an INOVA 200 kN servohydraulic testing machine in which the force vs. piston displacement curve was recorded. The same experiment was then numerically simulated and analyzed using the AUTOFORM software. Various parameters were monitored, such as thinning, strain magnitude, formability, and others. For the purpose of this simulation, a series of mechanical tests was conducted to obtain descriptions of the experimental material of 1.5 mm thickness. A material model was constructed from the tests data involving the work-hardening curve, the impact of anisotropy, and the forming limit diagram. Specifically, these tests included tensile tests, the Nakajima test, and the stacked test, which were carried out to determine materials data for the model. The actual sheet thickness was measured on a sectioned spherical-shaped drawn part using a NIKON optical microscope. The variations in thickness along defined lines on the sectioned drawn part were compared with the numerical simulations data using digital image correlation. The above-described experimental programme is suitable for calibrating a material model for any computational software and can correctly solve deep-drawing problems.

Combining the pressure effect with local heat treatment for improving the sheet metal forming process

NASA Astrophysics Data System (ADS)

Palumbo, G.; Piccininni, A.; Guglielmi, P.; Sorgente, D.; Tricarico, L.

2016-08-01

The present work deals with the advantages in the Hydromechanical Deep Drawing (HDD) when AA5754 Tailored Heat Treated Blanks (THTBs) are adopted. It is well known that the creation of a suitable distribution of material properties increases the process performance. When non heat-treatable alloys are considered, the THTB approach can be successfully applied to increase the Limit Drawing Ratio (LDR) by changing the peripheral zone into the annealed state starting from a cold-worked blank. If this approach is combined with the advantages of a counterpressure, even more remarkable improvements can be achieved. Due to the large number of involved parameters, the optimized design of both the local treatment and the pressure profile were investigated coupling an axial symmetric Finite Element model with the integration platform modeFRONTIER. Results confirmed the possibility of increasing the LDR from 2.0 (Deep Drawing using a blank in the annealed state) up to about 3.0 if combining the adoption of a THTB with the optimal pressure profile.

SPECIAL ACTIVITIES SUPPLEMENTAL TO AND RELATED TO THE ART PROGRAM AT DEEP RIVER OUTDOOR EDUCATION CENTER.

ERIC Educational Resources Information Center

Gary City Public School System, IN.

A CURRICULUM GUIDE DEALING WITH VARIOUS SUBJECT AREAS WAS PREPARED FOR POSSIBLE STUDY ACTIVITIES THAT WOULD USE THE LEARNING RESOURCES AVAILABLE AT THE DEEP RIVER OUTDOOR EDUCATION CENTER IN GARY, INDIANA. ACTIVITIES GUIDES ARE PRESENTED FOR (1) ART ACTITIVIES RELATED TO DESIGN, COLOR, LANDSCAPE REPRESENTATION, PAPER CONSTRUCTION, DRAWING, PRINT…

A Comparison of Programed Instruction with Conventional Methods for Teaching Two Units of Eighth Grade Science.

ERIC Educational Resources Information Center

Eshleman, Winston Hull

Compared were programed materials and conventional methods for teaching two units of eighth grade science. Programed materials used were linear programed books requiring constructed responses. The conventional methods included textbook study, written exercises, lectures, discussions, demonstrations, experiments, chalkboard drawings, films,…

Formability analysis of austenitic stainless steel-304 under warm conditions

NASA Astrophysics Data System (ADS)

Lade, Jayahari; Singh, Swadesh Kumar; Banoth, Balu Naik; Gupta, Amit Kumar

2013-12-01

A warm deep drawing process of austenitic stainless steel-304 (ASS-304) of circular blanks with coupled ther mal analysis is studied in this article. 65 mm blanks were deep drawn at different temperatures and thickness distribution is experimentally measured after cutting the drawn component into two halves. The process is simulated using explicit fin ite element code LS-DYNA. A Barlat 3 parameter model is used in the simulation, as the material is anisotropic up to 30 0°C. Material properties for the simulation are determined at different temperatures using a 5 T UTM coupled with a furn ace. In this analysis constant punch speed and variable blank holder force (BHF) is applied to draw cups without wrinkle.

Study of wear performance of deep drawing tooling

NASA Astrophysics Data System (ADS)

Naranje, Vishal G.; Karthikeyan, Ram; Nair, Vipin

2017-09-01

One of the most common challenges for many of the mechanical engineers and also in the field of materials science is the issue of occurrences of wear of the material parts which is used in certain applications that involves such surface interactions. In this paper, wear behaviour of particular grade High Carbon High Chromium Steel and many most famously D2, H13, O1 known as the Viking steel has been studied, evaluated and analyzed under certain processing parameters such as speed, load, track diameter and time required for deep drawing process to know it’s the wear rate and coefficient of friction. Also, the significance of the processing parameters which is used for wear testing analysis is also examined.

Imitation, Inspiration, and Creation: Cognitive Process of Creative Drawing by Copying Others' Artworks.

PubMed

Okada, Takeshi; Ishibashi, Kentaro

2017-09-01

To investigate the cognitive processes underlying creative inspiration, we tested the extent to which viewing or copying prior examples impacted creative output in art. In Experiment 1, undergraduates made drawings under three conditions: (a) copying an artist's drawing, then producing an original drawing; (b) producing an original drawing without having seen another's work; and (c) copying another artist's work, then reproducing that artist's style independently. We discovered that through copying unfamiliar abstract drawings, participants were able to produce creative drawings qualitatively different from the model drawings. Process analyses suggested that participants' cognitive constraints became relaxed, and new perspectives were formed from copying another's artwork. Experiment 2 showed that exposure to styles of artwork considered unfamiliar facilitated creativity in drawing, while styles considered familiar did not do so. Experiment 3 showed that both copying and thoroughly viewing artwork executed using an unfamiliar style facilitated creativity in drawing, whereas merely thinking about alternative styles of artistic representation did not do so. These experiments revealed that deep encounters with unfamiliar artworks-whether through copying or prolonged observation-change people's cognitive representations of the act of drawing to produce novel artwork. Copyright © 2016 Cognitive Science Society, Inc.

Fabrication of elliptical SRF cavities

NASA Astrophysics Data System (ADS)

Singer, W.

2017-03-01

The technological and metallurgical requirements of material for high-gradient superconducting cavities are described. High-purity niobium, as the preferred metal for the fabrication of superconducting accelerating cavities, should meet exact specifications. The content of interstitial impurities such as oxygen, nitrogen, and carbon must be below 10 μg g-1. The hydrogen content should be kept below 2 μg g-1 to prevent degradation of the quality factor (Q-value) under certain cool-down conditions. The material should be free of flaws (foreign material inclusions or cracks and laminations) that can initiate a thermal breakdown. Traditional and alternative cavity mechanical fabrication methods are reviewed. Conventionally, niobium cavities are fabricated from sheet niobium by the formation of half-cells by deep drawing, followed by trim machining and electron beam welding. The welding of half-cells is a delicate procedure, requiring intermediate cleaning steps and a careful choice of weld parameters to achieve full penetration of the joints. A challenge for a welded construction is the tight mechanical and electrical tolerances. These can be maintained by a combination of mechanical and radio-frequency measurements on half-cells and by careful tracking of weld shrinkage. The main aspects of quality assurance and quality management are mentioned. The experiences of 800 cavities produced for the European XFEL are presented. Another cavity fabrication approach is slicing discs from the ingot and producing cavities by deep drawing and electron beam welding. Accelerating gradients at the level of 35-45 MV m-1 can be achieved by applying electrochemical polishing treatment. The single-crystal option (grain boundary free) is discussed. It seems that in this case, high performance can be achieved by a simplified treatment procedure. Fabrication of the elliptical resonators from a seamless pipe as an alternative is briefly described. This technology has yielded good performance and is already available for multi-cell structures.

Exploitation of "Excess" Data Now Routinely Collected by Large N, Continuously Recorded Oil Exploration Surveys: From Microseismicity to Deep Crustal Imaging

NASA Astrophysics Data System (ADS)

Brown, L. D.

2014-12-01

The rapidly expanding use by the oil and gas industry of "nodal", large channel capacity areal arrays that record continuously for extended periods of time is generating large volumes of data in excess of that needed for the conventional CMP reflection imaging that is the primary goal of such surveys. These excess data, once considered as simply "noise", have recently been recognized to have utility not only for the exploration seismologist but also for addressing a diverse range of phenomena. The most widely recognized use for these "noise" records is surface wave tomographic imaging of near surface velocity structure via seismic interferometry of ambient natural noise. Such results are proving to be of great value in enhancing conventional 3D exploration imagery, but they should be appreciated in their own right for the information they provide on the shallow subsurface to the hydrologist, engineer and tectonicist. Another relatively dramatic application is the delineation of local structure by tracing the propagation of body and surface waves from local and teleseismic events across these dense arrays. Here I would like draw attention to three other promising uses for such data: a) detection and mapping of microseismicity below the detection thresholds of conventional earthquake monitoring networks, especially in areas of low conventional seismicity; b) reflection and refraction imaging of structure using cultural, as opposed to natural, energy sources, and c) systematic mapping of the basement in 3D using the existing exploration sources recorded at travel times longer than that typically harvested for resource purposes. We conclude by emphasizing that these potentially invaluable "extras" are now being recorded routinely around the world, but there is as yet no mechanism in place to ensure they are exploited rather than simply deleted.

Archaeological Investigation at El Dorado Lake, Butler County, Kansas. Phase III.

DTIC Science & Technology

1982-01-01

time during which deep disturbance predominated is estimated to be roughly equal to the number of years surface and shallow techniques have been... during excavation, but sampled. Measurements are therefore estimated from scale drawings of feature plans. However, the drawing of Feature 3 consists... roasting features with the limestones and/or deposited as refuse during separate disposal episodes. Fauna and Flora A total of 862 bones and bone

A nationwide survey of deep fungal infections and fungal prophylaxis after hematopoietic stem cell transplantation in Japan.

PubMed

Imataki, O; Kami, M; Kim, S-W; Gotoh, M; Komaba, S; Kasai, M; Hashino, S; Naito, K; Masuda, M; Anan, K; Teshima, H; Togitani, K; Inoue, T; Nishimura, M; Adachi, Y; Fukuhara, T; Yamashita, T; Uike, N; Kobayashi, Y; Hamaguchi, M; Higuchi, M; Kawakami, K; Takaue, Y

2004-06-01

We conducted a nationwide survey to define incidence of deep fungal infections and fungal prophylaxis practices after HSCT. In all, 63 institutions responded. Total number of in-patient transplantations was 935: 367 autologous, 414 allogeneic myeloablative, and 154 allogeneic reduced-intensity (RIST) (n=154). Number of patients who were cared for in a clean room at transplant was 261 (71%) in autologous, 409 (99%) in conventional and 93 (66%) in RIST, respectively. All patients received prophylactic antifungal agents; 89% fluconazole. Number of patients who received the dosage recommended in the CDC guidelines (400 mg/day) was 135 (42%) in conventional transplant and 34 (30%) in RIST (P=0.037). Number of patients who received fluconazole until engraftment and beyond day 75 in conventional transplant vs RIST was, respectively, 324 (100%) vs 109 (97%), and 39 (12%) vs 18 (16%), with no significant difference between the two groups. A total of 37 patients (4.0%) were diagnosed with deep fungal infections; autologous transplantation (0.03%), conventional transplantation (6.0%) and RIST (7.1%). Wide variations in antifungal prophylaxis practice according to the type of transplant and the institutions, and deep fungal infection remain significant problems in RIST.

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

PubMed

Hwang, Bosun; You, Jiwoo; Vaessen, Thomas; Myin-Germeys, Inez; Park, Cheolsoo; Zhang, Byoung-Tak

2018-02-08

Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extraction process. This study proposes a novel deep learning framework to recognize the stressful states, the Deep ECGNet, using ultra short-term raw ECG signals without any feature engineering methods. The Deep ECGNet was developed through various experiments and analysis of ECG waveforms. We proposed the optimal recurrent and convolutional neural networks architecture, and also the optimal convolution filter length (related to the P, Q, R, S, and T wave durations of ECG) and pooling length (related to the heart beat period) based on the optimization experiments and analysis on the waveform characteristics of ECG signals. The experiments were also conducted with conventional methods using HRV parameters and frequency features as a benchmark test. The data used in this study were obtained from Kwangwoon University in Korea (13 subjects, Case 1) and KU Leuven University in Belgium (9 subjects, Case 2). Experiments were designed according to various experimental protocols to elicit stressful conditions. The proposed framework to recognize stress conditions, the Deep ECGNet, outperformed the conventional approaches with the highest accuracy of 87.39% for Case 1 and 73.96% for Case 2, respectively, that is, 16.22% and 10.98% improvements compared with those of the conventional HRV method. We proposed an optimal deep learning architecture and its parameters for stress recognition, and the theoretical consideration on how to design the deep learning structure based on the periodic patterns of the raw ECG data. Experimental results in this study have proved that the proposed deep learning model, the Deep ECGNet, is an optimal structure to recognize the stress conditions using ultra short-term ECG data.

The Simpsons: Public Choice in the Tradition of Swift and Orwell

ERIC Educational Resources Information Center

Considine, John

2006-01-01

The author disagrees with Homer Simpson who claims that "...cartoons don't have any deep meaning. They're just stupid drawings that give you a cheap laugh." He argues that The Simpsons have a deep meaning in the same way as the works of Jonathan Swift and George Orwell. The message in The Simpsons, Swift, and Orwell is that those in charge do not…

Comparative evaluation of the amount of the residual monomer in conventional and deep-frozen heat cure polymethylmethacrylate acrylic resin: An in vitro study.

PubMed

Jadhav, Sonali S; Mahajan, Neerja; Sethuraman, Rajesh

2018-01-01

Heat cure acrylic resin material with reduced monomer content is generally recommended for clinical usage as it leads to improved mechanical, physical, and biocompatibility properties. The purpose of the present study was to evaluate and compare the amount of the residual monomer in the conventional and three different groups of deep-frozen heat cure polymethylmethacrylate (PMMA) acrylic resin. Totally 40 Specimens of heat cure PMMA acrylic resin (DPI India) (10 conventional heat cure and 30 deep frozen) were made using two disc-shaped stainless steel molds and invested into type II dental stone using compression molding technique. Each group contained 10 specimens ( n = 10). Group 1: Control group of conventional polished PMMA specimen stored in water for 24 h at +37°C (10 specimens), Group 2: Deep frozen unpolished PMMA (10 specimens), Group 3: Deep frozen polished PMMA (10 specimens), and Group 4: Deep frozen polished PMMA specimen stored in water for 24 h at +37°C (10 specimens). Amount of the residual monomer content in all the specimens was measured using high-performance liquid chromatography. Data were analyzed using One-Way Analysis of Variance and multiple comparison Tukey's post hoc test (α = 0.05). Least residual monomer content was found in Group 4 (0.12 wt%) followed by Group 3 (0.19 wt%), Group 2 (0.23 wt%), and Group 1 (0.26 wt%). Statistically significant difference ( P < 0.05) was found in residual monomer content for all the four groups tested. Post hoc test for intergroup comparison also showed a significant difference between groups. The amount of the residual monomer was found to be least in deep-frozen polished PMMA specimen stored in water for 24 h at +37°C (Group 4). Thus, it can be concluded that deep freezing, polishing, and storing in water can reduce the residual monomer content.

Computer-aided classification of lung nodules on computed tomography images via deep learning technique

PubMed Central

Hua, Kai-Lung; Hsu, Che-Hao; Hidayati, Shintami Chusnul; Cheng, Wen-Huang; Chen, Yu-Jen

2015-01-01

Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain. PMID:26346558

Computer-aided classification of lung nodules on computed tomography images via deep learning technique.

PubMed

Hua, Kai-Lung; Hsu, Che-Hao; Hidayati, Shintami Chusnul; Cheng, Wen-Huang; Chen, Yu-Jen

2015-01-01

Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain.

Deep level transient spectroscopy (DLTS) on colloidal-synthesized nanocrystal solids.

PubMed

Bozyigit, Deniz; Jakob, Michael; Yarema, Olesya; Wood, Vanessa

2013-04-24

We demonstrate current-based, deep level transient spectroscopy (DLTS) on semiconductor nanocrystal solids to obtain quantitative information on deep-lying trap states, which play an important role in the electronic transport properties of these novel solids and impact optoelectronic device performance. Here, we apply this purely electrical measurement to an ethanedithiol-treated, PbS nanocrystal solid and find a deep trap with an activation energy of 0.40 eV and a density of NT = 1.7 × 10(17) cm(-3). We use these findings to draw and interpret band structure models to gain insight into charge transport in PbS nanocrystal solids and the operation of PbS nanocrystal-based solar cells.

Wavelength dependence of the Brillouin spectral width of boron doped germanosilicate optical fibers.

PubMed

Law, Pi-Cheng; Dragic, Peter D

2010-08-30

Boron co-doped germanosilicate fibers are investigated via the Brillouin light scattering technique using two wavelengths, 1534 nm and 1064 nm. Several fibers are investigated, including four drawn from the same preform but at different draw temperatures. The Stokes' shifts and the Brillouin spectral widths are found to increase with increasing fiber draw temperature. A frequency-squared law has adequately described the wavelength dependence of the Brillouin spectral width of conventional Ge-doped fibers. However, it is found that unlike conventional Ge-doped fibers these fibers do not follow the frequency-squared law. This is explained through a frequency-dependent dynamic viscosity that modifies this law.

Generating Seismograms with Deep Neural Networks

NASA Astrophysics Data System (ADS)

Krischer, L.; Fichtner, A.

2017-12-01

The recent surge of successful uses of deep neural networks in computer vision, speech recognition, and natural language processing, mainly enabled by the availability of fast GPUs and extremely large data sets, is starting to see many applications across all natural sciences. In seismology these are largely confined to classification and discrimination tasks. In this contribution we explore the use of deep neural networks for another class of problems: so called generative models.Generative modelling is a branch of statistics concerned with generating new observed data samples, usually by drawing from some underlying probability distribution. Samples with specific attributes can be generated by conditioning on input variables. In this work we condition on seismic source (mechanism and location) and receiver (location) parameters to generate multi-component seismograms.The deep neural networks are trained on synthetic data calculated with Instaseis (http://instaseis.net, van Driel et al. (2015)) and waveforms from the global ShakeMovie project (http://global.shakemovie.princeton.edu, Tromp et al. (2010)). The underlying radially symmetric or smoothly three dimensional Earth structures result in comparatively small waveform differences from similar events or at close receivers and the networks learn to interpolate between training data samples.Of particular importance is the chosen misfit functional. Generative adversarial networks (Goodfellow et al. (2014)) implement a system in which two networks compete: the generator network creates samples and the discriminator network distinguishes these from the true training examples. Both are trained in an adversarial fashion until the discriminator can no longer distinguish between generated and real samples. We show how this can be applied to seismograms and in particular how it compares to networks trained with more conventional misfit metrics. Last but not least we attempt to shed some light on the black-box nature of neural networks by estimating the quality and uncertainties of the generated seismograms.

Both Sides Now: Visualizing and Drawing with the Right and Left Hemispheres of the Brain

ERIC Educational Resources Information Center

Schiferl, E. I.

2008-01-01

Neuroscience research provides new models for understanding vision that challenge Betty Edwards' (1979, 1989, 1999) assumptions about right brain vision and common conventions of "realistic" drawing. Enlisting PET and fMRI technology, neuroscience documents how the brains of normal adults respond to images of recognizable objects and scenes.…

Melted Ice

NASA Image and Video Library

2009-06-24

These drawings depict explanations for the source of intense heat that has been measured coming from Enceladus south polar region. These models predict that water could exist in a deep layer as an ocean or sea and also near the surface.

The Study on the Mechanical Properties of Multi-walled Carbon Nanotube/Polypropylene Fibers

NASA Astrophysics Data System (ADS)

Youssefi, Mostafa; Safaie, Banafsheh

2018-06-01

Polypropylene (PP) is an important semicrystalline polymer with various applications. Polypropylene fibers containing 1 wt% of multi-walled carbon nanotube was spun using a conventional melt spinning apparatus. The produced fibers were drawn with varying levels of draw ratio. The mechanical properties of the composites were studied. Tensile strength and modulus of the composite fibers were increased with the increase in draw ratio. Molecular orientation and helical content of the composite fibers were increased after drawing. To conclude, tensile properties and molecular orientation of the composite fibers were higher than those of neat polypropylene fibers with the same draw ratio.

The Study on the Mechanical Properties of Multi-walled Carbon Nanotube/Polypropylene Fibers

NASA Astrophysics Data System (ADS)

Youssefi, Mostafa; Safaie, Banafsheh

2018-01-01

Polypropylene (PP) is an important semicrystalline polymer with various applications. Polypropylene fibers containing 1 wt% of multi-walled carbon nanotube was spun using a conventional melt spinning apparatus. The produced fibers were drawn with varying levels of draw ratio. The mechanical properties of the composites were studied. Tensile strength and modulus of the composite fibers were increased with the increase in draw ratio. Molecular orientation and helical content of the composite fibers were increased after drawing. To conclude, tensile properties and molecular orientation of the composite fibers were higher than those of neat polypropylene fibers with the same draw ratio.

Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports.

PubMed

Qiu, John X; Yoon, Hong-Jun; Fearn, Paul A; Tourassi, Georgia D

2018-01-01

Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this study, we investigated deep learning and a convolutional neural network (CNN), for extracting ICD-O-3 topographic codes from a corpus of breast and lung cancer pathology reports. We performed two experiments, using a CNN and a more conventional term frequency vector approach, to assess the effects of class prevalence and inter-class transfer learning. The experiments were based on a set of 942 pathology reports with human expert annotations as the gold standard. CNN performance was compared against a more conventional term frequency vector space approach. We observed that the deep learning models consistently outperformed the conventional approaches in the class prevalence experiment, resulting in micro- and macro-F score increases of up to 0.132 and 0.226, respectively, when class labels were well populated. Specifically, the best performing CNN achieved a micro-F score of 0.722 over 12 ICD-O-3 topography codes. Transfer learning provided a consistent but modest performance boost for the deep learning methods but trends were contingent on the CNN method and cancer site. These encouraging results demonstrate the potential of deep learning for automated abstraction of pathology reports.

Student beats the teacher: deep neural networks for lateral ventricles segmentation in brain MR

NASA Astrophysics Data System (ADS)

Ghafoorian, Mohsen; Teuwen, Jonas; Manniesing, Rashindra; Leeuw, Frank-Erik d.; van Ginneken, Bram; Karssemeijer, Nico; Platel, Bram

2018-03-01

Ventricular volume and its progression are known to be linked to several brain diseases such as dementia and schizophrenia. Therefore accurate measurement of ventricle volume is vital for longitudinal studies on these disorders, making automated ventricle segmentation algorithms desirable. In the past few years, deep neural networks have shown to outperform the classical models in many imaging domains. However, the success of deep networks is dependent on manually labeled data sets, which are expensive to acquire especially for higher dimensional data in the medical domain. In this work, we show that deep neural networks can be trained on muchcheaper-to-acquire pseudo-labels (e.g., generated by other automated less accurate methods) and still produce more accurate segmentations compared to the quality of the labels. To show this, we use noisy segmentation labels generated by a conventional region growing algorithm to train a deep network for lateral ventricle segmentation. Then on a large manually annotated test set, we show that the network significantly outperforms the conventional region growing algorithm which was used to produce the training labels for the network. Our experiments report a Dice Similarity Coefficient (DSC) of 0.874 for the trained network compared to 0.754 for the conventional region growing algorithm (p < 0.001).

Quality characteristics of battered and fried chicken: comparison of pressure frying and conventional frying.

PubMed

Das, Rashmi; Pawar, Deepthi P; Modi, Vinod Kumar

2013-04-01

The marinated and battered chicken leg meat and breast meat were pressure fried and their physico-chemical qualities were compared to the conventional fried product (open pan deep fat frying). Shrinkage due to frying process was significantly lesser in case of pressure fried leg meat (PLM) and breast meat (PBM) as compared to products prepared by conventional frying leg meat (CLM) and breast meat (CBM). Also, juiciness of pressure fried chicken products was superior (p ≤ 0.05) than fried products obtained by the conventional method. PLM and PBM had lower fat content (p ≤ 0.05) compared to conventionally fried CLM and CBM. Lipid oxidation was higher (p ≤ 0.05) in conventional frying as compared to pressure frying. Irrespective of the type of chicken meat, conventionally fried meat required higher shear force as compared to pressure fried products. Salmonella, Staphylococcus aureus, Shigella and E. coli were not detected. The study indicates the usefulness and superiority of pressure frying in comparison to conventional deep fat frying.

Deep Drawing Simulations With Different Polycrystalline Models

NASA Astrophysics Data System (ADS)

Duchêne, Laurent; de Montleau, Pierre; Bouvier, Salima; Habraken, Anne Marie

2004-06-01

The goal of this research is to study the anisotropic material behavior during forming processes, represented by both complex yield loci and kinematic-isotropic hardening models. A first part of this paper describes the main concepts of the `Stress-strain interpolation' model that has been implemented in the non-linear finite element code Lagamine. This model consists of a local description of the yield locus based on the texture of the material through the full constraints Taylor's model. The texture evolution due to plastic deformations is computed throughout the FEM simulations. This `local yield locus' approach was initially linked to the classical isotropic Swift hardening law. Recently, a more complex hardening model was implemented: the physically-based microstructural model of Teodosiu. It takes into account intergranular heterogeneity due to the evolution of dislocation structures, that affects isotropic and kinematic hardening. The influence of the hardening model is compared to the influence of the texture evolution thanks to deep drawing simulations.

Analysis of Square Cup Deep-Drawing Test of Pure Titanium

NASA Astrophysics Data System (ADS)

Ogawa, Takaki; Ma, Ninshu; Ueyama, Minoru; Harada, Yasunori

2016-08-01

The prediction of formability of titunium is more difficult than steels since its strong anisotropy. If computer simulation can estimate the formability of titanium, we can select the optimal forming conditions. The purpose of this study was to acquire knowledge for the formability prediction by the computer simulation of the square cup deep-drawing of pure titanium. In this paper, the results of FEM analsis of pure titanium were compared with the experimental results to examine the analysis validity. We analyzed the formability of deepdrawing square cup of titanium by the FEM using solid elements. Compared the analysis results with the experimental results such as the forming shape, the punch load, and the thickness, the validity was confirmed. Further, through analyzing the change of the thickness around the forming corner, it was confirmed that the thickness increased to its maximum value during forming process at the stroke of 35mm more than the maximum stroke.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

The potential of iRest in measuring the hand function performance of stroke patients.

PubMed

Abdul Rahman, Hisyam; Khor, Kang Xiang; Yeong, Che Fai; Su, Eileen Lee Ming; Narayanan, Aqilah Leela T

2017-01-01

Clinical scales such as Fugl-Meyer Assessment (FMA) and Motor Assessment Scale (MAS) are widely used to evaluate stroke patient's motor performance. However, there are several limitations with these assessment scales such as subjectivity, lack of repeatability, time-consuming and highly depend on the ability of the physiotherapy. In contrast, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. However, robot-based assessments are not as well established as conventional assessment scale and the correlation to conventional assessment scale is unclear. This study was carried out to identify important parameters in designing tasks that efficiently assess hand function of stroke patients and to quantify potential benefits of robotic assessment modules to predict the conventional assessment score with iRest. Twelve predictive variables were explored, relating to movement time, velocity, strategy, accuracy and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. Regression models using up to four predictors were developed to describe the MAS. Results show that the time given should be not too long and it would affect the trajectory error. Besides, result also shows that it is possible to use iRest in predicting MAS score. There is a potential of using iRest, a non-motorized device in predicting MAS score.

Nitrate Contamination of Deep Aquifers in the Salinas Valley, California

NASA Astrophysics Data System (ADS)

Moran, J. E.; Esser, B. K.; Hillegonds, D. J.; Holtz, M.; Roberts, S. K.; Singleton, M. J.; Visser, A.; Kulongoski, J. T.; Belitz, K.

2011-12-01

The Salinas Valley, known as 'the salad bowl of the world', has been an agricultural center for more than 100 years. Irrigated row crops such as lettuce and strawberries dominate both land use and water use. Groundwater is the exclusive supply for both irrigation and drinking water. Some irrigation wells and most public water supply wells in the Salinas Valley are constructed to draw water from deep portions of the aquifer system, where contamination by nitrate is less likely than in the shallow portions of the aquifer system. However, a number of wells with top perforations greater than 75 m deep, screened below confining or semi-confining units, have nitrate concentrations greater than the Maximum Contaminant Limit (MCL) of 45 mg/L as NO3-. This study uses nitrate concentrations from several hundred irrigation, drinking water, and monitoring wells (Monterey County Water Resources Agency, 1997), along with tritium-helium groundwater ages acquired at Lawrence Livermore National Laboratory through the State of California Groundwater Monitoring and Assessment (GAMA) program (reported in Kulongoski et al., 2007 and in Moran et al., in press), to identify nitrate 'hot spots' in the deep aquifer and to examine possible modes of nitrate transport to the deep aquifer. In addition, observed apparent groundwater ages are compared with the results of transport simulations that use particle tracking and a stochastic-geostatistical framework to incorporate aquifer heterogeneity to determine the distribution of travel times from the water table to each well (Fogg et al., 1999). The combined evidence from nitrate, tritium, tritiogenic 3He, and radiogenic 4He concentrations, reveals complex recharge and flow to the capture zone of the deep drinking water wells. Widespread groundwater pumping for irrigation accelerates vertical groundwater flow such that high nitrate groundwater reaches some deep drinking water wells. Deeper portions of the wells often draw in water that recharged before agricultural activity began in the valley, while some shallower intervals draw in recycled irrigation water which can have a low tritium concentration but high nitrate concentration. The irrigation return water may take a decade or more to reach the water table, given that the vadose zone in some affected areas is more than 30 m deep, but downward migration is likely enhanced by preferential flow paths, plowing, crop removal, and sprinkler irrigation in surrounding fields. This work was performed under the auspices of the U.S. DOE by LLNL under Contract DE-AC52-07NA27344. Fogg et al., 1999, in AGU Geophysical Monograph 108. Kulongoski et al., 2007. USGS Data Series Report 167 Monterey County Water Agency, 1997. Water Resources Data Report (Water Year 1994-1995) Moran et al., 2011. California GAMA Special Study: Nitrate Fate and Transport in the Salinas Valley. LLNL, in press.

Springback optimization in automotive Shock Absorber Cup with Genetic Algorithm

NASA Astrophysics Data System (ADS)

Kakandikar, Ganesh; Nandedkar, Vilas

2018-02-01

Drawing or forming is a process normally used to achieve a required component form from a metal blank by applying a punch which radially draws the blank into the die by a mechanical or hydraulic action or combining both. When the component is drawn for more depth than the diameter, it is usually seen as deep drawing, which involves complicated states of material deformation. Due to the radial drawing of the material as it enters the die, radial drawing stress occurs in the flange with existence of the tangential compressive stress. This compression generates wrinkles in the flange. Wrinkling is unwanted phenomenon and can be controlled by application of a blank-holding force. Tensile stresses cause thinning in the wall region of the cup. Three main types of the errors occur in such a process are wrinkling, fracturing and springback. This paper reports a work focused on the springback and control. Due to complexity of the process, tool try-outs and experimentation may be costly, bulky and time consuming. Numerical simulation proves to be a good option for studying the process and developing a control strategy for reducing the springback. Finite-element based simulations have been used popularly for such purposes. In this study, the springback in deep drawing of an automotive Shock Absorber Cup is simulated with finite element method. Taguchi design of experiments and analysis of variance are used to analyze the influencing process parameters on the springback. Mathematical relations are developed to relate the process parameters and the resulting springback. The optimization problem is formulated for the springback, referring to the displacement magnitude in the selected sections. Genetic Algorithm is then applied for process optimization with an objective to minimize the springback. The results indicate that a better prediction of the springback and process optimization could be achieved with a combined use of these methods and tools.

Deep Learning for Automated Extraction of Primary Sites from Cancer Pathology Reports

DOE PAGES

Qiu, John; Yoon, Hong-Jun; Fearn, Paul A.; ...

2017-05-03

Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. Here in this study we investigated deep learning and a convolutional neural network (CNN), for extracting ICDO- 3 topographic codes from a corpus of breast and lung cancer pathology reports. We performed two experiments, using a CNN and a more conventional term frequency vector approach, to assess the effects of class prevalence and inter-class transfer learning. The experiments were based on a set of 942 pathology reports with human expert annotations asmore » the gold standard. CNN performance was compared against a more conventional term frequency vector space approach. We observed that the deep learning models consistently outperformed the conventional approaches in the class prevalence experiment, resulting in micro and macro-F score increases of up to 0.132 and 0.226 respectively when class labels were well populated. Specifically, the best performing CNN achieved a micro-F score of 0.722 over 12 ICD-O-3 topography codes. Transfer learning provided a consistent but modest performance boost for the deep learning methods but trends were contingent on CNN method and cancer site. Finally, these encouraging results demonstrate the potential of deep learning for automated abstraction of pathology reports.« less

Deep Learning for Automated Extraction of Primary Sites from Cancer Pathology Reports

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

Qiu, John; Yoon, Hong-Jun; Fearn, Paul A.

Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. Here in this study we investigated deep learning and a convolutional neural network (CNN), for extracting ICDO- 3 topographic codes from a corpus of breast and lung cancer pathology reports. We performed two experiments, using a CNN and a more conventional term frequency vector approach, to assess the effects of class prevalence and inter-class transfer learning. The experiments were based on a set of 942 pathology reports with human expert annotations asmore » the gold standard. CNN performance was compared against a more conventional term frequency vector space approach. We observed that the deep learning models consistently outperformed the conventional approaches in the class prevalence experiment, resulting in micro and macro-F score increases of up to 0.132 and 0.226 respectively when class labels were well populated. Specifically, the best performing CNN achieved a micro-F score of 0.722 over 12 ICD-O-3 topography codes. Transfer learning provided a consistent but modest performance boost for the deep learning methods but trends were contingent on CNN method and cancer site. Finally, these encouraging results demonstrate the potential of deep learning for automated abstraction of pathology reports.« less

Positron deep level transient spectroscopy — a new application of positron annihilation to semiconductor physics

NASA Astrophysics Data System (ADS)

Beling, C. D.; Fung, S.; Au, H. L.; Ling, C. C.; Reddy, C. V.; Deng, A. H.; Panda, B. K.

1997-05-01

Recent positron mobility and lifetime measurements made on ac-biased metal on semi-insulating GaAs junctions, which have identified the native EL2 defect through a determination of the characteristic ionization energy of the donor level, are reviewed. It is shown that these measurements point towards a new spectroscopy, tentatively named positron-DLTS (deep level transient spectroscopy), that is the direct complement to conventional DLTS in that it monitors transients in the electric field of the depletion region rather than the inversely related depletion width, as deep levels undergo ionization. In this new spectroscopy, which may be applied to doped material by use of a suitable positron beam, electric field transients are monitored through the Doppler shift of the annihilation radiation resulting from the drift velocity of the positron in the depletion region. Two useful extensions of the new spectroscopy beyond conventional capacitance-DLTS are suggested. The first is that in some instances information on the microstructure of the defect causing the deep level may be inferred from the sensitivity of the positron to vacancy defects of negative and neutral charge states. The second is that the positron annihilation technique is intrinsically much faster than conventional DLTS with the capability of observing transients some 10 6 times faster, thus allowing deep levels (and even shallow levels) to be investigated without problems associated with carrier freeze-out.

Detection of soft tissue densities from digital breast tomosynthesis: comparison of conventional and deep learning approaches

NASA Astrophysics Data System (ADS)

Fotin, Sergei V.; Yin, Yin; Haldankar, Hrishikesh; Hoffmeister, Jeffrey W.; Periaswamy, Senthil

2016-03-01

Computer-aided detection (CAD) has been used in screening mammography for many years and is likely to be utilized for digital breast tomosynthesis (DBT). Higher detection performance is desirable as it may have an impact on radiologist's decisions and clinical outcomes. Recently the algorithms based on deep convolutional architectures have been shown to achieve state of the art performance in object classification and detection. Similarly, we trained a deep convolutional neural network directly on patches sampled from two-dimensional mammography and reconstructed DBT volumes and compared its performance to a conventional CAD algorithm that is based on computation and classification of hand-engineered features. The detection performance was evaluated on the independent test set of 344 DBT reconstructions (GE SenoClaire 3D, iterative reconstruction algorithm) containing 328 suspicious and 115 malignant soft tissue densities including masses and architectural distortions. Detection sensitivity was measured on a region of interest (ROI) basis at the rate of five detection marks per volume. Moving from conventional to deep learning approach resulted in increase of ROI sensitivity from 0:832 +/- 0:040 to 0:893 +/- 0:033 for suspicious ROIs; and from 0:852 +/- 0:065 to 0:930 +/- 0:046 for malignant ROIs. These results indicate the high utility of deep feature learning in the analysis of DBT data and high potential of the method for broader medical image analysis tasks.

Hot forming and quenching pilot process development for low cost and low environmental impact manufacturing.

NASA Astrophysics Data System (ADS)

Hall, Roger W.; Foster, Alistair; Herrmann Praturlon, Anja

2017-09-01

The Hot Forming and in-tool Quenching (HFQ®) process is a proven technique to enable complex shaped stampings to be manufactured from high strength aluminium. Its widespread uptake for high volume production will be maximised if it is able to wholly amortise the additional investment cost of this process compared to conventional deep drawing techniques. This paper discusses the use of three techniques to guide some of the development decisions taken during upscaling of the HFQ® process. Modelling of Process timing, Cost and Life-cycle impact were found to be effective tools to identify where development budget could be focused in order to be able to manufacture low cost panels of different sizes from many different alloys in a sustainable way. The results confirm that raw material cost, panel trimming, and artificial ageing were some of the highest contributing factors to final component cost. Additionally, heat treatment and lubricant removal stages played a significant role in the overall life-cycle assessment of the final products. These findings confirmed development priorities as novel furnace design, fast artificial ageing and low-cost alloy development.

Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks

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

Phillips, Lawrence A.; Hodas, Nathan O.

Increasingly, cognitive scientists have demonstrated interest in applying tools from deep learning. One use for deep learning is in language acquisition where it is useful to know if a linguistic phenomenon can be learned through domain-general means. To assess whether unsupervised deep learning is appropriate, we first pose a smaller question: Can unsupervised neural networks apply linguistic rules productively, using them in novel situations. We draw from the literature on determiner/noun productivity by training an unsupervised, autoencoder network measuring its ability to combine nouns with determiners. Our simple autoencoder creates combinations it has not previously encountered, displaying a degree ofmore » overlap similar to actual children. While this preliminary work does not provide conclusive evidence for productivity, it warrants further investigation with more complex models. Further, this work helps lay the foundations for future collaboration between the deep learning and cognitive science communities.« less

Potential traceable markers of organic matter in organic and conventional dairy manure using ultraviolet–visible and solid-state 13C nuclear magnetic resonance spectroscopy

USDA-ARS?s Scientific Manuscript database

Organic dairy (OD) production is drawing increasing attention because of public concerns about food safety, animal welfare and the potential environmental impacts of conventional dairy (CD) systems. However, very limited information is available on how organic farming practices affect the chemical ...

Line-drawing algorithms for parallel machines

NASA Technical Reports Server (NTRS)

Pang, Alex T.

1990-01-01

The fact that conventional line-drawing algorithms, when applied directly on parallel machines, can lead to very inefficient codes is addressed. It is suggested that instead of modifying an existing algorithm for a parallel machine, a more efficient implementation can be produced by going back to the invariants in the definition. Popular line-drawing algorithms are compared with two alternatives; distance to a line (a point is on the line if sufficiently close to it) and intersection with a line (a point on the line if an intersection point). For massively parallel single-instruction-multiple-data (SIMD) machines (with thousands of processors and up), the alternatives provide viable line-drawing algorithms. Because of the pixel-per-processor mapping, their performance is independent of the line length and orientation.

Rising to the challenge: Deep acting is more beneficial when tasks are appraised as challenging.

PubMed

Huang, Jason L; Chiaburu, Dan S; Zhang, Xin-an; Li, Ning; Grandey, Alicia A

2015-09-01

Cumulative research indicates that deep acting has a nonsignificant relationship with employee exhaustion, despite arguments that deep acting can be beneficial. To illuminate when deep acting leads to more positive employee outcomes, we draw on the resource conservation perspective to propose a within-individual model of deep acting that focuses on service employees' daily fluctuation of emotional labor and emotional exhaustion. Specifically, we propose that the ongoing experience of felt challenge is a within-person boundary condition that moderates deep acting's relationship with emotional exhaustion, and model emotional exhaustion as a mediating mechanism that subsequently predicts momentary job satisfaction and daily customer conflict handling. Using an experience sampling design, we collected data from 84 service employees over a 3-week period. Deep acting was less emotionally exhausting for service providers when they saw their tasks as more challenging. Furthermore, emotional exhaustion mediated the deep acting by felt challenge interaction effect on momentary job satisfaction and daily customer conflict handling. The findings contribute to a better understanding of the deep acting experience at work, while highlighting customer conflict handling as a key behavioral outcome of emotional labor. (c) 2015 APA, 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.

Deep generative learning for automated EHR diagnosis of traditional Chinese medicine.

PubMed

Liang, Zhaohui; Liu, Jun; Ou, Aihua; Zhang, Honglai; Li, Ziping; Huang, Jimmy Xiangji

2018-05-04

Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the decision procedure of healthcare activities. Well-developed information infrastructure, such as hospital information systems and disease surveillance systems, provides abundant data for CAMDM. However, the complexity of EMR data with abstract medical knowledge makes the conventional model incompetent for the analysis. Thus a deep belief networks (DBN) based model is proposed to simulate the information analysis and decision-making procedure in medical practice. The purpose of this paper is to evaluate a deep learning architecture as an effective solution for CAMDM. A two-step model is applied in our study. At the first step, an optimized seven-layer deep belief network (DBN) is applied as an unsupervised learning algorithm to perform model training to acquire feature representation. Then a support vector machine model is adopted to DBN at the second step of the supervised learning. There are two data sets used in the experiments. One is a plain text data set indexed by medical experts. The other is a structured dataset on primary hypertension. The data are randomly divided to generate the training set for the unsupervised learning and the testing set for the supervised learning. The model performance is evaluated by the statistics of mean and variance, the average precision and coverage on the data sets. Two conventional shallow models (support vector machine / SVM and decision tree / DT) are applied as the comparisons to show the superiority of our proposed approach. The deep learning (DBN + SVM) model outperforms simple SVM and DT on two data sets in terms of all the evaluation measures, which confirms our motivation that the deep model is good at capturing the key features with less dependence when the index is built up by manpower. Our study shows the two-step deep learning model achieves high performance for medical information retrieval over the conventional shallow models. It is able to capture the features of both plain text and the highly-structured database of EMR data. The performance of the deep model is superior to the conventional shallow learning models such as SVM and DT. It is an appropriate knowledge-learning model for information retrieval of EMR system. Therefore, deep learning provides a good solution to improve the performance of CAMDM systems. Copyright © 2018. Published by Elsevier B.V.

An alternative tensiometer design for deep vadose zone monitoring

NASA Astrophysics Data System (ADS)

Moradi, A. B.; Kandelous, M. M.; Hopmans, J. W.

2015-12-01

The conventional tensiometer is among the most accurate devices for soil water matric potential measurements, as well as for estimations of soil water flux from soil water potential gradients. Uncertainties associated with conventional tensiometers such as caused by ambient temperature effects and the draining of the tensiometer tube, as well as their limitation for deep soil monitoring has prevented their widespread use for vadose zone monitoring, despite their superior accuracy, in general. We introduce an alternative tensiometer design that offers the accuracy of the conventional tensiometer, while minimizing afore-mentioned uncertainties and limitations. The proposed alternative tensiometer largely eliminates temperature-induced diurnal fluctuations and uncertainties associated with the draining of the tensiometer tube, and removes the limitation in installation depth. In addition, the manufacturing costs of this alternative tensiometer design is close to that of the conventional tensiometer, while it is especially suited for monitoring of soil water potential gradients as required for soil water flux measurements.

Development of a new method for the noninvasive measurement of deep body temperature without a heater.

PubMed

Kitamura, Kei-Ichiro; Zhu, Xin; Chen, Wenxi; Nemoto, Tetsu

2010-01-01

The conventional zero-heat-flow thermometer, which measures the deep body temperature from the skin surface, is widely used at present. However, this thermometer requires considerable electricity to power the electric heater that compensates for heat loss from the probe; thus, AC power is indispensable for its use. Therefore, this conventional thermometer is inconvenient for unconstrained monitoring. We have developed a new dual-heat-flux method that can measure the deep body temperature from the skin surface without a heater. Our method is convenient for unconstrained and long-term measurement because the instrument is driven by a battery and its design promotes energy conservation. Its probe consists of dual-heat-flow channels with different thermal resistances, and each heat-flow-channel has a pair of IC sensors attached on its top and bottom. The average deep body temperature measurements taken using both the dual-heat-flux and then the zero-heat-flow thermometers from the foreheads of 17 healthy subjects were 37.08 degrees C and 37.02 degrees C, respectively. In addition, the correlation coefficient between the values obtained by the 2 methods was 0.970 (p<0.001). These results show that our method can be used for monitoring the deep body temperature as accurately as the conventional method, and it overcomes the disadvantage of the necessity of AC power supply. (c) 2009 IPEM. Published by Elsevier Ltd. All rights reserved.

Authenticity and autonomy in deep-brain stimulation.

PubMed

Wardrope, Alistair

2014-08-01

Felicitas Kraemer draws on the experiences of patients undergoing deep-brain stimulation (DBS) to propose two distinct and potentially conflicting principles of respect: for an individual's autonomy (interpreted as mental competence), and for their authenticity. I argue instead that, according to commonly-invoked justifications of respect for autonomy, authenticity is itself in part constitutive of an analysis of autonomy worthy of respect; Kraemer's argument thus highlights the shortcomings of practical applications of respect for autonomy that emphasise competence while neglecting other important dimensions of autonomy such as authenticity, since it shows that competence alone cannot be interpreted as a reliable indicator of an individual's capacity for exercising autonomy. I draw from relational accounts to suggest how respect for a more expansive conception of autonomy might be interpreted for individuals undergoing DBS and in general. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Critical evaluation of the usability of augmented reality ophthalmoscopy for the training of inexperienced examiners.

PubMed

Leitritz, Martin A; Ziemssen, Focke; Suesskind, Daniela; Partsch, Michael; Voykov, Bogomil; Bartz-Schmidt, Karl U; Szurman, Gesine B

2014-04-01

To measure the value of augmented reality technology usage to teach the medical students performing binocular indirect ophthalmoscopy. Thirty-seven medical students were randomly assigned to the training of binocular indirect ophthalmoscopy either in the conventional way or with augmented reality ophthalmoscopy (ARO). For testing student's skills, they had to examine a real person using a conventional ophthalmoscopy system and draw the optic disk. They also had to fill out a questionnaire. Subjective and objective evaluations were performed. Thirty-seven students were randomly assigned to two groups. Eighteen students were trained with conventional ophthalmoscopy and 19 students with ARO. The questionnaires showed no differences. Performing an objective analysis, the median ophthalmoscopy training score for the conventional ophthalmoscopy group was 1.2 (range, 0.67-2) and showed a significant difference (P < 0.0033) to the ARO group (median 2; range, 0.67-2). The study provides evidence that a single ARO training is efficient to improve ophthalmoscopy skills. As the objective analysis showed, the ARO group had a significantly superior performance. Our study also indicates that subjective evaluation of the fundus drawings without systematic analysis is prone to errors.

Cellulosic ethanol production from green solvent-pretreated rice straw

USDA-ARS?s Scientific Manuscript database

Natural deep eutectic solvents (NADES) are recently developed “green solvents” consisted of bio-based ionic liquids and deep eutectic solvents mainly from plant based metabolites. NADES are biodegradable, non-toxic and environment-friendly. Conventional chemically synthesized ionic liquids have be...

In-Situ-measurement of restraining forces during forming of rectangular cups

NASA Astrophysics Data System (ADS)

Singer, M.; Liewald, M.

2016-11-01

This contribution introduces a new method for evaluating the restraining forces during forming of rectangular cups with the goal of eliminating the disadvantages of the currently used scientifically established measurement procedures. With this method forming forces are measured indirectly by the elastic deformation of die structure caused by locally varying tribological system. Therefore, two sensors were integrated into the punch, which measure the restraining forces during the forming process. Furthermore, it was possible to evaluate the effects of different lubricants showing the time dependent trend as a function of stroke during the forming of the materials DP600 and DC04. A main advantage of this testing method is to get real friction corresponding data out of the physical deep drawing process as well as the measurement of real acting restraining forces at different areas of the deep drawing part by one single test. Measurement results gained by both sensors have been integrated into LS-Dyna simulation in which the coefficient of friction was regarded as a function of time. The simulated and deep drawn parts afterwards are analysed and compared to specific areas with regard to locally measured thickness of part. Results show an improvement of simulation quality when using locally varying, time dependent coefficients of friction compared to commonly used constant values.

Dry writing of highly conductive electrodes on papers by using silver nanoparticle-graphene hybrid pencils.

PubMed

Park, Jun-Ho; Park, Myung-Joo; Lee, Jang-Sik

2017-01-05

The development of paper electronics would enable realization of extremely cheap devices for portable, disposable, and environmentally-benign electronics. Here, we propose a simple dry-writing tool similar to a pencil, which can be used to draw electrically conducting lines on paper for use in paper-based electronic devices. The fabricated pencil is composed of silver nanoparticles decorated on graphene layers to construct layered hybrid nanostructures. This pencil can draw highly conductive lines that are flexible and foldable on conventional papers. Electrodes drawn using this pencil on conventional copy paper are stable during repetitive mechanical folding and highly resistant to moisture/chemicals. This pencil can draw a conductive line where its resistance can be tuned by changing the amount of nanoparticles. A nonvolatile memory device is realized on papers by hand written lines with different resistance. All memory elements are composed of carbons on papers, so complete data security can be achieved by burning the memory papers. This work will provide a new opportunity to fabricate electronic devices on real papers with good conductivity as well as robust mechanical/chemical stability.

Influence of the pressure dependent coefficient of friction on deep drawing springback predictions

NASA Astrophysics Data System (ADS)

Gil, Imanol; Galdos, Lander; Mendiguren, Joseba; Mugarra, Endika; Sáenz de Argandoña, Eneko

2016-10-01

This research studies the effect of considering an advanced variable friction coefficient on the springback prediction of stamping processes. Traditional constant coefficient of friction considerations are being replaced by more advanced friction coefficient definitions. The aim of this work is to show the influence of defining a pressure dependent friction coefficient on numerical springback predictions of a DX54D mild steel, a HSLA380 and a DP780 high strength steel. The pressure dependent friction model of each material was fitted to the experimental data obtained by Strip Drawing tests. Then, these friction models were implemented in a numerical simulation of a drawing process of an industrial automotive part. The results showed important differences between defining a pressure dependent friction coefficient or a constant friction coefficient.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

NASA Astrophysics Data System (ADS)

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

PubMed

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-15

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

PubMed Central

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-01-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features. PMID:27079888

Hard Truths: Uncovering the Deep Structure of Schooling.

ERIC Educational Resources Information Center

Tye, Barbara Benham

The "deep structure of schooling" is composed of values and assumptions about education widely shared throughout our society. These values and assumptions are shaped by conventional wisdom, tradition, vested interests, and institutional inertia. Americans expect similarities in classrooms, policies, programs, pedagogy, resource allocation,…

Effects of inspiratory muscle training on balance ability and abdominal muscle thickness in chronic stroke patients

PubMed Central

Oh, Dongha; Kim, Gayeong; Lee, Wanhee; Shin, Mary Myong Sook

2016-01-01

[Purpose] This study evaluated the effects of inspiratory muscle training on pulmonary function, deep abdominal muscle thickness, and balance ability in stroke patients. [Subjects] Twenty-three stroke patients were randomly allocated to an experimental (n = 11) or control group (n = 12). [Methods] The experimental group received inspiratory muscle training-based abdominal muscle strengthening with conventional physical therapy; the control group received standard abdominal muscle strengthening with conventional physical therapy. Treatment was conducted 20 minutes per day, 3 times per week for 6 weeks. Pulmonary function testing was performed using an electronic spirometer. Deep abdominal muscle thickness was measured by ultrasonography. Balance was measured using the Berg balance scale. [Results] Forced vital capacity, forced expiratory volume in 1 second, deep abdominal muscle thickness, and Berg balance scale scores were significantly improved in the experimental group than in the control group. [Conclusion] Abdominal muscle strengthening accompanied by inspiratory muscle training is recommended to improve pulmonary function in stroke patients, and may also be used as a practical adjunct to conventional physical therapy. PMID:26957739

Teaching Flowers: A Photo Essay

ERIC Educational Resources Information Center

Hewson, Federico

2017-01-01

"Teaching Flowers" reflects on humanity's deep connections to horticulture by gathering varied thoughts from seminal writers in the field. In addition, this visual article draws attention to labor issues within the U.S. floral industry by documenting the author's exploration of flowers as social sculpture in New York City.

Phonetics and Other Disciplines: Then and Now.

ERIC Educational Resources Information Center

Bronstein, Arthur J.; Raphael, Lawrence J.

Phonetic science is becoming increasingly interdisciplinary. Phoneticians rely on, or at least collaborate with, sociologists, psychologists, biologists, poets, physicists, anthropologists, neurologists and others. A look at the history of phonetics reveals that this seemingly recent trend has deep roots. In fact, it is possible to draw parallels…

Thinking big

NASA Astrophysics Data System (ADS)

Collins, Harry

2008-02-01

Physicists are often quick to discount social research based on qualitative techniques such as ethnography and "deep case studies" - where a researcher draws conclusions about a community based on immersion in the field - thinking that only quantitative research backed up by statistical analysis is sound. The balance is not so clear, however.

Finding Meaning: Sense Inventories for Improved Word Sense Disambiguation

ERIC Educational Resources Information Center

Brown, Susan Windisch

2010-01-01

The deep semantic understanding necessary for complex natural language processing tasks, such as automatic question-answering or text summarization, would benefit from highly accurate word sense disambiguation (WSD). This dissertation investigates what makes an appropriate and effective sense inventory for WSD. Drawing on theories and…

The Impact of Data Fragmentation on High-Throughput Clinical Phenotyping

ERIC Educational Resources Information Center

Wei, Weiqi

2012-01-01

Subject selection is essential and has become the rate-limiting step for harvesting knowledge to advance healthcare through clinical research. Present manual approaches inhibit researchers from conducting deep and broad studies and drawing confident conclusions. High-throughput clinical phenotyping (HTCP), a recently proposed approach, leverages…

Wilderness Vision Quest: A Journey of Transformation.

ERIC Educational Resources Information Center

Brown, Michael H.

The Wilderness Vision Quest is an outdoor retreat which helps participants touch, explore, and develop important latent human resources such as imagination, intuition, creativity, inspiration, and insight. Through the careful and focused use of techniques such as deep relaxation, reflective writing, visualization, guided imagery, symbolic drawing,…

Catholic Education: From and for Faith

ERIC Educational Resources Information Center

Groome, Thomas

2014-01-01

Catholic education arises from the deep structures and earliest traditions of Christian faith. Its commitments throughout the centuries have been to educate both "from" and "for" faith. It educates from a faith perspective by drawing upon the universal values of Catholicism to provide a distinctive philosophy, perhaps even more…

Application of shell elements in simulation of cans ironing

NASA Astrophysics Data System (ADS)

Andrianov, A. V.; Erisov, Y. A.; Aryshensky, E. V.; Aryshensky, V. Y.

2017-01-01

In the present study, the special shell finite elements are used to simulate the drawing with high ironing ratio of aluminum beverage cans. These elements are implemented in commercial software complex PAM-STAMP 2G by means of T.T.S. normal stress option, which is used for ironing to describe well normal stress. By comparison of simulation and experimental data, it is shown that shell elements with T.T.S. option are capable to provide accurate simulation of deep drawing and ironing. The error of can thickness and height computation agrees with the engineering computation accuracy.

Finding Multiple Internal Rates of Return for a Project with Non-Conventional Cash Flows: Utilizing Popular Financial/Graphing Calculators and Spreadsheet Software

ERIC Educational Resources Information Center

Chen, Jeng-Hong

2008-01-01

This study demonstrates that a popular graphing calculator among students, TI-83 Plus, has a powerful function to draw the NPV profile and find the accurate multiple IRRs for a project with non-conventional cash flows. However, finance textbooks or related supplementary materials do not provide students instructions for this part. The detailed…

Cutoff-mesa isolated rib optical waveguide for III-V heterostructure photonic integrated circuits

DOEpatents

Vawter, Gregory A.; Smith, Robert E.

1998-01-01

A cutoff mesa rib waveguide provides single-mode performance regardless of any deep etches that might be used for electrical isolation between integrated electrooptic devices. Utilizing a principle of a cutoff slab waveguide with an asymmetrical refractive index profile, single mode operation is achievable with a wide range of rib widths and does not require demanding etch depth tolerances. This new waveguide design eliminates reflection effects, or self-interference, commonly seen when conventional rib waveguides are combined with deep isolation etches and thereby reduces high order mode propagation and crosstalk compared to the conventional rib waveguides.

Cutoff-mesa isolated rib optical waveguide for III-V heterostructure photonic integrated circuits

DOEpatents

Vawter, G.A.; Smith, R.E.

1998-04-28

A cutoff mesa rib waveguide provides single-mode performance regardless of any deep etches that might be used for electrical isolation between integrated electrooptic devices. Utilizing a principle of a cutoff slab waveguide with an asymmetrical refractive index profile, single mode operation is achievable with a wide range of rib widths and does not require demanding etch depth tolerances. This new waveguide design eliminates reflection effects, or self-interference, commonly seen when conventional rib waveguides are combined with deep isolation etches and thereby reduces high order mode propagation and crosstalk compared to the conventional rib waveguides. 7 figs.

Estimating surface hardening profile of blank for obtaining high drawing ratio in deep drawing process using FE analysis

NASA Astrophysics Data System (ADS)

Tan, C. J.; Aslian, A.; Honarvar, B.; Puborlaksono, J.; Yau, Y. H.; Chong, W. T.

2015-12-01

We constructed an FE axisymmetric model to simulate the effect of partially hardened blanks on increasing the limiting drawing ratio (LDR) of cylindrical cups. We partitioned an arc-shaped hard layer into the cross section of a DP590 blank. We assumed the mechanical property of the layer is equivalent to either DP980 or DP780. We verified the accuracy of the model by comparing the calculated LDR for DP590 with the one reported in the literature. The LDR for the partially hardened blank increased from 2.11 to 2.50 with a 1 mm depth of DP980 ring-shaped hard layer on the top surface of the blank. The position of the layer changed with drawing ratios. We proposed equations for estimating the inner and outer diameters of the layer, and tested its accuracy in the simulation. Although the outer diameters fitted in well with the estimated line, the inner diameters are slightly less than the estimated ones.

Student Orientations to Independent Learning.

ERIC Educational Resources Information Center

Jones, Alice; Jones, Douglas

1996-01-01

A study investigated the relationship of 46 college students' preferred teaching method (conventional lecture versus independent study package) and their own approaches to study (surface, deep, achieving). Results indicated that while students preferred the conventional lecture method, preference did not correlate with their study approach and…

Modeling of the effect of freezer conditions on the hardness of ice cream using response surface methodology.

PubMed

Inoue, K; Ochi, H; Habara, K; Taketsuka, M; Saito, H; Ichihashi, N; Iwatsuki, K

2009-12-01

The effect of conventional continuous freezer parameters [mix flow (L/h), overrun (%), drawing temperature ( degrees C), cylinder pressure (kPa), and dasher speed (rpm)] on the hardness of ice cream under varying measured temperatures (-5, -10, and -15 degrees C) was investigated systematically using response surface methodology (central composite face-centered design), and the relationships were expressed as statistical models. The range (maximum and minimum values) of each freezer parameter was set according to the actual capability of the conventional freezer and applicability to the manufacturing process. Hardness was measured using a penetrometer. These models showed that overrun and drawing temperature had significant effects on hardness. The models can be used to optimize freezer conditions to make ice cream of the least possible hardness under the highest overrun (120%) and a drawing temperature of approximately -5.5 degrees C (slightly warmer than the lowest drawing temperature of -6.5 degrees C) within the range of this study. With reference to the structural elements of the ice cream, we suggest that the volume of overrun and ice crystal content, ice crystal size, and fat globule destabilization affect the hardness of ice cream. In addition, the combination of a simple instrumental parameter and response surface methodology allows us to show the relation between freezer conditions and one of the most important properties-hardness-visually and quantitatively on the practical level.

Data Literacy: Real-World Learning through Problem-Solving with Data Sets

ERIC Educational Resources Information Center

Erwin, Robin W., Jr.

2015-01-01

The achievement of deep learning by secondary students requires teaching approaches that draw students into task commitment, integrated curricula, and analytical thinking. By using real-world data sets in project based instructional units, teachers can guide students in analyzing, interpreting, and reporting quantitative data. Working with…

Helping Disadvantaged Students: Findings from the Thuthuka Programme

ERIC Educational Resources Information Center

Barac, Karin

2015-01-01

Drawing on social closure theory, this study achieved a deep understanding of the perceptions and experiences of the first cohort of candidates passing through the Thuthuka support programme. Using semi-structured interviews as part of a qualitative approach, currently prevalent modes of professional closure were considered by taking the…

A Study of Undergraduate Students' Alternative Conceptions of Earth's Interior Using Drawing Tasks

ERIC Educational Resources Information Center

McAllister, Meredith L.

2014-01-01

Learning fundamental geoscience topics such as plate tectonics, earthquakes, and volcanoes requires students to develop a deep understanding of the conceptual models geologists use when describing the structure and dynamics of Earth's interior. Despite the importance of these mental models underlying much of the undergraduate geoscience…

Dance Like a Butterfly

ERIC Educational Resources Information Center

Stapp, Alicia; Chessin, Debby; Deason, Rebecca

2018-01-01

The authors represent the life cycle of the butterfly through writing, drawing, dance, and math. The Next Generation Science Standards (NGSS) (NGSS Lead States 2013) emphasize college and career readiness as well as critical thinking and problem-solving skills. Students must develop a deep understanding of science concepts and engage in scientific…

Intimacy and Ethical Action in Adult Education

ERIC Educational Resources Information Center

Plumb, Donovan

2009-01-01

This article suggests that thinking about the nature of intimacy, especially sexual intimacy, is a good way of deepening our understanding of how deep-seated psychic vulnerabilities play an important role in adult education contexts. Drawing on psychoanalytic accounts of human development, the paper outlines how the capacity for ethical action in…

Into the Deep: Mindful Music Learning

ERIC Educational Resources Information Center

Lind, Vicki R.

2014-01-01

This article outlines strategies for using thinking routines in the general music classroom to foster deeper learning. Based on the Artful Thinking program, a model developed by Harvard's Project Zero in collaboration with Traverse City [Michigan] Area Public Schools, thinking routines were developed to draw students into a more meaningful…

Improving Arterial Spin Labeling by Using Deep Learning.

PubMed

Kim, Ki Hwan; Choi, Seung Hong; Park, Sung-Hong

2018-05-01

Purpose To develop a deep learning algorithm that generates arterial spin labeling (ASL) perfusion images with higher accuracy and robustness by using a smaller number of subtraction images. Materials and Methods For ASL image generation from pair-wise subtraction, we used a convolutional neural network (CNN) as a deep learning algorithm. The ground truth perfusion images were generated by averaging six or seven pairwise subtraction images acquired with (a) conventional pseudocontinuous arterial spin labeling from seven healthy subjects or (b) Hadamard-encoded pseudocontinuous ASL from 114 patients with various diseases. CNNs were trained to generate perfusion images from a smaller number (two or three) of subtraction images and evaluated by means of cross-validation. CNNs from the patient data sets were also tested on 26 separate stroke data sets. CNNs were compared with the conventional averaging method in terms of mean square error and radiologic score by using a paired t test and/or Wilcoxon signed-rank test. Results Mean square errors were approximately 40% lower than those of the conventional averaging method for the cross-validation with the healthy subjects and patients and the separate test with the patients who had experienced a stroke (P < .001). Region-of-interest analysis in stroke regions showed that cerebral blood flow maps from CNN (mean ± standard deviation, 19.7 mL per 100 g/min ± 9.7) had smaller mean square errors than those determined with the conventional averaging method (43.2 ± 29.8) (P < .001). Radiologic scoring demonstrated that CNNs suppressed noise and motion and/or segmentation artifacts better than the conventional averaging method did (P < .001). Conclusion CNNs provided superior perfusion image quality and more accurate perfusion measurement compared with those of the conventional averaging method for generation of ASL images from pair-wise subtraction images. © RSNA, 2017.

Google DeepMind and healthcare in an age of algorithms.

PubMed

Powles, Julia; Hodson, Hal

2017-01-01

Data-driven tools and techniques, particularly machine learning methods that underpin artificial intelligence, offer promise in improving healthcare systems and services. One of the companies aspiring to pioneer these advances is DeepMind Technologies Limited, a wholly-owned subsidiary of the Google conglomerate, Alphabet Inc. In 2016, DeepMind announced its first major health project: a collaboration with the Royal Free London NHS Foundation Trust, to assist in the management of acute kidney injury. Initially received with great enthusiasm, the collaboration has suffered from a lack of clarity and openness, with issues of privacy and power emerging as potent challenges as the project has unfolded. Taking the DeepMind-Royal Free case study as its pivot, this article draws a number of lessons on the transfer of population-derived datasets to large private prospectors, identifying critical questions for policy-makers, industry and individuals as healthcare moves into an algorithmic age.

Testing for Controlled Rapid Pressurization

DOE Data Explorer

Steven Knudsen

2014-09-03

Borehole W1 is a NQ core hole drilled at our test site in Socorro. The rock is rhyolite. Borehole W1 which was used to test gas-gas explosive mixtures is 55 feet deep with casing (pinkish in the drawing) set to 35 feet. The model is a representation of the borehole and the holes we cored around the central borehole after the test. The brown colored core holes showed dye when we filled W1 with water and slightly pressurized it. This indicates there was some path between W1 and the colored core hole. The core holes are shown to their TD in the drawing. The green plane is a fracture plane which we believe is the result of the explosions of the gas mixture in W1. Data resource is a 2D .pdf Solid Works Drawing of borehole w-1

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

PubMed

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

2016-06-01

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

A Simple Deep Learning Method for Neuronal Spike Sorting

NASA Astrophysics Data System (ADS)

Yang, Kai; Wu, Haifeng; Zeng, Yu

2017-10-01

Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

Hybrid texture generator

NASA Astrophysics Data System (ADS)

Miyata, Kazunori; Nakajima, Masayuki

1995-04-01

A method is given for synthesizing a texture by using the interface of a conventional drawing tool. The majority of conventional texture generation methods are based on the procedural approach, and can generate a variety of textures that are adequate for generating a realistic image. But it is hard for a user to imagine what kind of texture will be generated simply by looking at its parameters. Furthermore, it is difficult to design a new texture freely without a knowledge of all the procedures for texture generation. Our method offers a solution to these problems, and has the following four merits: First, a variety of textures can be obtained by combining a set of feature lines and attribute functions. Second, data definitions are flexible. Third, the user can preview a texture together with its feature lines. Fourth, people can design their own textures interactively and freely by using the interface of a conventional drawing tool. For users who want to build this texture generation method into their own programs, we also give the language specifications for generating a texture. This method can interactively provide a variety of textures, and can also be used for typographic design.

The deep ocean under climate change

NASA Astrophysics Data System (ADS)

Levin, Lisa A.; Le Bris, Nadine

2015-11-01

The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems.

Fish, field, habitus and madness: the first wave mental health users movement in Great Britain.

PubMed

Crossley, N

1999-12-01

This paper traces and explains the emergence of the mental health users movement in Great Britain, focusing specifically upon the formation of the Mental Patients Union in the early 1970s. The analysis presented in the paper draws, to some extent, from conventional movement theory. In addition, however, it draws from the work of Pierre Bourdieu. This represents an innovation in movement analysis and the necessity of this innovation is argued for in an early section of the paper.

Process Design of Aluminum Tailor Heat Treated Blanks.

PubMed

Kahrimanidis, Alexander; Lechner, Michael; Degner, Julia; Wortberg, Daniel; Merklein, Marion

2015-12-09

In many industrials field, especially in the automotive sector, there is a trend toward lightweight constructions in order to reduce the weight and thereby the CO₂ and NO x emissions of the products. An auspicious approach within this context is the substitution of conventional deep drawing steel by precipitation hardenable aluminum alloys. However, based on the low formability, the application for complex stamping parts is challenging. Therefore, at the Institute of Manufacturing Technology, an innovative technology to enhance the forming limit of these lightweight materials was invented. The key idea of the so-called Tailor Heat Treated Blanks (THTB) is optimization of the mechanical properties by local heat treatment before the forming operation. An accurate description of material properties is crucial to predict the forming behavior of tailor heat treated blanks by simulation. Therefore, within in this research project, a holistic approach for the design of the THTB process in dependency of the main influencing parameters is presented and discussed in detail. The capability of the approach for the process development of complex forming operations is demonstrated by a comparison of local blank thickness of a tailgate with the corresponding results from simulation.

Process Design of Aluminum Tailor Heat Treated Blanks

PubMed Central

Kahrimanidis, Alexander; Lechner, Michael; Degner, Julia; Wortberg, Daniel; Merklein, Marion

2015-01-01

In many industrials field, especially in the automotive sector, there is a trend toward lightweight constructions in order to reduce the weight and thereby the CO2 and NOx emissions of the products. An auspicious approach within this context is the substitution of conventional deep drawing steel by precipitation hardenable aluminum alloys. However, based on the low formability, the application for complex stamping parts is challenging. Therefore, at the Institute of Manufacturing Technology, an innovative technology to enhance the forming limit of these lightweight materials was invented. The key idea of the so-called Tailor Heat Treated Blanks (THTB) is optimization of the mechanical properties by local heat treatment before the forming operation. An accurate description of material properties is crucial to predict the forming behavior of tailor heat treated blanks by simulation. Therefore, within in this research project, a holistic approach for the design of the THTB process in dependency of the main influencing parameters is presented and discussed in detail. The capability of the approach for the process development of complex forming operations is demonstrated by a comparison of local blank thickness of a tailgate with the corresponding results from simulation. PMID:28793727

Characterization of Tensile Properties, Limiting Strains, and Deep Drawing Behavior of AA5754-H22 Sheet at Elevated Temperature

NASA Astrophysics Data System (ADS)

Panicker, Sudhy S.; Singh, Har Govind; Panda, Sushanta Kumar; Dashwood, Richard

2015-11-01

Automotive industries are very much interested in characterization of formability improvement of aluminum alloys at elevated temperatures before designing tools, heating systems, and processing sequences for fabrication of auto-body panels by warm forming technology. In this study, tensile tests of AA5754-H22 aluminum alloy were carried out at five different temperatures and three different strain rates to investigate the deformation behavior correlating with Cowper-Symonds constitutive equation. Laboratory scale warm forming facilities were designed and fabricated to perform limiting dome height and deep drawing tests to evaluate forming limit strains and drawability of sheet metal at different tool temperatures. The forming limit strain and dome height improved significantly when both the die and punch were heated to 200 °C. Remarkable improvement in deep drawn cup depth was observed when die and punch temperatures were maintained at 200 and 30 °C, respectively, producing a non-isothermal temperature gradient of approximately 93 °C across the blank from flange to center. The forming behavior at different isothermal and non-isothermal conditions were predicted successfully using a thermo-mechanical FE model incorporating temperature-dependent properties in Barlat-89 yield criterion coupled with Cowper-Symonds hardening model, and the thinning/failure location in deformed cups were validated implementing the experimental limiting strains as damage model.

MX Siting Investigation. Geotechnical Siting Status Report. Volume 2.

DTIC Science & Technology

1978-06-21

greater tnan a nominal 50 feet deep. Rock is considered any earth material which is not readily rippable by conventional excavation techniques. b. Surface...material which is not readily rippable by conventional excavation techniques. _ b. Surface water absent and occurrences of ground water greater than a

Deep nursing: a thoughtful, co-created nursing process.

PubMed

Griffiths, Colin

2017-03-30

This article examines some of the challenges in nursing practice experienced by patients and nurses in the UK and Ireland, and considers some of the associated stressors in the system. Nurses must respond to these challenges by crafting their own practice, and the article offers a blueprint for developing personal nursing practice through acceptance, paying detailed attention to patients, taking time with patients and personal reflection. It draws on innovations in learning disability practice to suggest that care should be jointly thought through and co-created by patients and nurses, and that this process of thoughtful engagement constitutes 'deep nursing'.

Offshore Floating Wind Turbine-driven Deep Sea Water Pumping for Combined Electrical Power and District Cooling

NASA Astrophysics Data System (ADS)

Sant, T.; Buhagiar, D.; Farrugia, R. N.

2014-06-01

A new concept utilising floating wind turbines to exploit the low temperatures of deep sea water for space cooling in buildings is presented. The approach is based on offshore hydraulic wind turbines pumping pressurised deep sea water to a centralised plant consisting of a hydro-electric power system coupled to a large-scale sea water-cooled air conditioning (AC) unit of an urban district cooling network. In order to investigate the potential advantages of this new concept over conventional technologies, a simplified model for performance simulation of a vapour compression AC unit was applied independently to three different systems, with the AC unit operating with (1) a constant flow of sea surface water, (2) a constant flow of sea water consisting of a mixture of surface sea water and deep sea water delivered by a single offshore hydraulic wind turbine and (3) an intermittent flow of deep sea water pumped by a single offshore hydraulic wind turbine. The analysis was based on one year of wind and ambient temperature data for the Central Mediterranean that is known for its deep waters, warm climate and relatively low wind speeds. The study confirmed that while the present concept is less efficient than conventional turbines utilising grid-connected electrical generators, a significant portion of the losses associated with the hydraulic transmission through the pipeline are offset by the extraction of cool deep sea water which reduces the electricity consumption of urban air-conditioning units.

The effects of running in place in a limited area with abdominal drawing-in maneuvers on abdominal muscle thickness in chronic low back pain patients.

PubMed

Gong, Wontae

2016-11-21

Based on previous studies indicating that core stabilization exercises accompanied by abdominal drawing-in maneuvers increase the thickness of the transversus abdominis muscle. The purpose of this study was to compare the measurements of abdominal muscle thicknesses during running in place in a limited area with the abdominal drawing-in maneuver. The study classified the subjects into two experimental groups: the training group (M = 2, F = 13), and the control group (M = 2, F = 13). The training group performed three sets of running in place in a limited area with abdominal drawing-in maneuvers each time, three times a week for six weeks. The abdominal muscle thicknesses of the subjects were measured using ultrasonography. Comparing the training group's abdominal muscle thickness before and after this study, there was a statistical significance in all of the external obliquus abdominis, the internal obliquus abdominis, and the transversus abdominis. In particular, thicknesses of external obliquus abdominis and internal obliquus increased remarkably. Running in place in a limited area accompanied by abdominal drawing-in maneuvers increased the thickness of the deep abdominal muscles that are the basis of trunk stabilization.

Evaluation of mechanisms that might control transport of wastewater contaminants in bedrock multi-aquifer systems

USDA-ARS?s Scientific Manuscript database

Ongoing research has identified infectious human enteric viruses in the Madison, Wisconsin, public supply wells that draw water from a deep, confined sandstone aquifer. These viruses most likely originate from leaking sanitary sewers and are a potential human health risk. Due to a relatively short (...

Digital Storytelling: Emotions in Higher Education

ERIC Educational Resources Information Center

Ribeiro, Sandra; Moreira, António; da Silva, Cristina Pinto

2014-01-01

In tandem with the deep structural changes that have taken place in society, education must also shift towards a teaching approach focused on learning and the overall development of the student. The integration of technology may be the drive to foster the needed changes. We draw on the literature of pertaining to the role of emotions and…

Drawing on Popular Culture: Using Tattooing to Introduce Biological Concepts

ERIC Educational Resources Information Center

Poli, DorothyBelle; Fleenor, Matthew; Rearick, Matthew

2012-01-01

Collaboration between two biologists and a physicist resulted in the example of tattooing being used as a motivator to support discussion across several scientific fields (cell biology, microbiology, human health, and physics). Although often viewed as self-destructive and rebellious in the Western world, tattooing has a deep and rich history full…

Learning Styles: Fashion Fad or Lever for Change? The Application of Learning Style Theory to Inclusive Curriculum Delivery.

ERIC Educational Resources Information Center

Smith, Jan

2002-01-01

Examines how four classifications of learning styles--field dependence/independence, holistic/sequential, styles linked to the experiential learning cycle, and "deep" and "surface" learning--relate to curriculum values. Draws on research at Sheffield Hallam University into the learning styles of General National Vocational…

Lumbo-pelvic joint protection against antigravity forces: motor control and segmental stiffness assessed with magnetic resonance imaging.

PubMed

Richardson, C A; Hides, J A; Wilson, S; Stanton, W; Snijders, C J

2004-07-01

The antigravity muscles of the lumbo-pelvic region, especially transversus abdominis (TrA), are important for the protection and support of the weightbearing joints. Measures of TrA function (the response to the postural cue of drawing in the abdominal wall) have been developed and quantified using magnetic resonance imaging (MRI). Cross-sections through the trunk allowed muscle contraction as well as the large fascial attachments of the TrA to be visualized. The cross sectional area (CSA) of the deep musculo-fascial system was measured at rest and in the contracted state, using static images as well as a cine sequence. In this developmental study, MRI measures were undertaken on a small sample of low back pain (LBP) and non LBP subjects. Results demonstrated that, in non LBP subjects, the draw in action produced a symmetrical deep musculo-fascial "corset" which encircles the abdomen. This study demonstrated a difference in this "corset" measure between subjects with and without LBP. These measures may also prove useful to quantify the effect of unloading in bedrest and microgravity exposure.

Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Yamada, Kazuma; Kojima, Takuya; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

2018-02-01

The purpose of this study is to evaluate and compare the performance of modern deep learning techniques for automatically recognizing and segmenting multiple organ regions on 3D CT images. CT image segmentation is one of the important task in medical image analysis and is still very challenging. Deep learning approaches have demonstrated the capability of scene recognition and semantic segmentation on nature images and have been used to address segmentation problems of medical images. Although several works showed promising results of CT image segmentation by using deep learning approaches, there is no comprehensive evaluation of segmentation performance of the deep learning on segmenting multiple organs on different portions of CT scans. In this paper, we evaluated and compared the segmentation performance of two different deep learning approaches that used 2D- and 3D deep convolutional neural networks (CNN) without- and with a pre-processing step. A conventional approach that presents the state-of-the-art performance of CT image segmentation without deep learning was also used for comparison. A dataset that includes 240 CT images scanned on different portions of human bodies was used for performance evaluation. The maximum number of 17 types of organ regions in each CT scan were segmented automatically and compared to the human annotations by using ratio of intersection over union (IU) as the criterion. The experimental results demonstrated the IUs of the segmentation results had a mean value of 79% and 67% by averaging 17 types of organs that segmented by a 3D- and 2D deep CNN, respectively. All the results of the deep learning approaches showed a better accuracy and robustness than the conventional segmentation method that used probabilistic atlas and graph-cut methods. The effectiveness and the usefulness of deep learning approaches were demonstrated for solving multiple organs segmentation problem on 3D CT images.

Deep smarts.

PubMed

Leonard, Dorothy; Swap, Walter

2004-09-01

When a person sizes up a complex situation and rapidly comes to a decision that proves to be not just good but brilliant, you think, "That was smart." After you watch him do this a few times, you realize you're in the presence of something special. It's not raw brainpower, though that helps. It's not emotional intelligence, either, though that, too, is often involved. It's deep smarts. Deep smarts are not philosophical--they're not"wisdom" in that sense, but they're as close to wisdom as business gets. You see them in the manager who understands when and how to move into a new international market, in the executive who knows just what kind of talk to give when her organization is in crisis, in the technician who can track a product failure back to an interaction between independently produced elements. These are people whose knowledge would be hard to purchase on the open market. Their insight is based on know-how more than on know-what; it comprises a system view as well as expertise in individual areas. Because deep smarts are experienced based and often context specific, they can't be produced overnight or readily imported into an organization. It takes years for an individual to develop them--and no time at all for an organization to lose them when a valued veteran walks out the door. They can be taught, however, with the right techniques. Drawing on their forthcoming book Deep Smarts, Dorothy Leonard and Walter Swap say the best way to transfer such expertise to novices--and, on a larger scale, to make individual knowledge institutional--isn't through PowerPoint slides, a Web site of best practices, online training, project reports, or lectures. Rather, the sage needs to teach the neophyte individually how to draw wisdom from experience. Companies have to be willing to dedicate time and effort to such extensive training, but the investment more than pays for itself.

Experimental formability analysis of bondal sandwich sheet

NASA Astrophysics Data System (ADS)

Kami, Abdolvahed; Banabic, Dorel

2018-05-01

Metal/polymer/metal sandwich sheets have recently attracted the interests of industries like automotive industry. These sandwich sheets have superior properties over single-layer metallic sheets including good sound and vibration damping and light weight. However, the formability of these sandwich sheets should be enhanced which requires more research. In this paper, the formability of Bondal sheet (DC06/viscoelastic polymer/DC06 sandwich sheet) was studied through different types of experiments. The mechanical properties of Bondal were determined by uniaxial tensile tests. Hemispherical punch stretching and hydraulic bulge tests were carried out to determine the forming limit diagram (FLD) of Bondal. Furthermore, cylindrical and square cup drawing tests were performed in dry and oil lubricated conditions. These tests were conducted at different blank holding forces (BHFs). An interesting observation about Bondal sheet deep drawing was obtaining of higher drawing depths at dry condition in comparison with oil-lubricated condition.

The deep ocean under climate change.

PubMed

Levin, Lisa A; Le Bris, Nadine

2015-11-13

The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems. Copyright © 2015, American Association for the Advancement of Science.

Long-term scar quality after hydrosurgical versus conventional debridement of deep dermal burns (HyCon trial): study protocol for a randomized controlled trial.

PubMed

Legemate, Catherine M; Goei, Harold; Middelkoop, Esther; Oen, Irma M M H; Nijhuis, Tim H J; Kwa, Kelly A A; van Zuijlen, Paul P M; Beerthuizen, Gerard I J M; Nieuwenhuis, Marianne K; van Baar, Margriet E; van der Vlies, Cornelis H

2018-04-19

Deep dermal burns require tangential excision of non-viable tissue and skin grafting to improve wound healing and burn-scar quality. Tangential excision is conventionally performed with a knife, but during the last decade hydrosurgery has become popular as a new tool for tangential excision. Hydrosurgery is generally thought to be a more precise and controlled manner of burn debridement leading to preservation of viable tissue and, therefore, better scar quality. Although scar quality is considered to be one of the most important outcomes in burn surgery today, no randomized controlled study has compared the effect of these two common treatment modalities with scar quality as a primary outcome. The aim of this study is, therefore, to compare long-term scar quality after hydrosurgical versus conventional tangential excision in deep dermal burns. A multicenter, randomized, intra-patient, controlled trial will be conducted in the Dutch burn centers of Rotterdam, Beverwijk, and Groningen. All patients with deep dermal burns that require excision and grafting are eligible. Exclusion criteria are: a burn wound < 50 cm 2 , total body surface area (TBSA) burned > 30%, full-thickness burns, chemical or electrical burns, infected wounds (clinical symptoms in combination with positive wound swabs), insufficient knowledge of the Dutch or English language, patients that are unlikely to comply with requirements of the study protocol and follow-up, and patients who are (temporarily) incompetent because of sedation and/or intubation. A total of 137 patients will be included. Comparable wound areas A and B will be appointed, randomized and either excised conventionally with a knife or with the hydrosurgery system. The primary outcome is scar quality measured by the observer score of the Patient and Observer Scar Assessment Scale (POSAS); a subjective scar-assessment instrument, consisting of two separate six-item scales (observer and patient) that are both scored on a 10-point rating scale. This study will contribute to the optimal surgical treatment of patients with deep dermal burn wounds. Dutch Trial Register, NTR6232 . Registered on 23 January 2017.

From Scribbles to Stories: Supporting Writing Development.

ERIC Educational Resources Information Center

Diffily, Deborah

2001-01-01

Describes how caregivers can support young children's writing development. Outlines stages of writing: scribbling, drawing, invented letters, random letters, copying words, developmental spelling, and conventional spelling. Provides tips on what to say to children in each stage of writing. (KB)

Open Space: Nurturing Reflection, Dialogue, and Radical Listening in Higher Education

ERIC Educational Resources Information Center

Bach, Dorothe J.; Cook-Sather, Alison

2016-01-01

This article is about and for teachers wishing to open space at the intersection of the affective and the cognitive-space, we argue, that is particularly conducive to deep learning and within which students can empower themselves as learners and knowers. Drawing on written and spoken reflections of three faculty members, the authors explore how…

A Study of Secondary School English Teachers' Beliefs in the Context of Curriculum Reform in China

ERIC Educational Resources Information Center

Zhang, Fengjuan; Liu, Yongbing

2014-01-01

This study examines the beliefs of Chinese junior high school English teachers about foreign language teaching and influencing contextual factors in a time when curriculum innovation is confronting deep-rooted cultural traditions and complex teaching realities. Drawing upon data collected by means of questionnaires and interviews, this study…

Preservice Elementary Teachers Use Drawings and Make Sets of Materials to Explain Multiplication and Division by Fractions

ERIC Educational Resources Information Center

Rule, Audrey C., Ed.; Hallagan, Jean E., Ed.

2006-01-01

Background: Multiplication and division by fractions are among the most troublesome concepts in the elementary mathematics curriculum. Recent studies have shown that preservice elementary teachers in the United States do not have deep understandings of these concepts. Effective ways to improve preservice teachers' conceptual understanding of these…

America's Forgotten Children: Child Poverty in Rural America.

ERIC Educational Resources Information Center

Nadel, Wendy; Sagawa, Shirley

This report draws on research, statistics, and the voices of rural young people to document the extent and causes of rural child poverty, and related problems and reasons for hope in specific focus areas. About 2.5 million rural children are chronically poor. Rural poverty is concentrated in central Appalachia, the deep South, the U.S.-Mexican…

Ethnography as Method, Methodology, and "Deep Theorizing" Closing the Gap between Text and Context in Academic Writing Research

ERIC Educational Resources Information Center

Lillis, Theresa

2008-01-01

This article critically explores the value of ethnography for enhancing context-sensitive approaches to the study of academic writing. Drawing on data from two longitudinal studies, student writing in the United Kingdom and professional academic writing in Hungary, Slovakia, Spain, and Portugal, the author illustrates the different contributions…

Tilting at Windmills: School Reform, San Diego, and America?s Race to Renew Public Education

ERIC Educational Resources Information Center

Colvin, Richard Lee

2013-01-01

A book that draws equally on Richard Lee Colvin's deep acquaintance with contemporary education reform and the unique circumstances of the San Diego experience, "Tilting at Windmills" is a penetrating and invaluable account of Alan Bersin's contentious superintendency. Between 1998, when Alan Bersin became superintendent of the San Diego…

"Most Learn Almost Nothing": Building Democratic Citizenship by Engaging Controversial History through Inquiry in Post-Communist Europe

ERIC Educational Resources Information Center

Misco, Thomas

2011-01-01

This article addresses the challenges and pathways of Holocaust education in post-communist countries through two case studies. I first examine historiographical, institutional and cultural obstacles to deep and meaningful treatments of the Holocaust within Latvian and Romanian schools. Drawing upon the unique experiences both countries had with…

Hydrostatic collapse research in support of the Oman India gas pipeline

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

Stark, P.R.; McKeehan, D.S.

1995-12-01

This paper provides a summary of the collapse test program conducted as part of the technical development for the Ultra Deep Oman to India Pipeline. The paper describes the motivation for conducting the collapse test program, outlines the test objectives and procedures, presents the results obtained, and draws conclusions on the factors affecting collapse resistance.

Clinical results of computerized tomography-based simulation with laser patient marking.

PubMed

Ragan, D P; Forman, J D; He, T; Mesina, C F

1996-02-01

Accuracy of a patient treatment portal marking device and computerized tomography (CT) simulation have been clinically tested. A CT-based simulator has been assembled based on a commercial CT scanner. This includes visualization software and a computer-controlled laser drawing device. This laser drawing device is used to transfer the setup, central axis, and/or radiation portals from the CT simulator to the patient for appropriate patient skin marking. A protocol for clinical testing is reported. Twenty-five prospectively, sequentially accessioned patients have been analyzed. The simulation process can be completed in an average time of 62 min. Under many cases, the treatment portals can be designed and the patient marked in one session. Mechanical accuracy of the system was found to be within +/- 1mm. The portal projection accuracy in clinical cases is observed to be better than +/- 1.2 mm. Operating costs are equivalent to the conventional simulation process it replaces. Computed tomography simulation is a clinical accurate substitute for conventional simulation when used with an appropriate patient marking system and digitally reconstructed radiographs. Personnel time spent in CT simulation is equivalent to time in conventional simulation.

Deep tissue massage: What are we talking about?

PubMed

Koren, Yogev; Kalichman, Leonid

2018-04-01

Massage is a common treatment in complementary and integrative medicine. Deep tissue massage, a form of therapeutic massage, has become more and more popular in recent years. Hence, the use of massage generally and deep tissue massage specifically, should be evaluated as any other modality of therapy to establish its efficacy and safety. To determine the definitions used for deep tissue massage in the scientific literature and to review the current scientific evidence for its efficacy and safety. Narrative review. There is no commonly accepted definition of deep tissue massage in the literature. The definition most frequently used is the intention of the therapist. We suggest separating the definitions of deep massage and deep tissue massage as follows: deep massage should be used to describe the intention of the therapist to treat deep tissue by using any form of massage and deep tissue massage should be used to describe a specific and independent method of massage therapy, utilizing the specific set of principles and techniques as defined by Riggs: "The understanding of the layers of the body, and the ability to work with tissue in these layers to relax, lengthen, and release holding patterns in the most effective and energy efficient way possible within the client's parameters of comfort". Heterogeneity of techniques and protocols used in published studies have made it difficult to draw any clear conclusions. Favorable outcomes may result from deep tissue massage in pain populations and patients with decreased range of motion. In addition, several rare serious adverse events were found related to deep tissue massage, probably as a result of the forceful application of massage therapy. Future research of deep tissue massage should be based on a common definition, classification system and the use of common comparators as controls. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automated drafting system uses computer techniques

NASA Technical Reports Server (NTRS)

Millenson, D. H.

1966-01-01

Automated drafting system produces schematic and block diagrams from the design engineers freehand sketches. This system codes conventional drafting symbols and their coordinate locations on standard size drawings for entry on tapes that are used to drive a high speed photocomposition machine.

Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

PubMed

Gopakumar, G; Hari Babu, K; Mishra, Deepak; Gorthi, Sai Siva; Sai Subrahmanyam, Gorthi R K

2017-01-01

Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing process. Several neural network architectures were designed to provide human expertise to machines. In this paper, we explore and propose the feasibility of using deep-learning networks for cytopathologic analysis by performing the classification of three important unlabeled, unstained leukemia cell lines (K562, MOLT, and HL60). The cell images used in the classification are captured using a low-cost, high-throughput cell imaging technique: microfluidics-based imaging flow cytometry. We demonstrate that without any conventional fine segmentation followed by explicit feature extraction, the proposed deep-learning algorithms effectively classify the coarsely localized cell lines. We show that the designed deep belief network as well as the deeply pretrained convolutional neural network outperform the conventionally used decision systems and are important in the medical domain, where the availability of labeled data is limited for training. We hope that our work enables the development of a clinically significant high-throughput microfluidic microscopy-based tool for disease screening/triaging, especially in resource-limited settings.

A magnetic resonance imaging investigation of the transversus abdominis muscle during drawing-in of the abdominal wall in elite Australian Football League players with and without low back pain.

PubMed

Hides, Julie A; Boughen, Carly L; Stanton, Warren R; Strudwick, Mark W; Wilson, Stephen J

2010-01-01

Single-blinded quasi-experimental study. To investigate the ability of elite football players with and without low back pain (LBP) to voluntarily draw-in the abdominal wall. While there has been considerable debate regarding the contribution of the transversus abdominis (TrA) muscle to control the lumbar spine and pelvis, there is evidence that retraining motor control of the deep trunk muscles is commensurate with decreases in LBP. Magnetic resonance imaging (MRI) has been used to assess the TrA muscle during the draw-in maneuver, with the contraction of the TrA muscle reducing the circumference of the trunk. Impairments in performance of the draw-in maneuver have been shown in people with LBP. Forty-three elite players from a team in the Australian Football League were allocated to 3 groups: those with "no LBP," "a history of LBP but no current LBP," or "current LBP." MRI was used to image the cross-sectional area (CSA) of the trunk at the level of the L3-4 disc at the start and end of the draw-in maneuver. There was a significant decrease in the CSA of the trunk with the performance of the draw-in maneuver (P<.001). Subjects in the "no LBP" group were better able to "draw-in" the abdominal wall than subjects with current LBP (P = .015). This study provides evidence of an altered ability to draw-in the abdominal wall in footballers with current LBP. Retraining contraction of the TrA muscle may constitute one part of an exercise-therapy approach for athletes with current LBP.

A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.

PubMed

Tuikkala, Johannes; Vähämaa, Heidi; Salmela, Pekka; Nevalainen, Olli S; Aittokallio, Tero

2012-03-26

Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.

Biochips: non-conventional strategies for biosensing elements immobilization.

PubMed

Marquette, Christophe A; Corgier, Benjamin P; Heyries, Kevin A; Blum, Loic J

2008-01-01

The present article draws a general picture of non-conventional methods for biomolecules immobilization. The technologies presented are based either on original solid supports or on innovative immobilization processes. Polydimethylsiloxane elastomer will be presented as a popular immobilization support within the biochip developer community. Electro-addressing of biomolecules at the surface of conducting biochips will appear to be an interesting alternative to immobilization processes based on surface functionalization. Finally, bead-assisted biomolecules immobilization will be presented as an open field of research for biochip developments.

A proposed draft protocol for the European Convention on Biomedicine relating to research on the human embryo and fetus.

PubMed

Byk, J C

1997-02-01

The objective of this paper is to stimulate academic debate on embryo and fetal research from the perspective of the drafting of a protocol to the European Convention on Biomedicine. The Steering Committee on Bioethics of the Council of Europe was mandated to draw up such a protocol and for this purpose organised an important symposium on reproductive technologies and embryo research, in Strasbourg from the 16th to the 18th of December 1996.

The effect of cushion-ram pulsation on hot stamping

NASA Astrophysics Data System (ADS)

Landgrebe, Dirk; Rautenstrauch, Anja; Kunke, Andreas; Polster, Stefan; Kriechenbauer, Sebastian; Mauermann, Reinhard

2016-10-01

Hot stamping is an important technology for manufacturing high-strength components. This technology offers the possibility to achieve significant weight reductions. In this study, cushion-ram pulsation (CRP), a new technology for hot stamping on servo-screw presses, was investigated and applied for hot stamping. Compared to a conventional process, the tests yielded a significantly higher drawing depth. In this paper, the CRP technology and the first test results with hot stamping were described in comparison to the conventional process.

The extraction of motion-onset VEP BCI features based on deep learning and compressed sensing.

PubMed

Ma, Teng; Li, Hui; Yang, Hao; Lv, Xulin; Li, Peiyang; Liu, Tiejun; Yao, Dezhong; Xu, Peng

2017-01-01

Motion-onset visual evoked potentials (mVEP) can provide a softer stimulus with reduced fatigue, and it has potential applications for brain computer interface(BCI)systems. However, the mVEP waveform is seriously masked in the strong background EEG activities, and an effective approach is needed to extract the corresponding mVEP features to perform task recognition for BCI control. In the current study, we combine deep learning with compressed sensing to mine discriminative mVEP information to improve the mVEP BCI performance. The deep learning and compressed sensing approach can generate the multi-modality features which can effectively improve the BCI performance with approximately 3.5% accuracy incensement over all 11 subjects and is more effective for those subjects with relatively poor performance when using the conventional features. Compared with the conventional amplitude-based mVEP feature extraction approach, the deep learning and compressed sensing approach has a higher classification accuracy and is more effective for subjects with relatively poor performance. According to the results, the deep learning and compressed sensing approach is more effective for extracting the mVEP feature to construct the corresponding BCI system, and the proposed feature extraction framework is easy to extend to other types of BCIs, such as motor imagery (MI), steady-state visual evoked potential (SSVEP)and P300. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Spatial Visualization by Isometric View

ERIC Educational Resources Information Center

Yue, Jianping

2007-01-01

Spatial visualization is a fundamental skill in technical graphics and engineering designs. From conventional multiview drawing to modern solid modeling using computer-aided design, visualization skills have always been essential for representing three-dimensional objects and assemblies. Researchers have developed various types of tests to measure…

But How Do We Learn? Talking to Vietnamese Children about How They Learn in and out of School

ERIC Educational Resources Information Center

Phelps, Renata; Nhung, Ha Thi Tuyet; Graham, Anne; Geeves, Richard

2012-01-01

Vietnam is currently striving to introduce more child-centred approaches to pedagogy. From a Western perspective, child-centred education requires teachers to perceive children as capable, active partners in learning and to develop deep understandings of their students, including the variety of ways in which they learn. This paper draws from a…

Lifelong Learning Theory and Pre-Service Teachers' Development of Knowledge and Dispositions to Work with Australian Aboriginal Students

ERIC Educational Resources Information Center

Bennet, Maria; Moriarty, Beverley

2016-01-01

This article draws on previous research by the authors and others as well as lifelong learning theory to argue the case for providing pre-service teachers with deep and meaningful experiences over time that help them to build their personal capacity for developing knowledge and dispositions to work with Australian Aboriginal students, their…

Policy Critics and Policy Survivors: Who Are They and How Do They Contribute to a Department Policy Role Typology?

ERIC Educational Resources Information Center

Golding, Jennie

2017-01-01

This paper considers the policy "roles" adopted by teachers enacting policy in a department. It draws on a longitudinal study of two secondary mathematics departments endeavouring to make deep change aligned with a demanding curriculum policy. The study validates aspects of an existing typology, demonstrates the existence of a variety of…

Including Families and Communities in Urban Education. Issues in the Research, Theory, Policy, and Practice of Urban Education

ERIC Educational Resources Information Center

Hands, Catherine, Ed.; Hubbard, Lea, Ed.

2011-01-01

The work of school, family and community partnerships is complex and messy and demands a thoughtful and deep investigation. Currently, parent and community involvement does not draw on school reform and educational change literature and conversely the school change literature often ignores the crucial role that communities play in educational…

Embedding Learning How to Learn in School Policy: The Challenge for Leadership

ERIC Educational Resources Information Center

Swaffield, Sue; MacBeath, John

2006-01-01

Achieving lasting and deep-seated change in schools through the embedding of a new set of practices with associated values is a familiar goal. This paper draws upon interviews with school coordinators and head teachers participating in the Learning How to Learn Project to explore the nature of embedding and the related challenges for leadership.…

Social Capital, Team Efficacy and Team Potency: The Mediating Role of Team Learning Behaviors

ERIC Educational Resources Information Center

van Emmerik, Hetty; Jawahar, I. M.; Schreurs, Bert; de Cuyper, Nele

2011-01-01

Purpose: Drawing on social capital theory and self-identification theory, this study aims to examine the associations of two indicators of social capital, personal networks and deep-level similarity, with team capability measures of team efficacy and team potency. The central focus of the study is to be the hypothesized mediating role of team…

"Anti-American Studies" in the Deep South: Dissenting Rhetorics, the Practice of Democracy, and Academic Freedom in Wartime Universities

ERIC Educational Resources Information Center

Powers, M. Karen; Chaput, Catherine

2007-01-01

Using Frederic Jameson, we outline concentric circles of the political unconscious structuring debates about academic freedom at the national and state levels. By drawing parallels between the World War I university and the contemporary university, we suggest that such circles function historically, always bearing traces of an earlier time. To…

Making Hope and History Rhyme: Reflections on Popular Education and Leadership Following a Visit to Highlander

ERIC Educational Resources Information Center

Connolly, Bríd; Finnegan, Fergal

2016-01-01

This article draws on our backgrounds as adult educators in Ireland and our experience at Highlander in 2014. We review our development as critical educators, exposed to deep inequalities in Irish society. We explore role of popular education in fostering social change, beginning with the commitment to equality and freedom, whereby, we produce…

Deep listening: towards an imaginative reframing of health and well-being practices in international development

PubMed Central

Pavlicevic, Mercédès; Impey, Angela

2014-01-01

This paper challenges the “intervention-as-solution” approach to health and well-being as commonly practised in the international development sector, and draws on the disciplinary intersections between Community Music Therapy and ethnomusicology in seeking a more negotiated and situationally apposite framework for health engagement. Drawing inspiration from music-based health applications in conflict or post-conflict environments in particular, and focusing on case studies from Lebanon and South Sudan respectively, the paper argues for a re-imagined international development health and well-being framework based on the concept of deep listening. Defined by composer Pauline Oliveros as listening which “digs below the surface of what is heard … unlocking layer after layer of imagination, meaning, and memory down to the cellular level of human experience” (Oliveros, 2005), the paper explores the methodological applications of such a dialogic, discursive approach with reference to a range of related listening stances – cultural, social and therapeutic. In so doing, it explores opportunities for multi-levelled and culturally inclusive health and well-being practices relevant to different localities in the world and aimed at the re-integration of self, place and community. PMID:25729413

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.

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.

Finite Element Modeling of Dieless Tube Drawing of Strain Rate Sensitive Material with Coupled Thermo-Mechanical Analysis

NASA Astrophysics Data System (ADS)

Furushima, Tsuyoshi; Sakai, Takashi; Manabe, Ken-ichi

2004-06-01

Dieless drawing is a unique deformation process without conventional dies, which can achieve a great reduction of wire and tube metals in single pass by means of local heating and cooling approach. In this study, for microtube forming, the dieless drawing process applying superplastic behavior was analyzed by finite element method (FEM) in order to clarify the effect of dieless tube drawing conditions such as tensile speed, moving speed of heating and cooling system, and material properties on deformation behavior of the tube. In the calculation, the material properties were dealt in a special subroutine, whose constitutive equation was defined as σ = Kɛnɛ˙m, and was linked to the solver. A coupled thermo-mechanical analysis was performed for the dieless tube drawing using the FEM. In the thermal analysis of dieless tube drawing, heat transfer was introduced to calculate the heat flux between heating coil and tube surface, and heat conduction in a tube. The influence of dieless tube drawing conditions on deformation behavior was clarified. As a result, for the strain rate sensitive material, the maximum reduction of area and the minimum outer diameter in single pass attain to 90.9% and 2.56mm, respectively. From the result, it is concluded that the dieless tube drawing is essential to produce an extrafine microtube by reason of keeping cylindrical tube diameter ratio constant with extremely high reduction.

The effect of deep frying or conventional oven cooking on inactivation of Shiga toxin-producing cells of Escherichia coli (STEC) in meatballs

USDA-ARS?s Scientific Manuscript database

We investigated the effects deep frying or oven cooking on inactivation of Shiga toxin-producing cells of Escherichia coli (STEC) in meatballs. A finely-ground veal and/or a beef-pork-veal mixture were inoculated (ca. 7.0 log CFU/g) with an eight-strain, genetically-marked cocktail of rifampicin-res...

Effects of epitaxial structure and processing on electrical characteristics of InAs-based nBn infrared detectors

NASA Astrophysics Data System (ADS)

Du, X.; Savich, G. R.; Marozas, B. T.; Wicks, G. W.

2017-02-01

The conventional processing of the III-V nBn photodetectors defines mesa devices by etching the contact n-layer and stopping immediately above the barrier, i.e., a shallow etch. This processing enables great suppression of surface leakage currents without having to explore surface passivation techniques. However, devices that are made with this processing scheme are subject to lateral diffusion currents. To address the lateral diffusion current, we compare the effects of different processing approaches and epitaxial structures of nBn detectors. The conventional solution for eliminating lateral diffusion current, a deep etch through the barrier and the absorber, creates increased dark currents and an increased device failure rate. To avoid deep etch processing, a new device structure is proposed, the inverted-nBn structure. By comparing with the conventional nBn structure, the results show that the lateral diffusion current is effectively eliminated in the inverted-nBn structure without elevating the dark currents.

Determination of acrylamide in Thai-conventional snacks from Nong Mon market, Chonburi using GC-MS technique.

PubMed

Komthong, P; Suriyaphan, O; Charoenpanich, J

2012-01-01

Acrylamide in Thai-conventional snacks was analysed by GC/MS with a linear response ranged of 5-50 µg and r² > 0.99. The limit of detection (s/n = 3) and limit of quantification (s/n = 10) were 4 and 15 µg kg⁻¹, respectively, and RSD < 2%. Acrylamide in 19 food samples ranged from <15 µg kg⁻¹ to 1.26 mg kg⁻¹ with highest concentrations in Kanom Jak. Moderate levels (150-500 µg kg⁻¹) were detected mostly in deep-fried products, especially sweet potato and taro crisps, Kanom Kai Hong, banana fritters, durian chips and spring rolls. Thai-conventional snacks possessed low concentrations (<150 µg kg⁻¹) including Khao Larm, Pa Tong Koo, sweet banana crisps and deep-fried Chinese wonton. Acrylamide was lowest (<15 µg kg⁻¹) in fish strips, rice crackers, Hoi Jor and fried fish balls. Dietary habits by 400 tourists indicate a daily intake of acrylamide <150 ng, well below a toxic dose.

Deep multi-scale convolutional neural network for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

Students as Designers of Semantic Web Applications

ERIC Educational Resources Information Center

Tracy, Fran; Jordan, Katy

2012-01-01

This paper draws upon the experience of an interdisciplinary research group in engaging undergraduate university students in the design and development of semantic web technologies. A flexible approach to participatory design challenged conventional distinctions between "designer" and "user" and allowed students to play a role…

Novel Approach for Prediction of Localized Necking in Case of Nonlinear Strain Paths

NASA Astrophysics Data System (ADS)

Drotleff, K.; Liewald, M.

2017-09-01

Rising customer expectations regarding design complexity and weight reduction of sheet metal components alongside with further reduced time to market implicate increased demand for process validation using numerical forming simulation. Formability prediction though often is still based on the forming limit diagram first presented in the 1960s. Despite many drawbacks in case of nonlinear strain paths and major advances in research in the recent years, the forming limit curve (FLC) is still one of the most commonly used criteria for assessing formability of sheet metal materials. Especially when forming complex part geometries nonlinear strain paths may occur, which cannot be predicted using the conventional FLC-Concept. In this paper a novel approach for calculation of FLCs for nonlinear strain paths is presented. Combining an interesting approach for prediction of FLC using tensile test data and IFU-FLC-Criterion a model for prediction of localized necking for nonlinear strain paths can be derived. Presented model is purely based on experimental tensile test data making it easy to calibrate for any given material. Resulting prediction of localized necking is validated using an experimental deep drawing specimen made of AA6014 material having a sheet thickness of 1.04 mm. The results are compared to IFU-FLC-Criterion based on data of pre-stretched Nakajima specimen.

Radio Science from an Optical Communications Signal

NASA Technical Reports Server (NTRS)

Moision, Bruce; Asmar, Sami; Oudrhiri, Kamal

2013-01-01

NASA is currently developing the capability to deploy deep space optical communications links. This creates the opportunity to utilize the optical link to obtain range, doppler, and signal intensity estimates. These may, in turn, be used to complement or extend the capabilities of current radio science. In this paper we illustrate the achievable precision in estimating range, doppler, and received signal intensity of an non-coherent optical link (the current state-of-the-art for a deep-space link). We provide a joint estimation algorithm with performance close to the bound. We draw comparisons to estimates based on a coherent radio frequency signal, illustrating that large gains in either precision or observation time are possible with an optical link.

The ‘French exception’: the right to continuous deep sedation at the end of life

PubMed Central

Horn, Ruth

2018-01-01

In 2016, a law came into force in France granting terminally ill patients the right to continuous deep sedation (CDS) until death. This right was proposed as an alternative to euthanasia and presented as the ‘French response’ to problems at the end of life. The law draws a distinction between CDS and euthanasia and other forms of sympton control at the end of life. France is the first country in the world to legislate on CDS. This short report describes the particular context and underlying social values that led to this piece of legislation, and explores its meaning in the wider French context. PMID:29056584

Neuro-impressions: interpreting the nature of human creativity

PubMed Central

Siler, Todd Lael

2012-01-01

Understanding the creative process is essential for realizing human potential. Over the past four decades, the author has explored this subject through his brain-inspired drawings, paintings, symbolic sculptures, and experimental art installations that present myriad impressions of human creativity. These impressionistic artworks interpret rather than illustrate the complexities of the creative process. They draw insights from empirical studies that correlate how human beings create, learn, remember, innovate, and communicate. In addition to offering fresh aesthetic experiences, this metaphorical art raises fundamental questions concerning the deep connections between the brain and its creations. The author describes his artworks as embodiments of everyday observations about the neuropsychology of creativity, and its all-purpose applications for stimulating and accelerating innovation. PMID:23091455

Comparison of performance due to guided hyperlearning, unguided hyperlearning, and conventional learning in mathematics: an empirical study

NASA Astrophysics Data System (ADS)

Fathurrohman, Maman; Porter, Anne; Worthy, Annette L.

2014-07-01

In this paper, the use of guided hyperlearning, unguided hyperlearning, and conventional learning methods in mathematics are compared. The design of the research involved a quasi-experiment with a modified single-factor multiple treatment design comparing the three learning methods, guided hyperlearning, unguided hyperlearning, and conventional learning. The participants were from three first-year university classes, numbering 115 students in total. Each group received guided, unguided, or conventional learning methods in one of the three different topics, namely number systems, functions, and graphing. The students' academic performance differed according to the type of learning. Evaluation of the three methods revealed that only guided hyperlearning and conventional learning were appropriate methods for the psychomotor aspects of drawing in the graphing topic. There was no significant difference between the methods when learning the cognitive aspects involved in the number systems topic and the functions topic.

Cold pool organization and the merging of convective updrafts in a Large Eddy Simulation

NASA Astrophysics Data System (ADS)

Glenn, I. B.; Krueger, S. K.

2016-12-01

Cold pool organization is a process that accelerates the transition from shallow to deep cumulus convection, and leads to higher deep convective cloud top heights. The mechanism by which cold pool organization enhances convection remains not well understood, but the basic idea is that since precipitation evaporation and a low equivalent potential temperature in the mid-troposphere lead to strong cold pools, the net cold pool effect can be accounted for in a cumulus parameterization as a relationship involving those factors. Understanding the actual physical mechanism at work will help quantify the strength of the relationship between cold pools and enhanced deep convection. One proposed mechanism of enhancement is that cold pool organization leads to reduced distances between updrafts, creating a local environment more conducive to convection as updrafts entrain parcels of air recently detrained by their neighbors. We take this hypothesis one step further and propose that convective updrafts actually merge, not just exchange recently processed air. Because entrainment and detrainment around an updraft draws nearby air in or pushes it out, respectively, they act like dynamic flow sources and sinks, drawing each other in or pushing each other away. The acceleration is proportional to the inverse square of the distance between two updrafts, so a small reduction in distance can make a big difference in the rate of merging. We have shown in previous research how merging can be seen as collisions between different updraft air parcels using Lagrangian Parcel Trajectories (LPTs) released in a Large Eddy Simulation (LES) during a period with organized deep convection. Now we use a Eulerian frame of reference to examine the updraft merging process during the transition from shallow to organized deep convection. We use a case based on the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) for our LES. We directly measure the rate of entrainment and the properties of the entrained air for all convective updrafts in the simulation. We use a tracking algorithm to define merging between convective updrafts. We will show the rate of merging as the transition between shallow and deep convection occurs and the different distributions of entrainment rate and ultimate detrainment height of merged and non-merged updrafts.

Deep erosions of the palmar aspect of the navicular bone diagnosed by standing magnetic resonance imaging.

PubMed

Sherlock, C; Mair, T; Blunden, T

2008-11-01

Erosion of the palmar (flexor) aspect of the navicular bone is difficult to diagnose with conventional imaging techniques. To review the clinical, magnetic resonance (MR) and pathological features of deep erosions of the palmar aspect of the navicular bone. Cases of deep erosions of the palmar aspect of the navicular bone, diagnosed by standing low field MR imaging, were selected. Clinical details, results of diagnostic procedures, MR features and pathological findings were reviewed. Deep erosions of the palmar aspect of the navicular bone were diagnosed in 16 mature horses, 6 of which were bilaterally lame. Sudden onset of lameness was recorded in 63%. Radiography prior to MR imaging showed equivocal changes in 7 horses. The MR features consisted of focal areas of intermediate or high signal intensity on T1-, T2*- and T2-weighted images and STIR images affecting the dorsal aspect of the deep digital flexor tendon, the fibrocartilage of the palmar aspect, subchondral compact bone and medulla of the navicular bone. On follow-up, 7/16 horses (44%) had been subjected to euthanasia and only one was being worked at its previous level. Erosions of the palmar aspect of the navicular bone were confirmed post mortem in 2 horses. Histologically, the lesions were characterised by localised degeneration of fibrocartilage with underlying focal osteonecrosis and fibroplasia. The adjacent deep digital flexor tendon showed fibril formation and fibrocartilaginous metaplasia. Deep erosions of the palmar aspect of the navicular bone are more easily diagnosed by standing low field MR imaging than by conventional radiography. The lesions involve degeneration of the palmar fibrocartilage with underlying osteonecrosis and fibroplasia affecting the subchondral compact bone and medulla, and carry a poor prognosis for return to performance. Diagnosis of shallow erosive lesions of the palmar fibrocartilage may allow therapeutic intervention earlier in the disease process, thereby preventing progression to deep erosive lesions.

Constructing Stories in Kindergarten: Children's Knowledge of Genre

ERIC Educational Resources Information Center

Loizou, Eleni; Kyriakides, Elena; Hadjicharalambous, Maria

2011-01-01

This study investigated the ability of 23 kindergarten children to construct stories drawing upon genre conventions in order to differentiate simple narrative stories, a familiar and often-visited genre in the kindergarten literacy classroom, and humorous stories, familiar to the children's literacy experiences mostly outside official literacy…

37 CFR 1.84 - Standards for drawings.

Code of Federal Regulations, 2010 CFR

2010-07-01

... sheet. However, the relationship between the different parts must be clear and unambiguous. (3... hatching of juxtaposed different elements must be angled in a different way. In the case of large areas... hatched. Different types of hatching should have different conventional meanings as regards the nature of...

37 CFR 1.84 - Standards for drawings.

Code of Federal Regulations, 2011 CFR

2011-07-01

... sheet. However, the relationship between the different parts must be clear and unambiguous. (3... hatching of juxtaposed different elements must be angled in a different way. In the case of large areas... hatched. Different types of hatching should have different conventional meanings as regards the nature of...

Data Development of Detail Standards For Outside Machinery Operations

DTIC Science & Technology

1985-01-01

the preparation of food . oven operates differently than the conventional free heat The convection oven forces the heat to circulate by the For the...that the product at the various stages meets quality and technical workmanship established by drawings, Manufact - uring Standard Processes, as well as

Critical Relationships between Teachers and Learners of School Mathematics

ERIC Educational Resources Information Center

Wright, Pete

2017-01-01

This article draws on critical theories and perspectives on mathematics education to explain the tendency of mathematics teaching worldwide to remain focused on developing procedural understanding, despite repeated calls from the mathematics education community for a more relevant and engaging curriculum. It highlights how conventional approaches…

Academetron, Automaton, Phantom: Uncanny Digital Pedagogies

ERIC Educational Resources Information Center

Bayne, Sian

2010-01-01

This paper explores the possibility of an uncanny digital pedagogy. Drawing on theories of the uncanny from psychoanalysis, cultural studies and educational philosophy, it considers how being online defamiliarises teaching, asking us to question and consider anew established academic practices and conventions. It touches on recent thinking on…

How Secondary History Teachers Use and Think about Museums: Current Practices and Untapped Promise for Promoting Historical Understanding

ERIC Educational Resources Information Center

Marcus, Alan S.; Levine, Thomas H.; Grenier, Robin S.

2012-01-01

Museums have great potential to help secondary students develop a deep understanding of the past; however, we know little about what history teachers actually do or want to accomplish when they utilize museums. In this study, the authors draw on questionnaire and interview data from 94 secondary history teachers in Connecticut in an effort to…

'Not-Being-At-Home': Subject, Freedom and Transcending in Heideggerian Educational Philosophy

ERIC Educational Resources Information Center

d'Agnese, Vasco

2018-01-01

In my paper, by drawing on the writings Heidegger developed in the late 1920s, I wish to display what we may refer to as the thorough educational nature of Heideggerian reflection. It is my argument that the analysis of Dasein we find in the early Heidegger displays an extraordinary deep and dense reflection on selfhood and subjectivity, a…

Exploring the Use of Supplemental Instruction: Supporting Deep Understanding and Higher-Order Thinking in Chemistry

ERIC Educational Resources Information Center

Paideya, V.; Sookrajh, R.

2010-01-01

Many under-prepared university students do not know how to study (Martin and Arendale 1993) because they have not yet developed the abstract reasoning skills that allow them to learn new ideas simply by reading a text or listening to a lecture. This article draws from selected findings from a PhD study currently being undertaken at a university in…

A Critical Co-Constructed Autoethnography of a Gendered Cross-Cultural Mentoring between Two Early Career Latin@ Scholars Working in the Deep South

ERIC Educational Resources Information Center

Suriel, Regina L.; Martinez, James; Evans-Winters, Venus

2018-01-01

Multicultural mentoring has been suggested to support Latin@ faculty success in their careers, yet current literature on effective mentorships of Latin@ faculty is limited. This critical co-constructed autoethnography draws on critical race theory (CRT) and latin@ critical race theory (LatCrit) frameworks to highlight the lived experiences and key…

Slime mould biotechnology

NASA Astrophysics Data System (ADS)

Mayne, Richard

2015-03-01

Slime mould computing is an inherently multi-disciplinary subfield of unconventional computing that draws upon aspects of not only theoretical computer science and electronics, but also the natural sciences. This chapter focuses on the biology of slime moulds and expounds the viewpoint that a deep, intuitive understanding of slime mould life processes is a fundamental requirement for understanding -- and, hence, harnessing -- the incredible behaviour patterns we may characterise as "computation"...

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

PubMed

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

2017-04-18

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

Data augmentation-assisted deep learning of hand-drawn partially colored sketches for visual search

PubMed Central

Muhammad, Khan; Baik, Sung Wook

2017-01-01

In recent years, image databases are growing at exponential rates, making their management, indexing, and retrieval, very challenging. Typical image retrieval systems rely on sample images as queries. However, in the absence of sample query images, hand-drawn sketches are also used. The recent adoption of touch screen input devices makes it very convenient to quickly draw shaded sketches of objects to be used for querying image databases. This paper presents a mechanism to provide access to visual information based on users’ hand-drawn partially colored sketches using touch screen devices. A key challenge for sketch-based image retrieval systems is to cope with the inherent ambiguity in sketches due to the lack of colors, textures, shading, and drawing imperfections. To cope with these issues, we propose to fine-tune a deep convolutional neural network (CNN) using augmented dataset to extract features from partially colored hand-drawn sketches for query specification in a sketch-based image retrieval framework. The large augmented dataset contains natural images, edge maps, hand-drawn sketches, de-colorized, and de-texturized images which allow CNN to effectively model visual contents presented to it in a variety of forms. The deep features extracted from CNN allow retrieval of images using both sketches and full color images as queries. We also evaluated the role of partial coloring or shading in sketches to improve the retrieval performance. The proposed method is tested on two large datasets for sketch recognition and sketch-based image retrieval and achieved better classification and retrieval performance than many existing methods. PMID:28859140

Next Step Toward Widespread Residential Deep Energy Retrofits

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

McIlvaine, J.; Saunders, S.; Bordelon, E.

The complexity of deep energy retrofits warrants additional training to successfully manage multiple improvements that will change whole house air, heat, and moisture flow dynamics. The home performance contracting industry has responded to these challenges by aggregating skilled labor for assessment of and implementation under one umbrella. Two emerging business models are profiled that seek to resolve many of the challenges, weaknesses, opportunities, and threats described for the conventional business models.

A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization

PubMed Central

2012-01-01

Background Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. Methods We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. Results The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. Conclusions By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications. PMID:22448851

Relationship between clock and star drawing and the degree of hepatic encephalopathy.

PubMed

Edwin, Natasha; Peter, John Victor; John, George; Eapen, C E; Graham, Petra L

2011-09-01

PURPOSE OF THE STUDY Current hepatic encephalopathy grading tools are limited because of complexity or subjectivity. The degree of constructional apraxia could serve as a simple, objective and reproducible tool to grade encephalopathy. STUDY DESIGN In this cross-sectional study of patients with chronic liver disease, the degree of constructional apraxia was judged by their ability to copy a star and clock face and compared with conventional encephalopathy grading by the West Haven Criteria (WHC) and the Porto Systemic Encephalopathy Index (PSEI). Three blinded observers independently graded the figures. Sensitivity, specificity and positive predictive value (PPV) of clock and star scores (score 0 implying no encephalopathy and >0 hepatic encephalopathy) were assessed against conventional scoring systems (WHC grade >0 or PSEI ≥0.33 indicating encephalopathy). Mosaic and box plots were generated to assess if the degree of constructional apraxia correlated with the severity of encephalopathy. RESULTS 71 patients were studied between October 2008 and July 2009; 11 (15.4%) had WHC grade 0, 32 (45%) grade 1, and 28 (39.4%) grades 2 and 3 encephalopathy. The sensitivity, specificity and PPV of the clock drawing for the diagnosis of encephalopathy was 85%, 80%, and 96%, respectively, and 77%, 70%, and 94%, respectively, for the star drawing. Box plots and intervals on mean PSEI showed an increasing relationship between clock/star scores and PSEI. There was substantial agreement between WHC and clock (weighted κ 0.61) and star scores (weighted κ 0.71). Inter-observer reliability was at least 0.70 for star and at least 0.79 for the clock score. CONCLUSION Clock and star drawing may serve as reproducible, inexpensive bedside tools for diagnosing and grading the severity of hepatic encephalopathy.

A proposed draft protocol for the European Convention on Biomedicine relating to research on the human embryo and fetus.

PubMed Central

Byk, J C

1997-01-01

The objective of this paper is to stimulate academic debate on embryo and fetal research from the perspective of the drafting of a protocol to the European Convention on Biomedicine. The Steering Committee on Bioethics of the Council of Europe was mandated to draw up such a protocol and for this purpose organised an important symposium on reproductive technologies and embryo research, in Strasbourg from the 16th to the 18th of December 1996. PMID:9055160

Prediction of fatigue-related driver performance from EEG data by deep Riemannian model.

PubMed

Hajinoroozi, Mehdi; Jianqiu Zhang; Yufei Huang

2017-07-01

Prediction of the drivers' drowsy and alert states is important for safety purposes. The prediction of drivers' drowsy and alert states from electroencephalography (EEG) using shallow and deep Riemannian methods is presented. For shallow Riemannian methods, the minimum distance to Riemannian mean (mdm) and Log-Euclidian metric are investigated, where it is shown that Log-Euclidian metric outperforms the mdm algorithm. In addition the SPDNet, a deep Riemannian model, that takes the EEG covariance matrix as the input is investigated. It is shown that SPDNet outperforms all tested shallow and deep classification methods. Performance of SPDNet is 6.02% and 2.86% higher than the best performance by the conventional Euclidian classifiers and shallow Riemannian models, respectively.

Chemistry for Kids: What Do Chemists Do? A Program for Grades 1-3.

ERIC Educational Resources Information Center

Umland, Jean B.

1985-01-01

Proposes a simple solution to the problem of expressing graphically absolute configuration, racemic character, and relative configuration in molecules. As demonstrated by several examples, the proposed convention brings added clarity and simplicity to structural drawings and renders graphic displays of chiral molecules as explicit and information…

Restructuring a Master's Degree Dissertation as a Patchwork Text.

ERIC Educational Resources Information Center

Maisch, Maire

2003-01-01

Describes the introduction of the Patchwork Text format into the dissertation on a Master's degree in Social Work. Discusses the rationale for rethinking the conventional dissertation and the "patches" making up the revised dissertation format. Draws upon completed dissertations of two students on the program to illustrate how the characteristics…

Prevention of overweight and obesity in children and adolescents: Critical appraisal of the evidence base (in German)

USDA-ARS?s Scientific Manuscript database

Despite careful planning and implementation, overweight/obesity prevention interventions in children and adolescents typically show no, inconsistent or merely weak effects. Such programs usually aim at behavior changes, rarely also at environmental changes, that draw upon conventional wisdom regardi...

Building Alternative Agri-Food Networks: Certification, Embeddedness and Agri-Environmental Governance

ERIC Educational Resources Information Center

Higgins, Vaughan; Dibden, Jacqui; Cocklin, Chris

2008-01-01

This paper examines the role of certification in alternative agri-food networks (AAFNs), which are "in the process" of building markets for their produce outside conventional supply chains. Drawing upon recent writing on "embeddedness", we argue that certification provides an important focus for exploring the relationship and…

Rethinking the Idea/Ideal of Pedagogical Control: Assemblages of De/Stabilisation

ERIC Educational Resources Information Center

Sandvik, Ninni

2012-01-01

Inspired by a Deleuzian focus on a-personal machineries, this discussion focuses on a challenge to conventional pedagogical relationships and presents the possibility to think about pedagogical control differently. The work of Deleuze also underpins the methodological approach. Drawing on an extract constructed from the author's doctoral project…

Women's Speech, Women's Strength?

ERIC Educational Resources Information Center

Coates, Jennifer

A discussion of women's oral discourse patterns focuses on the uses made of minimal responses, hedges, and tag questions. The analysis draws on transcriptions of conversations among a group of women friends over a period of months. It is proposed that the conventional treatment of these forms as "weak" is inappropriate in all-female…

Turn the Wheel: Integral School Counseling for Male Adolescents.

ERIC Educational Resources Information Center

Forbes, David

2003-01-01

This article formulates an overarching, inclusive model of integral counseling that enables school counselors to help male adolescents challenge the norm of conventional masculinity. The model draws from 3 areas: transpersonal counseling, holistic education, and mindful social action. The aim is to move the students' level of self-development and…

Of Organic Farmers and "Good Farmers": Changing Habitus in Rural England

ERIC Educational Resources Information Center

Sutherland, Lee-Ann; Darnhofer, Ika

2012-01-01

In recent years, numerous studies have identified the importance of cultural constructions of "good farming" to farming practice. In this paper, we develop the "good farming" construct through an empirical study of organic and conventional farmers, focussing on how change occurs. Drawing on Bourdieu's concepts of cultural…

Reclaiming "Sense" from "Cents" in Accounting Education

ERIC Educational Resources Information Center

Dellaportas, Steven

2015-01-01

This essay adopts an interpretive methodology of relevant literature to explore the limitations of accounting education when it is taught purely as a technical practice. The essay proceeds from the assumption that conventional accounting education is captured by a positivistic neo-classical model of decision-making that draws on economic rationale…

Surrealistic and under 7

ERIC Educational Resources Information Center

Sutley, Jane

2012-01-01

Long before children enter school, it is their imagination that informs their play. Their drawing, too, relies heavily on their natural, unfettered ability to portray both the world around them and their own experiences within that world, without the conventional boundaries between "real" and "imaginary." Surrealism then, is an art movement and…

Art in Paleontology: The Example of Manfred Reichel

NASA Astrophysics Data System (ADS)

Leria, M.; Ferràndez-Cañadell, C.

2013-12-01

Scientific illustration is a fundamental tool to communicate information through a form of nonverbal language with its own grammar and syntax. Contrary to the idea of scientific illustration as a simple scientific analytic tool, without a personal identity, we present an example where rigor is intrinsically linked to a high sensibility, and a deep knowledge of drawing that brings as a result a beautiful piece of art. In 1918 Manfred Reichel left his studies in Fine Arts (École des Beaux-Arts in Geneva, Switzerland) and began his career as a scientist, obtaining a degree in biological sciences from University of Neuchâtel. Humble by nature, he assumed he would not become a great artist, as he would tell his students. His point of view in micropaleontology, focused in foraminifera, protozoa with a complex shell, had an impact on his students and other specialists. His background in art benefited him in the research of the more complex foraminiferal structures, which he clarified by means of rich illustrations, with a high degree of beauty, inspired by the French naturalists. His research on the study of the shell of some foraminiferal groups, such as alveolinids, orbitolinids and fusulinids, produced some superb illustrations, which display their complex structure in such a comprehensible way that they could not be improved by modern techniques and are still used today. Reichel started teaching micropaleontology in 1935 at the Geologisch-Paläontologisches Institut of the University of Basel. As a professor of paleontology, he trained his students in drawing to enhance the level of description of their illustrations. When the interpretation turned out to be too difficult, he would encourage them to reconstruct the architecture of foraminifera, creating a 3D model, in order to visualize how the drawing should be. Due to his interest on ornithology and the mechanics of flight, he also created pictorial illustrations of birds, published in magazines and books. He used this ability to elaborate vivid restorations of pterosaurus and extinct birds, such as Archaeopteryx. This study is based on a revision of the scientific papers by Manfred Reichel, along with some of the work done by his students related to the foraminiferal research. In addition, the examination of the collection of Reichel's drawings and casts held by the Natural History Museum in Basel, as well as interviews with his family and students were highly helpful to understand how he applied his artistic skills to teaching and research. From this study, we can assess the significance of visual education on micropaleontologists, arguing that classical convention in drawing is still and irreplaceable tool in natural sciences. Illustration of the test, scale 1:50, of Praealveolina cretacea tenuis. (Manfred Reichel, 1937. Étude sur les Alvéolines, Mémoires de la Société paléontologique Suisse, Vol. LIX, plate XI, fig. IIa)

Novel concept for measurement of global blank draw-in when deep drawing outer skin automotive components

NASA Astrophysics Data System (ADS)

Kraft, M.; Bürgel, U.

2017-09-01

Modern press shops in the automotive industry have to deal with many challenges. One challenge is to achieve a consistent part quality. In order to reach this target, modern press systems and tools are equipped with several types of sensors. For example, there are sensors to measure characteristic values of blanks or sensors to measure the temperature in the tools. Often several sensors are used simultaneously. A significant parameter for determining the quality of draw panels is the draw-in amount. Previously, it was only possible to measure selective points of the draw-in amount due to sensors in the tools. All the known sensors have disadvantages, for example, they are exposed to wearing or susceptible to contamination. In this paper, a sensor system will be introduced that allows the measurement of the global draw-in amount of a drawn panel. Here, the draw-in amount is not measured in the draw die, it is measured during the transportation of the part to the following operation. Within the short transport time the part can be fully covered by an optical system. This leads to a multitude of advantages compared with previously known systems. For example, it is no longer necessary to equip every tool with sensor technology to measure the draw-in amount. Now it is sufficient to equip every press line with a single system to measure the draw-in. This fact leads not only to lower costs, it also simplifies the tool design. In addition, the risk of contamination of the sensor system is greatly reduced. The paper will also introduce an actuator that was built to locally vary the blankholder forces for a sheet metal forming process. Furthermore, an FEM model is presented that allows the determination of the effective range of these actuators. With the knowledge from the FEM simulation, an approach for an open loop control is presented. With this approach, the press shops at Opel are developing a control procedure in order to influence the stamping process positively.

The Next Step Toward Widespread Residential Deep Energy Retrofits

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

McIlvaine, J.; Martin, E.; Saunders, S.

The complexity of deep energy retrofits warrants additional training to successfully manage multiple improvements that will change whole house air, heat, and moisture flow dynamics. The home performance contracting industry has responded to these challenges by aggregating skilled labor for assessment of and implementation under one umbrella. Two emerging business models are profiled that seek to resolve many of the challenges, weaknesses, opportunities, and threats described for the conventional business models.

6. INTERIOR VIEW OF BASEMENT OF CA. 1948 FACTORY ADDITION, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

6. INTERIOR VIEW OF BASEMENT OF CA. 1948 FACTORY ADDITION, WITH REINFORCED CONCRETE FRAME AND FLOOR OF REINFORCED CONCRETE TEE-BEAMS, LOOKING NORTH. AT LEFT IS DEEP DRAW, HEAVY PRESS MANUFACTURED BY E. W. BLISS CO., BROOKLYN, NEW YORK. PRESS #3-1/2 B, PATENTED BY E. W. BLISS CO., 1893. MANUFACTURERS PLATE INDICATES PRESS DATES FROM 1920. - Illinois Pure Aluminum Company, 109 Holmes Street, Lemont, Cook County, IL

Optimization of chemical compositions in low-carbon Al-killed enamel steel produced by ultra-fast continuous annealing

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

Dong, Futao, E-mail: dongft@sina.com; Du, Linxiu; Liu, Xianghua

2013-10-15

The influence of Mn,S and B contents on microstructural characteristics, mechanical properties and hydrogen trapping ability of low-carbon Al-killed enamel steel was investigated. The materials were produced and processed in a laboratory and the ultra-fast continuous annealing processing was performed using a continuous annealing simulator. It was found that increasing Mn,S contents in steel can improve its hydrogen trapping ability which is attributed by refined ferrite grains, more dispersed cementite and added MnS inclusions. Nevertheless, it deteriorates mechanical properties of steel sheet. Addition of trace boron results in both good mechanical properties and significantly improved hydrogen trapping ability. The boronmore » combined with nitrogen segregating at grain boundaries, cementite and MnS inclusions, provides higher amount of attractive hydrogen trapping sites and raises the activation energy for hydrogen desorption from them. - Highlights: • We study microstructures and properties in low-carbon Al-killed enamel steel. • Hydrogen diffusion coefficients are measured to reflect fish-scale resistance. • Manganese improves hydrogen trapping ability but decrease deep-drawing ability. • Boron improves both hydrogen trapping ability and deep-drawing ability. • Both excellent mechanical properties and fish-scale resistance can be matched.« less

Mechanical properties of Fe -10Ni -7Mn martensitic steel subjected to severe plastic deformation via cold rolling and wire drawing

NASA Astrophysics Data System (ADS)

Ghasemi-Nanesa, H.; Nili-Ahmadabadi, M.; Shirazi, H.

2010-07-01

Fe-Ni-Mn martensitic steels are one of the major groups of ultra-high strength steels that have good mechanical properties and ductility in as annealed condition but they suffer from severe inter-granular embitterment after aging. In this paper, the effect of heavy shaped cold rolling and wire drawing on the mechanical properties of Fe-Ni-Mn steel was investigated. This process could provide a large strain deformation in this alloy. The total strain was epsilon ~7. Aging behavior and tensile properties of Fe-10Ni-7Mn were studied after aging at 753 K. The results showed that the ultimate tensile strength and ductility after cold rolling, wire drawing and aging increased up to 2540 MPa and 7.1 %, respectively, while the conventional steels show a premature fracture stress of 830 MPa with about zero ductility after aging.

Applied photo interpretation for airbrush cartography

NASA Technical Reports Server (NTRS)

Inge, J. L.; Bridges, P. M.

1976-01-01

Lunar and planetary exploration has required the development of new techniques of cartographic portrayal. Conventional photo-interpretive methods employing size, shape, shadow, tone, pattern, and texture are applied to computer-processed satellite television images. Comparative judgements are affected by illumination, resolution, variations in surface coloration, and transmission or processing artifacts. The portrayal of tonal densities in a relief illustration is performed using a unique airbrush technique derived from hill-shading of contour maps. The control of tone and line quality is essential because the mid-gray to dark tone densities must be finalized prior to the addition of highlights to the drawing. This is done with an electric eraser until the drawing is completed. The drawing density is controlled with a reflectance-reading densitometer to meet certain density guidelines. The versatility of planetary photo-interpretive methods for airbrushed map portrayals is demonstrated by the application of these techniques to the synthesis of nonrelief data.

[Search for life in deep biospheres].

PubMed

Naganuma, Takeshi

2003-12-01

The life in deep biospheres bridges conventional biology and future exobiology. This review focuses the microbiological studies from the selected deep biospheres, i.e., deep-sea hydrothermal vents, sub-hydrothermal vents, terrestrial subsurface and a sub-glacier lake. The dark biospheres facilitate the emergence of organisms and communities dependent on chemolithoautotrophy, which are overwhelmed by photoautotrophy (photosynthesis) in the surface biospheres. The life at deep-sea hydrothermal vents owes much to chemolithoautotrophy based on the oxidation of sulfide emitted from the vents. It is likely that similarly active bodies such as the Jovian satellite Europa may have hydrothermal vents and associated biological communities. Anoxic or anaerobic condition is characteristic of deep subsurface biospheres. Subsurface microorganisms exploit available oxidants, or terminal electron acceptors (TEA), for anaerobic respiration. Sulfate, nitrate, iron (III) and CO2 are the representative TEAs in the deep subsurface. Below the 3000-4000 m-thick glacier on Antarctica, there have been >70 lakes with liquid water located. One of such sub-glacial lakes, Lake Vostok, is about to be drill-penetrated for microbiological studies. These deep biosphere "platforms" provide new knowledge about the diversity and potential of the Earth's life. The expertise obtained from the deep biosphere expeditions will facilitate the capability of exobiologial exploration.

The effect of elevated die temperature on deformation of deep drawn round metal cup

NASA Astrophysics Data System (ADS)

Basril, M. A. M.; Hafsyam, Y. M.; Azuddin, M.; Choudhury, I. A.

2017-06-01

One of the major considerations in the current deep drawing practice is the product quality. In this research, the effect of heating temperature on the drawability of the round metal cup has been investigated. Firstly, round metal cups of aluminium and mild steel were drawn from the blank diameters of 60 mm, 65 mm and 70 mm. The experiment conducted at room temperature first, then at 50°C and 100°C. The elongation of the major and minor strains along the cup profile after the process is measured and analysed. On the other hand, the defects from the experiment output and ABAQUS/CAE simulation are compared. The result from experiment shows that the highest major elongation is 11.64 mm and it is happened to a deep drawn aluminium round cup with LDR of 1.69 at temperature of 100°C. On the other hand, for deep drawn mild steel round cup, shows highest major elongation of 12.44 mm for a cup with LDR of 1.56 at 100°C. Both of these statements indicates that the higher temperature could improve the formability of the deep drawn parts besides reducing the probability of the defect to be happened.

Deep eutectic solvents as efficient solvent system for the extraction of κ-carrageenan from Kappaphycus alvarezii.

PubMed

Das, Arun Kumar; Sharma, Mukesh; Mondal, Dibyendu; Prasad, Kamalesh

2016-01-20

Three different deep eutectic solvents (DESs) prepared by the complexation of choline chloride with urea, ethylene glycol and glycerol along with their hydrated counterparts were used for the selective extraction of κ-carrageenan from Kappaphycus alvarezii. Upon comparison of the quality of the polysaccharide with the one obtained using water as extraction media as well as the one extracted using widely practiced conventional method, it was found that, the physicochemical as well as rheological properties of κ-carrageenan obtained using DESs as solvents was at par to the one obtained using conventional method and was superior in quality when compared to κ-carrageenan obtained using water as solvent. Considering the tedious nature of the extraction method employed in conventional extraction process, the DESs can be considered as suitable alternative solvents for the facile extraction of the polysaccharide directly from the seaweed. However, among the hydrated and non-hydrated DESs, the hydrated ones were found to be more effective in comparison to their non-hydrated counterparts. Copyright © 2015 Elsevier Ltd. All rights reserved.

Drawing method can improve musculoskeletal anatomy comprehension in medical faculty student.

PubMed

Joewono, Muliani; Karmaya, I Nyoman Mangku; Wirata, Gede; Yuliana; Widianti, I Gusti Ayu; Wardana, I Nyoman Gede

2018-03-01

The Chinese philosophy of Confucianism said "What I heard I forgot, what I see, I remember, what I do, I understand." During this time, most of the teaching and learning process relies on viewing and listening modalities only. As a result, much information does not last long in memory as well as the material understanding achieves became less deep. In studying anatomy science, drawing is one of effective important methods because it is an integration of ideas and knowledge of vision thereby increasing comprehension and learning motivation of college students. The purpose of this research is to know the musculoskeletal anatomy comprehension by drawing learning method in Medical Faculty student. This research uses observational analytic design with the cross-sectional design. Total sampling was done to the entire student of Physiotherapy Study Program in 2012, 2013, and 2014, Medical Faculty of Udayana University. The average value of musculoskeletal anatomy of the student in 2012, 2013, and 2014 sequentially are 31.67, 33.57, and 45.00, respectively. Normality test with Shapiro-Wilk and homogeneity with Levene's test showed normal results and homogeneous. One-way ANOVA test between groups showed a significant result that is 11.00 ( P <0.05). It is concluded that the drawing method can improve the musculoskeletal anatomy comprehension in Medical Faculty student.

[Obsessive-compulsive disorder, a new model of basal ganglia dysfunction? Elements from deep brain stimulation studies].

PubMed

Haynes, W I A; Millet, B; Mallet, L

2012-01-01

Deep brain stimulation was first developed for movement disorders but is now being offered as a therapeutic alternative in severe psychiatric disorders after the failure of conventional therapies. One of such pathologies is obsessive-compulsive disorder. This disorder which associates intrusive thoughts (obsessions) and repetitive irrepressible rituals (compulsions) is characterized by a dysfunction of a cortico-subcortical loop. After having reviewed the pathophysiological evidence to show why deep brain stimulation was an interesting path to take for severe and resistant cases of obsessive-compulsive disorder, we will present the results of the different clinical trials. Finally, we will provide possible mechanisms for the effects of deep brain stimulation in this pathology. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

The Changing Nature of Volunteering and the Cross-Border Mobility: Where Does Learning Come from?

ERIC Educational Resources Information Center

Pantea, Maria-Carmen

2013-01-01

This paper revisits the more conventional approaches of volunteering, by looking into the experiences of young people involved in long-term cross-border volunteering in Romania. Drawing on qualitative interviews with European Voluntary Service volunteers, the paper examines how this experience is intersecting their learning trajectories. The…

Conventional wisdoms of woody biomass utilization on federal public lands

Treesearch

Dennis R. Becker; Sarah M. McCaffrey; Dalia Abbas; Kathleen E. Halvorsen; Pamela Jakes; Cassandra. Moseley

2011-01-01

The appeal of biomass utilization grows as the need for wildfire risk reduction, economic development, and renewable energy generation becomes more pressing. However, uncertainty exists regarding the factors necessary to stimulate use. We draw on in-depth interviews with local industry, agency, community, and tribal representatives from 10 study sites on federal public...

Early Adopters: Playing New Literacies and Pretending New Technologies in Print-Centric Classrooms

ERIC Educational Resources Information Center

Wohlwend, Karen E.

2009-01-01

In this article, semiotic analysis of children's practices and designs with video game conventions considers how children use play and drawing as spatializing literacies that make room to import imagined technologies and user identities. Microanalysis of video data of classroom interactions collected during a three year ethnographic study of…

Appropriating Drama Pedagogy: Learning from the Local Practices in Hong Kong

ERIC Educational Resources Information Center

Tam, Po-chi

2010-01-01

This paper aims at describing and explaining how drama pedagogy is appropriated in Chinese language classrooms in Hong Kong. Drawing on the theories of dialogue and appropriation of Mikhail Bakhtin, the research shows that the dialogicality of drama in Hong Kong's classrooms is conditional, and therefore deviant from the conventional as…

"Measuring up"? Assessment and Students with Disabilities in the Modern University

ERIC Educational Resources Information Center

Bessant, Judith

2012-01-01

In this article, I ask how university students with disabilities negotiate with staff arrangements for alternative assessment practices. I draw on three case studies using a personal pronoun perspective to challenge the conventional view that educational policy and teaching practice are forms of rational action. I demonstrate how the lives of…

Telecollaboration in the Secondary Language Classroom: Case Study of Adolescent Interaction and Pedagogical Integration

ERIC Educational Resources Information Center

Ware, Paige; Kessler, Greg

2016-01-01

This study builds on research examining the in-school technology practices of adolescent language learners by exploring the patterns of classroom literacy practices that emerge when a telecollaborative project is introduced into a conventional secondary language classroom. We draw on the conceptual frameworks and discourse analytical tools…

Deep-sea mining: potential environmental, legal, economic, and societal implications - an interdisciplinary research.

PubMed

Koschinsky, Andrea; Heinrich, Luise; Boehnke, Klaus; Cohrs, J Christopher; Markus, Till; Shani, Maor; Singh, Pradeep; Stegen, Karen Smith; Werner, Welf

2018-06-19

Deep-sea mining refers to the retrieval of marine mineral resources such as manganese nodules, ferromanganese crusts and seafloor massive sulfide deposits, which contain a variety of metals that serve as crucial raw materials for a range of applications, from electronic devices to renewable energy technologies to construction materials. With the intent of decreasing dependence on imports, supporting the economy and potentially even overcoming the environmental problems related to conventional terrestrial mining, a number of public and private institutions have re-discovered their interest in exploring the prospects of deep-sea mining, which had been deemed economically and technically unfeasible in the early 1980 s. To date, many national and international research projects are grappling to understand the economic environmental, social and legal implications of potential commercial deep-sea mining operations: a challenging endeavor due to the complexity of direct impacts and spill-over effects. In this paper, we present a comprehensive overview of the current state of knowledge in the aforementioned fields as well as a comparison of the impacts associated with conventional terrestrial mining. Furthermore, we identify knowledge gaps that should be urgently addressed to ensure that the world at large benefits from safe, efficient and environmentally-sound mining procedures. We conclude by highlighting the need for interdisciplinary research and international cooperation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Automating Information Discovery Within the Invisible Web

NASA Astrophysics Data System (ADS)

Sweeney, Edwina; Curran, Kevin; Xie, Ermai

A Web crawler or spider crawls through the Web looking for pages to index, and when it locates a new page it passes the page on to an indexer. The indexer identifies links, keywords, and other content and stores these within its database. This database is searched by entering keywords through an interface and suitable Web pages are returned in a results page in the form of hyperlinks accompanied by short descriptions. The Web, however, is increasingly moving away from being a collection of documents to a multidimensional repository for sounds, images, audio, and other formats. This is leading to a situation where certain parts of the Web are invisible or hidden. The term known as the "Deep Web" has emerged to refer to the mass of information that can be accessed via the Web but cannot be indexed by conventional search engines. The concept of the Deep Web makes searches quite complex for search engines. Google states that the claim that conventional search engines cannot find such documents as PDFs, Word, PowerPoint, Excel, or any non-HTML page is not fully accurate and steps have been taken to address this problem by implementing procedures to search items such as academic publications, news, blogs, videos, books, and real-time information. However, Google still only provides access to a fraction of the Deep Web. This chapter explores the Deep Web and the current tools available in accessing it.

Computations in the deep vs superficial layers of the cerebral cortex.

PubMed

Rolls, Edmund T; Mills, W Patrick C

2017-11-01

A fundamental question is how the cerebral neocortex operates functionally, computationally. The cerebral neocortex with its superficial and deep layers and highly developed recurrent collateral systems that provide a basis for memory-related processing might perform somewhat different computations in the superficial and deep layers. Here we take into account the quantitative connectivity within and between laminae. Using integrate-and-fire neuronal network simulations that incorporate this connectivity, we first show that attractor networks implemented in the deep layers that are activated by the superficial layers could be partly independent in that the deep layers might have a different time course, which might because of adaptation be more transient and useful for outputs from the neocortex. In contrast the superficial layers could implement more prolonged firing, useful for slow learning and for short-term memory. Second, we show that a different type of computation could in principle be performed in the superficial and deep layers, by showing that the superficial layers could operate as a discrete attractor network useful for categorisation and feeding information forward up a cortical hierarchy, whereas the deep layers could operate as a continuous attractor network useful for providing a spatially and temporally smooth output to output systems in the brain. A key advance is that we draw attention to the functions of the recurrent collateral connections between cortical pyramidal cells, often omitted in canonical models of the neocortex, and address principles of operation of the neocortex by which the superficial and deep layers might be specialized for different types of attractor-related memory functions implemented by the recurrent collaterals. Copyright © 2017 Elsevier Inc. All rights reserved.

The Feasibility and Benefits of In Situ Exploration of `Oumuamua-like objects

NASA Astrophysics Data System (ADS)

Seligman, Darryl; Laughlin, Gregory

2018-04-01

A rapid accumulation of observations and interpretation have followed in the wake of 1I `Oumuamua's passage through the inner Solar System. We outline the consequences that this first detection of an interstellar asteroid implies for the planet-forming process, and we assess the near-term prospects for detecting and observing (both remotely and \\textit{in situ}) future Solar System visitors of this type. Drawing on detailed heat-transfer calculations that take both `Oumuamua's unusual shape and its chaotic tumbling into account, we affirm that the lack of a detectable coma in deep images of the object very likely arises from the presence of a radiation-modified coating of high molecular weight material (rather than a refractory bulk composition). Assuming that `Oumuamua is a typical representative of a larger population with a kinematic distribution similar to Population I stars in the local galactic neighborhood, we calculate expected arrival rates, impact parameters and velocities of similar objects and assess their prospects for detection using operational and forthcoming facilities. Using `Oumuamua as a proof-of-concept, we assess the prospects for missions that intercept ISOs using conventional chemical propulsion. Using a ``launch on detection'' paradigm, we estimate wait times of order a year between favorable mission opportunities with the detection capabilities of the Large-Scale Synoptic Survey Telescope (LSST), a figure that will be refined as the population of interstellar asteroids becomes observationally better constrained.

Verification Challenges at Low Numbers

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

Benz, Jacob M.; Booker, Paul M.; McDonald, Benjamin S.

2013-06-01

Many papers have dealt with the political difficulties and ramifications of deep nuclear arms reductions, and the issues of “Going to Zero”. Political issues include extended deterrence, conventional weapons, ballistic missile defense, and regional and geo-political security issues. At each step on the road to low numbers, the verification required to ensure compliance of all parties will increase significantly. Looking post New START, the next step will likely include warhead limits in the neighborhood of 1000 . Further reductions will include stepping stones at1000 warheads, 100’s of warheads, and then 10’s of warheads before final elimination could be considered ofmore » the last few remaining warheads and weapons. This paper will focus on these three threshold reduction levels, 1000, 100’s, 10’s. For each, the issues and challenges will be discussed, potential solutions will be identified, and the verification technologies and chain of custody measures that address these solutions will be surveyed. It is important to note that many of the issues that need to be addressed have no current solution. In these cases, the paper will explore new or novel technologies that could be applied. These technologies will draw from the research and development that is ongoing throughout the national laboratory complex, and will look at technologies utilized in other areas of industry for their application to arms control verification.« less

Crop response to deep tillage - a meta-analysis

NASA Astrophysics Data System (ADS)

Schneider, Florian; Don, Axel; Hennings, Inga; Schmittmann, Oliver; Seidel, Sabine J.

2017-04-01

Subsoil, i.e. the soil layer below the topsoil, stores tremendous stocks of nutrients and can keep water even under drought conditions. Deep tillage may be a method to enhance the plant-availability of subsoil resources. However, in field trials, deep tillage effects on crop yields were inconsistent. Therefore, we conducted a meta-analysis of crop yield response to subsoiling, deep ploughing and deep mixing of soil profiles. Our search resulted in 1530 yield comparisons following deep and conventional control tillage on 67 experimental cropping sites. The vast majority of the data derived from temperate latitudes, from trials conducted in the USA (679 observations) and Germany (630 observations). On average, crop yield response to deep tillage was slightly positive (6% increase). However, individual deep tillage effects were highly scattered including about 40% yield depressions after deep tillage. Deep tillage on soils with root restrictive layers increased crop yields about 20%, while soils containing >70% silt increased the risk of yield depressions following deep tillage. Generally, deep tillage effects increased with drought intensity indicating deep tillage as climate adaptation measure at certain sites. Our results suggest that deep tillage can facilitate the plant-availability of subsoil nutrients, which increases crop yields if (i) nutrients in the topsoil are growth limiting, and (ii) deep tillage does not come at the cost of impairing topsoil fertility. On sites with root restrictive soil layers, deep tillage can be an effective measure to mitigate drought stress and improve the resilience of crops. However, deep tillage should only be performed on soils with a stable structure, i.e. <70% silt content. We will discuss the contribution of deep tillage options to enhance the sustainability of agricultural production by facilitating the uptake of nutrients and water from the subsoil.

Matrix completion by deep matrix factorization.

PubMed

Fan, Jicong; Cheng, Jieyu

2018-02-01

Conventional methods of matrix completion are linear methods that are not effective in handling data of nonlinear structures. Recently a few researchers attempted to incorporate nonlinear techniques into matrix completion but there still exists considerable limitations. In this paper, a novel method called deep matrix factorization (DMF) is proposed for nonlinear matrix completion. Different from conventional matrix completion methods that are based on linear latent variable models, DMF is on the basis of a nonlinear latent variable model. DMF is formulated as a deep-structure neural network, in which the inputs are the low-dimensional unknown latent variables and the outputs are the partially observed variables. In DMF, the inputs and the parameters of the multilayer neural network are simultaneously optimized to minimize the reconstruction errors for the observed entries. Then the missing entries can be readily recovered by propagating the latent variables to the output layer. DMF is compared with state-of-the-art methods of linear and nonlinear matrix completion in the tasks of toy matrix completion, image inpainting and collaborative filtering. The experimental results verify that DMF is able to provide higher matrix completion accuracy than existing methods do and DMF is applicable to large matrices. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Pattern learning with deep neural networks in EMG-based speech recognition.

PubMed

Wand, Michael; Schultz, Tanja

2014-01-01

We report on classification of phones and phonetic features from facial electromyographic (EMG) data, within the context of our EMG-based Silent Speech interface. In this paper we show that a Deep Neural Network can be used to perform this classification task, yielding a significant improvement over conventional Gaussian Mixture models. Our central contribution is the visualization of patterns which are learned by the neural network. With increasing network depth, these patterns represent more and more intricate electromyographic activity.

Anomaly detection for medical images based on a one-class classification

NASA Astrophysics Data System (ADS)

Wei, Qi; Ren, Yinhao; Hou, Rui; Shi, Bibo; Lo, Joseph Y.; Carin, Lawrence

2018-02-01

Detecting an anomaly such as a malignant tumor or a nodule from medical images including mammogram, CT or PET images is still an ongoing research problem drawing a lot of attention with applications in medical diagnosis. A conventional way to address this is to learn a discriminative model using training datasets of negative and positive samples. The learned model can be used to classify a testing sample into a positive or negative class. However, in medical applications, the high unbalance between negative and positive samples poses a difficulty for learning algorithms, as they will be biased towards the majority group, i.e., the negative one. To address this imbalanced data issue as well as leverage the huge amount of negative samples, i.e., normal medical images, we propose to learn an unsupervised model to characterize the negative class. To make the learned model more flexible and extendable for medical images of different scales, we have designed an autoencoder based on a deep neural network to characterize the negative patches decomposed from large medical images. A testing image is decomposed into patches and then fed into the learned autoencoder to reconstruct these patches themselves. The reconstruction error of one patch is used to classify this patch into a binary class, i.e., a positive or a negative one, leading to a one-class classifier. The positive patches highlight the suspicious areas containing anomalies in a large medical image. The proposed method has been tested on InBreast dataset and achieves an AUC of 0.84. The main contribution of our work can be summarized as follows. 1) The proposed one-class learning requires only data from one class, i.e., the negative data; 2) The patch-based learning makes the proposed method scalable to images of different sizes and helps avoid the large scale problem for medical images; 3) The training of the proposed deep convolutional neural network (DCNN) based auto-encoder is fast and stable.

Surface temperatures and temperature gradient features of the US Gulf Coast waters

NASA Technical Reports Server (NTRS)

Huh, O. K.; Rouse, L. J., Jr.; Smith, G. W.

1977-01-01

Satellite thermal infrared data on the Gulf of Mexico show that a seasonal cycle exists in the horizontal surface temperature structure. In the fall, the surface temperatures of both coastal and deep waters are nearly uniform. With the onset of winter, atmospheric cold fronts, which are accompanied by dry, low temperature air and strong winds, draw heat from the sea. A band of cooler water forming on the inner shelf expands, until a thermal front develops seaward along the shelf break between the cold shelf waters and the warmer deep waters of the Gulf. Digital analysis of the satellite data was carried out in an interactive mode using a minicomputer and software. A time series of temperature profiles illustrates the temporal and spatial changes in the sea-surface temperature field.

Reflexive convention: civil partnership, marriage and family.

PubMed

Heaphy, Brian

2017-09-14

Drawing on an analysis of qualitative interview data from a study of formalized same-sex relationships (civil partnerships) this paper examines the enduring significance of marriage and family as social institutions. In doing so, it intervenes in current debates in the sociology of family and personal life about how such institutions are undermined by reflexivity or bolstered by convention. Against the backdrop of dominating sociological frames for understanding the links between the changing nature of marriage and family and same-sex relationship recognition, the paper analyses the diverse and overlapping ways (including the simple, relational, strategic, ambivalent and critical ways) in which same-sex partners reflexively constructed and engaged with marriage and family conventions. My analysis suggests that instead of viewing reflexivity and convention as mutually undermining, as some sociologists of family and personal life do, it is insightful to explore how diverse forms of reflexivity and convention interact in everyday life to reconfigure the social institutions of marriage and family, but do not undermine them as such. I argue the case for recognizing the ways in which 'reflexive convention', or reflexive investment in convention, contributes to the continuing significance of marriage and family as social institutions. © London School of Economics and Political Science 2017.

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

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

Comparative evaluation of surface and downhole steam-generation techniques

NASA Astrophysics Data System (ADS)

Hart, C.

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

Nanotribological behavior of deep cryogenically treated martensitic stainless steel

PubMed Central

Bakoglidis, Konstantinos D; Tuckart, Walter R; Broitman, Esteban

2017-01-01

Cryogenic treatments are increasingly used to improve the wear resistance of various steel alloys by means of transformation of retained austenite, deformation of virgin martensite and carbide refinement. In this work the nanotribological behavior and mechanical properties at the nano-scale of cryogenically and conventionally treated AISI 420 martensitic stainless steel were evaluated. Conventionally treated specimens were subjected to quenching and annealing, while the deep cryogenically treated samples were quenched, soaked in liquid nitrogen for 2 h and annealed. The elastic–plastic parameters of the materials were assessed by nanoindentation tests under displacement control, while the friction behavior and wear rate were evaluated by a nanoscratch testing methodology that it is used for the first time in steels. It was found that cryogenic treatments increased both hardness and elastic limit of a low-carbon martensitic stainless steel, while its tribological performance was enhanced marginally. PMID:28904837

Nanotribological behavior of deep cryogenically treated martensitic stainless steel.

PubMed

Prieto, Germán; Bakoglidis, Konstantinos D; Tuckart, Walter R; Broitman, Esteban

2017-01-01

Cryogenic treatments are increasingly used to improve the wear resistance of various steel alloys by means of transformation of retained austenite, deformation of virgin martensite and carbide refinement. In this work the nanotribological behavior and mechanical properties at the nano-scale of cryogenically and conventionally treated AISI 420 martensitic stainless steel were evaluated. Conventionally treated specimens were subjected to quenching and annealing, while the deep cryogenically treated samples were quenched, soaked in liquid nitrogen for 2 h and annealed. The elastic-plastic parameters of the materials were assessed by nanoindentation tests under displacement control, while the friction behavior and wear rate were evaluated by a nanoscratch testing methodology that it is used for the first time in steels. It was found that cryogenic treatments increased both hardness and elastic limit of a low-carbon martensitic stainless steel, while its tribological performance was enhanced marginally.

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.

Effects of conventional and no-tillage soil management and compost and sludge amendment on soil CO2 fluxes and microbial activities

NASA Astrophysics Data System (ADS)

Garcia-Gil, Juan Carlos; Haller, Isabel; Soler-Rovira, Pedro; Polo, Alfredo

2010-05-01

Soil management exerts a significant influence on the dynamic of soil organic matter, which is a key issue to enhance soil quality and its ecological functions, but also affects to greenhouse gas emissions and C sequestration processes. The objective of the present research was to determine the influence of soil management (conventional deep-tillage and no-tillage) and the application of two different organic amendment -thermally-dry sewage sludge (TSL) and municipal waste compost (MWC)- on soil CO2 fluxes and microbial activities in a long-term field experiment under semi-arid conditions. Both organic amendments were applied at a rate of 30 t ha-1 prior to sowing a barley crop. The experiment was conducted on an agricultural soil (Calcic Luvisol) from the experimental farm "La Higueruela" (Santa Olalla, Toledo). Unamended soils were used as control in both conventional and no-tillage management. During the course of the experiment, soil CO2 fluxes, microbial biomass C (MBC) and enzyme activities involved in the biogeochemical cycles of C, N and P were monitored during 12 months. The results obtained during the experiment for soil CO2 fluxes showed a great seasonal fluctuation due to semi-arid climate conditions. Overall, conventional deep-tillage soils exhibited higher CO2 fluxes, which was particularly larger during the first hours after deep-tillage was performed, and smaller MBC content and significantly lower dehydrogenase, beta-glucosidase, phosphatase, urease and BAA protease activities than no-tillage soils. Both MWC and TSL amendments provoked a significant increase of CO2 fluxes in both conventional and no-tillage soils, which was larger in TSL amended soils and particularly in no-tillage soils. The application of these organic amendments also enhanced MBC content and the overall enzyme activities in amended soils, which indicate a global revitalization of soil microbial metabolism in response to the fresh input of organic compounds that are energy sources for microbial growing, especially with TSL that is a raw organic material with no stabilization treatment.

Thesis by Publication in Education: An Autoethnographic Perspective for Educational Researchers

ERIC Educational Resources Information Center

Merga, Margaret K.

2015-01-01

Despite its growing popularity, the thesis by publication is a less conventional format for doctoral dissertations in the field of education. The author successfully undertook a thesis by publication in education from 2012, to submission in 2014. This paper draws on both the literature in the field and the experiences of the author through an…

"The Masters of War": Finding Ways to Talk about the First World War Today

ERIC Educational Resources Information Center

O'Connor, Peter

2017-01-01

This article sets out to challenge conventional descriptions and explanations of war and teaching about war. It draws on raw data from three qualitative arts-based projects to illustrate the complexity of cognitive and affective understandings of the place of war, past, present and future, through the jarring dissonance of "mash-up"--a…

Collaborative Learning with Screen-Based Simulation in Health Care Education: An Empirical Study of Collaborative Patterns and Proficiency Development

ERIC Educational Resources Information Center

Hall, L. O.; Soderstrom, T.; Ahlqvist, J.; Nilsson, T.

2011-01-01

This article is about collaborative learning with educational computer-assisted simulation (ECAS) in health care education. Previous research on training with a radiological virtual reality simulator has indicated positive effects on learning when compared to a more conventional alternative. Drawing upon the field of Computer-Supported…

On Wonderful Machines: The Transmission of Mechanical Knowledge by Jesuits

ERIC Educational Resources Information Center

Feldhay, Rivka

2006-01-01

This paper attempts to draw attention to non-conventional but popular modes of transmitting scientific knowledge in Jesuit institutions in the 17th century. The particular case study focuses on a fictive dialogue between Galileo, Mersenne and Paulus Guldin on the power needed for moving the huge globe of the earth by mechanical means. The dialogue…

Learning Leadership Matters: Teachers' Experiences of Innovatively and Conventionally Prepared Principals. School Leadership Study: Developing Successful Principals

ERIC Educational Resources Information Center

Orr, Margaret Terry; Orphanos, Stelios

2007-01-01

This paper investigates the relationship between innovative leadership preparation and teacher outcomes, building on prior research on the effects of preparation on leadership and effects of leadership on teacher outcomes by drawing on two different teacher samples (Stanford University-based study of innovative programs and the SASS teacher…

Relating to Our Work, Accounting for Our Selves: The Autobiographical Imperative in Teaching about Difference

ERIC Educational Resources Information Center

Thurlow, Crispin

2004-01-01

The central thesis in this essay is the need to get more "personal" and more "political" in our thinking and especially our teaching about interculturality. Offering a "radical" critique of the agenda of conventional Intercultural Communication scholarship, I draw my inspiration from the conceptual and philosophical roots of the field, while also…

A Model of Creativity in Organizations: John Holland's Theory of Vocational Choice (1973) at Multiple Levels of Analysis

ERIC Educational Resources Information Center

Sharif, Rukhsar

2017-01-01

This conceptual paper serves to create a model of creativity and innovation at different organizational levels. It draws on John Holland's Theory of Vocational Choice (1973) as the basis for its structure by incorporating the six different personality types from his theory: conventional, enterprising, realistic, social, investigative, and…

The Role of Graphic Orientations in Children's Drawings of Familiar and Novel Objects at Rest and in Motion.

ERIC Educational Resources Information Center

Ives, William; Rovet, Joanne

1979-01-01

Reports three experiments which investigate: whether familiar objects have standard graphic orientations (Experiment 1); the relationship between use of object orientations and more conventional methods in depicting familiar objects in motion (Experiment 2); and whether orientations are used differently in novel objects whose only defining feature…

Critical thinking.

PubMed

Price, A; Price, B

1996-05-01

Critical thinking is a process applied to midwifery theory, research and experience. It is a positive activity, responsive to context, drawing on negative and positive triggers and emotions to suggest ways of acting in future. Practice-based and reflective midwifery assignments should reflect the midwifery goals of critical thinking. This may require adjustments in assessment criteria and a questioning of standard academic conventions.

Critical by Design: Enacting Critical Action Learning in a Small Business Context

ERIC Educational Resources Information Center

Ram, Monder; Trehan, Kiran

2009-01-01

A small but growing strand of literature is beginning to make the case for "critical action learning" (CAL). Much of this interest operates on theoretical terrain, speculating on the extent to which it might differ from more conventional notions of action learning. This paper draws on insights from (CAL) to demonstrate the importance of being…

Chlorine condenser-evaporator simulation

NASA Astrophysics Data System (ADS)

Muraveva, E. A.

2017-10-01

Refrigeration machines are an integral part of chemical engineering. Coldness in mechanical engineering is used to improve the properties of steels, to stabilize the shape and size of steel parts, to restore the dimensions of worn steel hardened parts, to fasten the parts to be machined during cutting and grinding, to ensure fixed planting during assembly, bending pipelines, deep drawing and stamping parts from sheet materials, in the manufacture and processing of rubber parts, with solid anodizing of aluminum alloy parts.

Metal flow of a tailor-welded blank in deep drawing process

NASA Astrophysics Data System (ADS)

Yan, Qi; Guo, Ruiquan

2005-01-01

Tailor welded blanks were used in the automotive industry to consolidate parts, reduce weight, and increase safety. In recent years, this technology was developing rapidly in China. In Chinese car models, tailor welded blanks had been applied in a lot of automobile parts such as rail, door inner, bumper, floor panel, etc. Concerns on the properties of tailor welded blanks had become more and more important for automobile industry. A lot of research had shown that the strength of the welded seam was higher than that of the base metal, such that the weld failure in the aspect of strength was not a critical issue. However, formability of tailor welded blanks in the stamping process was complex. Among them, the metal flow of tailor welded blanks in the stamping process must be investigated thoroughly in order to reduce the scrap rate during the stamping process in automobile factories. In this paper, the behavior of metal flow for tailor welded blanks made by the laser welding process with two types of different thickness combinations were studied in the deep drawing process. Simulations and experiment verification of the movement of weld line for tailor welded blanks were discussed in detail. Results showed that the control on the movement of welded seam during stamping process by taking some measures in the aspect of blank holder was effective.

Deep Unfolding for Topic Models.

PubMed

Chien, Jen-Tzung; Lee, Chao-Hsi

2018-02-01

Deep unfolding provides an approach to integrate the probabilistic generative models and the deterministic neural networks. Such an approach is benefited by deep representation, easy interpretation, flexible learning and stochastic modeling. This study develops the unsupervised and supervised learning of deep unfolded topic models for document representation and classification. Conventionally, the unsupervised and supervised topic models are inferred via the variational inference algorithm where the model parameters are estimated by maximizing the lower bound of logarithm of marginal likelihood using input documents without and with class labels, respectively. The representation capability or classification accuracy is constrained by the variational lower bound and the tied model parameters across inference procedure. This paper aims to relax these constraints by directly maximizing the end performance criterion and continuously untying the parameters in learning process via deep unfolding inference (DUI). The inference procedure is treated as the layer-wise learning in a deep neural network. The end performance is iteratively improved by using the estimated topic parameters according to the exponentiated updates. Deep learning of topic models is therefore implemented through a back-propagation procedure. Experimental results show the merits of DUI with increasing number of layers compared with variational inference in unsupervised as well as supervised topic models.

Effect of the Yield Stress and r-value Distribution on the Earing Profile of Cup Drawing with Yld2000-2d Yield Function

NASA Astrophysics Data System (ADS)

Lou, Yanshan; Bae, Gihyun; Lee, Changsoo; Huh, Hoon

2010-06-01

This paper deals with the effect of the yield stress and r-value distribution on the earing in the cup drawing. The anisotropic yield function, Yld2000-2d yield function, is selected to describe the anisotropy of two metal sheets, 719B and AA5182-O. The tool dimension is referred from the Benchmark problem of NUMISHEET'2002. The Downhill Simplex method is applied to identify the anisotropic coefficients in Yld2000-2d yield function. Simulations of the drawing process are performed to investigate the earing profile of two materials. The earing profiles obtained from simulations are compared with the analytical model developed by Hosford and Caddell. Simulations are conducted with respect to the change of the yield stress and r-value distribution, respectively. The correlation between the anisotropy and the earing tendency is investigated based on simulation data. Finally, the earing mechanism is analyzed through the deformation process of the blank during the cup deep drawing. It can be concluded that ears locate at angular positions with lower yield stress and higher r-value while the valleys appear at the angular position with higher yield stress and lower r-value. The effect of the yield stress distribution is more important for the cup height distribution than that of the r-value distribution.

Electrical stimulation of acupoint combinations against deep venous thrombosis in elderly bedridden patients after major surgery.

PubMed

Hou, Lili; Chen, Cuiping; Xu, Lei; Yin, Peihao; Peng, Wen

2013-04-01

To compare the effects of electrical stimulation of different acupoint combinations among postoperative bedridden elderly patients on hemorheology and deep venous blood flow velocity and investigate the.role of electrical stimulation against deep vein thrombosis (DVT). From November 2010 to October 2011, a total of 160 elderly bedridden patients after major surgery were divided into the conventional care group, invigorating and promoting Qi group, blood-activating and damp-eliminating group, and acupoint-combination stimulation group. Whole blood viscosity, plasma viscosity, D-dimer levels, lower limb skin temperature, lower limb circumference, and flow velocities of the external iliac vein, femoral vein, popliteal vein, and deep calf veins in all patients were documented and compared among the four groups. Whole blood viscosity, plasma viscosity, D-dimer levels, and lower limb circumference were significantly reduced in the blood-activating and damp-eliminating group compared with the conventional care group (P < 0.05) and were almost equal to those in the acupoint-combination stimulation group (P > 0.05). Lower limb venous flow velocities were accelerated in the invigorating and promoting Qi group compared with the other groups, excluding the acupoint-combination stimulation group (P < 0.05). Hemorheological indices in postoperative bedridden elderly patients were improved after combined electrical stimulation at Yinlingquan (SP 9) and Sanyinjiao (SP 6). Combined electrical stimulation at Zusanli (ST 36) and Taichong (LR 3), on the other hand, accelerated lower limb venous flow.

A Comparison of Nannochloropsis salina Growth Performance in Two Outdoor Pond Designs: Conventional Raceways versus the ARID Pond with Superior Temperature Management

DOE PAGES

Crowe, Braden; Attalah, Said; Agrawal, Shweta; ...

2012-01-01

The present study examines how climatic conditions and pond design affect the growth performance of microalgae. From January to April of 2011, outdoor batch cultures of Nannochloropsis salina were grown in three replicate 780 L conventional raceways, as well as in an experimental 7500 L algae raceway integrated design (ARID) pond. The ARID culture system utilizes a series of 8-20 cm deep basins and a 1.5 m deep canal to enhance light exposure and mitigate temperature variations and extremes. The ARID culture reached the stationary phase 27 days earlier than the conventional raceways, which can be attributed to its superiormore » temperature management and shallower basins. On a night when the air temperature dropped to -9°C, the water temperature was 18°C higher in the ARID pond than in the conventional raceways. Lipid and fatty acid content ranged from 16 to 25% and from 5 to15%, respectively, as a percentage of AFDW. Palmitic, palmitoleic, and eicosapentaenoic acids comprised the majority of fatty acids. While the ARID culture system achieved nearly double the volumetric productivity relative to the conventional raceways (0.023 versus 0.013 g L -1day -1), areal biomass productivities were of similar magnitude in both pond systems (3.47 versus 3.34 g m -2day -1), suggesting that the ARID pond design has to be further optimized, most likely by increasing the culture depth or operating at higher cell densities while maintaining adequate mixing.« less

A comparison of Nannochloropsis salina growth performance in two outdoor pond designs: conventional raceways versus the ARID pond with superior temperature management

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

Crowe, Braden J.; Attalah, Said; Agrawal, Shweta

2012-10-01

The present study examines how climatic conditions and pond design affect the growth performance of microalgae. From January to April of 2011, outdoor batch cultures of Nannochloropsis salina were grown in three replicate 780 L conventional raceways, as well as in an experimental 7500 L ARID (Algae Raceway Integrated Design) pond. The ARID culture system utilizes a series of 8 to 20 cm deep basins and a 1.5 m deep canal to enhance light exposure and mitigate temperature variations and extremes. The ARID culture reached the stationary phase 27 days earlier than the conventional raceways, which can be attributed tomore » its superior temperature management and shallower basins. On a night when the air temperature dropped to -9 °C, the water temperature was 18 °C higher in the ARID pond than in the conventional raceways. Lipid and fatty acid content ranged from 16 - 25 % and 5 - 15 %, respectively, as a percentage of AFDW. Palmitic, palmitoleic, and eicosapentaenoic acid comprised the majority of fatty acids. While the ARID culture system achieved nearly double the volumetric productivity relative to the conventional raceways (0.023 vs 0.013 g L-1day-1), areal biomass productivities were of similar magnitude in both pond systems (3.34 vs. 3.47 g m-2day-1), suggesting that the ARID pond design has to be further optimized, most likely by increasing the culture depth or operating at higher cell densities while maintaining adequate mixing.« less

Enhancing boron rejection in FO using alkaline draw solutions.

PubMed

Wang, Yi-Ning; Li, Weiyi; Wang, Rong; Tang, Chuyang Y

2017-07-01

This study provides a novel method to enhance boron removal in a forward osmosis (FO) process. It utilizes the reverse solute diffusion (RSD) of ions from alkaline draw solutions (DSs) and the concentration polarization of the hydroxyl ions to create a highly alkaline environment near the membrane active surface. The results show that boron rejection can be significantly enhanced by increasing the pH of NaCl DS to 12.5 in the active-layer-facing-feed-solution (AL-FS) orientation. The effect of RSD enhanced boron rejection was further promoted in the presence of concentration polarization (e.g., in the active-layer-facing-draw-solution (AL-DS) orientation). The current study opens a new dimension for controlling contaminant removal by FO using tailored DS chemistry, where the RSD-induced localized water chemistry change is taken advantage in contrast to the conventional method of chemical dosing to the bulk feed water. Copyright © 2017 Elsevier Ltd. All rights reserved.

DeepInfer: open-source deep learning deployment toolkit for image-guided therapy

NASA Astrophysics Data System (ADS)

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-03-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research work ows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy.

PubMed

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A; Kapur, Tina; Wells, William M; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-02-11

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research workflows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

DeepInfer: Open-Source Deep Learning Deployment Toolkit for Image-Guided Therapy

PubMed Central

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-01-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research workflows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose “DeepInfer” – an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections. PMID:28615794

Synthetic Biology: Mapping the Scientific Landscape

PubMed Central

Oldham, Paul; Hall, Stephen; Burton, Geoff

2012-01-01

This article uses data from Thomson Reuters Web of Science to map and analyse the scientific landscape for synthetic biology. The article draws on recent advances in data visualisation and analytics with the aim of informing upcoming international policy debates on the governance of synthetic biology by the Subsidiary Body on Scientific, Technical and Technological Advice (SBSTTA) of the United Nations Convention on Biological Diversity. We use mapping techniques to identify how synthetic biology can best be understood and the range of institutions, researchers and funding agencies involved. Debates under the Convention are likely to focus on a possible moratorium on the field release of synthetic organisms, cells or genomes. Based on the empirical evidence we propose that guidance could be provided to funding agencies to respect the letter and spirit of the Convention on Biological Diversity in making research investments. Building on the recommendations of the United States Presidential Commission for the Study of Bioethical Issues we demonstrate that it is possible to promote independent and transparent monitoring of developments in synthetic biology using modern information tools. In particular, public and policy understanding and engagement with synthetic biology can be enhanced through the use of online interactive tools. As a step forward in this process we make existing data on the scientific literature on synthetic biology available in an online interactive workbook so that researchers, policy makers and civil society can explore the data and draw conclusions for themselves. PMID:22539946

Interleaving subthalamic nucleus deep brain stimulation to avoid side effects while achieving satisfactory motor benefits in Parkinson disease: A report of 12 cases.

PubMed

Zhang, Shizhen; Zhou, Peizhi; Jiang, Shu; Wang, Wei; Li, Peng

2016-12-01

Deep brain stimulation (DBS) of the subthalamic nucleus is an effective treatment for advanced Parkinson disease (PD). However, achieving ideal outcomes by conventional programming can be difficult in some patients, resulting in suboptimal control of PD symptoms and stimulation-induced adverse effects. Interleaving stimulation (ILS) is a newer programming technique that can individually optimize the stimulation area, thereby improving control of PD symptoms while alleviating stimulation-induced side effects after conventional programming fails to achieve the desired results. We retrospectively reviewed PD patients who received DBS programming during the previous 4 years in our hospital. We collected clinical and demographic data from 12 patients who received ILS because of incomplete alleviation of PD symptoms or stimulation-induced adverse effects after conventional programming had proven ineffective or intolerable. Appropriate lead location was confirmed with postoperative reconstruction images. The rationale and clinical efficacy of ILS was analyzed. We divided our patients into 4 groups based on the following symptoms: stimulation-induced dysarthria and choreoathetoid dyskinesias, gait disturbance, and incomplete control of parkinsonism. After treatment with ILS, patients showed satisfactory improvement in PD symptoms and alleviation of stimulation-induced side effects, with a mean improvement in Unified PD Rating Scale motor scores of 26.9%. ILS is a newer choice and effective programming strategy to maximize symptom control in PD while decreasing stimulation-induced adverse effects when conventional programming fails to achieve satisfactory outcome. However, we should keep in mind that most DBS patients are routinely treated with conventional stimulation and that not all patients benefit from ILS. ILS is not recommended as the first choice of programming, and it is recommended only when patients have unsatisfactory control of PD symptoms or stimulation-induced side effects after multiple treatments with conventional stimulation. A return to conventional stimulation may be required if ILS induces new side effects or the needs of the patient change.

Interleaving subthalamic nucleus deep brain stimulation to avoid side effects while achieving satisfactory motor benefits in Parkinson disease

PubMed Central

Zhang, Shizhen; Zhou, Peizhi; Jiang, Shu; Wang, Wei; Li, Peng

2016-01-01

Abstract Background: Deep brain stimulation (DBS) of the subthalamic nucleus is an effective treatment for advanced Parkinson disease (PD). However, achieving ideal outcomes by conventional programming can be difficult in some patients, resulting in suboptimal control of PD symptoms and stimulation-induced adverse effects. Interleaving stimulation (ILS) is a newer programming technique that can individually optimize the stimulation area, thereby improving control of PD symptoms while alleviating stimulation-induced side effects after conventional programming fails to achieve the desired results. Methods: We retrospectively reviewed PD patients who received DBS programming during the previous 4 years in our hospital. We collected clinical and demographic data from 12 patients who received ILS because of incomplete alleviation of PD symptoms or stimulation-induced adverse effects after conventional programming had proven ineffective or intolerable. Appropriate lead location was confirmed with postoperative reconstruction images. The rationale and clinical efficacy of ILS was analyzed. Results: We divided our patients into 4 groups based on the following symptoms: stimulation-induced dysarthria and choreoathetoid dyskinesias, gait disturbance, and incomplete control of parkinsonism. After treatment with ILS, patients showed satisfactory improvement in PD symptoms and alleviation of stimulation-induced side effects, with a mean improvement in Unified PD Rating Scale motor scores of 26.9%. Conclusions: ILS is a newer choice and effective programming strategy to maximize symptom control in PD while decreasing stimulation-induced adverse effects when conventional programming fails to achieve satisfactory outcome. However, we should keep in mind that most DBS patients are routinely treated with conventional stimulation and that not all patients benefit from ILS. ILS is not recommended as the first choice of programming, and it is recommended only when patients have unsatisfactory control of PD symptoms or stimulation-induced side effects after multiple treatments with conventional stimulation. A return to conventional stimulation may be required if ILS induces new side effects or the needs of the patient change. PMID:27930569

Fast algorithm for the rendering of three-dimensional surfaces

NASA Astrophysics Data System (ADS)

Pritt, Mark D.

1994-02-01

It is often desirable to draw a detailed and realistic representation of surface data on a computer graphics display. One such representation is a 3D shaded surface. Conventional techniques for rendering shaded surfaces are slow, however, and require substantial computational power. Furthermore, many techniques suffer from aliasing effects, which appear as jagged lines and edges. This paper describes an algorithm for the fast rendering of shaded surfaces without aliasing effects. It is much faster than conventional ray tracing and polygon-based rendering techniques and is suitable for interactive use. On an IBM RISC System/6000TM workstation it renders a 1000 X 1000 surface in about 7 seconds.

An adaptive signal-processing approach to online adaptive tutoring.

PubMed

Bergeron, Bryan; Cline, Andrew

2011-01-01

Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

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

PubMed Central

Hosseinyalamdary, Siavash

2018-01-01

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

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

PubMed

Hosseinyalamdary, Siavash

2018-04-24

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

"I'm Making It Different to the Book": Transmediation in Young Children's Multimodal and Digital Texts

ERIC Educational Resources Information Center

Mills, Kathy

2011-01-01

Young children shift meanings across multiple modes long before they have mastered formal writing skills. In a digital age, children are socialised into a wide range of new digital media conventions in the home, at school, and in community-based settings. This article draws on longitudinal classroom research with a culturally diverse cohort of…

Drawing a Crowd: Graphic Novel Events Are Great Ways to Generate Excitement

ERIC Educational Resources Information Center

MacDonald, Heidi

2004-01-01

As graphic novels grow in popularity, with teen readers, libraries are finding the world of comics, manga, and anime a fertile field for inspiring events, as well as a great way to promote libraries to teens in general. These events can range from simple--a reading/signing--to elaborate--workshops, or even a mini convention. All provide a unique…

Following Reading Primers the Wrong Way: Pedagogical Nonsense in Dr. Seuss

ERIC Educational Resources Information Center

Yang, Lichung

2017-01-01

A well-versed writer on the limitations and possibilities of the English language, Seuss follows the conventional primers the wrong way, not by retracing the tradition of the genre, but by working his way against the current. Drawing upon Jean-Jacques Lecercle's notion of nonsense, this essay is a small attempt to examine three of Dr. Seuss's…

Recasting the American Dream and American Politics: Barack Obama's Keynote Address to the 2004 Democratic National Convention

ERIC Educational Resources Information Center

Rowland, Robert C.; Jones, John M.

2007-01-01

This essay draws upon the work of Northrop Frye to show that stories enacting the American Dream contain elements associated with romance, and briefly traces how Ronald Reagan and conservatives utilized the romance of the American Dream to the point that many Americans associated it exclusively with conservatism. The essay then details how Barack…

Adolescents' Experiences of the Right to Play and Leisure in Northern Ireland

ERIC Educational Resources Information Center

Beckett, Helen

2010-01-01

Under Article 31 of the United Nations Convention on the Rights of the Child, every child under the age of 18 has the right to engage in age-appropriate play and leisure activities. Drawing on the qualitative findings of a wider review of children's rights in Northern Ireland, this article examines the degree to which adolescents in Northern…

Ariadne's Thread: Using Social Presence Indices to Distinguish Learning Events in Face-to-Face and ICT-Rich Settings

ERIC Educational Resources Information Center

Baskin, Colin; Henderson, Michael

2005-01-01

Drawing on ancient Greek mythology, this article traces the learning experiences of 164 pre-service education students as they make the transition from a conventional face-to-face (f-2-f) learning environment to an Information and Communication Technology (ICT) rich setting. Influenced by Social Presence Theory (Short, Williams & Christie,…

Young People's Voices: Disciplining Young People's Participation in Decision-Making in Special Educational Needs

ERIC Educational Resources Information Center

McKay, Jane

2014-01-01

In recent years, education and family policy in the UK has sought to incorporate the views of children and young people through an active participation agenda, in the fulfilment of children's rights under the obligations of the UN Convention for the Rights of the Child. Drawing on empirical evidence, this paper suggests that this aspiration is…

The Right to Education for Children in Domestic Labour: Empirical Evidence from Kenya

ERIC Educational Resources Information Center

Munene, Ishmael I.; Ruto, Sara J.

2010-01-01

Since 1948, various UN conventions have recognised basic education as a human right. Yet this right continues to be denied to many child labourers across the world. This articles draws on the results of a study examining how children in domestic labour in Kenya access and participate in education. Three issues were explored: (1) the correlates of…

Microfabricated Multianalyte Sensor Arrays for Metabolic Monitoring

DTIC Science & Technology

2007-09-01

Introduction Intensive treatment with the goal of maintaining blood glucose concentrations close to the normal range can prevent or delay...the occurrence of diabetic related complications.1 Diabetic patients, therefore, have to frequently monitor their blood glucose levels by drawing... blood necessary for conventional glucose monitoring. The blood data obtained gives no indication of direction or trend of blood sugar levels. Even the

Conversion of KEGG metabolic pathways to SBGN maps including automatic layout

PubMed Central

2013-01-01

Background Biologists make frequent use of databases containing large and complex biological networks. One popular database is the Kyoto Encyclopedia of Genes and Genomes (KEGG) which uses its own graphical representation and manual layout for pathways. While some general drawing conventions exist for biological networks, arbitrary graphical representations are very common. Recently, a new standard has been established for displaying biological processes, the Systems Biology Graphical Notation (SBGN), which aims to unify the look of such maps. Ideally, online repositories such as KEGG would automatically provide networks in a variety of notations including SBGN. Unfortunately, this is non‐trivial, since converting between notations may add, remove or otherwise alter map elements so that the existing layout cannot be simply reused. Results Here we describe a methodology for automatic translation of KEGG metabolic pathways into the SBGN format. We infer important properties of the KEGG layout and treat these as layout constraints that are maintained during the conversion to SBGN maps. Conclusions This allows for the drawing and layout conventions of SBGN to be followed while creating maps that are still recognizably the original KEGG pathways. This article details the steps in this process and provides examples of the final result. PMID:23953132

Metaphorically speaking: cognitive abilities and the production of figurative language.

PubMed

Beaty, Roger E; Silvia, Paul J

2013-02-01

Figurative language is one of the most common expressions of creative behavior in everyday life. However, the cognitive mechanisms behind figures of speech such as metaphors remain largely unexplained. Recent evidence suggests that fluid and executive abilities are important to the generation of conventional and creative metaphors. The present study investigated whether several factors of the Cattell-Horn-Carroll model of intelligence contribute to generating these different types of metaphors. Specifically, the roles of fluid intelligence (Gf), crystallized intelligence (Gc), and broad retrieval ability (Gr) were explored. Participants completed a series of intelligence tests and were asked to produce conventional and creative metaphors. Structural equation modeling was used to assess the contribution of the different factors of intelligence to metaphor production. For creative metaphor, there were large effects of Gf (β = .45) and Gr (β = .52); for conventional metaphor, there was a moderate effect of Gc (β = .30). Creative and conventional metaphors thus appear to be anchored in different patterns of abilities: Creative metaphors rely more on executive processes, whereas conventional metaphors primarily draw from acquired vocabulary knowledge.

Enabling lightweight designs by a new laser based approach for joining aluminum to steel

NASA Astrophysics Data System (ADS)

Brockmann, Rüdiger; Kaufmann, Sebastian; Kirchhoff, Marc; Candel-Ruiz, Antonio; Müllerschön, Oliver; Havrilla, David

2015-03-01

As sustainability is an essential requirement, lightweight design becomes more and more important, especially for mobility. Reduced weight ensures more efficient vehicles and enables better environmental impact. Besides the design, new materials and material combinations are one major trend to achieve the required weight savings. The use of Carbon Fiber Reinforced Plastics (abbr. CFRP) is widely discussed, but so far high volume applications are rarely to be found. This is mainly due to the fact that parts made of CFRP are much more expensive than conventional parts. Furthermore, the proper technologies for high volume production are not yet ready. Another material with a large potential for lightweight design is aluminum. In comparison to CFRP, aluminum alloys are generally more affordable. As aluminum is a metallic material, production technologies for high volume standard cutting or joining applications are already developed. In addition, bending and deep-drawing can be applied. In automotive engineering, hybrid structures such as combining high-strength steels with lightweight aluminum alloys retain significant weight reduction but also have an advantage over monolithic aluminum - enhanced behavior in case of crash. Therefore, since the use of steel for applications requiring high mechanical properties is unavoidable, methods for joining aluminum with steel parts have to be further developed. Former studies showed that the use of a laser beam can be a possibility to join aluminum to steel parts. In this sense, the laser welding process represents a major challenge, since both materials have different thermal expansion coefficients and properties related to the behavior in corrosive media. Additionally, brittle intermetallic phases are formed during welding. A promising approach to welding aluminum to steel is based on the use of Laser Metal Deposition (abbr. LMD) with deposit materials in the form of powders. Within the present work, the advantages of this approach in comparison to conventional processes, as well as expected limitations are described.

Questioning 'participation': a critical appraisal of its conceptualization in a Flemish participatory technology assessment.

PubMed

van Oudheusden, Michiel

2011-12-01

This article draws attention to struggles inherent in discourse about the meaning of participation in a Flemish participatory technology assessment (pTA) on nanotechnologies. It explores how, at the project's outset, key actors (e.g., nanotechnologists and pTA researchers) frame elements of the process like 'the public' and draw on interpretive repertoires to fit their perspective. The examples call into question normative commitments to cooperation, consensus building, and common action that conventionally guide pTA approaches. It is argued that pTA itself must reflect an awareness of competing interests and perspectives inherent in the discourse associated with the meaning of 'participation' if it is to incite action beyond vested interests and ensure genuine mutual learning.

Study of the influence of selected anisotropic parameter in the Barlat's model on the drawpiece shape

NASA Astrophysics Data System (ADS)

Kaldunski, Pawel; Kukielka, Leon; Patyk, Radoslaw; Kulakowska, Agnieszka; Bohdal, Lukasz; Chodor, Jaroslaw; Kukielka, Krzysztof

2018-05-01

In this paper, the numerical analysis and computer simulation of deep drawing process has been presented. The incremental model of the process in updated Lagrangian formulation with the regard of the geometrical and physical nonlinearity has been evaluated by variational and the finite element methods. The Frederic Barlat's model taking into consideration the anisotropy of materials in three main and six tangents directions has been used. The work out application in Ansys/Ls-Dyna program allows complex step by step analysis and prognoses: the shape, dimensions and state stress and strains of drawpiece. The paper presents the influence of selected anisotropic parameter in the Barlat's model on the drawpiece shape, which includes: height, sheet thickness and maximum drawing force. The important factors determining the proper formation of drawpiece and the ways of their determination have been described.

Optimizing Chemical Reactions with Deep Reinforcement Learning.

PubMed

Zhou, Zhenpeng; Li, Xiaocheng; Zare, Richard N

2017-12-27

Deep reinforcement learning was employed to optimize chemical reactions. Our model iteratively records the results of a chemical reaction and chooses new experimental conditions to improve the reaction outcome. This model outperformed a state-of-the-art blackbox optimization algorithm by using 71% fewer steps on both simulations and real reactions. Furthermore, we introduced an efficient exploration strategy by drawing the reaction conditions from certain probability distributions, which resulted in an improvement on regret from 0.062 to 0.039 compared with a deterministic policy. Combining the efficient exploration policy with accelerated microdroplet reactions, optimal reaction conditions were determined in 30 min for the four reactions considered, and a better understanding of the factors that control microdroplet reactions was reached. Moreover, our model showed a better performance after training on reactions with similar or even dissimilar underlying mechanisms, which demonstrates its learning ability.

Multi-component lightweight gearwheels with deep-drawn wheel body for automotive applications

NASA Astrophysics Data System (ADS)

Benkert, Tim; Hiller, Maria; Volk, Wolfram

2017-09-01

Multi-component gearwheels offer great lightweight opportunities for automotive applications. An assembly of a gear ring and a wheel body joined by press fit replaces the monolithic gearwheel. To save weight, the wheel body uses lightweight design. This lightweight design influences the assembled gearwheel’s mechanical properties like stiffness, weight and torque capacity. Further, the wheel body material influences the mentioned properties as well. In this paper, the effects of the lightweight wheel body manufactured by deep-drawing on the mechanical properties of the assembled gearwheel are investigated. Three different wheel body designs are examined regarding their stiffness and weight compared to a reference gearwheel. Using the best design, the influence of five materials with increasing yield strength on the maximum torque the gearwheel can transmit is studied. All research is done virtually using Abaqus 6.12-3.

The 'French exception': the right to continuous deep sedation at the end of life.

PubMed

Horn, Ruth

2018-03-01

In 2016, a law came into force in France granting terminally ill patients the right to continuous deep sedation (CDS) until death. This right was proposed as an alternative to euthanasia and presented as the 'French response' to problems at the end of life. The law draws a distinction between CDS and euthanasia and other forms of sympton control at the end of life. France is the first country in the world to legislate on CDS . This short report describes the particular context and underlying social values that led to this piece of legislation, and explores its meaning in the wider French context. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Light sleep versus slow wave sleep in memory consolidation: a question of global versus local processes?

PubMed

Genzel, Lisa; Kroes, Marijn C W; Dresler, Martin; Battaglia, Francesco P

2014-01-01

Sleep is strongly involved in memory consolidation, but its role remains unclear. 'Sleep replay', the active potentiation of relevant synaptic connections via reactivation of patterns of network activity that occurred during previous experience, has received considerable attention. Alternatively, sleep has been suggested to regulate synaptic weights homeostatically and nonspecifically, thereby improving the signal:noise ratio of memory traces. Here, we reconcile these theories by highlighting the distinction between light and deep nonrapid eye movement (NREM) sleep. Specifically, we draw on recent studies to suggest a link between light NREM and active potentiation, and between deep NREM and homeostatic regulation. This framework could serve as a key for interpreting the physiology of sleep stages and reconciling inconsistencies in terminology in this field. Copyright © 2013 Elsevier Ltd. All rights reserved.

Strength and Formability Improvement of Al-Cu-Mn Aluminum Alloy Complex Parts by Thermomechanical Treatment with Sheet Hydroforming

NASA Astrophysics Data System (ADS)

Chen, Yi-Zhe; Liu, Wei; Yuan, Shi-Jian

2015-05-01

Normally, the strength and formability of aluminum alloys can be increased largely by severe plastic deformation and heat treatment. However, many plastic deformation processes are more suitable for making raw material, not for formed parts. In this article, an experimental study of the thermomechanical treatment by using the sheet hydroforming process was developed to improve both mechanical strength and formability for aluminum alloys in forming complex parts. The limiting drawing ratio, thickness, and strain distribution of complex parts formed by sheet hydroforming were investigated to study the formability and sheet-deformation behavior. Based on the optimal formed parts, the tensile strength, microhardness, grain structure, and strengthening precipitates were analyzed to identify the strengthening effect of thermomechanical treatment. The results show that in the solution state, the limiting drawing ratio of cylindrical parts could be increased for 10.9% compared with traditional deep drawing process. The peak values of tensile stress and microhardness of formed parts are 18.0% and 12.5% higher than that in T6 state. This investigation shows that the thermomechanical treatment by sheet hydroforming is a potential method for the products manufacturing of aluminum alloy with high strength and good formability.

Leadership styles, emotion regulation, and burnout.

PubMed

Arnold, Kara A; Connelly, Catherine E; Walsh, Megan M; Martin Ginis, Kathleen A

2015-10-01

This study investigated the potential impact of leadership style on leaders' emotional regulation strategies and burnout. Drawing on the full-range model of leadership and Conservation of Resources (COR) theory, we tested whether transformational, contingent reward, management by exception-active and -passive, or laissez-faire leadership exert direct effects on leaders' reported use of surface acting, deep acting, and genuine emotion. In turn, we hypothesized and tested the indirect effect of leadership on burnout through surface acting. Three waves of data from 205 leaders were analyzed using OLS regression. Transformational leadership predicted deep acting and genuine emotion. Contingent reward predicted both surface and deep acting. Management by exception-active and -passive predicted surface acting, and laissez faire predicted genuine emotion. The indirect effects of management by exception-active and -passive on burnout through surface acting were not significant. Indirect effects of transformational leadership and laissez-faire on burnout through genuine emotion, however, were significant. This study provides empirical evidence for the hypothesized relationships between leadership style, emotion regulation, and burnout, and provides the basis for future research and theory building on this topic. (c) 2015 APA, all rights reserved).

Fishing tool retrieves MWD nuclear source from deep well

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

Not Available

A new wire line tool has successfully retrieved the nuclear sources and formation data from a measurement-while-drilling (MWD) tool stuck in a deep, highly deviated well in the Gulf of Mexico. On Nov. 8, 1993, Schlumberger Wireline and Testing and Anadrill ran a logging-while-drilling inductive coupling (LINC) tool on conventional wire line to fish the gamma ray and neutron sources from a compensated density neutron (CDN) tool stuck in a well at 19,855 ft with an inclination greater than 80[degree]. The paper briefly describes the operation and equipment.

Compendium of CARDEROCKDIV Articles Published in Navy Domestic Technology Transfer Fact Sheet, January 1990 through December 1992

DTIC Science & Technology

1992-12-01

longer in the Gulf of Mexico and the patrol, in such areas as th(. Florida Straits have learned what Yucatan Peninsula and from naval Ii means to look down...same performed on conventional deep - containing shallow cracks aW/W < J value have markedly different crack specimens The increa-ed 02, are commonly...the Jc values ’for characterization of the crack-tip atW ratio effects on the measured corresponding deep -crack spec- stress field Moreover, these

Design Principles for Nickel/Hydrogen Cells and Batteries

NASA Technical Reports Server (NTRS)

Thaller, Lawrence H.; Manzo, Michelle A.; Gonzalez-Sanabria, Olga D.

1987-01-01

Individual-pressure-vessel (IPV) nickel/hydrogen cells and bipolar batteries developed for use as energy-storage subsystems for satelite applications. Design principles applied draw upon extensive background in separator technology, alkaline-fuel-cell technology and several alkaline-cell technology areas. Principals are rather straightforward applications of capillary-force formalisms, coupled with slowly developing data base resulting from careful post-test analyses. Based on preconceived assumptions relative to how devices work and how to be designed so they display longer cycle lives at deep discharge.

Metropolitan Washington Area Water Supply Study. Appendix I. Outlying Service Areas.

DTIC Science & Technology

1983-09-01

wells listed in Table 1-21. All are deep well turbine pump systems which draw their water supply from the Magothy Aquifer (200-300 feet). The water...When the sixth well is placed on line, the Department will have the ability to produce a maximum of 4.0 mpply from the Magothy Aquifer (200-300 feet...1-42 MAL. FICUR! 1-12 ORC91IZATIONAL STRUCTURE OF MAJOR PUBLIC WATER SUPPLY SYSTEMS CHARLES COUMITY Surface GroundwaterWae ataWater Magothy Ratanso

Yoga Therapy: Building a Holding Environment for Somatic and Psyche Change.

PubMed

McClure, Bud

2015-01-01

Drawing on ideas from D.W. Winnicott and the work of Quaker theologian Parker Palmer, this article discusses the concept of a holding environment, its refined understanding in the literature over the years, and how it can be optimally used in yoga therapy. The evidence shows that effectively establishing a holding environment can facilitate both somatic and deep structural change in a client, facilitating healing from primal wounding as well as the potential reconnection to the true self.

Cost Evaluation of Dried Blood Spot Home Sampling as Compared to Conventional Sampling for Therapeutic Drug Monitoring in Children

PubMed Central

Martial, Lisa C.; Aarnoutse, Rob E.; Schreuder, Michiel F.; Henriet, Stefanie S.; Brüggemann, Roger J. M.; Joore, Manuela A.

2016-01-01

Dried blood spot (DBS) sampling for the purpose of therapeutic drug monitoring can be an attractive alternative for conventional blood sampling, especially in children. This study aimed to compare all costs involved in conventional sampling versus DBS home sampling in two pediatric populations: renal transplant patients and hemato-oncology patients. Total costs were computed from a societal perspective by adding up healthcare cost, patient related costs and costs related to loss of productivity of the caregiver. Switching to DBS home sampling was associated with a cost reduction of 43% for hemato-oncology patients (€277 to €158) and 61% for nephrology patients (€259 to €102) from a societal perspective (total costs) per blood draw. From a healthcare perspective, costs reduced with 7% for hemato-oncology patients and with 21% for nephrology patients. Total savings depend on the number of hospital visits that can be avoided by using home sampling instead of conventional sampling. PMID:27941974

Cost Evaluation of Dried Blood Spot Home Sampling as Compared to Conventional Sampling for Therapeutic Drug Monitoring in Children.

PubMed

Martial, Lisa C; Aarnoutse, Rob E; Schreuder, Michiel F; Henriet, Stefanie S; Brüggemann, Roger J M; Joore, Manuela A

2016-01-01

Dried blood spot (DBS) sampling for the purpose of therapeutic drug monitoring can be an attractive alternative for conventional blood sampling, especially in children. This study aimed to compare all costs involved in conventional sampling versus DBS home sampling in two pediatric populations: renal transplant patients and hemato-oncology patients. Total costs were computed from a societal perspective by adding up healthcare cost, patient related costs and costs related to loss of productivity of the caregiver. Switching to DBS home sampling was associated with a cost reduction of 43% for hemato-oncology patients (€277 to €158) and 61% for nephrology patients (€259 to €102) from a societal perspective (total costs) per blood draw. From a healthcare perspective, costs reduced with 7% for hemato-oncology patients and with 21% for nephrology patients. Total savings depend on the number of hospital visits that can be avoided by using home sampling instead of conventional sampling.

A simple and novel method for RNA-seq library preparation of single cell cDNA analysis by hyperactive Tn5 transposase.

PubMed

Brouilette, Scott; Kuersten, Scott; Mein, Charles; Bozek, Monika; Terry, Anna; Dias, Kerith-Rae; Bhaw-Rosun, Leena; Shintani, Yasunori; Coppen, Steven; Ikebe, Chiho; Sawhney, Vinit; Campbell, Niall; Kaneko, Masahiro; Tano, Nobuko; Ishida, Hidekazu; Suzuki, Ken; Yashiro, Kenta

2012-10-01

Deep sequencing of single cell-derived cDNAs offers novel insights into oncogenesis and embryogenesis. However, traditional library preparation for RNA-seq analysis requires multiple steps with consequent sample loss and stochastic variation at each step significantly affecting output. Thus, a simpler and better protocol is desirable. The recently developed hyperactive Tn5-mediated library preparation, which brings high quality libraries, is likely one of the solutions. Here, we tested the applicability of hyperactive Tn5-mediated library preparation to deep sequencing of single cell cDNA, optimized the protocol, and compared it with the conventional method based on sonication. This new technique does not require any expensive or special equipment, which secures wider availability. A library was constructed from only 100 ng of cDNA, which enables the saving of precious specimens. Only a few steps of robust enzymatic reaction resulted in saved time, enabling more specimens to be prepared at once, and with a more reproducible size distribution among the different specimens. The obtained RNA-seq results were comparable to the conventional method. Thus, this Tn5-mediated preparation is applicable for anyone who aims to carry out deep sequencing for single cell cDNAs. Copyright © 2012 Wiley Periodicals, Inc.

Suppression of Lateral Diffusion and Surface Leakage Currents in nBn Photodetectors Using an Inverted Design

NASA Astrophysics Data System (ADS)

Du, X.; Savich, G. R.; Marozas, B. T.; Wicks, G. W.

2018-02-01

Surface leakage and lateral diffusion currents in InAs-based nBn photodetectors have been investigated. Devices fabricated using a shallow etch processing scheme that etches through the top contact and stops at the barrier exhibited large lateral diffusion current but undetectably low surface leakage. Such large lateral diffusion current significantly increased the dark current, especially in small devices, and causes pixel-to-pixel crosstalk in detector arrays. To eliminate the lateral diffusion current, two different approaches were examined. The conventional solution utilized a deep etch process, which etches through the top contact, barrier, and absorber. This deep etch processing scheme eliminated lateral diffusion, but introduced high surface current along the device mesa sidewalls, increasing the dark current. High device failure rate was also observed in deep-etched nBn structures. An alternative approach to limit lateral diffusion used an inverted nBn structure that has its absorber grown above the barrier. Like the shallow etch process on conventional nBn structures, the inverted nBn devices were fabricated with a processing scheme that only etches the top layer (the absorber, in this case) but avoids etching through the barrier. The results show that inverted nBn devices have the advantage of eliminating the lateral diffusion current without introducing elevated surface current.

Nonlinear Programming shallow tomography improves deep structure imaging

NASA Astrophysics Data System (ADS)

Li, J.; Morozov, I.

2004-05-01

In areas with strong variations in topography or near-surface lithology, conventional seismic data processing methods do not produce clear images, neither shallow nor deep. The conventional reflection data processing methods do not resolve stacking velocities at very shallow depth; however, refraction tomography can be used to obtain the near-surface velocities. We use Nonlinear Programming (NP) via known velocity and depth in points from shallow boreholes and outcrop as well as derivation of slowness as constraint conditions to gain accurate shallow velocities. We apply this method to a 2D reflection survey shot across the Flame Mountain, a typical mountain with high gas reserve volume in Western China, by PetroChina and BGP in 1990s. The area has a highly rugged topography with strong variations of lithology near the surface. Over its hillside, the quality of reflection data is very good, but on the mountain ridge, reflection quality is poorer. Because of strong noise, only the first breaks are clear in the records, with velocities varying by more than 3 times in the near offsets. Because this region contains a steep cliff and an overthrust fold, it is very difficult to find a standard refraction horizon, therefore, GLI refractive statics conventional field and residual statics do not result in a good image. Our processing approach includes: 1) The Herglotz-Wiechert method to derive a starting velocity model which is better than horizontal velocity model; 2) using shallow boreholes and geological data, construct smoothness constraints on the velocity field as well as; 3) perform tomographic velocity inversion by NP algorithm; 4) by using the resulting accurate shallow velocities, derive the statics to correct the seismic data for the complex near-surface velocity variations. The result indicates that shallow refraction tomography can greatly improve deep seismic images in complex surface conditions.

Material and physical model for evaluation of deep brain activity contribution to EEG recordings

NASA Astrophysics Data System (ADS)

Ye, Yan; Li, Xiaoping; Wu, Tiecheng; Li, Zhe; Xie, Wenwen

2015-12-01

Deep brain activity is conventionally recorded with surgical implantation of electrodes. During the neurosurgery, brain tissue damage and the consequent side effects to patients are inevitably incurred. In order to eliminate undesired risks, we propose that deep brain activity should be measured using the noninvasive scalp electroencephalography (EEG) technique. However, the deeper the neuronal activity is located, the noisier the corresponding scalp EEG signals are. Thus, the present study aims to evaluate whether deep brain activity could be observed from EEG recordings. In the experiment, a three-layer cylindrical head model was constructed to mimic a human head. A single dipole source (sine wave, 10 Hz, altering amplitudes) was embedded inside the model to simulate neuronal activity. When the dipole source was activated, surface potential was measured via electrodes attached on the top surface of the model and raw data were recorded for signal analysis. Results show that the dipole source activity positioned at 66 mm depth in the model, equivalent to the depth of deep brain structures, is clearly observed from surface potential recordings. Therefore, it is highly possible that deep brain activity could be observed from EEG recordings and deep brain activity could be measured using the noninvasive scalp EEG technique.

A Novel Deep Inspiration Maneuver for Difficult Transseptal Puncture.

PubMed

Aksu, Tolga; Guler, Tumer Erdem; Yalin, Kivanc; Golcuk, Sukriye Ebru; Ozcan, Kazim Serhan; Guler, Niyazi

2017-02-01

Transseptal puncture (TSP) may not be possible in cases of an elastic, aneurysmal, or thickened interatrial septum (IAS). During deep inspiration (DI), the chest wall expands and the diaphragm descends. This makes intrapleural pressure to become more negative, which leads to movement of the IAS to the right side. The aim of this study was to verify prospectively the feasibility, safety, and outcome of DI associated with conventional TSP technique in patients with challenging IAS anatomy. From September 2012 to May 2016, 224 patients underwent TSP due to different indications. Patients were divided into 2 groups: 213 patients in whom the left atrium was successfully accessed in 3 attempts were grouped as conventional TSP group and 11 patients in whom left atrium access was failed after 3 conventional attempts were grouped as DI-TSP group. Conventional TSP was successful in 89.6% of patients with the first attempt. Second and third attempts were required in 4.1% and 1.4%, respectively. Septal puncture was achieved at the first attempt in 10 patients within a median of 1 second of DI maneuver (interquartile range, 1 to 3) and without any complications. Challenging IAS anatomy consisting of IAS aneurysm, a thick IAS, and an excessively mobile IAS were more frequent in the DI-TSP group (45% to 8%, 27% to 3%, and 21% to 5%, respectively, p <0.001). In conclusion, TSP by using the DI maneuver may be a reliable and safe method after failed conventional attempts. If there is any doubt about the correct location of the needle, additional imaging modalities have to be used. Copyright © 2016 Elsevier Inc. All rights reserved.

Predator-guided sampling reveals biotic structure in the bathypelagic.

PubMed

Benoit-Bird, Kelly J; Southall, Brandon L; Moline, Mark A

2016-02-24

We targeted a habitat used differentially by deep-diving, air-breathing predators to empirically sample their prey's distributions off southern California. Fine-scale measurements of the spatial variability of potential prey animals from the surface to 1,200 m were obtained using conventional fisheries echosounders aboard a surface ship and uniquely integrated into a deep-diving autonomous vehicle. Significant spatial variability in the size, composition, total biomass, and spatial organization of biota was evident over all spatial scales examined and was consistent with the general distribution patterns of foraging Cuvier's beaked whales (Ziphius cavirostris) observed in separate studies. Striking differences found in prey characteristics between regions at depth, however, did not reflect differences observed in surface layers. These differences in deep pelagic structure horizontally and relative to surface structure, absent clear physical differences, change our long-held views of this habitat as uniform. The revelation that animals deep in the water column are so spatially heterogeneous at scales from 10 m to 50 km critically affects our understanding of the processes driving predator-prey interactions, energy transfer, biogeochemical cycling, and other ecological processes in the deep sea, and the connections between the productive surface mixed layer and the deep-water column. © 2016 The Author(s).

Comparison of deep and superficial abdominal muscle activity between experienced Pilates and resistance exercise instructors and controls during stabilization exercise.

PubMed

Moon, Ji-Hyun; Hong, Sang-Min; Kim, Chang-Won; Shin, Yun-A

2015-06-01

Pilates and resistance exercises are used for lumbar stabilization training. However, it is unclear which exercise is more effective for lumbar stabilization. In our study, we aimed to compare surface muscle activity and deep muscle thickness during relaxation and spinal stabilization exercise in experienced Pilates and resistance exercise instructors. This study is a retrospective case control study set in the Exercise Prescription Laboratory and Sports Medicine Center. The participants included Pilates instructors (mean years of experience, 3.20±1.76; n=10), resistance exercise instructors (mean years of experience, 2.53±0.63; n=10), and controls (n=10). The participants performed 4 different stabilization exercises: abdominal drawing-in maneuver, bridging, roll-up, and one-leg raise. During the stabilization exercises, surface muscle activity was measured with electromyography, whereas deep muscle thickness was measured by ultrasound imaging. During the 4 stabilization exercises, the thickness of the transverse abdominis (TrA) was significantly greater in the Pilates-trained group than the other 2 other groups. The internal oblique (IO) thickness was significantly greater in the Pilates- and resistance-trained group than the control group, during the 4 exercises. However, the surface muscle activities were similar between the groups. Both Pilates and resistance exercise instructors had greater activation of deep muscles, such as the TrA and IO, than the control subjects. Pilates and resistance exercise are both effective for increasing abdominal deep muscle thickness.

Comparison of deep and superficial abdominal muscle activity between experienced Pilates and resistance exercise instructors and controls during stabilization exercise

PubMed Central

Moon, Ji-Hyun; Hong, Sang-Min; Kim, Chang-Won; Shin, Yun-A

2015-01-01

Pilates and resistance exercises are used for lumbar stabilization training. However, it is unclear which exercise is more effective for lumbar stabilization. In our study, we aimed to compare surface muscle activity and deep muscle thickness during relaxation and spinal stabilization exercise in experienced Pilates and resistance exercise instructors. This study is a retrospective case control study set in the Exercise Prescription Laboratory and Sports Medicine Center. The participants included Pilates instructors (mean years of experience, 3.20±1.76; n=10), resistance exercise instructors (mean years of experience, 2.53±0.63; n=10), and controls (n=10). The participants performed 4 different stabilization exercises: abdominal drawing-in maneuver, bridging, roll-up, and one-leg raise. During the stabilization exercises, surface muscle activity was measured with electromyography, whereas deep muscle thickness was measured by ultrasound imaging. During the 4 stabilization exercises, the thickness of the transverse abdominis (TrA) was significantly greater in the Pilates-trained group than the other 2 other groups. The internal oblique (IO) thickness was significantly greater in the Pilates- and resistance-trained group than the control group, during the 4 exercises. However, the surface muscle activities were similar between the groups. Both Pilates and resistance exercise instructors had greater activation of deep muscles, such as the TrA and IO, than the control subjects. Pilates and resistance exercise are both effective for increasing abdominal deep muscle thickness. PMID:26171383

Combining conventional and thermal drilling in order to increase speed and reduce costs of drilling operations to access deep geothermal resources

NASA Astrophysics Data System (ADS)

Rossi, Edoardo; Kant, Michael A.; von Rohr, Philipp Rudolf; Saar, Martin O.

2017-04-01

The exploitation of deep geothermal resources for energy production relies on finding cost effective solutions to increase the drilling performance in hard rocks. Conventional rotary drilling techniques, based on mechanical rock exportation, result in high rates of drilling tool wearing, causing significant costs. Additionally, rotary drilling results in low drilling speeds in the typically hard crystalline basement rocks targeted for enhanced geothermal energy utilization technologies. Furthermore, even lower overall drilling rates result, when considering tripping times required to exchange worn drill tools. Therefore, alternative drilling techniques, such as hammering, thermal drilling, plasma drilling, and jetting processes are widely investigated in order to provide cost-effective alternatives to conventional drilling methods. A promising approach, that combines conventional rotary and thermal drilling techniques, is investigated in the present work. Here, the rock material is thermally weakened before being exported by conventional cutters. Heat is locally provided by a flame, which moves over the rock surface, heat-treating the material. Besides reducing the rock strength, an in-depth smoothening effect of the mechanical rock properties is observed due to the thermal treatment. This results in reduced rates of drill bit wearing and higher rates of penetration, which in turn decreases drilling costs significantly, particularly for deep-drilling projects. Due to the high heating rates, rock-hardening, commonly observed at moderate temperatures, can be avoided. The flame action can be modelled as a localized, high heat transfer coefficient flame treatment, which results in orders of magnitude higher heating rates than conventional oven treatments. Therefore, we analyse rock strength variations after different maximum temperatures, flame-based heating rates, and rock confinement pressures. The results show that flame treatments lead to a monotonous decrease of rock strength with temperature. This is different from oven treatments, where an initial increase of strength is typically observed, followed by a steep decrease upon further (slow) oven-heating. Thus, the weakening of sandstone and granite samples due to flame treatments indicates the feasibility of a combined mechanical-thermal drilling system. These results suggest that the new combined method enables improved rates of penetration in hard rocks while reducing the rate of drill tool wear. We also present possible implementations of this combined drilling system in the field. From field test results, advantages and limitations of the proposed new technology are presented, with an emphasis on accessing geothermal energy resources in crystalline basement rocks.

Harnessing the Potential of Additive Manufacturing

DTIC Science & Technology

2016-12-01

manufacturing age, which is dominated by standards for materials, processes and process control. Conventional manufacturing is based upon a design that is...documented either in a drawing or a computer-aided design (CAD) file. The manufacturing team then develops a docu- mented public or private process for...31 Defense AT&L: November-December 2016 Harnessing the Potential of Additive Manufacturing Bill Decker Decker is director of Technology

Child Poverty as Public Policy: Direct Provision and Asylum Seeker Children in the Republic of Ireland

ERIC Educational Resources Information Center

Fanning, Bryan; Veale, Angela

2004-01-01

This paper evaluates responses to asylum seeker children in Ireland from a child poverty perspective and from that of the United Nations Convention on the Rights of the Child. It draws upon research undertaken in early 2001 on behalf of the Irish Refugee Council among asylum seeker families with children in Cork, Limerick and Ennis on their…

"Proper Masculinities" and the Fear of Feminisation in Modern Cyprus: University Students Talk about Homosexuality and Gendered Subjectivities

ERIC Educational Resources Information Center

Onoufriou, Andreas

2010-01-01

The present article attempts to pay attention to the ways in which a group of young Cypriot students engage in the construction of conventional notions of masculinities through the negation and the fear of homosexual desire. Drawing on interviews with 12 male and female university students, I argue that many young men go through complicated…

"Without Contraries Is No Progression": Dust as an All-Inclusive, Multifunctional Metaphor in Philip Pullman's "His Dark Materials."

ERIC Educational Resources Information Center

Bird, Anne-Marie

2001-01-01

Draws on Milton's "Paradise Lost" and on motifs found within Gnostic mythology and the poetry of William Blake to explore how Philip Pullman reworks the Judeo-Christian myth of the Fall in his trilogy, "His Dark Materials." Finds at its center "Dust": a conventional metaphor for human physicality in which good and evil, and spirit and matter…

Dialoguing, Cultural Capital, and Student Engagement: Toward a Hip Hop Pedagogy in the High School and University Classroom

ERIC Educational Resources Information Center

Rodriguez, Louie F.

2009-01-01

Hip hop culture is typically excluded from conventional educational spaces within the U.S. Drawing on the experiences of an educator who works with urban high school students and university level pre- and in-service educators, this article examines the role of hip hop culture for student engagement in two settings--an alternative high school…

System design package for a solar heating and cooling system installed at Akron, Ohio

NASA Technical Reports Server (NTRS)

1979-01-01

Information used to evaluate the design of a solar heating, cooling, and domestic hot water system is given. A conventional heat pump provides summer cooling items as the design data brochure, system performance specification, system hazard analysis, spare parts list, and detailed design drawings. A solar system is installed in a single-family dwelling at Akron, Ohio, and at Duffield, Virginia.

Purifying fluoride-contaminated water by a novel forward osmosis design with enhanced flux under reduced concentration polarization.

PubMed

Pal, Madhubonti; Chakrabortty, Sankha; Pal, Parimal; Linnanen, Lassi

2015-08-01

For purifying fluoride-contaminated water, a new forward osmosis scheme in horizontal flat-sheet cross flow module was designed and investigated. Effects of pressure, cross flow rate, draw solution and alignment of membrane module on separation and flux were studied. Concentration polarization and reverse salt diffusion got significantly reduced in the new hydrodynamic regime. This resulted in less membrane fouling, better solute separation and higher pure water flux than in a conventional module. The entire scheme was completed in two stages-an upstream forward osmosis for separating pure water from contaminated water and a downstream nanofiltration operation for continuous recovery and recycle of draw solute. Synchronization of these two stages of operation resulted in a continuous, steady-state process. From a set of commercial membranes, two polyamide composite membranes were screened out for the upstream and downstream filtrations. A 0.3-M NaCl solution was found to be the best one for forward osmosis draw solution. Potable water with less than 1% residual fluoride could be produced at a high flux of 60-62 L m(-2) h(-1) whereas more than 99% draw solute could be recovered and recycled in the downstream nanofiltration stage from where flux was 62-65 L m(-2) h(-1).

Deep tissue optical focusing and optogenetic modulation with time-reversed ultrasonically encoded light

PubMed Central

Ruan, Haowen; Brake, Joshua; Robinson, J. Elliott; Liu, Yan; Jang, Mooseok; Xiao, Cheng; Zhou, Chunyi; Gradinaru, Viviana; Yang, Changhuei

2017-01-01

Noninvasive light focusing deep inside living biological tissue has long been a goal in biomedical optics. However, the optical scattering of biological tissue prevents conventional optical systems from tightly focusing visible light beyond several hundred micrometers. The recently developed wavefront shaping technique time-reversed ultrasonically encoded (TRUE) focusing enables noninvasive light delivery to targeted locations beyond the optical diffusion limit. However, until now, TRUE focusing has only been demonstrated inside nonliving tissue samples. We present the first example of TRUE focusing in 2-mm-thick living brain tissue and demonstrate its application for optogenetic modulation of neural activity in 800-μm-thick acute mouse brain slices at a wavelength of 532 nm. We found that TRUE focusing enabled precise control of neuron firing and increased the spatial resolution of neuronal excitation fourfold when compared to conventional lens focusing. This work is an important step in the application of TRUE focusing for practical biomedical uses. PMID:29226248

A Study Of Undergraduate Students' Alternative Conceptions Of Earth's Interior Using Drawing Tasks

NASA Astrophysics Data System (ADS)

McAllister, Meredith L.

2014-12-01

Learning fundamental geoscience topics such as plate tectonics, earthquakes, and volcanoes requires students to develop a deep understanding of the conceptual models geologists use when describing the structure and dynamics of Earth's interior. Despite the importance of these mental models underlying much of the undergraduate geoscience curriculum, surprisingly little research related to this complex idea exists in the discipline-based science education research literature. To better understand non-science-majoring undergraduates' conceptual models of Earth's interior, student-generated drawings and interviews were used to probe student understanding of the Earth. Ninety-two semi-structured interviews were conducted with non-science-major college students at the beginning of an entry-level geology course at a large Midwestern university. Students were asked to draw a picture of Earth's interior and provide think-aloud explanations of their drawings. The results reveal that students hold a wide range of alternative conceptions about Earth, with only a small fraction having scientifically accurate ideas. Students' understandings ranged from conceptualizing Earth's interior as consisting of horizontal layers of rock and dirt, to more sophisticated views with Earth's interior being composed of concentric layers with unique physical and chemical characteristics. Processes occurring within Earth, such as "convection," were rarely mentioned or explained. These results provide a first-steps basis from which to further explore college students' thinking and contribute to the growing body of knowledge on earth science teaching and geoscience education research.

Using deep learning for content-based medical image retrieval

NASA Astrophysics Data System (ADS)

Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

2017-03-01

Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

Active Cooling of Oil after Deep-frying.

PubMed

Totani, Nagao; Yasaki, Naoko; Doi, Rena; Hasegawa, Etsuko

2017-10-01

Oil used for deep-frying is often left to stand after cooking. A major concern is oxidation during standing that might be avoidable, especially in the case of oil used repeatedly for commercial deep-frying as this involves large volumes that are difficult to cool in a conventional fryer. This paper describes a method to minimize oil oxidation. French fries were deep-fried and the oil temperature decreased in a manner typical for a commercial deep-fryer. The concentration of polar compounds generated from thermally oxidized oil remarkably increased at temperature higher than 100°C but little oxidation occurred below 60°C. Heating the oil showed that the peroxide and polar compound content did not increase when the oil was actively cooled using a running water-cooled Graham-type condenser system to cool the oil from 180°C to room temperature within 30 min. When French fries were fried and the oil was then immediately cooled using the condenser, the polar compound content during cooling did not increase. Our results demonstrate that active cooling of heated oil is simple and quite effective for inhibiting oxidation.

Pre-cementation of deep shaft

NASA Astrophysics Data System (ADS)

Heinz, W. F.

1988-12-01

Pre-cementation or pre-grouting of deep shafts in South Africa is an established technique to improve safety and reduce water ingress during shaft sinking. The recent completion of several pre-cementation projects for shafts deeper than 1000m has once again highlighted the effectiveness of pre-grouting of shafts utilizing deep slimline boreholes and incorporating wireline technique for drilling and conventional deep borehole grouting techniques for pre-cementation. Pre-cementation of deep shaft will: (i) Increase the safety of shaft sinking operation (ii) Minimize water and gas inflow during shaft sinking (iii) Minimize the time lost due to additional grouting operations during sinking of the shaft and hence minimize costly delays and standing time of shaft sinking crews and equipment. (iv) Provide detailed information of the geology of the proposed shaft site. Informations on anomalies, dykes, faults as well as reef (gold bearing conglomerates) intersections can be obtained from the evaluation of cores of the pre-cementation boreholes. (v) Provide improved rock strength for excavations in the immediate vicinity of the shaft area. The paper describes pre-cementation techniques recently applied successfully from surface and some conclusions drawn for further considerations.

Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

NASA Astrophysics Data System (ADS)

Kalinovsky, A.; Liauchuk, V.; Tarasau, A.

2017-05-01

In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For training and testing of the algorithms a domestic dataset of 338 3D CT scans of tuberculosis patients with manually labelled lesions was used. The algorithms which are based on using Deep Convolutional Networks were implemented and applied in three different ways including slice-wise lesion detection in 2D images using semantic segmentation, slice-wise lesion detection in 2D images using sliding window technique as well as straightforward detection of lesions via semantic segmentation in whole 3D CT scans. The algorithms demonstrate superior performance compared to algorithms based on conventional image analysis methods.

New generic indexing technology

NASA Technical Reports Server (NTRS)

Freeston, Michael

1996-01-01

There has been no fundamental change in the dynamic indexing methods supporting database systems since the invention of the B-tree twenty-five years ago. And yet the whole classical approach to dynamic database indexing has long since become inappropriate and increasingly inadequate. We are moving rapidly from the conventional one-dimensional world of fixed-structure text and numbers to a multi-dimensional world of variable structures, objects and images, in space and time. But, even before leaving the confines of conventional database indexing, the situation is highly unsatisfactory. In fact, our research has led us to question the basic assumptions of conventional database indexing. We have spent the past ten years studying the properties of multi-dimensional indexing methods, and in this paper we draw the strands of a number of developments together - some quite old, some very new, to show how we now have the basis for a new generic indexing technology for the next generation of database systems.

Depletion-Mode GaN HEMT Q-Spoil Switches for MRI Coils

PubMed Central

Lu, Jonathan Y.; Grafendorfer, Thomas; Zhang, Tao; Vasanawala, Shreyas; Robb, Fraser; Pauly, John M.; Scott, Greig C.

2017-01-01

Q-spoiling is the process of decoupling an MRI receive coil to protect the equipment and patient. Conventionally, Q-spoiling is performed using a PIN diode switch that draws significant current. In this work, a Q-spoiling technique using a depletion-mode Gallium Nitride HEMT device was developed for coil detuning at both 1.5 T and 3 T MRI. The circuits with conventional PIN diode Q-spoiling and the GaN HEMT device were implemented on surface coils. SNR was measured and compared for all surfaces coils. At both 1.5 T and 3 T, comparable SNR was achieved for all coils with the proposed technique and conventional Q-spoiling. The GaN HEMT device has significantly reduced the required power for Q-spoiling. The GaN HEMT device also provides useful safety features by detuning the coil when unpowered. PMID:27362895

Leveraging non-binding instruments for global health governance: reflections from the Global AIDS Reporting Mechanism for WHO reform.

PubMed

Taylor, A L; Alfven, T; Hougendobler, D; Tanaka, S; Buse, K

2014-02-01

As countries contend with an increasingly complex global environment with direct implications for population health, the international community is seeking novel mechanisms to incentivize coordinated national and international action towards shared health goals. Binding legal instruments have garnered increasing attention since the World Health Organization adopted its first convention in 2003. This paper seeks to expand the discourse on future global health lawmaking by exploring the potential value of non-binding instruments in global health governance, drawing on the case of the 2001 United Nations General Assembly Special Session Declaration of Commitment on HIV/AIDS. In other realms of international concern ranging from the environment to human rights to arms control, non-binding instruments are increasingly used as effective instruments of international cooperation. The experience of the Global AIDS Reporting Mechanism, established pursuant to the Declaration, evidences that, at times, non-binding legal instruments can offer benefits over slower, more rigid binding legal approaches to governance. The global AIDS response has demonstrated that the use of a non-binding instrument can be remarkably effective in galvanizing increasingly deep commitments, action, reporting compliance and ultimately accountability for results. Based on this case, the authors argued that non-binding instruments deserve serious consideration by the international community for the future of global health governance, including in the context of WHO reform. Copyright © 2013 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

The Feasibility and Benefits of In Situ Exploration of ‘Oumuamua-like Objects

NASA Astrophysics Data System (ADS)

Seligman, Darryl; Laughlin, Gregory

2018-05-01

A rapid accumulation of observations and interpretation has followed in the wake of 1I ‘Oumuamua’s passage through the inner solar system. We briefly outline the consequences that this first detection of an interstellar asteroid implies for the planet-forming process, and we assess the near-term prospects for detecting and observing (both remotely and in situ) future solar system visitors of this type. Drawing on detailed heat-transfer calculations that take both ‘Oumuamua’s unusual shape and its chaotic tumbling into account, we affirm that the lack of a detectable coma in deep images of the object very likely arises from the presence of a radiation-modified coating of high molecular weight material (rather than a refractory bulk composition). Assuming that ‘Oumuamua is a typical representative of a larger population with a kinematic distribution similar to Population I stars in the local galactic neighborhood, we calculate expected arrival rates, impact parameters, and velocities of similar objects and assess their prospects for detection using operational and forthcoming facilities. Using ‘Oumuamua as a proof of concept, we assess the prospects for missions that intercept interstellar objects using conventional chemical propulsion. Using a “launch on detection” paradigm, we estimate wait times of order of 10 years between favorable mission opportunities with the detection capabilities of the Large-scale Synoptic Survey Telescope, a figure that will be refined as the population of interstellar asteroids becomes observationally better constrained.

Students learning from patients: let's get real in medical education.

PubMed

Bleakley, Alan; Bligh, John

2008-03-01

Medical students must be prepared for working in inter-professional and multi-disciplinary clinical teams centred on a patient's care pathway. While there has been a good deal of rhetoric surrounding patient-centred medical education, there has been little attempt to conceptualise such a practice beyond the level of describing education of communication skills and empathy within a broad 'professionalism' framework. Paradoxically, while aiming to strengthen patient-student interactions, this approach tends to refocus on the role modelling of the physician, and opportunities for potentially deep collaborative working relationships between students and patients are missed. A radical overhaul of conventional doctor-led medical education may be necessary, that also challenges the orthodoxies of individualistic student-centred approaches, leading to an authentic patient-centred model that shifts the locus of learning from the relationship between doctor as educator and student to the relationship between patient and student, with expert doctor as resource. Drawing on contemporary poststructuralist theory of text and identity construction, and on innovative models of work-based learning, the potential quality of relationship between student and patient is articulated in terms of collaborative knowledge production, involving close reading with the patient as text, through dialogue. Here, a medical 'education' displaces traditional forms of medical 'training' that typically involve individual information reproduction. Students may, paradoxically, improve clinical acumen through consideration of silences, gaps, and contradictions in patients as texts, rather than treating communication as transparent. Such paradoxical effects have been systematically occluded or denied in traditional medical education.

The Fate and Impact of Internal Waves in Nearshore Ecosystems

NASA Astrophysics Data System (ADS)

Woodson, C. B.

2018-01-01

Internal waves are widespread features of global oceans that play critical roles in mixing and thermohaline circulation. Similarly to surface waves, internal waves can travel long distances, ultimately breaking along continental margins. These breaking waves can transport deep ocean water and associated constituents (nutrients, larvae, and acidic low-oxygen waters) onto the shelf and locally enhance turbulence and mixing, with important effects on nearshore ecosystems. We are only beginning to understand the role internal waves play in shaping nearshore ecosystems. Here, I review the physics of internal waves in shallow waters and identify two commonalities among internal waves in the nearshore: exposure to deep offshore waters and enhanced turbulence and mixing. I relate these phenomena to important ecosystem processes ranging from extreme events to fertilization success to draw general conclusions about the influence of internal waves on ecosystems and the effects of internal waves in a changing climate.

Volcano seismicity and ground deformation unveil the gravity-driven magma discharge dynamics of a volcanic eruption.

PubMed

Ripepe, Maurizio; Donne, Dario Delle; Genco, Riccardo; Maggio, Giuseppe; Pistolesi, Marco; Marchetti, Emanuele; Lacanna, Giorgio; Ulivieri, Giacomo; Poggi, Pasquale

2015-05-18

Effusive eruptions are explained as the mechanism by which volcanoes restore the equilibrium perturbed by magma rising in a chamber deep in the crust. Seismic, ground deformation and topographic measurements are compared with effusion rate during the 2007 Stromboli eruption, drawing an eruptive scenario that shifts our attention from the interior of the crust to the surface. The eruption is modelled as a gravity-driven drainage of magma stored in the volcanic edifice with a minor contribution of magma supplied at a steady rate from a deep reservoir. Here we show that the discharge rate can be predicted by the contraction of the volcano edifice and that the very-long-period seismicity migrates downwards, tracking the residual volume of magma in the shallow reservoir. Gravity-driven magma discharge dynamics explain the initially high discharge rates observed during eruptive crises and greatly influence our ability to predict the evolution of effusive eruptions.

Hope for health and health care.

PubMed

Stempsey, William E

2015-02-01

Virtually all activities of health care are motivated at some level by hope. Patients hope for a cure; for relief from pain; for a return home. Physicians hope to prevent illness in their patients; to make the correct diagnosis when illness presents itself; that their prescribed treatments will be effective. Researchers hope to learn more about the causes of illness; to discover new and more effective treatments; to understand how treatments work. Ultimately, all who work in health care hope to offer their patients hope. In this paper, I offer a brief analysis of hope, considering the definitions of Hobbes, Locke, Hume and Thomas Aquinas. I then differentiate shallow and deep hope and show how hope in health care can remain shallow. Next, I explore what a philosophy of deep hope in health care might look like, drawing important points from Ernst Bloch and Gabriel Marcel. Finally, I suggest some implications of this philosophy of hope for patients, physicians, and researchers.

Optimizing Chemical Reactions with Deep Reinforcement Learning

PubMed Central

2017-01-01

Deep reinforcement learning was employed to optimize chemical reactions. Our model iteratively records the results of a chemical reaction and chooses new experimental conditions to improve the reaction outcome. This model outperformed a state-of-the-art blackbox optimization algorithm by using 71% fewer steps on both simulations and real reactions. Furthermore, we introduced an efficient exploration strategy by drawing the reaction conditions from certain probability distributions, which resulted in an improvement on regret from 0.062 to 0.039 compared with a deterministic policy. Combining the efficient exploration policy with accelerated microdroplet reactions, optimal reaction conditions were determined in 30 min for the four reactions considered, and a better understanding of the factors that control microdroplet reactions was reached. Moreover, our model showed a better performance after training on reactions with similar or even dissimilar underlying mechanisms, which demonstrates its learning ability. PMID:29296675

The Fate and Impact of Internal Waves in Nearshore Ecosystems.

PubMed

Woodson, C B

2018-01-03

Internal waves are widespread features of global oceans that play critical roles in mixing and thermohaline circulation. Similarly to surface waves, internal waves can travel long distances, ultimately breaking along continental margins. These breaking waves can transport deep ocean water and associated constituents (nutrients, larvae, and acidic low-oxygen waters) onto the shelf and locally enhance turbulence and mixing, with important effects on nearshore ecosystems. We are only beginning to understand the role internal waves play in shaping nearshore ecosystems. Here, I review the physics of internal waves in shallow waters and identify two commonalities among internal waves in the nearshore: exposure to deep offshore waters and enhanced turbulence and mixing. I relate these phenomena to important ecosystem processes ranging from extreme events to fertilization success to draw general conclusions about the influence of internal waves on ecosystems and the effects of internal waves in a changing climate.

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

PubMed

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

2015-12-01

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

Machine Learning and Quantum Mechanics

NASA Astrophysics Data System (ADS)

Chapline, George

The author has previously pointed out some similarities between selforganizing neural networks and quantum mechanics. These types of neural networks were originally conceived of as away of emulating the cognitive capabilities of the human brain. Recently extensions of these networks, collectively referred to as deep learning networks, have strengthened the connection between self-organizing neural networks and human cognitive capabilities. In this note we consider whether hardware quantum devices might be useful for emulating neural networks with human-like cognitive capabilities, or alternatively whether implementations of deep learning neural networks using conventional computers might lead to better algorithms for solving the many body Schrodinger equation.

Issues in deep space radiation protection

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Shinn, J. L.; Tripathi, R. K.; Singleterry, R. C.; Clowdsley, M. S.; Thibeault, S. A.; Cheatwood, F. M.; Schimmerling, W.; Cucinotta, F. A.; Badhwar, G. D.;

Physician-reported practices on continuous deep sedation until death: A descriptive and comparative study.

PubMed

Papavasiliou, Evangelia Evie; Chambaere, Kenneth; Deliens, Luc; Brearley, Sarah; Payne, Sheila; Rietjens, Judith; Vander Stichele, Robert; Van den Block, Lieve

2014-06-01

Research on continuous deep sedation until death has focused on estimating prevalence and describing clinical practice across care settings. However, evidence on sedation practices by physician specialty is scarce. To compare and contrast physician-reported practices on continuous deep sedation until death between general practitioners and medical specialists. A secondary analysis drawing upon data from a large-scale, population-based, retrospective survey among physicians in Flanders, Belgium in 2007. Symptom prevalence and characteristics of sedation (drugs used, artificial nutrition and hydration administered, intentions, and decision-making) were measured. Response rate was 58.4%. The frequency of continuous deep sedation until death among all deaths was 11.3% for general practitioners and 18.4% for medical specialists. General practitioners reported significantly higher rates of severity and mean intensity of pain, delirium, dyspnea, and nausea in the last 24 h of life for sedated patients and a higher number of severe symptoms than medical specialists. No differences were found between groups in the drugs used, except in propofol, reported only by medical specialists (in 15.8% of all cases). Artificial nutrition and hydration was withheld or withdrawn in 97.2% of general practitioner and 36.2% of medical specialist cases. Explicit life-shortening intentions were reported by both groups (for 3%-4% of all cases). Continuous deep sedation until death was initiated without consent or request of either the patient or the family in 27.9% (medical specialists) and 4.7% (general practitioners) of the cases reported. Considerable variation, often largely deviating from professional guidelines, was observed in physician-reported performance and decision-making, highlighting the importance of providing clearer guidance on the specific needs of the context in which continuous deep sedation until death is to be performed. © The Author(s) 2014.

The relationship between the deep-level structure in crust and brewing of strong earthquakes in Xingtai area

NASA Astrophysics Data System (ADS)

Xiao, Lan-Xi; Zhu, Yuan-Qing; Zhang, Shao-Quan; Liu, Xu; Guo, Yu

1999-11-01

In this paper, crust medium is treated as Maxwell medium, and crust model includes hard inclusion, soft inclusion, deep-level fault. The stress concentration and its evolution with time are obtained by using three-dimensional finite element method and differential method. The conclusions are draw as follows: (1) The average stress concentration and maximum shear stress concentration caused by non-heterogeneous of crust are very high in hard inclusion and around the deep fault. With the time passing by, the concentration of average stress in the model gradually trends to uniform. At the same time, the concentration of maximum shear stress in hard inclusion increases gradually. This character is favorable to transfer shear strain energy from soft inclusion to hard inclusion. (2) When the upper mantle beneath the inclusion upheave at a certain velocity of 1 cm/a, the changes of average stress concentration with time become complex, and the boundary of the hard and soft inclusion become unconspicuous, but the maximum shear stress concentration increases much more in the hard inclusion with time at a higher velocity. This feature make for transformation of energy from the soft inclusion to the hard inclusion. (3) The changes of average stress concentration and maximum shear stress concentration with time around the deep-level fault result in further accumulation of maximum shear stress concentration and finally cause the deep-level fault instable and accelerated creep along fault direction. (4) The changes of vertical displacement on the surface of the model, which is caused by the accelerated creep of the deep-level fault, is similar to that of the observation data before Xingtai strong earthquake.

Deep Learning-Based Noise Reduction Approach to Improve Speech Intelligibility for Cochlear Implant Recipients.

PubMed

Lai, Ying-Hui; Tsao, Yu; Lu, Xugang; Chen, Fei; Su, Yu-Ting; Chen, Kuang-Chao; Chen, Yu-Hsuan; Chen, Li-Ching; Po-Hung Li, Lieber; Lee, Chin-Hui

2018-01-20

We investigate the clinical effectiveness of a novel deep learning-based noise reduction (NR) approach under noisy conditions with challenging noise types at low signal to noise ratio (SNR) levels for Mandarin-speaking cochlear implant (CI) recipients. The deep learning-based NR approach used in this study consists of two modules: noise classifier (NC) and deep denoising autoencoder (DDAE), thus termed (NC + DDAE). In a series of comprehensive experiments, we conduct qualitative and quantitative analyses on the NC module and the overall NC + DDAE approach. Moreover, we evaluate the speech recognition performance of the NC + DDAE NR and classical single-microphone NR approaches for Mandarin-speaking CI recipients under different noisy conditions. The testing set contains Mandarin sentences corrupted by two types of maskers, two-talker babble noise, and a construction jackhammer noise, at 0 and 5 dB SNR levels. Two conventional NR techniques and the proposed deep learning-based approach are used to process the noisy utterances. We qualitatively compare the NR approaches by the amplitude envelope and spectrogram plots of the processed utterances. Quantitative objective measures include (1) normalized covariance measure to test the intelligibility of the utterances processed by each of the NR approaches; and (2) speech recognition tests conducted by nine Mandarin-speaking CI recipients. These nine CI recipients use their own clinical speech processors during testing. The experimental results of objective evaluation and listening test indicate that under challenging listening conditions, the proposed NC + DDAE NR approach yields higher intelligibility scores than the two compared classical NR techniques, under both matched and mismatched training-testing conditions. When compared to the two well-known conventional NR techniques under challenging listening condition, the proposed NC + DDAE NR approach has superior noise suppression capabilities and gives less distortion for the key speech envelope information, thus, improving speech recognition more effectively for Mandarin CI recipients. The results suggest that the proposed deep learning-based NR approach can potentially be integrated into existing CI signal processors to overcome the degradation of speech perception caused by noise.

Shear Strengthening of RC Deep Beam Using Externally Bonded GFRP Fabrics

NASA Astrophysics Data System (ADS)

Kumari, A.; Patel, S. S.; Nayak, A. N.

2018-06-01

This work presents the experimental investigation of RC deep beams wrapped with externally bonded Glass Fibre Reinforced Polymer (GFRP) fabrics in order to study the Load versus deflection behavior, cracking pattern, failure modes and ultimate shear strength. A total number of five deep beams have been casted, which is designed with conventional steel reinforcement as per IS: 456 (Indian standard plain and reinforced concrete—code for practice, Bureau of Indian Standards, New Delhi, 2000). The spans to depth ratio for all RC deep beams have been kept less than 2 as per the above specification. Out of five RC deep beams, one without retrofitting serves as a reference beam and the rest four have been wrapped with GFRP fabrics in multiple layers and tested with two point loading condition. The first cracking load, ultimate load and the shear contribution of GFRP to the deep beams have been observed. A critical discussion is made with respect to the enhancement of the strength, behaviour and performance of retrofitted deep beams in comparison to the deep beam without GFRP in order to explore the potential use of GFRP for strengthening the RC deep beams. Test results have demonstrated that the deep beams retrofitted with GFRP shows a slower development of the diagonal cracks and improves shear carrying capacity of the RC deep beam. A comparative study of the experimental results with the theoretical ones predicted by various researchers available in the literatures has also been presented. It is observed that the ultimate load of the beams retrofitted with GFRP fabrics increases with increase of number of GFRP layers up to a specific number of layers, i.e. 3 layers, beyond which it decreases.

Shear Strengthening of RC Deep Beam Using Externally Bonded GFRP Fabrics

NASA Astrophysics Data System (ADS)

Kumari, A.; Patel, S. S.; Nayak, A. N.

2018-02-01

This work presents the experimental investigation of RC deep beams wrapped with externally bonded Glass Fibre Reinforced Polymer (GFRP) fabrics in order to study the Load versus deflection behavior, cracking pattern, failure modes and ultimate shear strength. A total number of five deep beams have been casted, which is designed with conventional steel reinforcement as per IS: 456 (Indian standard plain and reinforced concrete—code for practice, Bureau of Indian Standards, New Delhi, 2000). The spans to depth ratio for all RC deep beams have been kept less than 2 as per the above specification. Out of five RC deep beams, one without retrofitting serves as a reference beam and the rest four have been wrapped with GFRP fabrics in multiple layers and tested with two point loading condition. The first cracking load, ultimate load and the shear contribution of GFRP to the deep beams have been observed. A critical discussion is made with respect to the enhancement of the strength, behaviour and performance of retrofitted deep beams in comparison to the deep beam without GFRP in order to explore the potential use of GFRP for strengthening the RC deep beams. Test results have demonstrated that the deep beams retrofitted with GFRP shows a slower development of the diagonal cracks and improves shear carrying capacity of the RC deep beam. A comparative study of the experimental results with the theoretical ones predicted by various researchers available in the literatures has also been presented. It is observed that the ultimate load of the beams retrofitted with GFRP fabrics increases with increase of number of GFRP layers up to a specific number of layers, i.e. 3 layers, beyond which it decreases.

Fundamental studies on the feasibility of deep eutectic solvents for the selective partition of glaucarubinone present in the roots of Simarouba glauca.

PubMed

Kholiya, Faisal; Bhatt, Nidhi; Rathod, Meena R; Meena, Ramavatar; Prasad, Kamalesh

2015-07-14

Several deep eutectic solvents prepared by the complexation of choline chloride as the hydrogen bond acceptor and hydrogen bond donors such as urea, thiourea, ethylene glycol, and glycerol were employed to partition glaucarubinone, an antimalarial compound present in roots of the plant, Simarouba glauca. Among all the solvents, the deep eutectic solvent consisting of the mixture of choline chloride and urea the most suitable to partition the antimalarial compound from the extract selectively. Analytical tools such as high-performance liquid chromatography and electrospray ionization mass spectrometry were used for characterizations, and glaucarubinone extracted from the roots of the plant by conventional solvent extraction method was used as a reference for comparison. The hydrogen and noncovalent bonds formed between glaucarubinone and the deep eutectic solvents could be responsible for the selective partition of the drug molecule. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sounds of Waitakere: Using Practitioner Research to Explore How Year 6 Recorder Players Compose Responses to Visual Representations of a Natural Environment

ERIC Educational Resources Information Center

Locke, Linda; Locke, Terry

2011-01-01

How might primary students utilise the stimulus of a painting in a collaborative composition drawing on a non-conventional sound palette of their own making? This practitioner research features 17 recorder players from a Year 6 class (10-11-year-olds) who attend a West Auckland primary school in New Zealand. These children were invited to…

Mechanical properties and aesthetics of FRP orthodontic wire fabricated by hot drawing.

PubMed

Imai, T; Watari, F; Yamagata, S; Kobayashi, M; Nagayama, K; Toyoizumi, Y; Nakamura, S

1998-12-01

The FRP wires 0.5 mm in diameter with a multiple fiber structure were fabricated by drawing the fiber polymer complex at 250 degrees C for an esthetic, transparent orthodontic wire. Biocompatible CaO-P2O5-SiO2-Al2O3 (CPSA) glass fibers of 8-20 microm in diameter were oriented unidirectionally in the longitudinal direction in PMMA matrix. The mechanical properties were investigated by 3-point flexural test. The FRP wire showed sufficient strength and a very good elastic recovery after deformation. Young's modulus and the flexural load at deflection 1 mm were nearly independent of the fiber diameter and linearly increased with the fiber fraction. The dependence on fiber fraction obeys well the rule of mixture. This FRP wire could cover the range of strength corresponding to the conventional metal orthodontic wires from Ni-Ti used in the initial stage of orthodontic treatments to Co-Cr used in the final stage by changing the volume ratio of glass fibers with the same external diameter. The estheticity in external appearance was excellent. Thus the new FRP wire can satisfy both mechanical properties necessary for an orthodontic wire and enough estheticity, which was not possible for the conventional metal wire.

Visualization rhetoric: framing effects in narrative visualization.

PubMed

Hullman, Jessica; Diakopoulos, Nicholas

2011-12-01

Narrative visualizations combine conventions of communicative and exploratory information visualization to convey an intended story. We demonstrate visualization rhetoric as an analytical framework for understanding how design techniques that prioritize particular interpretations in visualizations that "tell a story" can significantly affect end-user interpretation. We draw a parallel between narrative visualization interpretation and evidence from framing studies in political messaging, decision-making, and literary studies. Devices for understanding the rhetorical nature of narrative information visualizations are presented, informed by the rigorous application of concepts from critical theory, semiotics, journalism, and political theory. We draw attention to how design tactics represent additions or omissions of information at various levels-the data, visual representation, textual annotations, and interactivity-and how visualizations denote and connote phenomena with reference to unstated viewing conventions and codes. Classes of rhetorical techniques identified via a systematic analysis of recent narrative visualizations are presented, and characterized according to their rhetorical contribution to the visualization. We describe how designers and researchers can benefit from the potentially positive aspects of visualization rhetoric in designing engaging, layered narrative visualizations and how our framework can shed light on how a visualization design prioritizes specific interpretations. We identify areas where future inquiry into visualization rhetoric can improve understanding of visualization interpretation. © 2011 IEEE

Non-conventional solvents in liquid phase microextraction and aqueous biphasic systems.

PubMed

An, Jiwoo; Trujillo-Rodríguez, María J; Pino, Verónica; Anderson, Jared L

2017-06-02

The development of rapid, convenient, and high throughput sample preparation approaches such as liquid phase microextraction techniques have been continuously developed over the last decade. More recently, significant attention has been given to the replacement of conventional organic solvents used in liquid phase microextraction techniques in order to reduce toxic waste and to improve selectivity and/or extraction efficiency. With these objectives, non-conventional solvents have been explored in liquid phase microextraction and aqueous biphasic systems. The utilized non-conventional solvents include ionic liquids, magnetic ionic liquids, and deep eutectic solvents. They have been widely used as extraction solvents or additives in various liquid phase microextraction modes including dispersive liquid-liquid microextraction, single-drop microextraction, hollow fiber-liquid phase microextraction, as well as in aqueous biphasic systems. This review provides an overview into the use of non-conventional solvents in these microextraction techniques in the past 5 years (2012-2016). Analytical applications of the techniques are also discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Melioidosis, Singapore, 2003–2014

PubMed Central

Pang, Long; Harris, Patrick N.A.; Seiler, Rachel L.; Ooi, Peng Lim; Cutter, Jeffrey; Goh, Kee Tai; Cook, Alex R.; Fisher, Dale

2018-01-01

In contrast with northern Australia and Thailand, in Singapore the incidence of melioidosis and co-incidence of melioidosis and pneumonia have declined. Burkholderia pseudomallei deep abscesses increased 20.4% during 2003–2014. These trends could not be explained by the environmental and climatic factors conventionally ascribed to melioidosis. PMID:29260679

Global Ocean Vertical Velocity From a Dynamically Consistent Ocean State Estimate

NASA Astrophysics Data System (ADS)

Liang, Xinfeng; Spall, Michael; Wunsch, Carl

2017-10-01

Estimates of the global ocean vertical velocities (Eulerian, eddy-induced, and residual) from a dynamically consistent and data-constrained ocean state estimate are presented and analyzed. Conventional patterns of vertical velocity, Ekman pumping, appear in the upper ocean, with topographic dominance at depth. Intense and vertically coherent upwelling and downwelling occur in the Southern Ocean, which are likely due to the interaction of the Antarctic Circumpolar Current and large-scale topographic features and are generally canceled out in the conventional zonally averaged results. These "elevators" at high latitudes connect the upper to the deep and abyssal oceans and working together with isopycnal mixing are likely a mechanism, in addition to the formation of deep and abyssal waters, for fast responses of the deep and abyssal oceans to the changing climate. Also, Eulerian and parameterized eddy-induced components are of opposite signs in numerous regions around the global ocean, particularly in the ocean interior away from surface and bottom. Nevertheless, residual vertical velocity is primarily determined by the Eulerian component, and related to winds and large-scale topographic features. The current estimates of vertical velocities can serve as a useful reference for investigating the vertical exchange of ocean properties and tracers, and its complex spatial structure ultimately permits regional tests of basic oceanographic concepts such as Sverdrup balance and coastal upwelling/downwelling.

Wireless power transfer to deep-tissue microimplants

PubMed Central

Yeh, Alexander J.; Neofytou, Evgenios; Kim, Sanghoek; Tanabe, Yuji; Patlolla, Bhagat; Beygui, Ramin E.; Poon, Ada S. Y.

2014-01-01

The ability to implant electronic systems in the human body has led to many medical advances. Progress in semiconductor technology paved the way for devices at the scale of a millimeter or less (“microimplants”), but the miniaturization of the power source remains challenging. Although wireless powering has been demonstrated, energy transfer beyond superficial depths in tissue has so far been limited by large coils (at least a centimeter in diameter) unsuitable for a microimplant. Here, we show that this limitation can be overcome by a method, termed midfield powering, to create a high-energy density region deep in tissue inside of which the power-harvesting structure can be made extremely small. Unlike conventional near-field (inductively coupled) coils, for which coupling is limited by exponential field decay, a patterned metal plate is used to induce spatially confined and adaptive energy transport through propagating modes in tissue. We use this method to power a microimplant (2 mm, 70 mg) capable of closed-chest wireless control of the heart that is orders of magnitude smaller than conventional pacemakers. With exposure levels below human safety thresholds, milliwatt levels of power can be transferred to a deep-tissue (>5 cm) microimplant for both complex electronic function and physiological stimulation. The approach developed here should enable new generations of implantable systems that can be integrated into the body at minimal cost and risk. PMID:24843161

Wireless power transfer to deep-tissue microimplants.

PubMed

Ho, John S; Yeh, Alexander J; Neofytou, Evgenios; Kim, Sanghoek; Tanabe, Yuji; Patlolla, Bhagat; Beygui, Ramin E; Poon, Ada S Y

2014-06-03

The ability to implant electronic systems in the human body has led to many medical advances. Progress in semiconductor technology paved the way for devices at the scale of a millimeter or less ("microimplants"), but the miniaturization of the power source remains challenging. Although wireless powering has been demonstrated, energy transfer beyond superficial depths in tissue has so far been limited by large coils (at least a centimeter in diameter) unsuitable for a microimplant. Here, we show that this limitation can be overcome by a method, termed midfield powering, to create a high-energy density region deep in tissue inside of which the power-harvesting structure can be made extremely small. Unlike conventional near-field (inductively coupled) coils, for which coupling is limited by exponential field decay, a patterned metal plate is used to induce spatially confined and adaptive energy transport through propagating modes in tissue. We use this method to power a microimplant (2 mm, 70 mg) capable of closed-chest wireless control of the heart that is orders of magnitude smaller than conventional pacemakers. With exposure levels below human safety thresholds, milliwatt levels of power can be transferred to a deep-tissue (>5 cm) microimplant for both complex electronic function and physiological stimulation. The approach developed here should enable new generations of implantable systems that can be integrated into the body at minimal cost and risk.

Reducing the stair step effect of layer manufactured surfaces by ball burnishing

NASA Astrophysics Data System (ADS)

Hiegemann, Lars; Agarwal, Chiranshu; Weddeling, Christian; Tekkaya, A. Erman

2016-10-01

The layer technology enables fast and flexible additive manufacturing of forming tools. The disadvantages of this system is the formation of stair steps in the range of tool radii. Within this work a new method to smooth this stair steps by ball burnishing is introduced. This includes studies on the general feasibility of the process and the determination of the influence of the rolling parameters. The investigations are carried out experimentally and numerically. Ultimately, the gained knowledge is applied to finish a deep drawing tool which is manufactured by layer technology.

Environmental philosophy: from theory to practice.

PubMed

Sarkar, Sahotra

2014-03-01

Environmental philosophy is a hybrid discipline drawing extensively from epistemology, ethics, and philosophy of science and analyzing disciplines such as conservation biology, restoration ecology, sustainability studies, and political ecology. The book being discussed both provides an overview of environmental philosophy and develops an anthropocentric framework for it. That framework treats natural values as deep cultural values. Tradeoffs between natural values are analyzed using decision theory to the extent possible, leaving many interesting question for philosophical deliberation. This framework is supposed to be applicable in practical contexts. Copyright © 2013 Elsevier Ltd. All rights reserved.

Advances in the application of holography for NDE

NASA Astrophysics Data System (ADS)

Sciammarella, C. A.

1985-01-01

The basic methodology of holographic interferometry in nondestructive testing (NDT) applications are described. Applications to crack detection in ceramic materials, including a crack 50 microns deep in a turbine blade, are discussed in detail. The theoretical principles of holographic interferometry are explained, and a general description of a holographic interferometric recording system is given. A nondestructive interferometric technique for measuring the gradual erosion of calcareous stones exposed to acid rain is also presented. Detailed line drawings illustrating the hologram recording and interferometric fringe pattern analysis elements in an interferometric holographic NDT device are provided.

Corporal diagnostic work and diagnostic spaces: clinicians' use of space and bodies during diagnosis.

PubMed

Gardner, John; Williams, Clare

2015-06-01

An emerging body of literature in sociology has demonstrated that diagnosis is a useful focal point for understanding the social dimensions of health and illness. This article contributes to this work by drawing attention to the relationship between diagnostic spaces and the way in which clinicians use their own bodies during the diagnostic process. As a case study, we draw upon fieldwork conducted with a multidisciplinary clinical team providing deep brain stimulation (DBS) to treat children with a movement disorder called dystonia. Interviews were conducted with team members and diagnostic examinations were observed. We illustrate that clinicians use communicative body work and verbal communication to transform a material terrain into diagnostic space, and we illustrate how this diagnostic space configures forms of embodied 'sensing-and-acting' within. We argue that a 'diagnosis' can be conceptualised as emerging from an interaction in which space, the clinician-body, and the patient-body (or body-part) mutually configure one another. By conceptualising diagnosis in this way, this article draws attention to the corporal bases of diagnostic power and counters Cartesian-like accounts of clinical work in which the patient-body is objectified by a disembodied medical discourse. © 2015 The Authors. Sociology of Health & Illness © 2015 Foundation for the Sociology of Health & Illness.

Some Findings Concerning Requirements in Agile Methodologies

NASA Astrophysics Data System (ADS)

Rodríguez, Pilar; Yagüe, Agustín; Alarcón, Pedro P.; Garbajosa, Juan

Agile methods have appeared as an attractive alternative to conventional methodologies. These methods try to reduce the time to market and, indirectly, the cost of the product through flexible development and deep customer involvement. The processes related to requirements have been extensively studied in literature, in most cases in the frame of conventional methods. However, conclusions of conventional methodologies could not be necessarily valid for Agile; in some issues, conventional and Agile processes are radically different. As recent surveys report, inadequate project requirements is one of the most conflictive issues in agile approaches and better understanding about this is needed. This paper describes some findings concerning requirements activities in a project developed under an agile methodology. The project intended to evolve an existing product and, therefore, some background information was available. The major difficulties encountered were related to non-functional needs and management of requirements dependencies.

PAX5 methylation detection by droplet digital PCR for ultra-sensitive deep surgical margins analysis of head and neck squamous cell carcinoma

PubMed Central

Hayashi, Masamichi; Guerrero-Preston, Rafael; Sidransky, David; Koch, Wayne M.

2015-01-01

Molecular deep surgical margin analysis has been shown to predict locoregional recurrences of head and neck squamous cell carcinoma (HNSCC). In order to improve the accuracy and versatility of the analysis, we used a highly tumor-specific methylation marker and highly sensitive detection technology to test DNA from surgical margins. Histologically cancer-negative deep surgical margin samples were prospectively collected from 82 eligible HNSCC surgeries by an imprinting procedure (n=75) and primary tissue collection (n=70). Bisulfite treated DNA from each sample was analyzed by both conventional quantitative methylation-specific polymerase chain reaction (QMSP) and QMSP by droplet digital PCR (ddQMSP) targeting PAX5 gene promoter methylation. The association between the presence of PAX5 methylation and locoregional recurrence free survival (LRFS) was evaluated. PAX5 methylation was found in 68.0% (51/75) of tumors in the imprint samples and 71.4% (50/70) in the primary tissue samples. Among cases which did not have postoperative radiation, (n=31 in imprint samples, n=29 in tissue samples), both conventional QMSP and ddQMSP revealed that PAX5 methylation positive margins was significantly associated with poor LRFS by univariate analysis. In particular, ddQMSP increased detection of the PAX5 marker from 29% to 71% in the non-radiated imprint cases. Also, PAX5 methylated imprint margins were an excellent predictor of poor LRFS (HR=3.89, 95%CI:1.19-17.52, P=0.023) by multivariate analysis. PAX5 methylation appears to be an excellent tumor-specific marker for molecular deep surgical margin analysis of HNSCC. Moreover, the ddQMSP assay displays increased sensitivity for methylation marker detection. PMID:26304463

Deep ensemble learning of virtual endoluminal views for polyp detection in CT colonography

NASA Astrophysics Data System (ADS)

Umehara, Kensuke; Näppi, Janne J.; Hironaka, Toru; Regge, Daniele; Ishida, Takayuki; Yoshida, Hiroyuki

2017-03-01

Robust training of a deep convolutional neural network (DCNN) requires a very large number of annotated datasets that are currently not available in CT colonography (CTC). We previously demonstrated that deep transfer learning provides an effective approach for robust application of a DCNN in CTC. However, at high detection accuracy, the differentiation of small polyps from non-polyps was still challenging. In this study, we developed and evaluated a deep ensemble learning (DEL) scheme for reviewing of virtual endoluminal images to improve the performance of computer-aided detection (CADe) of polyps in CTC. Nine different types of image renderings were generated from virtual endoluminal images of polyp candidates detected by a conventional CADe system. Eleven DCNNs that represented three types of publically available pre-trained DCNN models were re-trained by transfer learning to identify polyps from the virtual endoluminal images. A DEL scheme that determines the final detected polyps by a review of the nine types of VE images was developed by combining the DCNNs using a random forest classifier as a meta-classifier. For evaluation, we sampled 154 CTC cases from a large CTC screening trial and divided the cases randomly into a training dataset and a test dataset. At 3.9 falsepositive (FP) detections per patient on average, the detection sensitivities of the conventional CADe system, the highestperforming single DCNN, and the DEL scheme were 81.3%, 90.7%, and 93.5%, respectively, for polyps ≥6 mm in size. For small polyps, the DEL scheme reduced the number of false positives by up to 83% over that of using a single DCNN alone. These preliminary results indicate that the DEL scheme provides an effective approach for improving the polyp detection performance of CADe in CTC, especially for small polyps.

Navigation for the new millennium: Autonomous navigation for Deep Space 1

NASA Technical Reports Server (NTRS)

Reidel, J. E.; Bhaskaran, S.; Synnott, S. P.; Desai, S. D.; Bollman, W. E.; Dumont, P. J.; Halsell, C. A.; Han, D.; Kennedy, B. M.; Null, G. W.;

Advances in deep-UV processing using cluster tools

NASA Astrophysics Data System (ADS)

Escher, Gary C.; Tepolt, Gary; Mohondro, Robert D.

1993-09-01

Deep-UV laser lithography has shown the capability of supporting the manufacture of multiple generations of integrated circuits (ICs) due to its wide process latitude and depth of focus (DOF) for 0.2 micrometers to 0.5 micrometers feature sizes. This capability has been attained through improvements in deep-UV wide field lens technology, excimer lasers, steppers and chemically amplified, positive deep-UV resists. Chemically amplified deep-UV resists are required for 248 nm lithography due to the poor absorption and sensitivity of conventional novolac resists. The acid catalyzation processes of the new resists requires control of the thermal history and environmental conditions of the lithographic process. Work is currently underway at several resist vendors to reduce the need for these controls, but practical manufacturing solutions exist today. One of these solutions is the integration of steppers and resist tracks into a `cluster tool' or `Lithocell' to insure a consistent thermal profile for the resist process and reduce the time the resist is exposed to atmospheric contamination. The work here reports processing and system integration results with a Machine Technology, Inc (MTI) post-exposure bake (PEB) track interfaced with an advanced GCA XLS 7800 deep-UV stepper [31 mm diameter, variable NA (0.35 - 0.53) and variable sigma (0.3 - 0.74)].

Deep-sea genetic resources: New frontiers for science and stewardship in areas beyond national jurisdiction

NASA Astrophysics Data System (ADS)

Harden-Davies, Harriet

2017-03-01

The deep-sea is a large source of marine genetic resources (MGR), which have many potential uses and are a growing area of research. Much of the deep-sea lies in areas beyond national jurisdiction (ABNJ), including 65% of the global ocean. MGR in ABNJ occupy a significant gap in the international legal framework. Access and benefit sharing of MGR is a key issue in the development of a new international legally-binding instrument under the United Nations Convention on the Law of the Sea (UNCLOS) for the conservation and sustainable use of marine biological diversity in ABNJ. This paper examines how this is relevant to deep-sea scientific research and identifies emerging challenges and opportunities. There is no internationally agreed definition of MGR, however, deep-sea genetic resources could incorporate any biological material including genes, proteins and natural products. Deep-sea scientific research is the key actor accessing MGR in ABNJ and sharing benefits such as data, samples and knowledge. UNCLOS provides the international legal framework for marine scientific research, international science cooperation, capacity building and marine technology transfer. Enhanced implementation could support access and benefit sharing of MGR in ABNJ. Deep-sea scientific researchers could play an important role in informing practical new governance solutions for access and benefit sharing of MGR that promote scientific research in ABNJ and support deep-sea stewardship. Advancing knowledge of deep-sea biodiversity in ABNJ, enhancing open-access to data and samples, standardisation and international marine science cooperation are significant potential opportunity areas.

Fast deswelling of nanocomposite polymer hydrogels via magnetic field-induced heating for emerging FO desalination.

PubMed

Razmjou, Amir; Barati, Mohammad Reza; Simon, George P; Suzuki, Kiyonori; Wang, Huanting

2013-06-18

Freshwater shortage is one of the most pressing global issues. Forward osmosis (FO) desalination technology is emerging for freshwater production from saline water, which is potentially more energy-efficient than the current reverse osmosis process. However, the lack of a suitable draw solute is the major hurdle for commercial implementation of the FO desalination technology. We have previously reported that thermoresponsive hydrogels can be used as the draw agent for a FO process, and this new hydrogel-driven FO process holds promise for further development for practical application. In the present work, magnetic field-induced heating is explored for the purpose of developing a more effective way to recover water from swollen hydrogel draw agents. The composite hydrogel particles are prepared by copolymerization of sodium acrylate and N-isopropylacrylamide in the presence of magnetic nanoparticles (γ-Fe2O3, <50 nm). The results indicate that the magnetic heating is an effective and rapid method for dewatering of hydrogels by generating the heat more uniformly throughout the draw agent particles, and thus, a dense skin layer commonly formed via conventional heating from the outside of the particle is minimized. The FO dewatering performance is affected by the loading of magnetic nanoparticles and magnetic field intensity. Significantly enhanced liquid water recovery (53%) is achieved under magnetic heating, as opposed to only around 7% liquid water recovery obtained via convection heating. Our study shows that the magnetic heating is an attractive alternative stimulus for the extraction of highly desirable liquid water from the draw agent in the polymer hydrogel-driven forward osmosis process.

Deep neural networks to enable real-time multimessenger astrophysics

NASA Astrophysics Data System (ADS)

George, Daniel; Huerta, E. A.

2018-02-01

Gravitational wave astronomy has set in motion a scientific revolution. To further enhance the science reach of this emergent field of research, there is a pressing need to increase the depth and speed of the algorithms used to enable these ground-breaking discoveries. We introduce Deep Filtering—a new scalable machine learning method for end-to-end time-series signal processing. Deep Filtering is based on deep learning with two deep convolutional neural networks, which are designed for classification and regression, to detect gravitational wave signals in highly noisy time-series data streams and also estimate the parameters of their sources in real time. Acknowledging that some of the most sensitive algorithms for the detection of gravitational waves are based on implementations of matched filtering, and that a matched filter is the optimal linear filter in Gaussian noise, the application of Deep Filtering using whitened signals in Gaussian noise is investigated in this foundational article. The results indicate that Deep Filtering outperforms conventional machine learning techniques, achieves similar performance compared to matched filtering, while being several orders of magnitude faster, allowing real-time signal processing with minimal resources. Furthermore, we demonstrate that Deep Filtering can detect and characterize waveform signals emitted from new classes of eccentric or spin-precessing binary black holes, even when trained with data sets of only quasicircular binary black hole waveforms. The results presented in this article, and the recent use of deep neural networks for the identification of optical transients in telescope data, suggests that deep learning can facilitate real-time searches of gravitational wave sources and their electromagnetic and astroparticle counterparts. In the subsequent article, the framework introduced herein is directly applied to identify and characterize gravitational wave events in real LIGO data.

Tapered polysilicon core fibers for nonlinear photonics.

PubMed

Suhailin, Fariza H; Shen, Li; Healy, Noel; Xiao, Limin; Jones, Maxwell; Hawkins, Thomas; Ballato, John; Gibson, Ursula J; Peacock, Anna C

2016-04-01

We propose and demonstrate a novel approach to obtaining small-core polysilicon waveguides from the silicon fiber platform. The fibers were fabricated via a conventional drawing tower method and, subsequently, tapered down to achieve silicon core diameters of ∼1  μm, the smallest optical cores for this class of fiber to date. Characterization of the material properties have shown that the taper process helps to improve the local crystallinity of the silicon core, resulting in a significant reduction in the material loss. By exploiting the combination of small cores and low losses, these tapered fibers have enabled the first observation of nonlinear transmission within a polycrystalline silicon waveguide of any type. As the fiber drawing method is highly scalable, it opens a route for the development of low-cost and flexible nonlinear silicon photonic systems.

Theoretical simulation of the dual-heat-flux method in deep body temperature measurements.

PubMed

Huang, Ming; Chen, Wenxi

2010-01-01

Deep body temperature reveals individual physiological states, and is important in patient monitoring and chronobiological studies. An innovative dual-heat-flux method has been shown experimentally to be competitive with the conventional zero-heat-flow method in its performance, in terms of measurement accuracy and step response to changes in the deep temperature. We have utilized a finite element method to model and simulate the dynamic process of a dual-heat-flux probe in deep body temperature measurements to validate the fundamental principles of the dual-heat-flux method theoretically, and to acquire a detailed quantitative description of the thermal profile of the dual-heat-flux probe. The simulation results show that the estimated deep body temperature is influenced by the ambient temperature (linearly, at a maximum rate of 0.03 °C/°C) and the blood perfusion rate. The corresponding depth of the estimated temperature in the skin and subcutaneous tissue layer is consistent when using the dual-heat-flux probe. Insights in improving the performance of the dual-heat-flux method were discussed for further studies of dual-heat-flux probes, taking into account structural and geometric considerations.

Anchorage performance of a high-pressure pre-tightening resin anchor with a compressed grouting body

PubMed Central

Tian, Jiansheng; Hu, Li

2017-01-01

Supports for deep mine roadways located in soft surrounding rock face several problems: difficulty in applying pre-tightening force, low bearing capacity, and poor initial support. To solve these problems, this study proposes a high-pressure pre-tightening resin anchor with a compressed grouting body for use in soft and fractured rock surrounding a deep roadway. Using model experiments, we analyzed the anchorage performance of the proposed anchor and a conventional tensile-type anchor for three different values of the elastic modulus of the surrounding rock. The results showed that regardless of the surrounding rock type, the peak micro-strain (642–541) and displacement (6.09–6.5 mm) at the pull-out end of the proposed anchor were always smaller than the peak micro-strain (1433–1105) and displacement (8.77–9.2 mm) at the pull-out end of the conventional anchor. Furthermore, as the anchor’s pre-tightening force increased from 20 kN to 120 kN, the anchor’s strain remained concentrated over a length of 0.4 m from the bearing end. Compared with conventional tensile-type anchors, the proposed high-pressure pre-tightening resin anchor with a compressed grouting body has a higher ultimate bearing capacity, allows the grouting length to be decreased to 0.4 m, and provides initial support resistance. PMID:28196084

Application of natural deep eutectic solvents to the extraction of anthocyanins from Catharanthus roseus with high extractability and stability replacing conventional organic solvents.

PubMed

Dai, Yuntao; Rozema, Evelien; Verpoorte, Robert; Choi, Young Hae

2016-02-19

Natural deep eutectic solvents (NADES) have attracted a great deal of attention in recent times as promising green media. They are generally composed of neutral, acidic or basic compounds that form liquids of high viscosity when mixed in certain molar ratio. Despite their potential, viscosity and acid or basic nature of some ingredients may affect the extraction capacity and stabilizing ability of the target compounds. To investigate these effects, extraction with a series of NADES was employed for the analysis of anthocyanins in flower petals of Catharanthus roseus in combination with HPLC-DAD-based metabolic profiling. Along with the extraction yields of anthocyanins their stability in NADES was also studied. Multivariate data analysis indicates that the lactic acid-glucose (LGH), and 1,2-propanediol-choline chloride (PCH) NADES present a similar extraction power for anthocyanins as conventional organic solvents. Furthermore, among the NADES employed, LGH exhibits an at least three times higher stabilizing capacity for cyanidins than acidified ethanol, which facilitates their extraction and analysis process. Comparing NADES to the conventional organic solvents, in addition to their reduced environmental impact, they proved to provide higher stability for anthocyanins, and therefore have a great potential as possible alternatives to those organic solvents in health related areas such as food, pharmaceuticals and cosmetics. Copyright © 2016 Elsevier B.V. All rights reserved.

High Aspect-Ratio Neural Probes using Conventional Blade Dicing

NASA Astrophysics Data System (ADS)

Goncalves, S. B.; Ribeiro, J. F.; Silva, A. F.; Correia, J. H.

2016-10-01

Exploring deep neural circuits has triggered the development of long penetrating neural probes. Moreover, driven by brain displacement, the long neural probes require also a high aspect-ratio shafts design. In this paper, a simple and reproducible method of manufacturing long-shafts neural probes using blade dicing technology is presented. Results shows shafts up to 8 mm long and 200 µm wide, features competitive to the current state-of-art, being its outline simply accomplished by a single blade dicing program. Therefore, conventional blade dicing presents itself as a viable option to manufacture long neural probes.

Enhanced Virtual Presence for Immersive Visualization of Complex Situations for Mission Rehearsal

DTIC Science & Technology

1997-06-01

taken. We propose to join both these technologies together in a registration device . The registration device would be small and portable and easily...registering the panning of the camera (or other sensing device ) and also stitch together the shots to automatically generate panoramic files necessary to...database and as the base information changes each of the linked drawings is automatically updated. Filename Format A specific naming convention should be

Enculturating Seamless Language Learning through Artifact Creation and Social Interaction Process

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Chai, Ching Sing; Aw, Guat Poh; King, Ronnel B.

2015-01-01

This paper reports a design-based research (DBR) cycle of MyCLOUD (My Chinese ubiquitOUs learning Days). MyCLOUD is a seamless language learning model that addresses identified limitations of conventional Chinese language teaching, such as the decontextualized and unauthentic learning processes that usually hinder reflection and deep learning.…

Cranial MR imaging findings of potassium chlorate intoxication.

PubMed

Mutlu, Hakan; Silit, Emir; Pekkafali, Zekai; Basekim, C Cinar; Kizilkaya, Esref; Ay, Hakan; Karsli, A Fevzi

2003-08-01

We present the case of a patient who attempted suicide by ingesting matchstick heads (55% potassium chlorate). The patient presented to the emergency room with loss of consciousness, and MR imaging revealed symmetric hyperintense signal within the deep gray matter and medial temporal lobes. The patient improved after undergoing conventional treatment and hyperbaric oxygen.

Supercritical CO2 drying of poly(methyl methacrylate) photoresist for deep x-ray lithography: a brief note

NASA Astrophysics Data System (ADS)

Shukla, Rahul; Abhinandan, Lala; Sharma, Shivdutt

2017-07-01

Poly(methyl methacrylate) (PMMA) is an extensively used positive photoresist for deep x-ray lithography. The post-development release of the microstructures of PMMA becomes very critical for high aspect ratio fragile and freestanding microstructures. Release of high aspect ratio comb-drive microstructure of PMMA made by one-step x-ray lithography (OXL) is studied. The effect of low-surface tension Isopropyl alcohol (IPA) over water is investigated for release of the high aspect ratio microstructures using conventional and supercritical (SC) CO2 drying. The results of conventional drying are also compared for the samples released or dried in both in-house developed and commercial SC CO2 dryer. It is found that in all cases the microstructures of PMMA are permanently deformed and damaged while using SC CO2 for drying. For free-standing high aspect ratio microstructures of PMMA made by OXL, it is advised to use low-surface tension IPA over DI water. However, this brings a limitation on the design of the microstructure.

Novel Zero-Heat-Flux Deep Body Temperature Measurement in Lower Extremity Vascular and Cardiac Surgery.

PubMed

Mäkinen, Marja-Tellervo; Pesonen, Anne; Jousela, Irma; Päivärinta, Janne; Poikajärvi, Satu; Albäck, Anders; Salminen, Ulla-Stina; Pesonen, Eero

2016-08-01

The aim of this study was to compare deep body temperature obtained using a novel noninvasive continuous zero-heat-flux temperature measurement system with core temperatures obtained using conventional methods. A prospective, observational study. Operating room of a university hospital. The study comprised 15 patients undergoing vascular surgery of the lower extremities and 15 patients undergoing cardiac surgery with cardiopulmonary bypass. Zero-heat-flux thermometry on the forehead and standard core temperature measurements. Body temperature was measured using a new thermometry system (SpotOn; 3M, St. Paul, MN) on the forehead and with conventional methods in the esophagus during vascular surgery (n = 15), and in the nasopharynx and pulmonary artery during cardiac surgery (n = 15). The agreement between SpotOn and the conventional methods was assessed using the Bland-Altman random-effects approach for repeated measures. The mean difference between SpotOn and the esophageal temperature during vascular surgery was+0.08°C (95% limit of agreement -0.25 to+0.40°C). During cardiac surgery, during off CPB, the mean difference between SpotOn and the pulmonary arterial temperature was -0.05°C (95% limits of agreement -0.56 to+0.47°C). Throughout cardiac surgery (on and off CPB), the mean difference between SpotOn and the nasopharyngeal temperature was -0.12°C (95% limits of agreement -0.94 to+0.71°C). Poor agreement between the SpotOn and nasopharyngeal temperatures was detected in hypothermia below approximately 32°C. According to this preliminary study, the deep body temperature measured using the zero-heat-flux system was in good agreement with standard core temperatures during lower extremity vascular and cardiac surgery. However, agreement was questionable during hypothermia below 32°C. Copyright © 2016 Elsevier Inc. All rights reserved.

Declining conventional cancer treatment and using complementary and alternative medicine: a problem or a challenge?

PubMed

Verhoef, M J; Rose, M S; White, M; Balneaves, L G

2008-08-01

Several studies have shown that a small but significant percentage of cancer patients decline one or more conventional cancer treatments and use complementary and alternative medicine (CAM) instead. Here, drawing on the literature and on our own ongoing research, we describe why cancer patients decide to decline conventional cancer treatments, who those patients are, and the response by physicians to patients who make such decisions. Poor doctor-patient communication, the emotional impact of the cancer diagnosis, perceived severity of conventional treatment side effects, a high need for decision-making control, and strong beliefs in holistic healing appear to affect the decision by patients to decline some or all conventional cancer treatments. Many patients indicate that they value ongoing follow-up care from their oncologists provided that the oncologists respect their beliefs. Patients declining conventional treatments have a strong sense of internal control and prefer to make the final treatment decisions after considering the opinions of their doctors. Few studies have looked at the response by physicians to patients making such a decision. Where research has been done, it found that a tendency by doctors to dichotomize patient decisions as rational or irrational may interfere with the ability of the doctors to respond with sensitivity and understanding. Declining conventional treatment is not necessarily an indicator of distrust of the medical system, but rather a reflection of many personal factors. Accepting and respecting such decisions may be instrumental in "keeping the door open."

Seismic anisotropy of the crystalline crust: What does it tell us?

USGS Publications Warehouse

Rabbel, Wolfgang; Mooney, Walter D.

1996-01-01

The study of the directional dependence of seismic velocities (seismic anisotropy) promises more refined insight into mineral composition and physical properties of the crystalline crust than conventional deep seismic refraction or reflection profiles providing average values of P-and S-wave velocities. The alignment of specific minerals by ductile rock deformation, for instance, causes specific types of seismic anisotropy which can be identified by appropriate field measurements.Vice versa, the determination of anisotropy can help to discriminate between different rock candidates in the deep crust. Seismic field measurements at the Continental Deep Drilling Site (KTB, S Germany) are shown as an example that anisotropy has to be considered in crustal studies. At the KTB, the dependence of seismic velocity on the direction of wave propagation in situ was found to be compatible with the texture, composition and fracture density of drilled crustal rocks.

Objective Classification of Radar Profile Types, and Their Relationship to Lightning Occurrence

NASA Technical Reports Server (NTRS)

Boccippio, Dennis

2003-01-01

A cluster analysis technique is used to identify 16 "archetypal" vertical radar profile types from a large, globally representative sample of profiles from the TRMM Precipitation Radar. These include nine convective types (7 of these deep convective) and seven stratiform types (5 of these clearly glaciated). Radar profile classification provides an alternative to conventional deep convective storm metrics, such as 30 dBZ echo height, maximum reflectivity or VIL. As expected, the global frequency of occurrence of deep convective profile types matches satellite-observed total lightning production, including to very small scall local features. Each location's "mix" of profile types provides an objective description of the local convective spectrum, and in turn, is a first step in objectively classifying convective regimes. These classifiers are tested as inputs to a neural network which attempts to predict lightning occurrence based on radar-only storm observations, and performance is compared with networks using traditional radar metrics as inputs.

Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer

NASA Astrophysics Data System (ADS)

Weng, Sheng; Xu, Xiaoyun; Li, Jiasong; Wong, Stephen T. C.

2017-10-01

Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging.

Quicklook Constituent Abundance and Stretch Parameter Retrieval for the Juno Microwave Radiometer using Neural Networks

NASA Astrophysics Data System (ADS)

Bellotti, A.; Steffes, P. G.

2016-12-01

The Juno Microwave Radiometer (MWR) has six channels ranging from 1.36-50 cm and the ability to peer deep into the Jovian atmosphere. An Artifical Neural Network algorithm has been developed to rapidly perform inversion for the deep abundance of ammonia, the deep abundance of water vapor, and atmospheric "stretch" (a parameter that reflects the deviation from a wet adiabate in the higher atmosphere). This algorithm is "trained" by using simulated emissions at the six wavelengths computed using the Juno atmospheric microwave radiative transfer (JAMRT) model presented by Oyafuso et al. (This meeting). By exploiting the emission measurements conducted at six wavelengths and at various incident angles, the neural network can provide preliminary results to a useful precison in a computational method hundreds of times faster than conventional methods. This can quickly provide important insights into the variability and structure of the Jovian atmosphere.

Deep Invasive Fungal Infection of the Hand in a Child Mimicking a Local Gigantism.

PubMed

Chatterjee, Anirban; Chatterjee, Shamita

2018-04-01

Subcutaneous and deep fungal infections in the hand are rare among children. These are usually found in immunocompromised adults or in persons engaged in soil handling activities, due to direct exposure, especially in the tropics. Delay in diagnosis is usual because pyogenic and other granulomatous infections are considered first. The authors present the case of a healthy, immunocompetent 2½-year-old child who presented with progressive swelling of the right hand mimicking a localized gigantism of the entire hand. Multiple operative drainage procedures done previously had failed to resolve the condition. A biopsy established the presence of fungal hyphae, thus confirming the diagnosis of deep fungal infection of the hand and guided proper therapeutic intervention. A strong index of suspicion needs to be maintained in cases not responding to conventional antibacterial therapy, and both microbiologic and histopathologic samples need to be obtained to establish the diagnosis.

Deep learning for computational biology.

PubMed

Angermueller, Christof; Pärnamaa, Tanel; Parts, Leopold; Stegle, Oliver

2016-07-29

Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within them, and for making accurate predictions. In this review, we discuss applications of this new breed of analysis approaches in regulatory genomics and cellular imaging. We provide background of what deep learning is, and the settings in which it can be successfully applied to derive biological insights. In addition to presenting specific applications and providing tips for practical use, we also highlight possible pitfalls and limitations to guide computational biologists when and how to make the most use of this new technology. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

Enhanced perfusion defect clarity and inhomogeneity in smokers' lungs with deep-inspiratory breath-hold perfusion SPECT images.

PubMed

Suga, Kazuyoshi; Yasuhiko, Kawakami; Iwanaga, Hideyuki; Hayashi, Norio; Yamashita, Tomio; Matsunaga, Naofumi

2005-09-01

Deep-inspiratory breath-hold (DIBrH) Tc-99m-macroaggregated albumin (MAA) SPECT images were developed to accurately evaluate perfusion impairment in smokers' lungs. DIBrH SPECT was performed in 28 smokers with or without low attenuation areas (LAA) on CT images, using a triple-headed SPECT system and a laser light respiratory tracking device. DIBrH SPECT images were reconstructed from every 4 degrees projection of five adequate 360 degrees projection data sets with almost the same respiratory dimension at 20 sec DIBrH. Perfusion defect clarity was assessed by the lesion (defect)-to-contralateral normal lung count ratios (L/N ratios). Perfusion inhomogeneity was assessed by the coefficient of variation (CV) values of pixel counts and correlated with the diffusing capacity of the lungs for carbon monoxide/alveolar volume (DLCO/VA) ratios. The results were compared with those on conventional images. Five DIBrH projection data sets with minimal dimension differences of 2.9+/-0.6 mm were obtained in all subjects. DIBrH images enhanced perfusion defects compared with conventional images, with significantly higher L/N ratios (P<0.0001), and detected a total of 109 (26.9%) additional detects (513 vs. 404), with excellent inter-observer agreement (kappa value of 0.816). CV values in the smokers' lungs on DIBrH images were also significantly higher compared with those on conventional images (0.31+/-0.10 vs. 0.19+/-0.06, P<0.0001). CV values in smokers on DIBrH images showed a significantly closer correlation with DLCO/VA ratios compared with conventional images (R = 0.872, P<0.0001 vs. R=0.499, P<0.01). By reducing adverse effect of respiratory motion, DIBrH SPECT images enhance perfusion defect clarity and inhomogeneity, and provide more accurate assessment of impaired perfusion in smokers' lungs compared with conventional images.

Bottom-up and top-down triggers of diversification: A new look at the evolutionary ecology of scavenging amphipods in the deep sea

NASA Astrophysics Data System (ADS)

Havermans, Charlotte; Smetacek, Victor

2018-05-01

The initial, anthropocentric view of the deep ocean was that of a hostile environment inhabited by organisms rendered lethargic by constant high pressure, low temperature and sparse food supply, hence evolving slowly. This conceptual framework of a spatially and temporally homogeneous, connected, strongly bottom-up controlled habitat implied a strong constraint on, or poor incentive for, speciation. Hence, the discovery in the late 1960s of high species diversity of abyssal benthic invertebrates came as a surprise. Since then, the slow-motion view of deep-sea ecology and evolution has speeded up and diversified in the light of increasing evidence accumulating from in situ visual observations complemented by molecular and other tools. The emerging picture is that of a much livelier, highly diversified and more complex deep-sea fauna than previously assumed. In this review we examine the consequences of the incoming information for developing a broader view of evolutionary ecology in the deep sea, and for scavenging amphipods in particular. We revisit the food supply to the deep-sea floor and hypothesize that the dead bodies of animals, ranging from zooplankton to large fish are likely to be a more important source of food than their friable faeces. Camera observations of baited traps indicate that amphipod carrion-feeders arrive within hours at the bait which continues to draw new individuals for days to months later, presumably by scent trails in tidal currents. We explore the different stages of food acquisition upon which natural selection may have acted, from detection to ingestion, and discuss the possibility of a broader range of food acquisition strategies, including predation and specializations. Although currently neglected in deep-sea ecology, top-down factors are likely to play a more important role in the evolution of deep-sea organisms. Predation on amphipods at baits by bathyal and abyssal fishes, and large predatory crustaceans in the hadal zone, is often observed. Finally, we develop hypotheses regarding the effects of past, present and imminent anthropogenic activities on scavenger biomass and how these can be tested with the most modern tools.

Influence of Drawbeads in Deep-Drawing of Plane-Strain Channel Sections: Experimental and FE Analysis

NASA Astrophysics Data System (ADS)

Oliveira, M. C.; Baptista, A. J.; Alves, J. L.; Menezes, L. F.; Green, D. E.; Ghaei, A.

2007-05-01

The main purpose of the "Numisheet'05 Benchmark♯3: Channel Draw/Cylindrical Cup" was to evaluate the forming characteristics of materials in multi-stage processes. The concept was to verify the strain fields achieved during the two stage forming process and also to test the ability of numerical models to predict both strain and stress fields. The first stage consisted of forming channel sections in an industrial-scale channel draw die. The material that flows through the drawbead and over the die radii into the channel sidewalls is prestrained by cyclic bending and unbending. The prestrained channel sidewalls are subsequently cut and subjected to near plane-strain Marciniak-style cup test. This study emphasizes the analysis of the first stage process, the Channel Draw, since accurate numerical results for the first stage forming and springback are essential to guarantee proper initial state variables for the subsequent stage simulation. Four different sheet materials were selected: mild steel AKDQ-HDG, high strength steel HSLA-HDG, dual phase steel DP600-HDG and an aluminium alloy AA6022-T43. The four sheet materials were formed in the same channel draw die, but with drawbead penetrations of 25%, 50% and 100%. This paper describes the testing and measurement procedures for the numerical simulation of these conditions with DD3IMP FE code. A comparison between experimental and numerical simulation results for the first stage is presented. The experimental results indicate that an increase in drawbead penetration is accompanied by a general decrease in springback, with both sidewall radius of curvature and the sidewall angle increasing with increasing drawbead penetration. An exception to this trend occurs at the shallowest bead penetration: the radius of curvature in the sidewall is larger than expected. The sequence of cyclic tension and compression is numerically studied for each drawbead penetration in order to investigate this phenomenon.

Imbalance aware lithography hotspot detection: a deep learning approach

NASA Astrophysics Data System (ADS)

Yang, Haoyu; Luo, Luyang; Su, Jing; Lin, Chenxi; Yu, Bei

2017-03-01

With the advancement of VLSI technology nodes, light diffraction caused lithographic hotspots have become a serious problem affecting manufacture yield. Lithography hotspot detection at the post-OPC stage is imperative to check potential circuit failures when transferring designed patterns onto silicon wafers. Although conventional lithography hotspot detection methods, such as machine learning, have gained satisfactory performance, with extreme scaling of transistor feature size and more and more complicated layout patterns, conventional methodologies may suffer from performance degradation. For example, manual or ad hoc feature extraction in a machine learning framework may lose important information when predicting potential errors in ultra-large-scale integrated circuit masks. In this paper, we present a deep convolutional neural network (CNN) targeting representative feature learning in lithography hotspot detection. We carefully analyze impact and effectiveness of different CNN hyper-parameters, through which a hotspot-detection-oriented neural network model is established. Because hotspot patterns are always minorities in VLSI mask design, the training data set is highly imbalanced. In this situation, a neural network is no longer reliable, because a trained model with high classification accuracy may still suffer from high false negative results (missing hotspots), which is fatal in hotspot detection problems. To address the imbalance problem, we further apply minority upsampling and random-mirror flipping before training the network. Experimental results show that our proposed neural network model achieves highly comparable or better performance on the ICCAD 2012 contest benchmark compared to state-of-the-art hotspot detectors based on deep or representative machine leaning.

Deep, noninvasive imaging and surgical guidance of submillimeter tumors using targeted M13-stabilized single-walled carbon nanotubes

PubMed Central

Ghosh, Debadyuti; Bagley, Alexander F.; Na, Young Jeong; Birrer, Michael J.; Bhatia, Sangeeta N.; Belcher, Angela M.

2014-01-01

Highly sensitive detection of small, deep tumors for early diagnosis and surgical interventions remains a challenge for conventional imaging modalities. Second-window near-infrared light (NIR2, 950–1,400 nm) is promising for in vivo fluorescence imaging due to deep tissue penetration and low tissue autofluorescence. With their intrinsic fluorescence in the NIR2 regime and lack of photobleaching, single-walled carbon nanotubes (SWNTs) are potentially attractive contrast agents to detect tumors. Here, targeted M13 virus-stabilized SWNTs are used to visualize deep, disseminated tumors in vivo. This targeted nanoprobe, which uses M13 to stably display both tumor-targeting peptides and an SWNT imaging probe, demonstrates excellent tumor-to-background uptake and exhibits higher signal-to-noise performance compared with visible and near-infrared (NIR1) dyes for delineating tumor nodules. Detection and excision of tumors by a gynecological surgeon improved with SWNT image guidance and led to the identification of submillimeter tumors. Collectively, these findings demonstrate the promise of targeted SWNT nanoprobes for noninvasive disease monitoring and guided surgery. PMID:25214538

Deep, noninvasive imaging and surgical guidance of submillimeter tumors using targeted M13-stabilized single-walled carbon nanotubes.

PubMed

Ghosh, Debadyuti; Bagley, Alexander F; Na, Young Jeong; Birrer, Michael J; Bhatia, Sangeeta N; Belcher, Angela M

2014-09-23

Highly sensitive detection of small, deep tumors for early diagnosis and surgical interventions remains a challenge for conventional imaging modalities. Second-window near-infrared light (NIR2, 950-1,400 nm) is promising for in vivo fluorescence imaging due to deep tissue penetration and low tissue autofluorescence. With their intrinsic fluorescence in the NIR2 regime and lack of photobleaching, single-walled carbon nanotubes (SWNTs) are potentially attractive contrast agents to detect tumors. Here, targeted M13 virus-stabilized SWNTs are used to visualize deep, disseminated tumors in vivo. This targeted nanoprobe, which uses M13 to stably display both tumor-targeting peptides and an SWNT imaging probe, demonstrates excellent tumor-to-background uptake and exhibits higher signal-to-noise performance compared with visible and near-infrared (NIR1) dyes for delineating tumor nodules. Detection and excision of tumors by a gynecological surgeon improved with SWNT image guidance and led to the identification of submillimeter tumors. Collectively, these findings demonstrate the promise of targeted SWNT nanoprobes for noninvasive disease monitoring and guided surgery.

Database Technology Activities and Assessment for Defense Modeling and Simulation Office (DMSO) (August 1991-November 1992). A Documented Briefing

DTIC Science & Technology

1994-01-01

databases and identifying new data entities, data elements, and relationships . - Standard data naming conventions, schema, and definition processes...management system. The use of such a tool could offer: (1) structured support for representation of objects and their relationships to each other (and...their relationships to related multimedia objects such as an engineering drawing of the tank object or a satellite image that contains the installation

Direct Digital Control of HVAC (Heating, Ventilating, and Air Conditioning Equipment (User’s Guide)

DTIC Science & Technology

1985-01-01

reset, load shedding, chiller optimization , VAV fan synchronization, and optimum start/stop. The prospective buyer of a DDC system should investigate...current and accurate drawings for a conventional, built-up control system such as that illustrated in Fig- ure 4. Data on setpoints , reset schedules, and...are always available in the form of the computer program code (Figure 7). In addition to the control logic, setpoint and other data are readily

Valve for fluid control

DOEpatents

Oborny, Michael C.; Paul, Phillip H.; Hencken, Kenneth R.; Frye-Mason, Gregory C.; Manginell, Ronald P.

2001-01-01

A valve for controlling fluid flows. This valve, which includes both an actuation device and a valve body provides: the ability to incorporate both the actuation device and valve into a unitary structure that can be placed onto a microchip, the ability to generate higher actuation pressures and thus control higher fluid pressures than conventional microvalves, and a device that draws only microwatts of power. An electrokinetic pump that converts electric potential to hydraulic force is used to operate, or actuate, the valve.

Inferring common cognitive mechanisms from brain blood-flow lateralization data: a new methodology for fTCD analysis.

PubMed

Meyer, Georg F; Spray, Amy; Fairlie, Jo E; Uomini, Natalie T

2014-01-01

Current neuroimaging techniques with high spatial resolution constrain participant motion so that many natural tasks cannot be carried out. The aim of this paper is to show how a time-locked correlation-analysis of cerebral blood flow velocity (CBFV) lateralization data, obtained with functional TransCranial Doppler (fTCD) ultrasound, can be used to infer cerebral activation patterns across tasks. In a first experiment we demonstrate that the proposed analysis method results in data that are comparable with the standard Lateralization Index (LI) for within-task comparisons of CBFV patterns, recorded during cued word generation (CWG) at two difficulty levels. In the main experiment we demonstrate that the proposed analysis method shows correlated blood-flow patterns for two different cognitive tasks that are known to draw on common brain areas, CWG, and Music Synthesis. We show that CBFV patterns for Music and CWG are correlated only for participants with prior musical training. CBFV patterns for tasks that draw on distinct brain areas, the Tower of London and CWG, are not correlated. The proposed methodology extends conventional fTCD analysis by including temporal information in the analysis of cerebral blood-flow patterns to provide a robust, non-invasive method to infer whether common brain areas are used in different cognitive tasks. It complements conventional high resolution imaging techniques.

Local heat treatment of high strength steels with zoom-optics and 10kW-diode laser

NASA Astrophysics Data System (ADS)

Baumann, Markus; Krause, Volker; Bergweiler, Georg; Flaischerowitz, Martin; Banik, Janko

2012-03-01

High strength steels enable new solutions for weight optimized car bodies without sacrificing crash safety. However, cold forming of these steels is limited due to the need of high press capacity, increased tool wear, and limitations in possible geometries. One can compensate for these drawbacks by local heat treatment of the blanks. In high-deformation areas the strength of the material is reduced and the plasticity is increased by diode laser irradiation. Local heat treatment with diode laser radiation could also yield key benefits for the applicability of press hardened parts. High strength is not desired all over the part. Joint areas or deformation zones for requested crash properties require locally reduced strength. In the research project "LOKWAB" funded by the German Federal Ministry of Education and Research (BMBF), heat treatment of high strength steels was investigated in cooperation with Audi, BMW, Daimler, ThyssenKrupp, Fraunhofer- ILT, -IWU and others. A diode laser with an output power of 10 kW was set up to achieve acceptable process speed. Furthermore a homogenizing zoom-optics was developed, providing a rectangular focus with homogeneous power density. The spot size in x- and y-direction can be changed independently during operation. With pyrometer controlled laser power the surface temperature is kept constant, thus the laser treated zone can be flexibly adapted to the needs. Deep-drawing experiments show significant improvement in formability. With this technique, parts can be manufactured, which can conventionally only be made of steel with lower strength. Locally reduced strength of press hardened serial parts was demonstrated.

Multi objective genetic algorithm to optimize the local heat treatment of a hardenable aluminum alloy

NASA Astrophysics Data System (ADS)

Piccininni, A.; Palumbo, G.; Franco, A. Lo; Sorgente, D.; Tricarico, L.; Russello, G.

2018-05-01

The continuous research for lightweight components for transport applications to reduce the harmful emissions drives the attention to the light alloys as in the case of Aluminium (Al) alloys, capable to combine low density with high values of the strength-to-weight ratio. Such advantages are partially counterbalanced by the poor formability at room temperature. A viable solution is to adopt a localized heat treatment by laser of the blank before the forming process to obtain a tailored distribution of material properties so that the blank can be formed at room temperature by means of conventional press machines. Such an approach has been extensively investigated for age hardenable alloys, but in the present work the attention is focused on the 5000 series; in particular, the optimization of the deep drawing process of the alloy AA5754 H32 is proposed through a numerical/experimental approach. A preliminary investigation was necessary to correctly tune the laser parameters (focus length, spot dimension) to effectively obtain the annealed state. Optimal process parameters were then obtained coupling a 2D FE model with an optimization platform managed by a multi-objective genetic algorithm. The optimal solution (i.e. able to maximize the LDR) in terms of blankholder force and extent of the annealed region was thus evaluated and validated through experimental trials. A good matching between experimental and numerical results was found. The optimal solution allowed to obtain an LDR of the locally heat treated blank larger than the one of the material either in the wrought condition (H32) either in the annealed condition (H111).

Biology a la mode: Charles Darwin's aesthetics of "ornament".

PubMed

Menninghaus, Winfried

2009-01-01

Historians have long noted the importance of Victorian culture for the emergence of Darwin's ideas. This paper takes this understanding one step further by illustrating a deep cultural analysis for the underlying aesthetics framework which, on the one hand, is part of Darwin's notion of sexual selection while, at the same time, serving to give rise to a new "aesthetics semantics." While evolutionary biology avoids this language, it nevertheless had far-reaching influences in the decades following the publication of Darwin's work. Additionally, evolutionary aesthetics from Darwin provides unique insights on the philosophical foundations it draws upon.

Heated Hydro-Mechanical Deep Drawing of Magnesium Sheet Metal

NASA Astrophysics Data System (ADS)

Kurz, Gerrit

In order to reduce fuel consumption efforts have been made to decrease the weight of automobile constructions by increasing the use of lightweight materials. In this field of application magnesium alloys are important because of their low density. A promising alternative to large surfaced and thin die casting parts has been found in construction parts that are manufactured by sheet metal forming of magnesium. Magnesium alloys show a limited formability at room temperature. A considerable improvement of formability can be achieved by heating the material. Formability increases above a temperature of approximately T = 225 °C.

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

Not Available

The 21st Century Power Partnership's program in Mexico (21CPP Mexico) is one initiative of the Clean Energy Ministerial, carried out in cooperation with government and local stakeholders, drawing upon an international community of power system expertise. The overall goal of this program is to support Mexico's power system transformation by accelerating the transition to a reliable, financially robust, and low-carbon system. 21CPP Mexico activities focus on achieving positive outcomes for all participants, especially addressing critical questions and challenges facing policymakers, regulators, and system operators. In support of this goal, 21CPP Mexico taps into deep networks of expertise and professional connections.

Nonlinear friction model for servo press simulation

NASA Astrophysics Data System (ADS)

Ma, Ninshu; Sugitomo, Nobuhiko; Kyuno, Takunori; Tamura, Shintaro; Naka, Tetsuo

2013-12-01

The friction coefficient was measured under an idealized condition for a pulse servo motion. The measured friction coefficient and its changing with both sliding distance and a pulse motion showed that the friction resistance can be reduced due to the re-lubrication during unloading process of the pulse servo motion. Based on the measured friction coefficient and its changes with sliding distance and re-lubrication of oil, a nonlinear friction model was developed. Using the newly developed the nonlinear friction model, a deep draw simulation was performed and the formability was evaluated. The results were compared with experimental ones and the effectiveness was verified.

Influence of the forming process on the mechanical behavior of a commingled carbon PPS composite part

NASA Astrophysics Data System (ADS)

Patou, J.; De Luycker, E.; Bonnaire, R.; Cutard, T.; Bernhart, G.

2018-05-01

In this research work, the influence of the forming process on commingled thermoplastic composite parts mechanical behavior was investigated. The aim of this work is to evaluate the influence of fabric shearing on the mechanical response of composite laminate. Different sheets with a given shear angle are manufactured. Tensile experimental results are compared with the properties obtained from a simple model based on the laminate plate theory for various off angles. Later, the link with a tetrahedron shape 3D part manufactured by punch deep drawing will be made.

Method of sealing

DOEpatents

Groh, Edward F.; Cassidy, Dale A.

1978-01-01

A thermocouple lead or other small diameter wire, cable or tube is passed through a thin material such as sheet metal and sealed thereinto by drawing complementary longitudinally angled, laterally rounded grooves terminating at their base ends in a common plane in both sides of the thin material with shearing occuring at the deep end faces thereof to form a rounded opening in the thin material substantially perpendicular to the plane of the thin material, passing a thermocouple lead or similar object through the opening so formed and sealing the opening with a sealant which simultaneously bonds the lead to the thin material.

Lipid profile in antipsychotic drug users: A comparative study

PubMed Central

Roohafza, Hamidreza; Khani, Azam; Afshar, Hamid; Garakyaraghi, Mohammad; Amirpour, Afshin; Ghodsi, Basir

2013-01-01

BACKGROUND Schizophrenic patients who receive antipsychotic drugs may be highly prone to metabolic disorders such as weight gain, dyslipidemia, and insulin resistance. The objective of the present study was to compare the effect of atypical and conventional antipsychotics on lipid profile. METHODS 128 schizophrenic patients were enrolled into the study. Patients were divided into two groups. One group had received one type of atypical antipsychotic drug, and, the other, one type of conventional antipsychotic drug. They were considered as atypical and conventional groups. Moreover, both groups had not used any other antipsychotic drugs during the past year. Demographic data and food frequency questionnaire were completed by the participants. Serum triglyceride, total cholesterol (TC), high-density lipoprotein and low-density lipoprotein (LDL) cholesterols, and apolipoprotein A and B (Apo B) were tested by blood sample drawing after 12 hours of fasting through the antecubital vein. Student’s t-test was used to compare atypical and conventional groups. RESULTS There was no significant difference in age, gender, duration of illness, period of drug consumption, and age at onset of illness in the two groups. Patients in the atypical group used clozapine and risperidone (46.9%) more than olanzapine. In the conventional group 81.3% of patients used phenothiazines. Comparison between lipid profile in the conventional and atypical groups showed a significantly higher mean in TC (P = 0.01), LDL (P = 0.03), and Apo B (P = 0.01) in conventional group than the atypical group. CONCLUSION In schizophrenic patients, the level of lipid profile had been increased in both atypical and conventional antipsychotic users, especially conventional users, so the effect of antipsychotic drugs should be investigated periodically. PMID:23766777

Composing Science

NASA Astrophysics Data System (ADS)

Atkins, Leslie

2015-03-01

The course Scientific Inquiry at California State University was developed by faculty in biology, physics and English to meet ``writing proficiency'' requirements for non-science majors. Drawing from previous work in composition studies, the position that we take in this course is that we should be engaging students in writing that replicates the work that writing does in science, rather than replicating the particular structural conventions characteristic of scientific writing. That is, scientists use writing to have, remember, share, vet, challenge, and stabilize ideas, and our course requires students use writing to achieve those aims, rather than produce writing that obeys particular conventions of scientific writing. This talk will describe how we have integrated findings from composition studies with a course on scientific inquiry, and provide examples of how scientific communication has resulted from this dialogue. Funding by NSF #1140860.

A high quantum yield molecule-protein complex fluorophore for near-infrared II imaging

PubMed Central

Antaris, Alexander L.; Chen, Hao; Diao, Shuo; Ma, Zhuoran; Zhang, Zhe; Zhu, Shoujun; Wang, Joy; Lozano, Alexander X.; Fan, Quli; Chew, Leila; Zhu, Mark; Cheng, Kai; Hong, Xuechuan; Dai, Hongjie; Cheng, Zhen

2017-01-01

Fluorescence imaging in the second near-infrared window (NIR-II) allows visualization of deep anatomical features with an unprecedented degree of clarity. NIR-II fluorophores draw from a broad spectrum of materials spanning semiconducting nanomaterials to organic molecular dyes, yet unfortunately all water-soluble organic molecules with >1,000 nm emission suffer from low quantum yields that have limited temporal resolution and penetration depth. Here, we report tailoring the supramolecular assemblies of protein complexes with a sulfonated NIR-II organic dye (CH-4T) to produce a brilliant 110-fold increase in fluorescence, resulting in the highest quantum yield molecular fluorophore thus far. The bright molecular complex allowed for the fastest video-rate imaging in the second NIR window with ∼50-fold reduced exposure times at a fast 50 frames-per-second (FPS) capable of resolving mouse cardiac cycles. In addition, we demonstrate that the NIR-II molecular complexes are superior to clinically approved ICG for lymph node imaging deep within the mouse body. PMID:28524850

AISI/DOE Technology Roadmap Program: Cold Work Embrittlement of Interstitial Free Steel

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

John T Bowker; Pierre Martin

2002-10-31

This work addresses the issues of measurement of secondary cold work embrittlement (SCWE) of an IF steel in deep-drawn parts using laboratory tests, and its correlation with real part fracture. It aimed at evaluating the influence of the steel chemistry and processing condition, microstructure, and test conditions, on SCWE as well as the effect of SCWE on fatigue properties. Size 6-in. cups produced with various draw ratios or trimmed at different heights were tested to determine the ductile-to-brittle-transition temperature (DBTT) as a function of strain. The 2-in. cup/expansion test, bend test and fracture of notched specimens were also used tomore » generate information complementary to that provided by the 6-inch cup/expansion test. The relationship between laboratory tests and fracture in real parts was established by testing large-scale parts. The fatigue behavior was investigated in the as-rolled and deep drawn (high stain) conditions, using prestrained specimens taken from the wall of a formed part.« less

A high quantum yield molecule-protein complex fluorophore for near-infrared II imaging

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

Antaris, Alexander L.; Chen, Hao; Diao, Shuo

Fluorescence imaging in the second near-infrared window (NIR-II) allows visualization of deep anatomical features with an unprecedented degree of clarity. NIR-II fluorophores draw from a broad spectrum of materials spanning semiconducting nanomaterials to organic molecular dyes, yet unfortunately all water-soluble organic molecules with 41,000 nm emission suffer from low quantum yields that have limited temporal resolution and penetration depth. We report tailoring the supramolecular assemblies of protein complexes with a sulfonated NIR-II organic dye (CH-4T) to produce a brilliant 110-fold increase in fluorescence, resulting in the highest quantum yield molecular fluorophore thus far. The bright molecular complex allowed for themore » fastest video-rate imaging in the second NIR window with B50-fold reduced exposure times at a fast 50 frames-per-second (FPS) capable of resolving mouse cardiac cycles. Additionally, we demonstrate that the NIR-II molecular complexes are superior to clinically approved ICG for lymph node imaging deep within the mouse body.« less

A high quantum yield molecule-protein complex fluorophore for near-infrared II imaging

DOE PAGES

Antaris, Alexander L.; Chen, Hao; Diao, Shuo; ...

2017-05-19

Fluorescence imaging in the second near-infrared window (NIR-II) allows visualization of deep anatomical features with an unprecedented degree of clarity. NIR-II fluorophores draw from a broad spectrum of materials spanning semiconducting nanomaterials to organic molecular dyes, yet unfortunately all water-soluble organic molecules with 41,000 nm emission suffer from low quantum yields that have limited temporal resolution and penetration depth. We report tailoring the supramolecular assemblies of protein complexes with a sulfonated NIR-II organic dye (CH-4T) to produce a brilliant 110-fold increase in fluorescence, resulting in the highest quantum yield molecular fluorophore thus far. The bright molecular complex allowed for themore » fastest video-rate imaging in the second NIR window with B50-fold reduced exposure times at a fast 50 frames-per-second (FPS) capable of resolving mouse cardiac cycles. Additionally, we demonstrate that the NIR-II molecular complexes are superior to clinically approved ICG for lymph node imaging deep within the mouse body.« less

Reading in Two Writing Systems: Accommodation and Assimilation of the Brain's Reading Network

ERIC Educational Resources Information Center

Perfetti, Charles A.; Liu, Ying; Fiez, Julie; Nelson, Jessica; Bolger, Donald J.; Tan, Li-Hai

2007-01-01

Bilingual reading can require more than knowing two languages. Learners must acquire also the writing conventions of their second language, which can differ in its deep mapping principles (writing system) and its visual configurations (script). We review ERP (event-related potential) and fMRI studies of both Chinese-English bilingualism and…

Conventionalism as a Virtue: A Study of "Powwow Highway"

ERIC Educational Resources Information Center

Heil, Douglas

2009-01-01

Academia has long grappled with the relationship between filmmaking form and content. Film history courses are driven, in part, by aesthetic innovation, and it is not uncommon to study the editing advances made by D. W. Griffith and the silent-era Soviet filmmakers, the exploration of deep focus photography by Orson Welles and Gregg Toland, the…

How Low Can Conventional Generators Go? | News | NREL

Science.gov Websites

, lead author of the study. "So this paper is a deep dive into one of the many things we need to assumptions, the study is mainly targeted toward the grid modeling community-but the topic has broad policy implications for renewable deployment. According to the study authors, if minimum generation levels are

Ship localization in Santa Barbara Channel using machine learning classifiers.

PubMed

Niu, Haiqiang; Ozanich, Emma; Gerstoft, Peter

2017-11-01

Machine learning classifiers are shown to outperform conventional matched field processing for a deep water (600 m depth) ocean acoustic-based ship range estimation problem in the Santa Barbara Channel Experiment when limited environmental information is known. Recordings of three different ships of opportunity on a vertical array were used as training and test data for the feed-forward neural network and support vector machine classifiers, demonstrating the feasibility of machine learning methods to locate unseen sources. The classifiers perform well up to 10 km range whereas the conventional matched field processing fails at about 4 km range without accurate environmental information.

Low-abundance HIV drug-resistant viral variants in treatment-experienced persons correlate with historical antiretroviral use.

PubMed

Le, Thuy; Chiarella, Jennifer; Simen, Birgitte B; Hanczaruk, Bozena; Egholm, Michael; Landry, Marie L; Dieckhaus, Kevin; Rosen, Marc I; Kozal, Michael J

2009-06-29

It is largely unknown how frequently low-abundance HIV drug-resistant variants at levels under limit of detection of conventional genotyping (<20% of quasi-species) are present in antiretroviral-experienced persons experiencing virologic failure. Further, the clinical implications of low-abundance drug-resistant variants at time of virologic failure are unknown. Plasma samples from 22 antiretroviral-experienced subjects collected at time of virologic failure (viral load 1380 to 304,000 copies/mL) were obtained from a specimen bank (from 2004-2007). The prevalence and profile of drug-resistant mutations were determined using Sanger sequencing and ultra-deep pyrosequencing. Genotypes were interpreted using Stanford HIV database algorithm. Antiretroviral treatment histories were obtained by chart review and correlated with drug-resistant mutations. Low-abundance drug-resistant mutations were detected in all 22 subjects by deep sequencing and only in 3 subjects by Sanger sequencing. In total they accounted for 90 of 247 mutations (36%) detected by deep sequencing; the majority of these (95%) were not detected by standard genotyping. A mean of 4 additional mutations per subject were detected by deep sequencing (p<0.0001, 95%CI: 2.85-5.53). The additional low-abundance drug-resistant mutations increased a subject's genotypic resistance to one or more antiretrovirals in 17 of 22 subjects (77%). When correlated with subjects' antiretroviral treatment histories, the additional low-abundance drug-resistant mutations correlated with the failing antiretroviral drugs in 21% subjects and correlated with historical antiretroviral use in 79% subjects (OR, 13.73; 95% CI, 2.5-74.3, p = 0.0016). Low-abundance HIV drug-resistant mutations in antiretroviral-experienced subjects at time of virologic failure can increase a subject's overall burden of resistance, yet commonly go unrecognized by conventional genotyping. The majority of unrecognized resistant mutations correlate with historical antiretroviral use. Ultra-deep sequencing can provide important historical resistance information for clinicians when planning subsequent antiretroviral regimens for highly treatment-experienced patients, particularly when their prior treatment histories and longitudinal genotypes are not available.

Low-Abundance HIV Drug-Resistant Viral Variants in Treatment-Experienced Persons Correlate with Historical Antiretroviral Use

PubMed Central

Le, Thuy; Chiarella, Jennifer; Simen, Birgitte B.; Hanczaruk, Bozena; Egholm, Michael; Landry, Marie L.; Dieckhaus, Kevin; Rosen, Marc I.; Kozal, Michael J.

2009-01-01

Background It is largely unknown how frequently low-abundance HIV drug-resistant variants at levels under limit of detection of conventional genotyping (<20% of quasi-species) are present in antiretroviral-experienced persons experiencing virologic failure. Further, the clinical implications of low-abundance drug-resistant variants at time of virologic failure are unknown. Methodology/Principal Findings Plasma samples from 22 antiretroviral-experienced subjects collected at time of virologic failure (viral load 1380 to 304,000 copies/mL) were obtained from a specimen bank (from 2004–2007). The prevalence and profile of drug-resistant mutations were determined using Sanger sequencing and ultra-deep pyrosequencing. Genotypes were interpreted using Stanford HIV database algorithm. Antiretroviral treatment histories were obtained by chart review and correlated with drug-resistant mutations. Low-abundance drug-resistant mutations were detected in all 22 subjects by deep sequencing and only in 3 subjects by Sanger sequencing. In total they accounted for 90 of 247 mutations (36%) detected by deep sequencing; the majority of these (95%) were not detected by standard genotyping. A mean of 4 additional mutations per subject were detected by deep sequencing (p<0.0001, 95%CI: 2.85–5.53). The additional low-abundance drug-resistant mutations increased a subject's genotypic resistance to one or more antiretrovirals in 17 of 22 subjects (77%). When correlated with subjects' antiretroviral treatment histories, the additional low-abundance drug-resistant mutations correlated with the failing antiretroviral drugs in 21% subjects and correlated with historical antiretroviral use in 79% subjects (OR, 13.73; 95% CI, 2.5–74.3, p = 0.0016). Conclusions/Significance Low-abundance HIV drug-resistant mutations in antiretroviral-experienced subjects at time of virologic failure can increase a subject's overall burden of resistance, yet commonly go unrecognized by conventional genotyping. The majority of unrecognized resistant mutations correlate with historical antiretroviral use. Ultra-deep sequencing can provide important historical resistance information for clinicians when planning subsequent antiretroviral regimens for highly treatment-experienced patients, particularly when their prior treatment histories and longitudinal genotypes are not available. PMID:19562031

Do Gender-Specific and High-Resolution Three Dimensional Body Charts Facilitate the Communication of Pain for Women? A Quantitative and Qualitative Study

PubMed Central

Egsgaard, Line Lindhardt

2016-01-01

Background Chronic pain is more prevalent among women; however, the majority of standardized pain drawings are often collected using male-like androgynous body representations. Objective The purpose of this study was to assess whether gender-specific and high-resolution three-dimensional (3D) body charts facilitate the communication of pain for women. Methods Using mixed-methods and a cross-over design, female patients with chronic pain were asked to provide detailed drawings of their current pain on masculine and feminine two-dimensional (2D) body schemas (N=41, Part I) or on female 2D and 3D high-resolution body schemas (N=41, Part II) on a computer tablet. The consistency of the drawings between body charts were assessed by intraclass correlation coefficient (ICC) and Bland-Altman plots. Semistructured interviews and a preference questionnaire were then used to obtain qualitative and quantitative responses of the drawing experience. Results The consistency between body charts were high (Part I: ICC=0.980, Part II: ICC=0.994). The preference ratio for the masculine to feminine body schemas were 6:35 and 18:23 for the 2D to 3D female body charts. Patients reported that the 3D body chart enabled a more accurate expression of their pain due to the detailed contours of the musculature and bone structure, however, patients also reported the 3D body chart was too human and believed that skin-like appearance limited ‘deep pain’ expressions. Conclusions Providing gender-specific body charts may facilitate the communication of pain and the level of detail (2D vs 3D body charts) should be used according to patients’ needs. PMID:27440737

Through the eyes of children: Drawings as an evaluation tool for children's understanding about endangered Mexican primates.

PubMed

Franquesa-Soler, Montserrat; Serio-Silva, Juan Carlos

2017-12-01

This study seeks to understand children's perceptions and knowledge of endangered Mexican primates. The black howler monkey (Alouatta pigra) is a charismatic species endemic to Southern Mexico, Northern Belize, and Guatemala and is a symbol of the region that fosters a sense of local pride. Therefore, it can be considered a flagship species for the forests of Southern Mexico. We evaluated the perception and knowledge that 297 Mexican elementary school children (8-10 years old) have about black howler monkeys. Specifically, we analyzed and categorized drawings made by these children based on gender, geographic context (rural or urban), and residence within or outside of Protected Areas (PAs). Student drawings were categorized into three levels of knowledge (no familiarity, basic knowledge, and sophisticated knowledge). Common misconceptions and important landscape elements for black howler conservation were gathered from these visual representations. Children were largely unfamiliar with black howlers, despite sharing the same geographical location. Knowledge was affected by context and residence, with students living within PAs more aware of black howlers than students living outside of PAs. However, overall the children showed a deep understanding of the current forest conservation situation in Southern Mexico; meaning they could be presenting a shifting baseline syndrome. The study highlights the value of assessing children's drawings as a tool that can be used to help policy makers and educational practitioners in fine-tuning educational, environmental, and marketing programs. More importantly, it is a methodology that can be applied in future research for understanding children's perceptions and knowledge about endangered species and environmental change in deciding how to improve the effectiveness of conservation messaging. © 2017 Wiley Periodicals, Inc.

Evaluation of Deep Learning Based Stereo Matching Methods: from Ground to Aerial Images

NASA Astrophysics Data System (ADS)

Liu, J.; Ji, S.; Zhang, C.; Qin, Z.

2018-05-01

Dense stereo matching has been extensively studied in photogrammetry and computer vision. In this paper we evaluate the application of deep learning based stereo methods, which were raised from 2016 and rapidly spread, on aerial stereos other than ground images that are commonly used in computer vision community. Two popular methods are evaluated. One learns matching cost with a convolutional neural network (known as MC-CNN); the other produces a disparity map in an end-to-end manner by utilizing both geometry and context (known as GC-net). First, we evaluate the performance of the deep learning based methods for aerial stereo images by a direct model reuse. The models pre-trained on KITTI 2012, KITTI 2015 and Driving datasets separately, are directly applied to three aerial datasets. We also give the results of direct training on target aerial datasets. Second, the deep learning based methods are compared to the classic stereo matching method, Semi-Global Matching(SGM), and a photogrammetric software, SURE, on the same aerial datasets. Third, transfer learning strategy is introduced to aerial image matching based on the assumption of a few target samples available for model fine tuning. It experimentally proved that the conventional methods and the deep learning based methods performed similarly, and the latter had greater potential to be explored.

Deep Recurrent Neural Networks for Human Activity Recognition

PubMed Central

Murad, Abdulmajid

2017-01-01

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs. PMID:29113103

Deep Recurrent Neural Networks for Human Activity Recognition.

PubMed

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

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.

The role of molecular imaging in diagnosis of deep vein thrombosis

PubMed Central

Houshmand, Sina; Salavati, Ali; Hess, Søren; Ravina, Mudalsha; Alavi, Abass

2014-01-01

Venous thromboembolism (VTE) mostly presenting as deep venous thrombosis (DVT) and pulmonary embolism (PE) affects up to 600,000 individuals in United States each year. Clinical symptoms of VTE are nonspecific and sometimes misleading. Additionally, side effects of available treatment plans for DVT are significant. Therefore, medical imaging plays a crucial role in proper diagnosis and avoidance from over/under diagnosis, which exposes the patient to risk. In addition to conventional structural imaging modalities, such as ultrasonography and computed tomography, molecular imaging with different tracers have been studied for diagnosis of DVT. In this review we will discuss currently available and newly evolving targets and tracers for detection of DVT using molecular imaging methods. PMID:25143860

Effect of impurities and processing on silicon solar cells. Volume 1: Characterization methods for impurities in silicon and impurity effects data base

NASA Technical Reports Server (NTRS)

Hopkins, R. H.; Davis, J. R.; Rohatgi, A.; Campbell, R. B.; Blais, P. D.; Rai-Choudhury, P.; Stapleton, R. E.; Mollenkopf, H. C.; Mccormick, J. R.

1980-01-01

Two major topics are treated: methods to measure and evaluate impurity effects in silicon and comprehensive tabulations of data derived during the study. Discussions of deep level spectroscopy, detailed dark I-V measurements, recombination lifetime determination, scanned laser photo-response, conventional solar cell I-V techniques, and descriptions of silicon chemical analysis are presented and discussed. The tabulated data include lists of impurity segregation coefficients, ingot impurity analyses and estimated concentrations, typical deep level impurity spectra, photoconductive and open circuit decay lifetimes for individual metal-doped ingots, and a complete tabulation of the cell I-V characteristics of nearly 200 ingots.

A tunable sound-absorbing metamaterial based on coiled-up space

NASA Astrophysics Data System (ADS)

Wang, Yang; Zhao, Honggang; Yang, Haibin; Zhong, Jie; Zhao, Dan; Lu, Zhongliang; Wen, Jihong

2018-05-01

This paper presents a theoretical, numerical, and experimental investigation of a deep-subwavelength absorber based on the concept of coiled-up space. By adjusting a partition panel in the cavity to form an unequal-section channel, it is found that the resonance frequency of the absorber is easily tuned and near-total absorption is acquired under a fixed deep-subwavelength thickness. The absorption mechanism induced by nearly critical coupling is revealed by graphically analyzing the reflection coefficient in the complex plane. In contrast to conventional techniques, near-total absorption can be adjusted over a wider frequency range. To further enhance the absorption, we demonstrate a broadband absorber with a relative bandwidth up to 33.3%.

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.

[Between deontology and ethics, does the institution become respectable?].

PubMed

Breulet, M

1995-01-01

Deontology draws one's inspiration from Ethics. From this occurrence it seems important to avoid confusion between the first and the second. Psychiatry belongs truly to medical training. Nevertheless considering freedom pathology is its main particularity. This is the reason why human freedom must, at all cost, be preserved. This one is essential whenever individual subjectivity is concerned. The fundamental reference remains Human Rights Convention; even if opposed to principle of reality, one is necessarily obliged to a conflictual accommodation.

2,3-Dihydroxybenzoic acid amides of tetraazaalkanes and tetaaza cycloalkanes

DOEpatents

Weitl, F.L.; Raymond, K.N.

1980-01-01

This disclosure is directed to a compound of the formula given in the patent wherein X is hydrogen or a conventional electron-withdrawing group, particularly --SO[sub 3]H or a salt thereof; n is 2, 3, or 4; m is 2, 3, or 4; and p is 2 or 3. The present compounds are useful as specific sequestering agents for actinide (IV) ions. Also described is a method for the 2,3-dihydroxybenzamidation of azaalkanes. No Drawings

Justice from the victim's perspective.

PubMed

Herman, Judith Lewis

2005-05-01

What are the meanings of justice, as seen from the perspective of victims of violent crime? Are victims' visions of justice represented by the conventional legal system? Are they represented by restorative justice? The author engages these questions, drawing on in-depth interviews with 22 victims of violent crime. It is argued that survivors' views of justice do not fit well into either retributive or restorative models. This has implications for current efforts to use restorative models in cases of violence against women.

Deep Learning in Gastrointestinal Endoscopy.

PubMed

Patel, Vivek; Armstrong, David; Ganguli, Malika; Roopra, Sandeep; Kantipudi, Neha; Albashir, Siwar; Kamath, Markad V

2016-01-01

Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for several purposes, including, (1) making a clinical diagnosis, in real time, based on the visual appearances; (2) taking targeted tissue samples for subsequent histopathological examination; and (3) in some cases, performing therapeutic interventions targeted at specific lesions. GI endoscopy is therefore predicated on the assumption that the operator-the endoscopist-is able to identify and characterize abnormalities or lesions accurately and reproducibly. However, as in other areas of clinical medicine, such as histopathology and radiology, many studies have documented marked interobserver and intraobserver variability in lesion recognition. Thus, there is a clear need and opportunity for techniques or methodologies that will enhance the quality of lesion recognition and diagnosis and improve the outcomes of GI endoscopy. Deep learning models provide a basis to make better clinical decisions in medical image analysis. Biomedical image segmentation, classification, and registration can be improved with deep learning. Recent evidence suggests that the application of deep learning methods to medical image analysis can contribute significantly to computer-aided diagnosis. Deep learning models are usually considered to be more flexible and provide reliable solutions for image analysis problems compared to conventional computer vision models. The use of fast computers offers the possibility of real-time support that is important for endoscopic diagnosis, which has to be made in real time. Advanced graphics processing units and cloud computing have also favored the use of machine learning, and more particularly, deep learning for patient care. This paper reviews the rapidly evolving literature on the feasibility of applying deep learning algorithms to endoscopic imaging.

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.

Auger planting of oak seedlings in northern Arkansas

Treesearch

Eric Heitzman; Adrian Grell

2003-01-01

Planting oak seedlings to regenerate upland oak forests is a promising but untested silvicultural practice in the Ozark Mountains of northern Arkansas. The stony (cherty) soils of the region make it difficult to dig deep planting holes using conventional hand planting tools. In 2001, we planted 1-0 northern red oak and white oak seedlings in 0.5 to 1 acre group...

State-of-the-Art Applicability of Conventional Densification Techniques to Increase Disposal Area Storage Capacity

DTIC Science & Technology

1977-04-01

Dipper dredge and silt. Approaches dry density incoarser material. Clam shell or orange peel. bucket d-redge SEndless chain bucket dredge Cutterhead...stage the big disk wheel is pulled by a tractor making ditches about 0.5 to 0.6 m deep and 10 m apart. When the first layer of mud has been

Aerodynamic Characteristics of Three Deep-Stepped Planing-Tail Flying-Boat Hulls

NASA Technical Reports Server (NTRS)

Riebe, John M.; Naeseth, Rodger L.

1947-01-01

An investigation was made in the Langley 300 MPH 7- by 10-foot tunnel to determine the aerodynamic characteristics of three deep-stepped planing-tail flying-boat hulls differing only in the amount of step fairing. The hulls were derived by increasing the unfaired step depth of a planing-tail hull of a previous aerodynamic investigation to a depth about 92 percent of the hull beam. Tests were also made on a transverse-stepped hull with an extended afterbody for the purpose of comparison and in order to extend and verify the results of a previous investigation. The investigation indicated that the extended afterbody hull had a minimum drag coefficient about the same as a conventional hull, 0.0066, and an angle-of-attack range for minimum drag coefficient of 0.0057 which was 14 percent less than the transverse stepped hull with extended afterbody; the hulls with step fairing had up to 44 percent less minimum drag coefficient than the transverse-stepped hull, or slightly more drag than a streamlined body having approximately the same length and volume. Longitudinal and lateral instability varied little with step fairing and was about the same as a conventional hull.

Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence.

PubMed

Zhang, Ran; Peng, Zhen; Wu, Lifeng; Yao, Beibei; Guan, Yong

2017-03-09

Intelligent condition monitoring and fault diagnosis by analyzing the sensor data can assure the safety of machinery. Conventional fault diagnosis and classification methods usually implement pretreatments to decrease noise and extract some time domain or frequency domain features from raw time series sensor data. Then, some classifiers are utilized to make diagnosis. However, these conventional fault diagnosis approaches suffer from the expertise of feature selection and they do not consider the temporal coherence of time series data. This paper proposes a fault diagnosis model based on Deep Neural Networks (DNN). The model can directly recognize raw time series sensor data without feature selection and signal processing. It also takes advantage of the temporal coherence of the data. Firstly, raw time series training data collected by sensors are used to train the DNN until the cost function of DNN gets the minimal value; Secondly, test data are used to test the classification accuracy of the DNN on local time series data. Finally, fault diagnosis considering temporal coherence with former time series data is implemented. Experimental results show that the classification accuracy of bearing faults can get 100%. The proposed fault diagnosis approach is effective in recognizing the type of bearing faults.

Pseudomorphic InGaAs/AlGaAs modulation-doped FET's with reduced low-frequency noise and thermally stable performance

NASA Technical Reports Server (NTRS)

Liu, Shih-Ming; Das, M. B.; Peng, C. K.; Klem, J.; Henderson, T.

1987-01-01

A high-performance MODFET structure grown by MBE with the incorporation of a single quantum well In(0.15)Ga(0.85)As layer for the transport of two-dimensional electron gas has been critically examined for its thermal stability at 80 K and low-frequency noise form 0.01 to 10 to the 8th Hz. Experimental results indicate that the behavior of this device in both these respects is much superior when compared with the same behavior of conventional MODFETs. A maximum low-field carrier mobility of 29,000 sq cm/s at 80 K and an average carrier saturation velocity of 2 x 10 to the 7th cm/s at 300 K in a 1-micron gate device clearly indicate that the quality of the pseudomorphic quantum well (InGaAs) layer is either comparable or better than that of the usual GaAs buffer layer. The deep level spectra, obtained through photo-FET measurements, and the low-frequency noise spectra at different temperatures obtained for the new pseudomorphic and conventional MODFET's have clearly indicated that contributions from various deep levels present in the new structure are significantly reduced.

A Deep Denoising Autoencoder Approach to Improving the Intelligibility of Vocoded Speech in Cochlear Implant Simulation.

PubMed

Lai, Ying-Hui; Chen, Fei; Wang, Syu-Siang; Lu, Xugang; Tsao, Yu; Lee, Chin-Hui

2017-07-01

In a cochlear implant (CI) speech processor, noise reduction (NR) is a critical component for enabling CI users to attain improved speech perception under noisy conditions. Identifying an effective NR approach has long been a key topic in CI research. Recently, a deep denoising autoencoder (DDAE) based NR approach was proposed and shown to be effective in restoring clean speech from noisy observations. It was also shown that DDAE could provide better performance than several existing NR methods in standardized objective evaluations. Following this success with normal speech, this paper further investigated the performance of DDAE-based NR to improve the intelligibility of envelope-based vocoded speech, which simulates speech signal processing in existing CI devices. We compared the performance of speech intelligibility between DDAE-based NR and conventional single-microphone NR approaches using the noise vocoder simulation. The results of both objective evaluations and listening test showed that, under the conditions of nonstationary noise distortion, DDAE-based NR yielded higher intelligibility scores than conventional NR approaches. This study confirmed that DDAE-based NR could potentially be integrated into a CI processor to provide more benefits to CI users under noisy conditions.

Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence

PubMed Central

Zhang, Ran; Peng, Zhen; Wu, Lifeng; Yao, Beibei; Guan, Yong

2017-01-01

Intelligent condition monitoring and fault diagnosis by analyzing the sensor data can assure the safety of machinery. Conventional fault diagnosis and classification methods usually implement pretreatments to decrease noise and extract some time domain or frequency domain features from raw time series sensor data. Then, some classifiers are utilized to make diagnosis. However, these conventional fault diagnosis approaches suffer from the expertise of feature selection and they do not consider the temporal coherence of time series data. This paper proposes a fault diagnosis model based on Deep Neural Networks (DNN). The model can directly recognize raw time series sensor data without feature selection and signal processing. It also takes advantage of the temporal coherence of the data. Firstly, raw time series training data collected by sensors are used to train the DNN until the cost function of DNN gets the minimal value; Secondly, test data are used to test the classification accuracy of the DNN on local time series data. Finally, fault diagnosis considering temporal coherence with former time series data is implemented. Experimental results show that the classification accuracy of bearing faults can get 100%. The proposed fault diagnosis approach is effective in recognizing the type of bearing faults. PMID:28282936

Recognition of emotions using multimodal physiological signals and an ensemble deep learning model.

PubMed

Yin, Zhong; Zhao, Mengyuan; Wang, Yongxiong; Yang, Jingdong; Zhang, Jianhua

2017-03-01

Using deep-learning methodologies to analyze multimodal physiological signals becomes increasingly attractive for recognizing human emotions. However, the conventional deep emotion classifiers may suffer from the drawback of the lack of the expertise for determining model structure and the oversimplification of combining multimodal feature abstractions. In this study, a multiple-fusion-layer based ensemble classifier of stacked autoencoder (MESAE) is proposed for recognizing emotions, in which the deep structure is identified based on a physiological-data-driven approach. Each SAE consists of three hidden layers to filter the unwanted noise in the physiological features and derives the stable feature representations. An additional deep model is used to achieve the SAE ensembles. The physiological features are split into several subsets according to different feature extraction approaches with each subset separately encoded by a SAE. The derived SAE abstractions are combined according to the physiological modality to create six sets of encodings, which are then fed to a three-layer, adjacent-graph-based network for feature fusion. The fused features are used to recognize binary arousal or valence states. DEAP multimodal database was employed to validate the performance of the MESAE. By comparing with the best existing emotion classifier, the mean of classification rate and F-score improves by 5.26%. The superiority of the MESAE against the state-of-the-art shallow and deep emotion classifiers has been demonstrated under different sizes of the available physiological instances. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Learning representations for the early detection of sepsis with deep neural networks.

PubMed

Kam, Hye Jin; Kim, Ha Young

2017-10-01

Sepsis is one of the leading causes of death in intensive care unit patients. Early detection of sepsis is vital because mortality increases as the sepsis stage worsens. This study aimed to develop detection models for the early stage of sepsis using deep learning methodologies, and to compare the feasibility and performance of the new deep learning methodology with those of the regression method with conventional temporal feature extraction. Study group selection adhered to the InSight model. The results of the deep learning-based models and the InSight model were compared. With deep feedforward networks, the area under the ROC curve (AUC) of the models were 0.887 and 0.915 for the InSight and the new feature sets, respectively. For the model with the combined feature set, the AUC was the same as that of the basic feature set (0.915). For the long short-term memory model, only the basic feature set was applied and the AUC improved to 0.929 compared with the existing 0.887 of the InSight model. The contributions of this paper can be summarized in three ways: (i) improved performance without feature extraction using domain knowledge, (ii) verification of feature extraction capability of deep neural networks through comparison with reference features, and (iii) improved performance with feedforward neural networks using long short-term memory, a neural network architecture that can learn sequential patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales.

PubMed

Schiro, Kathleen A; Ahmed, Fiaz; Giangrande, Scott E; Neelin, J David

2018-05-01

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014-2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation-buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

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.

Osmotic versus conventional membrane bioreactors integrated with reverse osmosis for water reuse: Biological stability, membrane fouling, and contaminant removal.

PubMed

Luo, Wenhai; Phan, Hop V; Xie, Ming; Hai, Faisal I; Price, William E; Elimelech, Menachem; Nghiem, Long D

2017-02-01

This study systematically compares the performance of osmotic membrane bioreactor - reverse osmosis (OMBR-RO) and conventional membrane bioreactor - reverse osmosis (MBR-RO) for advanced wastewater treatment and water reuse. Both systems achieved effective removal of bulk organic matter and nutrients, and almost complete removal of all 31 trace organic contaminants investigated. They both could produce high quality water suitable for recycling applications. During OMBR-RO operation, salinity build-up in the bioreactor reduced the water flux and negatively impacted the system biological treatment by altering biomass characteristics and microbial community structure. In addition, the elevated salinity also increased soluble microbial products and extracellular polymeric substances in the mixed liquor, which induced fouling of the forward osmosis (FO) membrane. Nevertheless, microbial analysis indicated that salinity stress resulted in the development of halotolerant bacteria, consequently sustaining biodegradation in the OMBR system. By contrast, biological performance was relatively stable throughout conventional MBR-RO operation. Compared to conventional MBR-RO, the FO process effectively prevented foulants from permeating into the draw solution, thereby significantly reducing fouling of the downstream RO membrane in OMBR-RO operation. Accumulation of organic matter, including humic- and protein-like substances, as well as inorganic salts in the MBR effluent resulted in severe RO membrane fouling in conventional MBR-RO operation. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

How can we restrict the sale of sports and energy drinks to children? A proposal for a World Health Organization-sponsored framework convention to restrict the sale of sports and energy drinks.

PubMed

Jean, G

2017-12-01

High-sugar drinks, including fruit drinks, soft drinks, sports drinks and energy drinks, are of no nutritional value and contribute to the burden of dental disease in all age groups. The manufacturers of sports and energy drinks have elected to target children in their marketing campaigns and promote a misleading association between their products, healthy lifestyles and sporting prowess. The World Health Organization (WHO) has acknowledged that strategies aimed at prevention of dental disease are the only economically viable options for managing the oral health of children in low- and middle-income countries. Developed nations will also be advantaged by preventive programmes given that the cost of providing dental care to those who cannot pay draws valuable resources away from more pressing health issues. The Convention on the Rights of the Child (CRC) obligates governments to develop legislation to protect the health of children. A framework convention modelled on the existing Framework Convention for Tobacco Control, supported by the WHO, would assist governments to proactively legislate to restrict the sale of sports and energy drinks to children. This article will consider how a framework convention would be an advantage with reference to the strategies used by sports and energy drink manufacturers in Australia. © 2017 Australian Dental Association.

Segmentation of white matter hyperintensities using convolutional neural networks with global spatial information in routine clinical brain MRI with none or mild vascular pathology.

PubMed

Rachmadi, Muhammad Febrian; Valdés-Hernández, Maria Del C; Agan, Maria Leonora Fatimah; Di Perri, Carol; Komura, Taku

2018-06-01

We propose an adaptation of a convolutional neural network (CNN) scheme proposed for segmenting brain lesions with considerable mass-effect, to segment white matter hyperintensities (WMH) characteristic of brains with none or mild vascular pathology in routine clinical brain magnetic resonance images (MRI). This is a rather difficult segmentation problem because of the small area (i.e., volume) of the WMH and their similarity to non-pathological brain tissue. We investigate the effectiveness of the 2D CNN scheme by comparing its performance against those obtained from another deep learning approach: Deep Boltzmann Machine (DBM), two conventional machine learning approaches: Support Vector Machine (SVM) and Random Forest (RF), and a public toolbox: Lesion Segmentation Tool (LST), all reported to be useful for segmenting WMH in MRI. We also introduce a way to incorporate spatial information in convolution level of CNN for WMH segmentation named global spatial information (GSI). Analysis of covariance corroborated known associations between WMH progression, as assessed by all methods evaluated, and demographic and clinical data. Deep learning algorithms outperform conventional machine learning algorithms by excluding MRI artefacts and pathologies that appear similar to WMH. Our proposed approach of incorporating GSI also successfully helped CNN to achieve better automatic WMH segmentation regardless of network's settings tested. The mean Dice Similarity Coefficient (DSC) values for LST-LGA, SVM, RF, DBM, CNN and CNN-GSI were 0.2963, 0.1194, 0.1633, 0.3264, 0.5359 and 5389 respectively. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction.

PubMed

Yang, Guang; Yu, Simiao; Dong, Hao; Slabaugh, Greg; Dragotti, Pier Luigi; Ye, Xujiong; Liu, Fangde; Arridge, Simon; Keegan, Jennifer; Guo, Yike; Firmin, David; Keegan, Jennifer; Slabaugh, Greg; Arridge, Simon; Ye, Xujiong; Guo, Yike; Yu, Simiao; Liu, Fangde; Firmin, David; Dragotti, Pier Luigi; Yang, Guang; Dong, Hao

2018-06-01

Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging-based fast MRI, which utilizes multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning-based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training data sets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN)-based model is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilize our U-Net based generator, which provides an end-to-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency-domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CS-MRI reconstruction methods and newly investigated deep learning approaches. Compared with these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing.

Imbalance aware lithography hotspot detection: a deep learning approach

NASA Astrophysics Data System (ADS)

Yang, Haoyu; Luo, Luyang; Su, Jing; Lin, Chenxi; Yu, Bei

2017-07-01

With the advancement of very large scale integrated circuits (VLSI) technology nodes, lithographic hotspots become a serious problem that affects manufacture yield. Lithography hotspot detection at the post-OPC stage is imperative to check potential circuit failures when transferring designed patterns onto silicon wafers. Although conventional lithography hotspot detection methods, such as machine learning, have gained satisfactory performance, with the extreme scaling of transistor feature size and layout patterns growing in complexity, conventional methodologies may suffer from performance degradation. For example, manual or ad hoc feature extraction in a machine learning framework may lose important information when predicting potential errors in ultra-large-scale integrated circuit masks. We present a deep convolutional neural network (CNN) that targets representative feature learning in lithography hotspot detection. We carefully analyze the impact and effectiveness of different CNN hyperparameters, through which a hotspot-detection-oriented neural network model is established. Because hotspot patterns are always in the minority in VLSI mask design, the training dataset is highly imbalanced. In this situation, a neural network is no longer reliable, because a trained model with high classification accuracy may still suffer from a high number of false negative results (missing hotspots), which is fatal in hotspot detection problems. To address the imbalance problem, we further apply hotspot upsampling and random-mirror flipping before training the network. Experimental results show that our proposed neural network model achieves comparable or better performance on the ICCAD 2012 contest benchmark compared to state-of-the-art hotspot detectors based on deep or representative machine leaning.

Different stage, different performance: the protective strategy of role play on emotional health in sex work.

PubMed

Abel, Gillian M

2011-04-01

This paper uses Arlie Hochschild's (1983) concept of emotion management and "surface" and "deep acting" to explore how sex workers separate and distance themselves from their public role. Experiences of stigmatisation prevail among sex workers and how stigma is resisted or managed has an impact on their health. In-depth interviews were carried out between August 2006 and April 2007 with 58 sex workers in five cities in New Zealand following decriminalisation of the sex industry. Most participants drew on ideas of professionalism in sustaining a psychological distance between their private and public lives. They utilised "deep acting", transmuting private experiences for use in the work environment, to accredit themselves as professional in their business practices. They also constructed different meanings for sex between public and private relationships with the condom providing an important symbol in separating the two. A few (mostly female street-based) participants were less adept at "deep acting" and relied on drugs to maintain a separation of roles. This paper argues that in an occupation which is highly stigmatised and in which depersonalisation as an aspect of burn-out has been reported as a common occurrence, the ability to draw on strategies which require "deep acting" provides a healthy estrangement between self and role and can be seen as protective. The separation of self from work identity is not damaging as many radical feminists would claim, but an effective strategy to manage emotions. Hochschild, A. (1983). The managed heart: Commercialization of human feeling. Berkeley: University of California Press. Copyright © 2011 Elsevier Ltd. All rights reserved.

Photonic bandgap narrowing in conical hollow core Bragg fibers

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

Ozturk, Fahri Emre; Yildirim, Adem; Kanik, Mehmet

2014-08-18

We report the photonic bandgap engineering of Bragg fibers by controlling the thickness profile of the fiber during the thermal drawing. Conical hollow core Bragg fibers were produced by thermal drawing under a rapidly alternating load, which was applied by introducing steep changes to the fiber drawing speed. In conventional cylindrical Bragg fibers, light is guided by omnidirectional reflections from interior dielectric mirrors with a single quarter wave stack period. In conical fibers, the diameter reduction introduced a gradient of the quarter wave stack period along the length of the fiber. Therefore, the light guided within the fiber encountered slightlymore » smaller dielectric layer thicknesses at each reflection, resulting in a progressive blueshift of the reflectance spectrum. As the reflectance spectrum shifts, longer wavelengths of the initial bandgap cease to be omnidirectionally reflected and exit through the cladding, which narrows the photonic bandgap. A narrow transmission bandwidth is particularly desirable in hollow waveguide mid-infrared sensing schemes, where broadband light is coupled to the fiber and the analyte vapor is introduced into the hollow core to measure infrared absorption. We carried out sensing simulations using the absorption spectrum of isopropyl alcohol vapor to demonstrate the importance of narrow bandgap fibers in chemical sensing applications.« less

Prediction of properties of wheat dough using intelligent deep belief networks

NASA Astrophysics Data System (ADS)

Guha, Paramita; Bhatnagar, Taru; Pal, Ishan; Kamboj, Uma; Mishra, Sunita

2017-11-01

In this paper, the rheological and chemical properties of wheat dough are predicted using deep belief networks. Wheat grains are stored at controlled environmental conditions. The internal parameters of grains viz., protein, fat, carbohydrates, moisture, ash are determined using standard chemical analysis and viscosity of the dough is measured using Rheometer. Here, fat, carbohydrates, moisture, ash and temperature are considered as inputs whereas protein and viscosity are chosen as outputs. The prediction algorithm is developed using deep neural network where each layer is trained greedily using restricted Boltzmann machine (RBM) networks. The overall network is finally fine-tuned using standard neural network technique. In most literature, it has been found that fine-tuning is done using back-propagation technique. In this paper, a new algorithm is proposed in which each layer is tuned using RBM and the final network is fine-tuned using deep neural network (DNN). It has been observed that with the proposed algorithm, errors between the actual and predicted outputs are less compared to the conventional algorithm. Hence, the given network can be considered as beneficial as it predicts the outputs more accurately. Numerical results along with discussions are presented.

Detection of Emerging Vaccine-Related Polioviruses by Deep Sequencing.

PubMed

Sahoo, Malaya K; Holubar, Marisa; Huang, ChunHong; Mohamed-Hadley, Alisha; Liu, Yuanyuan; Waggoner, Jesse J; Troy, Stephanie B; Garcia-Garcia, Lourdes; Ferreyra-Reyes, Leticia; Maldonado, Yvonne; Pinsky, Benjamin A

2017-07-01

Oral poliovirus vaccine can mutate to regain neurovirulence. To date, evaluation of these mutations has been performed primarily on culture-enriched isolates by using conventional Sanger sequencing. We therefore developed a culture-independent, deep-sequencing method targeting the 5' untranslated region (UTR) and P1 genomic region to characterize vaccine-related poliovirus variants. Error analysis of the deep-sequencing method demonstrated reliable detection of poliovirus mutations at levels of <1%, depending on read depth. Sequencing of viral nucleic acids from the stool of vaccinated, asymptomatic children and their close contacts collected during a prospective cohort study in Veracruz, Mexico, revealed no vaccine-derived polioviruses. This was expected given that the longest duration between sequenced sample collection and the end of the most recent national immunization week was 66 days. However, we identified many low-level variants (<5%) distributed across the 5' UTR and P1 genomic region in all three Sabin serotypes, as well as vaccine-related viruses with multiple canonical mutations associated with phenotypic reversion present at high levels (>90%). These results suggest that monitoring emerging vaccine-related poliovirus variants by deep sequencing may aid in the poliovirus endgame and efforts to ensure global polio eradication. Copyright © 2017 Sahoo et al.

Pre-operative intra-articular deep tissue sampling with novel retrograde forceps improves the diagnostics in periprosthetic joint infection.

PubMed

Wimmer, Matthias D; Ploeger, Milena M; Friedrich, Max J; Hügle, Thomas; Gravius, Sascha; Randau, Thomas M

2017-07-01

Histopathological tissue analysis is a key parameter within the diagnostic algorithm for suspected periprosthetic joint infections (PJIs), conventionally acquired in open surgery. In 2014, Hügle and co-workers introduced novel retrograde forceps for retrograde synovial biopsy with simultaneous fluid aspiration of the knee joint. We hypothesised that tissue samples acquired by retrograde synovial biopsy are equal to intra-operatively acquired deep representative tissue samples regarding bacterial detection and differentiation of periprosthetic infectious membranes. Thirty patients (male n = 15, 50%; female n = 15, 50%) with 30 suspected PJIs in painful total hip arthroplasties (THAs) were included in this prospective, controlled, non-blinded trial. The results were compared with intra-operatively obtained representative deep tissue samples. In summary, 27 out of 30 patients were diagnosed correctly as infected (17/17) or non-infected (10/13). The sensitivity to predict a PJI using the Retroforce® sampling forceps in addition to standard diagnostics was 85%, the specificity 100%. Retrograde synovial biopsy is a new and rapid diagnostic procedure under local anaesthesia in patients with painful THAs with similar histological results compared to deep tissue sampling.

Holographic deep learning for rapid optical screening of anthrax spores

PubMed Central

Jo, YoungJu; Park, Sangjin; Jung, JaeHwang; Yoon, Jonghee; Joo, Hosung; Kim, Min-hyeok; Kang, Suk-Jo; Choi, Myung Chul; Lee, Sang Yup; Park, YongKeun

2017-01-01

Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be used in realistic settings of biological warfare. We present an optical method for rapid and label-free screening of Bacillus anthracis spores through the synergistic application of holographic microscopy and deep learning. A deep convolutional neural network is designed to classify holographic images of unlabeled living cells. After training, the network outperforms previous techniques in all accuracy measures, achieving single-spore sensitivity and subgenus specificity. The unique “representation learning” capability of deep learning enables direct training from raw images instead of manually extracted features. The method automatically recognizes key biological traits encoded in the images and exploits them as fingerprints. This remarkable learning ability makes the proposed method readily applicable to classifying various single cells in addition to B. anthracis, as demonstrated for the diagnosis of Listeria monocytogenes, without any modification. We believe that our strategy will make holographic microscopy more accessible to medical doctors and biomedical scientists for easy, rapid, and accurate point-of-care diagnosis of pathogens. PMID:28798957

Quantum dots versus organic fluorophores in fluorescent deep-tissue imaging--merits and demerits.

PubMed

Bakalova, Rumiana; Zhelev, Zhivko; Gadjeva, Veselina

2008-12-01

The use of fluorescence in deep-tissue imaging is rapidly expanding in last several years. The progress in fluorescent molecular probes and fluorescent imaging techniques gives an opportunity to detect single cells and even molecular targets in live organisms. The highly sensitive and high-speed fluorescent molecular sensors and detection devices allow the application of fluorescence in functional imaging. With the development of novel bright fluorophores based on nanotechnologies and 3D fluorescence scanners with high spatial and temporal resolution, the fluorescent imaging has a potential to become an alternative of the other non-invasive imaging techniques as magnetic resonance imaging, positron-emission tomography, X-ray, computing tomography. The fluorescent imaging has also a potential to give a real map of human anatomy and physiology. The current review outlines the advantages of fluorescent nanoparticles over conventional organic dyes in deep-tissue imaging in vivo and defines the major requirements to the "perfect fluorophore". The analysis proceeds from the basic principles of fluorescence and major characteristics of fluorophores, light-tissue interactions, and major limitations of fluorescent deep-tissue imaging. The article is addressed to a broad readership - from specialists in this field to university students.

Deep eutectic-solvothermal synthesis of nanostructured ceria

PubMed Central

Hammond, Oliver S.; Edler, Karen J.; Bowron, Daniel T.; Torrente-Murciano, Laura

2017-01-01

Ceria is a technologically important material with applications in catalysis, emissions control and solid-oxide fuel cells. Nanostructured ceria becomes profoundly more active due to its enhanced surface area to volume ratio, reactive surface oxygen vacancy concentration and superior oxygen storage capacity. Here we report the synthesis of nanostructured ceria using the green Deep Eutectic Solvent reline, which allows morphology and porosity control in one of the less energy-intensive routes reported to date. Using wide Q-range liquid-phase neutron diffraction, we elucidate the mechanism of reaction at a molecular scale at considerably milder conditions than the conventional hydrothermal synthetic routes. The reline solvent plays the role of a latent supramolecular catalyst where the increase in reaction rate from solvent-driven pre-organization of the reactants is most significant. This fundamental understanding of deep eutectic-solvothermal methodology will enable future developments in low-temperature synthesis of nanostructured ceria, facilitating its large-scale manufacturing using green, economic, non-toxic solvents. PMID:28120829

Effect of deep cryogenic treatment on the microstructure and wear performance of Cr-Mn-Cu white cast iron grinding media

NASA Astrophysics Data System (ADS)

Vidyarthi, M. K.; Ghose, A. K.; Chakrabarty, I.

2013-12-01

The phase transformation and grinding wear behavior of Cr-Mn-Cu white cast irons subjected to destabilization treatment followed by air cooling or deep cryogenic treatment were studied as a part of the development program of substitute alloys for existing costly wear resistant alloys. The microstructural evolution during heat treatment and the consequent improvement in grinding wear performance were evaluated with optical and scanning electron microscopy, X-ray diffraction analysis, bulk hardness, impact toughness and corrosion rate measurements, laboratory ball mill grinding wear test etc. The deep cryogenic treatment has a significant effect in minimizing the retained austenite content and converts it to martensite embedded with fine M7C3 alloy carbides. The cumulative wear losses in cryotreated alloys are lesser than those with conventionally destabilized alloys followed by air cooling both in wet and dry grinding conditions. The cryotreated Cr-Mn-Cu irons exhibit comparable wear performance to high chromium irons.

Architectural design of a ground-based deep-space optical reception antenna

NASA Technical Reports Server (NTRS)

Kerr, E. L.

1989-01-01

An architectural design of a ground-based antenna (telescope) for receiving optical communications from deep space is presented. Physical and optical parameters, and their effect on the performance and cost considerations, are described. The channel capacity of the antenna is 100 kbits/s from Saturn and 5 Mbits/s from Mars. A novel sunshade is designed to permit optical communication even when the deep-space laser source is as close to the sun as 12 deg. Inserts in the tubes of the sunshade permit operations at solar elongations as small as 6 or 3 deg. The Nd:YAG source laser and the Fraunhofer filter (a narrow-band predetection optical filter) are tuned to match the Doppler shifts of the source and background. A typical Saturn-to-earth data link can reduce its source power requirement from 8.2 W to 2 W of laser output by employing a Fraunhofer filter instead of a conventional multilayer dielectric filter.

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

PubMed

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

2014-05-01

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

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue

PubMed Central

Peyster, Eliot G.; Frank, Renee; Margulies, Kenneth B.; Feldman, Michael D.

2018-01-01

Over 26 million people worldwide suffer from heart failure annually. When the cause of heart failure cannot be identified, endomyocardial biopsy (EMB) represents the gold-standard for the evaluation of disease. However, manual EMB interpretation has high inter-rater variability. Deep convolutional neural networks (CNNs) have been successfully applied to detect cancer, diabetic retinopathy, and dermatologic lesions from images. In this study, we develop a CNN classifier to detect clinical heart failure from H&E stained whole-slide images from a total of 209 patients, 104 patients were used for training and the remaining 105 patients for independent testing. The CNN was able to identify patients with heart failure or severe pathology with a 99% sensitivity and 94% specificity on the test set, outperforming conventional feature-engineering approaches. Importantly, the CNN outperformed two expert pathologists by nearly 20%. Our results suggest that deep learning analytics of EMB can be used to predict cardiac outcome. PMID:29614076

Deep donor state of the copper acceptor as a source of green luminescence in ZnO

NASA Astrophysics Data System (ADS)

Lyons, J. L.; Alkauskas, A.; Janotti, A.; Van de Walle, C. G.

2017-07-01

Copper impurities have long been linked with green luminescence (GL) in ZnO. Copper is known to introduce an acceptor level close to the conduction band of ZnO, and the GL has conventionally been attributed to transitions involving an excited state which localizes holes on neighboring oxygen atoms. To date, a theoretical description of the optical properties of such deep centers has been difficult to achieve due to the limitations of functionals in the density functional theory. Here, we employ a screened hybrid density functional to calculate the properties of Cu in ZnO. In agreement with the experiment, we find that CuZn features an acceptor level near the conduction band of ZnO. However, we find that CuZn also gives rise to a deep donor level 0.46 eV above the valence band of ZnO; the calculated optical transitions involving this state agree well with the GL observed in ZnO:Cu.

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.

PubMed

Nirschl, Jeffrey J; Janowczyk, Andrew; Peyster, Eliot G; Frank, Renee; Margulies, Kenneth B; Feldman, Michael D; Madabhushi, Anant

2018-01-01

Over 26 million people worldwide suffer from heart failure annually. When the cause of heart failure cannot be identified, endomyocardial biopsy (EMB) represents the gold-standard for the evaluation of disease. However, manual EMB interpretation has high inter-rater variability. Deep convolutional neural networks (CNNs) have been successfully applied to detect cancer, diabetic retinopathy, and dermatologic lesions from images. In this study, we develop a CNN classifier to detect clinical heart failure from H&E stained whole-slide images from a total of 209 patients, 104 patients were used for training and the remaining 105 patients for independent testing. The CNN was able to identify patients with heart failure or severe pathology with a 99% sensitivity and 94% specificity on the test set, outperforming conventional feature-engineering approaches. Importantly, the CNN outperformed two expert pathologists by nearly 20%. Our results suggest that deep learning analytics of EMB can be used to predict cardiac outcome.

Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer.

PubMed

Weng, Sheng; Xu, Xiaoyun; Li, Jiasong; Wong, Stephen T C

2017-10-01

Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Generative Adversarial Networks: An Overview

NASA Astrophysics Data System (ADS)

Creswell, Antonia; White, Tom; Dumoulin, Vincent; Arulkumaran, Kai; Sengupta, Biswa; Bharath, Anil A.

2018-01-01

Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this through deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image super-resolution and classification. The aim of this review paper is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application.

Minimal Magnetic States of the Sun and the Solar Wind: Implications for the Origin of the Slow Solar Wind

NASA Astrophysics Data System (ADS)

Cliver, E. W.; von Steiger, R.

2017-09-01

During the last decade it has been proposed that both the Sun and the solar wind have minimum magnetic states, lowest order levels of magnetism that underlie the 11-yr cycle as well as longer-term variability. Here we review the literature on basal magnetic states at the Sun and in the heliosphere and draw a connection between the two based on the recent deep 2008-2009 minimum between cycles 23 and 24. In particular, we consider the implications of the low solar activity during the recent minimum for the origin of the slow solar wind.

“I’m stronger than I thought”: Native women reconnecting to body, health, and place

PubMed Central

Schultz, Katie; Walters, Karina L.; Beltran, Ramona; Stroud, Sandy; Johnson-Jennings, Michelle

2016-01-01

This community-based research applied principles of wilderness experience programming and Indigenous knowledges in an exploratory intervention designed to address health disparities in a tribal community. Drawing on historical trauma frameworks, tribal members rewalked the Trail of Tears to consider its effect on contemporary tribal health. Qualitative data from tribal members suggest that engagement with place and experiential learning, particularly the physical and emotional challenge of the Trail, facilitated changes in health beliefs, attitudes, and behaviors. Deep engagement outside of traditional health service settings should be considered in interventions and may be particularly effective in promoting positive health behaviors in Native communities. PMID:27164432

Coalbed methane: Clean energy for the world

USGS Publications Warehouse

Ahmed, A.-J.; Johnston, S.; Boyer, C.; Lambert, S.W.; Bustos, O.A.; Pashin, J.C.; Wray, A.

2009-01-01

Coalbed methane (CBM) has the potential to emerge as a significant clean energy resource. It also has the potential to replace other diminishing hydrocarbon reserves. The latest developments in technologies and methodologies are playing a key role in harnessing this unconventional resource. Some of these developments include adaptations of existing technologies used in conventional oil and gas generations, while others include new applications designed specifically to address coal's unique properties. Completion techniques have been developed that cause less damage to the production mechanisms of coal seams, such as those occurring during cementing operations. Stimulation fluids have also been engineered specifically to enhance CBM production. Deep coal deposits that remain inaccessible by conventional mining operations offer CBM development opportunities.

Performance of 75 millimeter-bore arched outer-race ball bearings

NASA Technical Reports Server (NTRS)

Coe, H. H.; Hamrock, B. J.

1976-01-01

An investigation was performed to determine the operating characteristics of 75-mm bore, arched outer-race bearings, and to compare the data with those for a similar, but conventional, deep groove ball bearing. Further, results of an analytical study, made using a computer program developed previously, were compared with the experimental data. Bearings were tested up to 28,000 rpm shaft speed with a load of 2200 N (500 lb). The amount of arching was 0.13, 0.25, and 0.51 mm (.005, .010, and .020 in.). All bearings operated satisfactorily. The outer-race temperatures and the torques, however, were consistently higher for the arched bearings than for the conventional bearing.

Performance of 75-millimeter bore arched outer-race ball bearings

NASA Technical Reports Server (NTRS)

Coe, H. H.; Hamrock, B. J.

1976-01-01

An investigation was performed to determine the operating characteristics of 75-mm bore, arched outer-race bearings, and to compare the data with those for a similar, but conventional, deep groove ball bearing. Further, results of an analytical study, made using a computer program developed previously, were compared with the experimental data. Bearings were tested up to 28,000 rpm shaft speed with a load of 2,200 N (500 lb). The amount of arching was 0.13, 0.25, and 0.51 mm (0.005, 0.010, and 0.020 in). All bearings operated satisfactorily. The outer-race temperatures and the torques, however, were consistently higher for the arched bearings than for the conventional bearings

An update on coating/manufacturing techniques of microneedles.

PubMed

Tarbox, Tamara N; Watts, Alan B; Cui, Zhengrong; Williams, Robert O

2017-12-29

Recently, results have been published for the first successful phase I human clinical trial investigating the use of dissolving polymeric microneedles… Even so, further clinical development represents an important hurdle that remains in the translation of microneedle technology to approved products. Specifically, the potential for accumulation of polymer within the skin upon repeated application of dissolving and coated microneedles, combined with a lack of safety data in humans, predicates a need for further clinical investigation. Polymers are an important consideration for microneedle technology-from both manufacturing and drug delivery perspectives. The use of polymers enables a tunable delivery strategy, but the scalability of conventional manufacturing techniques could arguably benefit from further optimization. Micromolding has been suggested in the literature as a commercially viable means to mass production of both dissolving and swellable microneedles. However, the reliance on master molds, which are commonly manufactured using resource intensive microelectronics industry-derived processes, imparts notable material and design limitations. Further, the inherently multi-step filling and handling processes associated with micromolding are typically batch processes, which can be challenging to scale up. Similarly, conventional microneedle coating processes often follow step-wise batch processing. Recent developments in microneedle coating and manufacturing techniques are highlighted, including micromilling, atomized spraying, inkjet printing, drawing lithography, droplet-born air blowing, electro-drawing, continuous liquid interface production, 3D printing, and polyelectrolyte multilayer coating. This review provides an analysis of papers reporting on potentially scalable production techniques for the coating and manufacturing of microneedles.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Performance improvement of AlGaN-based deep-ultraviolet light-emitting diodes via Al-composition graded quantum wells

NASA Astrophysics Data System (ADS)

Lu, Lin; Zhang, Yu; Xu, Fujun; Ding, Gege; Liu, Yuhang

2018-06-01

Characteristics of AlGaN-based deep-ultraviolet light-emitting diodes (DUV-LEDs) with step-like and Al-composition graded quantum wells have been investigated. The simulation results show that compared to DUV-LEDs with the conventional AlGaN multiple quantum wells (MQWs) structure, the light output power (LOP) and efficiency droop of DUV-LEDs with the Al-composition graded wells were remarkably improved. The key factor accounting for the improved performance is ascribed to the better modulation of carrier distribution in the quantum wells to increase the overlap between electron and hole wavefunctions, which contributes to more efficient recombination of electrons and holes, and thereby a significant enhancement in the LOP.

The decision-making process in Brazil's ratification of the World Health Organization Framework Convention on Tobacco Control.

PubMed

Rangel, Erica Cavalcanti; Pereira, Andre; Cavalcante, Tania Maria; Oliveira, Egléubia Andrade; Silva, Vera Luiza da Costa E

2017-09-21

Tobacco consumption is a leading cause of various types of cancer and other tobacco-related diseases. In 2003, the World Health Assembly adopted the World Health Organization Framework Convention on Tobacco Control (WHO-FCTC), which aims to protect citizens from the health, social, environmental, and economic consequences of tobacco consumption and exposure to tobacco smoke. The Convention was to be ratified by the Member States of the WHO; in Brazil's case, ratification involved the National Congress, which held public hearings in the country's leading tobacco growing communities (municipalities). The current study analyzes this decision-making process according to the different interests, positions, and stakeholders. In methodological terms, this is a qualitative study based on document research, drawing primarily on the shorthand notes from the public hearings. We analyze the interests and arguments for and against ratification. The article shows that although preceded by intense debates, the final decision in favor of ratification was made by a limited group of government stakeholders, characterizing a decision-making process similar to a funnel.

Experimental and Numerical Studies on Isothermal and Non-isothermal Deep Drawing of IS 513 CR3 Steel Sheets

NASA Astrophysics Data System (ADS)

Mayavan, T.; Karthikeyan, L.; Senthilkumar, V. S.

2016-11-01

The present work aims to investigate the effects of the temperature gradient developed within the tool profiles on the formability of IS 513 CR3-grade steel sheets using the cup drawing test. The deformation characteristics of steel sheets were analyzed by comparing the thicknesses in various regions of the formed cup and also the limiting drawing ratios (LDR). Finite element simulations were carried out to predict the behavior of the steel sheets in isothermal and non-isothermal forming using Abaqus/Standard 6.12-1. An analytical model created by Kim was used to validate the experimental and finite element analysis (FEA) results on identical process parameters. Both the FEA and analytical modeling results showed that formability improvement is possible in warm forming; the findings are in good agreement with the experimental results in determining the locations and values of excessive thinning. The results also indicated that formability improvement cannot be achieved by keeping the tooling temperature at the same level. The LDR increased by around 9.5% in isothermal forming and by 19% in non-isothermal forming (with the punch maintained at a lower temperature compared with the die and blank holder). In addition, the fractured surfaces of unsuccessfully formed samples were analyzed using scanning electron microscopy. Metallographic investigations confirmed that the fracture mechanism during the forming of IS 513 CR3-grade steel sheets depends on the brittleness, strain hardening value, forming temperature, and magnitude of stresses developed.

Pipeline corridors through wetlands - impacts on plant communities: Deep Creek and Brandy Branch crossings, Nassau County, Florida

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

Shem, L.M.; Van Dyke, G.D.; Zimmerman, R.E.

The goal of the Gas Research Institute Wetland Corridors Program is to document impacts of existing pipelines on the wetlands they traverse. To accomplish this goal, 12 existing wetland crossings were surveyed. These sites varied in elapsed time since pipeline construction, wetland type, pipeline installation techniques, and right-of-way (ROW) management practices. This report presents the results of surveys conducted July 14-18, 1992, at the Deep Creek and the Brandy Branch crossings of a pipeline installed during May 1991 in Nassau County, Florida. Both floodplains supported bottomland hardwood forests. The pipeline at the Deep Creek crossing was installed by means ofmore » horizontal directional drilling after the ROW had been clear-cut, while the pipeline at the Brandy Branch crossing was installed by means of conventional open trenching. Neither site was seeded or fertilized. At the time of sampling, a dense vegetative community, made up primarily of native perennial herbaceous species, occupied the ROW within the Deep Creek floodplain. The Brandy Branch ROW was vegetated by a less dense stand of primarily native perennial herbaceous plants. Plant diversity was also lower at the Brandy Branch crossing than at the Deep Creek crossing. The results suggest that some of the differences in plant communities are related to the more hydric conditions at the Brandy Branch floodplain.« less