Urban High School Students' Critical Science Agency: Conceptual Understandings and Environmental Actions around Climate Change

ERIC Educational Resources Information Center

McNeill, Katherine L.; Vaughn, Meredith Houle

2012-01-01

This study investigates how the enactment of a climate change curriculum supports students' development of critical science agency, which includes students developing deep understandings of science concepts and the ability to take action at the individual and community levels. We examined the impact of a four to six week urban ecology curriculum…

Curriculum Development for Quantitative Skills in Degree Programs: A Cross-Institutional Study Situated in the Life Sciences

ERIC Educational Resources Information Center

Matthews, Kelly E.; Belward, Shaun; Coady, Carmel; Rylands, Leanne; Simbag, Vilma

2016-01-01

Higher education policies are increasingly focused on graduate learning outcomes, which infer an emphasis on, and deep understanding of, curriculum development across degree programs. As disciplinary influences are known to shape teaching and learning activities, research situated in disciplinary contexts is useful to further an understanding of…

DeepNeuron: an open deep learning toolbox for neuron tracing.

PubMed

Zhou, Zhi; Kuo, Hsien-Chi; Peng, Hanchuan; Long, Fuhui

2018-06-06

Reconstructing three-dimensional (3D) morphology of neurons is essential for understanding brain structures and functions. Over the past decades, a number of neuron tracing tools including manual, semiautomatic, and fully automatic approaches have been developed to extract and analyze 3D neuronal structures. Nevertheless, most of them were developed based on coding certain rules to extract and connect structural components of a neuron, showing limited performance on complicated neuron morphology. Recently, deep learning outperforms many other machine learning methods in a wide range of image analysis and computer vision tasks. Here we developed a new Open Source toolbox, DeepNeuron, which uses deep learning networks to learn features and rules from data and trace neuron morphology in light microscopy images. DeepNeuron provides a family of modules to solve basic yet challenging problems in neuron tracing. These problems include but not limited to: (1) detecting neuron signal under different image conditions, (2) connecting neuronal signals into tree(s), (3) pruning and refining tree morphology, (4) quantifying the quality of morphology, and (5) classifying dendrites and axons in real time. We have tested DeepNeuron using light microscopy images including bright-field and confocal images of human and mouse brain, on which DeepNeuron demonstrates robustness and accuracy in neuron tracing.

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation.

PubMed

Hohman, Fred; Hodas, Nathan; Chau, Duen Horng

2017-05-01

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as "black-boxes" due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user's data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

Level of Neutral Buoyancy, Deep Convective Outflow, and Hot Tower: New Perspectives Based on the A-Train Observations

NASA Astrophysics Data System (ADS)

Takahashi, H.; Luo, J.; Stephens, G. L.

2016-12-01

Deep convective cores, or "hot towers (HTs)", play a significant role in controlling the energy budgets and hydrological cycles. The vertical convective transport by HTs is like an express elevator transporting the near-surface air directly into the upper troposphere or lower stratosphere (e.g., Riehl and Malkus, 1958; Sun and Lindzen, 1993; Soden and Fu, 1995). The vertical convective transport will eventually make a transition to horizontal outflows where widespread cirrus anvils develop, which also play an important role in radiative-convective feedbacks (e.g., Stephens et al. 2008). In this study, we introduce two proxies to evaluate the strength of vertical and horizontal convective mass transport by hot towers. Result shows that HTs tend to have wider horizontal mass transport over land than ocean. In addition, an important aspect of the deep convection-to-outflow transition is the altitude where the outflow occurs, which can be conveniently summarized into a single parameter called level of neutral buoyancy (LNB). LNB is a critical parameter for understanding convection because it sets the potential vertical extent for convective development. This study develops a deeper and more comprehensive understanding of the relationship between LNB and deep convective outflow, including regional variations. To this end, a useful proxy to estimate convective dilution is introduced. Results show that active convective dilution can be seen over the Warm Pool throughout the year, while deep convection over tropical Africa and Amazonia tends to be less diluted.

A Comparative Study of Learning Strategies Used by Romanian and Hungarian Preuniversity Students in Science Learning

ERIC Educational Resources Information Center

Lingvay, Mónika; Timofte, Roxana S.; Ciascai, Liliana; Predescu, Constantin

2015-01-01

Development of pupils' deep learning approach is an important goal of education nowadays, considering that a deep learning approach is mediating conceptual understanding and transfer. Different performance at PISA tests of Romanian and Hungarian pupils cause us to commence a study for the analysis of learning approaches employed by these pupils.…

Reading with Understanding: A Global Expectation

ERIC Educational Resources Information Center

Shea, Mary; Ceprano, Maria

2017-01-01

This article outlines the complexity of reading with understanding, what is required for full and deep comprehension, the state of affairs with regard to reading comprehension in developed countries, possible etiologies for low performances, and suggestions for instruction in specific skills and strategies to improve students' demonstrated…

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

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

Hohman, Frederick M.; Hodas, Nathan O.; Chau, Duen Horng

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as “black-boxes” due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user’s data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

The Development of a Conceptual Framework and Tools to Assess Undergraduates' Principled Use of Models in Cellular Biology

ERIC Educational Resources Information Center

Richmond, Gail; Merritt, Brett; Urban-Lurain, Mark; Parker, Joyce

2010-01-01

Recent science education reform has been marked by a shift away from a focus on facts toward deep, rich, conceptual understanding. This requires assessment that also focuses on conceptual understanding rather than recall of facts. This study outlines our development of a new assessment framework and tool--a taxonomy--which, unlike existing…

Innovations in deep brain stimulation methodology.

PubMed

Kühn, Andrea A; Volkmann, Jens

2017-01-01

Deep brain stimulation is a powerful clinical method for movement disorders that no longer respond satisfactorily to pharmacological management, but its progress has been hampered by stagnation in technological procedure solutions and device development. Recently, the combined research efforts of bioengineers, neuroscientists, and clinicians have helped to better understand the mechanisms of deep brain stimulation, and solutions for the translational roadblock are emerging. Here, we define the needs for methodological advances in deep brain stimulation from a neurophysiological perspective and describe technological solutions that are currently evaluated for near-term clinical application. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Deep Space Habitat Concept Demonstrator

NASA Technical Reports Server (NTRS)

Bookout, Paul S.; Smitherman, David

2015-01-01

This project will develop, integrate, test, and evaluate Habitation Systems that will be utilized as technology testbeds and will advance NASA's understanding of alternative deep space mission architectures, requirements, and operations concepts. Rapid prototyping and existing hardware will be utilized to develop full-scale habitat demonstrators. FY 2014 focused on the development of a large volume Space Launch System (SLS) class habitat (Skylab Gen 2) based on the SLS hydrogen tank components. Similar to the original Skylab, a tank section of the SLS rocket can be outfitted with a deep space habitat configuration and launched as a payload on an SLS rocket. This concept can be used to support extended stay at the Lunar Distant Retrograde Orbit to support the Asteroid Retrieval Mission and provide a habitat suitable for human missions to Mars.

Understanding social collaboration between actors and technology in an automated and digitised deep mining environment.

PubMed

Sanda, M-A; Johansson, J; Johansson, B; Abrahamsson, L

2011-10-01

The purpose of this article is to develop knowledge and learning on the best way to automate organisational activities in deep mines that could lead to the creation of harmony between the human, technical and the social system, towards increased productivity. The findings showed that though the introduction of high-level technological tools in the work environment disrupted the social relations developed over time amongst the employees in most situations, the technological tools themselves became substitute social collaborative partners to the employees. It is concluded that, in developing a digitised mining production system, knowledge of the social collaboration between the humans (miners) and the technology they use for their work must be developed. By implication, knowledge of the human's subject-oriented and object-oriented activities should be considered as an important integral resource for developing a better technological, organisational and human interactive subsystem when designing the intelligent automation and digitisation systems for deep mines. STATEMENT OF RELEVANCE: This study focused on understanding the social collaboration between humans and the technologies they use to work in underground mines. The learning provides an added knowledge in designing technologies and work organisations that could better enhance the human-technology interactive and collaborative system in the automation and digitisation of underground mines.

Geoscience Education and Global Development

ERIC Educational Resources Information Center

Locke, Sharon; Libarkin, Julie; Chang, Chun-Yen

2012-01-01

A fundamental goal of geoscience education is ensuring that all inhabitants of the planet have knowledge of the natural processes that shape the physical environment, and understand how the actions of humans have an impact on the Earth on local, regional, and global scales. Geoscientists accept that deep understanding of natural processes requires…

Systems and Cycles: Learning about Aquatic Ecosystems

ERIC Educational Resources Information Center

Hmelo-Silver, Cindy E.; Jordan, Rebecca; Eberbach, Catherine; Rugaber, Spencer; Goel, Ashok

2011-01-01

In this research, the authors present both the design and preliminary testing of a technology-intensive classroom intervention designed to support middle schools students' understanding of an aquatic ecosystem. The goals of their intervention are to help learners develop deep understanding of ecosystems and to use tools that make the relationships…

The subsurface record for the Anthropocene based on the global analysis of deep wells

NASA Astrophysics Data System (ADS)

Rose, K.

2016-12-01

While challenges persist in the characterization of Earth's subsurface, over two centuries of exploration resulting in more than six million deep wellbores, offer insights into these systems. Characteristics of the subsurface vary and can be analyzed on a variety of spatial scales using geospatial tools and methods. Characterization and prediction of subsurface properties, such as depth, thickness, porosity, permeability, pressure and temperature, are important for models and interpretations of the subsurface. Subsurface studies contribute to insights and understanding of natural system but also enable predictions and assessments of subsurface resources and support environmental and geohazard assessments. As the geo-data science landscape shifts, becoming more open, there are increasing opportunities to fill knowledge gaps, mine large, interrelated datasets, and develop innovative methods to improve our understanding of the subsurface and the impacts of its exploration. In this study, a global dataset of more than 6,000,000 deep subsurface wells has been assembled using ArcGIS and Access, which reflects to a first order, the cumulative representation of over two centuries of drilling. Wellbore data, in general represent the only portal for direct measurement and characterization of deep subsurface properties. As human engineering of the subsurface evolves from a focus on hydrocarbon resource development to include subsurface waste product disposal (e.g. CO2, industrial waste, etc) and production of other deep subsurface resources, such as heat and water resources, there is the increasing need to improve characterization techniques and understand local and global ramifications of anthropogenic interaction with the subsurface. Data and geospatial analyses are reviewed to constrain the extent to which human interactions, not just with Earth's surface systems, atmospheric and geologic, but subsurface systems will result in an enduring signature of human influences on the planet. Specifically, the extent and enduring signature of subsurface interactions with the planet, utilizing the four-dimensional, spatial and temporal, record for known deep wellbores is utilized.

Future Mission Trends and their Implications for the Deep Space Network

NASA Technical Reports Server (NTRS)

Abraham, Douglas S.

2006-01-01

Planning for the upgrade and/or replacement of Deep Space Network (DSN) assets that typically operate for forty or more years necessitates understanding potential customer needs as far into the future as possible. This paper describes the methodology Deep Space Network (DSN) planners use to develop this understanding, some key future mission trends that have emerged from application of this methodology, and the implications of the trends for the DSN's future evolution. For NASA's current plans out to 2030, these trends suggest the need to accommodate: three times as many communication links, downlink rates two orders of magnitude greater than today's, uplink rates some four orders of magnitude greater, and end-to-end link difficulties two-to-three orders of magnitude greater. To meet these challenges, both DSN capacity and capability will need to increase.

ACTIVIS: Visual Exploration of Industry-Scale Deep Neural Network Models.

PubMed

Kahng, Minsuk; Andrews, Pierre Y; Kalro, Aditya; Polo Chau, Duen Horng

2017-08-30

While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ACTIVIS, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance- and subset-level. ACTIVIS has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ACTIVIS may work with different models.

Understanding the Patient Experience of Peripherally Inserted Central Catheter-Related Deep Vein Thrombosis Using Interpretive Phenomenology.

PubMed

Meyer, Britt M

The purpose of this interpretive phenomenological study was to determine what it means to patients to live with a peripherally inserted central catheter (PICC)-related deep vein thrombosis and to describe the influence of the experience on the individual's quality of life. The sample included 11 adult patients from an acute care setting who developed a PICC-related symptomatic thrombus between November 2014 and March 2016, using purposive sampling. Three distinct themes emerged from the data in this study: a loss of trust in health care providers, additional burdens to existing problems, and a yearning for understanding.

A Discussion-Based Online Approach to Fostering Deep Cultural Inquiry in an Introductory Language Course

ERIC Educational Resources Information Center

Garrett-Rucks, Paula

2013-01-01

Fostering and assessing language learners' cultural understanding is a daunting task, particularly at the early stages of language learning with target language instruction. The purpose of this study was to explore the development of beginning French language learners' intercultural understanding in a computer-mediated environment where students…

A Prototype Performance Assessment Model for Generic Deep Borehole Repository for High-Level Nuclear Waste - 12132

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

Lee, Joon H.; Arnold, Bill W.; Swift, Peter N.

2012-07-01

A deep borehole repository is one of the four geologic disposal system options currently under study by the U.S. DOE to support the development of a long-term strategy for geologic disposal of commercial used nuclear fuel (UNF) and high-level radioactive waste (HLW). The immediate goal of the generic deep borehole repository study is to develop the necessary modeling tools to evaluate and improve the understanding of the repository system response and processes relevant to long-term disposal of UNF and HLW in a deep borehole. A prototype performance assessment model for a generic deep borehole repository has been developed using themore » approach for a mined geological repository. The preliminary results from the simplified deep borehole generic repository performance assessment indicate that soluble, non-sorbing (or weakly sorbing) fission product radionuclides, such as I-129, Se-79 and Cl-36, are the likely major dose contributors, and that the annual radiation doses to hypothetical future humans associated with those releases may be extremely small. While much work needs to be done to validate the model assumptions and parameters, these preliminary results highlight the importance of a robust seal design in assuring long-term isolation, and suggest that deep boreholes may be a viable alternative to mined repositories for disposal of both HLW and UNF. (authors)« less

Machine Learning, deep learning and optimization in computer vision

NASA Astrophysics Data System (ADS)

Canu, Stéphane

2017-03-01

As quoted in the Large Scale Computer Vision Systems NIPS workshop, computer vision is a mature field with a long tradition of research, but recent advances in machine learning, deep learning, representation learning and optimization have provided models with new capabilities to better understand visual content. The presentation will go through these new developments in machine learning covering basic motivations, ideas, models and optimization in deep learning for computer vision, identifying challenges and opportunities. It will focus on issues related with large scale learning that is: high dimensional features, large variety of visual classes, and large number of examples.

Deep Molecular Diversity of Mammalian Synapses: Why It Matters and How to Measure It

PubMed Central

O’Rourke, Nancy A.; Weiler, Nick C.; Micheva, Kristina D.; Smith, Stephen J

2013-01-01

Summary Pioneering studies during the middle of the twentieth century revealed substantial diversity amongst mammalian chemical synapses and led to a widely accepted synapse type classification based on neurotransmitter molecule identity. Subsequently, powerful new physiological, genetic and structural methods have enabled the discovery of much deeper functional and molecular diversity within each traditional neurotransmitter type. Today, this deep diversity continues to pose both daunting challenges and exciting new opportunities for neuroscience. Our growing understanding of deep synapse diversity may transform how we think about and study neural circuit development, structure and function. PMID:22573027

Exploring the relationships between epistemic beliefs about medicine and approaches to learning medicine: a structural equation modeling analysis.

PubMed

Chiu, Yen-Lin; Liang, Jyh-Chong; Hou, Cheng-Yen; Tsai, Chin-Chung

2016-07-18

Students' epistemic beliefs may vary in different domains; therefore, it may be beneficial for medical educators to better understand medical students' epistemic beliefs regarding medicine. Understanding how medical students are aware of medical knowledge and how they learn medicine is a critical issue of medical education. The main purposes of this study were to investigate medical students' epistemic beliefs relating to medical knowledge, and to examine their relationships with students' approaches to learning medicine. A total of 340 undergraduate medical students from 9 medical colleges in Taiwan were surveyed with the Medical-Specific Epistemic Beliefs (MSEB) questionnaire (i.e., multi-source, uncertainty, development, justification) and the Approach to Learning Medicine (ALM) questionnaire (i.e., surface motive, surface strategy, deep motive, and deep strategy). By employing the structural equation modeling technique, the confirmatory factor analysis and path analysis were conducted to validate the questionnaires and explore the structural relations between these two constructs. It was indicated that medical students with multi-source beliefs who were suspicious of medical knowledge transmitted from authorities were less likely to possess a surface motive and deep strategies. Students with beliefs regarding uncertain medical knowledge tended to utilize flexible approaches, that is, they were inclined to possess a surface motive but adopt deep strategies. Students with beliefs relating to justifying medical knowledge were more likely to have mixed motives (both surface and deep motives) and mixed strategies (both surface and deep strategies). However, epistemic beliefs regarding development did not have significant relations with approaches to learning. Unexpectedly, it was found that medical students with sophisticated epistemic beliefs (e.g., suspecting knowledge from medical experts) did not necessarily engage in deep approaches to learning medicine. Instead of a deep approach, medical students with sophisticated epistemic beliefs in uncertain and justifying medical knowledge intended to employ a flexible approach and a mixed approach, respectively.

Stable architectures for deep neural networks

NASA Astrophysics Data System (ADS)

Haber, Eldad; Ruthotto, Lars

2018-01-01

Deep neural networks have become invaluable tools for supervised machine learning, e.g. classification of text or images. While often offering superior results over traditional techniques and successfully expressing complicated patterns in data, deep architectures are known to be challenging to design and train such that they generalize well to new data. Critical issues with deep architectures are numerical instabilities in derivative-based learning algorithms commonly called exploding or vanishing gradients. In this paper, we propose new forward propagation techniques inspired by systems of ordinary differential equations (ODE) that overcome this challenge and lead to well-posed learning problems for arbitrarily deep networks. The backbone of our approach is our interpretation of deep learning as a parameter estimation problem of nonlinear dynamical systems. Given this formulation, we analyze stability and well-posedness of deep learning and use this new understanding to develop new network architectures. We relate the exploding and vanishing gradient phenomenon to the stability of the discrete ODE and present several strategies for stabilizing deep learning for very deep networks. While our new architectures restrict the solution space, several numerical experiments show their competitiveness with state-of-the-art networks.

Connecting Reflective Practice, Dialogic Protocols, and Professional Learning

ERIC Educational Resources Information Center

Nehring, James; Laboy, Wilfredo T.; Catarius, Lynn

2010-01-01

In recent years, elements of reflective practice have been popularized in state school professional development. As reflective practice has moved into the mainstream, dialogic protocols have been developed by numerous organizations to structure discourse for deep understanding, enhance professional practice and advance organizational learning.…

Early Childhood Education Students' Perceptions of Community College Distance Education Courses

ERIC Educational Resources Information Center

Crump, Tracy Lynn

2010-01-01

In order for children to receive the best in quality care, early childhood teachers must have a deep understanding of child development and developmentally appropriate teaching methodologies that can only be acquired through accessible and sustainable professional development. This type of professional development for many students comes in the…

Can Slope Be Negative in 3-Space? Studying Concept Image of Slope through Collective Definition Construction

ERIC Educational Resources Information Center

Moore-Russo, Deborah; Conner, AnnaMarie; Rugg, Kristina I.

2011-01-01

Developing deep conceptual understanding of what Ma (1999) calls fundamental mathematics is a well-accepted goal of teacher education. This paper presents a microanalysis of an intriguing episode within a course designed to encourage such understanding. An adaptation of Krummheuer's (1995) elaboration of Toulmin's (1958/2003) diagrams is used to…

Developing Deep Understanding and Literacy while Addressing a Gender-Based Literacy Gap

ERIC Educational Resources Information Center

Sun, Yanqing; Zhang, Jianwei; Scardamalia, Marlene

2010-01-01

Online discourse from a class of 22 students (11 boys and 11 girls) was analysed to assess advances in conceptual understanding and literacy. The students worked over a two-year period (Grades 3-4), during which they contributed notes to an online Knowledge Building environment--Knowledge Forum[R]. Contributions revealed that both boys and girls…

Professional Development Aligned with AP Chemistry Curriculum: Promoting Science Practices and Facilitating Enduring Conceptual Understanding

ERIC Educational Resources Information Center

Herrington, Deborah G.; Yezierski, Ellen J.

2014-01-01

The recent revisions to the advanced placement (AP) chemistry curriculum promote deep conceptual understanding of chemistry content over more rote memorization of facts and algorithmic problem solving. For many teachers, this will mean moving away from traditional worksheets and verification lab activities that they have used to address the vast…

Deep Carbon Observatory investigates Carbon from Crust to Core: An Academic Record of the History of Deep Carbon Science

NASA Astrophysics Data System (ADS)

Mitton, S. A.

2017-12-01

Carbon plays an unparalleled role in our lives: as the element of life, as the basis of most of society's energy, as the backbone of most new materials, and as the central focus in efforts to understand Earth's variable and uncertain climate. Yet in spite of carbon's importance, scientists remain largely ignorant of the physical, chemical, and biological behavior of many of Earth's carbon-bearing systems. The Deep Carbon Observatory (DCO) is a global research program to transform our understanding of carbon in Earth. At its heart, DCO is a community of scientists, from biologists to physicists, geoscientists to chemists, and many others whose work crosses these disciplinary lines, forging a new, integrative field of deep carbon science. As a historian of science, I specialise in the history of planetary science and astronomy since 1900. This is directed toward understanding of the history of the steps on the road to discovering the internal dynamics of our planet. Within a framework that describes the historical background to the new field of Earth System Science, I present the first history of deep carbon science. This project will identifies the key discoveries of deep carbon science. It will assess the impact of new knowledge on geochemistry, geodynamics, and geobiology. The project will lead to publication, in book form in 2019, of an illuminating narrative that will highlight the engaging human stories of many remarkable scientists and natural philosophers from whom we have learned about the complexity of Earth's internal world. On this journey of discovery we will encounter not just the pioneering researchers of deep carbon science, but also their institutions, their instrumental inventiveness, and their passion for exploration. The book is organised thematically around the four communities of the Deep Carbon Observatory: Deep Life, Extreme Physics and Chemistry, Reservoirs and Fluxes, and Deep Energy. The presentation has a gallery and list of Deep Carbon Pioneers. As a biographer, I am keenly searching for people who may have been overlooked in the standard accounts of the historical development of geology, geodynamics, and the study of subsurface life. Whom would you choose as pioneers? Can you nominate a colleague, or even add a selfie? Do you have a standout story or personal recollection to enrich my chronicle?

Machine learning for quantum dynamics: deep learning of excitation energy transfer properties

DOE PAGES

Häse, Florian; Kreisbeck, Christoph; Aspuru-Guzik, Alán

2017-01-01

Understanding the relationship between the structure of light-harvesting systems and their excitation energy transfer properties is of fundamental importance in many applications including the development of next generation photovoltaics.

The Secret to Successful Deep-Sea Invasion: Does Low Temperature Hold the Key?

PubMed Central

Smith, Kathryn E.; Thatje, Sven

2012-01-01

There is a general consensus that today’s deep-sea biodiversity has largely resulted from recurrent invasions and speciations occurring through homogenous waters during periods of the Phanerozoic eon. Migrations likely continue today, primarily via isothermal water columns, such as those typical of Polar Regions, but the necessary ecological and physiological adaptations behind them are poorly understood. In an evolutionary context, understanding the adaptations, which allow for colonisation to high-pressure environments, may enable us to predict future events. In this investigation, we examine pressure tolerance during development, in the shallow-water neogastropod Buccinum undatum using thermally acclimated egg masses from temperate and sub-polar regions across the species range. Fossil records indicate neogastropods to have a deep-water origin, suggesting shallow-water species may be likely candidates for re-emergence into the deep sea. Our results show population level differences in physiological thresholds, which indicate low temperature acclimation to increase pressure tolerance. These findings imply this species is capable of deep-sea penetration through isothermal water columns prevailing at high latitudes. This study gives new insight into the fundamentals behind past and future colonisation events. Such knowledge is instrumental to understand better how changes in climate envelopes affect the distribution and radiation of species along latitudinal as well as bathymetric temperature gradients. PMID:23227254

The secret to successful deep-sea invasion: does low temperature hold the key?

PubMed

Smith, Kathryn E; Thatje, Sven

2012-01-01

There is a general consensus that today's deep-sea biodiversity has largely resulted from recurrent invasions and speciations occurring through homogenous waters during periods of the Phanerozoic eon. Migrations likely continue today, primarily via isothermal water columns, such as those typical of Polar Regions, but the necessary ecological and physiological adaptations behind them are poorly understood. In an evolutionary context, understanding the adaptations, which allow for colonisation to high-pressure environments, may enable us to predict future events. In this investigation, we examine pressure tolerance during development, in the shallow-water neogastropod Buccinum undatum using thermally acclimated egg masses from temperate and sub-polar regions across the species range. Fossil records indicate neogastropods to have a deep-water origin, suggesting shallow-water species may be likely candidates for re-emergence into the deep sea. Our results show population level differences in physiological thresholds, which indicate low temperature acclimation to increase pressure tolerance. These findings imply this species is capable of deep-sea penetration through isothermal water columns prevailing at high latitudes. This study gives new insight into the fundamentals behind past and future colonisation events. Such knowledge is instrumental to understand better how changes in climate envelopes affect the distribution and radiation of species along latitudinal as well as bathymetric temperature gradients.

Teaching as if your life depends on it: Environmental studies as a vehicle for societal and educational transformation

NASA Astrophysics Data System (ADS)

Giuliano, Jackie Alan

1998-11-01

This work presents a process for teaching environmental studies that is based on active engagement and participation with the world around us. In particular, the importance of recognizing our intimate connection to the natural world is stressed as an effective tool to learn about humans' role in the environment. Understanding our place in the natural world may be a pivotal awareness that must be developed if we are to heal the many wounds we are experiencing today. This work contains approaches to teaching that are based on critical thinking, problem solving, and nonlinear, non-patriarchal approaches to thinking, reasoning, and learning. With these tools, a learner is challenged to think and to understand diverse cultural, social, and intellectual perspectives and to perceive the natural world as an intimate and integral part of our lives. To develop this Deep Teaching Process principles were drawn from many elements including deep ecology, ecofeminism, despairwork, spiritual ecology, bioregionalism, critical thinking, movement therapy, and the author's own teaching experience with learners of all ages. The need for a deep teaching process is demonstrated through a discussion of a number of the environmental challenges we face today and how they affect a learner's perceptions. Two key items are vital to this process. First, 54 experiential learning experiences are presented that the author has developed or adapted to enhance the teaching of our relationship to the natural world. These experiences move the body and activate the creative impulses. Secondly, the author has developed workbooks for each class he has designed that provide foundational notes for each course. These workbooks insure that the student is present for the experience and not immersed in taking notes. The deep teaching process is a process to reawaken our senses. A reawakening of the senses and an intimate awareness of our connections to the natural world and the web of life may be the primary goal of any deep environmental studies educator.

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

ERIC Educational Resources Information Center

Bailey, Judy

2015-01-01

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

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

PubMed

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

2018-03-19

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

The use of micro-/milli-fluidics to better understand the mechanisms behind deep venous thrombosis

NASA Astrophysics Data System (ADS)

Schofield, Zoe; Alexiadis, Alessio; Brill, Alexander; Nash, Gerard; Vigolo, Daniele

2016-11-01

Deep venous thrombosis (DVT) is a dangerous and painful condition in which blood clots form in deep veins (e.g., femoral vein). If these clots become unstable and detach from the thrombus they can be delivered to the lungs resulting in a life threatening complication called pulmonary embolism (PE). Mechanisms of clot development in veins remain unclear but researchers suspect that the specific flow patterns in veins, especially around the valve flaps, play a fundamental role. Here we show how it is now possible to mimic the current murine model by developing micro-/milli-fluidic experiments. We exploited a novel detection technique, ghost particle velocimetry (GPV), to analyse the velocity profiles for various geometries. These vary from regular microfluidics with a rectangular cross section with a range of geometries (mimicking the presence of side and back branches in veins, closed side branch and flexible valves) to a more accurate venous representation with a 3D cylindrical geometry obtained by 3D printing. In addition to the GPV experiments, we analysed the flow field developing in these geometries by using computational fluid dynamic simulations to develop a better understanding of the mechanisms behind DVT. ZS gratefully acknowledges financial support from the EPSRC through a studentship from the Sci-Phy-4-Health Centre for Doctoral Training (EP/L016346/1).

Perspectives on Applying Metabolomics to Understand Carbon Cycling and Process Rates in Deep-Sea Microorganisms

NASA Astrophysics Data System (ADS)

Vidoudez, C.; Saghatelian, A.; Girguis, P. R.

2014-12-01

The metabolisms of deep-sea microorganisms are still poorly characterized. So far, transcriptomics has been the most comprehensive proxy for the whole metabolisms of these organisms, but this approach is limited because it only represents the physiological poise of the cells, and is not linearly correlated to the rates and activity of the metabolic pathways. Using thermodynamics calculations and isotopic analyses can provide constraints on activity, but there are often discrepancies between available energy and calculated active biomass. A further understanding of metabolism both at the species and community level is necessary and metabolomics provides a means of capturing a "snapshot" of cell's metabolite pools, or of following labelled substrates as they move through metabolic pathways. We present our method development and initial results from our studies of the model organism Photobacterium profundum, and the benefits and challenges in meaningfully applying these methods to natural communities. These methods open the way to better understanding deep-sea metabolism on a more comprehensive level, including reserves compounds, alternate and secondary metabolism and potentially new metabolic pathways, and moreover the response of metabolism to changes in experimental conditions and carbon source can be readily followed. These will allow a better understanding of the carbon cycling pathways and their rate in natural communities.

Optimizing the flow of care for prevention and treatment of deep vein thrombosis and pulmonary embolism.

PubMed

Ecklund, M M

1995-11-01

Critically ill patients have multiple risk factors for deep vein thrombosis and pulmonary embolism. The majority of patients with pulmonary embolism have a lower extremity deep vein thrombosis as a source of origin. Pulmonary embolism causes a high mortality rate in the hemodynamically compromised individual. Awareness of risk factors relative to the development of deep vein thrombosis and pulmonary embolism is important for the critical care nurse. Understanding the pathophysiology can help guide prophylaxis and treatment plans. The therapies, from invasive to mechanical, all carry risks and benefits, and are weighed for each patient. The advanced practice nurse, whether in the direct or indirect role, has an opportunity to impact the care of the high risk patient. Options range from teaching the nurse who is new to critical care, to teaching patients and families. Development of multidisciplinary protocols and clinical pathways are ways to impact the standard of care. Improved delivery of care methods can optimize the care rendered in an ever changing field of critical care.

The State of Professional Development for Teachers of Beginning Readers in Florida's Rural Schools

ERIC Educational Resources Information Center

Helvenston, Susan S.

2013-01-01

This study reviews the state of professional development (PD) for teachers of beginning readers in Florida's rural schools. Teachers of beginning readers need to have a deep understanding of language, of how the reading process develops, and of effective pedagogy in early literacy. Few teachers begin their careers with sufficient knowledge and…

A Different Kind of Kid, a Different Kind of Teacher Education: Middle Grades Teachers Reflect on Their Preparation to Teach Young Adolescents

ERIC Educational Resources Information Center

Ochanji, Moses K.; Chen, Rong-Ji; Daniels, Erika; Deringer, Marlene L.; McDaniel, Janet; Stowell, Laurie; Cambra-Adamson, Christina

2016-01-01

Good teaching at the middle grades comes out of a deep understanding of the unique cognitive, physical, social, emotional, and moral needs of young adolescents. Specialized preparation therefore is necessary to help teacher candidates understand how to operationalize the intersection of young adolescent development and the effective pedagogy that…

Combining deep learning and satellite data to inform sustainable development

NASA Astrophysics Data System (ADS)

Lobell, D. B.

2017-12-01

Methods in machine learning, and in particular deep learning, are quickly advancing, in parallel with dramatic increases in the availability of fine resolution satellite data. The combination of both offers the possibility to improve understanding of some of the poorest regions of the world, where traditional data sources are limited. This talk will cover recent applications to track poverty at the village level in Africa, spot the onset of disease outbreaks in agriculture, and identify land use patterns and crop productivity.

Final Report: DOE award: ER64516-1031199-0013966 2007-2011 Genomic Structure, Metagenomics, Horizontal Gene Transfer, and Natural Diversity of Prochlorococcus and Vibrio

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

Chisholm, Sally; Polz, Martin F.; Alm, Eric J

Our overarching goal with this proposal was to develop a deep understanding of the design of Prochlorococcus and Vibrio cells, the variations in their designs, and the constraints that have shaped this variation at the cell-environment interface. That is, we wanted to develop our understanding of the biology of these microbes at all scales of biological organization, from individual cell design to the dynamics of large populations.

D.E.E.P. Learning: Promoting Informal STEM Learning through a Popular Gaming Platform

NASA Astrophysics Data System (ADS)

Simms, E.; Rohrlick, D.; Layman, C.; Peach, C. L.; Orcutt, J. A.

2011-12-01

The research and development of educational games, and the study of the educational value of interactive games in general, have lagged far behind efforts for games created for the purpose of entertainment. But evidence suggests that digital simulations and games have the "potential to advance multiple science learning goals, including motivation to learn science, conceptual understanding, science process skills, understanding of the nature of science, scientific discourse and argumentation, and identification with science and science learning." (NRC, 2011). It is also generally recognized that interactive digital games have the potential to promote the development of valuable learning and life skills, including data processing, decision-making, critical thinking, planning, communication and collaboration (Kirriemuir and MacFarlane, 2006). Video games are now played in 67% of American households (ESA, 2010), and across a broad range of ages, making them a potentially valuable tool for Science, Technology, Engineering and Mathematics (STEM) learning among the diverse audiences associated with informal science education institutions (ISEIs; e.g., aquariums, museums, science centers). We are attempting to capitalize on this potential by developing games based on the popular Microsoft Xbox360 gaming platform and the free Microsoft XNA game development kit. The games, collectively known as Deep-sea Extreme Environment Pilot (D.E.E.P.), engage ISEI visitors in the exploration and understanding of the otherwise remote deep-sea environment. Players assume the role of piloting a remotely-operated vehicle (ROV) to explore ocean observing systems and hydrothermal vent environments, and are challenged to complete science-based objectives in order to earn points under timed conditions. The current games are intended to be relatively brief visitor experiences (on the order of several minutes) that support complementary exhibits and programming, and promote interactive visitor experiences. In addition to creating a unique educational product, our efforts are intended to inform the broader understanding of the key elements of a successful STEM-based game experience at an ISEI. Which characteristics of the ISEI environment (e.g., age and cultural diversity, limited time of engagement) are conducive or inhibitive to learning via digital gaming? Which aspects of game design (e.g., challenge, curiosity, fantasy, personal recognition) are most effective at maximizing both learning and enjoyment? We will share our progress and assessment results to date, and discuss the potential benefits and challenges to interactive gaming as a tool to support STEM literacy at ISEIs.

Microbial activity in the marine deep biosphere: progress and prospects.

PubMed

Orcutt, Beth N; Larowe, Douglas E; Biddle, Jennifer F; Colwell, Frederick S; Glazer, Brian T; Reese, Brandi Kiel; Kirkpatrick, John B; Lapham, Laura L; Mills, Heath J; Sylvan, Jason B; Wankel, Scott D; Wheat, C Geoff

2013-01-01

The vast marine deep biosphere consists of microbial habitats within sediment, pore waters, upper basaltic crust and the fluids that circulate throughout it. A wide range of temperature, pressure, pH, and electron donor and acceptor conditions exists-all of which can combine to affect carbon and nutrient cycling and result in gradients on spatial scales ranging from millimeters to kilometers. Diverse and mostly uncharacterized microorganisms live in these habitats, and potentially play a role in mediating global scale biogeochemical processes. Quantifying the rates at which microbial activity in the subsurface occurs is a challenging endeavor, yet developing an understanding of these rates is essential to determine the impact of subsurface life on Earth's global biogeochemical cycles, and for understanding how microorganisms in these "extreme" environments survive (or even thrive). Here, we synthesize recent advances and discoveries pertaining to microbial activity in the marine deep subsurface, and we highlight topics about which there is still little understanding and suggest potential paths forward to address them. This publication is the result of a workshop held in August 2012 by the NSF-funded Center for Dark Energy Biosphere Investigations (C-DEBI) "theme team" on microbial activity (www.darkenergybiosphere.org).

Microbial activity in the marine deep biosphere: progress and prospects

PubMed Central

Orcutt, Beth N.; LaRowe, Douglas E.; Biddle, Jennifer F.; Colwell, Frederick S.; Glazer, Brian T.; Reese, Brandi Kiel; Kirkpatrick, John B.; Lapham, Laura L.; Mills, Heath J.; Sylvan, Jason B.; Wankel, Scott D.; Wheat, C. Geoff

2013-01-01

The vast marine deep biosphere consists of microbial habitats within sediment, pore waters, upper basaltic crust and the fluids that circulate throughout it. A wide range of temperature, pressure, pH, and electron donor and acceptor conditions exists—all of which can combine to affect carbon and nutrient cycling and result in gradients on spatial scales ranging from millimeters to kilometers. Diverse and mostly uncharacterized microorganisms live in these habitats, and potentially play a role in mediating global scale biogeochemical processes. Quantifying the rates at which microbial activity in the subsurface occurs is a challenging endeavor, yet developing an understanding of these rates is essential to determine the impact of subsurface life on Earth's global biogeochemical cycles, and for understanding how microorganisms in these “extreme” environments survive (or even thrive). Here, we synthesize recent advances and discoveries pertaining to microbial activity in the marine deep subsurface, and we highlight topics about which there is still little understanding and suggest potential paths forward to address them. This publication is the result of a workshop held in August 2012 by the NSF-funded Center for Dark Energy Biosphere Investigations (C-DEBI) “theme team” on microbial activity (www.darkenergybiosphere.org). PMID:23874326

The deep, hot biosphere: Twenty-five years of retrospection.

PubMed

Colman, Daniel R; Poudel, Saroj; Stamps, Blake W; Boyd, Eric S; Spear, John R

2017-07-03

Twenty-five years ago this month, Thomas Gold published a seminal manuscript suggesting the presence of a "deep, hot biosphere" in the Earth's crust. Since this publication, a considerable amount of attention has been given to the study of deep biospheres, their role in geochemical cycles, and their potential to inform on the origin of life and its potential outside of Earth. Overwhelming evidence now supports the presence of a deep biosphere ubiquitously distributed on Earth in both terrestrial and marine settings. Furthermore, it has become apparent that much of this life is dependent on lithogenically sourced high-energy compounds to sustain productivity. A vast diversity of uncultivated microorganisms has been detected in subsurface environments, and we show that H 2 , CH 4 , and CO feature prominently in many of their predicted metabolisms. Despite 25 years of intense study, key questions remain on life in the deep subsurface, including whether it is endemic and the extent of its involvement in the anaerobic formation and degradation of hydrocarbons. Emergent data from cultivation and next-generation sequencing approaches continue to provide promising new hints to answer these questions. As Gold suggested, and as has become increasingly evident, to better understand the subsurface is critical to further understanding the Earth, life, the evolution of life, and the potential for life elsewhere. To this end, we suggest the need to develop a robust network of interdisciplinary scientists and accessible field sites for long-term monitoring of the Earth's subsurface in the form of a deep subsurface microbiome initiative.

Deep Filter Banks for Texture Recognition, Description, and Segmentation.

PubMed

Cimpoi, Mircea; Maji, Subhransu; Kokkinos, Iasonas; Vedaldi, Andrea

Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descriptors in an orderless manner have had a tremendous impact in diverse applications. In this paper we make several contributions to texture understanding. First, instead of focusing on texture instance and material category recognition, we propose a human-interpretable vocabulary of texture attributes to describe common texture patterns, complemented by a new describable texture dataset for benchmarking. Second, we look at the problem of recognizing materials and texture attributes in realistic imaging conditions, including when textures appear in clutter, developing corresponding benchmarks on top of the recently proposed OpenSurfaces dataset. Third, we revisit classic texture represenations, including bag-of-visual-words and the Fisher vectors, in the context of deep learning and show that these have excellent efficiency and generalization properties if the convolutional layers of a deep model are used as filter banks. We obtain in this manner state-of-the-art performance in numerous datasets well beyond textures, an efficient method to apply deep features to image regions, as well as benefit in transferring features from one domain to another.

Marshall Space Flight Center - Launching the Future of Science and Exploration

NASA Technical Reports Server (NTRS)

Shivers, Alisa; Shivers, Herbert

2010-01-01

Topics include: NASA Centers around the country, launching a legacy (Explorer I), Marshall's continuing role in space exploration, MSFC history, lifting from Earth, our next mission STS 133, Space Shuttle propulsion systems, Space Shuttle facts, Space Shuttle and the International Space Station, technologies/materials originally developed for the space program, astronauts come from all over, potential future missions and example technologies, significant accomplishments, living and working in space, understanding our world, understanding worlds beyond, from exploration to innovation, inspiring the next generation, space economy, from exploration to opportunity, new program assignments, NASA's role in education, and images from deep space including a composite of a galaxy with a black hole, Sagittarius A, Pillars of Creation, and an ultra deep field

Connecting Literacy and Science to Increase Achievement for English Language Learners

ERIC Educational Resources Information Center

Huerta, Margarita; Jackson, Julie

2010-01-01

Giving students a purpose and a passion for sharing their thinking through authentic learning experiences and giving them tools for writing through which they can risk new vocabulary, new language, and new thought is critical for the linguistic and cognitive development of students. Furthermore, students develop a deep understanding of content…

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…

How Do We Help Students Build Beliefs That Allow Them to Avoid Critical Learning Barriers and Develop a Deep Understanding of Geology?

ERIC Educational Resources Information Center

Dal, Burçkin

2007-01-01

Students hold a surprising number of ideas about the Earth's structure and process. This paper begins with a discussion on the nature of understanding in the conceptually confined domain of geosciences. There then follows a report on a study of the ideas about a range of concepts relating to "crystals", "volcanoes",…

Deep Bore Storage of Nuclear Waste Using MMW (Millimeter Wave) Technology. Full Project Final Report

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

Oglesby, Kenneth D.; Woskov, Paul; Einstein, Herbert

This DOE Nuclear STTR project DE-SC001238 investigated the use of MMW directed energy to form rock melt and steel plugs in deep wellbores to further isolate highly radioactive nuclear waste in ultra-deep basement rocks for long term storage. This current project builds upon a prior DOE project, DE-EE0005504, which developed the basic low power, low 28 GHz frequency waveguide setup, process and instruments. This research adds to our understanding of using MMW power to melt and vaporize rocks and steel/ metals and laid plans for future higher power field prototype testing. This technology also has potential for deep well drillingmore » for nuclear storage, geothermal and oil and gas industries. It also has the potential for simultaneously sealing and securing the wellbore with a thick rock melt liner as the wellbore is drilled, called 'mono-bore drilling'. This allows for higher levels of safety and protection of the environment during deep drilling operations while providing vast cost savings. The larger purpose of this project was to find answers to key questions in developing MMW technology for its many subsurface applications.« less

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

PubMed

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

2017-07-15

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

Morphometry and mixing regime of a tropical lake: Lake Nova (Southeastern Brazil).

PubMed

Gonçalves, Monica A; Garcia, Fábio C; Barroso, Gilberto F

2016-09-01

Lake Nova (15.5 km2) is the second largest lake in the Lower Doce River Valley (Southeastern Brazil). A better understanding of ecosystem structure and functioning requires knowledge about lake morphometry, given that lake basin form influences water column stratification. The present study aims to contribute to the understanding of relationship between morphometry and mixing patterns of deep tropical lakes in Brazil. Water column profiles of temperature and dissolved oxygen were taken on four sampling sites along the lake major axis during 2011, 2012 and 2013. The bathymetric survey was carried out in July 2011, along 131.7 km of hydrographic tracks yield 51,692 depth points. Morphometric features of lake size and form factors describe the relative deep subrectangular elongated basin with maximum length of 15.7 km, shoreline development index 5.0, volume of 0.23 km3, volume development of 1.3, and maximum, mean and relative depths of 33.9 m, 14.7 m and 0.7 %, respectively. The deep basin induces a monomictic pattern, with thermal stratification during the wet/warm season associated with anoxic bottom waters (1/3 of lake volume), and mixing during dry and cool season. Based on in situ measurements of tributary river discharges, theoretical retention time (RT) has been estimated in 13.4 years. The morphometry of Lake Nova promote long water RT and the warm monomictic mixing pattern, which is in accordance to the deep tropical lakes in Brazil.

Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks.

PubMed

Tran, Son N; d'Avila Garcez, Artur S

2018-02-01

Developments in deep learning have seen the use of layerwise unsupervised learning combined with supervised learning for fine-tuning. With this layerwise approach, a deep network can be seen as a more modular system that lends itself well to learning representations. In this paper, we investigate whether such modularity can be useful to the insertion of background knowledge into deep networks, whether it can improve learning performance when it is available, and to the extraction of knowledge from trained deep networks, and whether it can offer a better understanding of the representations learned by such networks. To this end, we use a simple symbolic language-a set of logical rules that we call confidence rules-and show that it is suitable for the representation of quantitative reasoning in deep networks. We show by knowledge extraction that confidence rules can offer a low-cost representation for layerwise networks (or restricted Boltzmann machines). We also show that layerwise extraction can produce an improvement in the accuracy of deep belief networks. Furthermore, the proposed symbolic characterization of deep networks provides a novel method for the insertion of prior knowledge and training of deep networks. With the use of this method, a deep neural-symbolic system is proposed and evaluated, with the experimental results indicating that modularity through the use of confidence rules and knowledge insertion can be beneficial to network performance.

Listening to the Deep: live monitoring of ocean noise and cetacean acoustic signals.

PubMed

André, M; van der Schaar, M; Zaugg, S; Houégnigan, L; Sánchez, A M; Castell, J V

2011-01-01

The development and broad use of passive acoustic monitoring techniques have the potential to help assessing the large-scale influence of artificial noise on marine organisms and ecosystems. Deep-sea observatories have the potential to play a key role in understanding these recent acoustic changes. LIDO (Listening to the Deep Ocean Environment) is an international project that is allowing the real-time long-term monitoring of marine ambient noise as well as marine mammal sounds at cabled and standalone observatories. Here, we present the overall development of the project and the use of passive acoustic monitoring (PAM) techniques to provide the scientific community with real-time data at large spatial and temporal scales. Special attention is given to the extraction and identification of high frequency cetacean echolocation signals given the relevance of detecting target species, e.g. beaked whales, in mitigation processes, e.g. during military exercises. Copyright © 2011. Published by Elsevier Ltd.

Linking white matter and deep gray matter alterations in premanifest Huntington disease.

PubMed

Faria, Andreia V; Ratnanather, J Tilak; Tward, Daniel J; Lee, David Soobin; van den Noort, Frieda; Wu, Dan; Brown, Timothy; Johnson, Hans; Paulsen, Jane S; Ross, Christopher A; Younes, Laurent; Miller, Michael I

2016-01-01

Huntington disease (HD) is a fatal progressive neurodegenerative disorder for which only symptomatic treatment is available. A better understanding of the pathology, and identification of biomarkers will facilitate the development of disease-modifying treatments. HD is potentially a good model of a neurodegenerative disease for development of biomarkers because it is an autosomal-dominant disease with complete penetrance, caused by a single gene mutation, in which the neurodegenerative process can be assessed many years before onset of signs and symptoms of manifest disease. Previous MRI studies have detected abnormalities in gray and white matter starting in premanifest stages. However, the understanding of how these abnormalities are related, both in time and space, is still incomplete. In this study, we combined deep gray matter shape diffeomorphometry and white matter DTI analysis in order to provide a better mapping of pathology in the deep gray matter and subcortical white matter in premanifest HD. We used 296 MRI scans from the PREDICT-HD database. Atrophy in the deep gray matter, thalamus, hippocampus, and nucleus accumbens was analyzed by surface based morphometry, and while white matter abnormalities were analyzed in (i) regions of interest surrounding these structures, using (ii) tractography-based analysis, and using (iii) whole brain atlas-based analysis. We detected atrophy in the deep gray matter, particularly in putamen, from early premanifest stages. The atrophy was greater both in extent and effect size in cases with longer exposure to the effects of the CAG expansion mutation (as assessed by greater CAP-scores), and preceded detectible abnormalities in the white matter. Near the predicted onset of manifest HD, the MD increase was widespread, with highest indices in the deep and posterior white matter. This type of in-vivo macroscopic mapping of HD brain abnormalities can potentially indicate when and where therapeutics could be targeted to delay the onset or slow the disease progression.

STEM Gives Meaning to Mathematics

ERIC Educational Resources Information Center

Hefty, Lukas J.

2015-01-01

The National Council of Teachers of Mathematics' (NCTM's) "Principles and Standards for School Mathematics" (2000) outlines fi ve Process Standards that are essential for developing deep understanding of mathematics: (1) Problem Solving; (2) Reasoning and Proof; (3) Communication; (4) Connections; and (5) Representation. The Common Core…

An Investigation of the Development of Pre-Service Teacher Assessment Literacy through Individualized Tutoring and Peer Debriefing

ERIC Educational Resources Information Center

Odo, Dennis Murphy

2016-01-01

Many pre-service teachers lack deep understanding of assessment concepts and have low selfefficacy for using assessments but pre-service on-campus programs have been shown to support their assessment literacy development. Likewise, individualized tutoring has helped pre-service candidates improve instructional practice and peer debriefing has been…

Middle school students' understanding of the natural history of the Earth and life on Earth as a function of deep time

NASA Astrophysics Data System (ADS)

Pulling, Azalie Cecile

The purpose of this study was to use deep time, that is geologic time as a mechanism to explore middle school students' understanding of the natural history of the earth and the evolution of life on earth. Geologic time is a logical precursor to middle school students' understanding of biological evolution. This exploratory, mixed model study used qualitative and quantitative methods in each stage of the research to explore sixth grade students, understanding of geologic time, their worldviews (e.g., conceptual ecology), and conceptual change. The study included fifty-nine students in the large group study and four case studies. The primary data collection instrument was the Geologic Timeline Survey. Additional data collection instruments and methods (e.g., concept evaluation statement, journal entries, word associations, interviews, and formal tests) were used to triangulate the study findings. These data were used to create narrative modal profiles of the categories of student thinking that emerged from the large group analysis: Middle School (MS) Scientists (correct science), MS Protoscientists (approaching correct science), MS Prescientists (dinosaur understanding), and MS Pseudoscientists (fundamental religious understanding). Case studies were used to provide a thick description of each category. This study discovered a pattern of student thinking about geologic time that moved along a knowledge continuum from pseudoscience (fundamental creationist understanding) to prescience (everyday-science understanding) to science (correct or approaching correct science). The researcher described the deep-seated misconceptions produced by the prescience thinking level, e.g., dinosaur misconceptions, and cautioned the science education community about using dinosaurs as a glamour-science topic. The most limiting conceptual frameworks found in this study were prescience (a dinosaur focus) and pseudoscience (a fundamental religious focus). An understanding of geologic time as Piaget's system of time (e.g., chronological ordering of events, before and after relationships, duration or evolutionary time) was a necessary conceptual framework for students to develop a scientific understanding of deep time. An examination of students, worldviews and the interface of science and religion indicated that students often successfully applied a demarcation between science and religion in their public thinking (e.g., the formal classroom setting), but in their private thinking, the demarcation was often blurred.

How Do Lessons Learned on the International Space Station (ISS) Help Plan Life Support for Mars?

NASA Technical Reports Server (NTRS)

Jones, Harry W.; Hodgson, Edward W.; Gentry, Gregory J.; Kliss, Mark H.

2016-01-01

How can our experience in developing and operating the International Space Station (ISS) guide the design, development, and operation of life support for the journey to Mars? The Mars deep space Environmental Control and Life Support System (ECLSS) must incorporate the knowledge and experience gained in developing ECLSS for low Earth orbit, but it must also meet the challenging new requirements of operation in deep space where there is no possibility of emergency resupply or quick crew return. The understanding gained by developing ISS flight hardware and successfully supporting a crew in orbit for many years is uniquely instructive. Different requirements for Mars life support suggest that different decisions may be made in design, testing, and operations planning, but the lessons learned developing the ECLSS for ISS provide valuable guidance.

Home - Deep Underground Neutrino ExperimentDeep Underground Neutrino

Science.gov Websites

understanding of neutrinos and their role in the universe. DUNE prototype detectors are under construction at understanding of neutrinos and their role in the universe. DUNE_Forces_011116_FINAL Unification of Forces With

How can we identify and communicate the ecological value of deep-sea ecosystem services?

PubMed

Jobstvogt, Niels; Townsend, Michael; Witte, Ursula; Hanley, Nick

2014-01-01

Submarine canyons are considered biodiversity hotspots which have been identified for their important roles in connecting the deep sea with shallower waters. To date, a huge gap exists between the high importance that scientists associate with deep-sea ecosystem services and the communication of this knowledge to decision makers and to the wider public, who remain largely ignorant of the importance of these services. The connectivity and complexity of marine ecosystems makes knowledge transfer very challenging, and new communication tools are necessary to increase understanding of ecological values beyond the science community. We show how the Ecosystem Principles Approach, a method that explains the importance of ocean processes via easily understandable ecological principles, might overcome this challenge for deep-sea ecosystem services. Scientists were asked to help develop a list of clear and concise ecosystem principles for the functioning of submarine canyons through a Delphi process to facilitate future transfers of ecological knowledge. These ecosystem principles describe ecosystem processes, link such processes to ecosystem services, and provide spatial and temporal information on the connectivity between deep and shallow waters. They also elucidate unique characteristics of submarine canyons. Our Ecosystem Principles Approach was successful in integrating ecological information into the ecosystem services assessment process. It therefore has a high potential to be the next step towards a wider implementation of ecological values in marine planning. We believe that successful communication of ecological knowledge is the key to a wider public support for ocean conservation, and that this endeavour has to be driven by scientists in their own interest as major deep-sea stakeholders.

How Can We Identify and Communicate the Ecological Value of Deep-Sea Ecosystem Services?

PubMed Central

Jobstvogt, Niels; Townsend, Michael; Witte, Ursula; Hanley, Nick

2014-01-01

Submarine canyons are considered biodiversity hotspots which have been identified for their important roles in connecting the deep sea with shallower waters. To date, a huge gap exists between the high importance that scientists associate with deep-sea ecosystem services and the communication of this knowledge to decision makers and to the wider public, who remain largely ignorant of the importance of these services. The connectivity and complexity of marine ecosystems makes knowledge transfer very challenging, and new communication tools are necessary to increase understanding of ecological values beyond the science community. We show how the Ecosystem Principles Approach, a method that explains the importance of ocean processes via easily understandable ecological principles, might overcome this challenge for deep-sea ecosystem services. Scientists were asked to help develop a list of clear and concise ecosystem principles for the functioning of submarine canyons through a Delphi process to facilitate future transfers of ecological knowledge. These ecosystem principles describe ecosystem processes, link such processes to ecosystem services, and provide spatial and temporal information on the connectivity between deep and shallow waters. They also elucidate unique characteristics of submarine canyons. Our Ecosystem Principles Approach was successful in integrating ecological information into the ecosystem services assessment process. It therefore has a high potential to be the next step towards a wider implementation of ecological values in marine planning. We believe that successful communication of ecological knowledge is the key to a wider public support for ocean conservation, and that this endeavour has to be driven by scientists in their own interest as major deep-sea stakeholders. PMID:25055119

The deep, hot biosphere: Twenty-five years of retrospection

PubMed Central

Colman, Daniel R.; Poudel, Saroj; Stamps, Blake W.; Boyd, Eric S.; Spear, John R.

2017-01-01

Twenty-five years ago this month, Thomas Gold published a seminal manuscript suggesting the presence of a “deep, hot biosphere” in the Earth’s crust. Since this publication, a considerable amount of attention has been given to the study of deep biospheres, their role in geochemical cycles, and their potential to inform on the origin of life and its potential outside of Earth. Overwhelming evidence now supports the presence of a deep biosphere ubiquitously distributed on Earth in both terrestrial and marine settings. Furthermore, it has become apparent that much of this life is dependent on lithogenically sourced high-energy compounds to sustain productivity. A vast diversity of uncultivated microorganisms has been detected in subsurface environments, and we show that H2, CH4, and CO feature prominently in many of their predicted metabolisms. Despite 25 years of intense study, key questions remain on life in the deep subsurface, including whether it is endemic and the extent of its involvement in the anaerobic formation and degradation of hydrocarbons. Emergent data from cultivation and next-generation sequencing approaches continue to provide promising new hints to answer these questions. As Gold suggested, and as has become increasingly evident, to better understand the subsurface is critical to further understanding the Earth, life, the evolution of life, and the potential for life elsewhere. To this end, we suggest the need to develop a robust network of interdisciplinary scientists and accessible field sites for long-term monitoring of the Earth’s subsurface in the form of a deep subsurface microbiome initiative. PMID:28674200

Strong Community, Deep Learning: Exploring the Link

ERIC Educational Resources Information Center

Chapman, Carole; Ramondt, Leonie; Smiley, Glenn

2005-01-01

This explores the constructivist understanding that shared practitioner research in collaborative online spaces leads to deeper learning. The research was developed within the context of building the National College of School Leaderships (NCSLs) online learning communities. A community and a learning scale, both emerging through grounded…

Capitalizing on Curiosity

ERIC Educational Resources Information Center

Devitt, Adam

2011-01-01

State and national standards have shifted what science learning should be from "plug and chug" formulas, to deep understanding of natural phenomena, competence developing ideas through the inquiry process, and even communicating scientific ideas among their communities (NRC 2007). By inquiring into his own teaching endeavors, the author continues…

Deepwater Program: Studies of Gulf of Mexico lower continental slope communities related to chemosynthetic and hard substrate habitats

USGS Publications Warehouse

Ross, Steve W.; Demopoulos, Amanda W.J.; Kellogg, Christina A.; Morrison, Cheryl L.; Nizinski, Martha S.; Ames, Cheryl L.; Casazza, Tara L.; Gualtieri, Daniel; Kovacs, Kaitlin; McClain, Jennifer P.; Quattrini, Andrea M.; Roa-Varon, Adela Y.; Thaler, Andrew D.

2012-01-01

This report summarizes research funded by the U.S. Geological Survey (USGS) in collaboration with the University of North Carolina at Wilmington (UNCW) on the ecology of deep chemosynthetic communities in the Gulf of Mexico. The research was conducted at the request of the U.S. Bureau of Ocean Energy Management, Regulation and Enforcement (BOEMRE; formerly Minerals Management Service) to complement a BOEMRE-funded project titled "Deepwater Program: Investigations of Chemosynthetic Communities on the Lower Continental Slope of the Gulf of Mexico." The overall research partnership, known as "Chemo III," was initiated to increase understanding of the distribution, structure, function, and vulnerabilities of these poorly known associations of animals and microbes for water depths greater than 1,000 meters (m) in the Gulf of Mexico. Chemosynthetic communities rely on carbon sources that are largely independent of sunlight and photosynthetic food webs. Despite recent research directed toward chemosynthetic and deep coral (for example, Lophelia pertusa) based ecosystems, these habitats are still poorly studied, especially at depths greater than 1,000 m. With the progression into deeper waters by fishing and energy industries, developing sufficient knowledge to manage these deep ecosystems is essential. Increased understanding of deep-sea communities will enable sound evaluations of potential impacts and appropriate mitigations.

The North Pacific Acoustic Laboratory deep-water acoustic propagation experiments in the Philippine Sea.

PubMed

Worcester, Peter F; Dzieciuch, Matthew A; Mercer, James A; Andrew, Rex K; Dushaw, Brian D; Baggeroer, Arthur B; Heaney, Kevin D; D'Spain, Gerald L; Colosi, John A; Stephen, Ralph A; Kemp, John N; Howe, Bruce M; Van Uffelen, Lora J; Wage, Kathleen E

2013-10-01

A series of experiments conducted in the Philippine Sea during 2009-2011 investigated deep-water acoustic propagation and ambient noise in this oceanographically and geologically complex region: (i) the 2009 North Pacific Acoustic Laboratory (NPAL) Pilot Study/Engineering Test, (ii) the 2010-2011 NPAL Philippine Sea Experiment, and (iii) the Ocean Bottom Seismometer Augmentation of the 2010-2011 NPAL Philippine Sea Experiment. The experimental goals included (a) understanding the impacts of fronts, eddies, and internal tides on acoustic propagation, (b) determining whether acoustic methods, together with other measurements and ocean modeling, can yield estimates of the time-evolving ocean state useful for making improved acoustic predictions, (c) improving our understanding of the physics of scattering by internal waves and spice, (d) characterizing the depth dependence and temporal variability of ambient noise, and (e) understanding the relationship between the acoustic field in the water column and the seismic field in the seafloor. In these experiments, moored and ship-suspended low-frequency acoustic sources transmitted to a newly developed distributed vertical line array receiver capable of spanning the water column in the deep ocean. The acoustic transmissions and ambient noise were also recorded by a towed hydrophone array, by acoustic Seagliders, and by ocean bottom seismometers.

Life on the Number Line: Routes to Understanding Fraction Magnitude for Students With Difficulties Learning Mathematics.

PubMed

Gersten, Russell; Schumacher, Robin F; Jordan, Nancy C

Magnitude understanding is critical for students to develop a deep understanding of fractions and more advanced mathematics curriculum. The research reports in this special issue underscore magnitude understanding for fractions and emphasize number lines as both an assessment and an instructional tool. In this commentary, we discuss how number lines broaden the concept of fractions for students who are tied to the more general part-whole representations of area models. We also discuss how number lines, compared to other representations, are a superior and more mathematically correct way to explain fraction concepts.

Dust Measurements Onboard the Deep Space Gateway

NASA Astrophysics Data System (ADS)

Horanyi, M.; Kempf, S.; Malaspina, D.; Poppe, A.; Srama, R.; Sternovsky, Z.; Szalay, J.

2018-02-01

A dust instrument onboard the Deep Space Gateway will revolutionize our understanding of the dust environment at 1 AU, help our understanding of the evolution of the solar system, and improve dust hazard models for the safety of crewed and robotic missions.

The Gravity Wave Response Above Deep Convection in a Squall Line Simulation

NASA Technical Reports Server (NTRS)

Alexander, M. J.; Holton, J. R.; Durran, D. R.

1995-01-01

High-frequency gravity waves generated by convective storms likely play an important role in the general circulation of the middle atmosphere. Yet little is known about waves from this source. This work utilizes a fully compressible, nonlinear, numerical, two-dimensional simulation of a midlatitude squall line to study vertically propagating waves generated by deep convection. The model includes a deep stratosphere layer with high enough resolution to characterize the wave motions at these altitudes. A spectral analysis of the stratospheric waves provides an understanding of the necessary characteristics of the spectrum for future studies of their effects on the middle atmosphere in realistic mean wind scenarios. The wave spectrum also displays specific characteristics that point to the physical mechanisms within the storm responsible for their forcing. Understanding these forcing mechanisms and the properties of the storm and atmosphere that control them are crucial first steps toward developing a parameterization of waves from this source. The simulation also provides a description of some observable signatures of convectively generated waves, which may promote observational verification of these results and help tie any such observations to their convective source.

Deep Belief Networks for Electroencephalography: A Review of Recent Contributions and Future Outlooks.

PubMed

Movahedi, Faezeh; Coyle, James L; Sejdic, Ervin

2018-05-01

Deep learning, a relatively new branch of machine learning, has been investigated for use in a variety of biomedical applications. Deep learning algorithms have been used to analyze different physiological signals and gain a better understanding of human physiology for automated diagnosis of abnormal conditions. In this paper, we provide an overview of deep learning approaches with a focus on deep belief networks in electroencephalography applications. We investigate the state-of-the-art algorithms for deep belief networks and then cover the application of these algorithms and their performances in electroencephalographic applications. We covered various applications of electroencephalography in medicine, including emotion recognition, sleep stage classification, and seizure detection, in order to understand how deep learning algorithms could be modified to better suit the tasks desired. This review is intended to provide researchers with a broad overview of the currently existing deep belief network methodology for electroencephalography signals, as well as to highlight potential challenges for future research.

What Must Be Taught about Writing: Five Kinds of Knowledge and Five Kinds of Composing

ERIC Educational Resources Information Center

Wilhelm, Jeff, Ed.

2012-01-01

Students need to develop five kinds of knowledge to be successful in any kind of specific reading or writing task. These kinds of knowledge can be developed through five different kinds of composing that lead to deep understanding of how texts are constructed with specific content to create particular effects and meaning. Following this process…

Student Interactions in Technology-Rich Classrooms

ERIC Educational Resources Information Center

Fonkert, Karen L.

2010-01-01

Students are more likely to develop a deep conceptual understanding of mathematics when they interact with and discuss their thoughts with others. The National Council of Teachers of Mathematics (NCTM) (1989, 2000) has recommended that students be active learners--communicating with one another, conjecturing, exploring, and justifying claims by…

Approaches to Learning and Kolb's Learning Styles of Undergraduates with Better Grades

NASA Astrophysics Data System (ADS)

Almeida, Patrícia; Teixeira-Dias, José Joaquim; Martinho, Mariana; Balasooriya, Chinthaka

The purpose of this study is to investigate if the teaching, learning and assessment strategies conceived and implemented in a higher education chemistry course promote the development of conceptual understanding, as intended. Thus, our aim is to analyse the learning styles and the approaches to learning of chemistry undergraduates with better grades. The overall results show that the students with better grades possess the assimilator learning style, that is usually associated to the archetypal chemist. Moreover, the students with the highest grades revealed a conception of learning emphasising understanding. However, these students diverged both in their learning approaches and in their preferences for teaching strategies. The majority of students adopted a deep approach or a combination of a deep and a strategic approach, but half of them revealed their preference for teaching-centred strategies.

Deep-Elaborative Learning of Introductory Management Accounting for Business Students

ERIC Educational Resources Information Center

Choo, Freddie; Tan, Kim B.

2005-01-01

Research by Choo and Tan (1990; 1995) suggests that accounting students, who engage in deep-elaborative learning, have a better understanding of the course materials. The purposes of this paper are: (1) to describe a deep-elaborative instructional approach (hereafter DEIA) that promotes deep-elaborative learning of introductory management…

First step to understand the importance of new deep aquifer pumping regime in groundwater system in a developing country, Kwale, Kenya.

NASA Astrophysics Data System (ADS)

Ferrer, Nuria; Folch, Albert; Lane, Mike; Thomas, Mike; Sasaka, Willie; Wara, Calvince; Banje, Said; Olago, Dan; Katuva, Jacob; Thomson, Patrick; Hope, Rob

2016-04-01

The population growth in the world carries on the one hand, an increased demand of fresh water and on the other hand, a decrease of quality and quantity of this resource. To avoid this deterioration it is essential doing a good management of surface water and groundwater, specially the second one, which has become the major source of water supply for domestic, industrial and agricultural sectors of many countries (UNEP 1999). This groundwater management starts with an accurate hydrogeological characterization of aquifer systems, mainly in that aquifer systems in which is changing the abstraction regime. In this context of population growth and new abstraction regimes on aquifer system is where the project "Gro for Good: Groundwater Risk for Growth and Development" is founded by UPGro. This interdisciplinary project has the main goal to design, test and transfer to the society an innovative Groundwater Risk Management Tool to improve and get by new governance transformations the balance between economic growth, groundwater sustainability (in terms of quality and quantity) and human development (http://upgro.org/consortium/gro-for-good/). The study area is located on the south eastern coast of Kenya, in Kwale County. The Kwale coastal groundwater system formed by a shallow and deep aquifer systems has long served urban water demands and an established tourism industry but now faces unprecedented ground and surface water resource demands especially from KISCOL's (5,500 hectares of irrigated sugarcane) and the country's largest mining operation (Base Titanium Ltd.). Despite both companies have drilled deep boreholes around the study area (416 km2) to extract groundwater from deep aquifer; no major pumping activity has started yet, allowing baseline evaluation. Scattered around the study are 440 handpumps providing drinking water to over 90,000 people. The relationship between the shallow and deep aquifers remains uncertain and so, the future influence on groundwater level and its quality either. So, in order to define the system and start to understand the different complex interactions, we present the initial results of the first complete water sampling field campaign (September 2015). Water isotope data and major ions were analyzed from 78 shallow and deep wells and surface water spread around study area. This field survey has been useful to understand the recharge, discharge areas and groundwater quality of deep aquifer system and which will have an important role for sustainable water management in the of Kwale area. Acknowledgements The research is primarily supported under the NERC/ESRC/DFID Unlocking the Potential of Groundwater for the Poor (UPGro) as a Catalyst Grant (NE/L001950/1) with work extending until 2019 as a Consortium Grant (NE/M008894/1), see http://www.upgro.org. Data for the paper will be publicly posted on the National Geoscience Data Centre and the UK Data Archive under the terms of the UPGro data management agreement.

Deep Habits: Workshop as Critique in Creative Writing

ERIC Educational Resources Information Center

Stukenberg, Jill

2017-01-01

The creative writing workshop, involving peer critique of manuscripts in progress, is deeply connected to many writerly habits of mind. As such, this article examines workshop as a signature pedagogy in creative writing. Through workshop, students develop awareness of their readers, understanding of how texts are created by readers and through…

Using a Water Purification Activity to Teach the Philosophy and Nature of Technology

ERIC Educational Resources Information Center

Kruse, Jerrid; Wilcox, Jesse

2017-01-01

Next Generation Science Standards (NGSS), with new emphasis on engineering, reflects broadening definitions of scientific and technological literacy. However, engaging in science and engineering practices is necessary, but insufficient, for developing technological literacy. Just as robust scientific literacy includes a deep understanding of the…

Exploring Children's Literature. Second Edition

ERIC Educational Resources Information Center

Gamble, Nikki; Yates, Sally

2008-01-01

This book is based on the belief that deep subject knowledge of language and literature provides a foundation for effective teaching and learning. It provides a guide to the range of genres and characteristic features of English language fiction written for children. It is designed to help readers to develop their understanding of literature…

Preservice Teachers Developing Coherent Inquiry Investigations in Elementary Astronomy

ERIC Educational Resources Information Center

Plummer, Julia D.; Tanis Ozcelik, Arzu

2015-01-01

For students to attain deep understanding of scientific practices, they will need to have opportunities to participate in sustained engagement in doing science. Such opportunities begin with elementary teachers implementing coherent and well-sequenced inquiry-based investigations in their classrooms. This study explored how preservice teachers (N…

Experimenting "Learn by Doing" and "Learn by Failing"

ERIC Educational Resources Information Center

Pozzi, Rossella; Noè, Carlo; Rossi, Tommaso

2015-01-01

According to the literature, in recent years, developing experiential learning has fulfilled the requirement of a deep understanding of lean philosophy by engineering students, demonstrating the advantages and disadvantages of some of the key principles of lean manufacturing. On the other hand, the literature evidences how some kinds of game-based…

Using Number Sense to Compare Fractions

ERIC Educational Resources Information Center

Bray, Wendy S.; Abreu-Sanchez, Laura

2010-01-01

One mathematical focus for third graders is to develop deep understanding of fractions and fraction equivalence, including comparing fractions through use of models and reasoning strategies. Before reading further, consider how you might solve the following problem: Which fraction is greater, 14/24 or 17/36? The initial impulse of many adults is…

Between Writers: Exploring Literature from (Deep) Within.

ERIC Educational Resources Information Center

Lang, Frederick K.

This paper provides a creative approach to developing literary understanding and writing ability in students in a college introduction to literature course. Eight assignments are described which pair literary works having some feature in common. A sample suggestion from the first group of exercises, concerned with characterization, is as follows:…

Error sources in passive and active microwave satellite soil moisture over Australia

USDA-ARS?s Scientific Manuscript database

Development of a long-term climate record of soil moisture (SM) involves combining historic and present satellite-retrieved SM data sets. This in turn requires a consistent characterization and deep understanding of the systematic differences and errors in the individual data sets, which vary due to...

Asynchronous Discourse in a Web-Assisted Mathematics Education Course

ERIC Educational Resources Information Center

Li, Zhongxiao

2009-01-01

Fall term of 2006, a web-assisted undergraduate mathematics course was taught at the University of Idaho: Math 235 Mathematics for Elementary Teachers I. The course goals were: To foster a deep understanding of critical mathematical content; and to promote the development of mathematical communication and collaboration concepts, skills, and…

Examining Hip-Hop as Culturally Relevant Pedagogy

ERIC Educational Resources Information Center

Kim, Jung; Pulido, Isaura

2015-01-01

Culturally relevant pedagogy is a framework that conceptualizes the process of student learning as contingent upon educators' deep understanding of students' cultural backgrounds to co-construct knowledge and develop academic skills. Concurrently, there are a growing number of studies that explore hip-hop as a culturally relevant curriculum for…

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…

Mechanism of saline groundwater migration under the influence of deep groundwater exploitation in the North China Plain

NASA Astrophysics Data System (ADS)

Han, D.; Cao, G.; Currell, M. J.

2016-12-01

Understanding the mechanism of salt water transport in response to the exploitation of deep freshwater has long been one of the major regional environmental hydrogeological problems and scientific challenges in the North China Plain. It is also the key to a correct understanding of the sources of deep groundwater pumpage. This study will look at the Hengshui - Cangzhou region as a region with typical vertical salt water distribution, and high levels of groundwater exploitation, integrating a variety of techniques in geology, hydrogeology, geophysics, hydrodynamics, and hydrochemistry - stable isotopes. Information about the problem will be determined using multiple lines of evidence, including field surveys of drilling and water sampling, as well as laboratory experiments and physical and numerical simulations. The project will characterize and depict the migration characteristics of salt water bodies and their relationship with the geological structure and deep ground water resources. The work will reveal the freshwater-saltwater interface shape; determine the mode and mechanism of hydrodynamic transport and salt transport; estimate the vertical migration time of salt water in a thick aquitard; and develop accurate hydrogeological conceptual models. This work will utilize groundwater variable density flow- solute transport numerical models to simulate the water and salt transport processes in vertical one-dimensional (typical bore) and two-dimensional (typical cross-section) space. Both inversion of the downward movement of saltwater caused by groundwater exploitation through history, and examining future saltwater migration trends under groundwater exploitation scenarios will be conducted, to quantitatively evaluate the impact of salt water migration to the deep groundwater body in the North China Plain. The research results will provide a scientific basis for the sustainable utilization of deep groundwater resources in this area.

Jet-images — deep learning edition

DOE PAGES

de Oliveira, Luke; Kagan, Michael; Mackey, Lester; ...

2016-07-13

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Jet-images — deep learning edition

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

de Oliveira, Luke; Kagan, Michael; Mackey, Lester

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

The Nature of Conceptual Understanding in Biomedicine: The Deep Structure of Complex Ideas and the Development of Misconceptions. Technical Report No. 440.

ERIC Educational Resources Information Center

Feltovich, Paul J.; And Others

This report presents a general framework for studying the acquisition and cognitive representation of biomedical concepts and analyzing the nature and development of misconceptions. The central approach of the report is a selective and highly concentrated analysis of the true nature of clusters of complex concepts and the manner in which they are…

Starvation and recovery in the deep-sea methanotroph Methyloprofundus sedimenti.

PubMed

Tavormina, Patricia L; Kellermann, Matthias Y; Antony, Chakkiath Paul; Tocheva, Elitza I; Dalleska, Nathan F; Jensen, Ashley J; Valentine, David L; Hinrichs, Kai-Uwe; Jensen, Grant J; Dubilier, Nicole; Orphan, Victoria J

2017-01-01

In the deep ocean, the conversion of methane into derived carbon and energy drives the establishment of diverse faunal communities. Yet specific biological mechanisms underlying the introduction of methane-derived carbon into the food web remain poorly described, due to a lack of cultured representative deep-sea methanotrophic prokaryotes. Here, the response of the deep-sea aerobic methanotroph Methyloprofundus sedimenti to methane starvation and recovery was characterized. By combining lipid analysis, RNA analysis, and electron cryotomography, it was shown that M. sedimenti undergoes discrete cellular shifts in response to methane starvation, including changes in headgroup-specific fatty acid saturation levels, and reductions in cytoplasmic storage granules. Methane starvation is associated with a significant increase in the abundance of gene transcripts pertinent to methane oxidation. Methane reintroduction to starved cells stimulates a rapid, transient extracellular accumulation of methanol, revealing a way in which methane-derived carbon may be routed to community members. This study provides new understanding of methanotrophic responses to methane starvation and recovery, and lays the initial groundwork to develop Methyloprofundus as a model chemosynthesizing bacterium from the deep sea. © 2016 John Wiley & Sons Ltd.

The Importance of Conducting Life Sciences Experiments on the Deep Space Gateway Platform

NASA Technical Reports Server (NTRS)

Bhattacharya, S.

2018-01-01

Over the last several decades important information has been gathered by conducting life science experiments on the Space Shuttle and on the International Space Station. It is now time to leverage that scientific knowledge, as well as aspects of the hardware that have been developed to support the biological model systems, to NASA's next frontier - the Deep Space Gateway. In order to facilitate long duration deep space exploration for humans, it is critical for NASA to understand the effects of long duration, low dose, deep space radiation on biological systems. While carefully controlled ground experiments on Earth-based radiation facilities have provided valuable preliminary information, we still have a significant knowledge gap on the biological responses of organisms to chronic low doses of the highly ionizing particles encountered beyond low Earth orbit. Furthermore, the combined effects of altered gravity and radiation have the potential to cause greater biological changes than either of these parameters alone. Therefore a thorough investigation of the biological effects of a cis-lunar environment will facilitate long term human exploration of deep space.

Deep-Sea Microbes: Linking Biogeochemical Rates to -Omics Approaches

NASA Astrophysics Data System (ADS)

Herndl, G. J.; Sintes, E.; Bayer, B.; Bergauer, K.; Amano, C.; Hansman, R.; Garcia, J.; Reinthaler, T.

2016-02-01

Over the past decade substantial progress has been made in determining deep ocean microbial activity and resolving some of the enigmas in understanding the deep ocean carbon flux. Also, metagenomics approaches have shed light onto the dark ocean's microbes but linking -omics approaches to biogeochemical rate measurements are generally rare in microbial oceanography and even more so for the deep ocean. In this presentation, we will show by combining metagenomics, -proteomics and biogeochemical rate measurements on the bulk and single-cell level that deep-sea microbes exhibit characteristics of generalists with a large genome repertoire, versatile in utilizing substrate as revealed by metaproteomics. This is in striking contrast with the apparently rather uniform dissolved organic matter pool in the deep ocean. Combining the different -omics approaches with metabolic rate measurements, we will highlight some major inconsistencies and enigmas in our understanding of the carbon cycling and microbial food web structure in the dark ocean.

Measuring Student Understanding of Geological Time

ERIC Educational Resources Information Center

Dodick, Jeff; Orion, Nir

2003-01-01

There have been few discoveries in geology more important than "deep time"--the understanding that the universe has existed for countless millennia, such that man's existence is confined to the last milliseconds of the metaphorical geological clock. The influence of deep time is felt in a variety of sciences including geology, cosmology,…

Advancing an In situ Laser Spectrometer for Carbon Isotope Analyses in the Deep Ocean

NASA Astrophysics Data System (ADS)

Michel, A.; Wankel, S. D.; Kapit, J.; Girguis, P. R.

2016-02-01

Development of in situ chemical sensors is critical for improving our understanding of deep-ocean biogeochemistry and recent advances in chemical sensors are already expanding the breadth and depth of deep sea/seafloor exploration and research. Although initially developed for high sensitivity measurements of atmospheric gases, laser-based spectroscopic sensors are now being developed for research in the deep sea by incorporating the use of semi-permeable membranes. Here we present on recent deep-sea deployments of an in situ laser-based analyzer of carbon isotopes of methane (δ13CH4), highlighting several advances including a new capability for also measuring δ13C of DIC or CO2 by incorporating a second laser and an in line acidification module. A bubble trapping approach was designed and implemented for the collection and analysis of both CH4 and CO2 from deep-sea bubbles. The newly advanced laser spectrometer was deployed at both Kick `Em Jenny volcano off of the island of Grenada and in a brine pool in the western Gulf of Mexico ("The Jacuzzi of Despair") using the E/V Nautilus and the ROV Hercules. At Kick `Em Jenny, seafloor measurements were made of both emanating fluids and bubbles from within and around the crater - revealing high levels of magmatic CO2 with minor amounts of CH4 and hydrogen sulfide. At the brine pool, spot measurements and depth profile measurements into the brine pool were made for chemical mapping, revealing fluids that were saturated with respect to methane. New technologies such as the laser spectrometer will enable us to obtain high resolution and near real-time, in situ chemical and isotopic data and to make geochemical maps over a range of spatial and temporal scales.

Hess Deep Interactive Lab: Exploring the Structure and Formation of the Oceanic Crust through Hands-On Models and Online Tools

NASA Astrophysics Data System (ADS)

Kurtz, N.; Marks, N.; Cooper, S. K.

2014-12-01

Scientific ocean drilling through the International Ocean Discovery Program (IODP) has contributed extensively to our knowledge of Earth systems science. However, many of its methods and discoveries can seem abstract and complicated for students. Collaborations between scientists and educators/artists to create accurate yet engaging demonstrations and activities have been crucial to increasing understanding and stimulating interest in fascinating geological topics. One such collaboration, which came out of Expedition 345 to the Hess Deep Rift, resulted in an interactive lab to explore sampling rocks from the usually inacessible lower oceanic crust, offering an insight into the geological processes that form the structure of the Earth's crust. This Hess Deep Interactive Lab aims to explain several significant discoveries made by oceanic drilling utilizing images of actual thin sections and core samples recovered from IODP expeditions. . Participants can interact with a physical model to learn about the coring and drilling processes, and gain an understanding of seafloor structures. The collaboration of this lab developed as a need to explain fundamental notions of the ocean crust formed at fast-spreading ridges. A complementary interactive online lab can be accessed at www.joidesresolution.org for students to engage further with these concepts. This project explores the relationship between physical and on-line models to further understanding, including what we can learn from the pros and cons of each.

On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

NASA Astrophysics Data System (ADS)

LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

2017-12-01

The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

Deep learning for healthcare: review, opportunities and challenges.

PubMed

Miotto, Riccardo; Wang, Fei; Wang, Shuang; Jiang, Xiaoqian; Dudley, Joel T

2017-05-06

Gaining knowledge and actionable insights from complex, high-dimensional and heterogeneous biomedical data remains a key challenge in transforming health care. Various types of data have been emerging in modern biomedical research, including electronic health records, imaging, -omics, sensor data and text, which are complex, heterogeneous, poorly annotated and generally unstructured. Traditional data mining and statistical learning approaches typically need to first perform feature engineering to obtain effective and more robust features from those data, and then build prediction or clustering models on top of them. There are lots of challenges on both steps in a scenario of complicated data and lacking of sufficient domain knowledge. The latest advances in deep learning technologies provide new effective paradigms to obtain end-to-end learning models from complex data. In this article, we review the recent literature on applying deep learning technologies to advance the health care domain. Based on the analyzed work, we suggest that deep learning approaches could be the vehicle for translating big biomedical data into improved human health. However, we also note limitations and needs for improved methods development and applications, especially in terms of ease-of-understanding for domain experts and citizen scientists. We discuss such challenges and suggest developing holistic and meaningful interpretable architectures to bridge deep learning models and human interpretability. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

DCO-VIVO: A Collaborative Data Platform for the Deep Carbon Science Communities

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.; West, P.; Erickson, J. S.; Ma, X.; Fox, P. A.

2014-12-01

Deep Carbon Observatory (DCO) is a decade-long scientific endeavor to understand carbon in the complex deep Earth system. Thousands of DCO scientists from institutions across the globe are organized into communities representing four domains of exploration: Extreme Physics and Chemistry, Reservoirs and Fluxes, Deep Energy, and Deep Life. Cross-community and cross-disciplinary collaboration is one of the most distinctive features in DCO's flexible research framework. VIVO is an open-source Semantic Web platform that facilitates cross-institutional researcher and research discovery. it includes a number of standard ontologies that interconnect people, organizations, publications, activities, locations, and other entities of research interest to enable browsing, searching, visualizing, and generating Linked Open (research) Data. The DCO-VIVO solution expedites research collaboration between DCO scientists and communities. Based on DCO's specific requirements, the DCO Data Science team developed a series of extensions to the VIVO platform including extending the VIVO information model, extended query over the semantic information within VIVO, integration with other open source collaborative environments and data management systems, using single sign-on, assigning of unique Handles to DCO objects, and publication and dataset ingesting extensions using existing publication systems. We present here the iterative development of these requirements that are now in daily use by the DCO community of scientists for research reporting, information sharing, and resource discovery in support of research activities and program management.

"She's Weird!"--The Social Construction of Bullying in School: A Review of Qualitative Research

ERIC Educational Resources Information Center

Thornberg, Robert

2011-01-01

Qualitative research provides opportunities to study bullying and peer harassment as social processes, interactions and meaning-making in the everyday context of particular settings. It offers the possibility of developing a deep understanding of the culture and group processes of bullying and the participants' perspectives on peer harassment as…

Using Design-Based Research to Develop Meaningful Online Discussions in Undergraduate Field Experience Courses

ERIC Educational Resources Information Center

Johnson, Carol; Hill, Laurie; Lock, Jennifer; Altowairiki, Noha; Ostrowski, Chris; da Rosa dos Santos, Luciano; Liu, Yang

2017-01-01

From a design perspective, the intentionality of students to engage in surface or deep learning is often experienced through prescribed activities and learning tasks. Educators understand that meaningful learning can be furthered through the structural and organizational design of the online environment that motivates the student towards task…

Promoting Complex Systems Learning through the Use of Conceptual Representations in Hypermedia

ERIC Educational Resources Information Center

Liu, Lei; Hmelo-Silver, Cindy E.

2009-01-01

Studying complex systems is increasingly important in many science domains. Many features of complex systems make it difficult for students to develop deep understanding. Our previous research indicated that a function-centered conceptual representation is part of the disciplinary toolbox of biologists, suggesting that it is an appropriate…

Exploring Children's Literature: Teaching the Language and Reading of Fiction.

ERIC Educational Resources Information Center

Gamble, Nikki; Yates, Sally

This book, a comprehensive guide to the range of genres and characteristic features of English-language fiction written for children, is based on the belief that deep subject knowledge of language and literature provides a foundation for effective teaching and learning. The book helps readers to develop their understanding of literature within…

Physics Assessment and the Development of a Taxonomy

ERIC Educational Resources Information Center

Buick, J. M.

2011-01-01

Aspects of assessment in physics are considered with the aim of designing assessments that will encourage a deep approach to student learning and will ultimately lead to higher levels of achievement. A range of physics questions are considered and categorized by the level of knowledge and understanding which is require for a successful answer.…

The Problem Solving Studio: An Apprenticeship Environment for Aspiring Engineers

ERIC Educational Resources Information Center

Le Doux, Joseph M.; Waller, Alisha A.

2016-01-01

This paper describes the problem-solving studio (PSS) learning environment. PSS was designed to teach students how to solve difficult analytical engineering problems without resorting to rote memorization of algorithms, while at the same time developing their deep conceptual understanding of the course topics. There are several key features of…

Using Integrative Graphic Assignments to Promote Deep Learning of the Market Mechanism

ERIC Educational Resources Information Center

Green, Gareth P.; Kelly, Brian D.; Peterson, Dean J.; Bean, John C.

2015-01-01

Economics faculty expect that students have an integrated understanding of economic theory upon graduation and that they grasp and appreciate how all elements of markets naturally move to equilibrium. Through assessment activities, the authors discovered that their students were not developing that knowledge, so they turned to learning theory to…

Learning by Thinking during Play: The Power of Reflection to Aid Performance

ERIC Educational Resources Information Center

Salmon, Angela K.

2016-01-01

Coupled with reflection, play leads to the development of thinking dispositions and promotes deep learning and understanding. The twenty-first century world demands that children learn how to learn by becoming reflective, self-regulating inquirers capable of metacognition (thinking about thinking). This manuscript aims to analyse how young minds…

YASS: A System Simulator for Operating System and Computer Architecture Teaching and Learning

ERIC Educational Resources Information Center

Mustafa, Besim

2013-01-01

A highly interactive, integrated and multi-level simulator has been developed specifically to support both the teachers and the learners of modern computer technologies at undergraduate level. The simulator provides a highly visual and user configurable environment with many pedagogical features aimed at facilitating deep understanding of concepts…

Under Construction: Minority Girls Becoming Technologically Fluent in an Urban After-School Program

ERIC Educational Resources Information Center

De La Pena, Yvonne

2012-01-01

Technological fluency involves having a deep understanding of information technology as well as an identity as someone who engages with technology in meaningful and complex ways. Hence, it is more fruitful to think about individuals not as developing technological fluency but rather as becoming technologically fluent. Although physical access to…

Changing International Constructs: How Metropolitan Universities Must Engage Globally

ERIC Educational Resources Information Center

Leventhal, Mitch; Zimpher, Nancy L.

2007-01-01

The mission of American metropolitan universities has never before been so relevant, both to the future of institutions themselves and to the United States. The success of the mission requires that we develop a deep understanding of the impact of both urbanization and de-urbanization, as well as the challenges metropolitan universities face with…

Waiting for a Crisis: Case Studies of Crisis Leaders in Higher Education

ERIC Educational Resources Information Center

Muffet-Willett, Stacy L.

2010-01-01

This study examines the system of crisis leadership in higher education. Using case study methods, five crisis leadership participants were interviewed to develop a deep understanding of how they perceive their university crisis leadership system. Two participants were from a private institution, and three were from a public institution. Higher…

The evolution of dorsal-ventral patterning mechanisms in insects.

PubMed

Lynch, Jeremy A; Roth, Siegfried

2011-01-15

The gene regulatory network (GRN) underpinning dorsal-ventral (DV) patterning of the Drosophila embryo is among the most thoroughly understood GRNs, making it an ideal system for comparative studies seeking to understand the evolution of development. With the emergence of widely applicable techniques for testing gene function, species with sequenced genomes, and multiple tractable species with diverse developmental modes, a phylogenetically broad and molecularly deep understanding of the evolution of DV axis formation in insects is feasible. Here, we review recent progress made in this field, compare our emerging molecular understanding to classical embryological experiments, and suggest future directions of inquiry.

1.5 My benthic foraminiferal B/Ca record of carbonate chemistry in the deep Atlantic: Implications for ocean alkalinity and atmospheric CO2

NASA Astrophysics Data System (ADS)

Rosenthal, Y.; Sosdian, S. M.; Toggweiler, J. R.

2017-12-01

Most hypotheses to explain glacial-interglacial changes in atmospheric CO2 invoke shifts in ocean alkalinity explain roughly half the reduction in glacial CO2 via CaCO3 compensatory mechanism. It follows that changes in CaCO3 burial occur in response to an increase in deep ocean respired carbon content. To date our understanding of this process comes from benthic carbon isotope and %CaCO3 records. However, to understand the nature of the ocean's buffering capacity and its role in modulating pCO2, orbitally resolved reconstructions of the deep ocean carbonate system parameters are necessary. Here we present a 1.5 Myr orbitally resolved deep ocean calcite saturation record (ΔCO32-) derived from benthic foraminiferal B/Ca ratios in the North Atlantic. Glacial B/Ca values decline across the mid-Pleistocene transition (MPT) suggesting increased sequestration of carbon in the deep Atlantic. The magnitude, timing, and structure of deep Atlantic Ocean ΔCO32- and %CaCO3 cycles contrast with the small amplitude, anti-phased swings in IndoPacific ΔCO32- and %CaCO3 during the mid-to-late Pleistocene. Increasing corrosivity of the deep Atlantic causes the locus of CaCO3 burial to shift into the equatorial Pacific where the flux of CaCO3 to the seafloor is high enough to establish and maintain a new "hot spot". We propose that the CO32- in the deep IndoPacific rises in response to the same mechanism that keeps the CO32- in the deep Atlantic low and the atmospheric CO2 low. The increase in interglacial atmospheric pCO2 levels following the Mid-Brunhes event ( 400ka) are associated with increased G/IG ΔCO3 amplitude, expressed by a decrease in the glacial ΔCO32- values. We propose the low persistent ΔCO32- levels at Marine Isotope Stage (MIS) 12 set the stage for the high pCO2 levels at MIS 11 via an increase in whole ocean alkalinity followed by enhanced CaCO3 preservation. Based on this, we suggest that the development of classic (`anticorrelated') CaCO3 patterns was driven by increased stratification and worsening ventilation in the deep Atlantic across the MPT.

Understanding deep roots and their functions in ecosystems: an advocacy for more unconventional research

PubMed Central

Pierret, Alain; Maeght, Jean-Luc; Clément, Corentin; Montoroi, Jean-Pierre; Hartmann, Christian; Gonkhamdee, Santimaitree

2016-01-01

Background Deep roots are a common trait among a wide range of plant species and biomes, and are pivotal to the very existence of ecosystem services such as pedogenesis, groundwater and streamflow regulation, soil carbon sequestration and moisture content in the lower troposphere. Notwithstanding the growing realization of the functional significance of deep roots across disciplines such as soil science, agronomy, hydrology, ecophysiology or climatology, research efforts allocated to the study of deep roots remain incommensurate with those devoted to shallow roots. This is due in part to the fact that, despite technological advances, observing and measuring deep roots remains challenging. Scope Here, other reasons that explain why there are still so many fundamental unresolved questions related to deep roots are discussed. These include the fact that a number of hypotheses and models that are widely considered as verified and sufficiently robust are only partly supported by data. Evidence has accumulated that deep rooting could be a more widespread and important trait among plants than usually considered based on the share of biomass that it represents. Examples that indicate that plant roots have different structures and play different roles with respect to major biochemical cycles depending on their position within the soil profile are also examined and discussed. Conclusions Current knowledge gaps are identified and new lines of research for improving our understanding of the processes that drive deep root growth and functioning are proposed. This ultimately leads to a reflection on an alternative paradigm that could be used in the future as a unifying framework to describe and analyse deep rooting. Despite the many hurdles that pave the way to a practical understanding of deep rooting functions, it is anticipated that, in the relatively near future, increased knowledge about the deep rooting traits of a variety of plants and crops will have direct and tangible influence on how we manage natural and cultivated ecosystems. PMID:27390351

Convective Available Potential Energy of World Ocean

NASA Astrophysics Data System (ADS)

Su, Z.; Ingersoll, A. P.; Thompson, A. F.

2012-12-01

Here, for the first time, we propose the concept of Ocean Convective Available Potential Energy (OCAPE), which is the maximum kinetic energy (KE) per unit seawater mass achievable by ocean convection. OCAPE occurs through a different mechanism from atmospheric CAPE, and involves the interplay of temperature and salinity on the equation of state of seawater. The thermobaric effect, which arises because the thermal coefficient of expansion increases with depth, is an important ingredient of OCAPE. We develop an accurate algorithm to calculate the OCAPE for a given temperature and salinity profile. We then validate our calculation of OCAPE by comparing it with the conversion of OCAPE to KE in a 2-D numerical model. We propose that OCAPE is an important energy source of ocean deep convection and contributes to deep water formation. OCAPE, like Atmospheric CAPE, can help predict deep convection and may also provide a useful constraint for modelling deep convection in ocean GCMs. We plot the global distribution of OCAPE using data from the World Ocean Atlas 2009 (WOA09) and see many important features. These include large values of OCAPE in the Labrador, Greenland, Weddell and Mediterranean Seas, which are consistent with our present observations and understanding, but also identify some new features like the OCAPE pattern in the Antarctic Circumpolar Current (ACC). We propose that the diagnosis of OCAPE can improve our understanding of global patterns of ocean convection and deep water formation as well as ocean stratification, the meridional overturning circulation and mixed layer processes. The background of this work is briefly introduced as below. Open-ocean deep convection can significantly modify water properties both at the ocean surface and throughout the water column (Gordon 1982). Open-ocean convection is also an important mechanism for Ocean Deep Water formation and the transport of heat, freshwater and nutrient (Marshall and Schott 1999). Open-ocean convection may arise through strong surface buoyancy fluxes (Schott et al. 1996), or by thermobaric instability (Akitomo 1999a, b). Ingersoll (2005) demonstrated that thermobaric-induced deep convection is due to the abrupt release of ocean potential energy into kinetic energy. In atmospheric dynamics, Convective Available Potential Energy (CAPE) has long been an important thermodynamic variable (Arakawa and Schubert 1974) that has been used to forecast moist convection (Doswell and Rasmussen 1994) and to test the performance of GCMs (Ye et al. 1998). However, the development of a similar diagnostic in the ocean has received little attention.; World Ocean Convective Available Potential Energy distribution in North-Hemisphere Autumn (J/kg)

3-D architecture modeling using high-resolution seismic data and sparse well control: Example from the Mars {open_quotes}Pink{close_quotes} reservoir, Mississippi Canyon Area, Gulf of Mexico

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

Chapin, M.A.; Tiller, G.M.; Mahaffie, M.J.

1996-12-31

Economic considerations of the deep-water turbidite play, in the Gulf of Mexico and elsewhere, require large reservoir volumes to be drained by relatively few, very expensive wells. Deep-water development projects to date have been planned on the basis of high-quality 3-D seismic data and sparse well control. The link between 3-D seismic, well control, and the 3-D geological and reservoir architecture model are demonstrated here for Pliocene turbidite sands of the {open_quotes}Pink{close_quotes} reservoir, Prospect Mars, Mississippi Canyon Areas 763 and 807, Gulf of Mexico. This information was used to better understand potential reservoir compartments for development well planning.

Sensory processing of deep tissue nociception in the rat spinal cord and thalamic ventrobasal complex.

PubMed

Sikandar, Shafaq; West, Steven J; McMahon, Stephen B; Bennett, David L; Dickenson, Anthony H

2017-07-01

Sensory processing of deep somatic tissue constitutes an important component of the nociceptive system, yet associated central processing pathways remain poorly understood. Here, we provide a novel electrophysiological characterization and immunohistochemical analysis of neural activation in the lateral spinal nucleus (LSN). These neurons show evoked activity to deep, but not cutaneous, stimulation. The evoked responses of neurons in the LSN can be sensitized to somatosensory stimulation following intramuscular hypertonic saline, an acute model of muscle pain, suggesting this is an important spinal relay site for the processing of deep tissue nociceptive inputs. Neurons of the thalamic ventrobasal complex (VBC) mediate both cutaneous and deep tissue sensory processing, but in contrast to the lateral spinal nucleus our electrophysiological studies do not suggest the existence of a subgroup of cells that selectively process deep tissue inputs. The sensitization of polymodal and thermospecific VBC neurons to mechanical somatosensory stimulation following acute muscle stimulation with hypertonic saline suggests differential roles of thalamic subpopulations in mediating cutaneous and deep tissue nociception in pathological states. Overall, our studies at both the spinal (lateral spinal nucleus) and supraspinal (thalamic ventrobasal complex) levels suggest a convergence of cutaneous and deep somatosensory inputs onto spinothalamic pathways, which are unmasked by activation of muscle nociceptive afferents to produce consequent phenotypic alterations in spinal and thalamic neural coding of somatosensory stimulation. A better understanding of the sensory pathways involved in deep tissue nociception, as well as the degree of labeled line and convergent pathways for cutaneous and deep somatosensory inputs, is fundamental to developing targeted analgesic therapies for deep pain syndromes. © 2017 University College London. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.

The Benefits of Virtual Presence in Space (VPS) to Deep Space Missions

NASA Technical Reports Server (NTRS)

De Jong, Eric M.; McGuffie, Barbara A; Levoe, Steven R.; Suzuki, Shigeru; Gorjian, Zareh; Leung, Chris; Cordell, Christopher; Loaiza, Frank; Baldwin, Robert; Craig, Jason;

VAFB-20180329-PH_CNW01_0019

NASA Image and Video Library

2018-03-29

In the Astrotech facility at Vandenberg Air Force Base in California, the heatshield is lifted for placement on NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

VAFB-20180329-PH_CNW01_0031

NASA Image and Video Library

2018-03-29

In the Astrotech facility at Vandenberg Air Force Base in California, the heatshield is placed on NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Encapsulation

NASA Image and Video Library

2018-04-16

In the Astrotech facility at Vandenberg Air Force Base in California, NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander is encapsulated in its payload fairing. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Encapsulation

NASA Image and Video Library

2018-04-16

In the Astrotech facility at Vandenberg Air Force Base in California, technicians and engineers encapsulate NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander in its payload fairing. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Rollout to Pad

NASA Image and Video Library

2018-04-23

Encapsulated in its payload fairing, NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander is transported to Space Launch Complex 3 at Vandenberg Air Force Base in California. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Rollout to Pad

NASA Image and Video Library

2018-04-23

Encapsulated in its payload fairing NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander arrives at Space Launch Complex 3 at Vandenberg Air Force Base in California. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Rollout to Pad

NASA Image and Video Library

2018-04-23

Encapsulated in its payload fairing NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander is transported to Space Launch Complex 3 at Vandenberg Air Force Base in California. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Lift & Mate

NASA Image and Video Library

2018-04-23

Encapsulated in its payload fairing NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander is prepared for transport to Space Launch Complex 3 at Vandenberg Air Force Base in California. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Battery Installation

NASA Image and Video Library

2018-04-20

In the gantry at Space Launch Complex 3 at Vandenberg Air Force Base in California, a technician prepares batteries for installation in NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

The Effects of Temperature and Hydrostatic Pressure on Metal Toxicity: Insights into Toxicity in the Deep Sea.

PubMed

Brown, Alastair; Thatje, Sven; Hauton, Chris

2017-09-05

Mineral prospecting in the deep sea is increasing, promoting concern regarding potential ecotoxicological impacts on deep-sea fauna. Technological difficulties in assessing toxicity in deep-sea species has promoted interest in developing shallow-water ecotoxicological proxy species. However, it is unclear how the low temperature and high hydrostatic pressure prevalent in the deep sea affect toxicity, and whether adaptation to deep-sea environmental conditions moderates any effects of these factors. To address these uncertainties we assessed the effects of temperature and hydrostatic pressure on lethal and sublethal (respiration rate, antioxidant enzyme activity) toxicity in acute (96 h) copper and cadmium exposures, using the shallow-water ecophysiological model organism Palaemon varians. Low temperature reduced toxicity in both metals, but reduced cadmium toxicity significantly more. In contrast, elevated hydrostatic pressure increased copper toxicity, but did not affect cadmium toxicity. The synergistic interaction between copper and cadmium was not affected by low temperature, but high hydrostatic pressure significantly enhanced the synergism. Differential environmental effects on toxicity suggest different mechanisms of action for copper and cadmium, and highlight that mechanistic understanding of toxicity is fundamental to predicting environmental effects on toxicity. Although results infer that sensitivity to toxicants differs across biogeographic ranges, shallow-water species may be suitable ecotoxicological proxies for deep-sea species, dependent on adaptation to habitats with similar environmental variability.

Data assimilation for the investigation of deep temperature and geothermal energy in the Netherlands.

NASA Astrophysics Data System (ADS)

Bonté, Damien; Limberger, Jon; Lipsey, Lindsey; Cloetingh, Sierd; van Wees, Jan-Diederik

2016-04-01

Deep geothermal energy systems, mostly for the direct use of heat, have been attracting more and more interest in the past 10 years in Western Europe. In the Netherlands, where the sector took off with the first system in 2005, geothermal energy is seen has a key player for a sustainable future. To support the development of deep geothermal energy system, the scientific community has been working on tools that could be used to highlight area of potential interest for geothermal exploration. In the Netherlands, ThermoGIS is one such tool that has been developed to inform the general public, policy makers, and developers in the energy sector of the possibility of geothermal energy development. One major component incorporated in this tool is the temperature model. For the Netherlands, we created a thermal model at the lithospheric scale that focus on the sedimentary deposits for deep geothermal exploration. This regional thermal modelling concentrates on the variations of geological thermal conductivity and heat production both in the sediments and in the crust. In addition, we carried out special modelling in order to specifically understand convectivity in the basin, focusing on variations at a regional scale. These works, as well as recent improved of geological knowledge in the deeper part of the basin, show interesting evidence for geothermal energy development. At this scale, the aim of this work is to build on these models and, using data assimilation, to discriminate in the actual causes of the observed anomalies. The temperature results obtained for the Netherlands show some thermal patterns that relate to the variation of the thermal conductivity and the geometry of the sediments. There is also strong evidence to indicate that deep convective flows are responsible for thermal anomalies. The combination of conductive and local convective thermal patterns makes the deeper part of the Dutch sedimentary basin of great interest for the development of geothermal energy.

Landcover Classification Using Deep Fully Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Wang, J.; Li, X.; Zhou, S.; Tang, J.

2017-12-01

Land cover classification has always been an essential application in remote sensing. Certain image features are needed for land cover classification whether it is based on pixel or object-based methods. Different from other machine learning methods, deep learning model not only extracts useful information from multiple bands/attributes, but also learns spatial characteristics. In recent years, deep learning methods have been developed rapidly and widely applied in image recognition, semantic understanding, and other application domains. However, there are limited studies applying deep learning methods in land cover classification. In this research, we used fully convolutional networks (FCN) as the deep learning model to classify land covers. The National Land Cover Database (NLCD) within the state of Kansas was used as training dataset and Landsat images were classified using the trained FCN model. We also applied an image segmentation method to improve the original results from the FCN model. In addition, the pros and cons between deep learning and several machine learning methods were compared and explored. Our research indicates: (1) FCN is an effective classification model with an overall accuracy of 75%; (2) image segmentation improves the classification results with better match of spatial patterns; (3) FCN has an excellent ability of learning which can attains higher accuracy and better spatial patterns compared with several machine learning methods.

MR Anatomy of Deep Brain Nuclei with Special Reference to Specific Diseases and Deep Brain Stimulation Localization

PubMed Central

Telford, Ryan; Vattoth, Surjith

2014-01-01

Summary Diseases affecting the basal ganglia and deep brain structures vary widely in etiology and include metabolic, infectious, ischemic, and neurodegenerative conditions. Some neurologic diseases, such as Wernicke encephalopathy or pseudohypoparathyroidism, require specific treatments, which if unrecognized could lead to further complications. Other pathologies, such as hypertrophic olivary degeneration, if not properly diagnosed may be mistaken for a primary medullary neoplasm and create unnecessary concern. The deep brain structures are complex and can be difficult to distinguish on routine imaging. It is imperative that radiologists first understand the intrinsic anatomic relationships between the different basal ganglia nuclei and deep brain structures with magnetic resonance (MR) imaging. It is important to understand the "normal" MR signal characteristics, locations, and appearances of these structures. This is essential to recognizing diseases affecting the basal ganglia and deep brain structures, especially since most of these diseases result in symmetrical, and therefore less noticeable, abnormalities. It is also crucial that neurosurgeons correctly identify the deep brain nuclei presurgically for positioning deep brain stimulator leads, the most important being the subthalamic nucleus for Parkinson syndromes and the thalamic ventral intermediate nucleus for essential tremor. Radiologists will be able to better assist clinicians in diagnosis and treatment once they are able to accurately localize specific deep brain structures. PMID:24571832

Teaching with Procedural Variation: A Chinese Way of Promoting Deep Understanding of Mathematics

ERIC Educational Resources Information Center

Lai, Mun Yee; Murray, Sara

2012-01-01

In mathematics education, there has been tension between deep learning and repetitive learning. Western educators often emphasize the need for students to construct a conceptual understanding of mathematical symbols and rules before they practise the rules (Li, 2006). On the other hand, Chinese learners tend to be oriented towards rote learning…

Collective Landmarks for Deep Time: A New Tool for Evolution Education

ERIC Educational Resources Information Center

Delgado, Cesar

2014-01-01

Evolution is a fundamental, organising concept in biology, yet there is widespread resistance to evolution among US students and there are rising creationist challenges in Europe. Resistance to evolution is linked to lack of understanding of the age of the Earth. An understanding of deep time is thus essential for effective biology education.…

Cultural sensitivity in public health: defined and demystified.

PubMed

Resnicow, K; Baranowski, T; Ahluwalia, J S; Braithwaite, R L

1999-01-01

There is consensus that health promotion programs should be culturally sensitive (CS). Yet, despite the ubiquitous nature of CS within public health research and practice, there has been surprisingly little attention given to defining CS or delineating a framework for developing culturally sensitive programs and practitioners. This paper describes a model for understanding CS from a public health perspective; describes a process for applying this model in the development of health promotion and disease prevention interventions; and highlights research priorities. Cultural sensitivity is defined by two dimensions: surface and deep structures. Surface structure involves matching intervention materials and messages to observable, "superficial" characteristics of a target population. This may involve using people, places, language, music, food, locations, and clothing familiar to, and preferred by, the target audience. Surface structure refers to how well interventions fit within a specific culture. Deep structure involves incorporating the cultural, social, historical, environmental and psychological forces that influence the target health behavior in the proposed target population. Whereas surface structure generally increases the "receptivity" or "acceptance" of messages, deep structure conveys salience. Techniques, borrowed from social marketing and health communication theory, for developing culturally sensitive interventions are described. Research is needed to determine the effectiveness of culturally sensitive programs.

Research and Teaching About the Deep Earth

NASA Astrophysics Data System (ADS)

Williams, Michael L.; Mogk, David W.; McDaris, John

2010-08-01

Understanding the Deep Earth: Slabs, Drips, Plumes and More; Virtual Workshop, 17-19 February and 24-26 February 2010; Images and models of active faults, subducting plates, mantle drips, and rising plumes are spurring new excitement about deep-Earth processes and connections between Earth's internal systems and plate tectonics. The new results and the steady progress of Earthscope's USArray across the country are also providing a special opportunity to reach students and the general public. The pace of discoveries about the deep Earth is accelerating due to advances in experimental, modeling, and sensing technologies; new data processing capabilities; and installation of new networks, especially the EarthScope facility. EarthScope is an interdisciplinary program that combines geology and geophysics to study the structure and evolution of the North American continent. To explore the current state of deep-Earth science and ways in which it can be brought into the undergraduate classroom, 40 professors attended a virtual workshop given by On the Cutting Edge, a program that strives to improve undergraduate geoscience education through an integrated cooperative series of workshops and Web-based resources. The 6-day two-part workshop consisted of plenary talks, large and small group discussions, and development and review of new classroom and laboratory activities.

Beginning Teachers and the Emotional Drama of the Classroom

ERIC Educational Resources Information Center

Intrator, Sam M.

2006-01-01

As a teacher educator, the author believes that he must prepare teachers to go forth into schools with a deep understanding of the subjects they will teach, an appreciation for how students learn, and a repertoire of instructional strategies that will help them make learning come alive for their students. As they develop these skills, they must…

Exploring Children's Literature: Teaching the Language and Reading of Fiction. First Edition

ERIC Educational Resources Information Center

Gamble, Nikki; Yates, Sally

2002-01-01

This book is based on the belief that deep subject knowledge of language and literature provides a foundation for effective teaching and learning. It provides a guide to the range of genres and characteristic features of English language fiction written for children, and is designed to help readers: (1) Develop their understanding of literature…

Visual Culture and Literacy Online: Image Galleries as Sites of Learning

ERIC Educational Resources Information Center

Carpenter, B. Stephen, II; Cifuentes, Lauren

2011-01-01

As new media emerge in the common culture, the authors recommend that art educators adopt those media to facilitate deep understanding of visual culture and literacy. They report here on applications of an online image gallery that helps users develop ways to interpret what they see and compose. Over the past few years the authors have…

Moving Authentic Soil Research into High School Classrooms: Student Engagement and Learning

ERIC Educational Resources Information Center

Moebius-Clune, Bianca N.; Elsevier, Irka H.; Crawford, Barbara A.; Trautmann, Nancy M.; Schindelbeck, Robert R.; van Es, Harold M.

2011-01-01

Inquiry-based teaching helps students develop a deep, applied understanding of human-environmental connections, but most high school curricula do not use inquiry-based methods. Soil science topics, which are also generally lacking from curricula, can provide hands-on model systems for learning inquiry skills. We report on the implementation of a…

Using Technology-Enabled Active Learning Tools to Introduce Business Ethics Topics in Business Law Courses: A Few Practical Examples

ERIC Educational Resources Information Center

Reid, Linda A.; Weber, Curt M.

2008-01-01

In this article, the authors echo the assertion of the Association to Advance Collegiate Schools of Business (AACSB) Ethics Education Task Force that business schools must encourage students to develop a deep understanding of the myriad challenges surrounding corporate responsibility and corporate governance; provide them with tools for…

A Concept-Based Approach to Teaching Speech Acts in the EFL Classroom

ERIC Educational Resources Information Center

Nicholas, Allan

2015-01-01

While concept-based instruction (CBI), grounded in sociocultural theory, has been the subject of increased attention in recent years, it is still a relatively unknown methodology in language teaching contexts. In this approach, the emphasis is on helping learners develop a deep, conceptual understanding of a skill or knowledge area, so that this…

The Open World: Access to Knowledge as a Foundation for an Open World

ERIC Educational Resources Information Center

Rossini, Carolina

2010-01-01

The change brought about in the networked information environment is deep and structural, in a way that has the potential to empower cultures left out of the Industrial Revolution. Thus, the author stresses that it is fundamental for individuals to understand, from a developing nation's perspective, how the Internet changes the capacity of…

100 Campfires: Towards a Personal Canoeing Philosophy

ERIC Educational Resources Information Center

Bain, David

2012-01-01

In this article, the author talks about canoeing and shares his experience canoeing with a group of trippers in Canada. He also discusses how he developed an understanding of where canoeing in Canada has come from. He contends that the way individuals canoe sends a deep, unconscious message to the brain, and it defines the canoeing experience for…

Too Much Teaching, Not Enough Learning: What Is the Solution?

ERIC Educational Resources Information Center

Lujan, Heidi L.; DiCarlo, Stephen E.

2006-01-01

The curriculum is packed with so much content that teachers resort to telling students what they know and students simply commit facts to memory. The packed curriculum leaves little time for students to acquire a deep understanding of the subject or to develop life-long skills such as critical thinking, problem solving, and communication. However,…

Determining the "Essentials" for an Undergraduate Sustainability Degree Program: A Delphi Study at Dalhousie University

ERIC Educational Resources Information Center

Wright, Tarah S. A.; DeFields, Danielle

2012-01-01

Fostering a deep understanding of sustainability in students is critical in order to create a new generation of leaders. Universities have a significant role to play in this endeavour. Dalhousie University has recently developed the Environment, Sustainability and Society (ESS) program, which gives students the opportunity to study sustainability…

Classroom Interaction in Teaching English as Foreign Language at Lower Secondary Schools in Indonesia

ERIC Educational Resources Information Center

Sundari, Hanna

2017-01-01

The aim of this study was to develop a deep understanding of interaction in language classroom in foreign language context. Interviews, as major instrument, to twenty experienced English language teachers from eight lower secondary schools (SMP) were conducted in Jakarta, completed by focus group discussions and class observation/recordings. The…

English Learners, Writing, and the Common Core

ERIC Educational Resources Information Center

Olson, Carol Booth; Scarcella, Robin; Matuchniak, Tina

2015-01-01

Adopted by 46 states, the Common Core State Standards (CCSS) present a vision of what it means to be literate in the twenty-first century and call for all students, including English learners, to develop critical reading skills necessary for a deep understanding of complex texts, and critical writing skills to write about those texts. This article…

The Relation between Executive Function and Theory of Mind Is More than Skin Deep

ERIC Educational Resources Information Center

Carlson, Stephanie M.; Claxton, Laura J.; Moses, Louis J.

2015-01-01

A simple "expression" account of the relation between executive function (EF) and children's developing theory of mind (ToM) has difficulty accounting for the generality of the changes occurring in children's mental-state understanding during the preschool years. The current study of preschool children (N = 43) showed that EF--especially…

Reading for Deep Understanding: Knowledge Building and Conceptual Artifacts in Secondary English

ERIC Educational Resources Information Center

Nachowitz, Marc

2012-01-01

The purpose of this design-based experiment is two-fold: to see if classroom pedagogies can be developed to improve student achievement in English literature as well as prepare them for 21st Century literacies. Applying Bereiter and Scardamalia's theory of Knowledge Building to English curricula, this experiment tracked the progress of a…

Understanding Deep Representations Learned in Modeling Users Likes.

PubMed

Guntuku, Sharath Chandra; Zhou, Joey Tianyi; Roy, Sujoy; Lin, Weisi; Tsang, Ivor W

2016-08-01

Automatically understanding and discriminating different users' liking for an image is a challenging problem. This is because the relationship between image features (even semantic ones extracted by existing tools, viz., faces, objects, and so on) and users' likes is non-linear, influenced by several subtle factors. This paper presents a deep bi-modal knowledge representation of images based on their visual content and associated tags (text). A mapping step between the different levels of visual and textual representations allows for the transfer of semantic knowledge between the two modalities. Feature selection is applied before learning deep representation to identify the important features for a user to like an image. The proposed representation is shown to be effective in discriminating users based on images they like and also in recommending images that a given user likes, outperforming the state-of-the-art feature representations by  ∼ 15 %-20%. Beyond this test-set performance, an attempt is made to qualitatively understand the representations learned by the deep architecture used to model user likes.

Deep subsurface microbial processes

USGS Publications Warehouse

Lovley, D.R.; Chapelle, F.H.

1995-01-01

Information on the microbiology of the deep subsurface is necessary in order to understand the factors controlling the rate and extent of the microbially catalyzed redox reactions that influence the geophysical properties of these environments. Furthermore, there is an increasing threat that deep aquifers, an important drinking water resource, may be contaminated by man's activities, and there is a need to predict the extent to which microbial activity may remediate such contamination. Metabolically active microorganisms can be recovered from a diversity of deep subsurface environments. The available evidence suggests that these microorganisms are responsible for catalyzing the oxidation of organic matter coupled to a variety of electron acceptors just as microorganisms do in surface sediments, but at much slower rates. The technical difficulties in aseptically sampling deep subsurface sediments and the fact that microbial processes in laboratory incubations of deep subsurface material often do not mimic in situ processes frequently necessitate that microbial activity in the deep subsurface be inferred through nonmicrobiological analyses of ground water. These approaches include measurements of dissolved H2, which can predict the predominant microbially catalyzed redox reactions in aquifers, as well as geochemical and groundwater flow modeling, which can be used to estimate the rates of microbial processes. Microorganisms recovered from the deep subsurface have the potential to affect the fate of toxic organics and inorganic contaminants in groundwater. Microbial activity also greatly influences 1 the chemistry of many pristine groundwaters and contributes to such phenomena as porosity development in carbonate aquifers, accumulation of undesirably high concentrations of dissolved iron, and production of methane and hydrogen sulfide. Although the last decade has seen a dramatic increase in interest in deep subsurface microbiology, in comparison with the study of other habitats, the study of deep subsurface microbiology is still in its infancy.

Quantum-chemical insights from deep tensor neural networks

PubMed Central

Schütt, Kristof T.; Arbabzadah, Farhad; Chmiela, Stefan; Müller, Klaus R.; Tkatchenko, Alexandre

2017-01-01

Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol−1) predictions in compositional and configurational chemical space for molecules of intermediate size. As an example of chemical relevance, the model reveals a classification of aromatic rings with respect to their stability. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantum-chemical systems. PMID:28067221

Quantum-chemical insights from deep tensor neural networks.

PubMed

Schütt, Kristof T; Arbabzadah, Farhad; Chmiela, Stefan; Müller, Klaus R; Tkatchenko, Alexandre

2017-01-09

Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol -1 ) predictions in compositional and configurational chemical space for molecules of intermediate size. As an example of chemical relevance, the model reveals a classification of aromatic rings with respect to their stability. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantum-chemical systems.

Quantum-chemical insights from deep tensor neural networks

NASA Astrophysics Data System (ADS)

Schütt, Kristof T.; Arbabzadah, Farhad; Chmiela, Stefan; Müller, Klaus R.; Tkatchenko, Alexandre

2017-01-01

Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol-1) predictions in compositional and configurational chemical space for molecules of intermediate size. As an example of chemical relevance, the model reveals a classification of aromatic rings with respect to their stability. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantum-chemical systems.

Does seismic activity control carbon exchanges between transform-faults in old ocean crust and the deep sea? A hypothesis examined by the EU COST network FLOWS

NASA Astrophysics Data System (ADS)

Lever, M. A.

2014-12-01

The European Cooperation in Science and Technology (COST)-Action FLOWS (http://www.cost.eu/domains_actions/essem/Actions/ES1301) was initiated on the 25th of October 2013. It is a consortium formed by members of currently 14 COST countries and external partners striving to better understand the interplay between earthquakes and fluid flow at transform-faults in old oceanic crust. The recent occurrence of large earthquakes and discovery of deep fluid seepage calls for a revision of the postulated hydrogeological inactivity and low seismic activity of old oceanic transform-type plate boundaries, and indicates that earthquakes and fluid flow are intrinsically associated. This Action merges the expertise of a large number of research groups and supports the development of multidisciplinary knowledge on how seep fluid (bio)chemistry relates to seismicity. It aims to identify (bio)geochemical proxies for the detection of precursory seismic signals and to develop innovative physico-chemical sensors for deep-ocean seismogenic faults. National efforts are coordinated through Working Groups (WGs) focused on 1) geophysical and (bio)geochemical data acquisition; 2) modelling of structure and seismicity of faults; 3) engineering of deep-ocean physico-chemical seismic sensors; and 4) integration and dissemination. This poster will illustrate the overarching goals of the FLOWS Group, with special focus to research goals concerning the role of seismic activity in controlling the release of carbon from the old ocean crust into the deep ocean.

WHATS-3: An improved flow-through multi-bottle fluid sampler for deep-sea geofluid research

NASA Astrophysics Data System (ADS)

Miyazaki, Junichi; Makabe, Akiko; Matsui, Yohei; Ebina, Naoya; Tsutsumi, Saki; Ishibashi, Jun-ichiro; Chen, Chong; Kaneko, Sho; Takai, Ken; Kawagucci, Shinsuke

2017-06-01

Deep-sea geofluid systems, such as hydrothermal vents and cold seeps, are key to understanding subseafloor environments of Earth. Fluid chemistry, especially, provides crucial information towards elucidating the physical, chemical and biological processes that occur in these ecosystems. To accurately assess fluid and gas properties of deep-sea geofluids, well-designed pressure-tight fluid samplers are indispensable and as such they are important assets of deep-sea geofluid research. Here, the development of a new flow-through, pressure-tight fluid sampler capable of four independent sampling events (two subsamples for liquid and gas analyses from each) is reported. This new sampler, named WHATS-3, is a new addition to the WHATS-series samplers and a major upgrade from the previous WHATS-2 sampler with improvements in sample number, valve operational time, physical robustness, and ease of maintenance. Routine laboratory-based pressure tests proved that it is suitable for operation up to 35 MPa pressure. Successful field tests of the new sampler were also carried out in five hydrothermal fields, two in Indian Ocean and three in Okinawa Trough (max. depth 3,300 m). Relations of Mg and major ion species demonstrated bimodal mixing trends between a hydrothermal fluid and seawater, confirming the high-quality of fluids sampled. The newly developed WHATS-3 sampler is well-balanced in sampling capability, field usability, and maintenance feasibility, and can serve as one of the best geofluid samplers available at present to conduct efficient research of deep-sea geofluid systems.

On evolutionary climate tracks in deep mantle volatile cycle computed from numerical mantle convection simulations and its impact on the habitability of the Earth-like planets

NASA Astrophysics Data System (ADS)

Nakagawa, T.; Tajika, E.; Kadoya, S.

2017-12-01

Discussing an impact of evolution and dynamics in the Earth's deep interior on the surface climate change for the last few decades (see review by Ehlmann et al., 2016), the mantle volatile (particularly carbon) degassing in the mid-oceanic ridges seems to play a key role in understanding the evolutionary climate track for Earth-like planets (e.g. Kadoya and Tajika, 2015). However, since the mantle degassing occurs not only in the mid-oceanic ridges but also in the wedge mantle (island arc volcanism) and hotspots, to incorporate more accurate estimate of mantle degassing flux into the climate evolution framework, we developed a coupled model of surface climate-deep Earth evolution in numerical mantle convection simulations, including more accurate deep water and carbon cycle (e.g. Nakagawa and Spiegelman, 2017) with an energy balance theory of climate change. Modeling results suggest that the evolution of planetary climate computed from a developed model is basically consistent with an evolutionary climate track in simplified mantle degassing model (Kadoya and Tajika, 2015), but an occurrence timing of global (snowball) glaciation is strongly dependent on mantle degassing rate occurred with activities of surface plate motions. With this implication, the surface plate motion driven by deep mantle dynamics would play an important role in the planetary habitability of such as the Earth and Earth-like planets over geologic time-scale.

Modeling human craniofacial disorders in Xenopus

PubMed Central

Dubey, Aditi; Saint-Jeannet, Jean-Pierre

2017-01-01

Purpose of Review Craniofacial disorders are among the most common human birth defects and present an enormous health care and social burden. The development of animal models has been instrumental to investigate fundamental questions in craniofacial biology and this knowledge is critical to understand the etiology and pathogenesis of these disorders. Recent findings The vast majority of craniofacial disorders arise from abnormal development of the neural crest, a multipotent and migratory cell population. Therefore, defining the pathogenesis of these conditions starts with a deep understanding of the mechanisms that preside over neural crest formation and its role in craniofacial development. Summary This review discusses several studies using Xenopus embryos to model human craniofacial conditions, and emphasizes the strength of this system to inform important biological processes as they relate to human craniofacial development and disease. PMID:28255527

Development and validation of a method for measuring depth of understanding in constructivist learning

NASA Astrophysics Data System (ADS)

Guarino, Lucia Falsetti

A method for measuring depth of understanding of students in the middle-level science classroom was developed and validated. A common theme in the literature on constructivism in science education is that constructivist pedagogy, as opposed to objectivist pedagogy, results in a greater depth of understanding. Since few instruments measuring this construct exist at the present time, the development of such a tool to measure this construct was a significant contribution to the current body of assessment technologies in science education. The author's Depth of Understanding Assessment (DUA) evolved from a writing measure originally designed as a history assessment. The study involved 230 eighth grade science students studying a chemical change unit. The main research questions were: (1) What is the relationship between the DUA and each of the following independent variables: recall, application, and questioning modalities as measured by the Cognitive Preference Test; deep, surface, achieving, and deep-achieving approaches as measured by the Learning Process Questionnaire; achievement as measured by the Chemical Change Quiz, and teacher perception of student ability to conceptualize science content? (2) Is there a difference in depth of understanding, as measured by the DUA, between students who are taught by objectivist pedagogy and students who are taught by constructivist pedagogy favoring the constructivist group? (3) Is there a gender difference in depth of understanding as measured by the DUA? (4) Do students who are taught by constructivist pedagogy perceive their learning environment as more constructivist than students who are taught by objectivist pedagogy? Six out of nine hypothesis tests supported the validity of the DUA. The results of the qualitative component of this study which consisted of student interviews substantiated the quantitative results by providing additional information and insights. There was a significant difference in depth of understanding between the two groups favoring the constructivist group, however, since only two teachers and their students participated in the study, the significance of this result is limited. There was a significant gender difference in depth of understanding favoring females. Students in the constructivist group perceived their learning environment to be more constructivist than students in the objectivist group.

Deep brain stimulation for severe autism: from pathophysiology to procedure.

PubMed

Sinha, Saurabh; McGovern, Robert A; Sheth, Sameer A

2015-06-01

Autism is a heterogeneous neurodevelopmental disorder characterized by early-onset impairment in social interaction and communication and by repetitive, restricted behaviors and interests. Because the degree of impairment may vary, a spectrum of clinical manifestations exists. Severe autism is characterized by complete lack of language development and potentially life-threatening self-injurious behavior, the latter of which may be refractory to medical therapy and devastating for affected individuals and their caretakers. New treatment strategies are therefore needed. Here, the authors propose deep brain stimulation (DBS) of the basolateral nucleus of the amygdala (BLA) as a therapeutic intervention to treat severe autism. The authors review recent developments in the understanding of the pathophysiology of autism. Specifically, they describe the genetic and environmental alterations that affect neurodevelopment. The authors also highlight the resultant microstructural, macrostructural, and functional abnormalities that emerge during brain development, which create a pattern of dysfunctional neural networks involved in socioemotional processing. They then discuss how these findings implicate the BLA as a key node in the pathophysiology of autism and review a reported case of BLA DBS for treatment of severe autism. Much progress has been made in recent years in understanding the pathophysiology of autism. The BLA represents a logical neurosurgical target for treating severe autism. Further study is needed that considers mechanistic and operative challenges.

Technology concept in the view of Iranian nurses.

PubMed

Mehraban, Marzieh Adel; Hassanpour, Marzieh; Yazdannik, Ahmadreza; Ajami, Sima

2013-05-01

Over the years, the concept technology has modified, especially from the viewpoint of the development of scientific knowledge as well as the philosophical and artistic aspects. However, the concept of technology in nursing are still poorly understood. Only small qualitative studies, especially in Iran, have investigated this phenomenon and they just are about information technology. The aim of this study is to gain a better understanding of the concept of technology in the view of Iranian nurses. This study was qualitative explorative study which was done with a purposeful sampling of 23 nurses (staffs, supervisors and chief nurse managers) working in Isfahan hospitals. Unstructured interviews were including 13 individual interviews and 2 focused-group interviews. In addition to this, filed notes and memos were used in data collection. After this data transcribing was done and then conventional content analysis was used for data coding and classification. The results showed that there are various definitions for technology among nurses. In the view of nurses, technology means using new equipment, computers, information technology, etc). Data analysis revealed that nurses understand technology up to three main concepts: Change, Equipment and Knowledge. In deep overview on categories, we found that the most important concept about technology in nursing perspective is equipment. Therefore, it is necessary to develop deep understanding about the possible concepts technology among nurses. We suppose that technology concepts must be defined separately in all disciplines.

Deep-sea piezosphere and piezophiles: geomicrobiology and biogeochemistry.

PubMed

Fang, Jiasong; Zhang, Li; Bazylinski, Dennis A

2010-09-01

The deep-sea piezosphere accounts for approximately 75% of the total ocean volume and hosts active and diverse biological communities. Evidence obtained thus far suggests that the microbial biomass present in the piezosphere is significant. Continued international interest in exploring the deep ocean provides impetus to increase our understanding of the deep-sea piezosphere and of the influence of piezophilic microbial communities on the global ocean environment and on biogeochemical cycling occurring in the deep sea. Here, we review the diversity, metabolic characteristics, geomicrobiology and biogeochemistry of the deep-sea piezophiles. Copyright 2010 Elsevier Ltd. All rights reserved.

InSight Final Flight Installation of Heatshield

NASA Image and Video Library

2018-04-12

In the Astrotech facility at Vandenberg Air Force Base in California, technicians and engineers place the heatshield on NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander prior to encapsulation in its payload fairing. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

Liftoff of InSight

NASA Image and Video Library

2018-05-05

A United Launch Alliance Atlas V rocket lifts off at 4:05 a.m. PDT (7:05 a.m. EDT) from Space Launch Complex 3 at Vandenberg Air Force Base in California carrying NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created.

InSight Liftoff

NASA Image and Video Library

2018-05-05

A United Launch Alliance Atlas V rocket lifts off from Space Launch Complex 3 at Vandenberg Air Force Base, California, carrying NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander. Liftoff was at 4:05 a.m. PDT (7:05 a.m. EDT). The spacecraft will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. InSight will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created.

InSight Rollout to Pad

NASA Image and Video Library

2018-04-23

At Space Launch Complex 3 at Vandenberg Air Force Base in California, NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander is positioned atop a United Launch Alliance Atlas V rocket. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Liftoff

NASA Image and Video Library

2018-05-05

A United Launch Alliance Atlas V rocket lifts off from Space Launch Complex 3 at Vandenberg Air Force Base, California, carrying NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander. Liftoff was at 4:05 a.m. PDT (7:05 a.m. EDT). The spacecraft will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. InSight will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created.

InSight Lift & Mate

NASA Image and Video Library

2018-04-23

At Space Launch Complex 3 at Vandenberg Air Force Base in California, technicians and engineers position NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander atop a United Launch Alliance Atlas V rocket. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Rollout to Pad

NASA Image and Video Library

2018-04-23

At Space Launch Complex 3 at Vandenberg Air Force Base in California, technicians and engineers position NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander atop a United Launch Alliance Atlas V rocket. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Rollout to Pad

NASA Image and Video Library

2018-04-23

At Space Launch Complex 3 at Vandenberg Air Force Base in California, NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander has been mated atop a United Launch Alliance Atlas V rocket. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Rollout to Pad

NASA Image and Video Library

2018-04-23

At Space l Launch Complex 3 at Vandenberg Air Force Base in California, a crane is used to lift NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander for mating atop a United Launch Alliance Atlas V rocket. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Rollout to Pad

NASA Image and Video Library

2018-04-23

At Space Launch Complex 3 at Vandenberg Air Force Base in California, a crane is used to lift NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander for mating atop a United Launch Alliance Atlas V rocket. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Lift & Mate

NASA Image and Video Library

2018-04-23

At Space Launch Complex 3 at Vandenberg Air Force Base in California, a crane is used to lift NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander for mating atop a United Launch Alliance Atlas V rocket. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Battery Installation

NASA Image and Video Library

2018-04-20

In the gantry at Space Launch Complex 3 at Vandenberg Air Force Base in California, technicians and engineers prepare batteries for installation in NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

The Opportunity in Commercial Approaches for Future NASA Deep Space Exploration Elements

NASA Technical Reports Server (NTRS)

Zapata, Edgar

2017-01-01

In 2011, NASA released a report assessing the market for commercial crew and cargo services to low Earth orbit (LEO). The report stated that NASA had spent a few hundred million dollars in the Commercial Orbital Transportation Services (COTS) program on the portion related to the development of the Falcon 9 launch vehicle. Yet a NASA cost model predicted the cost would have been significantly more with a non-commercial cost-plus contracting approach. By 2016 a NASA request for information stated it must "maximize the efficiency and sustainability of the Exploration Systems development programs", as "critical to free resources for reinvestment...such as other required deep space exploration capabilities." This work joins the previous two events, showing the potential for commercial, public private partnerships, modeled on programs like COTS, to reduce the cost to NASA significantly for "...other required deep space exploration capabilities." These other capabilities include landers, stages and more. We mature the concept of "costed baseball cards", adding cost estimates to NASA's space systems "baseball cards." We show some potential costs, including analysis, the basis of estimates, data sources and caveats to address a critical question - based on initial assessment, are significant agency resources justified for more detailed analysis and due diligence to understand and invest in public private partnerships for human deep space exploration systems? The cost analysis spans commercial to cost-plus contracting approaches, for smaller elements vs. larger, with some variation for lunar or Mars. By extension, we delve briefly into the potentially much broader significance of the individual cost estimates if taken together as a NASA investment portfolio where public private partnership are stitched together for deep space exploration. How might multiple improvements in individual systems add up to NASA human deep space exploration achievements, realistically, affordably, sustainably, in a relevant timeframe?

Developing bioproxies of past ocean ecosystem change through compound-specific stable isotope analysis of proteinaceous deep-sea corals.

NASA Astrophysics Data System (ADS)

McMahon, K.; Williams, B.; Mccarthy, M. D.; Etnoyer, P. J.

2015-12-01

Our understanding of current and future ocean conditions is framed by our ability to reconstruct past changes in ecosystem structure and function recorded in paleoarchives. One such archive, proteinaceous deep-sea corals, act as "living sediment traps" with the potential to greatly improve our ability to reconstruct long-term, high-resolution biogeochemical records of export production. Compound-specific stable isotope analysis (CSIA) of individual amino acids (AAs) in deep-sea corals has provided highly detailed new tools to reconstruct changes in both plankton community composition and sources of nitrogen. However, to realize the full potential of CSIA in deep-sea corals, it is critical to better understand the link between the biogeochemical signatures of deep-sea coral polyp tissue and diagenetically resistant proteinaceous skeletal material. We conducted the first detailed comparison of δ13C and δ15N values for individual AAs between tissue and skeleton for three deep-sea coral genera (Primnoa, Isidella, and Kulamanamana). For δ13C values, we found minimal offsets in both essential and non-essential AAs across genera, strongly supporting coral skeleton AA fingerprinting as a new tool to reconstruct plankton community structure. Similarly, there was no significant offset in source AA δ15N values between tissue and skeleton, supporting the use of Phe δ15N as a proxy for baseline nitrogen sources. However, and rather unexpectedly, we found that the d15N values of the trophic AA group were consistently 3-4‰ lighter in skeleton than polyp tissue for all three genera. We hypothesize that this may reflect a partitioning of either N flux or pathways associated with AA transamination between polyp and skeleton tissues. This offset leads to an underestimate of trophic position using current CSIA-based calculations. Overall, our work strongly supports the applicability of CSIA in proteinaceous deep-sea corals to reconstruct past changes in biogeochemical cycling and plankton community dynamics. However, it also indicates that a new correction factor will be required to reconstruct accurate records of change in plankton trophic structure.

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…

The Process of Thinking among Junior High School Students in Solving HOTS Question

ERIC Educational Resources Information Center

Bakry, Md Nor Bin Bakar

2015-01-01

Higher order thinking skills (HOTS) is one of the important aspect of teaching and learning mathematics. By using HOTS, student will be able to acquire a deep understand of mathematical concepts and can be applied in real life. Students ability to develop the capacity of the HOTS is closely related with thinking processes while solving mathematics…

Exploring the Hidden Structure of Astronomical Images: A "Pixelated" View of Solar System and Deep Space Features!

ERIC Educational Resources Information Center

Ward, R. Bruce; Sienkiewicz, Frank; Sadler, Philip; Antonucci, Paul; Miller, Jaimie

2013-01-01

We describe activities created to help student participants in Project ITEAMS (Innovative Technology-Enabled Astronomy for Middle Schools) develop a deeper understanding of picture elements (pixels), image creation, and analysis of the recorded data. ITEAMS is an out-of-school time (OST) program funded by the National Science Foundation (NSF) with…

Math Strategies You Can Count On: Tools & Activities to Build Math Appreciation, Understanding & Skills

ERIC Educational Resources Information Center

Forsten, Char

2005-01-01

This book offers classroom-tested activities designed to make even the most reluctant learners crazy about math. Appealing to everyone from sports fans to readers, future fashion designers to budding musicians, the activities presented in this book offer ways to develop a deep-rooted love and appreciation of math in every student. Teachers are…

Adolescents' TV Viewing Patterns in the Digital Era: A Cross-Cultural Study

ERIC Educational Resources Information Center

Ugalde, Leire; Martínez-de-Morentin, Juan-Ignacio; María-Concepción Medrano

2017-01-01

The deep-rooted changes that have taken place in the media world over recent years have brought about changes in both television itself and in the relationships established with this medium. Consequently, it is important to understand how young people watch television today, in order to design strategies to help them develop the capacities they…

Understanding Randomness and Its Impact on Student Learning: Lessons Learned from Building the Biology Concept Inventory (BCI)

ERIC Educational Resources Information Center

Garvin-Doxas, Kathy; Klymkowsky, Michael W.

2008-01-01

While researching student assumptions for the development of the Biology Concept Inventory (BCI; http://bioliteracy.net), we found that a wide class of student difficulties in molecular and evolutionary biology appears to be based on deep-seated, and often unaddressed, misconceptions about random processes. Data were based on more than 500…

Environmental Systems Microbiology of Contaminated Environments

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

Sayler, Gary; Hazen, Terry C.

Environmental Systems Microbiology is well positioned to move forward in dynamic complex system analysis probing new questions and developing new insight into the function, robustness and resilience in response to anthropogenic perturbations. Recent studies have demonstrated that natural bacterial communities can be used as quantitative biosensors in both groundwater and deep ocean water, predicting oil concentration from the Gulf of Mexico Deep Water Horizon spill and from groundwater at nuclear production waste sites (16, 17, 25). Since the first demonstration of catabolic gene expression in soil remediation (34) it has been clear that extension beyond organismal abundance to process andmore » function of microbial communities as a whole using the whole suite of omic tools available to the post genomic era. Metatranscriptomics have been highlighted as a prime vehicle for understanding responses to environmental drivers (35) in complex systems and with rapidly developing metabolomics, full functional understanding of complex community biogeochemical cycling is an achievable goal. Perhaps more exciting is the dynamic nature of these systems and their complex adaptive strategies that may lead to new control paradigms and emergence of new states and function in the course of a changing environment.« less

Developing a Fault Management Guidebook for Nasa's Deep Space Robotic Missions

NASA Technical Reports Server (NTRS)

Fesq, Lorraine M.; Jacome, Raquel Weitl

2015-01-01

NASA designs and builds systems that achieve incredibly ambitious goals, as evidenced by the Curiosity rover traversing on Mars, the highly complex International Space Station orbiting our Earth, and the compelling plans for capturing, retrieving and redirecting an asteroid into a lunar orbit to create a nearby a target to be investigated by astronauts. In order to accomplish these feats, the missions must be imbued with sufficient knowledge and capability not only to realize the goals, but also to identify and respond to off-nominal conditions. Fault Management (FM) is the discipline of establishing how a system will respond to preserve its ability to function even in the presence of faults. In 2012, NASA released a draft FM Handbook in an attempt to coalesce the field by establishing a unified terminology and a common process for designing FM mechanisms. However, FM approaches are very diverse across NASA, especially between the different mission types such as Earth orbiters, launch vehicles, deep space robotic vehicles and human spaceflight missions, and the authors were challenged to capture and represent all of these views. The authors recognized that a necessary precursor step is for each sub-community to codify its FM policies, practices and approaches in individual, focused guidebooks. Then, the sub-communities can look across NASA to better understand the different ways off-nominal conditions are addressed, and to seek commonality or at least an understanding of the multitude of FM approaches. This paper describes the development of the "Deep Space Robotic Fault Management Guidebook," which is intended to be the first of NASA's FM guidebooks. Its purpose is to be a field-guide for FM practitioners working on deep space robotic missions, as well as a planning tool for project managers. Publication of this Deep Space Robotic FM Guidebook is expected in early 2015. The guidebook will be posted on NASA's Engineering Network on the FM Community of Practice website so that it will be available to all NASA projects. Future plans for subsequent guidebooks for the other NASA sub-communities are proposed.

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network.

PubMed

Katzman, Jared L; Shaham, Uri; Cloninger, Alexander; Bates, Jonathan; Jiang, Tingting; Kluger, Yuval

2018-02-26

Medical practitioners use survival models to explore and understand the relationships between patients' covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear Cox proportional hazards model require extensive feature engineering or prior medical knowledge to model treatment interaction at an individual level. While nonlinear survival methods, such as neural networks and survival forests, can inherently model these high-level interaction terms, they have yet to be shown as effective treatment recommender systems. We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's covariates and treatment effectiveness in order to provide personalized treatment recommendations. We perform a number of experiments training DeepSurv on simulated and real survival data. We demonstrate that DeepSurv performs as well as or better than other state-of-the-art survival models and validate that DeepSurv successfully models increasingly complex relationships between a patient's covariates and their risk of failure. We then show how DeepSurv models the relationship between a patient's features and effectiveness of different treatment options to show how DeepSurv can be used to provide individual treatment recommendations. Finally, we train DeepSurv on real clinical studies to demonstrate how it's personalized treatment recommendations would increase the survival time of a set of patients. The predictive and modeling capabilities of DeepSurv will enable medical researchers to use deep neural networks as a tool in their exploration, understanding, and prediction of the effects of a patient's characteristics on their risk of failure.

Developing convolutional neural networks for measuring climate change opinions from social media data

NASA Astrophysics Data System (ADS)

Mao, H.; Bhaduri, B. L.

2016-12-01

Understanding public opinions on climate change is important for policy making. Public opinion, however, is typically measured with national surveys, which are often too expensive and thus being updated at a low frequency. Twitter has become a major platform for people to express their opinions on social and political issues. Our work attempts to understand if Twitter data can provide complimentary insights about climate change perceptions. Since the nature of social media is real-time, this data source can especially help us understand how public opinion changes over time in response to climate events and hazards, which though is very difficult to be captured by manual surveys. We use the Twitter Streaming API to collect tweets that contain keywords, "climate change" or "#climatechange". Traditional machine-learning based opinion mining algorithms require a significant amount of labeled data. Data labeling is notoriously time consuming. To address this problem, we use hashtags (a significant feature used to mark topics of tweets) to annotate tweets automatically. For example, hashtags, #climatedenial and #climatescam, are negative opinion labels, while #actonclimate and #climateaction are positive. Following this method, we can obtain a large amount of training data without human labor. This labeled dataset is used to train a deep convolutional neural network that classifies tweets into positive (i.e. believe in climate change) and negative (i.e. do not believe). Based on the positive/negative tweets obtained, we will further analyze risk perceptions and opinions towards policy support. In addition, we analyze twitter user profiles to understand the demographics of proponents and opponents of climate change. Deep learning techniques, especially convolutional deep neural networks, have achieved much success in computer vision. In this work, we propose a convolutional neural network architecture for understanding opinions within text. This method is compared with lexicon-based opinion analysis approaches. Results and the advantages/limitations of this method are to be discussed.

Digging Deep: Exploring College Students' Knowledge of Macroevolutionary Time

ERIC Educational Resources Information Center

Catley, Kefyn M.; Novick, Laura R.

2009-01-01

Some ability to comprehend deep time is a prerequisite for understanding macroevolution. This study examines students' knowledge of deep time in the context of seven major historical and evolutionary events (e.g., the age of the Earth, the emergence of life, the appearance of a pre-modern human, "Homo habilis"). The subjects were 126…

Method to Identify Deep Cases Based on Relationships between Nouns, Verbs, and Particles

ERIC Educational Resources Information Center

Ide, Daisuke; Kimura, Masaomi

2016-01-01

Deep cases representing the significant meaning of nouns in sentences play a crucial role in semantic analysis. However, a case tends to be manually identified because it requires understanding the meaning and relationships of words. To address this problem, we propose a method to predict deep cases by analyzing the relationship between nouns,…

Recent advances and state-of-the-art strategies in strain and process engineering for biobutanol production by Clostridium acetobutylicum.

PubMed

Xue, Chuang; Zhao, Jingbo; Chen, Lijie; Yang, Shang-Tian; Bai, Fengwu

Butanol as an advanced biofuel has gained great attention due to its environmental benefits and superior properties compared to ethanol. However, the cost of biobutanol production via conventional acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum is not economically competitive, which has hampered its industrial application. The strain performance and downstream process greatly impact the economics of biobutanol production. Although various engineered strains with carefully orchestrated metabolic and sporulation-specific pathways have been developed, none of them is ideal for industrial biobutanol production. For further strain improvement, it is necessary to develop advanced genome editing tools and a deep understanding of cellular functioning of genes in metabolic and regulatory pathways. Processes with integrated product recovery can increase fermentation productivity by continuously removing inhibitory products while generating butanol (ABE) in a concentrated solution. In this review, we provide an overview of recent advances in C. acetobutylicum strain engineering and process development focusing on in situ product recovery. With deep understanding of systematic cellular bioinformatics, the exploration of state-of-the-art genome editing tools such as CRISPR-Cas for targeted gene knock-out and knock-in would play a vital role in Clostridium cell engineering for biobutanol production. Developing advanced hybrid separation processes for in situ butanol recovery, which will be discussed with a detailed comparison of advantages and disadvantages of various recovery techniques, is also imperative to the economical development of biobutanol. Copyright © 2017 Elsevier Inc. All rights reserved.

Standardization of deep partial-thickness scald burns in C57BL/6 mice

PubMed Central

Medina, Jorge L; Fourcaudot, Andrea B; Sebastian, Eliza A; Shankar, Ravi; Brown, Ammon W; Leung, Kai P

2018-01-01

Mouse burn models are used to understand the wound healing process and having a reproducible model is important. The different protocols used by researchers can lead to differences in depth of partial-thickness burn wounds. Additionally, standardizing a protocol for mouse burns in the laboratory for one strain may result in substantially different results in other strains. In our current study we describe the model development of a deep partial-thickness burn in C57BL/6 mice using hot water scalding as the source of thermal injury. As part of our model development we designed a template with specifications to allow for even contact of bare mouse skin (2×3 cm) with hot water while protecting the rest of the mouse. Burn depth was evaluated with H&E, Masson’s trichrome, and TUNEL staining. Final results were validated with pathology analysis. A water temperature of 54°C with a scalding time of 20 seconds produced consistent deep partial-thickness burns with available equipment described. Other than temperature and time, factors such as template materials and cooling steps after the burn could affect the uniformity of the burns. These findings are useful to burn research by providing some key parameters essential for researchers to simplify the development of their own mouse burn models. PMID:29755839

Refined Three-Dimensional Modelling of Thermally-Driven Flow in the Bormio System (Central Italian Alps)

NASA Astrophysics Data System (ADS)

Volpi, Giorgio; Riva, Federico; Frattini, Paolo; Battista Crosta, Giovanni; Magri, Fabien

2016-04-01

Thermal springs are widespread in the European Alps, where more than 80 geothermal sites are known and exploited. The quantitative assessment of those thermal flow systems is a challenging issue and requires accurate conceptual model and a thorough understanding of thermo-hydraulic properties of the aquifers. Accordingly in the last years, several qualitative studies were carried out to understand the heat and fluid transport processes driving deep fluids from the reservoir to the springs. Our work focused on thermal circulation and fluid outflows of the area around Bormio (Central Italian Alps), where nine geothermal springs discharge from dolomite bodies located close to a regional alpine thrust, called the Zebrù Line. At this site, water is heated in deep circulation systems and vigorously upwells at temperature of about 40°C. The aim of this paper is to explore the mechanisms of heat and fluid transport in the Bormio area by carrying out refined steady and transient three-dimensional finite element simulations of thermally-driven flow and to quantitatively assess the source area of the thermal waters. The full regional model (ca. 700 km2) is discretized with a highly refined triangular finite element planar grid obtained with Midas GTS NX software. The structural 3D features of the regional Zebrù thrust are built by interpolating series of geological cross sections using Fracman. A script was developed to convert and implement the thrust grid into FEFLOW mesh that comprises ca. 4 million elements. The numerical results support the observed discharge rates and temperature field within the simulated domain. Flow and temperature patterns suggest that thermal groundwater flows through a deep system crossing both sedimentary and metamorphic lithotypes, and a fracture network associated to the thrust system. Besides providing a numerical framework to simulate complex fractured systems, this example gives insights into the influence of deep alpine structures on groundwater circulation that underlies the development of many hydrothermal systems.

Automated Generation of Geo-Referenced Mosaics From Video Data Collected by Deep-Submergence Vehicles: Preliminary Results

NASA Astrophysics Data System (ADS)

Rhzanov, Y.; Beaulieu, S.; Soule, S. A.; Shank, T.; Fornari, D.; Mayer, L. A.

2005-12-01

Many advances in understanding geologic, tectonic, biologic, and sedimentologic processes in the deep ocean are facilitated by direct observation of the seafloor. However, making such observations is both difficult and expensive. Optical systems (e.g., video, still camera, or direct observation) will always be constrained by the severe attenuation of light in the deep ocean, limiting the field of view to distances that are typically less than 10 meters. Acoustic systems can 'see' much larger areas, but at the cost of spatial resolution. Ultimately, scientists want to study and observe deep-sea processes in the same way we do land-based phenomena so that the spatial distribution and juxtaposition of processes and features can be resolved. We have begun development of algorithms that will, in near real-time, generate mosaics from video collected by deep-submergence vehicles. Mosaics consist of >>10 video frames and can cover 100's of square-meters. This work builds on a publicly available still and video mosaicking software package developed by Rzhanov and Mayer. Here we present the results of initial tests of data collection methodologies (e.g., transects across the seafloor and panoramas across features of interest), algorithm application, and GIS integration conducted during a recent cruise to the Eastern Galapagos Spreading Center (0 deg N, 86 deg W). We have developed a GIS database for the region that will act as a means to access and display mosaics within a geospatially-referenced framework. We have constructed numerous mosaics using both video and still imagery and assessed the quality of the mosaics (including registration errors) under different lighting conditions and with different navigation procedures. We have begun to develop algorithms for efficient and timely mosaicking of collected video as well as integration with navigation data for georeferencing the mosaics. Initial results indicate that operators must be properly versed in the control of the video systems as well as maintaining vehicle attitude and altitude in order to achieve the best results possible.

Deep electrode insertion and sound coding in cochlear implants.

PubMed

Hochmair, Ingeborg; Hochmair, Erwin; Nopp, Peter; Waller, Melissa; Jolly, Claude

2015-04-01

Present-day cochlear implants demonstrate remarkable speech understanding performance despite the use of non-optimized coding strategies concerning the transmission of tonal information. Most systems rely on place pitch information despite possibly large deviations from correct tonotopic placement of stimulation sites. Low frequency information is limited as well because of the constant pulse rate stimulation generally used and, being even more restrictive, of the limited insertion depth of the electrodes. This results in a compromised perception of music and tonal languages. Newly available flexible long straight electrodes permit deep insertion reaching the apical region with little or no insertion trauma. This article discusses the potential benefits of deep insertion which are obtained using pitch-locked temporal stimulation patterns. Besides the access to low frequency information, further advantages of deeply inserted long electrodes are the possibility to better approximate the correct tonotopic location of contacts, the coverage of a wider range of cochlear locations, and the somewhat reduced channel interaction due to the wider contact separation for a given number of channels. A newly developed set of strategies has been shown to improve speech understanding in noise and to enhance sound quality by providing a more "natural" impression, which especially becomes obvious when listening to music. The benefits of deep insertion should not, however, be compromised by structural damage during insertion. The small cross section and the high flexibility of the new electrodes can help to ensure less traumatic insertions as demonstrated by patients' hearing preservation rate. This article is part of a Special Issue entitled . Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Developing anti-tobacco messages for Australian Aboriginal and Torres Strait Islander peoples: evidence from a national cross-sectional survey.

PubMed

Gould, Gillian S; Watt, Kerrianne; Stevenson, Leah; McEwen, Andy; Cadet-James, Yvonne; Clough, Alan R

2014-03-13

Smoking rates in Australian Aboriginal and Torres Strait Islander peoples remain high, with limited impact of government measures for many subgroups. The aim of this cross-sectional study was to investigate differences in organisational practice for developing anti-tobacco messages for these target populations. Telephone interviews were conducted with 47 organisation representatives using a structured questionnaire based on health communication and health promotion frameworks. Responses were coded into phases of message development, message types (educational, threat, positive or advocacy), target groups, message recommendations, and evaluations undertaken. Cultural sensitivity for message development was divided into surface structure (use of images, language, demographics) and deep structure (use of socio-cultural values). A categorical principal component analysis explored the key dimensions of the findings and their component relationships. Among organisations interviewed, a community-orientated, bottom-up approach for developing anti-tobacco messages was reported by 47% (n=24); 55% based message development on a theoretical framework; 87% used a positive benefit appeal; 38% used threat messages. More Aboriginal Medical Services (AMSs) targeted youth (p<0.005) and advised smokers to quit (p<0.05) than other types of organisations. AMSs were significantly more likely to report using deep structure in tailoring messages compared with non-government (p<0.05) and government organisations (p<0.05). Organisations that were oriented to the general population were more likely to evaluate their programs (p<0.05). A two-dimensional non-linear principal component analysis extracted components interpreted as "cultural understanding" (bottom-up, community-based approaches, deep structures) and "rigour" (theoretical frameworks, and planned/completed evaluations), and accounted for 53% of the variability in the data. Message features, associated with successful campaigns in other populations, are starting to be used for Aboriginal and Torres Strait Islander peoples. A model is proposed to facilitate the development of targeted anti-tobacco messages for Aboriginal and Torres Strait Islander peoples. Organisations could consider incorporating both components of cultural understanding-rigour to enable the growth of evidence-based practice.

Using Computer Technology to Foster Learning for Understanding

PubMed Central

VAN MELLE, ELAINE; TOMALTY, LEWIS

2000-01-01

The literature shows that students typically use either a surface approach to learning, in which the emphasis is on memorization of facts, or a deep approach to learning, in which learning for understanding is the primary focus. This paper describes how computer technology, specifically the use of a multimedia CD-ROM, was integrated into a microbiology curriculum as part of the transition from focusing on facts to fostering learning for understanding. Evaluation of the changes in approaches to learning over the course of the term showed a statistically significant shift in a deep approach to learning, as measured by the Study Process Questionnaire. Additional data collected showed that the use of computer technology supported this shift by providing students with the opportunity to apply what they had learned in class to order tests and interpret the test results in relation to specific patient-focused case studies. The extent of the impact, however, varied among different groups of students in the class. For example, students who were recent high school graduates did not show a statistically significant increase in deep learning scores over the course of the term and did not perform as well in the course. The results also showed that a surface approach to learning was an important aspect of learning for understanding, although only those students who were able to combine a surface with a deep approach to learning were successfully able to learn for understanding. Implications of this finding for the future use of computer technology and learning for understanding are considered. PMID:23653533

Challenges and Solutions for the Integration of Structural and Hydrogeological Understanding of Fracture Systems - Insights from the Olkiluoto Site, Finland

NASA Astrophysics Data System (ADS)

Hartley, L. J.; Aaltonen, I.; Baxter, S. J.; Cottrell, M.; Fox, A. L.; Hoek, J.; Koskinen, L.; Mattila, J.; Mosley, K.; Selroos, J. O.; Suikkanen, J.; Vanhanarkaus, O.; Williams, T. R. N.

2017-12-01

A field site at Olkiluoto in SW Finland has undergone extensive investigations as a location for a deep geological repository for spent nuclear fuel, which is expected to become operational in the early 2020s. Characterisation data comes from 58 deep cored drillholes, a wide variety of geophysical investigations, many outcrops, kilometres of underground mapping and testing in the ONKALO research facility, and groundwater pressure monitoring and sampling in both deep and shallow holes. A primary focus is on the properties of natural fractures and brittle fault zones in the low permeability crystalline rocks at Olkiluoto; an understanding of the flow and transport processes in these features are an essential part of assessing long-term safety of the repository. This presentation will illustrate how different types of source data and cross-disciplinary interpretations are integrated to develop conceptual and numerical models of the fracture system. A model of the brittle fault zones developed from geological and geophysical data provides the hydrostructural backbone controlling the most intense fracturing and dynamic conduits for fluids. Models of ductile deformation and lithology form a tectonic framework for the description of fracture heterogeneity in the background rock, revealing correlations between the intensity and orientation of fractures with geological and spatial properties. The sizes of brittle features are found to be best defined on two scales relating to individual fractures and zones. Inferred fracture-specific from flow logging are correlated with fracture geometric and mechanical properties along with in situ stress measurements to create a hydromechanical description of fracture hydraulic properties. The insights and understandings gained from these efforts help define a discrete fracture network (DFN) model for the Olkiluoto site, with hydrogeological characteristics consistent with monitoring data of hydraulic heads and their disturbances to pumping and underground construction. This work offers ideas and proposed solutions on how some of the challenges in describing fractured rock hydrogeology can be tackled.

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…

The Use of Deep Learning Strategies in Online Business Courses to Impact Student Retention

ERIC Educational Resources Information Center

DeLotell, Pam Jones; Millam, Loretta A.; Reinhardt, Michelle M.

2010-01-01

Interest, application and understanding--these are key elements in successful online classroom experiences and all part of what is commonly referred to as deep learning. Deep learning occurs when students are able to connect with course topics, find value in them and see how to apply them to real-world situations. Asynchronous discussion forums in…

InSight Spacecraft Lift to Spin Table & Pre-Spin Processing

NASA Image and Video Library

2018-03-28

In the Astrotech facility at Vandenberg Air Force Base in California, technicians and engineers inspect NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, spacecraft after it was placed on a spin table during preflight processing. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

InSight Lift/Mate to PLA with SC to GTV

NASA Image and Video Library

2018-04-11

In the Astrotech facility at Vandenberg Air Force Base in California, technicians and engineers monitor progress as NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander is prepared for encapsulation in its payload fairing. InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. The spacecraft will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created. InSight is scheduled for liftoff May 5, 2018.

Launch and Commissioning of the Deep Space Climate Observatory

NASA Technical Reports Server (NTRS)

Frey, Nicholas P.; Davis, Edward P.

2016-01-01

The Deep Space Climate Observatory (DSCOVR), formerly known as Triana, successfully launched on February 11th, 2015. To date, each of the five space-craft attitude control system (ACS) modes have been operating as expected and meeting all guidance, navigation, and control (GN&C) requirements, although since launch, several anomalies were encountered. While unplanned, these anomalies have proven to be invaluable in developing a deeper understanding of the ACS, and drove the design of three alterations to the ACS task of the flight software (FSW). An overview of the GN&C subsystem hardware, including re-furbishment, and ACS architecture are introduced, followed by a chronological discussion of key events, flight performance, as well as anomalies encountered by the GN&C team.

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

A single evolutionary innovation drives the deep evolution of symbiotic N2-fixation in angiosperms

PubMed Central

Werner, Gijsbert D. A.; Cornwell, William K.; Sprent, Janet I.; Kattge, Jens; Kiers, E. Toby

2014-01-01

Symbiotic associations occur in every habitat on earth, but we know very little about their evolutionary histories. Current models of trait evolution cannot adequately reconstruct the deep history of symbiotic innovation, because they assume homogenous evolutionary processes across millions of years. Here we use a recently developed, heterogeneous and quantitative phylogenetic framework to study the origin of the symbiosis between angiosperms and nitrogen-fixing (N2) bacterial symbionts housed in nodules. We compile the largest database of global nodulating plant species and reconstruct the symbiosis’ evolution. We identify a single, cryptic evolutionary innovation driving symbiotic N2-fixation evolution, followed by multiple gains and losses of the symbiosis, and the subsequent emergence of ‘stable fixers’ (clades extremely unlikely to lose the symbiosis). Originating over 100 MYA, this innovation suggests deep homology in symbiotic N2-fixation. Identifying cryptic innovations on the tree of life is key to understanding the evolution of complex traits, including symbiotic partnerships. PMID:24912610

Extreme Longevity in Proteinaceous Deep-Sea Corals

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

Roark, E B; Guilderson, T P; Dunbar, R B

2009-02-09

Deep-sea corals are found on hard substrates on seamounts and continental margins world-wide at depths of 300 to {approx}3000 meters. Deep-sea coral communities are hotspots of deep ocean biomass and biodiversity, providing critical habitat for fish and invertebrates. Newly applied radiocarbon age date from the deep water proteinaceous corals Gerardia sp. and Leiopathes glaberrima show that radial growth rates are as low as 4 to 35 {micro}m yr{sup -1} and that individual colony longevities are on the order of thousands of years. The management and conservation of deep sea coral communities is challenged by their commercial harvest for the jewelrymore » trade and damage caused by deep water fishing practices. In light of their unusual longevity, a better understanding of deep sea coral ecology and their interrelationships with associated benthic communities is needed to inform coherent international conservation strategies for these important deep-sea ecosystems.« less

Initial public perceptions of deep geological and oceanic disposal of carbon dioxide.

PubMed

Palmgren, Claire R; Morgan, M Granger; Bruine de Bruin, Wändi; Keith, David W

2004-12-15

Two studies were conducted to gauge likely public perceptions of proposals to avoid releasing carbon dioxide from power plants to the atmosphere by injecting it into deep geological formations or the deep ocean. Following a modified version of the mental model interview method, Study 1 involved face-to-face interviews with 18 nontechnical respondents. Respondents shared their beliefs after receiving basic information about the technologies and again after getting specific details. Many interviewees wanted to frame the issue in the broader context of alternative strategies for carbon management, but public understanding of mitigation strategies is limited. The second study, administered to a sample of 126 individuals, involved a closed-form survey that measured the prevalence of general beliefs revealed in study 1 and also assessed the respondent's views of these technologies. Study results suggest that the public may develop misgivings about deep injection of carbon dioxide because it can be seen as temporizing and perhaps creating future problems. Ocean injection was seen as more problematic than geological injection. An approach to public communication and regulation that is open and respectful of public concerns is likely to be a prerequisite to the successful adoption of this technology.

Increases in tropical rainfall driven by changes in frequency of organized deep convection.

PubMed

Tan, Jackson; Jakob, Christian; Rossow, William B; Tselioudis, George

2015-03-26

Increasing global precipitation has been associated with a warming climate resulting from a strengthening of the hydrological cycle. This increase, however, is not spatially uniform. Observations and models have found that changes in rainfall show patterns characterized as 'wet-gets-wetter' and 'warmer-gets-wetter'. These changes in precipitation are largely located in the tropics and hence are probably associated with convection. However, the underlying physical processes for the observed changes are not entirely clear. Here we show from observations that most of the regional increase in tropical precipitation is associated with changes in the frequency of organized deep convection. By assessing the contributions of various convective regimes to precipitation, we find that the spatial patterns of change in the frequency of organized deep convection are strongly correlated with observed change in rainfall, both positive and negative (correlation of 0.69), and can explain most of the patterns of increase in rainfall. In contrast, changes in less organized forms of deep convection or changes in precipitation within organized deep convection contribute less to changes in precipitation. Our results identify organized deep convection as the link between changes in rainfall and in the dynamics of the tropical atmosphere, thus providing a framework for obtaining a better understanding of changes in rainfall. Given the lack of a distinction between the different degrees of organization of convection in climate models, our results highlight an area of priority for future climate model development in order to achieve accurate rainfall projections in a warming climate.

Insights into Deep-Sea Sediment Fungal Communities from the East Indian Ocean Using Targeted Environmental Sequencing Combined with Traditional Cultivation

PubMed Central

Zhang, Xiao-yong; Tang, Gui-ling; Xu, Xin-ya; Nong, Xu-hua; Qi, Shu-Hua

2014-01-01

The fungal diversity in deep-sea environments has recently gained an increasing amount attention. Our knowledge and understanding of the true fungal diversity and the role it plays in deep-sea environments, however, is still limited. We investigated the fungal community structure in five sediments from a depth of ∼4000 m in the East India Ocean using a combination of targeted environmental sequencing and traditional cultivation. This approach resulted in the recovery of a total of 45 fungal operational taxonomic units (OTUs) and 20 culturable fungal phylotypes. This finding indicates that there is a great amount of fungal diversity in the deep-sea sediments collected in the East Indian Ocean. Three fungal OTUs and one culturable phylotype demonstrated high divergence (89%–97%) from the existing sequences in the GenBank. Moreover, 44.4% fungal OTUs and 30% culturable fungal phylotypes are new reports for deep-sea sediments. These results suggest that the deep-sea sediments from the East India Ocean can serve as habitats for new fungal communities compared with other deep-sea environments. In addition, different fungal community could be detected when using targeted environmental sequencing compared with traditional cultivation in this study, which suggests that a combination of targeted environmental sequencing and traditional cultivation will generate a more diverse fungal community in deep-sea environments than using either targeted environmental sequencing or traditional cultivation alone. This study is the first to report new insights into the fungal communities in deep-sea sediments from the East Indian Ocean, which increases our knowledge and understanding of the fungal diversity in deep-sea environments. PMID:25272044

Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma.

PubMed

Young, Jonathan D; Cai, Chunhui; Lu, Xinghua

2017-10-03

One approach to improving the personalized treatment of cancer is to understand the cellular signaling transduction pathways that cause cancer at the level of the individual patient. In this study, we used unsupervised deep learning to learn the hierarchical structure within cancer gene expression data. Deep learning is a group of machine learning algorithms that use multiple layers of hidden units to capture hierarchically related, alternative representations of the input data. We hypothesize that this hierarchical structure learned by deep learning will be related to the cellular signaling system. Robust deep learning model selection identified a network architecture that is biologically plausible. Our model selection results indicated that the 1st hidden layer of our deep learning model should contain about 1300 hidden units to most effectively capture the covariance structure of the input data. This agrees with the estimated number of human transcription factors, which is approximately 1400. This result lends support to our hypothesis that the 1st hidden layer of a deep learning model trained on gene expression data may represent signals related to transcription factor activation. Using the 3rd hidden layer representation of each tumor as learned by our unsupervised deep learning model, we performed consensus clustering on all tumor samples-leading to the discovery of clusters of glioblastoma multiforme with differential survival. One of these clusters contained all of the glioblastoma samples with G-CIMP, a known methylation phenotype driven by the IDH1 mutation and associated with favorable prognosis, suggesting that the hidden units in the 3rd hidden layer representations captured a methylation signal without explicitly using methylation data as input. We also found differentially expressed genes and well-known mutations (NF1, IDH1, EGFR) that were uniquely correlated with each of these clusters. Exploring these unique genes and mutations will allow us to further investigate the disease mechanisms underlying each of these clusters. In summary, we show that a deep learning model can be trained to represent biologically and clinically meaningful abstractions of cancer gene expression data. Understanding what additional relationships these hidden layer abstractions have with the cancer cellular signaling system could have a significant impact on the understanding and treatment of cancer.

Combustion and NOx emission characteristics with respect to staged-air damper opening in a 600 MWe down-fired pulverized-coal furnace under deep-air-staging conditions.

PubMed

Kuang, Min; Li, Zhengqi; Wang, Zhihua; Jing, Xinjing; Liu, Chunlong; Zhu, Qunyi; Ling, Zhongqian

2014-01-01

Deep-air-staging combustion conditions, widely used in tangential-fired and wall-arranged furnaces to significantly reduce NOx emissions, are premature up to now in down-fired furnaces that are designed especially for industry firing low-volatile coals such as anthracite and lean coal. To uncover combustion and NOx emission characteristics under deep-air-staging conditions within a newly operated 600 MWe down-fired furnace and simultaneously understand the staged-air effect on the furnace performance, full-load industrial-size measurements taken of gas temperatures and species concentrations in the furnace, CO and NOx emissions in flue gas, and carbon in fly ash were performed at various staged-air damper openings of 10%, 20%, 30%, and 50%. Increasing the staged-air damper opening, gas temperatures along the flame travel (before the flame penetrating the staged-air zone) increased initially but then decreased, while those in the staged-air zone and the upper part of the hopper continuously decreased and increased, respectively. On opening the staged-air damper to further deepen the air-staging conditions, O2 content initially decreased but then increased in both two near-wall regions affected by secondary air and staged air, respectively, whereas CO content in both two regions initially increased but then decreased. In contrast to the conventional understanding about the effects of deep-air-staging conditions, here increasing the staged-air damper opening to deepen the air-staging conditions essentially decreased the exhaust gas temperature and carbon in fly ash and simultaneously increased both NOx emissions and boiler efficiency. In light of apparently low NOx emissions and high carbon in fly ash (i.e., 696-878 mg/m(3) at 6% O2 and 9.81-13.05%, respectively) developing in the down-fired furnace under the present deep-air-staging conditions, further adjustments such as enlarging the staged-air declination angle to prolong pulverized-coal residence times in the furnace should be considered to improve the deep-air-staging combustion configuration.

Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Zulia Mayari; Papuga, Shirley Anne; Swetish, Jessica Blaine; van Leeuwen, Willem Jan Dirk; Szutu, Daphne; Hartfield, Kyle

2014-05-01

As changes in precipitation dynamics continue to alter the water availability in dryland ecosystems, understanding the feedbacks between the vegetation and the hydrologic cycle and their influence on the climate system is critically important. We designed a field campaign to examine the influence of two-layer soil moisture control on bare and canopy albedo dynamics in a semiarid shrubland ecosystem. We conducted this campaign during 2011 and 2012 within the tower footprint of the Santa Rita Creosote Ameriflux site. Albedo field measurements fell into one of four Cases within a two-layer soil moisture framework based on permutations of whether the shallow and deep soil layers were wet or dry. Using these Cases, we identified differences in how shallow and deep soil moisture influence canopy and bare albedo. Then, by varying the number of canopy and bare patches within a gridded framework, we explore the influence of vegetation and soil moisture on ecosystem albedo. Our results highlight the importance of deep soil moisture in land surface-atmosphere interactions through its influence on aboveground vegetation characteristics. For instance, we show how green-up of the vegetation is triggered by deep soil moisture, and link deep soil moisture to a decrease in canopy albedo. Understanding relationships between vegetation and deep soil moisture will provide important insights into feedbacks between the hydrologic cycle and the climate system.

Scandal and Tragedy Or Acquisition Lessons Relearned by the F-35 Program

DTIC Science & Technology

2017-01-01

Ribbon Commission on Defense Management , referred to as the Packard Commission Report, determined that MDAPs take too long to develop, cost too much...understanding program management discipline. Yin (1994) and Patton (2002) believed a deep-rooted and multilevel case study analysis could help formulate... management ), good recommendations come from open questions, often applying the researcher’s and SME’s own expe- riences, instead of from scientific

"Digging Deep": Self-Study as a Reflexive Approach to Improving My Practice as an Artist, Researcher and Teacher

ERIC Educational Resources Information Center

Scott, Lee

2014-01-01

In this article, I show how I enhanced my understanding of my practice as an artist, researcher and teacher using a self-study approach in my recently completed Master of Technology (M.Tech.) dissertation in Graphic Design. As part of my M.Tech. research, I conceptualised and developed a creative teaching tool that I named "PicTopics."…

Biopolitical science.

PubMed

Arnhart, Larry

2010-03-01

This article develops a theoretical framework for biopolitical science as a science of political animals. This science moves through three levels of deep political history: the universal political history of the species, the cultural political history of the group, and the individual political history of animals in the group. To illustrate the particular application of biopolitical science, this essay shows how this science would help us to understand Abraham Lincoln's Emancipation Proclamation of January 1, 1863.

Role of future scenarios in understanding deep uncertainty in ...

EPA Pesticide Factsheets

The environment and its interactions with human systems, whether economic, social or political, are complex. Relevant drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions. This kind of deep uncertainty presents a challenge to organizations faced with making decisions about the future, including those involved in air quality management. Scenario Planning is a structured process that involves the development of narratives describing alternative future states of the world, designed to differ with respect to the most critical and uncertain drivers. The resulting scenarios are then used to understand the consequences of those futures and to prepare for them with robust management strategies. We demonstrate a novel air quality management application of Scenario Planning. Through a series of workshops, important air quality drivers were identified. The most critical and uncertain drivers were found to be “technological development” and “change in societal paradigms.” These drivers were used as a basis to develop four distinct scenario storylines. The energy and emission implications of each storyline were then modeled using the MARKAL energy system model. NOX and SO2 emissions were found to decrease for all scenarios, largely a response to existing air quality regulations. Future-year emissions differed considerably from one scenario to another, however, with key differentiating factors being transition

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.

Role of future scenarios in understanding deep uncertainty in long-term air quality management.

PubMed

Gamas, Julia; Dodder, Rebecca; Loughlin, Dan; Gage, Cynthia

2015-11-01

The environment and its interactions with human systems, whether economic, social, or political, are complex. Relevant drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions. This kind of "deep uncertainty" presents a challenge to organizations faced with making decisions about the future, including those involved in air quality management. Scenario Planning is a structured process that involves the development of narratives describing alternative future states of the world, designed to differ with respect to the most critical and uncertain drivers. The resulting scenarios are then used to understand the consequences of those futures and to prepare for them with robust management strategies. We demonstrate a novel air quality management application of Scenario Planning. Through a series of workshops, important air quality drivers were identified. The most critical and uncertain drivers were found to be "technological development" and "change in societal paradigms." These drivers were used as a basis to develop four distinct scenario storylines. The energy and emissions implications of each storyline were then modeled using the MARKAL energy system model. NOx emissions were found to decrease for all scenarios, largely a response to existing air quality regulations, whereas SO2 emissions ranged from 12% greater to 7% lower than 2015 emissions levels. Future-year emissions differed considerably from one scenario to another, however, with key differentiating factors being transition to cleaner fuels and energy demand reductions. Application of scenarios in air quality management provides a structured means of sifting through and understanding the dynamics of the many complex driving forces affecting future air quality. Further, scenarios provide a means to identify opportunities and challenges for future air quality management, as well as a platform for testing the efficacy and robustness of particular management options across wide-ranging conditions.

A Non-Invasive Deep Tissue PH Monitor.

DTIC Science & Technology

1995-08-11

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

A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease.

PubMed

Ambastha, Abhinit Kumar; Leong, Tze-Yun

2017-01-01

Alzheimer's disease (AD) is a neurological degenerative disorder that leads to progressive mental deterioration. This work introduces a computational approach to improve our understanding of the progression of AD. We use ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD; this provides an understanding of how AD progresses in the brain. The proposed technique has a classification accuracy of 81.79% for AD against healthy subjects using a single modality imaging dataset.

Investigating the Relationship Between Fin and Blue Whale Locations, Zooplankton Concentrations and Hydrothermal Venting on the Juan de Fuca Ridge

DTIC Science & Technology

2009-09-30

Ridge. Our goal is to understand the influences of globally distributed hydrothermal plumes on the trophic ecology of the deep ocean. OBJECTIVES...to understand the influences of globally distributed hydrothermal plumes on the trophic ecology of the deep ocean. 15. SUBJECT TERMS 16. SECURITY... hydrothermal plume at 1.9 km depth [Burd et al., 1992; Thomson et al., 1991a], leading to the inference that the zooplankton were taking advantage of the

Planning for Crew Exercise for Deep Space Mission Scenarios

NASA Technical Reports Server (NTRS)

Moore, E. Cherice; Ryder, Jeff

2015-01-01

Exercise which is necessary for maintaining crew health on-orbit and preparing the crew for return to 1G can be challenging to incorporate into spaceflight vehicles. Deep space missions will require further understanding of the physiological response to microgravity, understanding appropriate mitigations, and designing the exercise systems to effectively provide mitigations, and integrating effectively into vehicle design with a focus to support planned mission scenarios. Recognizing and addressing the constraints and challenges can facilitate improved vehicle design and exercise system incorporation.

Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?

PubMed

Bini, Stefano A

2018-02-27

This article was presented at the 2017 annual meeting of the American Association of Hip and Knee Surgeons to introduce the members gathered as the audience to the concepts behind artificial intelligence (AI) and the applications that AI can have in the world of health care today. We discuss the origin of AI, progress to machine learning, and then discuss how the limits of machine learning lead data scientists to develop artificial neural networks and deep learning algorithms through biomimicry. We will place all these technologies in the context of practical clinical examples and show how AI can act as a tool to support and amplify human cognitive functions for physicians delivering care to increasingly complex patients. The aim of this article is to provide the reader with a basic understanding of the fundamentals of AI. Its purpose is to demystify this technology for practicing surgeons so they can better understand how and where to apply it. Copyright © 2018 Elsevier Inc. All rights reserved.

Flow in the Deep Mantle from Seisimc Anisotropy: Progress and Prospects

NASA Astrophysics Data System (ADS)

Long, M. D.

2017-12-01

Observations of seismic anisotropy, or the directional dependence of seismic wavespeeds, provide one some of the most direct constraints on the pattern of flow in the Earth's mantle. In particular, as our understanding of crystallographic preferred orientation (CPO) of olivine aggregates under a range of deformation conditions has improved, our ability to exploit observations of upper mantle anisotropy has led to fundamental discoveries about the patterns of flow in the upper mantle and the drivers of that flow. It has been a challenge, however, to develop a similar framework for understanding flow in the deep mantle (transition zone, uppermost lower mantle, and lowermost mantle), even though there is convincing observational evidence for seismic anisotropy at these depths. Recent progress on the observational front has allowed for an increasingly detailed view of mid-mantle anisotropy (transition zone and uppermost lower mantle), particularly in subduction systems, which may eventually lead to a better understanding of mid-mantle deformation and the dynamics of slab interaction with the surrounding mid-mantle. New approaches to the observation and modeling of lowermost mantle anisotropy, in combination with constraints from mineral physics, are progressing towards interpretive frameworks that allow for the discrimination of different mantle flow geometries in different regions of D". In particular, observational strategies that involve the use of multiple types of body wave phases sampled over a range of propagation azimuths enable detailed forward modeling approaches that can discriminate between different mechanisms for D" anisotropy (e.g., CPO of post-perovskite, bridgmanite, or ferropericlase, or shape preferred orientation of partial melt) and identify plausible anisotropic orientations. We have recently begun to move towards a full waveform modeling approach in this work, which allows for a more accurate simulation for seismic wave propagation. Ongoing improvements in seismic observational strategies, experimental and computational mineral physics, and geodynamic modeling approaches are leading to new avenues for understanding flow in the deep mantle through the study of seismic anisotropy.

The role of future scenarios to understand deep uncertainty

EPA Science Inventory

The environment and its interaction with human systems(economic, social and political) is complex and dynamic. Key drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents a challe...

Uptake and distribution of organo-iodine in deep-sea corals.

PubMed

Prouty, Nancy G; Roark, E Brendan; Mohon, Leslye M; Chang, Ching-Chih

2018-07-01

Understanding iodine concentration, transport, and bioavailability is essential in evaluating iodine's impact to the environment and its effectiveness as an environmental biogeotracer. While iodine and its radionuclides have proven to be important tracers in geologic and biologic studies, little is known about transport of this element to the deep sea and subsequent uptake in deep-sea coral habitats. Results presented here on deep-sea black coral iodine speciation and iodine isotope variability provides key information on iodine behavior in natural and anthropogenic environments, and its geochemical pathway in the Gulf of Mexico. Organo-iodine is the dominant iodine species in the black corals, demonstrating that binding of iodine to organic matter plays an important role in the transport and transfer of iodine to the deep-sea corals. The identification of growth bands captured in high-resolution scanning electron images (SEM) with synchronous peaks in iodine variability suggest that riverine delivery of terrestrial-derived organo-iodine is the most plausible explanation to account for annual periodicity in the deep-sea coral geochemistry. Whereas previous studies have suggested the presence of annual growth rings in deep-sea corals, this present study provides a mechanism to explain the formation of annual growth bands. Furthermore, deep-sea coral ages based on iodine peak counts agree well with those ages derived from radiocarbon ( 14 C) measurements. These results hold promise for developing chronologies independent of 14 C dating, which is an essential component in constraining reservoir ages and using radiocarbon as a tracer of ocean circulation. Furthermore, the presence of enriched 129 I/ 127 I ratios during the most recent period of skeleton growth is linked to nuclear weapons testing during the 1960s. The sensitivity of the coral skeleton to record changes in surface water 129 I composition provides further evidence that iodine composition and isotope variability captured in proteinaceous deep-sea corals is a promising geochronometer as well as an emerging tracer for continental material flux. Published by Elsevier Ltd.

Uptake and distribution of organo-iodine in deep-sea corals

USGS Publications Warehouse

Prouty, Nancy G.; Roark, E. Brendan; Mohon, Leslye M.; Chang, Ching-Chih

2018-01-01

Understanding iodine concentration, transport, and bioavailability is essential in evaluating iodine's impact to the environment and its effectiveness as an environmental biogeotracer. While iodine and its radionuclides have proven to be important tracers in geologic and biologic studies, little is known about transport of this element to the deep sea and subsequent uptake in deep-sea coral habitats. Results presented here on deep-sea black coral iodine speciation and iodine isotope variability provides key information on iodine behavior in natural and anthropogenic environments, and its geochemical pathway in the Gulf of Mexico. Organo-iodine is the dominant iodine species in the black corals, demonstrating that binding of iodine to organic matter plays an important role in the transport and transfer of iodine to the deep-sea corals. The identification of growth bands captured in high-resolution scanning electron images (SEM) with synchronous peaks in iodine variability suggest that riverine delivery of terrestrial-derived organo-iodine is the most plausible explanation to account for annual periodicity in the deep-sea coral geochemistry. Whereas previous studies have suggested the presence of annual growth rings in deep-sea corals, this present study provides a mechanism to explain the formation of annual growth bands. Furthermore, deep-sea coral ages based on iodine peak counts agree well with those ages derived from radiocarbon (14C) measurements. These results hold promise for developing chronologies independent of 14C dating, which is an essential component in constraining reservoir ages and using radiocarbon as a tracer of ocean circulation. Furthermore, the presence of enriched 129I/127I ratios during the most recent period of skeleton growth is linked to nuclear weapons testing during the 1960s. The sensitivity of the coral skeleton to record changes in surface water 129I composition provides further evidence that iodine composition and isotope variability captured in proteinaceous deep-sea corals is a promising geochronometer as well as an emerging tracer for continental material flux.

The influence of muscle pennation angle and cross-sectional area on contact forces in the ankle joint.

PubMed

Sopher, Ran S; Amis, Andrew A; Davies, D Ceri; Jeffers, Jonathan Rt

2017-01-01

Data about a muscle's fibre pennation angle and physiological cross-sectional area are used in musculoskeletal modelling to estimate muscle forces, which are used to calculate joint contact forces. For the leg, muscle architecture data are derived from studies that measured pennation angle at the muscle surface, but not deep within it. Musculoskeletal models developed to estimate joint contact loads have usually been based on the mean values of pennation angle and physiological cross-sectional area. Therefore, the first aim of this study was to investigate differences between superficial and deep pennation angles within each muscle acting over the ankle and predict how differences may influence muscle forces calculated in musculoskeletal modelling. The second aim was to investigate how inter-subject variability in physiological cross-sectional area and pennation angle affects calculated ankle contact forces. Eight cadaveric legs were dissected to excise the muscles acting over the ankle. The mean surface and deep pennation angles, fibre length and physiological cross-sectional area were measured. Cluster analysis was applied to group the muscles according to their architectural characteristics. A previously validated OpenSim model was used to estimate ankle muscle forces and contact loads using architecture data from all eight limbs. The mean surface pennation angle for soleus was significantly greater (54%) than the mean deep pennation angle. Cluster analysis revealed three groups of muscles with similar architecture and function: deep plantarflexors and peroneals, superficial plantarflexors and dorsiflexors. Peak ankle contact force was predicted to occur before toe-off, with magnitude greater than five times bodyweight. Inter-specimen variability in contact force was smallest at peak force. These findings will help improve the development of experimental and computational musculoskeletal models by providing data to estimate force based on both surface and deep pennation angles. Inter-subject variability in muscle architecture affected ankle muscle and contact loads only slightly. The link between muscle architecture and function contributes to the understanding of the relationship between muscle structure and function.

Calibrating amino acid δ13C and δ15N offsets between polyp and protein skeleton to develop proteinaceous deep-sea corals as paleoceanographic archives

NASA Astrophysics Data System (ADS)

McMahon, Kelton W.; Williams, Branwen; Guilderson, Thomas P.; Glynn, Danielle S.; McCarthy, Matthew D.

2018-01-01

Compound-specific stable isotopes of amino acids (CSI-AA) from proteinaceous deep-sea coral skeletons have the potential to improve paleoreconstructions of plankton community composition, and our understanding of the trophic dynamics and biogeochemical cycling of sinking organic matter in the Ocean. However, the assumption that the molecular isotopic values preserved in protein skeletal material reflect those of the living coral polyps has never been directly investigated in proteinaceous deep-sea corals. We examined CSI-AA from three genera of proteinaceous deep-sea corals from three oceanographically distinct regions of the North Pacific: Primnoa from the Gulf of Alaska, Isidella from the Central California Margin, and Kulamanamana from the North Pacific Subtropical Gyre. We found minimal offsets in the δ13C values of both essential and non-essential AAs, and in the δ15N values of source AAs, between paired samples of polyp tissue and protein skeleton. Using an essential AA δ13C fingerprinting approach, we show that estimates of the relative contribution of eukaryotic microalgae and prokaryotic cyanobacteria to the sinking organic matter supporting deep-sea corals are the same when calculated from polyp tissue or recently deposited skeletal tissue. The δ15N values of trophic AAs in skeletal tissue, on the other hand, were consistently 3-4‰ lower than polyp tissue for all three genera. We hypothesize that this offset reflects a partitioning of nitrogen flux through isotopic branch points in the synthesis of polyp (fast turnover tissue) and skeleton (slow, unidirectional incorporation). This offset indicates an underestimation, albeit correctable, of approximately half a trophic position from gorgonin protein-based deep-sea coral skeleton. Together, our observations open the door for applying many of the rapidly evolving CSI-AA based tools developed for metabolically active tissues in modern systems to archival coral tissues in a paleoceanographic context.

InSight Rollout for Launch

NASA Image and Video Library

2018-05-04

At Vandenberg Air Force Base in California, the gantry rolls back at Space Launch Complex 3 in preparation for the liftoff of NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport, or InSight, Mars lander. The United Launch Alliance Atlas V rocket now is poised to boost the spacecraft with liftoff scheduled for 4:05 a.m. PDT (7:05 a.m. EDT). InSight will be the first mission to look deep beneath the Martian surface. It will study the planet's interior by measuring its heat output and listen for marsquakes. InSight will use the seismic waves generated by marsquakes to develop a map of the planet’s deep interior. The resulting insight into Mars’ formation will provide a better understanding of how other rocky planets, including Earth, were created.

Korean letter handwritten recognition using deep convolutional neural network on android platform

NASA Astrophysics Data System (ADS)

Purnamawati, S.; Rachmawati, D.; Lumanauw, G.; Rahmat, R. F.; Taqyuddin, R.

2018-03-01

Currently, popularity of Korean culture attracts many people to learn everything about Korea, particularly its language. To acquire Korean Language, every single learner needs to be able to understand Korean non-Latin character. A digital approach needs to be carried out in order to make Korean learning process easier. This study is done by using Deep Convolutional Neural Network (DCNN). DCNN performs the recognition process on the image based on the model that has been trained such as Inception-v3 Model. Subsequently, re-training process using transfer learning technique with the trained and re-trained value of model is carried though in order to develop a new model with a better performance without any specific systemic errors. The testing accuracy of this research results in 86,9%.

Planetary science and exploration in the deep subsurface: results from the MINAR Program, Boulby Mine, UK

NASA Astrophysics Data System (ADS)

Payler, Samuel J.; Biddle, Jennifer F.; Coates, Andrew J.; Cousins, Claire R.; Cross, Rachel E.; Cullen, David C.; Downs, Michael T.; Direito, Susana O. L.; Edwards, Thomas; Gray, Amber L.; Genis, Jac; Gunn, Matthew; Hansford, Graeme M.; Harkness, Patrick; Holt, John; Josset, Jean-Luc; Li, Xuan; Lees, David S.; Lim, Darlene S. S.; McHugh, Melissa; McLuckie, David; Meehan, Emma; Paling, Sean M.; Souchon, Audrey; Yeoman, Louise; Cockell, Charles S.

2017-04-01

The subsurface exploration of other planetary bodies can be used to unravel their geological history and assess their habitability. On Mars in particular, present-day habitable conditions may be restricted to the subsurface. Using a deep subsurface mine, we carried out a program of extraterrestrial analog research - MINe Analog Research (MINAR). MINAR aims to carry out the scientific study of the deep subsurface and test instrumentation designed for planetary surface exploration by investigating deep subsurface geology, whilst establishing the potential this technology has to be transferred into the mining industry. An integrated multi-instrument suite was used to investigate samples of representative evaporite minerals from a subsurface Permian evaporite sequence, in particular to assess mineral and elemental variations which provide small-scale regions of enhanced habitability. The instruments used were the Panoramic Camera emulator, Close-Up Imager, Raman spectrometer, Small Planetary Linear Impulse Tool, Ultrasonic drill and handheld X-ray diffraction (XRD). We present science results from the analog research and show that these instruments can be used to investigate in situ the geological context and mineralogical variations of a deep subsurface environment, and thus habitability, from millimetre to metre scales. We also show that these instruments are complementary. For example, the identification of primary evaporite minerals such as NaCl and KCl, which are difficult to detect by portable Raman spectrometers, can be accomplished with XRD. By contrast, Raman is highly effective at locating and detecting mineral inclusions in primary evaporite minerals. MINAR demonstrates the effective use of a deep subsurface environment for planetary instrument development, understanding the habitability of extreme deep subsurface environments on Earth and other planetary bodies, and advancing the use of space technology in economic mining.

D.E.E.P. Learning: Promoting Informal STEM Learning through Ocean Research Simulation Games

NASA Astrophysics Data System (ADS)

Simms, E.; Rohrlick, D.; Layman, C.; Peach, C. L.; Orcutt, J. A.; Keen, C. S.; Matthews, J.; Nsf Ooi-Ci Education; Public Engagement Team

2010-12-01

It is generally recognized that interactive digital games have the potential to promote the development of valuable learning and life skills, including data processing, decision-making, critical thinking, planning, communication and collaboration (Kirriemuir and MacFarlane, 2006). But the research and development of educational games, and the study of the educational value of interactive games in general, have lagged far behind the same efforts for games created for the purpose of entertainment. Our group is attempting to capitalize on the facts that games are now played in 67% of American households (ESA, 2010), and across a broad range of ages, by developing effective and engaging simulation games that promote Science, Technology, Engineering and Mathematics (STEM) literacy in informal science education institutions (ISEIs; e.g., aquariums, museums, science centers). In particular, we are developing games based on the popular Microsoft Xbox360 gaming platform and the free Microsoft XNA game development kit, which engage ISEI visitors in the exploration and understanding of the deep-sea environment. Known as Deep-sea Extreme Environment Pilot (D.E.E.P.), the games place players in the role of piloting a remotely-operated vehicle (ROV) to complete science-based objectives associated with the exploration of ocean observing systems and hydrothermal vent environments. In addition to creating a unique educational product, our efforts are intended to identify 1) the key elements of a successful STEM-based simulation game experience in an informal science education institution, and 2) which aspects of game design (e.g., challenge, curiosity, fantasy, personal recognition) are most effective at maximizing both learning and enjoyment. We will share our progress to date, including formative assessment results from testing the game prototypes at Birch Aquarium at Scripps, and discuss the potential benefits and challenges to interactive gaming as a tool to support STEM literacy.

Development of deep eutectic solvents applied in extraction and separation.

PubMed

Li, Xiaoxia; Row, Kyung Ho

2016-09-01

Deep eutectic solvents, as an alternative to ionic liquids, have greener credentials than ionic liquids, and have attracted considerable attention in related chemical research. Deep eutectic solvents have attracted increasing attention in chemistry for the extraction and separation of various target compounds from natural products. This review highlights the preparation of deep eutectic solvents, unique properties of deep eutectic solvents, and synthesis of deep-eutectic-solvent-based materials. On the other hand, application in the extraction and separation of deep eutectic solvents is also included in this report. In this paper, the available data and references in this field are reviewed to summarize the applications and developments of deep eutectic solvents. Based on the development of deep eutectic solvents, an exploitation of new deep eutectic solvents and deep eutectic solvents-based materials is expected to diversify into extraction and separation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Is Multitask Deep Learning Practical for Pharma?

PubMed

Ramsundar, Bharath; Liu, Bowen; Wu, Zhenqin; Verras, Andreas; Tudor, Matthew; Sheridan, Robert P; Pande, Vijay

2017-08-28

Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack of acceptance stems from both software difficulties and lack of understanding of the robustness of multitask deep networks. Our work aims to resolve both of these barriers to adoption. We introduce a high-quality open-source implementation of multitask deep networks as part of the DeepChem open-source platform. Our implementation enables simple python scripts to construct, fit, and evaluate sophisticated deep models. We use our implementation to analyze the performance of multitask deep networks and related deep models on four collections of pharmaceutical data (three of which have not previously been analyzed in the literature). We split these data sets into train/valid/test using time and neighbor splits to test multitask deep learning performance under challenging conditions. Our results demonstrate that multitask deep networks are surprisingly robust and can offer strong improvement over random forests. Our analysis and open-source implementation in DeepChem provide an argument that multitask deep networks are ready for widespread use in commercial drug discovery.

Unraveling the Tangled Skein: The Evolution of Transcriptional Regulatory Networks in Development.

PubMed

Rebeiz, Mark; Patel, Nipam H; Hinman, Veronica F

2015-01-01

The molecular and genetic basis for the evolution of anatomical diversity is a major question that has inspired evolutionary and developmental biologists for decades. Because morphology takes form during development, a true comprehension of how anatomical structures evolve requires an understanding of the evolutionary events that alter developmental genetic programs. Vast gene regulatory networks (GRNs) that connect transcription factors to their target regulatory sequences control gene expression in time and space and therefore determine the tissue-specific genetic programs that shape morphological structures. In recent years, many new examples have greatly advanced our understanding of the genetic alterations that modify GRNs to generate newly evolved morphologies. Here, we review several aspects of GRN evolution, including their deep preservation, their mechanisms of alteration, and how they originate to generate novel developmental programs.

The Livermore Brain: Massive Deep Learning Networks Enabled by High Performance Computing

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

Chen, Barry Y.

The proliferation of inexpensive sensor technologies like the ubiquitous digital image sensors has resulted in the collection and sharing of vast amounts of unsorted and unexploited raw data. Companies and governments who are able to collect and make sense of large datasets to help them make better decisions more rapidly will have a competitive advantage in the information era. Machine Learning technologies play a critical role for automating the data understanding process; however, to be maximally effective, useful intermediate representations of the data are required. These representations or “features” are transformations of the raw data into a form where patternsmore » are more easily recognized. Recent breakthroughs in Deep Learning have made it possible to learn these features from large amounts of labeled data. The focus of this project is to develop and extend Deep Learning algorithms for learning features from vast amounts of unlabeled data and to develop the HPC neural network training platform to support the training of massive network models. This LDRD project succeeded in developing new unsupervised feature learning algorithms for images and video and created a scalable neural network training toolkit for HPC. Additionally, this LDRD helped create the world’s largest freely-available image and video dataset supporting open multimedia research and used this dataset for training our deep neural networks. This research helped LLNL capture several work-for-others (WFO) projects, attract new talent, and establish collaborations with leading academic and commercial partners. Finally, this project demonstrated the successful training of the largest unsupervised image neural network using HPC resources and helped establish LLNL leadership at the intersection of Machine Learning and HPC research.« less

Understanding of the management information system based on MVC pattern

NASA Astrophysics Data System (ADS)

Chen, Sida

2018-04-01

With the development of the society, people have come to realize the significance of information, not only linguistically but also in the written form. To build an effective and efficient working flow, a new subject called Management Information System (MIS) came up. MIS is an integrated discipline, which utilizes comprehensive and systematical methods to manage information, and it enhances the work efficiency through building structured information platform. This paper demonstrates the Management Information System from shallow too deep with the understanding of MVC pattern, including its basic structure and application with ASP.NET. Also some discussions about its features are made in the last section.

The role of future scenarios to understand deep uncertainty in air quality management

EPA Science Inventory

The environment and it’s interaction with human systems (economic, social and political) is complex and dynamic. Key drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents ...

The role of future scenarios to understand deep uncertainty for air quality management.

EPA Science Inventory

The environment and its interaction with human systems (economic, social and political) is complex and dynamic. Key drivers may disrupt systemdynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents a challeng...

Command History Calendar Year 1992 (Navy Personnel Research and Development Center)

DTIC Science & Technology

1993-07-01

efficiently. and manage our personnel resources optimally. By combining a deep understanding of operational requirements with first-rate scientific and...the needs of manpower, personnel, and training managers in the Navy, Marine Corps, and Department of Defense (DOD); to the operating forces; and to the...NPRDC Professional Publications Award and the 1990 Commander’s Award for Management Excellence. He is a fellow of the American Association for the

Deep Tissue Injury in Development of Pressure Ulcers: A Decrease of Inflammasome Activation and Changes in Human Skin Morphology in Response to Aging and Mechanical Load

PubMed Central

Stojadinovic, Olivera; Minkiewicz, Julia; Sawaya, Andrew; Bourne, Jonathan W.; Torzilli, Peter; de Rivero Vaccari, Juan Pablo; Dietrich, W. Dalton; Keane, Robert W.; Tomic-Canic, Marjana

2013-01-01

Molecular mechanisms leading to pressure ulcer development are scarce in spite of high mortality of patients. Development of pressure ulcers that is initially observed as deep tissue injury is multifactorial. We postulate that biomechanical forces and inflammasome activation, together with ischemia and aging, may play a role in pressure ulcer development. To test this we used a newly-developed bio-mechanical model in which ischemic young and aged human skin was subjected to a constant physiological compressive stress (load) of 300 kPa (determined by pressure plate analyses of a person in a reclining position) for 0.5–4 hours. Collagen orientation was assessed using polarized light, whereas inflammasome proteins were quantified by immunoblotting. Loaded skin showed marked changes in morphology and NLRP3 inflammasome protein expression. Sub-epidermal separations and altered orientation of collagen fibers were observed in aged skin at earlier time points. Aged skin showed significant decreases in the levels of NLRP3 inflammasome proteins. Loading did not alter NLRP3 inflammasome proteins expression in aged skin, whereas it significantly increased their levels in young skin. We conclude that aging contributes to rapid morphological changes and decrease in inflammasome proteins in response to tissue damage, suggesting that a decline in the innate inflammatory response in elderly skin could contribute to pressure ulcer pathogenesis. Observed morphological changes suggest that tissue damage upon loading may not be entirely preventable. Furthermore, newly developed model described here may be very useful in understanding the mechanisms of deep tissue injury that may lead towards development of pressure ulcers. PMID:23967056

Nitrate removal in deep sediments of a nitrogen-rich river network: A test of a conceptual model

USGS Publications Warehouse

Stelzer, Robert S.; Bartsch, Lynn

2012-01-01

Many estimates of nitrogen removal in streams and watersheds do not include or account for nitrate removal in deep sediments, particularly in gaining streams. We developed and tested a conceptual model for nitrate removal in deep sediments in a nitrogen-rich river network. The model predicts that oxic, nitrate-rich groundwater will become depleted in nitrate as groundwater upwelling through sediments encounters a zone that contains buried particulate organic carbon, which promotes redox conditions favorable for nitrate removal. We tested the model at eight sites in upwelling reaches of lotic ecosystems in the Waupaca River Watershed that varied by three orders of magnitude in groundwater nitrate concentration. We measured denitrification potential in sediment core sections to 30 cm and developed vertical nitrate profiles to a depth of about 1 m with peepers and piezometer nests. Denitrification potential was higher, on average, in shallower core sections. However, core sections deeper than 5 cm accounted for 70%, on average, of the depth-integrated denitrification potential. Denitrification potential increased linearly with groundwater nitrate concentration up to 2 mg NO3-N/L but the relationship broke down at higher concentrations (> 5 mg NO3-N/L), a pattern that suggests nitrate saturation. At most sites groundwater nitrate declined from high concentrations at depth to much lower concentrations prior to discharge into the surface water. The profiles suggested that nitrate removal occurred at sediment depths between 20 and 40 cm. Dissolved oxygen concentrations were much higher in deep sediments than in pore water at 5 cm sediment depth at most locations. The substantial denitrification potential in deep sediments coupled with the declines in nitrate and dissolved oxygen concentrations in upwelling groundwater suggest that our conceptual model for nitrate removal in deep sediments is applicable to this river network. Our results suggest that nitrate removal rates can be high in deep sediments of upwelling stream reaches, which may have implications for efforts to understand and quantify nitrogen transport and removal at larger scales.

Two-dimensional joint inversion of Magnetotelluric and local earthquake data: Discussion on the contribution to the solution of deep subsurface structures

NASA Astrophysics Data System (ADS)

Demirci, İsmail; Dikmen, Ünal; Candansayar, M. Emin

2018-02-01

Joint inversion of data sets collected by using several geophysical exploration methods has gained importance and associated algorithms have been developed. To explore the deep subsurface structures, Magnetotelluric and local earthquake tomography algorithms are generally used individually. Due to the usage of natural resources in both methods, it is not possible to increase data quality and resolution of model parameters. For this reason, the solution of the deep structures with the individual usage of the methods cannot be fully attained. In this paper, we firstly focused on the effects of both Magnetotelluric and local earthquake data sets on the solution of deep structures and discussed the results on the basis of the resolving power of the methods. The presence of deep-focus seismic sources increase the resolution of deep structures. Moreover, conductivity distribution of relatively shallow structures can be solved with high resolution by using MT algorithm. Therefore, we developed a new joint inversion algorithm based on the cross gradient function in order to jointly invert Magnetotelluric and local earthquake data sets. In the study, we added a new regularization parameter into the second term of the parameter correction vector of Gallardo and Meju (2003). The new regularization parameter is enhancing the stability of the algorithm and controls the contribution of the cross gradient term in the solution. The results show that even in cases where resistivity and velocity boundaries are different, both methods influence each other positively. In addition, the region of common structural boundaries of the models are clearly mapped compared with original models. Furthermore, deep structures are identified satisfactorily even with using the minimum number of seismic sources. In this paper, in order to understand the future studies, we discussed joint inversion of Magnetotelluric and local earthquake data sets only in two-dimensional space. In the light of these results and by means of the acceleration on the three-dimensional modelling and inversion algorithms, it is thought that it may be easier to identify underground structures with high resolution.

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.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

PubMed Central

2017-01-01

Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs) for robust movement decoding of Parkinson's disease (PD) and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value) at about 0.729 ± 0.16 for decoding movement from the resting state and about 0.671 ± 0.14 for decoding left and right visually cued movements. PMID:29201041

Development of a Shared Decision Making coding system for analysis of patient-healthcare provider encounters

PubMed Central

Clayman, Marla L.; Makoul, Gregory; Harper, Maya M.; Koby, Danielle G.; Williams, Adam R.

2012-01-01

Objectives Describe the development and refinement of a scheme, Detail of Essential Elements and Participants in Shared Decision Making (DEEP-SDM), for coding Shared Decision Making (SDM) while reporting on the characteristics of decisions in a sample of patients with metastatic breast cancer. Methods The Evidence-Based Patient Choice instrument was modified to reflect Makoul and Clayman’s Integrative Model of SDM. Coding was conducted on video recordings of 20 women at the first visit with their medical oncologists after suspicion of disease progression. Noldus Observer XT v.8, a video coding software platform, was used for coding. Results The sample contained 80 decisions (range: 1-11), divided into 150 decision making segments. Most decisions were physician-led, although patients and physicians initiated similar numbers of decision-making conversations. Conclusion DEEP-SDM facilitates content analysis of encounters between women with metastatic breast cancer and their medical oncologists. Despite the fractured nature of decision making, it is possible to identify decision points and to code each of the Essential Elements of Shared Decision Making. Further work should include application of DEEP-SDM to non-cancer encounters. Practice Implications: A better understanding of how decisions unfold in the medical encounter can help inform the relationship of SDM to patient-reported outcomes. PMID:22784391

Three-Dimensional Analysis of Deep Space Network Antenna Coverage

NASA Technical Reports Server (NTRS)

Kegege, Obadiah; Fuentes, Michael; Meyer, Nicholas; Sil, Amy

2012-01-01

There is a need to understand NASA s Deep Space Network (DSN) coverage gaps and any limitations to provide redundant communication coverage for future deep space missions, especially for manned missions to Moon and Mars. The DSN antennas are required to provide continuous communication coverage for deep space flights, interplanetary missions, and deep space scientific observations. The DSN consists of ground antennas located at three sites: Goldstone in USA, Canberra in Australia, and Madrid in Spain. These locations are not separated by the exactly 120 degrees and some DSN antennas are located in the bowl-shaped mountainous terrain to shield against radiofrequency interference resulting in a coverage gap in the southern hemisphere for the current DSN architecture. To analyze the extent of this gap and other coverage limitations, simulations of the DSN architecture were performed. In addition to the physical properties of the DSN assets, the simulation incorporated communication forward link calculations and azimuth/elevation masks that constrain the effects of terrain for each DSN antenna. Analysis of the simulation data was performed to create coverage profiles with the receiver settings at a deep space altitudes ranging from 2 million to 10 million km and a spherical grid resolution of 0.25 degrees with respect to longitude and latitude. With the results of these simulations, two- and three-dimensional representations of the area without communication coverage and area with coverage were developed, showing the size and shape of the communication coverage gap projected in space. Also, the significance of this communication coverage gap is analyzed from the simulation data.

Rapid Fine Conformational Epitope Mapping Using Comprehensive Mutagenesis and Deep Sequencing*

PubMed Central

Kowalsky, Caitlin A.; Faber, Matthew S.; Nath, Aritro; Dann, Hailey E.; Kelly, Vince W.; Liu, Li; Shanker, Purva; Wagner, Ellen K.; Maynard, Jennifer A.; Chan, Christina; Whitehead, Timothy A.

2015-01-01

Knowledge of the fine location of neutralizing and non-neutralizing epitopes on human pathogens affords a better understanding of the structural basis of antibody efficacy, which will expedite rational design of vaccines, prophylactics, and therapeutics. However, full utilization of the wealth of information from single cell techniques and antibody repertoire sequencing awaits the development of a high throughput, inexpensive method to map the conformational epitopes for antibody-antigen interactions. Here we show such an approach that combines comprehensive mutagenesis, cell surface display, and DNA deep sequencing. We develop analytical equations to identify epitope positions and show the method effectiveness by mapping the fine epitope for different antibodies targeting TNF, pertussis toxin, and the cancer target TROP2. In all three cases, the experimentally determined conformational epitope was consistent with previous experimental datasets, confirming the reliability of the experimental pipeline. Once the comprehensive library is generated, fine conformational epitope maps can be prepared at a rate of four per day. PMID:26296891

ClearSee: a rapid optical clearing reagent for whole-plant fluorescence imaging

PubMed Central

Kurihara, Daisuke; Mizuta, Yoko; Sato, Yoshikatsu; Higashiyama, Tetsuya

2015-01-01

Imaging techniques for visualizing and analyzing precise morphology and gene expression patterns are essential for understanding biological processes during development in all organisms. With the aid of chemical screening, we developed a clearing method using chemical solutions, termed ClearSee, for deep imaging of morphology and gene expression in plant tissues. ClearSee rapidly diminishes chlorophyll autofluorescence while maintaining fluorescent protein stability. By adjusting the refractive index mismatch, whole-organ and whole-plant imaging can be performed by both confocal and two-photon excitation microscopy in ClearSee-treated samples. Moreover, ClearSee is applicable to multicolor imaging of fluorescent proteins to allow structural analysis of multiple gene expression. Given that ClearSee is compatible with staining by chemical dyes, the technique is useful for deep imaging in conjunction with genetic markers and for plant species not amenable to transgenic approaches. This method is useful for whole imaging for intact morphology and will help to accelerate the discovery of new phenomena in plant biological research. PMID:26493404

ASSESSING THE GEOCHEMICAL FATE OF DEEP-WELL-INJECTED HAZARDOUS WASTE: A REFERENCE GUIDE

EPA Science Inventory

The geochemical fate of deep-well-injected wastes must be thoroughly understood to avoid problems when incompatibility between the injected wastes and the injection-zone formation is a possibility. An understanding of geochemical fate will be useful when a geochemical no-migratio...

Role of future scenarios in understanding deep uncertainty in long-term air quality management

EPA Science Inventory

The environment and its interactions with human systems, whether economic, social or political, are complex. Relevant drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions. This kind of deep uncertainty presents a challenge to ...

First biological measurements of deep-sea corals from the Red Sea

PubMed Central

Roder, C.; Berumen, M. L.; Bouwmeester, J.; Papathanassiou, E.; Al-Suwailem, A.; Voolstra, C. R.

2013-01-01

It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with ‘deep-sea’ and ‘cold-water’ corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20°C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the key adaptations to prevailing environmental conditions. We investigated four sites and encountered six species of which at least two appear to be undescribed. One species is previously reported from the Red Sea but occurs in deep cold waters outside the Red Sea raising interesting questions about presumed environmental constraints for other deep-sea corals. Our findings suggest that the present understanding of deep-sea coral persistence and resilience needs to be revisited. PMID:24091830

Exploitation of deep-sea resources: the urgent need to understand the role of high pressure in the toxicity of chemical pollutants to deep-sea organisms.

PubMed

Mestre, Nélia C; Calado, Ricardo; Soares, Amadeu M V M

2014-02-01

The advent of industrial activities in the deep sea will inevitably expose deep-sea organisms to potentially toxic compounds. Although international regulations require environmental risk assessment prior to exploitation activities, toxicity tests remain focused on shallow-water model species. Moreover, current tests overlook potential synergies that may arise from the interaction of chemicals with natural stressors, such as the high pressures prevailing in the deep sea. As pressure affects chemical reactions and the physiology of marine organisms, it will certainly affect the toxicity of pollutants arising from the exploitation of deep-sea resources. We emphasize the need for environmental risk assessments based on information generated from ecotoxicological trials that mimic, as close as possible, the deep-sea environment, with emphasis to a key environmental factor - high hydrostatic pressure. Copyright © 2013 Elsevier Ltd. All rights reserved.

First biological measurements of deep-sea corals from the Red Sea.

PubMed

Roder, C; Berumen, M L; Bouwmeester, J; Papathanassiou, E; Al-Suwailem, A; Voolstra, C R

2013-10-03

It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with 'deep-sea' and 'cold-water' corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20°C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the key adaptations to prevailing environmental conditions. We investigated four sites and encountered six species of which at least two appear to be undescribed. One species is previously reported from the Red Sea but occurs in deep cold waters outside the Red Sea raising interesting questions about presumed environmental constraints for other deep-sea corals. Our findings suggest that the present understanding of deep-sea coral persistence and resilience needs to be revisited.

The New Possibilities from "Big Data" to Overlooked Associations Between Diabetes, Biochemical Parameters, Glucose Control, and Osteoporosis.

PubMed

Kruse, Christian

2018-06-01

To review current practices and technologies within the scope of "Big Data" that can further our understanding of diabetes mellitus and osteoporosis from large volumes of data. "Big Data" techniques involving supervised machine learning, unsupervised machine learning, and deep learning image analysis are presented with examples of current literature. Supervised machine learning can allow us to better predict diabetes-induced osteoporosis and understand relative predictor importance of diabetes-affected bone tissue. Unsupervised machine learning can allow us to understand patterns in data between diabetic pathophysiology and altered bone metabolism. Image analysis using deep learning can allow us to be less dependent on surrogate predictors and use large volumes of images to classify diabetes-induced osteoporosis and predict future outcomes directly from images. "Big Data" techniques herald new possibilities to understand diabetes-induced osteoporosis and ascertain our current ability to classify, understand, and predict this condition.

Potential impacts of leakage from deep CO2 geosequestration on overlying freshwater aquifers.

PubMed

Little, Mark G; Jackson, Robert B

2010-12-01

Carbon Capture and Storage may use deep saline aquifers for CO(2) sequestration, but small CO(2) leakage could pose a risk to overlying fresh groundwater. We performed laboratory incubations of CO(2) infiltration under oxidizing conditions for >300 days on samples from four freshwater aquifers to 1) understand how CO(2) leakage affects freshwater quality; 2) develop selection criteria for deep sequestration sites based on inorganic metal contamination caused by CO(2) leaks to shallow aquifers; and 3) identify geochemical signatures for early detection criteria. After exposure to CO(2), water pH declines of 1-2 units were apparent in all aquifer samples. CO(2) caused concentrations of the alkali and alkaline earths and manganese, cobalt, nickel, and iron to increase by more than 2 orders of magnitude. Potentially dangerous uranium and barium increased throughout the entire experiment in some samples. Solid-phase metal mobility, carbonate buffering capacity, and redox state in the shallow overlying aquifers influence the impact of CO(2) leakage and should be considered when selecting deep geosequestration sites. Manganese, iron, calcium, and pH could be used as geochemical markers of a CO(2) leak, as their concentrations increase within 2 weeks of exposure to CO(2).

Prediction of the biomechanical effects of compression therapy on deep veins using finite element modelling.

PubMed

Rohan, Pierre-Yves; Badel, Pierre; Lun, Bertrand; Rastel, Didier; Avril, Stéphane

2015-02-01

Clinicians generally assume that Medical Compression Stockings (MCS) work by reducing vein luminal diameter and, in this way, help to prevent blood pooling. Conflicting results have been reported however in the case of lower leg deep veins which call into question this hypothesis. The purpose of this contribution is to study the biomechanical response of the main lower leg deep veins to elastic compression and muscle contraction with the objective of improving our current understanding of the mechanism by which MCS convey their benefits. The development of a finite-element model of a slice of the lower leg from MR images is detailed. Analysis of the finite-element model shows that the contribution of the MCS to the deep vein diameter reduction is rather small, and in fact negligible, compared to that of the contracting muscle (3 and 9% decrease in the vein cross-sectional area with a grade II compression stocking in the supine and standing positions respectively, while complete collapse was obtained at the end of muscle activation). A more accurate representation of the muscle activation is eventually proposed to study the effect of muscle contraction on a vein wall. The impact on the venous blood draining is discussed.

De Novo Deep Transcriptome Analysis of Medicinal Plants for Gene Discovery in Biosynthesis of Plant Natural Products.

PubMed

Han, R; Rai, A; Nakamura, M; Suzuki, H; Takahashi, H; Yamazaki, M; Saito, K

2016-01-01

Study on transcriptome, the entire pool of transcripts in an organism or single cells at certain physiological or pathological stage, is indispensable in unraveling the connection and regulation between DNA and protein. Before the advent of deep sequencing, microarray was the main approach to handle transcripts. Despite obvious shortcomings, including limited dynamic range and difficulties to compare the results from distinct experiments, microarray was widely applied. During the past decade, next-generation sequencing (NGS) has revolutionized our understanding of genomics in a fast, high-throughput, cost-effective, and tractable manner. By adopting NGS, efficiency and fruitful outcomes concerning the efforts to elucidate genes responsible for producing active compounds in medicinal plants were profoundly enhanced. The whole process involves steps, from the plant material sampling, to cDNA library preparation, to deep sequencing, and then bioinformatics takes over to assemble enormous-yet fragmentary-data from which to comb and extract information. The unprecedentedly rapid development of such technologies provides so many choices to facilitate the task, which can cause confusion when choosing the suitable methodology for specific purposes. Here, we review the general approaches for deep transcriptome analysis and then focus on their application in discovering biosynthetic pathways of medicinal plants that produce important secondary metabolites. © 2016 Elsevier Inc. All rights reserved.

Simulation technology used for risky assessment in deep exploration project in China

NASA Astrophysics Data System (ADS)

jiao, J.; Huang, D.; Liu, J.

2013-12-01

Deep exploration has been carried out in China for five years in which various heavy duty instruments and equipments are employed for gravity, magnetic, seismic and electromagnetic data prospecting as well as ultra deep drilling rig established for obtaining deep samples, and so on. The deep exploration is a large and complex system engineering crossing multiple subjects with great investment. It is necessary to employ advanced technical means technology for verification, appraisal, and optimization of geographical prospecting equipment development. To reduce risk of the application and exploration, efficient and allegeable management concept and skills have to be enhanced in order to consolidate management measure and workflow to benefit the ambitious project. Therefore, evidence, prediction, evaluation and related decision strategies have to be taken into accouter simultaneously to meet practical scientific requests and technique limits and extendable attempts. Simulation technique is then proposed as a tool that can be used to carry out dynamic test on actual or imagined system. In practice, it is necessary to combine the simulation technique with the instruments and equipment to accomplish R&D tasks. In this paper, simulation technique is introduced into the R&D process of heavy-duty equipment and high-end engineering project technology. Based on the information provided by a drilling group recently, a digital model is constructed by combination of geographical data, 3d visualization, database management, and visual reality technologies together. It result in push ahead a R&D strategy, in which data processing , instrument application, expected result and uncertainty, and even operation workflow effect environment atmosphere are simulated systematically or simultaneously, in order to obtain an optimal consequence as well as equipment updating strategy. The simulation technology is able to adjust, verify, appraise and optimize the primary plan due to changing in the real world or process, which can provide new insight to the equipment to meet requests from application and construction process and facilitates by means of direct perception and understanding of installation, debugging and experimental process of key equipment for deep exploration. Finally, the objective of project cost conservation and risk reduction can be reasonably approached. Risk assessment can be used to quantitatively evaluate the possible degree of the impact. During the research and development stage, information from the installation, debugging and simulation demonstration of the experiment process of the key instrument and equipment are used to evaluate the fatigue and safety of the device. It needs fully understanding the controllable and uncontrollable risk factors during the process, and then adjusting and improving the unsafe risk factors in the risk assessment and prediction. With combination with professional Geo software to process and interpret the environment to obtain evaluation parameters, simulation modeling is more likely close to exploration target which need more details of evaluations. From micro and macro comprehensive angles to safety and risk assessment can be achieved to satisfy the purpose of reducing the risk of equipment development, and to avoid unnecessary loss on the way of the development.

Science and Technology Review December 2010

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

Blobaum, K M

This month's issue has the following articles: (1) More Insight to Better Understand Climate Change - Commentary by Tomas Diaz de la Rubia; (2) Strengthening Our Understanding of Climate Change - Researchers at the Center for Accelerator Mass Spectrometry are working to better understand climate variation and sharpen the accuracy of predictive models; (3) Precision Diagnostics Tell All - The National Ignition Facility relies on sophisticated diagnostic instruments for measuring the key physical processes that occur in high-energy-density experiments; (4) Quick Detection of Pathogens by the Thousands - Livermore scientists have developed a device that can simultaneously identify thousands ofmore » viruses and bacteria within 24 hours; and (5) Carbon Dioxide into the Briny Deep - A proposed technique for burying carbon dioxide underground could help mitigate the effects of this greenhouse gas while producing freshwater.« less

Bringing OTEC Environmental Assessments of the 1980s Up To 21st Century Oceanographic Standards (Invited)

NASA Astrophysics Data System (ADS)

Sansone, F. J.; Comfort, C. M.; Weng, K. C.

2010-12-01

Although the potential environmental effects of OTEC plant construction and operation were evaluated in the 1980s as part of earlier OTEC development, recent OTEC efforts have led to the re-examination of the issues involved. During the intervening years we have significantly increased our understanding of the oceans, and our ability to observe and model the marine environment has improved markedly. For example, OTEC environmental assessments have traditionally included the effects of discharging deep seawater, with its elevated levels of dissolved inorganic nutrients and dissolved inorganic carbon, and depleted levels of dissolved oxygen, into the upper water column. However, the role of trace elements in controlling marine primary production rates is now widely accepted, and their natural vertical distribution in the ocean needs to be considered. Our expanded understanding of ocean biogeochemistry also makes environmental assessment more complicated. For example, discharges of deep seawater within the photic zone of the ocean, but below the surface mixed layer, should result in photosynthetic production that would remove both dissolved nutrients and dissolved carbon dioxide at approximately the same stoichiometric ratio as they are elevated in deep seawater; thus, the only large-scale related environmental impact would involve the fate of the resulting photosynthetically produced organic matter. Similarly, our improved knowledge of marine physical chemistry allows a better understanding of OTEC’s potential impact on the ocean’s inorganic carbon chemistry. For example, the reduction in pressure of deep seawater as it is brought to the surface, and the increase in temperature due to OTEC heat exchange, will both lead to an increase in the deep water’s pH; opposite effects will occur in the shallow seawater used by OTEC. Determination of the net effect will require modeling using predicted pumping rates for warm and cold seawater, the planned intake and discharge depths and temperatures, the inorganic carbon chemistry at the specific site, and recently refined inorganic carbon equilibria data. Ecological data (e.g., primary productivity, the biomass of various trophic levels, biota attraction to floating objects, etc.) should also be updated with the results from more contemporary studies. Additional factors that should be examined include electromagnetic effects of cabling, alterations in the bio-physical coupling of water column as a result of the discharge plume, potential harmful algal bloom development, and low-frequency noise production. Moreover, new ocean observation techniques such as gliders and AUVs allow large areas of the ocean to be monitored in 3-D for extended periods of time. Similarly, new marine modeling techniques, such as regional ocean modeling systems (ROMS), allow OTEC plumes to be studied in the context of a 3-D dynamic ocean, including such features as internal tides and mesoscales eddies, and allow assimilation of 3-D data to improve model performance. As an early step in these efforts, we have used HOT time-series data to determine patterns of seasonal variability in the upper ocean (warm water intake and discharge zone) and in the deep ocean (cold water uptake) near the site for the proposed Kahe Point, Oahu OTEC demonstration plant.

Supercritical sedimentary structures and bedforms and criteria for recognition in the field: insights from the Middle Eocene deep-marine Morillo and Guaso systems, Ainsa Basin, Spanish Pyrenees

NASA Astrophysics Data System (ADS)

Torley, John; Pickering, Kevin

2017-04-01

It has long been acknowledged that for most submarine slopes with gradients > 0.5, common to many deep-water environments, they should contain abundant evidence of supercritical flows and their deposits. However, it is common for deep-marine sands/sandstones to be routinely modelled using the Bouma (1962) sequence for turbidites. Recently, the importance of supercritical flows has been highlighted from seafloor observations, with numerical and physical experiments. Such experiments have produced previously unrecognised bedforms which fail to be interpreted adequately by Bouma's model, including antidunes, chutes-and-pools, and cyclic steps. Fieldwork in the Middle Eocene Ainsa Basin, Spanish Pyrenees, has been undertaken in the Morillo and Guaso systems of the Upper Hecho Group. Approximately 5,000 beds were measured and documented in detail, e.g., grain size, sedimentary structures, bedforms and facies. Collectively, this data can be used to understand supercritical versus subcritical flow. The relative importance of supercritical flow can then be compared and contrasted within individual ancient deep-marine systems. The Morillo System is relatively coarse-grained, compared with the Guaso System. The results of this research contribute to an improved understanding of the processes in deep-marine systems, and directly benefit the hydrocarbon industry by providing better constraints to predict deep-water reservoir composition and architecture.

The economic implications of changing regulations for deep sea fishing under the European Common Fisheries Policy: UK case study.

PubMed

Mangi, Stephen C; Kenny, Andrew; Readdy, Lisa; Posen, Paulette; Ribeiro-Santos, Ana; Neat, Francis C; Burns, Finlay

2016-08-15

Economic impact assessment methodology was applied to UK fisheries data to better understand the implications of European Commission proposal for regulations to fishing for deep-sea stocks in the North-East Atlantic (EC COM 371 Final 2012) under the Common Fisheries Policy (CFP). The aim was to inform the on-going debate to develop the EC proposal, and to assist the UK fishing industry and Government in evaluating the most effective options to manage deep sea fish stocks. Results indicate that enforcing the EC proposal as originally drafted results in a number of implications for the UK fleet. Because of the proposed changes to the list of species defined as being deep sea species, and a new definition of what constitutes a vessel targeting deep sea species, a total of 695 active UK fishing vessels would need a permit to fish for deep sea species. However, due to existing and capped capacity limits many vessels would potentially not be able to obtain such a permit. The economic impact of these changes from the status quo reveals that in the short term, landings would decrease by 6540 tonnes, reducing gross value added by £3.3 million. Alternative options were also assessed that provide mitigation measures to offset the impacts of the proposed regulations whilst at the same time providing more effective protection of deep sea Vulnerable Marine Ecosystems (VMEs). The options include setting a 400m depth rule that identifies a depth beyond which vessels would potentially be classified as fishing for deep sea species and designating 'core areas' for deep sea fishing at depths>400m to minimise the risk of further impacts of bottom fishing gear on deep sea habitats. Applying a 400m depth limit and 'core fishing' area approach deeper than 400m, the impact of the EC proposal would essentially be reduced to zero, that is, on average no vessels (using the status quo capacity baseline) would be impacted by the proposal. Copyright © 2016 Elsevier B.V. All rights reserved.

Depth of Information Processing and Memory for Medical Facts.

ERIC Educational Resources Information Center

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

1995-01-01

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

A Machine Reading System for Assembling Synthetic Paleontological Databases

PubMed Central

Peters, Shanan E.; Zhang, Ce; Livny, Miron; Ré, Christopher

2014-01-01

Many aspects of macroevolutionary theory and our understanding of biotic responses to global environmental change derive from literature-based compilations of paleontological data. Existing manually assembled databases are, however, incomplete and difficult to assess and enhance with new data types. Here, we develop and validate the quality of a machine reading system, PaleoDeepDive, that automatically locates and extracts data from heterogeneous text, tables, and figures in publications. PaleoDeepDive performs comparably to humans in several complex data extraction and inference tasks and generates congruent synthetic results that describe the geological history of taxonomic diversity and genus-level rates of origination and extinction. Unlike traditional databases, PaleoDeepDive produces a probabilistic database that systematically improves as information is added. We show that the system can readily accommodate sophisticated data types, such as morphological data in biological illustrations and associated textual descriptions. Our machine reading approach to scientific data integration and synthesis brings within reach many questions that are currently underdetermined and does so in ways that may stimulate entirely new modes of inquiry. PMID:25436610

Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Tian; Icke, Ilknur; Dogdas, Belma; Parimal, Sarayu; Sampath, Smita; Forbes, Joseph; Bagchi, Ansuman; Chin, Chih-Liang; Chen, Antong

2017-02-01

In developing treatment of cardiovascular diseases, short axis cine MRI has been used as a standard technique for understanding the global structural and functional characteristics of the heart, e.g. ventricle dimensions, stroke volume and ejection fraction. To conduct an accurate assessment, heart structures need to be segmented from the cine MRI images with high precision, which could be a laborious task when performed manually. Herein a fully automatic framework is proposed for the segmentation of the left ventricle from the slices of short axis cine MRI scans of porcine subjects using a deep learning approach. For training the deep learning models, which generally requires a large set of data, a public database of human cine MRI scans is used. Experiments on the 3150 cine slices of 7 porcine subjects have shown that when comparing the automatic and manual segmentations the mean slice-wise Dice coefficient is about 0.930, the point-to-curve error is 1.07 mm, and the mean slice-wise Hausdorff distance is around 3.70 mm, which demonstrates the accuracy and robustness of the proposed inter-species translational approach.

Drop impact into a deep pool: vortex shedding and jet formation

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

Agbaglah, G.; Thoraval, M. -J.; Thoroddsen, S. T.

2015-02-01

One of the simplest splashing scenarios results from the impact of a single drop on a deep pool. The traditional understanding of this process is that the impact generates an axisymmetric sheet-like jet that later breaks up into secondary droplets. Recently it was shown that even this simplest of scenarios is more complicated than expected because multiple jets can be generated from a single impact event and there are transitions in the multiplicity of jets as the experimental parameters are varied. Here, we use experiments and numerical simulations of a single drop impacting on a deep pool to examine themore » transition from impacts that produce a single jet to those that produce two jets. Using high-speed X-ray imaging methods we show that vortex separation within the drop leads to the formation of a second jet long after the formation of the ejecta sheet. Using numerical simulations we develop a phase diagram for this transition and show that the capillary number is the most appropriate order parameter for the transition.« less

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.

Dystonia.

PubMed

De Pablo-Fernandez, Eduardo; Warner, Thomas T

2017-09-01

Dystonia is a clinically heterogeneous group of hyperkinetic movement disorders. Recent advances have provided a better understanding of these conditions with significant clinical impact. Peer reviewed journals and reviews. PubMed.gov. A recent consensus classification, including the assessment of phenomenology and identification of the dystonia syndromes, has provided a helpful tool for the clinical assessment. New forms of monogenic dystonia have been recently identified. Despite recent advances in the understanding of dystonia, treatment remains symptomatic in most patients. Recent advances in genetics have provided a better understanding of the potential pathogenic mechanisms involved in dystonia. Deep brain stimulation has shown to improve focal and combined forms of dystonia and its indications are constantly expanding. Growing understanding of the disease mechanisms involved will allow the development of targeted and disease-modifying therapies in the future. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Technical Report - FINAL

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

Barbara Luke, Director, UNLV Engineering Geophysics Laboratory

2007-04-25

Improve understanding of the earthquake hazard in the Las Vegas Valley and to assess the state of preparedness of the area's population and structures for the next big earthquake. 1. Enhance the seismic monitoring network in the Las Vegas Valley 2. Improve understanding of deep basin structure through active-source seismic refraction and reflection testing 3. Improve understanding of dynamic response of shallow sediments through seismic testing and correlations with lithology 4. Develop credible earthquake scenarios by laboratory and field studies, literature review and analyses 5. Refine ground motion expectations around the Las Vegas Valley through simulations 6. Assess current buildingmore » standards in light of improved understanding of hazards 7. Perform risk assessment for structures and infrastructures, with emphasis on lifelines and critical structures 8. Encourage and facilitate broad and open technical interchange regarding earthquake safety in southern Nevada and efforts to inform citizens of earthquake hazards and mitigation opportunities« less

Materials Requirements for Advanced Propulsion Systems

NASA Technical Reports Server (NTRS)

Whitaker, Ann F.; Cook, Mary Beth; Clinton, R. G., Jr.

2005-01-01

NASA's mission to "reach the Moon and Mars" will be obtained only if research begins now to develop materials with expanded capabilities to reduce mass, cost and risk to the program. Current materials cannot function satisfactorily in the deep space environments and do not meet the requirements of long term space propulsion concepts for manned missions. Directed research is needed to better understand materials behavior for optimizing their processing. This research, generating a deeper understanding of material behavior, can lead to enhanced implementation of materials for future exploration vehicles. materials providing new approaches for manufacture and new options for In response to this need for more robust materials, NASA's Exploration Systems Mission Directorate (ESMD) has established a strategic research initiative dedicated to materials development supporting NASA's space propulsion needs. The Advanced Materials for Exploration (AME) element directs basic and applied research to understand material behavior and develop improved materials allowing propulsion systems to operate beyond their current limitations. This paper will discuss the approach used to direct the path of strategic research for advanced materials to ensure that the research is indeed supportive of NASA's future missions to the moon, Mars, and beyond.

Control of unsteady separated flow associated with the dynamic pitching of airfoils

NASA Technical Reports Server (NTRS)

Ahmed, Sajeer

1991-01-01

Although studies have been done to understand the dependence of parameters for the occurrence of deep stall, studies to control the flow for sustaining lift for a longer time has been little. To sustain the lift for a longer time, an understanding of the development of the flow over the airfoil is essential. Studies at high speed are required to study how the flow behavior is dictated by the effects of compressibility. When the airfoil is pitched up in ramp motion or during the upstroke of an oscillatory cycle, the flow development on the upper surface of the airfoil and the formation of the vortex dictates the increase in lift behavior. Vortex shedding past the training edge decreases the lift. It is not clear what is the mechanism associated with the unsteady separation and vortex formation in present unsteady environment. To develop any flow control device, to suppress the vortex formation or delay separation, it is important that this mechanism be properly understood. The research activities directed toward understanding these questions are presented and the results are summarized.

Key Largo Limestone revisited: Pleistocene shelf-edge facies, Florida Keys, USA

USGS Publications Warehouse

Gray, Multer H.; Gischler, E.; Lundberg, J.; Simmons, K.R.; Shinn, E.A.

2002-01-01

New dates and analysis of 12 deep and 57 shallow cores allow a more detailed interpretation of the Pleistocene shelf edge of the Florida Platform as found in various facies of the Key Largo Limestone beneath the Florida Keys. In this study a three-phase evolution of the Quaternary units (Q1-Q5) of the Key Largo is presented with new subdivision of the Q5. (1) In the first phase, the Q1 and Q2 (perhaps deposited during oxygen-isotope stage 11) deep-water quartz-rich environment evolved into a shallow carbonate phase. (2) Subsequently, a Q3 (presumably corresponding to oxygen-isotope stage 9) flourishing reef and productive high-platform sediment phase developed. (3) Finally, a Q4 and Q5 (corresponding to oxygen-isotope stages 7 and 5) stabilization phase occured with reefs and leeward productive lagoons, followed by lower sea levels presenting a sequence of younger (isotope substages 5c, 5a) shelf-margin wedges, sediment veneers and outlier reefs. The Key Largo Limestone provides an accessible model of a carbonate shelf edge with fluctuating water depth, bordering a deep seaward basin for a period of at least 300 ka. During this time, at least four onlaps/offlaps, often separated by periods of karst development with associated diagenetic alterations, took place. The story presented by this limestone not only allows a better understanding of the history of south Florida but also aids in the interpretation of similar persistent shelf-edge sites bordering deep basins in other areas.

Medusa Sea Floor Monitoring System

NASA Technical Reports Server (NTRS)

Flynn, Michael

2004-01-01

The objective of the research described in this poster presentation is to develop technologies to enable fundamental research into understanding the potential for and limits to chemolithoautotrophic life. The Medusa Isosampler (isobaric sampler), for sampling fluids eminating from deep sea hydrothermal vents and cold seep sites analogous to extraterrestrial environments, is described by the presentation. The following instruments are integrated with the isosampler, and also described: in situ flow-through chemical sensor, intrinsic fluorescent-based microbial detector, isotope ratio spectral detector.

History of Science and Science Museums

NASA Astrophysics Data System (ADS)

Faria, Cláudia; Guilherme, Elsa; Gaspar, Raquel; Boaventura, Diana

2015-10-01

The activities presented in this paper, which are addressed to elementary school, are focused on the pioneering work of the Portuguese King Carlos I in oceanography and involve the exploration of the exhibits belonging to two different science museums, the Aquarium Vasco da Gama and the Maritime Museum. Students were asked to study fish adaptations to deep sea, through the exploration of a fictional story, based on historical data and based on the work of the King that served as a guiding script for all the subsequent tasks. In both museums, students had access to: historical collections of organisms, oceanographic biological sampling instruments, fish gears and ships. They could also observe the characteristics and adaptations of diverse fish species characteristic of deep sea. The present study aimed to analyse the impact of these activities on students' scientific knowledge, on their understanding of the nature of science and on the development of transversal skills. All students considered the project very popular. The results obtained suggest that the activity promoted not only the understanding of scientific concepts, but also stimulated the development of knowledge about science itself and the construction of scientific knowledge, stressing the relevance of creating activities informed by the history of science. As a final remark we suggest that the partnership between elementary schools and museums should be seen as an educational project, in which the teacher has to assume a key mediating role between the school and the museums.

New innovations: therapeutic opportunities for intellectual disabilities.

PubMed

Picker, Jonathan D; Walsh, Christopher A

2013-09-01

Intellectual disability is common and is associated with significant morbidity. Until the latter half of the 20th century, there were no efficacious treatments. Following initial breakthroughs associated with newborn screening and metabolic corrections, little progress was made until recently. With improved understanding of genetic and cellular mechanisms, novel treatment options are beginning to appear for a number of specific conditions. Fragile X and tuberous sclerosis offer paradigms for the development of targeted therapeutics, but advances in understanding of other disorders such as Down syndrome and Rett syndrome, for example, are also resulting in promising treatment directions. In addition, better understanding of the underlying neurobiology is leading to novel developments in enzyme replacement for storage disorders and adjunctive therapies for metabolic disorders, as well as potentially more generalizable approaches that target dysfunctional cell regulation via RNA and chromatin. Physiologic therapies, including deep brain stimulation and transcranial magnetic stimulation, offer yet another direction to enhance cognitive functioning. Current options and evolving opportunities for the intellectually disabled are reviewed and exemplified. Copyright © 2013 American Neurological Association.

Heterogeneous Sensor Data Exploration and Sustainable Declarative Monitoring Architecture: Application to Smart Building

NASA Astrophysics Data System (ADS)

Servigne, S.; Gripay, Y.; Pinarer, O.; Samuel, J.; Ozgovde, A.; Jay, J.

2016-09-01

Concerning energy consumption and monitoring architectures, our goal is to develop a sustainable declarative monitoring architecture for lower energy consumption taking into account the monitoring system itself. Our second is to develop theoretical and practical tools to model, explore and exploit heterogeneous data from various sources in order to understand a phenomenon like energy consumption of smart building vs inhabitants' social behaviours. We focus on a generic model for data acquisition campaigns based on the concept of generic sensor. The concept of generic sensor is centered on acquired data and on their inherent multi-dimensional structure, to support complex domain-specific or field-oriented analysis processes. We consider that a methodological breakthrough may pave the way to deep understanding of voluminous and heterogeneous scientific data sets. Our use case concerns energy efficiency of buildings to understand relationship between physical phenomena and user behaviors. The aim of this paper is to give a presentation of our methodology and results concerning architecture and user-centric tools.

Research, development and demonstration of nickel-zinc batteries for electric vehicle propulsion

NASA Astrophysics Data System (ADS)

1980-06-01

The feasibility of the nickel zinc battery for electric vehicle propulsion is discussed. The program is divided into seven distinct but highly interactive tasks collectively aimed at the development and commercialization of nickel zinc technology. These basic technical tasks are separator development, electrode development, product design and analysis, cell/module battery testing, process development, pilot manufacturing, and thermal manufacturing, and thermal management. Significant progress has been made in the understanding of separator failure mechanisms, and a generic category of materials has been specified for the 300+ deep discharge applications. Shape change has been reduced significantly. Progress in the area of thermal management was significant, with the development of a model that accurately represents heat generation and rejection rates during battery operation.

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

Deep Learning for Space Weather Prediction

NASA Astrophysics Data System (ADS)

Pauly, M.; Shah, Y.; Cheung, C. M. M.

2016-12-01

Through the use of our current fleet of in-orbit solar observatories, we have accumulated a vast amount of high quality solar event data which has greatly helped us to understand the underlying mechanisms of how the Sun works. However, we still lack an accurate and robust system for autonomously predicting solar eruptive events, which are known to cause geomagnetic storms, disturbances in electrical grids, radio black outs, increased drag on satellites, and increased radiation exposure to astronauts. We address the need for a flare prediction system by developing deep neural networks (DNNs) trained with solar data taken by the Helioseismic & Magnetic Imager (HMI) and Atmospheric Imaging Assembly (AIA) instruments onboard the Solar Dynamics Observatory and X-ray flux data taken by the GOES satellites. We describe the architecture of the DNNs trained and compare the performance between different implementations.

Long term seismic noise acquisition and analysis in the Homestake mine with tunable monolithic sensors

NASA Astrophysics Data System (ADS)

Acernese, Fausto; De Rosa, Rosario; De Salvo, Riccardo; Giordano, Gerardo; Harms, Jan; Mandic, Vuk; Sajeva, Angelo; Trancynger, Thomas; Barone, Fabrizio

2009-09-01

In this paper we describe the scientific data recorded along one month of data taking of two mechanical monolithic horizontal sensor prototypes located in a blind-ended (side) tunnel 2000 ft deep in the Homestake (South Dakota, USA) mine chosen to host the Deep Underground Science and Engineering Laboratory (DUSEL). The two mechanical monolithic sensors, developed at the University of Salerno, are placed, in thermally insulating enclosures, onto concrete slabs connected to the bedrock, and behind a sound-proofing wall. The main goal of this experiment is to characterize the Homestake site in the frequency band 10-4 ÷ 30 H z and to estimate the level of Newtonian noise, providing also the necessary preliminary information to understand the feasibility of underground gravitational-wave interferometers sensitive at 1 H z and below.

Numerical and experimental evidence of the inter-blade cavitation vortex development at deep part load operation of a Francis turbine

NASA Astrophysics Data System (ADS)

Yamamoto, K.; Müller, A.; Favrel, A.; Landry, C.; Avellan, F.

2016-11-01

Francis turbines are subject to various types of the cavitation flow depending on the operating conditions. In order to compensate for the stochastic nature of renewable energy sources, it is more and more required to extend the operating range of the generating units, from deep part load to full load conditions. In the deep part load condition, the formation of cavitation vortices in the turbine blade to blade channels called inter-blade cavitation vortex is often observed. The understanding of the dynamic characteristics of these inter-blade vortices and their formation mechanisms is of key importance in an effort of developing reliable flow simulation tools. This paper reports the numerical and experimental investigations carried out in order to establish the vortex characteristics, especially the inception and the development of the vortex structure. The unsteady RANS simulation for the multiphase flow is performed with the SST- SAS turbulence model by using the commercial flow solver ANSYS CFX. The simulation results in terms of the vortex structure and the cavitation volume are evaluated by comparing them to the flow visualizations of the blade channel acquired through a specially instrumented guide vane as well as from the downstream of the runner across the draft tube cone. The inter-blade cavitation vortex is successfully captured by the simulation and both numerical and experimental results evidence that the inter-blade vortices are attached to the runner hub.

The horizontal brain slice preparation: a novel approach for visualizing and recording from all layers of the tadpole tectum.

PubMed

Hamodi, Ali S; Pratt, Kara G

2015-01-01

The Xenopus tadpole optic tectum is a multisensory processing center that receives direct visual input as well as nonvisual mechanosensory input. The tectal neurons that comprise the optic tectum are organized into layers. These neurons project their dendrites laterally into the neuropil where visual inputs target the distal region of the dendrite and nonvisual inputs target the proximal region of the same dendrite. The Xenopus tadpole tectum is a popular model to study the development of sensory circuits. However, whole cell patch-clamp electrophysiological studies of the tadpole tectum (using the whole brain or in vivo preparations) have focused solely on the deep-layer tectal neurons because only neurons of the deep layer are visible and accessible for whole cell electrophysiological recordings. As a result, whereas the development and plasticity of these deep-layer neurons has been well-studied, essentially nothing has been reported about the electrophysiology of neurons residing beyond this layer. Hence, there exists a large gap in our understanding about the functional development of the amphibian tectum as a whole. To remedy this, we developed a novel isolated brain preparation that allows visualizing and recording from all layers of the tectum. We refer to this preparation as the "horizontal brain slice preparation." Here, we describe the preparation method and illustrate how it can be used to characterize the electrophysiology of neurons across all of the layers of the tectum as well as the spatial pattern of synaptic input from the different sensory modalities. Copyright © 2015 the American Physiological Society.

Superparamagnetic Iron Oxide Nanoparticles: Promises for Diagnosis and Treatment of Multiple Sclerosis

PubMed Central

2011-01-01

Smart superparamagnetic iron oxide nanoparticles (SPIONs) are the most promising candidate for theragnosis (i.e., diagnosis and treatment) of multiple sclerosis. A deep understanding of the dynamics of the in vivo neuropathology of multiple sclerosis can be achieved by improving the efficiency of various medical techniques (e.g., positron emission tomography and magnetic resonance imaging) using multimodal SPIONs. In this Review, recent advances and challenges in the development of smart SPIONs for theragnostic applications are comprehensively described. In addition, critical outlines of emerging developments are provided from the points of view of both clinicians and nanotechnologists. PMID:22778862

Towards a model-based understanding of the Mediterranean circulation during the Messinian Salinity Crisis

NASA Astrophysics Data System (ADS)

Simon, Dirk; Meijer, Paul

2016-04-01

Today, the Atlantic-Mediterranean gateway (the Strait of Gibraltar) and the strong evaporative loss in the east let the Mediterranean Sea attain a salinity of 2-3 g/l higher than the Atlantic Ocean. During the winter months, strong cooling of surface waters in the north forms deep water, which mixes the Mediterranean, while during summer the water column is stratified. During the Messinian Salinity Crisis (MSC, 5.97-5.33Ma) the salt concentration was high enough to reach the saturation of gypsum (~130-160 g/l) and halite (~350 g/l). This caused large deposits of these evaporites all over the basin, capturing 6% of the World Ocean salt within the Mediterranean at the time. Although several mechanisms have been proposed as to how the Mediterranean circulation might have functioned, these mechanisms have yet to be rooted in physics and tested quantitatively. Understanding circulation during the MSC becomes particularly important when comparing Mediterranean marginal to deep basins. On the one hand, many of the marginal basins in the Mediterranean are well studied, like the Sorbas basin (Spain) or the Vena del Gesso basin (Italy). On the other hand, the deep Mediterranean is less well studied, as no full record of the whole deep sequence exists. This makes it very complicated to correlate marginal and deep basin records. Here we are presenting the first steps in working towards a physics-based understanding of the mixing and stratification bahaviour of the Mediterranean Sea during the MSC. The final goal is to identify the physical mechanism needed to form such a salt brine and to understand how it differs from today's situation. We are hoping to compare our results to, and learn from, the much smaller but best available analog to the MSC, the Dead Sea, where recent overturning has been documented.

Deep and Surface Learning in Problem-Based Learning: A Review of the Literature

ERIC Educational Resources Information Center

Dolmans, Diana H. J. M.; Loyens, Sofie M. M.; Marcq, Hélène; Gijbels, David

2016-01-01

In problem-based learning (PBL), implemented worldwide, students learn by discussing professionally relevant problems enhancing application and integration of knowledge, which is assumed to encourage students towards a deep learning approach in which students are intrinsically interested and try to understand what is being studied. This review…

Measuring Deep, Reflective Comprehension and Learning Strategies: Challenges and Successes

ERIC Educational Resources Information Center

McNamara, Danielle S.

2011-01-01

There is a heightened understanding that metacognition and strategy use are crucial to deep, long-lasting comprehension and learning, but their assessment is challenging. First, students' judgments of what their abilities and habits and measurements of their performance often do not match. Second, students tend to learn and comprehend differently…

Complex Cloud and Radiative Processes Unfolding at the Earth's Terminator: A Unique Perspective from the Proposed Deep Space Gateway

NASA Astrophysics Data System (ADS)

Davis, A. B.; Marshak, A.

2018-02-01

The Deep Space Gateway offers a unique vantage for Earth observation using reflected sunlight: day/night or night/day terminators slowly marching across the disc. It's an opportunity to improve our understanding of clouds at that key moment in their daily cycle.

Changes in VEGF and nitric oxide after deep dermal injury in the female, red Duroc pig-further similarities between female, Duroc scar and human hypertrophic scar.

PubMed

Zhu, Kathy Q; Engrav, Loren H; Armendariz, Rebecca; Muangman, Pornprom; Klein, Matthew B; Carrougher, Gretchen J; Deubner, Heike; Gibran, Nicole S

2005-02-01

Despite decades of research, our understanding of human hypertrophic scar is limited. A reliable animal model could significantly increase our understanding. We previously confirmed similarities between scarring in the female, red, Duroc pig and human hypertrophic scarring. The purpose of this study was to: (1) measure vascular endothelial growth factor (VEGF) and nitric oxide (NO) levels in wounds on the female Duroc; and (2) to compare the NO levels to those reported for human hypertrophic scar. Shallow and deep wounds were created on four female Durocs. VEGF levels were measured using ELISA and NO levels with the Griess reagent. VEGF and NO levels were increased in deep wounds at 10 days when compared to shallow wounds (p < 0.05). At 15 weeks, VEGF and NO levels had returned to the level of shallow wounds. At 21 weeks, VEGF and NO levels had declined below baseline levels in deep wounds and the NO levels were significantly lower (p < 0.01). We found that VEGF and NO exhibit two distinctly different temporal patterns in shallow and deep wounds on the female Durocs. Furthermore, NO is decreased in female, Duroc scar as it is in human, hypertrophic scar further validating the usefulness of the model.

Soil carbon stocks and their rates of accumulation and loss in a boreal forest landscape

USGS Publications Warehouse

Rapalee, G.; Trumbore, S.E.; Davidson, E.A.; Harden, J.W.; Veldhuis, H.

1998-01-01

Boreal forests and wetlands are thought to be significant carbon sinks, and they could become net C sources as the Earth warms. Most of the C of boreal forest ecosystems is stored in the moss layer and in the soil. The objective of this study was to estimate soil C stocks (including moss layers) and rates of accumulation and loss for a 733 km2 area of the BOReal Ecosystem-Atmosphere Study site in northern Manitoba, using data from smaller-scale intensive field studies. A simple process-based model developed from measurements of soil C inventories and radiocarbon was used to relate soil C storage and dynamics to soil drainage and forest stand age. Soil C stocks covary with soil drainage class, with the largest C stocks occurring in poorly drained sites. Estimated rates of soil C accumulation or loss are sensitive to the estimated decomposition constants for the large pool of deep soil C, and improved understanding of deep soil C decomposition is needed. While the upper moss layers regrow and accumulate C after fires, the deep C dynamics vary across the landscape, from a small net sink to a significant source. Estimated net soil C accumulation, averaged for the entire 733 km2 area, was 20 g C m-2 yr-1 (28 g C m-2 yr-1 accumulation in surface mosses offset by 8 g C m-2 yr-1 lost from deep C pools) in a year with no fire. Most of the C accumulated in poorly and very poorly drained soils (peatlands and wetlands). Burning of the moss layer in only 1% of uplands would offset the C stored in the remaining 99% of the area. Significant interannual variability in C storage is expected because of the irregular occurrence of fire in space and time. The effects of climate change and management on fire frequency and on decomposition of immense deep soil C stocks are key to understanding future C budgets in boreal forests.

Subsurface geology of the Lusi region: preliminary results from a comprehensive seismic-stratigraphic study.

NASA Astrophysics Data System (ADS)

Moscariello, Andrea; Do Couto, Damien; Lupi, Matteo; Mazzini, Adriano

2016-04-01

We investigate the subsurface data of a large sector in the Sidoarjo district (East Java, Indonesia) where the sudden catastrophic Lusi eruption started the 26th May 2006. Our goal is to understand the stratigraphic and structural features which can be genetically related to the surface manifestations of deep hydrothermal fluids and thus allow us to predict possible future similar phenomena in the region. In the framework of the Lusi Lab project (ERC grant n° 308126) we examined a series of densely spaced 2D reflection commercial seismic lines This allowed the reconstruction of the lateral variability of key stratigraphic horizons as well as the main tectonic features. In particular, we shed light on the deep structure of the Watukosek fault system and the associated fracture corridors crossing the entire stratigraphic successions. To the South-West, when approaching the volcanic complex, we could identify a clear contrast in seismic facies between chaotic volcanoclastic wedges and clastic-prone sedimentary successions as well as between the deeper stratigraphic units consisting of carbonates and lateral shales units. The latter show possible ductile deformation associated to fault-controlled diapirism which control in turns deformation of overlying stratigraphic units and deep geo-fluids circulation. Large collapse structures recognized in the study area (e.g. well PRG-1) are interpreted as the results of shale movement at depth. Similarly to Lusi, vertical deformation zones ("pipes"), likely associated with deeply rooted strike-slip systems seem to be often located at the interface between harder carbonate rocks forming isolated build ups and the laterally nearby clastic (shale-prone)-units. The mechanisms of deformation of structural features (strike vs dip slip systems) which may affect either the basement rock or the overlying deeper stratigraphic rocks is also being investigated to understand the relationship between deep and shallower (i.e. meteoric) fluid circulation. Seismic stratigraphic study of the basin margin (closer to volcanic accumulations) will also allow reconstructing the relationships between present and past volcanic activity recorded in the deep subsurface with the genesis of piercement structures and development of vertical deformation zones

Ecosystem Services: a Framework for Environmental Management of the Deep Sea

NASA Astrophysics Data System (ADS)

Le, J. T.; Levin, L. A.; Carson, R. T.

2016-02-01

As demand for deep-sea resources rapidly expands in the food, energy, mineral, and pharmaceutical sectors, it has become increasingly clear that a regulatory structure for extracting these resources is not yet in place. There are jurisdictional gaps and a lack of regulatory consistency regarding what aspects of the deep sea need protection and what requirements might help guarantee that protection. Given the mining sector's intent to exploit seafloor massive sulphides, Mn nodules, cobalt crusts, and phosphorites in the coming years, there is an urgent need for deep-ocean environmental management. Here, we propose an ecosystem services-based framework to inform decisions and best practices regarding resource exploitation, and to guide baseline studies, preventative actions, monitoring, and remediation. With policy in early stages of development, an ecosystem services approach has the potential to serve as an overarching framework that takes protection of natural capital provided by the environment into account during the decision-making process. We show how an ecosystem services approach combined with economic tools, such as benefit transfer techniques, should help illuminate issues where there are direct conflicts among different industries, and between industry and conservation. We argue for baseline and monitoring measurements and metrics that inform about deep-sea ecosystem services that would be impaired by mining, and discuss ways to incorporate the value of those losses into decision making, mitigation measures, and ultimately product costs. This proposal is considered relative to current International Seabed Authority recommendations and contractor practices, and new actions are proposed. An ecosystem services-based understanding of how these systems work and their value to society can improve sustainability and stewardship of the deep ocean.

[Distribution Characteristics and Source of Fluoride in Groundwater in Lower Plain Area of North China Plain: A Case Study in Nanpi County].

PubMed

Kong, Xiao-le; Wang, Shi-qin; Zhao, Huan; Yuan, Rui-qiang

2015-11-01

There is an obvious regional contradiction between water resources and agricultural produce in lower plain area of North China, however, excessive fluorine in deep groundwater further limits the use of regional water resources. In order to understand the spatial distribution characteristics and source of F(-) in groundwater, study was carried out in Nanpi County by field survey and sampling, hydrogeochemical analysis and stable isotopes methods. The results showed that the center of low fluoride concentrations of shallow groundwater was located around reservoir of Dalang Lake, and centers of high fluoride concentrations were located in southeast and southwest of the study area. The region with high fluoride concentration was consistent with the over-exploitation region of deep groundwater. Point source pollution of subsurface drainage and non-point source of irrigation with deep groundwater in some regions were the main causes for the increasing F(-) concentrations of shallow groundwater in parts of the sampling sites. Rock deposition and hydrogeology conditions were the main causes for the high F(-) concentrations (1.00 mg x L(-1), threshold of drinking water quality standard in China) in deep groundwater. F(-) released from clay minerals into the water increased the F(-) concentrations in deep groundwater because of over-exploitation. With the increasing exploitation and utilization of brackish shallow groundwater and the compressing and restricting of deep groundwater exploitation, the water environment in the middle and east lower plain area of North China will undergo significant change, and it is important to identify the distribution and source of F(-) in surface water and groundwater for reasonable development and use of water resources in future.

Physiologic and behavioral effects of papoose board on anxiety in dental patients with special needs.

PubMed

Chen, Hsin-Yung; Yang, Hsiang; Chi, Huang-Ju; Chen, Hsin-Ming

2014-02-01

Anxiety induced by dental treatment can become a serious problem, especially for patients with special needs. Application of deep touch pressure, which is a sensory adaptation technique, may ameliorate anxiety in disabled patients. However, few empiric studies have investigated the possible links between the clinical effects of deep touch pressure and its behavioral and physiologic aspects. Equally little progress has been made concerning theoretical development. The current study is a crossover intervention trial to investigate the behavioral and physiological effects of deep touch pressure for participants receiving dental treatment. Nineteen disabled participants, who were retrospectively subclassified for positive trend or negative trend, were recruited to receive the papoose board as an application of deep touch pressure. Quantitative analyses of behavioral assessments and physiological measurements, including electrodermal activity and heart rate variability, were conducted. We sought to understand the modulation of the autonomic nervous system and the orchestration of sympathetic and parasympathetic (PsNS) nervous systems. Behavioral assessments reported that higher levels of anxiety were induced by the dental treatment for participants with both groups of positive and negative trends. Although no significant differences were found in the SNS activity, physiologic responses indicated that significantly changes of PsNS activity were observed under the stress condition (dental treatment) when deep touch pressure intervention was applied, especially for participants in the group of positive trend. Our results suggest that the PsNS activation plays a critical role in the process of ANS modulation. This study provides not only physiologic evidence for the modulation effects of deep touch pressure on stressful conditions in dental environments but also the evidence that the application of papoose board, as a sensory adaptation technique, is not harmful for dental patients with special needs. Copyright © 2012. Published by Elsevier B.V.

The Narrow Road to the Deep Past: In Search of the Chemistry of the Origin of Life.

PubMed

Szostak, Jack W

2017-09-04

The sequence of events that gave rise to the first life on our planet took place in the Earth's deep past, seemingly forever beyond our reach. Perhaps for that very reason the idea of reconstructing our ancient story is tantalizing, almost irresistible. Understanding the processes that led to synthesis of the chemical building blocks of biology and the ways in which these molecules self-assembled into cells that could grow, divide and evolve, nurtured by a rich and complex environment, seems at times insurmountably difficult. And yet, to my own surprise, simple experiments have revealed robust processes that could have driven the growth and division of primitive cell membranes. The nonenzymatic replication of RNA is more complicated and less well understood, but here too significant progress has come from surprising developments. Even our efforts to combine replicating compartments and genetic materials into a full protocell model have moved forward in unexpected ways. Fortunately, many challenges remain before we will be close to a full understanding of the origin of life, so the future of research in this field is brighter than ever! © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

BIOMETORE Project - Studying the Biodiversity in the Northeastern Atlantic Seamounts

NASA Astrophysics Data System (ADS)

Dos Santos, A.; Biscoito, M.; Campos, A.; Tuaty Guerra, M.; Meneses, G.; Santos, A. M. P. A.

2016-02-01

Understanding the deep-sea ecosystem functioning is a key issue in the study of ocean sciences. Bringing together researchers from several scientific domains, the BIOMETORE project aims to the increase knowledge on deep-sea ecosystems and biodiversity at the Atlantic seamounts of the Madeira-Tore and Great Meteor geological complexes. The project outputs will provide important information for the understanding and sustainable management of the target seamount ecosystems, thus contributing to fulfill knowledge gaps on their biodiversity, from bacteria to mammals, and food webs, as well as to promote future sustainable fisheries and sea-floor integrity. The plan includes the realization of eight multidisciplinary surveys, four done during the summer of 2015 and another four planned for the same season of 2016, in target seamounts: the Gorringe bank, the Josephine, and others in the Madeira-Tore, and selected ones in the Greta Meteor (northeastern Atlantic Ocean). The surveys cover a number of scientific areas in the domains of oceanography, ecology, integrative taxonomy, geology, fisheries and spatial mapping. We present and discuss BIOMETORE developments, the preliminary results from the four 2015 summer surveys, and the planning of the next four surveys.

Multidirectional Cosmic Ray Ion Detector for Deep Space CubeSats

NASA Technical Reports Server (NTRS)

Wrbanek, John D.; Wrbanek, Susan Y.

2016-01-01

Understanding the nature of anisotropy of solar energetic protons (SEPs) and galactic cosmic ray (GCR) fluxes in the interplanetary medium is crucial in characterizing time-dependent radiation exposure in interplanetary space for future exploration missions. NASA Glenn Research Center has proposed a CubeSat-based instrument to study solar and cosmic ray ions in lunar orbit or deep space. The objective of Solar Proton Anisotropy and Galactic cosmic ray High Energy Transport Instrument (SPAGHETI) is to provide multi-directional ion data to further understand anisotropies in SEP and GCR flux. The instrument is to be developed using large area detectors fabricated from high density, high purity silicon carbide (SiC) to measure linear energy transfer (LET) of ions. Stacks of these LET detectors are arranged in a CubeSat at orthogonal directions to provide multidirectional measurements. The low-noise, thermally-stable nature of silicon carbide and its radiation tolerance allows the multidirectional array of detector stacks to be packed in a 6U CubeSat without active cooling. A concept involving additional coincidence/anticoincidence detectors and a high energy Cherenkov detector is possible to further expand ion energy range and sensitivity.

Species replacement dominates megabenthos beta diversity in a remote seamount setting.

PubMed

Victorero, Lissette; Robert, Katleen; Robinson, Laura F; Taylor, Michelle L; Huvenne, Veerle A I

2018-03-07

Seamounts are proposed to be hotspots of deep-sea biodiversity, a pattern potentially arising from increased productivity in a heterogeneous landscape leading to either high species co-existence or species turnover (beta diversity). However, studies on individual seamounts remain rare, hindering our understanding of the underlying causes of local changes in beta diversity. Here, we investigated processes behind beta diversity using ROV video, coupled with oceanographic and quantitative terrain parameters, over a depth gradient in Annan Seamount, Equatorial Atlantic. By applying recently developed beta diversity analyses, we identified ecologically unique sites and distinguished between two beta diversity processes: species replacement and changes in species richness. The total beta diversity was high with an index of 0.92 out of 1 and was dominated by species replacement (68%). Species replacement was affected by depth-related variables, including temperature and water mass in addition to the aspect and local elevation of the seabed. In contrast, changes in species richness component were affected only by the water mass. Water mass, along with substrate also affected differences in species abundance. This study identified, for the first time on seamount megabenthos, the different beta diversity components and drivers, which can contribute towards understanding and protecting regional deep-sea biodiversity.

Identity development in upper-level physics students: transitions in and out of physics

NASA Astrophysics Data System (ADS)

Irving, Paul

2016-03-01

In this era of unprecedented attention from the White House and Congress, the STEM community must rise to the challenge of recruiting and retaining students to achieve the mandate of producing one million additional college graduates with degrees in STEM. However, the number of students choosing to pursue and persist with physics as a degree has had a stagnated growth rate when compared to other STEM fields, and some institutions are experiencing dramatic shifts in the demographics of the students entering their programs. The development of a subject-specific identity is a strong influence on students' persistence in a discipline and is a productive lens from which to understand the stagnated growth rate of physics majors and how to support a shift in student demographics. In this presentation, ongoing research is presented that aims to understand identity development in STEM with a focus on the transition from physics student to physicist. Community development and exposure to authentic practice are established as crucial factors that contribute to the development of a professional identity. How these findings can be implemented into course design is discussed with an outline of the P3 learning environment. The P3 learning environment blends the regular focus of reform-based teaching practices on deep conceptual understanding with a focus on students obtaining understanding through engagement with authentic scientific practices. By establishing and studying learning environments similar to P3 we can further explore the development of subject-specific identity while also developing effective teaching practices.

WRF nested large-eddy simulations of deep convection during SEAC4RS

NASA Astrophysics Data System (ADS)

Heath, Nicholas Kyle

Deep convection is an important component of atmospheric circulations that affects many aspects of weather and climate. Therefore, improved understanding and realistic simulations of deep convection are critical to both operational and climate forecasts. Large-eddy simulations (LESs) often are used with observations to enhance understanding of convective processes. This study develops and evaluates a nested-LES method using the Weather Research and Forecasting (WRF) model. Our goal is to evaluate the extent to which the WRF nested-LES approach is useful for studying deep convection during a real-world case. The method was applied on 2 September 2013, a day of continental convection having a robust set of ground and airborne data available for evaluation. A three domain mesoscale WRF simulation is run first. Then, the finest mesoscale output (1.35 km grid length) is used to separately drive nested-LES domains with grid lengths of 450 and 150 m. Results reveal that the nested-LES approach reasonably simulates a broad spectrum of observations, from reflectivity distributions to vertical velocity profiles, during the study period. However, reducing the grid spacing does not necessarily improve results for our case, with the 450 m simulation outperforming the 150 m version. We find that simulated updrafts in the 150 m simulation are too narrow to overcome the negative effects of entrainment, thereby generating convection that is weaker than observed. Increasing the sub-grid mixing length in the 150 m simulation leads to deeper, more realistic convection, but comes at the expense of delaying the onset of the convection. Overall, results show that both the 450 m and 150 m simulations are influenced considerably by the choice of sub-grid mixing length used in the LES turbulence closure. Finally, the simulations and observations are used to study the processes forcing strong midlevel cloud-edge downdrafts that were observed on 2 September. Results suggest that these downdrafts are forced by evaporative cooling due to mixing near cloud edge and by vertical perturbation pressure gradient forces acting to restore mass continuity around neighboring updrafts. We conclude that the WRF nested-LES approach provides an effective method for studying deep convection for our real-world case. The method can be used to provide insight into physical processes that are important to understanding observations. The WRF nested-LES approach could be adapted for other case studies in which high-resolution observations are available for validation.

> Exploring the Scandinavian Mountain Belt by Deep Drilling (COSC)

NASA Astrophysics Data System (ADS)

Juhlin, C.; Gee, D. G.; Lorenz, H.; Pascal, C.; Pedersen, K.; Tsang, C.-F.

2012-04-01

The Collisional Orogeny in the Scandinavian Caledonides (COSC) project proposes to drill two fully cored scientific boreholes, both to c. 2.5 km depth, in the Swedish Caledonides, one near the town of Åre (COSC 1) and the other further east (COSC 2). Together they will provide a c. 5 km deep high-resolution mid-crustal section through this major mid-Palaeozoic orogen. Main project objectives include (i) improved understanding of mountain building processes (orogeny), (ii) investigation of the geothermal gradient and its response to palaeoclimatic influences, (iii) the hydrogeological-hydrochemical state of the mountain belt, (iv) the deep biosphere in the metamorphic rocks and crystalline basement, and (v) calibration of surface geophysics and geology. The Caledonide Orogen is comparable in size and many other respects to today's Himalayan mountain belt. Silurian collision with underthrusting of the paleo-continent Baltica below Laurentia resulted in widespread formation of eclogite. Major allochthons were transported many hundreds of kilometers onto the Baltoscandian Platform, including high-grade metamorphic rocks and migmatites which were generated during continental margin subduction and emplaced ductilely at mid-crustal levels. COSC will provide detailed insight into mid-Palaeozoic mountain building processes and further our understanding of past, present and future orogen dynamics. Located in a key-area for Caledonian geology, it is close to a major geophysical transect across the mountain belt which has been complemented recently with high-resolution reflection seismics and aerogeophysics for site-selection. The COSC research program is being developed by five working groups, geology, geophysics, geothermics, hydrogeology and microbiology. It has direct relevance for society by improving our understanding of mountain building processes, hydrological-hydrochemical regimes in mountain areas and Precambrian shields, deep subsurface conditions for underground engineering, ore genesis and assessment of geothermal potential. After a general scientific workshop supported by ICDP in 2010, the hydrogeological aspects of deep drilling were the topic of a separate workshop last year; orogen dynamics will provide a focus at EGU; and geothermics research will be addressed at a workshop in Autumn 2012. The geothermics workshop will be announced on the ICDP homepage. Partial funding for the drilling has been achieved through national sources and ICDP. Additional funding (c. 500000€) is being sought to allow drilling to commence in 2013. Scientific and financial partners, both from academia and industry, are welcome to the project. The presentation will review the current status of the COSC project and the research leading up to the site selection for COSC 1.

The development of deep karst in the anticlinal aquifer structure based on the coupling of multistage flow systems

NASA Astrophysics Data System (ADS)

Xu, M.; Zhong, L.; Yang, Y.

2017-12-01

Under the background of neotectonics, the multistage underground flow system has been form due the different responses of main stream and tributaries to crust uplift. The coupling of multistage underground flow systems influences the development of karst thoroughly. At first, the research area is divided into vadose area, shunted area and exorheic area based on the development characteristics of transverse valley. Combining the controlling-drain action with topographic index and analyzing the coupling features of multistage underground flow system. And then, based on the coupling of multistage underground flow systems, the characteristics of deep karst development were verified by the lossing degree of surface water, water bursting and karst development characteristics of tunnels. The vadose area is regional water system based, whose deep karst developed well. It resulted the large water inflow of tunnels and the surface water drying up. The shunted area, except the region near the transverse valleys, is characterized by regional water system. The developed deep karst make the surface water connect with deep ground water well, Which caused the relatively large water flow of tunnels and the serious leakage of surface water. The deep karst relatively developed poor in the regions near transverse valleys which is characterized by local water system. The exorheic area is local water system based, whose the deep karst developed poor, as well as the connection among surface water and deep ground water. It has result in the poor lossing of the surface water under the tunnel construction. This study broadens the application field of groundwater flow systems theory, providing a new perspective for the study of Karst development theory. Meanwhile it provides theoretical guidance for hazard assessment and environmental negative effect in deep-buried Karst tunnel construction.

Towards deep learning with segregated dendrites

PubMed Central

Guerguiev, Jordan; Lillicrap, Timothy P

2017-01-01

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

Towards deep learning with segregated dendrites.

PubMed

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

2017-12-05

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

Possible seasonality in large deep-focus earthquakes

NASA Astrophysics Data System (ADS)

Zhan, Zhongwen; Shearer, Peter M.

2015-09-01

Large deep-focus earthquakes (magnitude > 7.0, depth > 500 km) have exhibited strong seasonality in their occurrence times since the beginning of global earthquake catalogs. Of 60 such events from 1900 to the present, 42 have occurred in the middle half of each year. The seasonality appears strongest in the northwest Pacific subduction zones and weakest in the Tonga region. Taken at face value, the surplus of northern hemisphere summer events is statistically significant, but due to the ex post facto hypothesis testing, the absence of seasonality in smaller deep earthquakes, and the lack of a known physical triggering mechanism, we cannot rule out that the observed seasonality is just random chance. However, we can make a testable prediction of seasonality in future large deep-focus earthquakes, which, given likely earthquake occurrence rates, should be verified or falsified within a few decades. If confirmed, deep earthquake seasonality would challenge our current understanding of deep earthquakes.

Interannual variability (1979-2013) of the North-Western Mediterranean deep water mass formation: past observation reanalysis and coupled ocean-atmosphere high-resolution modelling

NASA Astrophysics Data System (ADS)

Somot, Samuel; Houpert, Loic; Sevault, Florence; Testor, Pierre; Bosse, Anthony; Durrieu de Madron, Xavier; Dubois, Clotilde; Herrmann, Marine; Waldman, Robin; Bouin, Marie-Noëlle; Cassou, Christophe

2015-04-01

The North-Western Mediterranean Sea is known as one of the only place in the world where open-sea deep convection occurs (often up to more than 2000m) with the formation of the Western Mediterranean Deep Water (WMDW). This phenomena is mostly driven by local preconditioning of the water column and strong buoyancy losses during Winter. At the event scale, the WMDW formation is characterized by different phases (preconditioning, strong mixing, restratification and spreading), intense air-sea interaction and strong meso-scale activity but, on a longer time scale, it also shows a large interannual variability and may be strongly affected by climate change with impact on the regional biogeochemistry. Therefore observing, simulating and understanding the long-term temporal variability of the North-Western Mediterranean deep water formation is still today a very challenging task. We try here to tackle those issues thanks to (1) a thorough reanalysis of past in-situ observations (CTD, Argo, surface and deep moorings, gliders) and (2) an ERA-Interim driven simulation using a recently-developed fully coupled Regional Climate System Model (CNRM-RCSM4, Sevault et al. 2014). The multi-decadal simulation (1979-2013) is designed to be temporally and spatially homogeneous with a realistic chronology, a high resolution representation of both the regional ocean and atmosphere, specific initial conditions, a long-term spin-up and a full ocean-atmosphere coupling without constraint at the air-sea interface. The observation reanalysis allows to reconstruct interannual time series of deep water formation indicators (ocean surface variables, mixed layer depth, surface of the convective area, dense water volumes and characteristics of the deep water). Using the observation-based indicators and the model outputs, the 34 Winters of the period 1979-2013 are analysed in terms of weather regimes, related Winter air-sea fluxes, ocean preconditioning, mixed layer depth, surface of the convective area, deep water formation rate and long-term evolution of the deep water hydrology.

Oxygen uptake and vertical transport during deep convection events

NASA Astrophysics Data System (ADS)

Sun, D.; Ito, T.; Bracco, A.

2016-02-01

Dissolved oxygen (O2) is essential for the chemistry and living organisms of the oceans. O2 is consumed in the interior ocean due to the respiration of organic matter, and must be replenished by physical ventilation with the O2-rich surface waters. The O2 supply to the deep waters happens only through the subduction and deep convection during cold seasons at high latitude oceans. The Labrador Sea is one of the few regions where deep ventilation occurs. According to observational and modeling studies, the intensity, duration and timing of deep convection events have varied significantly on the interannual and decadal timescales. In this study we develop a theoretical framework to understand the air-sea transfer of O2 during open-ocean deep convection events. The theory is tested against a suite of numerical integrations using MITgcm in non-hydrostatic configuration including the parameterization of diffusive and bubble mediated gas transfer. Forced with realistic air-sea buoyancy fluxes, the model can reproduce the evolution of temperature, salinity and dissolved O2 observed by ARGO floats in the Labrador Sea. Idealized sensitivity experiments are performed changing the intensity and duration of the buoyancy forcing as well as the wind speed for the gas exchange parameterizations. The downward transport of O2 results from the combination of vertical homogenization of existing O2 and the uptake from the air-sea flux. The intensity of the buoyancy forcing controls the vertical extent of convective mixing which brings O2 to the deep ocean. Integrated O2 uptake increases with the duration of convection even when the total buoyancy loss is held constant. The air-sea fluxes are highly sensitive to the wind speed especially for the bubble injection flux, which is a major addition to the diffusive flux under strong winds. However, the bubble injection flux can be partially compensated by the diffusive outgassing in response to the elevated saturation state. Under strong buoyancy forcing, this compensation is suppressed by the entrainment of relatively O2-poor deep waters. These results imply and allow to quantify the direct link between variability of deep convection and the supply of O2 in the North Atlantic.

Social Empathy as a Framework for Teaching Social Justice

ERIC Educational Resources Information Center

Segal, Elizabeth A.; Wagaman, M. Alex

2017-01-01

Social work education stresses training students to understand oppressive structural barriers and promote social and economic justice. Social empathy, which is rooted in a deep understanding of those who are different from us through contextual understanding and macro perspective-taking, offers a framework for teaching social justice that…

Radiation Hazards and Countermeasures for Human Space Flight

NASA Technical Reports Server (NTRS)

Adams, James

2004-01-01

The protection of astronauts from the hazards of ionizing radiation in space is a moral and legal obligation of NASA. If there are to be manned deep-space missions, means must be found to provide this protection. There are two parts to providing this protection: understanding the effects of space radiation on humans so that radiation exposure limits can be established; and developing countermeasures so that exposures can be kept below these limits. This talk will cover both parts of this problem.

Temporal Loss of Tsc1: Neural Development and Brain Disease in Tuberous Sclerosis

DTIC Science & Technology

2014-06-01

funding. He was also was aware of my being named as a Simmons Foundation Autism Research Initiative (SFARI) investigator. !Regardless, the outcome is...2001). The thalamus has also been linked to the autism component in human TS (Asano et al., 2001) and is poised to play an important role in brain...nearly all TS patients and cognitive deficits and autism in a substantial cohort of TS patients. However, a deep understanding of how the TS brain

Retaining a Resilient and Enduring Workforce: Examination of Duty/Position Rotational Assignments for Civilian Acquisition Positions

DTIC Science & Technology

2015-04-12

the Defense Acquisition Workforce becomes increasingly volatile due to reduced resources, an aging workforce, limitations imposed by the BCA, and...development frameworks is visualized in Figures 3 through 6. “[S]enior leaders in the military are expected to yield a ‘ rich array of career...selectively at mid-grade ranks, so that a base of deep understanding is built before these leaders become senior in position and are expected to shape and

Understanding Soviet Naval Developments

DTIC Science & Technology

1991-07-01

submarine noise reduction technology. A single-unit experimental, deep diving SSN. SSBN in a process that converted the unit to dubbed the MIKE class, was...is second only to that of Ja- ties. When the Soviet MIKE SSN suffered a pan in total catch tonnage each year. fire in the Norwegian Sea in April of... sharpl \\ tapered nose providing better o~er-the-nose visibil- ity: this change ’. as miade possible by the absence of’ the MIiG-23’s air intercept radar

Development of an Integrated ISFET pH Sensor for High Pressure Applications in the Deep-Sea

DTIC Science & Technology

2012-09-30

Measurements in the upper ocean suggest that sensor precision is comparable to the annual pH change due to ocean acidification (Fig. 2). An array of...profiling floats equipped with pH sensors would be capable of directly monitoring the process of ocean acidification . Further refinement of the sensor...Quality of Life The high pressure pH sensor will have direct applications to our understanding of ocean acidification and the impacts on ecosystem

The Deep-Sea and Sub-Seafloor Frontier initiative - a key to link EC research and international scientific ocean drilling

NASA Astrophysics Data System (ADS)

Kopf, A.

2009-04-01

The Deep-Sea and Sub-Seafloor Frontiers project, DS3F, represents the continuation of the DSF roadmap towards the sustainable management of oceanic resources on a European scale. It will develop strategies for sub-seafloor sampling to contribute to a better understanding of deep-sea and sub-seafloor processes by connecting marine research in life and geosciences, climate and environmental change, as well as socio-economic issues and policy building. We propose to establish a long-lived research approach that considers (i) the need for a sustainable management of the ocean, and particularly the deep sea with enhanced activity (fishery, hydrocarbon exploration), (ii) the necessity to unravel deep-seated geological processes that drive seafloor ecosystems, and (iii) the value of seabed archives for the reconstruction of paleo-environmental conditions and the improved prediction of future climate change. Sub-seafloor drilling and sampling can provide two key components in understanding how deep-sea ecosystems function at present, and how they will respond to global change: (a) an inventory of present subsurface processes and biospheres, and their links to surface ecosystems, including seafloor observation and baseline studies, and (b) a high resolution archive of past variations in environmental conditions and biodiversity. For both components, an international effort is needed to share knowledge, methods and technologies, including mission-specific platforms to increase the efficiency, coverage and accuracy of sub-seafloor sampling and exploration. The deep biosphere has been discovered only within the past two decades and comprises the last major frontier for biological exploration. We lack fundamental knowledge of composition, diversity, distribution and metabolism in sub-seafloor biological communities at Earth's extremes, and their repercussions on seafloor ecosystems and life in the deep sea. There is equally an emerging need to shed light on geodynamic processes fuelling biological activity, and how such processes tie into the emission of geofuels and the formation of hydrocarbons and other resources. In addition, geodynamic processes may be cause natural hazards such as earthquake slip, submarine landslides, or tsunamis with a profound effect for humans and ecosystems. Their governing principles and potential triggers are poorly understood and often related to the sub-seafloor environment. In summary, the three main research areas in the Integrated Ocean Drilling Program (IODP; see Initial Science Plan www.iodp.org/isp/), i.e. geodynamics, climate and deep biosphere, as well as the goals of DS3F show a strong overlap and suggest an emerging need to join forces. This will result in the most efficient use of sub-seafloor sampling techniques and existing marine infrastructure to study the geosystem and its effects on biosphere and marine ecosystems. The DS3F initiative aims at providing a comprehensive "white paper" for a sustainable use of the oceans, an European Maritime Policy, and a strong link between European mission-specific drilling projects including IODP, IMAGES, ESF-EuroMARC and EC campaigns.

Development and application of deep convolutional neural network in target detection

NASA Astrophysics Data System (ADS)

Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

2018-04-01

With the development of big data and algorithms, deep convolution neural networks with more hidden layers have more powerful feature learning and feature expression ability than traditional machine learning methods, making artificial intelligence surpass human level in many fields. This paper first reviews the development and application of deep convolutional neural networks in the field of object detection in recent years, then briefly summarizes and ponders some existing problems in the current research, and the future development of deep convolutional neural network is prospected.

Bioluminescence resonance energy transfer (BRET) imaging of protein–protein interactions within deep tissues of living subjects

PubMed Central

Dragulescu-Andrasi, Anca; Chan, Carmel T.; Massoud, Tarik F.; Gambhir, Sanjiv S.

2011-01-01

Identifying protein–protein interactions (PPIs) is essential for understanding various disease mechanisms and developing new therapeutic approaches. Current methods for assaying cellular intermolecular interactions are mainly used for cells in culture and have limited use for the noninvasive assessment of small animal disease models. Here, we describe red light-emitting reporter systems based on bioluminescence resonance energy transfer (BRET) that allow for assaying PPIs both in cell culture and deep tissues of small animals. These BRET systems consist of the recently developed Renilla reniformis luciferase (RLuc) variants RLuc8 and RLuc8.6, used as BRET donors, combined with two red fluorescent proteins, TagRFP and TurboFP635, as BRET acceptors. In addition to the native coelenterazine luciferase substrate, we used the synthetic derivative coelenterazine-v, which further red-shifts the emission maxima of Renilla luciferases by 35 nm. We show the use of these BRET systems for ratiometric imaging of both cells in culture and deep-tissue small animal tumor models and validate their applicability for studying PPIs in mice in the context of rapamycin-induced FK506 binding protein 12 (FKBP12)-FKBP12 rapamycin binding domain (FRB) association. These red light-emitting BRET systems have great potential for investigating PPIs in the context of drug screening and target validation applications. PMID:21730157

Deep brain stimulation for psychiatric disorders: where we are now.

PubMed

Cleary, Daniel R; Ozpinar, Alp; Raslan, Ahmed M; Ko, Andrew L

2015-06-01

Fossil records showing trephination in the Stone Age provide evidence that humans have sought to influence the mind through physical means since before the historical record. Attempts to treat psychiatric disease via neurosurgical means in the 20th century provided some intriguing initial results. However, the indiscriminate application of these treatments, lack of rigorous evaluation of the results, and the side effects of ablative, irreversible procedures resulted in a backlash against brain surgery for psychiatric disorders that continues to this day. With the advent of psychotropic medications, interest in invasive procedures for organic brain disease waned. Diagnosis and classification of psychiatric diseases has improved, due to a better understanding of psychiatric patho-physiology and the development of disease and treatment biomarkers. Meanwhile, a significant percentage of patients remain refractory to multiple modes of treatment, and psychiatric disease remains the number one cause of disability in the world. These data, along with the safe and efficacious application of deep brain stimulation (DBS) for movement disorders, in principle a reversible process, is rekindling interest in the surgical treatment of psychiatric disorders with stimulation of deep brain sites involved in emotional and behavioral circuitry. This review presents a brief history of psychosurgery and summarizes the development of DBS for psychiatric disease, reviewing the available evidence for the current application of DBS for disorders of the mind.

The influence of muscle pennation angle and cross-sectional area on contact forces in the ankle joint

PubMed Central

Sopher, Ran S; Amis, Andrew A; Davies, D Ceri; Jeffers, Jonathan RT

2016-01-01

Data about a muscle’s fibre pennation angle and physiological cross-sectional area are used in musculoskeletal modelling to estimate muscle forces, which are used to calculate joint contact forces. For the leg, muscle architecture data are derived from studies that measured pennation angle at the muscle surface, but not deep within it. Musculoskeletal models developed to estimate joint contact loads have usually been based on the mean values of pennation angle and physiological cross-sectional area. Therefore, the first aim of this study was to investigate differences between superficial and deep pennation angles within each muscle acting over the ankle and predict how differences may influence muscle forces calculated in musculoskeletal modelling. The second aim was to investigate how inter-subject variability in physiological cross-sectional area and pennation angle affects calculated ankle contact forces. Eight cadaveric legs were dissected to excise the muscles acting over the ankle. The mean surface and deep pennation angles, fibre length and physiological cross-sectional area were measured. Cluster analysis was applied to group the muscles according to their architectural characteristics. A previously validated OpenSim model was used to estimate ankle muscle forces and contact loads using architecture data from all eight limbs. The mean surface pennation angle for soleus was significantly greater (54%) than the mean deep pennation angle. Cluster analysis revealed three groups of muscles with similar architecture and function: deep plantarflexors and peroneals, superficial plantarflexors and dorsiflexors. Peak ankle contact force was predicted to occur before toe-off, with magnitude greater than five times bodyweight. Inter-specimen variability in contact force was smallest at peak force. These findings will help improve the development of experimental and computational musculoskeletal models by providing data to estimate force based on both surface and deep pennation angles. Inter-subject variability in muscle architecture affected ankle muscle and contact loads only slightly. The link between muscle architecture and function contributes to the understanding of the relationship between muscle structure and function. PMID:29805194

Can Creative Podcasting Promote Deep Learning? The Use of Podcasting for Learning Content in an Undergraduate Science Unit

ERIC Educational Resources Information Center

Pegrum, Mark; Bartle, Emma; Longnecker, Nancy

2015-01-01

This paper examines the effect of a podcasting task on the examination performance of several hundred first-year chemistry undergraduate students. Educational researchers have established that a deep approach to learning that promotes active understanding of meaning can lead to better student outcomes, higher grades and superior retention of…

Understanding Cognitive Presence in an Online and Blended Community of Inquiry: Assessing Outcomes and Processes for Deep Approaches to Learning

ERIC Educational Resources Information Center

Akyol, Zehra; Garrison, D. Randy

2011-01-01

This paper focuses on deep and meaningful learning approaches and outcomes associated with online and blended communities of inquiry. Applying mixed methodology for the research design, the study used transcript analysis, learning outcomes, perceived learning, satisfaction, and interviews to assess learning processes and outcomes. The findings for…

Multidirectional Cosmic Ray Ion Detector for Deep Space CubeSats

NASA Technical Reports Server (NTRS)

Wrbanek, John D.; Wrbanek, Susan Y.

2016-01-01

NASA Glenn Research Center has proposed a CubeSat-based instrument to study solar and cosmic ray ions in lunar orbit or deep space. The objective of Solar Proton Anisotropy and Galactic cosmic ray High Energy Transport Instrument (SPAGHETI) is to provide multi-directional ion data to further understand anisotropies in SEP and GCR flux.

Tectonic and climatic considerations for deep geological disposal of radioactive waste: A UK perspective.

PubMed

McEvoy, F M; Schofield, D I; Shaw, R P; Norris, S

2016-11-15

Identifying and evaluating the factors that might impact on the long-term integrity of a deep Geological Disposal Facility (GDF) and its surrounding geological and surface environment is central to developing a safety case for underground disposal of radioactive waste. The geological environment should be relatively stable and its behaviour adequately predictable so that scientifically sound evaluations of the long-term radiological safety of a GDF can be made. In considering this, it is necessary to take into account natural processes that could affect a GDF or modify its geological environment up to 1millionyears into the future. Key processes considered in this paper include those which result from plate tectonics, such as seismicity and volcanism, as well as climate-related processes, such as erosion, uplift and the effects of glaciation. Understanding the inherent variability of process rates, critical thresholds and likely potential influence of unpredictable perturbations represent significant challenges to predicting the natural environment. From a plate-tectonic perspective, a one million year time frame represents a very short segment of geological time and is largely below the current resolution of observation of past processes. Similarly, predicting climate system evolution on such time-scales, particularly beyond 200ka AP is highly uncertain, relying on estimating the extremes within which climate and related processes may vary with reasonable confidence. The paper highlights some of the challenges facing a deep geological disposal program in the UK to review understanding of the natural changes that may affect siting and design of a GDF. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

3D reconstruction of synapses with deep learning based on EM Images

NASA Astrophysics Data System (ADS)

Xiao, Chi; Rao, Qiang; Zhang, Dandan; Chen, Xi; Han, Hua; Xie, Qiwei

2017-03-01

Recently, due to the rapid development of electron microscope (EM) with its high resolution, stacks delivered by EM can be used to analyze a variety of components that are critical to understand brain function. Since synaptic study is essential in neurobiology and can be analyzed by EM stacks, the automated routines for reconstruction of synapses based on EM Images can become a very useful tool for analyzing large volumes of brain tissue and providing the ability to understand the mechanism of brain. In this article, we propose a novel automated method to realize 3D reconstruction of synapses for Automated Tapecollecting Ultra Microtome Scanning Electron Microscopy (ATUM-SEM) with deep learning. Being different from other reconstruction algorithms, which employ classifier to segment synaptic clefts directly. We utilize deep learning method and segmentation algorithm to obtain synaptic clefts as well as promote the accuracy of reconstruction. The proposed method contains five parts: (1) using modified Moving Least Square (MLS) deformation algorithm and Scale Invariant Feature Transform (SIFT) features to register adjacent sections, (2) adopting Faster Region Convolutional Neural Networks (Faster R-CNN) algorithm to detect synapses, (3) utilizing screening method which takes context cues of synapses into consideration to reduce the false positive rate, (4) combining a practical morphology algorithm with a suitable fitting function to segment synaptic clefts and optimize the shape of them, (5) applying the plugin in FIJI to show the final 3D visualization of synapses. Experimental results on ATUM-SEM images demonstrate the effectiveness of our proposed method.

Diversity in deep-sea benthic macrofauna: the importance of local ecology, the larger scale, history and the Antarctic

NASA Astrophysics Data System (ADS)

Gage, John D.

2004-07-01

High diversity in macrobenthos in the deep sea still lacks satisfactory explanation, even if this richness may not be exceptional compared to that in coastal soft sediments. Explanations have assumed a highly ecologically interactive, saturated local community with co-existence controlled by either niche heterogeneity, or spatio-temporal heterogeneity embodying disturbance. All have failed to provide convincing support. Local/regional scale biodiversity relationships support the idea of local richness in macrobenthos being predominantly dependent on the larger, rather local scale. Local-scale ecological interactions seem unlikely to have overriding importance in co-existence of species in the deep sea, even for relatively abundant, 'core' species with wide distributions. Variety in observed larger-scale pattern and the strong inter-regional pattern, particularly in the poorly known southern hemisphere, seem to have a pluralistic causation. These include regional-scale barriers and extinctions (e.g., Arctic), and ongoing adaptive zone re-colonisation (e.g., Mediterranean), along with other historical constraints on speciation and migration of species caused by changes in ocean and ocean-basin geometry. At the global scale lack of knowledge of the Antarctic deep sea, for example, blocks coherent understanding of latitudinal species diversity gradients. We need to reconcile emerging understanding of large-scale historical variability in the deep-sea environment—with massive extinctions among microfossil indicators as recently as the Pliocene—to results from cladistic studies indicating ancient lineages, such as asellote isopods, that have evolved entirely within the deep sea. The degree to which the great age, diversity, and high degree of endemism in Antarctic shelf benthos might have enriched biodiversity in the adjacent deep seas basins remains unclear. Basin confluence with the Atlantic, Indian and Pacific Oceans may have encouraged northwards dispersion of species from and into the deep Antarctic basins so that any regional identity is superficial. Interpretation of the Antarctic deep sea as a diversity pump for global deep-sea biodiversity may simply reflect re-colonisation, via basin confluence, of northern hemisphere areas impoverished by the consequences of rapid environmental change during the Quaternary.

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).

Deep Seawater Intrusion Enhanced by Geothermal Through Deep Faults in Xinzhou Geothermal Field in Guangdong, China

NASA Astrophysics Data System (ADS)

Lu, G.; Ou, H.; Hu, B. X.; Wang, X.

2017-12-01

This study investigates abnormal sea water intrusion from deep depth, riding an inland-ward deep groundwater flow, which is enhanced by deep faults and geothermal processes. The study site Xinzhou geothermal field is 20 km from the coast line. It is in southern China's Guangdong coast, a part of China's long coastal geothermal belt. The geothermal water is salty, having fueled an speculation that it was ancient sea water retained. However, the perpetual "pumping" of the self-flowing outflow of geothermal waters might alter the deep underground flow to favor large-scale or long distant sea water intrusion. We studied geochemical characteristics of the geothermal water and found it as a mixture of the sea water with rain water or pore water, with no indication of dilution involved. And we conducted numerical studies of the buoyancy-driven geothermal flow in the deep ground and find that deep down in thousand meters there is favorable hydraulic gradient favoring inland-ward groundwater flow, allowing seawater intrude inland for an unusually long tens of kilometers in a granitic groundwater flow system. This work formed the first in understanding geo-environment for deep ground water flow.

Biodiversity of the Deep-Sea Continental Margin Bordering the Gulf of Maine (NW Atlantic): Relationships among Sub-Regions and to Shelf Systems

PubMed Central

Kelly, Noreen E.; Shea, Elizabeth K.; Metaxas, Anna; Haedrich, Richard L.; Auster, Peter J.

2010-01-01

Background In contrast to the well-studied continental shelf region of the Gulf of Maine, fundamental questions regarding the diversity, distribution, and abundance of species living in deep-sea habitats along the adjacent continental margin remain unanswered. Lack of such knowledge precludes a greater understanding of the Gulf of Maine ecosystem and limits development of alternatives for conservation and management. Methodology/Principal Findings We use data from the published literature, unpublished studies, museum records and online sources, to: (1) assess the current state of knowledge of species diversity in the deep-sea habitats adjacent to the Gulf of Maine (39–43°N, 63–71°W, 150–3000 m depth); (2) compare patterns of taxonomic diversity and distribution of megafaunal and macrofaunal species among six distinct sub-regions and to the continental shelf; and (3) estimate the amount of unknown diversity in the region. Known diversity for the deep-sea region is 1,671 species; most are narrowly distributed and known to occur within only one sub-region. The number of species varies by sub-region and is directly related to sampling effort occurring within each. Fishes, corals, decapod crustaceans, molluscs, and echinoderms are relatively well known, while most other taxonomic groups are poorly known. Taxonomic diversity decreases with increasing distance from the continental shelf and with changes in benthic topography. Low similarity in faunal composition suggests the deep-sea region harbours faunal communities distinct from those of the continental shelf. Non-parametric estimators of species richness suggest a minimum of 50% of the deep-sea species inventory remains to be discovered. Conclusions/Significance The current state of knowledge of biodiversity in this deep-sea region is rudimentary. Our ability to answer questions is hampered by a lack of sufficient data for many taxonomic groups, which is constrained by sampling biases, life-history characteristics of target species, and the lack of trained taxonomists. PMID:21124960

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

Gerke, Brian F.; Wechsler, Risa H.; Behroozi, Peter S.

We develop empirical methods for modeling the galaxy population and populating cosmological N-body simulations with mock galaxies according to the observed properties of galaxies in survey data. We use these techniques to produce a new set of mock catalogs for the DEEP2 Galaxy Redshift Survey based on the output of the high-resolution Bolshoi simulation, as well as two other simulations with different cosmological parameters, all of which we release for public use. The mock-catalog creation technique uses subhalo abundance matching to assign galaxy luminosities to simulated dark-matter halos. It then adds color information to the resulting mock galaxies in amore » manner that depends on the local galaxy density, in order to reproduce the measured color-environment relation in the data. In the course of constructing the catalogs, we test various models for including scatter in the relation between halo mass and galaxy luminosity, within the abundance-matching framework. We find that there is no constant-scatter model that can simultaneously reproduce both the luminosity function and the autocorrelation function of DEEP2. This result has implications for galaxy-formation theory, and it restricts the range of contexts in which the mock catalogs can be usefully applied. Nevertheless, careful comparisons show that our new mock catalogs accurately reproduce a wide range of the other properties of the DEEP2 catalog, suggesting that they can be used to gain a detailed understanding of various selection effects in DEEP2.« less

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation. PMID:25780910

An abyssal mobilome: viruses, plasmids and vesicles from deep-sea hydrothermal vents.

PubMed

Lossouarn, Julien; Dupont, Samuel; Gorlas, Aurore; Mercier, Coraline; Bienvenu, Nadege; Marguet, Evelyne; Forterre, Patrick; Geslin, Claire

2015-12-01

Mobile genetic elements (MGEs) such as viruses, plasmids, vesicles, gene transfer agents (GTAs), transposons and transpovirions, which collectively represent the mobilome, interact with cellular organisms from all three domains of life, including those thriving in the most extreme environments. While efforts have been made to better understand deep-sea vent microbial ecology, our knowledge of the mobilome associated with prokaryotes inhabiting deep-sea hydrothermal vents remains limited. Here we focus on the abyssal mobilome by reviewing accumulating data on viruses, plasmids and vesicles associated with thermophilic and hyperthermophilic Bacteria and Archaea present in deep-sea hydrothermal vents. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Taxonomic revision of deep-sea Ostracoda from the Arctic Ocean

USGS Publications Warehouse

Yasuhara, Moriaki; Stepanova, Anna; Okahashi, Hisayo; Cronin, Thomas M.; Brouwers, Elisabeth M.

2015-01-01

Taxonomic revision of deep-sea Ostracoda from the Arctic Ocean was conducted to reduce taxonomic uncertainty that will improve our understanding of species ecology, biogeography and relationship to faunas from other deep-sea regions. Fifteen genera and 40 species were examined and (re-)illustrated with high-resolution scanning electron microscopy images, covering most of known deep-sea species in the central Arctic Ocean. Seven new species are described: Bythoceratina lomonosovensis n. sp., Cytheropteron parahamatum n. sp., Cytheropteron lanceae n. sp.,Cytheropteron irizukii n. sp., Pedicythere arctica n. sp., Cluthiawhatleyi n. sp., Krithe hunti n. sp. This study provides a robust taxonomic baseline for application to paleoceanographical reconstruction and biodiversity analyses in this climatically sensitive region.

Not All the Organelles of Living Cells Are Equal! Or Are They? Engaging Students in Deep Learning and Conceptual Change

ERIC Educational Resources Information Center

Cherif, Abour H.; Siuda, JoElla Eaglin; Jedlicka, Dianne M.; Bondoc, Jasper Marc; Movahedzadeh, Farahnaz

2016-01-01

The cell is the fundamental basis for understanding biology much like the atom is the fundamental basis for understanding physics. Understanding biology requires the understanding of the fundamental functions performed by components within each cell. These components, or organelles, responsible for both maintenance and functioning of the cell…

Development of levees on deep-sea channels: Insights from high-resolution AUV exploration of the Lucia Chica system, offshore central California

NASA Astrophysics Data System (ADS)

Maier, K. L.; Fildani, A.; Romans, B.; Paull, C. K.; McHargue, T.; Graham, S. A.; Caress, D. W.

2010-12-01

The Lucia Chica, a tributary channel system of the Lucia Canyon, offshore central California, was imaged using the Monterey Bay Aquarium Research Institute’s (MBARI) Autonomous Underwater Vehicle (AUV) in order to investigate seafloor and subsurface morphologies associated with low-relief submarine channels. In larger, previously investigated seafloor channel-levee systems, initial deposits are either eroded, compacted, or below the resolution of available imaging. In this dataset from the Lucia Chica, the unprecedented high-resolution multibeam bathymetry (1 m lateral resolution) and chirp sub-bottom profiles (11 cm vertical resolution) reveal a highly irregular seafloor with scours, depressions, and discontinuous low-relief conduits over an area of ~70 km2. Sediment packages associated with channels, levees, and deposits related to less confined flows are correlated between chirp profiles and with the multibeam bathymetric image to determine the stratigraphic evolution of the Lucia Chica and the sequence of channel-levee development. In the Lucia Chica, channels appear to have initiated as trains of scours that eventually coalesced into continuous channel thalwegs carved by erosional turbidity currents. Channel incision and stepped lateral migration led to the development of terraces, complex levee stratigraphy, and distinct morphologies associated with inner and outer bends of sinuous channels. The inner bend levee stratigraphy indicates that the channel position migrated in discrete shifts, as opposed to continuous channel migration associated with lateral accretion. Discrete levee packages, formed from flow-stripped turbidity currents, later infilled abandoned portions of the channel and overbank areas. While processes of initial channel and levee development are well established in fluvial settings, detailed examples are lacking for deep-sea systems. These results highlight the differences in initiation between submarine channel systems, their fluvial counterparts, and larger submarine channel-levee systems imaged only with lower-resolution technologies. High-resolution imaging and detailed mapping made possible by cutting-edge oceanographic technology provide an unprecedented examination of deep-water channel-levee morphology and improve understanding of deep-water channel migration and levee development.

From the Field to the Classroom: Developing Scientifically Literate Citizens Using the Understanding Global Change Framework in Education and Citizen Science

NASA Astrophysics Data System (ADS)

Toupin, C.; Bean, J. R.; Gavenus, K.; Johnson, H.; Toupin, S.

2017-12-01

With the copious amount of science and pseudoscience reported on by non-experts in the media, it is critical for educators to help students develop into scientifically literate citizens. One of the most direct ways to help students develop deep scientific understanding and the skills to critically question the information they encounter is to bring science into their daily experiences and to contextualize scientific inquiry within the classroom. Our work aims to use a systems-based models approach to engage students in science, in both formal and informal contexts. Using the Understanding Global Change (UGC) and the Understanding Science models developed at the Museum of Paleontology at UC Berkeley, high school students from Arizona were tasked with developing a viable citizen science program for use at the Center for Alaskan Coastal Studies in Homer, Alaska. Experts used the UGC model to help students define why they were doing the work, and give context to the importance of citizen science. Empowered with an understanding of the scientific process, excited by the purpose of their work and how it could contribute to the scientific community, students whole-heartedly worked together to develop intertidal monitoring protocols for two locations while staying at Peterson Bay Field Station, Homer. Students, instructors, and scientists used system models to communicate and discuss their understanding of the biological, physical, and chemical processes in Kachemak Bay. This systems-based models approach is also being used in an integrative high school physics, chemistry, and biology curriculum in a truly unprecedented manner. Using the Understanding Global Change framework to organize curriculum scope and sequence, the course addresses how the earth systems work, how interdisciplinary science knowledge is necessary to understand those systems, and how scientists and students can measure changes within those systems.

Eukaryotic opportunists dominate the deep-subsurface biosphere in South Africa

PubMed Central

Borgonie, G.; Linage-Alvarez, B.; Ojo, A. O.; Mundle, S.O.C.; Freese, L B.; Van Rooyen, C.; Kuloyo, O.; Albertyn, J.; Pohl, C.; Cason, E. D.; Vermeulen, J.; Pienaar, C.; Litthauer, D.; Van Niekerk, H.; Van Eeden, J.; Lollar, B. Sherwood.; Onstott, T. C.; Van Heerden, E.

2015-01-01

Following the discovery of the first Eukarya in the deep subsurface, intense interest has developed to understand the diversity of eukaryotes living in these extreme environments. We identified that Platyhelminthes, Rotifera, Annelida and Arthropoda are thriving at 1.4 km depths in palaeometeoric fissure water up to 12,300 yr old in South African mines. Protozoa and Fungi have also been identified; however, they are present in low numbers. Characterization of the different species reveals that many are opportunistic organisms with an origin due to recharge from surface waters rather than soil leaching. This is the first known study to demonstrate the in situ distribution of biofilms on fissure rock faces using video documentation. Calculations suggest that food, not dissolved oxygen is the limiting factor for eukaryal population growth. The discovery of a group of Eukarya underground has important implications for the search for life on other planets in our solar system. PMID:26597082

Viking telecommunication effects of GEOS satellite interference based on testing at the Madrid deep space station

NASA Technical Reports Server (NTRS)

Stuhr, F. V.; Kent, S. S.; Galvez, J. L.; Luaces, B. G.; Pasero, G. R.; Urech, J. M.

1976-01-01

In support of the ongoing NASA-European Space Agency (ESA) effort to understand and control possible interference between missions, testing was conducted at the Madrid Deep Space Station from July 1975 to February 1976 to characterize the effect on Viking 1975 telecommunication link performance of Geodetic Earth-Orbiting Satellite (GEOS) downlink signals. The prime use of the data was to develop a capability to predict GEOS interference effects for evaluation of Viking 1975 mission impacts and possible temporary GEOS shutdown. Also, the data would serve as a basis for assessment of the GEOS impact on missions other than Viking as well as for more general interference applications. Performances of the reference receiver, telemetry, and planetary ranging were measured in the presence of various types of GEOS-related interference, including an unmodulated GEOS carrier and simulation of the actual spectrum by an ESA-supplied GEOS suitcase model.

Eukaryotic opportunists dominate the deep-subsurface biosphere in South Africa.

PubMed

Borgonie, G; Linage-Alvarez, B; Ojo, A O; Mundle, S O C; Freese, L B; Van Rooyen, C; Kuloyo, O; Albertyn, J; Pohl, C; Cason, E D; Vermeulen, J; Pienaar, C; Litthauer, D; Van Niekerk, H; Van Eeden, J; Sherwood Lollar, B; Onstott, T C; Van Heerden, E

2015-11-24

Following the discovery of the first Eukarya in the deep subsurface, intense interest has developed to understand the diversity of eukaryotes living in these extreme environments. We identified that Platyhelminthes, Rotifera, Annelida and Arthropoda are thriving at 1.4 km depths in palaeometeoric fissure water up to 12,300 yr old in South African mines. Protozoa and Fungi have also been identified; however, they are present in low numbers. Characterization of the different species reveals that many are opportunistic organisms with an origin due to recharge from surface waters rather than soil leaching. This is the first known study to demonstrate the in situ distribution of biofilms on fissure rock faces using video documentation. Calculations suggest that food, not dissolved oxygen is the limiting factor for eukaryal population growth. The discovery of a group of Eukarya underground has important implications for the search for life on other planets in our solar system.

In too deep: understanding, detecting and managing DVT.

PubMed

Meetoo, Danny

Venous thromboembolism (VTE), which includes deep vein thrombosis (DVT) and pulmonary embolism (PE), is a serious health and social care problem of the developed world, affecting 1 in 1000 adults every year, and with an annual financial overhead of approximately £640 million. The nature of DVT means that often the condition can go unrecognized until the thrombus becomes an embolus. The pathogenesis of DVT continues to be based on Virchow's triad, which attributes VTE to 'hypercoagulability', 'stasis' and 'intimal injury'. The diagnosis of DVT is often the result of a number of tests performed either sequentially or in combination before mechanical and/or chemical treatment is embarked on. Creating public awareness of DVT and PE is the best way to prevent this condition. Nurses are in an ideal position to discuss the importance of lifestyle changes and other related measures to prevent DVT.

Evolution of Deep Brain Stimulation: Human Electrometer and Smart Devices Supporting the Next Generation of Therapy

PubMed Central

Lee, Kendall H.; Blaha, Charles D.; Garris, Paul A.; Mohseni, Pedram; Horne, April E.; Bennet, Kevin E.; Agnesi, Filippo; Bledsoe, Jonathan M.; Lester, Deranda B.; Kimble, Chris; Min, Hoon-Ki; Kim, Young-Bo; Cho, Zang-Hee

2010-01-01

Deep Brain Stimulation (DBS) provides therapeutic benefit for several neuropathologies including Parkinson’s disease (PD), epilepsy, chronic pain, and depression. Despite well established clinical efficacy, the mechanism(s) of DBS remains poorly understood. In this review we begin by summarizing the current understanding of the DBS mechanism. Using this knowledge as a framework, we then explore a specific hypothesis regarding DBS of the subthalamic nucleus (STN) for the treatment of PD. This hypothesis states that therapeutic benefit is provided, at least in part, by activation of surviving nigrostriatal dopaminergic neurons, subsequent striatal dopamine release, and resumption of striatal target cell control by dopamine. While highly controversial, we present preliminary data that are consistent with specific predications testing this hypothesis. We additionally propose that developing new technologies, e.g., human electrometer and closed-loop smart devices, for monitoring dopaminergic neurotransmission during STN DBS will further advance this treatment approach. PMID:20657744

A New Mechanism for the Dependence of Tropical Convection on Free-Tropospheric Humidity

NASA Astrophysics Data System (ADS)

Virman, M.; Bister, M.; Sinclair, V. A.; Järvinen, H.; Räisänen, J.

2018-03-01

Atmospheric deep convection is responsible for transport of the most important greenhouse gas, water vapor, to the free-troposphere and for most of the precipitation on Earth. Observations show that deep convection is strongly sensitive to the amount of moisture in the low-to-midtroposphere. The current understanding is that this sensitivity is due to entrainment. In this study, it is found that over tropical oceans shallow warm anomalies, likely strong enough to hinder subsequent convection, are observed just above the boundary layer after precipitation, but only where the low-to-midtroposphere is dry. The results, showing a cold anomaly above the warm anomaly, suggest that evaporation of stratiform precipitation and subsidence warming below likely cause these temperature anomalies. Evaporation of stratiform precipitation should therefore be a topic of high priority for developing more realistic theories of convective weather phenomena and for improving climate and weather forecast models.

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

PubMed

Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

2018-04-01

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

Quasispecies Analyses of the HIV-1 Near-full-length Genome With Illumina MiSeq

PubMed Central

Ode, Hirotaka; Matsuda, Masakazu; Matsuoka, Kazuhiro; Hachiya, Atsuko; Hattori, Junko; Kito, Yumiko; Yokomaku, Yoshiyuki; Iwatani, Yasumasa; Sugiura, Wataru

2015-01-01

Human immunodeficiency virus type-1 (HIV-1) exhibits high between-host genetic diversity and within-host heterogeneity, recognized as quasispecies. Because HIV-1 quasispecies fluctuate in terms of multiple factors, such as antiretroviral exposure and host immunity, analyzing the HIV-1 genome is critical for selecting effective antiretroviral therapy and understanding within-host viral coevolution mechanisms. Here, to obtain HIV-1 genome sequence information that includes minority variants, we sought to develop a method for evaluating quasispecies throughout the HIV-1 near-full-length genome using the Illumina MiSeq benchtop deep sequencer. To ensure the reliability of minority mutation detection, we applied an analysis method of sequence read mapping onto a consensus sequence derived from de novo assembly followed by iterative mapping and subsequent unique error correction. Deep sequencing analyses of aHIV-1 clone showed that the analysis method reduced erroneous base prevalence below 1% in each sequence position and discarded only < 1% of all collected nucleotides, maximizing the usage of the collected genome sequences. Further, we designed primer sets to amplify the HIV-1 near-full-length genome from clinical plasma samples. Deep sequencing of 92 samples in combination with the primer sets and our analysis method provided sufficient coverage to identify >1%-frequency sequences throughout the genome. When we evaluated sequences of pol genes from 18 treatment-naïve patients' samples, the deep sequencing results were in agreement with Sanger sequencing and identified numerous additional minority mutations. The results suggest that our deep sequencing method would be suitable for identifying within-host viral population dynamics throughout the genome. PMID:26617593

Education And Public Outreach For NASA's EPOXI Mission

NASA Astrophysics Data System (ADS)

McFadden, Lucy-Ann A.; Warner, E. M.; Crow, C. A.; Ristvey, J. D.; Counley, J.

2008-09-01

NASA's EPOXI mission has two scientific objectives in using the Deep Impact flyby spacecraft for further studies of comets and adding studies of extra-solar planets around other stars. During the Extrasolar Planetary Observations and Characterization (EPOCh) phase of the mission, observations of extrasolar planets transiting their parent stars are observed to further knowledge and understanding of planetary systems. Observations of Earth allow for comparison with Earth-like planets around other stars. A movie of Earth during a day when the Moon passed between Earth and the spacecraft is an educational highlight with scientific significance. The Deep Impact Extended Investigation (DIXI) continues the Deep Impact theme of investigating comets with a flyby of comet Hartley 2 in November 2010 to further explore the properties of comets and their formation. The EPOXI Education and Public Outreach (E/PO) program builds upon existing materials related to exploring comets and the Deep Impact mission, updating and modifying activities based on results from Deep Impact. An educational activity called Comparing Comets is under development that will guide students in conducting analyses similar to those that DIXI scientists will perform after observing comet Hartley 2. Existing educational materials related to planet finding from other NASA programs are linked from EPOXI's web page. Journey Through the Universe at the National Air and Space Museum encourages education in family and community groups and reaches out to underrepresented minorities. EPOXI's E/PO program additionally offers a newsletter to keep the public, teachers, and space enthusiasts apprised of mission activities. For more information visit: http://epoxi.umd.edu.

Geothermal implications of a refined composition-age geologic map for the volcanic terrains of southeast Oregon, northeast California, and southwest Idaho, USA

USGS Publications Warehouse

Burns, Erick; Gannett, Marshall W.; Sherrod, David R.; Keith, Mackenzie K.; Curtis, Jennifer A.; Bartolino, James R.; Engott, John A.; Scandella, Benjamin P.; Stern, Michelle A.; Flint, Alan L.

2017-01-01

Sufficient temperatures to generate steam likely exist under most of the dominantly volcanic terrains of southeast Oregon, northeast California, and southeast Idaho, USA, but finding sufficient permeability to allow efficient advective heat exchange is an outstanding challenge. A new thematic interpretation of existing state-level geologic maps provides an updated and refined distribution of the composition and age of geologic units for the purposes of assessing the implications for measurement and development of geothermal resources. This interpretation has been developed to better understand geothermal and hydrologic resources of the region. Comparison of the new geologic categories with available hydrologic data shows that younger volcanogenic terrains tend to have higher primary permeability than older terrains. Decrease in primary permeability with age is attributable to weathering and hydrothermal alteration of volcanogenic deposits to pore-filling clays and deposition of secondary deposits (e.g., zeolites). Spring density as a function of geology and precipitation can be used to infer groundwater flow path length within the upper aquifers. Beneath the upper aquifers, we postulate that, due to accelerated hydrothermal alteration at temperatures ~>30 °C, primary permeability at depths of geothermal interest will be limited, and that secondary permeability is a more viable target for hydrothermal fluid withdrawal. Because open fractures resulting from tensile stresses will affect all geologic layers, regions with a significant amount of groundwater flow through shallow, structurally controlled secondary permeability may overlay zones of deep secondary permeability. Regardless of whether the shallow permeability is connected with the deep permeability, shallow groundwater flow can mask the presence of deep hydrothermal flow, resulting in blind geothermal systems. Ideally, hydraulic connectivity between shallow and deep secondary permeability is limited, so that shallow groundwater does not cool potential geothermal reservoirs.

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

PubMed

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

Hierarchical semantic structures for medical NLP.

PubMed

Taira, Ricky K; Arnold, Corey W

2013-01-01

We present a framework for building a medical natural language processing (NLP) system capable of deep understanding of clinical text reports. The framework helps developers understand how various NLP-related efforts and knowledge sources can be integrated. The aspects considered include: 1) computational issues dealing with defining layers of intermediate semantic structures to reduce the dimensionality of the NLP problem; 2) algorithmic issues in which we survey the NLP literature and discuss state-of-the-art procedures used to map between various levels of the hierarchy; and 3) implementation issues to software developers with available resources. The objective of this poster is to educate readers to the various levels of semantic representation (e.g., word level concepts, ontological concepts, logical relations, logical frames, discourse structures, etc.). The poster presents an architecture for which diverse efforts and resources in medical NLP can be integrated in a principled way.

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

NASA Astrophysics Data System (ADS)

Shi, Mingyu; Wang, Jianjun; Yi, Chenggao; Bai, Jianhui; Wang, Jing

2017-11-01

Gulf of Mexico (GoM) is the earliest offshore oilfield which has ever been developed. It tends to breed increasingly value of efficient, secure and cheap key technology of deep-water development. Thus, the analyze of development expenditure in this area is significantly important the evaluation concept of deep-water oilfield all over the world. This article emphasizes on deep-water development concept and EPC contract value in GoM in recent 10 years in case of comparison and selection to the economic efficiency. Besides, the QUETOR has been put into use in this research processes the largest upstream cost database to simulate and calculate the calculating examples’ expenditure. By analyzing and forecasting the deep-water oilfield development expenditure, this article explores the relevance between expenditure index and oil price.

Double-Sided Laser Heating in Radial Diffraction Geometry for Diamond Anvil Cell Deformation Experiments at Simultaneous High Pressures and Temperatures

NASA Astrophysics Data System (ADS)

Miyagi, L. M.; Kunz, M.; Couper, S.; Lin, F.; Yan, J.; Doran, A.; MacDowell, A. A.

2017-12-01

The rheology of rocks and minerals in the Earth's deep interior plays a primary role in controlling large scale geodynamic processes such as mantle convection and slab subduction. Plastic deformation resulting from these processes can lead to texture development and associated seismic anisotropy. If a detailed understanding of the link between deformation and seismic anisotropy is established, observations of seismic anisotropy can be used to understand the dynamic state in the deep Earth. However, performing deformation experiments at lower mantle pressure and temperature conditions are extremely challenging. Thus most deformation studies have been performed either at room temperature and high pressure or at reduced pressures and high temperature. Only a few extraordinary efforts have attained pressures and temperatures relevant to lower mantle. Therefore our ability to interpret observations of lower mantle seismic anisotropy in terms of mantle flow models remains limited. In order to expand the pressure and temperature range available for deformation of deep Earth relevant mineral phases, we have developed a laser heating system for in-situ double-sided heating in radial diffraction geometry at beamline 12.2.2 of the Advanced Light Source of Lawrence Berkeley National Laboratory. This allows texture and lattice strain measurements to be recorded at simultaneous high pressures and temperatures in the diamond anvil cell. This new system is integrated into the newly built axial laser heating system to allow for rapid and reliable transitioning between double-sided laser heating in axial and radial geometries. Transitioning to radial geometry is accomplished by redirecting the laser and imaging paths from 0° and 180° to 90° and 270°. To redirect the 90° path, a motorized periscope mirror pair with an objective lens can be inserted into the downstream axial beam path. The 270° redirection is accomplished by removing the upstream axial objective lens and manually installing a small assembly carrying 2 infrared mirrors and an objective lens. Using this system we have performed two pilot studies recording texture and lattice strain development during deformation of FeO up to 1300 K and 45 GPa and bridgmanite up to 1600 K and 80 GPa.

Pavilion Lake Research Project - using multi-scaled approaches to understanding the provenance, maintenance and morphological characteristics of microbialites

NASA Astrophysics Data System (ADS)

Lim, D. S.; Brady, A. L.; Cardman, Z.; Cowie, B. R.; Forrest, A.; Marinova, M.; Shepard, R.; Laval, B.; Slater, G. F.; Gernhardt, M.; Andersen, D. T.; Hawes, I.; Sumner, D. Y.; Trembanis, A. C.; McKay, C. P.

2009-12-01

Microbialites can be metre-scale or larger discrete structures that cover kilometre-scale regions, for example in Pavilion Lake, British Columbia, Canada, while the organisms associated with their growth and development are much smaller (less than millimeter scale). As such, a multi-scaled approach to understanding their provenance, maintenance and morphological characteristics is required. Research members of the Pavilion Lake Research Project (PLRP) (www.pavilionlake.com) have been working to understand microbialite morphogenesis in Pavilion Lake, B.C., Canada and the potential for biosignature preservation in these carbonate rocks using a combination of field and lab based techniques. PLRP research participants have been: (1) exploring the physical and chemical limnological properties of the lake, especially as these characteristics pertain to microbialite formation, (2) using geochemical and molecular tools to test the hypothesized biological origin of the microbialites and the associated meso-scale processes, and (3) using geochemical and microscopic tools to characterize potential biosignature preservation in the microbialites on the micro scale. To address these goals, PLRP identified the need to (a) map Pavilion Lake to gain a contextual understanding of microbialite distribution and possible correlation between their lake-wide distribution and the ambient growth conditions, and (b) sample the microbialites, including those from deepest regions of the lake (60m). Initial assessments showed that PLRP science diving operations did not prove adequate for mapping and sample recovery in the large and deep (0.8 km x 5.7 km; 65m max depth) lake. As such, the DeepWorker Science and Exploration (DSE) program was established by the PLRP. At the heart of this program are two DeepWorker (DW) submersibles, single-person vehicles that offer Scientist-Pilots (SP) an opportunity to study the lake in a 1 atm pressurized environment. In addition, the use of Autonomous Underwater Vehicles (AUVs) for landscape level geophysical mapping (side-scan and multibeam) provides and additional large-scale context of the microbialite associations. The multi-scaled approach undertaken by the PLRP team members has created an opportunity to weave together a comprehensive understanding of the modern microbialites in Pavilion Lake, and their relevance to interpreting ancient carbonate fabrics. An overview of the team’s findings to date and on-going research will be presented.

Box Tomography: An efficient tomographic method for imaging localized structures in the deep Earth

NASA Astrophysics Data System (ADS)

Masson, Yder; Romanowicz, Barbara

2017-04-01

The accurate imaging of localized geological structures inside the deep Earth is key to understand our planet and its history. Since the introduction of the Preliminary Reference Earth Model, many generations of global tomographic models have been developed and give us access to the 3D structure of the Earth's interior. The latest generation of global tomographic models has emerged with the development of accurate numerical wavefield computations in a 3D earth combined with access to enhanced HPC capabilities. These models have sharpened up mantle images and unveiled relatively small scale structures that were blurred out in previous generation models. Fingerlike structures have been found at the base of the oceanic asthenosphere, and vertically oriented broad low velocity plume conduits [1] extend throughout the lower mantle beneath those major hotspots that are located within the perimeter of the deep mantle large low shear velocity provinces (LLSVPs). While providing new insights into our understanding of mantle dynamics, the detailed morphology of these features requires further efforts to obtain higher resolution images. In recent years, we developed a theoretical framework [2][3] for the tomographic imaging of localised geological structures buried inside the Earth, where no seismic sources nor receivers are necessarily present. We call this "box tomography" [4]. The essential difference between box-tomography and standard tomographic methods is that the numerical modeling (i.e. the raytracing in travel time tomography and the wave propagation in waveform tomography or full waveform inversion) is completely confined within the small box-region imaged. Thus, box tomography is a lot more efficient than global tomography (i.e. where we invert for the velocity in the larger volume that encompasses all the sources and receivers), for imaging localised objects. We present 2D and 3D examples showing that box tomography can be employed for imaging structures present within the D'' region at the base of the mantle. Further, we show that box-tomography performs well even in the difficult situation where the velocity distribution in the mantle above the target structure is not known a-priori. REFERENCES [1] French, S. W. and B. Romanowicz (2015) Broad Plumes at the base of the mantle beneath major hotspots, Nature, 525, 95-99 [2] Masson, Y., Cupillard, P., Capdeville, Y., & Romanowicz, B. (2013). On the numerical implementation of time-reversal mirrors for tomographic imaging. Geophysical Journal International, ggt459. [3] Masson, Y., & Romanowicz, B. (2017). Fast computation of synthetic seismograms within a medium containing remote localized perturbations: a numerical solution to the scattering problem. Geophysical Journal International, 208(2), 674-692. [4] Masson, Y., & Romanowicz, B. (2017). Box Tomography: Localised imaging of remote targets buried in an unknown medium, a step forward for understanding key structures in the deep Earth. Geophysical Journal International, (under review).

Long-term evaluation of impedance levels and clinical development in subthalamic deep brain stimulation for Parkinson's disease.

PubMed

Hartmann, C J; Wojtecki, L; Vesper, J; Volkmann, J; Groiss, S J; Schnitzler, A; Südmeyer, M

2015-10-01

This study was conducted to better understand the development of clinical efficacy and impedance levels in the long-term course of deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD). In this retrospective study of twenty PD patients, the motor part of the Unified Parkinson's Disease Rating Scale was periodically assessed i) after withdrawal of medication and inactivated stimulation, ii) after withdrawal of medication with activated stimulation and iii) after challenge with l-Dopa during activated stimulation up to 13 years after surgery. STN-DBS with or without medication significantly improved motor function up to 13 years after surgery. The contribution of axial symptoms increased over time. While the stimulation parameters were kept constant, the therapeutic impedances progressively declined. STN-DBS in PD remains effective in the long-term course of the disease. Constant current stimulation might be preferable over voltage-controlled stimulation, as it would alleviate the impact of impedance changes on the volume of tissue activated. Copyright © 2015 Elsevier Ltd. All rights reserved.

Educating the Public about Deep-Earth Science

NASA Astrophysics Data System (ADS)

Cronin, V. S.

2010-12-01

The nature of Earth’s interior is an active frontier of scientific research. Much of our current understanding of sub-crustal Earth is based on knowledge acquired in the last 2-3 decades, made possible by public funding and by dense seismic arrays, satellite remote sensing, increases in computer power that enable use of enhanced numerical techniques, improved theoretical and experimental knowledge of high PT mineral physics and chemistry, and a vigorous scientific community that has been trained to take advantage of these opportunities. An essential component of science is effective communication; therefore, providing for public education about science is a responsibility of the research community. Current public understanding of Earth’s interior is meager at best. In pre-college texts and in non-technical mass media, Earth's interior is typically visualized as an onion or baseball of concentric different-colored shells along whose upper surface "crustal" plates move like packages on conveyor belts of convecting mantle. Or the crust is thought to float on a molten mantle, as in the 19th century ideas of William Lowthian Green. Misconceptions about Earth that are brought to the undergraduate classroom must be confronted frankly and replaced by current understanding based on good science. Persistent ignorance has consequences. What do we want the public to know? First, the public should understand that knowledge of Earth's interior is important, not irrelevant. The public should know that deep-Earth processes result in Earth's dynamic magnetic field. Deep-Earth processes affect how radiation from the Sun reaches Earth, consequently affecting the atmosphere, the oceans, and the viability of life on Earth. The composition and differentiated structure of Earth's interior is a result of the early accretionary history of Earth and the Earth-Moon system. The public should also know that lithospheric tectonics, with all of its consequences (dynamic topography, volcanoes, earthquakes, resource concentrations, oceans, atmospheric composition and flow, possibly even life), is made possible by the specific characteristics of Earth's interior. Accepting that knowledge of Earth’s interior is important, the next task is to let the public know what we have learned about the deep Earth, and how we have developed that scientific knowledge. How do we incorporate uncertainty in this work? How do we test hypotheses? What are the current open questions about the deep Earth that we seek to address through ongoing or future scientific research? The cognitive distance between research experts and the public must be bridged -- an interpretive task that requires substantial expertise and collaboration. Reaching the ultimate audience (the general public) requires the education and active involvement of K-12+ teachers, education boards, textbook publishers and mass-media producers. Information must be packaged to suit each intended audience, at the appropriate cognitive level. The effectiveness of the education-and-outreach element of any research enterprise largely determines whether the processes and results of science are transferred successfully to the public consciousness.

In vivo imaging of cardiac development and function in zebrafish using light sheet microscopy.

PubMed

Weber, Michael; Huisken, Jan

2015-01-01

Detailed studies of heart development and function are crucial for our understanding of cardiac failures and pave the way for better diagnostics and treatment. However, the constant motion and close incorporation into the cardiovascular system prevent in vivo studies of the living, unperturbed heart. The complementary strengths of the zebrafish model and light sheet microscopy provide a useful platform to fill this gap. High-resolution images of the embryonic vertebrate heart are now recorded from within the living animal: deep inside the unperturbed heart we can follow cardiac contractions and measure action potentials and calcium transients. Three-dimensional reconstructions of the entire beating heart with cellular resolution give new insights into its ever-changing morphology and facilitate studies into how individual cells form the complex cardiac network. In addition, cardiac dynamics and robustness are now examined with targeted optical manipulation. Overall, the combination of zebrafish and light sheet microscopy represents a promising addition for cardiac research and opens the door to a better understanding of heart function and development.

Deep Reinforcement Learning of Cell Movement in the Early Stage of C. elegans Embryogenesis.

PubMed

Wang, Zi; Wang, Dali; Li, Chengcheng; Xu, Yichi; Li, Husheng; Bao, Zhirong

2018-04-25

Cell movement in the early phase of C. elegans development is regulated by a highly complex process in which a set of rules and connections are formulated at distinct scales. Previous efforts have demonstrated that agent-based, multi-scale modeling systems can integrate physical and biological rules and provide new avenues to study developmental systems. However, the application of these systems to model cell movement is still challenging and requires a comprehensive understanding of regulatory networks at the right scales. Recent developments in deep learning and reinforcement learning provide an unprecedented opportunity to explore cell movement using 3D time-lapse microscopy images. We present a deep reinforcement learning approach within an agent-based modeling system to characterize cell movement in the embryonic development of C. elegans. Our modeling system captures the complexity of cell movement patterns in the embryo and overcomes the local optimization problem encountered by traditional rule-based, agent-based modeling that uses greedy algorithms. We tested our model with two real developmental processes: the anterior movement of the Cpaaa cell via intercalation and the rearrangement of the superficial left-right asymmetry. In the first case, the model results suggested that Cpaaa's intercalation is an active directional cell movement caused by the continuous effects from a longer distance (farther than the length of two adjacent cells), as opposed to a passive movement caused by neighbor cell movements. In the second case, a leader-follower mechanism well explained the collective cell movement pattern in the asymmetry rearrangement. These results showed that our approach to introduce deep reinforcement learning into agent-based modeling can test regulatory mechanisms by exploring cell migration paths in a reverse engineering perspective. This model opens new doors to explore the large datasets generated by live imaging. Source code is available at https://github.com/zwang84/drl4cellmovement. dwang7@utk.edu, baoz@mskcc.org. Supplementary data are available at Bioinformatics online.

New Insights into Passive Margin Development from a Global Deep Seismic Reflection Dataset

NASA Astrophysics Data System (ADS)

Bellingham, Paul; Pindell, James; Graham, Rod; Horn, Brian

2014-05-01

The kinematic and dynamic evolution of the world's passive margins is still poorly understood. Yet the need to replace reserves, a high oil price and advances in drilling technology have pushed the international oil and gas industry to explore in the deep and ultra-deep waters of the continental margins. To support this exploration and help understand these margins, ION-GXT has acquired, processed and interpreted BasinSPAN surveys across many of the world's passive margins. Observations from these data lead us to consider the modes of subsidence and uplift at both volcanic and non-volcanic margins. At non-volcanic margins, it appears that frequently much of the subsidence post-dates major rifting and is not thermal in origin. Rather the subsidence is associated with extensional displacement on a major fault or shear zone running at least as deep as the continental Moho. We believe that the subsidence is structural and is probably associated with the pinching out (boudinage) of the Lower Crust so that the Upper crust effectively collapses onto the mantle. Eventually this will lead to the exhumation of the sub-continental mantle at the sea bed. Volcanic margins present more complex challenges both in terms of imaging and interpretation. The addition of volcanic and plutonic material into the system and dynamic effects all impact subsidence and uplift. However, we will show some fundamental observations regarding the kinematic development of volcanic margins and especially SDRs which demonstate that the process of collapse and the development of shear zones within and below the crust are also in existence at this type of margin. A model is presented of 'magma welds' whereby packages of SDRs collapse onto an emerging sub-crustal shear zone and it is this collapse which creates the commonly observed SDR geometry. Examples will be shown from East India, Newfoundland, Brazil, Argentina and the Gulf of Mexico.

Deepest X-Rays Ever Reveal universe Teeming With Black Holes

NASA Astrophysics Data System (ADS)

2001-03-01

For the first time, astronomers believe they have proof black holes of all sizes once ruled the universe. NASA's Chandra X-ray Observatory provided the deepest X-ray images ever recorded, and those pictures deliver a novel look at the past 12 billion years of black holes. Two independent teams of astronomers today presented images that contain the faintest X-ray sources ever detected, which include an abundance of active super massive black holes. "The Chandra data show us that giant black holes were much more active in the past than at present," said Riccardo Giacconi, of Johns Hopkins University and Associated Universities, Inc., Washington, DC. The exposure is known as "Chandra Deep Field South" since it is located in the Southern Hemisphere constellation of Fornax. "In this million-second image, we also detect relatively faint X-ray emission from galaxies, groups, and clusters of galaxies". The images, known as Chandra Deep Fields, were obtained during many long exposures over the course of more than a year. Data from the Chandra Deep Field South will be placed in a public archive for scientists beginning today. "For the first time, we are able to use X-rays to look back to a time when normal galaxies were several billion years younger," said Ann Hornschemeier, Pennsylvania State University, University Park. The group’s 500,000-second exposure included the Hubble Deep Field North, allowing scientists the opportunity to combine the power of Chandra and the Hubble Space Telescope, two of NASA's Great Observatories. The Penn State team recently acquired an additional 500,000 seconds of data, creating another one-million-second Chandra Deep Field, located in the constellation of Ursa Major. Chandra Deep Field North/Hubble Deep Field North Press Image and Caption The images are called Chandra Deep Fields because they are comparable to the famous Hubble Deep Field in being able to see further and fainter objects than any image of the universe taken at X-ray wavelengths. Both Chandra Deep Fields are comparable in observation time to the Hubble Deep Fields, but cover a much larger area of the sky. "In essence, it is like seeing galaxies similar to our own Milky Way at much earlier times in their lives," Hornschemeier added. "These data will help scientists better understand star formation and how stellar-sized black holes evolve." Combining infrared and X-ray observations, the Penn State team also found veils of dust and gas are common around young black holes. Another discovery to emerge from the Chandra Deep Field South is the detection of an extremely distant X-ray quasar, shrouded in gas and dust. "The discovery of this object, some 12 billion light years away, is key to understanding how dense clouds of gas form galaxies, with massive black holes at their centers," said Colin Norman of Johns Hopkins University. The Chandra Deep Field South results were complemented by the extensive use of deep optical observations supplied by the Very Large Telescope of the European Southern Observatory in Garching, Germany. The Penn State team obtained optical spectroscopy and imaging using the Hobby-Eberly Telescope in Ft. Davis, TX, and the Keck Observatory atop Mauna Kea, HI. Chandra's Advanced CCD Imaging Spectrometer was developed for NASA by Penn State and Massachusetts Institute of Technology under the leadership of Penn State Professor Gordon Garmire. NASA's Marshall Space Flight Center, Huntsville, AL, manages the Chandra program for the Office of Space Science, Washington, DC. TRW, Inc., Redondo Beach, California, is the prime contractor for the spacecraft. The Smithsonian's Chandra X-ray Center controls science and flight operations from Cambridge, MA. More information is available on the Internet at: http://chandra.harvard.edu AND http://chandra.nasa.gov

3D Geological Model for "LUSI" - a Deep Geothermal System

NASA Astrophysics Data System (ADS)

Sohrabi, Reza; Jansen, Gunnar; Mazzini, Adriano; Galvan, Boris; Miller, Stephen A.

2016-04-01

Geothermal applications require the correct simulation of flow and heat transport processes in porous media, and many of these media, like deep volcanic hydrothermal systems, host a certain degree of fracturing. This work aims to understand the heat and fluid transport within a new-born sedimentary hosted geothermal system, termed Lusi, that began erupting in 2006 in East Java, Indonesia. Our goal is to develop conceptual and numerical models capable of simulating multiphase flow within large-scale fractured reservoirs such as the Lusi region, with fractures of arbitrary size, orientation and shape. Additionally, these models can also address a number of other applications, including Enhanced Geothermal Systems (EGS), CO2 sequestration (Carbon Capture and Storage CCS), and nuclear waste isolation. Fractured systems are ubiquitous, with a wide-range of lengths and scales, making difficult the development of a general model that can easily handle this complexity. We are developing a flexible continuum approach with an efficient, accurate numerical simulator based on an appropriate 3D geological model representing the structure of the deep geothermal reservoir. Using previous studies, borehole information and seismic data obtained in the framework of the Lusi Lab project (ERC grant n°308126), we present here the first 3D geological model of Lusi. This model is calculated using implicit 3D potential field or multi-potential fields, depending on the geological context and complexity. This method is based on geological pile containing the geological history of the area and relationship between geological bodies allowing automatic computation of intersections and volume reconstruction. Based on the 3D geological model, we developed a new mesh algorithm to create hexahedral octree meshes to transfer the structural geological information for 3D numerical simulations to quantify Thermal-Hydraulic-Mechanical-Chemical (THMC) physical processes.

Predicting The Intrusion Layer From Deep Ocean Oil Spills

NASA Astrophysics Data System (ADS)

Wang, Dayang; Chow, Aaron; Adams, E. Eric

2015-11-01

Oil spills from deep ocean blowout events motivate our study of multiphase plumes in a water column. Key to understanding the long-term fate of these plumes is the ability to predict the depth and persistence of intrusion layers. While intrusion layers from multiphase plumes have been studied under stagnant conditions, their behavior in the presence of crossflow, especially in mild crossflow, remains poorly understood. The classical classification of plume behavior identifies two regimes: crossflow-dominant and stratification-dominant--but it does not account for the interplay between the two effects, leaving the transition region unexplored. We conduct laboratory tank experiments to investigate the behavior of intrusion layers under the simultaneous action of crossflow and stratification. Our experiments use an inverted frame of reference, using glass beads with a range of sizes to simulate oil droplets. We find that crossflow creates enhanced mixing, which in turn leads to a shallower intrusion layer of the released fluid (correspondingly, a deeper layer in the case of a deep ocean blowout). We develop a mathematical formulation that extends previous models to account for crossflow effects, and use field observations to validate the analytical and experimental findings.

Deep Learning in Label-free Cell Classification

PubMed Central

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-01-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells. PMID:26975219

Deep gluteal space problems: piriformis syndrome, ischiofemoral impingement and sciatic nerve release.

PubMed

Carro, Luis Perez; Hernando, Moises Fernandez; Cerezal, Luis; Navarro, Ivan Saenz; Fernandez, Ana Alfonso; Castillo, Alexander Ortiz

2016-01-01

Deep gluteal syndrome (DGS) is an underdiagnosed entity characterized by pain and/or dysesthesias in the buttock area, hip or posterior thigh and/or radicular pain due to a non-discogenic sciatic nerve entrapment in the subgluteal space. Multiple pathologies have been incorporated in this all-included "piriformis syndrome", a term that has nothing to do with the presence of fibrous bands, obturator internus/gemellus syndrome, quadratus femoris/ischiofemoral pathology, hamstring conditions, gluteal disorders and orthopedic causes. This article describes the subgluteal space anatomy, reviews known and new etiologies of DGS, and assesses the role of the radiologist and orthopaedic surgeons in the diagnosis, treatment and postoperative evaluation of sciatic nerve entrapments. DGS is an under-recognized and multifactorial pathology. The development of periarticular hip endoscopy has led to an understanding of the pathophysiological mechanisms underlying piriformis syndrome, which has supported its further classification. The whole sciatic nerve trajectory in the deep gluteal space can be addressed by an endoscopic surgical technique. Endoscopic decompression of the sciatic nerve appears useful in improving function and diminishing hip pain in sciatic nerve entrapments, but requires significant experience and familiarity with the gross and endoscopic anatomy. IV.

Deep Learning in Label-free Cell Classification

NASA Astrophysics Data System (ADS)

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-03-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

The terminal Velocity of the Deep Impact dust Ejecta

NASA Astrophysics Data System (ADS)

Rengel, M.; Küppers, M.; Keller, H. U.; Gutierrez, P.; Hviid, S. F.

2009-05-01

The collision of the projectile released from NASA Deep Impact spacecraft on the nucleus of comet 9P/Tempel 1 generated a hot plume. Afterwards ejecta were created, and material moved slowly in a form of a dust cloud, which dissipated during several days after the impact. Here we report a study about the distribution of terminal velocities of the particles ejected by the impact. This is performed by the development and application of an ill-conditioned inverse problem approach. We model the light-curves as seen by the Narrow Angle Camera (NAC) of OSIRIS onboard the ESA spacecraft Rosetta, and we compare them with the OSIRIS observations. Terminal velocities are derived using a maximum likelihood estimator. The dust velocity distribution is well constrained, and peaks at around 220 m s^{-1}, which is in good agreement with published estimates of the expansion velocities of the dust cloud. Measured and modeled velocity of the dust cloud suggests that the impact ejecta were quickly accelerated by the gas in the cometary coma. This analysis provides a more thorough understanding of the properties (velocity and mass of dust) of the Deep Impact dust cloud.

Ecosystem function and services provided by the deep sea

NASA Astrophysics Data System (ADS)

Thurber, A. R.; Sweetman, A. K.; Narayanaswamy, B. E.; Jones, D. O. B.; Ingels, J.; Hansman, R. L.

2014-07-01

The deep sea is often viewed as a vast, dark, remote, and inhospitable environment, yet the deep ocean and seafloor are crucial to our lives through the services that they provide. Our understanding of how the deep sea functions remains limited, but when treated synoptically, a diversity of supporting, provisioning, regulating and cultural services becomes apparent. The biological pump transports carbon from the atmosphere into deep-ocean water masses that are separated over prolonged periods, reducing the impact of anthropogenic carbon release. Microbial oxidation of methane keeps another potent greenhouse gas out of the atmosphere while trapping carbon in authigenic carbonates. Nutrient regeneration by all faunal size classes provides the elements necessary for fueling surface productivity and fisheries, and microbial processes detoxify a diversity of compounds. Each of these processes occur on a very small scale, yet considering the vast area over which they occur they become important for the global functioning of the ocean. The deep sea also provides a wealth of resources, including fish stocks, enormous bioprospecting potential, and elements and energy reserves that are currently being extracted and will be increasingly important in the near future. Society benefits from the intrigue and mystery, the strange life forms, and the great unknown that has acted as a muse for inspiration and imagination since near the beginning of civilization. While many functions occur on the scale of microns to meters and timescales up to years, the derived services that result are only useful after centuries of integrated activity. This vast dark habitat, which covers the majority of the globe, harbors processes that directly impact humans in a variety of ways; however, the same traits that differentiate it from terrestrial or shallow marine systems also result in a greater need for integrated spatial and temporal understanding as it experiences increased use by society. In this manuscript we aim to provide a foundation for informed conservation and management of the deep sea by summarizing the important role of the deep sea in society.

A Comprehensive Phylogenetic Analysis of the Scleractinia (Cnidaria, Anthozoa) Based on Mitochondrial CO1 Sequence Data

PubMed Central

Kitahara, Marcelo V.; Cairns, Stephen D.; Stolarski, Jarosław; Blair, David; Miller, David J.

2010-01-01

Background Classical morphological taxonomy places the approximately 1400 recognized species of Scleractinia (hard corals) into 27 families, but many aspects of coral evolution remain unclear despite the application of molecular phylogenetic methods. In part, this may be a consequence of such studies focusing on the reef-building (shallow water and zooxanthellate) Scleractinia, and largely ignoring the large number of deep-sea species. To better understand broad patterns of coral evolution, we generated molecular data for a broad and representative range of deep sea scleractinians collected off New Caledonia and Australia during the last decade, and conducted the most comprehensive molecular phylogenetic analysis to date of the order Scleractinia. Methodology Partial (595 bp) sequences of the mitochondrial cytochrome oxidase subunit 1 (CO1) gene were determined for 65 deep-sea (azooxanthellate) scleractinians and 11 shallow-water species. These new data were aligned with 158 published sequences, generating a 234 taxon dataset representing 25 of the 27 currently recognized scleractinian families. Principal Findings/Conclusions There was a striking discrepancy between the taxonomic validity of coral families consisting predominantly of deep-sea or shallow-water species. Most families composed predominantly of deep-sea azooxanthellate species were monophyletic in both maximum likelihood and Bayesian analyses but, by contrast (and consistent with previous studies), most families composed predominantly of shallow-water zooxanthellate taxa were polyphyletic, although Acroporidae, Poritidae, Pocilloporidae, and Fungiidae were exceptions to this general pattern. One factor contributing to this inconsistency may be the greater environmental stability of deep-sea environments, effectively removing taxonomic “noise” contributed by phenotypic plasticity. Our phylogenetic analyses imply that the most basal extant scleractinians are azooxanthellate solitary corals from deep-water, their divergence predating that of the robust and complex corals. Deep-sea corals are likely to be critical to understanding anthozoan evolution and the origins of the Scleractinia. PMID:20628613

DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

PubMed

Lanchantin, Jack; Singh, Ritambhara; Wang, Beilun; Qi, Yanjun

2017-01-01

Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals and give insights as to why TFs bind to certain locations. In this paper, we propose a toolkit called the Deep Motif Dashboard (DeMo Dashboard) which provides a suite of visualization strategies to extract motifs, or sequence patterns from deep neural network models for TFBS classification. We demonstrate how to visualize and understand three important DNN models: convolutional, recurrent, and convolutional-recurrent networks. Our first visualization method is finding a test sequence's saliency map which uses first-order derivatives to describe the importance of each nucleotide in making the final prediction. Second, considering recurrent models make predictions in a temporal manner (from one end of a TFBS sequence to the other), we introduce temporal output scores, indicating the prediction score of a model over time for a sequential input. Lastly, a class-specific visualization strategy finds the optimal input sequence for a given TFBS positive class via stochastic gradient optimization. Our experimental results indicate that a convolutional-recurrent architecture performs the best among the three architectures. The visualization techniques indicate that CNN-RNN makes predictions by modeling both motifs as well as dependencies among them.

Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks

PubMed Central

Lanchantin, Jack; Singh, Ritambhara; Wang, Beilun; Qi, Yanjun

2018-01-01

Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals and give insights as to why TFs bind to certain locations. In this paper, we propose a toolkit called the Deep Motif Dashboard (DeMo Dashboard) which provides a suite of visualization strategies to extract motifs, or sequence patterns from deep neural network models for TFBS classification. We demonstrate how to visualize and understand three important DNN models: convolutional, recurrent, and convolutional-recurrent networks. Our first visualization method is finding a test sequence’s saliency map which uses first-order derivatives to describe the importance of each nucleotide in making the final prediction. Second, considering recurrent models make predictions in a temporal manner (from one end of a TFBS sequence to the other), we introduce temporal output scores, indicating the prediction score of a model over time for a sequential input. Lastly, a class-specific visualization strategy finds the optimal input sequence for a given TFBS positive class via stochastic gradient optimization. Our experimental results indicate that a convolutional-recurrent architecture performs the best among the three architectures. The visualization techniques indicate that CNN-RNN makes predictions by modeling both motifs as well as dependencies among them. PMID:27896980

Anomalies of rupture velocity in deep earthquakes

NASA Astrophysics Data System (ADS)

Suzuki, M.; Yagi, Y.

2010-12-01

Explaining deep seismicity is a long-standing challenge in earth science. Deeper than 300 km, the occurrence rate of earthquakes with depth remains at a low level until ~530 km depth, then rises until ~600 km, finally terminate near 700 km. Given the difficulty of estimating fracture properties and observing the stress field in the mantle transition zone (410-660 km), the seismic source processes of deep earthquakes are the most important information for understanding the distribution of deep seismicity. However, in a compilation of seismic source models of deep earthquakes, the source parameters for individual deep earthquakes are quite varied [Frohlich, 2006]. Rupture velocities for deep earthquakes estimated using seismic waveforms range from 0.3 to 0.9Vs, where Vs is the shear wave velocity, a considerably wider range than the velocities for shallow earthquakes. The uncertainty of seismic source models prevents us from determining the main characteristics of the rupture process and understanding the physical mechanisms of deep earthquakes. Recently, the back projection method has been used to derive a detailed and stable seismic source image from dense seismic network observations [e.g., Ishii et al., 2005; Walker et al., 2005]. Using this method, we can obtain an image of the seismic source process from the observed data without a priori constraints or discarding parameters. We applied the back projection method to teleseismic P-waveforms of 24 large, deep earthquakes (moment magnitude Mw ≥ 7.0, depth ≥ 300 km) recorded since 1994 by the Data Management Center of the Incorporated Research Institutions for Seismology (IRIS-DMC) and reported in the U.S. Geological Survey (USGS) catalog, and constructed seismic source models of deep earthquakes. By imaging the seismic rupture process for a set of recent deep earthquakes, we found that the rupture velocities are less than about 0.6Vs except in the depth range of 530 to 600 km. This is consistent with the depth variation of deep seismicity: it peaks between about 530 and 600 km, where the fast rupture earthquakes (greater than 0.7Vs) are observed. Similarly, aftershock productivity is particularly low from 300 to 550 km depth and increases markedly at depth greater than 550 km [e.g., Persh and Houston, 2004]. We propose that large fracture surface energy (Gc) value for deep earthquakes generally prevent the acceleration of dynamic rupture propagation and generation of earthquakes between 300 and 700 km depth, whereas small Gc value in the exceptional depth range promote dynamic rupture propagation and explain the seismicity peak near 600 km.

Fingering and fracturing during multiphase flow in porous media (Invited)

NASA Astrophysics Data System (ADS)

Juanes, R.

2013-12-01

The displacement of one fluid by another in a porous medium give rise to a rich variety of hydrodynamic instabilities. Beyond their scientific value as fascinating models of pattern formation, unstable porous-media flows are essential to understanding many natural and man-made processes, including water infiltration in the vadose zone, carbon dioxide injection and storage in deep saline aquifers, and hydrocarbon recovery. Here, we review the pattern-selection mechanisms of a wide spectrum of porous-media flows that develop hydrodynamic instabilities, discuss their origin and the mathematical models that have been used to describe them. We point out many challenges that remain to be resolved in the context of multiphase flows, and suggest modeling approaches that may offer new quantitative understanding.

How to Better Understand the Diverse Mathematical Thinking of Learners

ERIC Educational Resources Information Center

Hunt, Jessica

2015-01-01

In this article Jessica Hunt explores the use of clinical interviews to gain a deep understanding of students' knowledge. Examples of clinical interviews are provided and advice for planning, giving and interpreting the results of interviews is also included.

Transcriptomes and expression profiling of deep-sea corals from the Red Sea provide insight into the biology of azooxanthellate corals.

PubMed

Yum, Lauren K; Baumgarten, Sebastian; Röthig, Till; Roder, Cornelia; Roik, Anna; Michell, Craig; Voolstra, Christian R

2017-07-25

Despite the importance of deep-sea corals, our current understanding of their ecology and evolution is limited due to difficulties in sampling and studying deep-sea environments. Moreover, a recent re-evaluation of habitat limitations has been suggested after characterization of deep-sea corals in the Red Sea, where they live at temperatures of above 20 °C at low oxygen concentrations. To gain further insight into the biology of deep-sea corals, we produced reference transcriptomes and studied gene expression of three deep-sea coral species from the Red Sea, i.e. Dendrophyllia sp., Eguchipsammia fistula, and Rhizotrochus typus. Our analyses suggest that deep-sea coral employ mitochondrial hypometabolism and anaerobic glycolysis to manage low oxygen conditions present in the Red Sea. Notably, we found expression of genes related to surface cilia motion that presumably enhance small particle transport rates in the oligotrophic deep-sea environment. This is the first study to characterize transcriptomes and in situ gene expression for deep-sea corals. Our work offers several mechanisms by which deep-sea corals might cope with the distinct environmental conditions present in the Red Sea As such, our data provide direction for future research and further insight to organismal response of deep-sea coral to environmental change and ocean warming.

Iris Transponder-Communications and Navigation for Deep Space

NASA Technical Reports Server (NTRS)

Duncan, Courtney B.; Smith, Amy E.; Aguirre, Fernando H.

2014-01-01

The Jet Propulsion Laboratory has developed the Iris CubeSat compatible deep space transponder for INSPIRE, the first CubeSat to deep space. Iris is 0.4 U, 0.4 kg, consumes 12.8 W, and interoperates with NASA's Deep Space Network (DSN) on X-Band frequencies (7.2 GHz uplink, 8.4 GHz downlink) for command, telemetry, and navigation. This talk discusses the Iris for INSPIRE, it's features and requirements; future developments and improvements underway; deep space and proximity operations applications for Iris; high rate earth orbit variants; and ground requirements, such as are implemented in the DSN, for deep space operations.

Understanding the Effects of Collisional Evolution and Spacecraft Impact Experiments on Comets and Asteroids

NASA Technical Reports Server (NTRS)

Lederer, S.M.; Jensen, E.A.; Fane, M.; Smith, D.C.; Holmes, J.; Keller, L.P.; Lindsay, S.S.; Wooden, D.H.; Whizin, A.; Cintala, M.J.;

Deep Knowledge: Learning to Teach Science for Understanding and Equity. Teaching for Social Justice

ERIC Educational Resources Information Center

Larkin, Douglas B.

2013-01-01

"Deep Knowledge" is a book about how people's ideas change as they learn to teach. Using the experiences of six middle and high school student teachers as they learn to teach science in diverse classrooms, Larkin explores how their work changes the way they think about students, society, schools, and science itself. Through engaging case stories,…

BEETLE II: Deep Natural Language Understanding and Automatic Feedback Generation for Intelligent Tutoring in Basic Electricity and Electronics

ERIC Educational Resources Information Center

Dzikovska, Myroslava; Steinhauser, Natalie; Farrow, Elaine; Moore, Johanna; Campbell, Gwendolyn

2014-01-01

Within STEM domains, physics is considered to be one of the most difficult topics to master, in part because many of the underlying principles are counter-intuitive. Effective teaching methods rely on engaging the student in active experimentation and encouraging deep reasoning, often through the use of self-explanation. Supporting such…

Using an In-Class Simulation in the First Accounting Class: Moving from Surface to Deep Learning

ERIC Educational Resources Information Center

Phillips, Mary E.; Graeff, Timothy R.

2014-01-01

As students often find the first accounting class to be abstract and difficult to understand, the authors designed an in-class simulation as an intervention to move students toward deep learning and away from surface learning. The simulation consists of buying and selling merchandise and accounting for transactions. The simulation is an effective…

Metagenetic community analysis of microbial eukaryotes illuminates biogeographic patterns in deep-sea and shallow water sediments

PubMed Central

Bik, Holly M.; Sung, Way; De Ley, Paul; Baldwin, James G.; Sharma, Jyotsna; Rocha-Olivares, Axayácatl; Thomas, W. Kelley

2011-01-01

Summary Microbial eukaryotes (nematodes, protists, fungi, etc., loosely referred to as meiofauna) are ubiquitous in marine sediments and likely play pivotal roles in maintaining ecosystem function. Although the deep-sea benthos represents one of the world’s largest habitats, we lack a firm understanding of the biodiversity and community interactions amongst meiobenthic organisms in this ecosystem. Within this vast environment key questions concerning the historical genetic structure of species remain a mystery, yet have profound implications for our understanding of global biodiversity and how we perceive and mitigate the impact of environmental change and anthropogenic disturbance. Using a metagenetic approach, we present an assessment of microbial eukaryote communities across depth (shallow water to abyssal) and ocean basins (deep-sea Pacific and Atlantic). Within the 12 sites examined, our results suggest that some taxa can maintain eurybathic ranges and cosmopolitan deep-sea distributions, but the majority of species appear to be regionally restricted. For OCTUs reporting wide distributions, there appears to be a taxonomic bias towards a small subset of taxa in most phyla; such bias may be driven by specific life history traits amongst these organisms. In addition, low genetic divergence between geographically disparate deep-sea sites suggests either a shorter coalescence time between deep-sea regions or slower rates of evolution across this vast oceanic ecosystem. While high-throughput studies allow for broad assessment of genetic patterns across microbial eukaryote communities, intragenomic variation in rRNA gene copies and the patchy coverage of reference databases currently present substantial challenges for robust taxonomic interpretations of eukaryotic datasets. PMID:21985648

Deep Operations in Airland Battle Doctrine: The Employment of U.S. Ground Forces in Deep Operational Maneuver

DTIC Science & Technology

1989-05-16

development and is manifested today in the Operational .Maneuver Group. As the name implies, the Soviet emphiasis is at the operational level. The mission of...high-intensity war! 10 answer this question I (1) analyze Soviet deep operations theory to determine how their concept developed and what they expect...USA, 32 pageF., In Soviet Army doctrine, deep operations has been a long time in development and is manifested today in the Operational Maneuver Group

Species-energy relationship in the deep sea: A test using the Quaternary fossil record

USGS Publications Warehouse

Hunt, G.; Cronin, T. M.; Roy, K.

2005-01-01

Little is known about the processes regulating species richness in deep-sea communities. Here we take advantage of natural experiments involving climate change to test whether predictions of the species-energy hypothesis hold in the deep sea. In addition, we test for the relationship between temperature and species richness predicted by a recent model based on biochemical kinetics of metabolism. Using the deep-sea fossil record of benthic foraminifera and statistical meta-analyses of temperature-richness and productivity-richness relationships in 10 deep-sea cores, we show that temperature but not productivity is a significant predictor of species richness over the past c. 130 000 years. Our results not only show that the temperature-richness relationship in the deep-sea is remarkably similar to that found in terrestrial and shallow marine habitats, but also that species richness tracks temperature change over geological time, at least on scales of c. 100 000 years. Thus, predicting biotic response to global climate change in the deep sea would require better understanding of how temperature regulates the occurrences and geographical ranges of species. ??2005 Blackwell Publishing Ltd/CNRS.

Gene Ontology: Pitfalls, Biases, and Remedies.

PubMed

Gaudet, Pascale; Dessimoz, Christophe

2017-01-01

The Gene Ontology (GO) is a formidable resource, but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its structure or how it is developed, which is both a strength and a weakness. In this chapter, we discuss some common misinterpretations of the ontology and the annotations. A better understanding of the pitfalls and the biases in the GO should help users make the most of this very rich resource. We also review some of the misconceptions and misleading assumptions commonly made about GO, including the effect of data incompleteness, the importance of annotation qualifiers, and the transitivity or lack thereof associated with different ontology relations. We also discuss several biases that can confound aggregate analyses such as gene enrichment analyses. For each of these pitfalls and biases, we suggest remedies and best practices.

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

PubMed

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

2017-09-05

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

GANViz: A Visual Analytics Approach to Understand the Adversarial Game.

PubMed

Wang, Junpeng; Gou, Liang; Yang, Hao; Shen, Han-Wei

2018-06-01

Generative models bear promising implications to learn data representations in an unsupervised fashion with deep learning. Generative Adversarial Nets (GAN) is one of the most popular frameworks in this arena. Despite the promising results from different types of GANs, in-depth understanding on the adversarial training process of the models remains a challenge to domain experts. The complexity and the potential long-time training process of the models make it hard to evaluate, interpret, and optimize them. In this work, guided by practical needs from domain experts, we design and develop a visual analytics system, GANViz, aiming to help experts understand the adversarial process of GANs in-depth. Specifically, GANViz evaluates the model performance of two subnetworks of GANs, provides evidence and interpretations of the models' performance, and empowers comparative analysis with the evidence. Through our case studies with two real-world datasets, we demonstrate that GANViz can provide useful insight into helping domain experts understand, interpret, evaluate, and potentially improve GAN models.

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

PubMed

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

Deep-Earth reactor: nuclear fission, helium, and the geomagnetic field.

PubMed

Hollenbach, D F; Herndon, J M

2001-09-25

Geomagnetic field reversals and changes in intensity are understandable from an energy standpoint as natural consequences of intermittent and/or variable nuclear fission chain reactions deep within the Earth. Moreover, deep-Earth production of helium, having (3)He/(4)He ratios within the range observed from deep-mantle sources, is demonstrated to be a consequence of nuclear fission. Numerical simulations of a planetary-scale geo-reactor were made by using the SCALE sequence of codes. The results clearly demonstrate that such a geo-reactor (i) would function as a fast-neutron fuel breeder reactor; (ii) could, under appropriate conditions, operate over the entire period of geologic time; and (iii) would function in such a manner as to yield variable and/or intermittent output power.

DEEP DESULFURIZATION OF DIESEL FUELS BY A NOVEL INTEGRATED APPROACH

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

Xiaoliang Ma; Uday Turaga; Shingo Watanabe

2004-05-01

The overall objective of this project is to explore a new desulfurization system concept, which consists of efficient separation of the refractory sulfur compounds from diesel fuel by selective adsorption, and effective hydrodesulfurization of the concentrated fraction of the refractory sulfur compounds in diesel fuels. Our approaches focused on (1) selecting and developing new adsorbents for selective adsorption of sulfur or sulfur compounds in commercial diesel fuel; (2) conducting the adsorption desulfurization of model fuels and real diesel fuels by the selective-adsorption-for-removing-sulfur (PSUSARS) process over various developed adsorbents, and examining the adsorptive desulfurization performance of various adsorbents; (3) developing andmore » evaluating the regeneration methods for various spent adsorbent; (4) developing new catalysts for hydrodesulfurization of the refractory sulfur existing in the commercial diesel fuel; (5) on the basis of the fundamental understanding of the adsorptive performance and regeneration natures of the adsorbents, further confirming and improving the conceptual design of the novel PSU-SARS process for deep desulfurization of diesel fuel Three types of adsorbents, the metal-chloride-based adsorbents, the activated nickel-based adsorbents and the metal-sulfide-based adsorbents, have been developed for selective adsorption desulfurization of liquid hydrocarbons. All of three types of the adsorbents exhibit the significant selectivity for sulfur compounds, including alkyl dibenzothiophenes (DBTs), in diesel fuel. Adsorption desulfurization of real diesel fuels (regular diesel fuel (DF), S: 325 ppmw; low sulfur diesel fuel (LSD-I), S: 47 ppmw) over the nickel-based adsorbents (A-2 and A-5) has been conducted at different conditions by using a flowing system. The adsorption capacity of DF over A-2 corresponding to an outlet sulfur level of 30 ppmw is 2.8 mg-S/g-A. The adsorption capacity of LSD-I over A-5 corresponding to the break-through point at 5.0 ppmw sulfur level is 0.35 mg-S/g-A. The spent A-5 can be regenerated by using H2 gas at a flowing rate of 40-50 ml/min, 500 C, and ambient pressure. Adsorption desulfurization of model diesel fuels over metal-sulfide-based adsorbents (A-6-1 and A-6-2) has been conducted at different temperatures to examine the capacity and selectivity of the adsorbents. A regeneration method for the spent metal-sulfide-based adsorbents has been developed. The spent A-6-1 can be easily regenerated by washing the spent adsorbent with a polar solvent followed by heating the adsorbent bed to remove the remainder solvent. Almost all adsorption capacity of the fresh A-6-1 can be recovered after the regeneration. On the other hand, a MCM-41-supported HDS catalyst was developed for deep desulfurization of the refractory sulfur compounds. The results show that the developed MCM-41-supported catalyst demonstrates consistently higher activity for the HDS of the refractory dibenzothiophenic sulfur compounds than the commercial catalyst. On the basis of the fundamental understanding of the adsorptive performance and regeneration natures of the adsorbents, the conceptual design of the novel PSU-SARS process for deep desulfurization of diesel fuel is confirmed and improved further.« less

Crystal Clear Assessment

ERIC Educational Resources Information Center

Stone, Jody H.; Lockhart, Amy

2013-01-01

Great science activities don't just happen; they are orchestrated by highly skilled teachers who are creative, caring, and innovative. Effective classroom teachers possess a deep understanding of the developmental characteristics of their students and are adept at translating this understanding into opportunities for individual students to…

From Offshore to Onshore: Multiple Origins of Shallow-Water Corals from Deep-Sea Ancestors

PubMed Central

Lindner, Alberto; Cairns, Stephen D.; Cunningham, Clifford W.

2008-01-01

Shallow-water tropical reefs and the deep sea represent the two most diverse marine environments. Understanding the origin and diversification of this biodiversity is a major quest in ecology and evolution. The most prominent and well-supported explanation, articulated since the first explorations of the deep sea, holds that benthic marine fauna originated in shallow, onshore environments, and diversified into deeper waters. In contrast, evidence that groups of marine organisms originated in the deep sea is limited, and the possibility that deep-water taxa have contributed to the formation of shallow-water communities remains untested with phylogenetic methods. Here we show that stylasterid corals (Cnidaria: Hydrozoa: Stylasteridae)—the second most diverse group of hard corals—originated and diversified extensively in the deep sea, and subsequently invaded shallow waters. Our phylogenetic results show that deep-water stylasterid corals have invaded the shallow-water tropics three times, with one additional invasion of the shallow-water temperate zone. Our results also show that anti-predatory innovations arose in the deep sea, but were not involved in the shallow-water invasions. These findings are the first robust evidence that an important group of tropical shallow-water marine animals evolved from deep-water ancestors. PMID:18560569

Differential impact of thalamic versus subthalamic deep brain stimulation on lexical processing.

PubMed

Krugel, Lea K; Ehlen, Felicitas; Tiedt, Hannes O; Kühn, Andrea A; Klostermann, Fabian

2014-10-01

Roles of subcortical structures in language processing are vague, but, interestingly, basal ganglia and thalamic Deep Brain Stimulation can go along with reduced lexical capacities. To deepen the understanding of this impact, we assessed word processing as a function of thalamic versus subthalamic Deep Brain Stimulation. Ten essential tremor patients treated with thalamic and 14 Parkinson׳s disease patients with subthalamic Deep Brain Stimulation performed an acoustic Lexical Decision Task ON and OFF stimulation. Combined analysis of task performance and event-related potentials allowed the determination of processing speed, priming effects, and N400 as neurophysiological correlate of lexical stimulus processing. 12 age-matched healthy participants acted as control subjects. Thalamic Deep Brain Stimulation prolonged word decisions and reduced N400 potentials. No comparable ON-OFF effects were present in patients with subthalamic Deep Brain Stimulation. In the latter group of patients with Parkinson' disease, N400 amplitudes were, however, abnormally low, whether under active or inactive Deep Brain Stimulation. In conclusion, performance speed and N400 appear to be influenced by state functions, modulated by thalamic, but not subthalamic Deep Brain Stimulation, compatible with concepts of thalamo-cortical engagement in word processing. Clinically, these findings specify cognitive sequels of Deep Brain Stimulation in a target-specific way. Copyright © 2014 Elsevier Ltd. All rights reserved.

Understanding Ice Shelf Basal Melting Using Convergent ICEPOD Data Sets: ROSETTA-Ice Study of Ross Ice Shelf

NASA Astrophysics Data System (ADS)

Bell, R. E.; Frearson, N.; Tinto, K. J.; Das, I.; Fricker, H. A.; Siddoway, C. S.; Padman, L.

2017-12-01

The future stability of the ice shelves surrounding Antarctica will be susceptible to increases in both surface and basal melt as the atmosphere and ocean warm. The ROSETTA-Ice program is targeted at using the ICEPOD airborne technology to produce new constraints on Ross Ice Shelf, the underlying ocean, bathymetry, and geologic setting, using radar sounding, gravimetry and laser altimetry. This convergent approach to studying the ice-shelf and basal processes enables us to develop an understanding of the fundamental controls on ice-shelf evolution. This work leverages the stratigraphy of the ice shelf, which is detected as individual reflectors by the shallow-ice radar and is often associated with surface scour, form close to the grounding line or pinning points on the ice shelf. Surface accumulation on the ice shelf buries these reflectors as the ice flows towards the calving front. This distinctive stratigraphy can be traced across the ice shelf for the major East Antarctic outlet glaciers and West Antarctic ice streams. Changes in the ice thickness below these reflectors are a result of strain and basal melting and freezing. Correcting the estimated thickness changes for strain using RIGGS strain measurements, we can develop decadal-resolution flowline distributions of basal melt. Close to East Antarctica elevated melt-rates (>1 m/yr) are found 60-100 km from the calving front. On the West Antarctic side high melt rates primarily develop within 10 km of the calving front. The East Antarctic side of Ross Ice Shelf is dominated by melt driven by saline water masses that develop in Ross Sea polynyas, while the melting on the West Antarctic side next to Hayes Bank is associated with modified Continental Deep Water transported along the continental shelf. The two sides of Ross Ice Shelf experience differing basal melt in part due to the duality in the underlying geologic structure: the East Antarctic side consists of relatively dense crust, with low amplitude magnetic anomalies, and deep bathymetry. The West Antarctic side displays high amplitude magnetic anomalies, lower densities and shallower water depths. The geologically-controlled bathymetry influences the access of water masses capable of basal melting into the ice shelf cavity with the deep troughs on the East Antarctic side facilitating melting.

Respiratory flows during early childhood: Computational models to examine therapeutic aerosols in the developing airways

NASA Astrophysics Data System (ADS)

Tenenbaum-Katan, Janna; Hofemeier, Philipp; Sznitman, Josué; Janna Tenenbaum-Katan Team

2015-11-01

Inhalation therapy is the cornerstone of early-childhood respiratory treatments, as well as a rising potential for systemic drug delivery and pulmonary vaccination. As such, indispensable understanding of respiratory flow phenomena, coupled with particle transport at the deep regions of children's lungs is necessary to attain efficient targeting of aerosol therapy. However, fundamental research of pulmonary transport is overwhelmingly focused on adults. In our study, we have developed an anatomically-inspired computational model of representing pulmonary acinar regions at several age points during a child's development. Our numerical simulations examine respiratory flows and particle deposition maps within the acinar model, accounting for varying age dependant anatomical considerations and ventilation patterns. Resulting deposition maps of aerosols alter with age, such findings might suggest that medication protocols of inhalation therapy in young children should be considered to be accordingly amended with the child's development. Additionally to understanding basic scientific concepts of age effects on aerosol deposition, our research can potentially contribute practical guidelines to therapy protocols, and its' necessary modifications with age. We acknowledge the support of the ISF and the Israeli ministry of Science.

JAMSTEC E-library of Deep-sea Images (J-EDI) Realizes a Virtual Journey to the Earth's Unexplored Deep Ocean

NASA Astrophysics Data System (ADS)

Sasaki, T.; Azuma, S.; Matsuda, S.; Nagayama, A.; Ogido, M.; Saito, H.; Hanafusa, Y.

2016-12-01

The Japan Agency for Marine-Earth Science and Technology (JAMSTEC) archives a large amount of deep-sea research videos and photos obtained by JAMSTEC's research submersibles and vehicles with cameras. The web site "JAMSTEC E-library of Deep-sea Images : J-EDI" (http://www.godac.jamstec.go.jp/jedi/e/) has made videos and photos available to the public via the Internet since 2011. Users can search for target videos and photos by keywords, easy-to-understand icons, and dive information at J-EDI because operating staffs classify videos and photos as to contents, e.g. living organism and geological environment, and add comments to them.Dive survey data including videos and photos are not only valiant academically but also helpful for education and outreach activities. With the aim of the improvement of visibility for broader communities, we added new functions of 3-dimensional display synchronized various dive survey data with videos in this year.New Functions Users can search for dive survey data by 3D maps with plotted dive points using the WebGL virtual map engine "Cesium". By selecting a dive point, users can watch deep-sea videos and photos and associated environmental data, e.g. water temperature, salinity, rock and biological sample photos, obtained by the dive survey. Users can browse a dive track visualized in 3D virtual spaces using the WebGL JavaScript library. By synchronizing this virtual dive track with videos, users can watch deep-sea videos recorded at a point on a dive track. Users can play an animation which a submersible-shaped polygon automatically traces a 3D virtual dive track and displays of dive survey data are synchronized with tracing a dive track. Users can directly refer to additional information of other JAMSTEC data sites such as marine biodiversity database, marine biological sample database, rock sample database, and cruise and dive information database, on each page which a 3D virtual dive track is displayed. A 3D visualization of a dive track makes users experience a virtual dive survey. In addition, by synchronizing a virtual dive track with videos, it is easy to understand living organisms and geological environments of a dive point. Therefore, these functions will visually support understanding of deep-sea environments in lectures and educational activities.

Influences of spatial and temporal variability of sound scattering layers on deep diving odontocete behavior

NASA Astrophysics Data System (ADS)

Copeland, Adrienne Marie

Patchiness of prey can influence the behavior of a predator, as predicted by the optimal foraging theory which states that an animal will maximize the energy gain while minimizing energy loss. While this relationship has been studied and is relatively well understood in some terrestrial systems, the same is far from true in marine systems. It is as important to investigate this in the marine realm in order to better understand predator distribution and behavior. Micronekton, organisms from 2-20 cm, might be a key component in understanding this as it is potentially an essential link in the food web between primary producers and higher trophic levels, including cephalopods which are primary prey items of deep diving odontocetes (toothed whales). My dissertation assesses the spatial and temporal variability of micronekton in the Northwestern Hawaiian Islands (NWHI), the Main Hawaiian Islands' (MHI) Island of Hawaii, and the Gulf of Mexico (GOM). Additionally it focuses on understanding the relationship between the spatial distribution of micronekton and environmental and geographic factors, and how the spatial and temporal variability of this micronekton relates to deep diving odontocete foraging. I used both an active Simrad EK60 echosounder system to collect water column micronekton backscatter and a passive acoustic system to detect the presence of echolocation clicks from deep diving beaked, sperm, and short-finned pilot whales. My results provide insight into what might be contributing to hotspots of micronekton which formed discrete layers in all locations, a shallow scattering layer (SSL) from the surface to about 200 m and a deep scattering layer (DSL) starting at about 350 m. In both the GOM and the NWHI, the bathymetry and proximity to shore influenced the amount of micronekton backscatter with locations closer to shore and at shallower depths having higher backscatter. We found in all three locations that some species of deep diving odontocetes were searching for prey in these areas with higher micronekton backscatter. Beaked whales in the NWHI, short-finned pilot whales in the NWHI and MHI, and sperm whales in the GOM where present in areas of higher micronekton backscatter. These hotspots of backscatter may be good predictors of the distribution of some deep-diving toothed whale foragers since the hotspots potentially indicate a food web supporting the prey of the cetaceans.

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

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

Lindstrom, Jason

2010-01-31

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

Overview of North Ecliptic Pole Deep Multi-Wavelength Survey Nep-Deep

NASA Astrophysics Data System (ADS)

Matsuhara, H.; Wada, T.; Oi, N.; Takagi, T.; Nakagawa, T.; Murata, K.; Goto, T.; Oyabu, S.; Takeuchi, T. T.; Malek, K.; Solarz, A.; Ohyama, Y.; Miyaji, T.; Krumpe, M.; Lee, H. M.; Im, M.; Serjeant, S.; Pearson, C. P.; White, G. J.; Malkan, M. A.; Hanami, H.; Ishigaki, T.; Burgarella, D.; Buat, V.; Pollo, A.

2017-03-01

The recent updates of the North Ecliptic Pole deep (0.5~deg$^2$, NEP-Deep) multi-wavelength survey covering from X-ray to radio-wave is presented. The NEP-Deep provides us with several thousands of 15~$\\mu$m or 18~$\\mu$m selected sample of galaxies, which is the largest sample ever made at this wavelengths. A continuous filter coverage in the mid-infrared wavelength (7, 9, 11, 15, 18, and 24~$\\mu$m) is unique and vital to diagnose the contributions from starbursts and AGNs in the galaxies out to $z$=2.The new goal of the project is to resolve the nature of the cosmic star formation history at the violent epoch (e.g. $z$=1--2), and to find a clue to understand its decline from $z$=1 to present universe by utilizing the unique power of the multi-wavelength survey. The progress in this context is briefly mentioned.

Monsoon dependent ecosystems: Implications of the vertical distribution of soil moisture on land surface-atmosphere interactions

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Zulia M.

Uncertainty of predicted change in precipitation frequency and intensity motivates the scientific community to better understand, quantify, and model the possible outcome of dryland ecosystems. In pulse dependent ecosystems (i.e. monsoon driven) soil moisture is tightly linked to atmospheric processes. Here, I analyze three overarching questions; Q1) How does soil moisture presence or absence in a shallow or deep layer influence the surface energy budget and planetary boundary layer characteristics?, Q2) What is the role of vegetation on ecosystem albedo in the presence or absence of deep soil moisture?, Q3) Can we develop empirical relationships between soil moisture and the planetary boundary layer height to help evaluate the role of future precipitation changes in land surface atmosphere interactions? . To address these questions I use a conceptual framework based on the presence or absence of soil moisture in a shallow or deep layer. I define these layers by using root profiles and establish soil moisture thresholds for each layer using four years of observations from the Santa Rita Creosote Ameriflux site. Soil moisture drydown curves were used to establish the shallow layer threshold in the shallow layer, while NEE (Net Ecosystem Exchange of carbon dioxide) was used to define the deep soil moisture threshold. Four cases were generated using these thresholds: Case 1, dry shallow layer and dry deep layer; Case 2, wet shallow layer and dry deep layer; Case 3, wet shallow layer and wet deep layer, and Case 4 dry shallow and wet deep layer. Using this framework, I related data from the Ameriflux site SRC (Santa Rita Creosote) from 2008 to 2012 and from atmospheric soundings from the nearby Tucson Airport; conducted field campaigns during 2011 and 2012 to measure albedo from individual bare and canopy patches that were then evaluated in a grid to estimate the influence of deep moisture on albedo via vegetation cover change; and evaluated the potential of using a two-layer bucket model and empirical relationships to evaluate the link between deep soil moisture and the planetary boundary layer height under changing precipitation regime. My results indicate that (1) the presence or absence of water in two layers plays a role in surface energy dynamics, (2) soil moisture presence in the deep layer is linked with decreased ecosystem albedo and planetary boundary layer height, (3) deep moisture sustains vegetation greenness and decreases albedo, and (4) empirical relationships are useful in modeling planetary boundary layer height from dryland ecosystems. Based on these results we argue that deep soil moisture plays an important role in land surface-atmosphere interactions.

Challenges and Changes: Developing Teachers' and Initial Teacher Education Students' Understandings of the Nature of Science

NASA Astrophysics Data System (ADS)

Ward, Gillian; Haigh, Mavis

2017-12-01

Teachers need an understanding of the nature of science (NOS) to enable them to incorporate NOS into their teaching of science. The current study examines the usefulness of a strategy for challenging or changing teachers' understandings of NOS. The teachers who participated in this study were 10 initial teacher education chemistry students and six experienced teachers from secondary and primary schools who were introduced to an explicit and reflective activity, a dramatic reading about a historical scientific development. Concept maps were used before and after the activity to assess teachers' knowledge of NOS. The participants also took part in a focus group interview to establish whether they perceived the activity as useful in developing their own understanding of NOS. Initial analysis led us to ask another group, comprising seven initial teacher education chemistry students, to take part in a modified study. These participants not only completed the same tasks as the previous participants but also completed a written reflection commenting on whether the activity and focus group discussion enhanced their understanding of NOS. Both Lederman et al.'s (Journal of Research in Science Teaching, 39(6), 497-521, 2002) concepts of NOS and notions of "naive" and "informed" understandings of NOS and Hay's (Studies in Higher Education, 32(1), 39-57, 2007) notions of "surface" and "deep" learning were used as frameworks to examine the participants' specific understandings of NOS and the depth of their learning. The ways in which participants' understandings of NOS were broadened or changed by taking part in the dramatic reading are presented. The impact of the data-gathering tools on the participants' professional learning is also discussed.

Understanding the Deep Earth: Slabs, Drips, Plumes and More - An On the Cutting Edge Workshop

NASA Astrophysics Data System (ADS)

Williams, M. L.; Mogk, D. W.; McDaris, J. R.

2010-12-01

Exciting new science is emerging from the study of the deep Earth using a variety of approaches: observational instrumentation (e.g. EarthScope’s USArray; IRIS), analysis of rocks (xenoliths, isotopic tracers), experimental methods (COMPRES facilities), and modeling (physical and computational, e.g. CIG program). New images and models of active faults, subducting plates, mantle drips, and rising plumes are spurring a new excitement about deep Earth processes and connections between Earth’s internal systems, the plate tectonic system, and the physiography of Earth’s surface. The integration of these lines of research presents unique opportunities and also challenges in geoscience education. How can we best teach about the architecture, composition, and processes of Earth where it is hidden from direct observation. How can we make deep Earth science relevant and meaningful to students across the geoscience curriculum? And how can we use the exciting new discoveries about Earth processes to attract new students into science? To explore the intersection of research and teaching about the deep Earth, a virtual workshop was convened in February 2010 for experts in deep Earth research and undergraduate geoscience education. The six-day workshop consisted of online plenary talks, large and small group discussions, asynchronous contributions using threaded listservs and web-based work spaces, as well as development and review of new classroom and laboratory activities. The workshop goals were to: 1) help participants stay current about data, tools, services, and research related to the deep earth, 2) address the "big science questions" related to deep earth (e.g. plumes, slabs, drips, post-perovskite, etc.) and explore exciting new scientific approaches, 3) to consider ways to effectively teach about "what can't be seen", at least not directly, and 4) develop and review classroom teaching activities for undergraduate education using these data, tools, services, and research results to facilitate teaching about the deep earth across the geoscience curriculum. Another goal of the workshop was to experiment with, and evaluate the effectiveness of, the virtual format. Although there are advantages to face-to-face workshops, the virtual format was remarkably effective. The interactive discussions during synchronous presentations were vibrant, and the virtual format allowed participants to introduce references, images and ideas in real-time. The virtual nature of the workshop allowed participation by those who are not able to attend a traditional workshop, with an added benefit that participants had direct access to all their research and teaching materials to share with the workshop. Some participants broadcast the workshop ‘live’ to their classes and many brought discussions directly from the presentation to the classroom. The workshop webpage includes the workshop program with links to recordings of all presentations, discussion summaries, a collection of recommended resources about deep Earth research, and collections of peer-reviewed instructional activities. http://serc.carleton.edu/NAGTWorkshops/deepearth/index.html

What's in a label?: Multiple meanings of ‘MSM’ among same-gender-loving Black men in Mississippi

PubMed Central

Truong, Nhan; Perez-Brumer, Amaya; Burton, Melissa; Gipson, June; Hickson, DeMarc

2016-01-01

Men who have sex with men (MSM) and other same-gender-loving men continue to be disproportionately affected by HIV and AIDS, particularly among the Black population. Innovative strategies are needed to support the health of this community; however, public health efforts primarily approach MSM as a monolithic population erasing the diverse identities, practices, and sexualities within and beyond this category. To better understand diversity within MSM in a geographic region with the largest proportion of Black Americans in the U.S. and among the most heavily affected by the epidemic, the Deep South, we conducted four focus groups (n=29) with Black men who reported having sex with other men residing in Jackson, Mississippi. Results suggest multiple overlapping usages of MSM as identity and behavior, reflecting internalization of behavioral categories and co-creation of identities unique to the Black community. These narratives contribute to the literature by documenting the evolving understandings of the category ‘MSM’ among Black men to reflect intersections between race, socioeconomic status, sexual behavior, sexuality, subjectivities, and social context. Findings suggest the current monolithic approach to treating MSM may limit public health efforts in developing effective HIV prevention and promotion programs targeting same-gender-loving Black men in the Deep South. PMID:26950431

Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community

NASA Astrophysics Data System (ADS)

Ball, John E.; Anderson, Derek T.; Chan, Chee Seng

2017-10-01

In recent years, deep learning (DL), a rebranding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, and natural language processing. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV, e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should not only be aware of advancements such as DL, but also be leading researchers in this area. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools, and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as they relate to (i) inadequate data sets, (ii) human-understandable solutions for modeling physical phenomena, (iii) big data, (iv) nontraditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial, and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.

What is in a label? Multiple meanings of 'MSM' among same-gender-loving Black men in Mississippi.

PubMed

Truong, Nhan; Perez-Brumer, Amaya; Burton, Melissa; Gipson, June; Hickson, DeMarc

2016-01-01

Men who have sex with men (MSM) and other same-gender-loving (SGL) men continue to be disproportionately affected by HIV and AIDS, particularly among the Black population. Innovative strategies are needed to support the health of this community; however, public health efforts primarily approach MSM as a monolithic population erasing the diverse identities, practices, and sexualities within and beyond this category. To better understand diversity within MSM in a geographic region with the largest proportion of Black Americans in the U.S.A. and among the most heavily affected by the epidemic, the Deep South, we conducted four focus groups (n = 29) with Black men who reported having sex with other men residing in Jackson, Mississippi. Results suggest multiple overlapping usages of MSM as identity and behaviour, reflecting internalisation of behavioural categories and co-creation of identities unique to the Black community. These narratives contribute to the literature by documenting the evolving understandings of the category 'MSM' among Black men to reflect intersections between race, socioeconomic status, sexual behaviour, sexuality, subjectivities, and social context. Findings suggest the current monolithic approach to treating MSM may limit public health efforts in developing effective HIV prevention and promotion programmes targeting SGL Black men in the Deep South.

“Points requiring elucidation” about Hawaiian volcanism: Chapter 24

USGS Publications Warehouse

Poland, Michael P.; Carey, Rebecca; Cayol, Valérie; Poland, Michael P.; Weis, Dominique

2015-01-01

Hawaiian volcanoes, which are easily accessed and observed at close range, are among the most studied on the planet and have spurred great advances in the geosciences, from understanding deep Earth processes to forecasting volcanic eruptions. More than a century of continuous observation and study of Hawai‘i's volcanoes has also sharpened focus on those questions that remain unanswered. Although there is good evidence that volcanism in Hawai‘i is the result of a high-temperature upwelling plume from the mantle, the source composition and dynamics of the plume are controversial. Eruptions at the surface build the volcanoes of Hawai‘i, but important topics, including how the volcanoes grow and collapse and how magma is stored and transported, continue to be subjects of intense research. Forecasting volcanic activity is based mostly on pattern recognition, but determining and predicting the nature of eruptions, especially in serving the critical needs of hazards mitigation, require more realistic models and a greater understanding of what drives eruptive activity. These needs may be addressed by better integration among disciplines as well as by developing dynamic physics- and chemistry-based models that more thoroughly relate the physiochemical behavior of Hawaiian volcanism, from the deep Earth to the surface, to geological, geochemical, and geophysical data.

Surfing the vegetal pole in a small population: extracellular vertical transmission of an 'intracellular' deep-sea clam symbiont.

PubMed

Ikuta, Tetsuro; Igawa, Kanae; Tame, Akihiro; Kuroiwa, Tsuneyoshi; Kuroiwa, Haruko; Aoki, Yui; Takaki, Yoshihiro; Nagai, Yukiko; Ozawa, Genki; Yamamoto, Masahiro; Deguchi, Ryusaku; Fujikura, Katsunori; Maruyama, Tadashi; Yoshida, Takao

2016-05-01

Symbiont transmission is a key event for understanding the processes underlying symbiotic associations and their evolution. However, our understanding of the mechanisms of symbiont transmission remains still fragmentary. The deep-sea clam Calyptogena okutanii harbours obligate sulfur-oxidizing intracellular symbiotic bacteria in the gill epithelial cells. In this study, we determined the localization of their symbiont associating with the spawned eggs, and the population size of the symbiont transmitted via the eggs. We show that the symbionts are located on the outer surface of the egg plasma membrane at the vegetal pole, and that each egg carries approximately 400 symbiont cells, each of which contains close to 10 genomic copies. The very small population size of the symbiont transmitted via the eggs might narrow the bottleneck and increase genetic drift, while polyploidy and its transient extracellular lifestyle might slow the rate of genome reduction. Additionally, the extracellular localization of the symbiont on the egg surface may increase the chance of symbiont exchange. This new type of extracellular transovarial transmission provides insights into complex interactions between the host and symbiont, development of both host and symbiont, as well as the population dynamics underlying genetic drift and genome evolution in microorganisms.

Transition Metal Doped ZnO for Spintronics

DTIC Science & Technology

2007-07-01

TM-doped material, including understanding the role of deep level co- dopants in mediating ferromagnetism. Experiments will focus on correlating...magnetic properties (Curie temperature, moment/TM dopant ) with the TM and deep level dopant concentrations. Epitaxial film growth and ion implantation of...With Cobalt ," Florida Chapter American Vacuum Society Meeting, Orlando, FL, March 2007 3. "Carrier Type Conversion In Post Annealed ZnO:P Thin Films

Emotional effects of continuity of care on family physicians and the therapeutic relationship.

PubMed

Schultz, Karen; Delva, Dianne; Kerr, Jonathan

2012-02-01

To explore conceptions of continuity of care among family physicians in traditional practices, family medicine-trained physicians working in episodic care, and family medicine residents to better understand the emotional effects on physicians of establishing long-term relationships with patients as a starting point for developing a tool to measure the qualitative connections between physicians and their patients. Qualitative descriptive study using focus groups. Traditional family practice, family medicine residency training, and episodic-care settings in Kingston, Ont. Three groups of first-year family medicine residents (n = 18), 2 groups of family physicians in established traditional practice (n = 9), and 2 groups of family physicians working in episodic-care settings (n = 10). Using focus groups, a semistructured discussion guide, and a phenomenologic approach, we explored residents' and practising physicians' conceptions about continuity of care, predominantly exploring the emotional effects on physicians of providing care for a group of patients over time. Providing care for patients over time and developing a deep knowledge of, and often a deep connection to, patients affected physicians in various ways. Most of these effects were rewarding: feelings of connection, trust, curiosity, enhanced professional competence (diagnostically and therapeutically), personal growth, and being cared for and respected. Some, however, were distressing: anxiety, grief, frustration, boundary issues, and negative effects on personal life. Family physicians experience myriad emotions connected with providing care to patients. Knowledge of what physicians find rewarding from their long-term connections with patients, and of the difficulties that arise, might be useful in further understanding interpersonal continuity of care and the therapeutic relationship, and in informing resident education about developing therapeutic relationships, evaluating resident educational experiences with continuity of care, and addressing physician burnout.

Emotional effects of continuity of care on family physicians and the therapeutic relationship

PubMed Central

Schultz, Karen; Delva, Dianne; Kerr, Jonathan

2012-01-01

Abstract Objective To explore conceptions of continuity of care among family physicians in traditional practices, family medicine–trained physicians working in episodic care, and family medicine residents to better understand the emotional effects on physicians of establishing long-term relationships with patients as a starting point for developing a tool to measure the qualitative connections between physicians and their patients. Design Qualitative descriptive study using focus groups. Setting Traditional family practice, family medicine residency training, and episodic-care settings in Kingston, Ont. Participants Three groups of first-year family medicine residents (n = 18), 2 groups of family physicians in established traditional practice (n = 9), and 2 groups of family physicians working in episodic-care settings (n = 10). Methods Using focus groups, a semistructured discussion guide, and a phenomenologic approach, we explored residents’ and practising physicians’ conceptions about continuity of care, predominantly exploring the emotional effects on physicians of providing care for a group of patients over time. Main findings Providing care for patients over time and developing a deep knowledge of, and often a deep connection to, patients affected physicians in various ways. Most of these effects were rewarding: feelings of connection, trust, curiosity, enhanced professional competence (diagnostically and therapeutically), personal growth, and being cared for and respected. Some, however, were distressing: anxiety, grief, frustration, boundary issues, and negative effects on personal life. Conclusion Family physicians experience myriad emotions connected with providing care to patients. Knowledge of what physicians find rewarding from their long-term connections with patients, and of the difficulties that arise, might be useful in further understanding interpersonal continuity of care and the therapeutic relationship, and in informing resident education about developing therapeutic relationships, evaluating resident educational experiences with continuity of care, and addressing physician burnout. PMID:22337743

Philippine microplate tectonics and hydrocarbon exploration

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

Gallagher, J.J. Jr.

1986-07-01

Hydrocarbon traps in the Philippine Islands developed during a long, complex history of microplate tectonics. Carbonate and clastic stratigraphic traps formed during Mesozoic and early Cenozoic rifting and drifting. Hydrocarbons, generated in deep rift basins, migrated to the traps during drifting. Later Cenozoic compressional tectonic activity and concomitant faulting enhanced some traps and destroyed others. Seismic data offshore from Palawan Island reveal the early trap histories. Later trap histories can be interpreted from seismic, outcrop, and remote-sensing data. Understanding the microplate tectonic history of the Philippines is the key to interpreting trap histories.

Southeast Ecological Science Center

USGS Publications Warehouse

Pawlitz, Rachel J.

2010-01-01

Aquatic ecosystems, from deep sea reefs and coastal marshes to freshwater springs and wetlands, are home to diverse assemblages of life. These commercially and ecologically important systems are part of our national heritage, and are often treasured places or refuges that protect rare or threatened species. In the water-rich Southeastern United States, managers face the challenge of understanding how water and land use affect the region's aquatic life. The Southeast Ecological Science Center (SESC) helps address that challenge by providing objective science that can be used to evaluate proposed actions and develop management strategies.

Genes In Space-5

NASA Image and Video Library

2018-04-13

iss055e020319 (April 13, 2018) --- Flight Engineer Ricky Arnold processes of samples inside the Miniature Polymerase Chain Reaction (miniPCR) for the Genes In Space-5 experiment. The research gathered from Genes in Space-5 may be valuable in the development of procedures to maintain astronaut health and prevent an increased risk of cancer on deep space missions. The investigation also provides a deeper understanding of the human immune system, while giving student researchers a direct connection to the space program and offering hands-on educational experiences on Earth and promoting involvement in STEM fields.

Electromagnetic Induction

ERIC Educational Resources Information Center

Yochum, Hank; Vinion-Dubiel, Arlene; Granger, Jill; Lindsay, Lynne; Maass, Teresa; Mayhew, Sarah

2013-01-01

Engaging children in authentic investigation opens the doors for them to gain deep conceptual understanding in science. As students engage in investigation, they experience the practices employed by scientists and engineers, as highlighted in the Next Generation Science Standards (Achieve Inc. 2013). They also begin to understand the nature of…

EL2 and related defects in GaAs - Challenges and pitfalls. [microdefect introducing a deep donor level

NASA Technical Reports Server (NTRS)

Gatos, H. C.; Lagowski, J.

1985-01-01

The incorporation process of nonequilibrium vacancies in melt-grown GaAs is strongly complicated by deviations from stoichiometry and the presence of two sublattices. Many of the microdefects originating in these vacancies and their interactions introduce energy levels (shallow and deep) within the energy gap. The direct identification of the chemical or structural signature of these defects and its direct correlation to their electronic behavior is not generally possible. It is necessary, therefore, to rely on indirect methods and phenomenological models and deal with the associated pitfalls. EL2, a microdefect introducing a deep donor level, has been in the limelight in recent years because it is believed to be responsible for the semi-insulating behavior of undoped GaAs. Although much progress has been made towards understanding its origin and nature, some relevant questions remain unanswered. An attempt is made to assess the present status of understanding of EL2 in the light of most recent results.

Needs-Based Innovation in Interventional Radiology: The Biodesign Process.

PubMed

Steinberger, Jonathan D; Denend, Lyn; Azagury, Dan E; Brinton, Todd J; Makower, Josh; Yock, Paul G

2017-06-01

There are many possible mechanisms for innovation and bringing new technology into the marketplace. The Stanford Biodesign innovation process is based in a deep understanding of clinical unmet needs as the basis for focused ideation and development. By identifying and vetting a compelling unmet need, the aspiring innovator can "derisk" a project and maximize chances for successful development in an increasingly challenging regulatory and economic environment. As a specialty founded by tinkerers, with a history of disruptive innovation that has yielded countless new ways of delivering care with minimal invasiveness, lower morbidity, and lower cost, interventional radiologists are uniquely well positioned to identify unmet needs and develop novel solutions free of dogmatic convention. Copyright © 2017 Elsevier Inc. All rights reserved.

Two radars for the AIM mission to characterize the regolith and deep interior structure of the asteroid

NASA Astrophysics Data System (ADS)

Ciarletti, V.; Herique, A.; Plettemeier, D.

2015-12-01

Very little is known till now about the interior of asteroids. The information available has been so far mainly obtained through remote observations of the surface and inferred from theoretical modeling. Observations of asteroids deep interior and regolith structure are needed to better understand the asteroid accretion and dynamical evolution, and to provide answers that will directly improve our ability to understand and model the mechanisms driving Near Earth Asteroids (NEA) deflection and other risk mitigation techniques. Radar operating from a spacecraft is the only technique capable of characterizing the internal structure and heterogeneity from submetric to global scale for the benefit of science as well as for planetary defence or exploration. Access to the deep interior structure requires a low-frequency radar (LFR) that is able to penetrate and propagate throughout the complete body. The LFR will be a bi-static radar similar to the CONSERT radar designed for the Rosetta mission and will perform a tomography of the asteroid. On the other hand, the characterization of the first tens of meters of the subsurface with a submetric resolution will be achieved by a monostatic radar operating at higher frequencies (HFR). It will allow the identification of the layering and the reconnection of the surface features to the internal structure. Its design will be based on the design of the WISDOM radar developped for the ExoMars mission. This presentation reviews, in the context of the AIDA/AIM mission, the benefits of radar measurements performed from a spacecraft. The concept of both HFR and LFR are presented as well as the expected performances of the instruments.

Succession in the petroleum reservoir microbiome through an oil field production lifecycle.

PubMed

Vigneron, Adrien; Alsop, Eric B; Lomans, Bartholomeus P; Kyrpides, Nikos C; Head, Ian M; Tsesmetzis, Nicolas

2017-09-01

Subsurface petroleum reservoirs are an important component of the deep biosphere where indigenous microorganisms live under extreme conditions and in isolation from the Earth's surface for millions of years. However, unlike the bulk of the deep biosphere, the petroleum reservoir deep biosphere is subject to extreme anthropogenic perturbation, with the introduction of new electron acceptors, donors and exogenous microbes during oil exploration and production. Despite the fundamental and practical significance of this perturbation, there has never been a systematic evaluation of the ecological changes that occur over the production lifetime of an active offshore petroleum production system. Analysis of the entire Halfdan oil field in the North Sea (32 producing wells in production for 1-15 years) using quantitative PCR, multigenic sequencing, comparative metagenomic and genomic bins reconstruction revealed systematic shifts in microbial community composition and metabolic potential, as well as changing ecological strategies in response to anthropogenic perturbation of the oil field ecosystem, related to length of time in production. The microbial communities were initially dominated by slow growing anaerobes such as members of the Thermotogales and Clostridiales adapted to living on hydrocarbons and complex refractory organic matter. However, as seawater and nitrate injection (used for secondary oil production) delivered oxidants, the microbial community composition progressively changed to fast growing opportunists such as members of the Deferribacteres, Delta-, Epsilon- and Gammaproteobacteria, with energetically more favorable metabolism (for example, nitrate reduction, H 2 S, sulfide and sulfur oxidation). This perturbation has profound consequences for understanding the microbial ecology of the system and is of considerable practical importance as it promotes detrimental processes such as reservoir souring and metal corrosion. These findings provide a new conceptual framework for understanding the petroleum reservoir biosphere and have consequences for developing strategies to manage microbiological problems in the oil industry.

Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective.

PubMed

Mohamed, Aly A; Luo, Yahong; Peng, Hong; Jankowitz, Rachel C; Wu, Shandong

2017-09-20

Mammographic breast density has been established as an independent risk marker for developing breast cancer. Breast density assessment is a routine clinical need in breast cancer screening and current standard is using the Breast Imaging and Reporting Data System (BI-RADS) criteria including four qualitative categories (i.e., fatty, scattered density, heterogeneously dense, or extremely dense). In each mammogram examination, a breast is typically imaged with two different views, i.e., the mediolateral oblique (MLO) view and cranial caudal (CC) view. The BI-RADS-based breast density assessment is a qualitative process made by visual observation of both the MLO and CC views by radiologists, where there is a notable inter- and intra-reader variability. In order to maintain consistency and accuracy in BI-RADS-based breast density assessment, gaining understanding on radiologists' reading behaviors will be educational. In this study, we proposed to leverage the newly emerged deep learning approach to investigate how the MLO and CC view images of a mammogram examination may have been clinically used by radiologists in coming up with a BI-RADS density category. We implemented a convolutional neural network (CNN)-based deep learning model, aimed at distinguishing the breast density categories using a large (15,415 images) set of real-world clinical mammogram images. Our results showed that the classification of density categories (in terms of area under the receiver operating characteristic curve) using MLO view images is significantly higher than that using the CC view. This indicates that most likely it is the MLO view that the radiologists have predominately used to determine the breast density BI-RADS categories. Our study holds a potential to further interpret radiologists' reading characteristics, enhance personalized clinical training to radiologists, and ultimately reduce reader variations in breast density assessment.

Deep-sea bioluminescence blooms after dense water formation at the ocean surface.

PubMed

Tamburini, Christian; Canals, Miquel; Durrieu de Madron, Xavier; Houpert, Loïc; Lefèvre, Dominique; Martini, Séverine; D'Ortenzio, Fabrizio; Robert, Anne; Testor, Pierre; Aguilar, Juan Antonio; Samarai, Imen Al; Albert, Arnaud; André, Michel; Anghinolfi, Marco; Anton, Gisela; Anvar, Shebli; Ardid, Miguel; Jesus, Ana Carolina Assis; Astraatmadja, Tri L; Aubert, Jean-Jacques; Baret, Bruny; Basa, Stéphane; Bertin, Vincent; Biagi, Simone; Bigi, Armando; Bigongiari, Ciro; Bogazzi, Claudio; Bou-Cabo, Manuel; Bouhou, Boutayeb; Bouwhuis, Mieke C; Brunner, Jurgen; Busto, José; Camarena, Francisco; Capone, Antonio; Cârloganu, Christina; Carminati, Giada; Carr, John; Cecchini, Stefano; Charif, Ziad; Charvis, Philippe; Chiarusi, Tommaso; Circella, Marco; Coniglione, Rosa; Costantini, Heide; Coyle, Paschal; Curtil, Christian; Decowski, Patrick; Dekeyser, Ivan; Deschamps, Anne; Donzaud, Corinne; Dornic, Damien; Dorosti, Hasankiadeh Q; Drouhin, Doriane; Eberl, Thomas; Emanuele, Umberto; Ernenwein, Jean-Pierre; Escoffier, Stéphanie; Fermani, Paolo; Ferri, Marcelino; Flaminio, Vincenzo; Folger, Florian; Fritsch, Ulf; Fuda, Jean-Luc; Galatà, Salvatore; Gay, Pascal; Giacomelli, Giorgio; Giordano, Valentina; Gómez-González, Juan-Pablo; Graf, Kay; Guillard, Goulven; Halladjian, Garadeb; Hallewell, Gregory; van Haren, Hans; Hartman, Joris; Heijboer, Aart J; Hello, Yann; Hernández-Rey, Juan Jose; Herold, Bjoern; Hößl, Jurgen; Hsu, Ching-Cheng; de Jong, Marteen; Kadler, Matthias; Kalekin, Oleg; Kappes, Alexander; Katz, Uli; Kavatsyuk, Oksana; Kooijman, Paul; Kopper, Claudio; Kouchner, Antoine; Kreykenbohm, Ingo; Kulikovskiy, Vladimir; Lahmann, Robert; Lamare, Patrick; Larosa, Giuseppina; Lattuada, Dario; Lim, Gordon; Presti, Domenico Lo; Loehner, Herbert; Loucatos, Sotiris; Mangano, Salvatore; Marcelin, Michel; Margiotta, Annarita; Martinez-Mora, Juan Antonio; Meli, Athina; Montaruli, Teresa; Moscoso, Luciano; Motz, Holger; Neff, Max; Nezri, Emma Nuel; Palioselitis, Dimitris; Păvălaş, Gabriela E; Payet, Kevin; Payre, Patrice; Petrovic, Jelena; Piattelli, Paolo; Picot-Clemente, Nicolas; Popa, Vlad; Pradier, Thierry; Presani, Eleonora; Racca, Chantal; Reed, Corey; Riccobene, Giorgio; Richardt, Carsten; Richter, Roland; Rivière, Colas; Roensch, Kathrin; Rostovtsev, Andrei; Ruiz-Rivas, Joaquin; Rujoiu, Marius; Russo, Valerio G; Salesa, Francisco; Sánchez-Losa, Augustin; Sapienza, Piera; Schöck, Friederike; Schuller, Jean-Pierre; Schussler, Fabian; Shanidze, Rezo; Simeone, Francesco; Spies, Andreas; Spurio, Maurizio; Steijger, Jos J M; Stolarczyk, Thierry; Taiuti, Mauro G F; Toscano, Simona; Vallage, Bertrand; Van Elewyck, Véronique; Vannoni, Giulia; Vecchi, Manuela; Vernin, Pascal; Wijnker, Guus; Wilms, Jorn; de Wolf, Els; Yepes, Harold; Zaborov, Dmitry; De Dios Zornoza, Juan; Zúñiga, Juan

2013-01-01

The deep ocean is the largest and least known ecosystem on Earth. It hosts numerous pelagic organisms, most of which are able to emit light. Here we present a unique data set consisting of a 2.5-year long record of light emission by deep-sea pelagic organisms, measured from December 2007 to June 2010 at the ANTARES underwater neutrino telescope in the deep NW Mediterranean Sea, jointly with synchronous hydrological records. This is the longest continuous time-series of deep-sea bioluminescence ever recorded. Our record reveals several weeks long, seasonal bioluminescence blooms with light intensity up to two orders of magnitude higher than background values, which correlate to changes in the properties of deep waters. Such changes are triggered by the winter cooling and evaporation experienced by the upper ocean layer in the Gulf of Lion that leads to the formation and subsequent sinking of dense water through a process known as "open-sea convection". It episodically renews the deep water of the study area and conveys fresh organic matter that fuels the deep ecosystems. Luminous bacteria most likely are the main contributors to the observed deep-sea bioluminescence blooms. Our observations demonstrate a consistent and rapid connection between deep open-sea convection and bathypelagic biological activity, as expressed by bioluminescence. In a setting where dense water formation events are likely to decline under global warming scenarios enhancing ocean stratification, in situ observatories become essential as environmental sentinels for the monitoring and understanding of deep-sea ecosystem shifts.

Atmospheric and Oceanic Response to Southern Ocean Deep Convection Oscillations on Decadal to Centennial Time Scales in Climate Models

NASA Astrophysics Data System (ADS)

Martin, T.; Reintges, A.; Park, W.; Latif, M.

2014-12-01

Many current coupled global climate models simulate open ocean deep convection in the Southern Ocean as a recurring event with time scales ranging from a few years to centennial (de Lavergne et al., 2014, Nat. Clim. Ch.). The only observation of such event, however, was the occurrence of the Weddell Polynya in the mid-1970s, an open water area of 350 000 km2 within the Antarctic sea ice in three consecutive winters. Both the wide range of modeled frequency of occurrence and the absence of deep convection in the Weddell Sea highlights the lack of understanding concerning the phenomenon. Nevertheless, simulations indicate that atmospheric and oceanic responses to the cessation of deep convection in the Southern Ocean include a strengthening of the low-level atmospheric circulation over the Southern Ocean (increasing SAM index) and a reduction in the export of Antarctic Bottom Water (AABW), potentially masking the regional effects of global warming (Latif et al., 2013, J. Clim.; Martin et al., 2014, Deep Sea Res. II). It is thus of great importance to enhance our understanding of Southern Ocean deep convection and clarify the associated time scales. In two multi-millennial simulations with the Kiel Climate Model (KCM, ECHAM5 T31 atmosphere & NEMO-LIM2 ~2˚ ocean) we showed that the deep convection is driven by strong oceanic warming at mid-depth periodically overriding the stabilizing effects of precipitation and ice melt (Martin et al., 2013, Clim. Dyn.). Sea ice thickness also affects location and duration of the deep convection. A new control simulation, in which, amongst others, the atmosphere grid resolution is changed to T42 (~2.8˚), yields a faster deep convection flip-flop with a period of 80-100 years and a weaker but still significant global climate response similar to CMIP5 simulations. While model physics seem to affect the time scale and intensity of the phenomenon, the driving mechanism is a rather robust feature. Finally, we compare the atmospheric and oceanic responses among CMIP5 models. Since open ocean convection is the dominant mode of AABW formation in these models, the northward extent and strength of the AABW cell in the Atlantic correlates with the deep convection intensity but varies between models. Likewise, atmospheric response patterns outside the Southern Ocean region are not consistent among models.

Neutral solute transport across osteochondral interface: A finite element approach.

PubMed

Arbabi, Vahid; Pouran, Behdad; Weinans, Harrie; Zadpoor, Amir A

2016-12-08

Investigation of the solute transfer across articular cartilage and subchondral bone plate could nurture the understanding of the mechanisms of osteoarthritis (OA) progression. In the current study, we approached the transport of neutral solutes in human (slight OA) and equine (healthy) samples using both computed tomography and biphasic-solute finite element modeling. We developed a multi-zone biphasic-solute finite element model (FEM) accounting for the inhomogeneity of articular cartilage (superficial, middle and deep zones) and subchondral bone plate. Fitting the FEM model to the concentration-time curves of the cartilage and the equilibrium concentration of the subchondral plate/calcified cartilage enabled determination of the diffusion coefficients in the superficial, middle and deep zones of cartilage and subchondral plate. We found slightly higher diffusion coefficients for all zones in the human samples as compared to the equine samples. Generally the diffusion coefficient in the superficial zone of human samples was about 3-fold higher than the middle zone, the diffusion coefficient of the middle zone was 1.5-fold higher than that of the deep zone, and the diffusion coefficient of the deep zone was 1.5-fold higher than that of the subchondral plate/calcified cartilage. Those ratios for equine samples were 9, 2 and 1.5, respectively. Regardless of the species considered, there is a gradual decrease of the diffusion coefficient as one approaches the subchondral plate, whereas the rate of decrease is dependent on the type of species. Copyright © 2016 Elsevier Ltd. All rights reserved.

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images.

PubMed

Albarqouni, Shadi; Baur, Christoph; Achilles, Felix; Belagiannis, Vasileios; Demirci, Stefanie; Navab, Nassir

2016-05-01

The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases for real world images, its application for biomedical purposes requires a deeper understanding and hence, more precise definition of the actual annotation task. The fact that expert tasks are being outsourced to non-expert users may lead to noisy annotations introducing disagreement between users. Despite being a valuable resource for learning annotation models from crowdsourcing, conventional machine-learning methods may have difficulties dealing with noisy annotations during training. In this manuscript, we present a new concept for learning from crowds that handle data aggregation directly as part of the learning process of the convolutional neural network (CNN) via additional crowdsourcing layer (AggNet). Besides, we present an experimental study on learning from crowds designed to answer the following questions. 1) Can deep CNN be trained with data collected from crowdsourcing? 2) How to adapt the CNN to train on multiple types of annotation datasets (ground truth and crowd-based)? 3) How does the choice of annotation and aggregation affect the accuracy? Our experimental setup involved Annot8, a self-implemented web-platform based on Crowdflower API realizing image annotation tasks for a publicly available biomedical image database. Our results give valuable insights into the functionality of deep CNN learning from crowd annotations and prove the necessity of data aggregation integration.

Elucidating Small-Scale Animal-Fluid Interactions in the Deep Sea

NASA Astrophysics Data System (ADS)

Katija, K.; Sherman, A.; Graves, D.; Kecy, C. D.; Klimov, D.; Robison, B. H.

2016-02-01

The midwater region of the ocean (below the euphotic zone and above the benthos) is one of the largest ecosystems on our planet, yet remains one of the least explored. Little-known marine organisms that inhabit midwater have developed life strategies that contribute to their evolutionary success, and understanding interactions with their physical, fluid environment will shed light on these strategies. Although significant advances in underwater vehicle technologies have improved access to midwater, small-scale, in situ fluid mechanics measurement methods that seek to quantify the interactions that midwater organisms have with their physical environment are lacking. Here we present DeepPIV, an instrumentation package affixed to remotely operated vehicles that quantifies fluid motions from the surface of the ocean down to 4000 m depths. Utilizing ambient suspended particulate, fluid-structure interactions can be evaluated on a range of marine organisms in midwater and on the benthos. As a proof of concept for DeepPIV, we targeted giant larvaceans (Bathochordaeus stygias) in Monterey Bay that create mucus houses to filter food. Once mucus houses become clogged, they are abandoned by the larvacean, and are left to sink to the ocean bottom; in Monterey Bay, sinking mucus houses contribute to nearly a third of the particulate on the ocean bottom. Little is known about the structure of these mucus houses and the function they play in selectively filtering particles. Using DeepPIV, we reveal the complex structures and flows generated within larvacean mucus houses, which are used to ultimately elucidate how these structures function.

Understanding wetland sub-surface hydrology using geologic and isotopic signatures

NASA Astrophysics Data System (ADS)

Sikdar, P. K.; Sahu, P.

2009-07-01

This paper attempts to utilize hydrogeology and isotope composition of groundwater to understand the present hydrological processes prevalent in a freshwater wetland, source of wetland groundwater, surface water/groundwater interaction and mixing of groundwater of various depth zones in the aquifer. This study considers East Calcutta Wetlands (ECW) - a freshwater peri-urban inland wetland ecosystem located at the lower part of the deltaic alluvial plain of South Bengal Basin and east of Kolkata city. This wetland is well known over the world for its resource recovery systems, developed by local people through ages, using wastewater of the city. Geological investigations reveal that the sub-surface geology is completely blanketed by the Quaternary sediments comprising a succession of silty clay, sand of various grades and sand mixed with occasional gravels and thin intercalations of silty clay. At few places the top silty clay layer is absent due to scouring action of past channels. In these areas sand is present throughout the geological column and the areas are vulnerable to groundwater pollution. Groundwater mainly flows from east to west and is being over-extracted to the tune of 65×103 m3/day. δ18O and δD values of shallow and deep groundwater are similar indicating resemblance in hydrostratigraphy and climate of the recharge areas. Groundwater originates mainly from monsoonal rain with some evaporation prior to or during infiltration and partly from bottom of ponds, canals and infiltration of groundwater withdrawn for irrigation. Relatively high tritium content of the shallow groundwater indicates local recharge, while the deep groundwater with very low tritium is recharged mainly from distant areas. At places the deep aquifer has relatively high tritium, indicating mixing of groundwater of shallow and deep aquifers. Metals such as copper, lead, arsenic, cadmium, aluminium, nickel and chromium are also present in groundwater of various depths. Therefore, aquifers of wetland and surrounding urban areas which are heavily dependent on groundwater are vulnerable to pollution. In the area south of ECW isotope data indicates no interaction between shallow and deep aquifer and hence this area may be a better location to treat sewage water than within ECW. To reduce the threat of pollution in ECW's aquifer, surface water-groundwater interaction should be minimized by regulating tubewell operation time, introducing treated surface water supply system and artificial recharging of the aquifer.

AUV Reveals Deep-Water Coral Mound Distribution, Morphology and Oceanography in the Florida Straits

NASA Astrophysics Data System (ADS)

Grasmueck, M.; Eberli, G. P.; Viggiano, D. A.; Correa, T.; Rathwell, G.; Luo, J.

2006-12-01

Since the 1960's dredge sampling and submersible dives have discovered numerous mound-forming deep- water corals in water depths of 400-800 m in the Straits of Florida. This extensive collection of samples and observations however can not be put into a geomorphologic context as existing bathymetric charts do not resolve coral mounds. To make progress in understanding the distribution and genesis of coral mounds, maps of morphology and oceanographic conditions resolving features at the 1-10 m scale are needed. On 11-18 December 2005 the C-Surveyor II(TM) mapped five sites ranging from 14-48 km2 in 590-875 m water acquiring 1-3 m resolution bathymetry and acoustic backscatter together with subbottom profiles, current vectors, salinity, and temperature. The areas mapped with the AUV contain hundreds of coral mounds with heights of 1-120 m. Mound distribution, morphology and currents are different for each survey site. Coral mounds develop on off-bank transported sediment ridges and slump features at the toe-of-slope of Great Bahama bank, while chevron pattern ridges and sinusoidal ridges are found further east in the Straits. Currents range from 0.1-0.5 m/s. At two sites currents reversed every 6 hours indicating tidal control. The AUV surveys and subsequent ground truthing with a drop camera and a submersible revealed a surprising abundance and diversity of deep-water coral habitats. The boundaries between mound fields and the barren muddy or sandy seafloor are sharp. Hull- mounted multi-beam reconnaissance mapping helped us select the most promising coral mound areas to optimize the use of valuable AUV time. Such combined use of hull-mounted and AUV-based mapping enables efficient environmental characterization of large deep-water regions such as the Florida Straits. The synoptic high-resolution datasets acquired by the multiple sensors on board the AUV enable for the first time a comprehensive assessment of deep-water coral mound ecosystems. Utilization of such state-of-the-art deepwater exploration tools is essential to understand and protect these slow growing and fragile oases which are resources for seafood, new medicines and long-term climate records. The AUV data will guide future sampling and monitoring to critical locations and provide the geospatial framework for making inventories of mound resources and designing research and management plans.

Active Learning Session Based on Didactical Engineering Framework for Conceptual Change in Students' Equilibrium and Stability Understanding

ERIC Educational Resources Information Center

Canu, Michael; Duque, Mauricio; de Hosson, Cécile

2017-01-01

Engineering students on control courses lack a deep understanding of equilibrium and stability that are crucial concepts in this discipline. Several studies have shown that students find it difficult to understand simple familiar or academic static equilibrium cases as well as dynamic ones from mechanics even if they know the discipline's criteria…

DNA barcoding reveals high diversity of deep-sea octocorals on Hawaiian seamounts

NASA Astrophysics Data System (ADS)

Baco-Taylor, A.; Morgan, N.; LaBelle, B.; Figueroa, D.; Ormos, A.; Cairns, S.; Driskell, A.

2016-02-01

Globally, studies of deep-sea octocoral distribution and diversity have been hampered by a lack of keys and a plethora of unidentified specimens. Even in areas where intensive morphological work has been done, as many as half of the specimens remain unidentified to species or even genus. Recently, a suite of genetic markers have been identified as barcoding proxies for octocorals. Here, we make one of the first attempts at broad-scale application of 3 of these markers, to recent and museum collections of octocorals of approximately 1000 specimens from the Hawaiian Archipelago, to gain a better understanding of the diversity and distribution of deep-sea octocorals there. Sequence results for all 3 markers show a greater number of haplotypes than morphological species. Each of these markers as taken alone has been shown to underestimate species richness. Extrapolating from this we show that morphological work to date on these specimens underestimates species richness by 30-40%, suggesting the diversity of octocorals in the Hawaiian Archipelago is substantially greater than previously thought. The large percentage of haplotypes represented by single individuals suggests that the full diversity of deep-sea octocorals in Hawaii remains drastically undersampled. This work also shows that species ranges based on current species designations are overestimated, with multiple smaller-range haplotypes for given morphological operational taxonomic units. We evaluate these results to assess the usefulness of application of these markers to understanding deep-sea coral distributions in the broader Pacific and beyond.

Eric Davidson and deep time.

PubMed

Erwin, Douglas H

2017-10-13

Eric Davidson had a deep and abiding interest in the role developmental mechanisms played in generating evolutionary patterns documented in deep time, from the origin of the euechinoids to the processes responsible for the morphological architectures of major animal clades. Although not an evolutionary biologist, Davidson's interests long preceded the current excitement over comparative evolutionary developmental biology. Here I discuss three aspects at the intersection between his research and evolutionary patterns in deep time: First, understanding the mechanisms of body plan formation, particularly those associated with the early diversification of major metazoan clades. Second, a critique of early claims about ancestral metazoans based on the discoveries of highly conserved genes across bilaterian animals. Third, Davidson's own involvement in paleontology through a collaborative study of the fossil embryos from the Ediacaran Doushantuo Formation in south China.

Deep-Earth reactor: Nuclear fission, helium, and the geomagnetic field

PubMed Central

Hollenbach, D. F.; Herndon, J. M.

2001-01-01

Geomagnetic field reversals and changes in intensity are understandable from an energy standpoint as natural consequences of intermittent and/or variable nuclear fission chain reactions deep within the Earth. Moreover, deep-Earth production of helium, having 3He/4He ratios within the range observed from deep-mantle sources, is demonstrated to be a consequence of nuclear fission. Numerical simulations of a planetary-scale geo-reactor were made by using the SCALE sequence of codes. The results clearly demonstrate that such a geo-reactor (i) would function as a fast-neutron fuel breeder reactor; (ii) could, under appropriate conditions, operate over the entire period of geologic time; and (iii) would function in such a manner as to yield variable and/or intermittent output power. PMID:11562483

Compact, High-Power, Fiber-Laser-Based Coherent Sources Tunable in the Mid-Infrared and THz Spectrum

DTIC Science & Technology

2015-02-20

conversion sources and optical parametric oscillators (OPOs) for the deep mid-infrared (mid-IR) spectral regions >5 μm. We have successfully developed... oscillators (OPOs) for the deep mid-infrared (mid-IR) spectral regions >5 µm. We have successfully developed tunable deep mid-IR systems in both...the advancement of nonlinear frequency conversion sources and optical parametric oscillators (OPOs) for the deep mid-infrared (mid- IR) spectral

Using geophysical data to assess scour development

USGS Publications Warehouse

Placzek, Gary; Haeni, Peter F.; Trent, Roy; ,

1993-01-01

The development of scour holes in the Connecticut River near the new Baldwin Bridge has been documented by comparing geophysical records collected before (1989), during (1990), and after (1992) bridge construction. Eight piers that support the 570-m (meter) span over the Connecticut River were protected by 12-m wide cofferdams during construction. The maximum flow during the study was equivalent to a 3-year recurrence-interval flood, indicating no significant floods. Fathometer data indicate that deep scour holes, 1.5 to 6.4 m deep, developed north of piers 6, 7, and 8. Scour holes, less than 1.3 m-deep, developed south of these piers. The deepest scour hole was north of pier 7, where data show a flat river bottom in 1989, a scour 3.3-m deep in 1990, and a scour hole 6.4-m deep in 1992. Continuous seismic-profiling (CSP) data show that a 1.5 -m deep scour hole north of pier 6 in 1990 was filled in with 1.5-m of material by 1992. No infilling was detected in the scour holes north of piers 7 and 8. Numerous subbottom reflectors from geologic layers, up to 7.6 -m deep were identified in the CSP records.

Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.).

PubMed

Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Xu, Kai; Wei, Haibin; Feng, Fangjun; Li, Tiemei; Pang, Xiaomeng; Shi, Caiping; Luo, Lijun; Zhong, Yang

2017-01-01

Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots.

Root Transcriptomic Analysis Revealing the Importance of Energy Metabolism to the Development of Deep Roots in Rice (Oryza sativa L.)

PubMed Central

Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Xu, Kai; Wei, Haibin; Feng, Fangjun; Li, Tiemei; Pang, Xiaomeng; Shi, Caiping; Luo, Lijun; Zhong, Yang

2017-01-01

Drought is the most serious abiotic stress limiting rice production, and deep root is the key contributor to drought avoidance. However, the genetic mechanism regulating the development of deep roots is largely unknown. In this study, the transcriptomes of 74 root samples from 37 rice varieties, representing the extreme genotypes of shallow or deep rooting, were surveyed by RNA-seq. The 13,242 differentially expressed genes (DEGs) between deep rooting and shallow rooting varieties (H vs. L) were enriched in the pathway of genetic information processing and metabolism, while the 1,052 DEGs between the deep roots and shallow roots from each of the plants (D vs. S) were significantly enriched in metabolic pathways especially energy metabolism. Ten quantitative trait transcripts (QTTs) were identified and some were involved in energy metabolism. Forty-nine candidate DEGs were confirmed by qRT-PCR and microarray. Through weighted gene co-expression network analysis (WGCNA), we found 18 hub genes. Surprisingly, all these hub genes expressed higher in deep roots than in shallow roots, furthermore half of them functioned in energy metabolism. We also estimated that the ATP production in the deep roots was faster than shallow roots. Our results provided a lot of reliable candidate genes to improve deep rooting, and firstly highlight the importance of energy metabolism to the development of deep roots. PMID:28798764

Deep Space Gateway Ecosystem Observatory

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Campbell, P. E.; Middleton, E. M.

2018-02-01

Advance global understanding of seasonal change and diurnal variability of terrestrial ecosystem function, photosynthesis, and stress responses using spectral reflectance, thermal, and fluorescence signals.

The deathly hallows: Harry Potter and adolescent development.

PubMed

Rosegrant, John

2009-12-01

The enormous popularity of the Harry Potter books points to the deep resonance readers feel with the psychological issues they bring to life. Three developmental issues provide central themes: the necessity for partial disenchantment and increasing attunement to reality, while retaining a capacity for wonder; repudiation or endorsement of the narcissistic solution to life's difficulties; and aggression and castration fantasies while growing into adult power. These developmental issues are particularly acute during adolescence but start earlier and continue to be reworked throughout the life span, accounting for the books' appeal to a wide age-range of readers despite their apparent focus on adolescence. These developmental themes are explored in order to better understand the Harry Potter books, as, conversely, the books are explored in order to better understand these themes.

Never-Ending Learning for Deep Understanding of Natural Language

DTIC Science & Technology

2017-10-01

CA policy clarification memorandum dated 16 Jan 09. 13. SUPPLEMENTARY NOTES 14. ABSTRACT This research has explored the thesis that very... thesis we have built on our earlier research on the Never Ending Language Learning (NELL) computer system, which has been running non- stop since... thesis that very significant amounts of background knowledge can lead to very substantial improvements in the accuracy of deep text analysis and

MOCHA - Multi-Study Ocean Acoustics Human Effects Analysis

DTIC Science & Technology

2015-09-30

understanding of the response of marine mammals to navy sonar and other acoustic stimuli, by maximizing the information gain from Behavioral Response Studies...focussed on a functional/taxonomic group of marine mammals (deep divers, other odontocetes, pilot whales and baleen whales). We began with deep divers...Controlled Exposure Experiments component of the Marine Mammals and Biology Program, and it will also address broader commitments of the Navy for

Chesapeake Bay impact structure: A blast from the past

USGS Publications Warehouse

Powars, David S.; Edwards, Lucy E.; Gohn, Gregory S.; Horton, J. Wright

2015-10-28

Since its discovery in the early 1990s, scientists have conducted deep drilling and geophysical surveys of the impact structure to find out more about its size, composition, structure, age, and biological effects and to understand its lingering influences on the regional groundwater system. These efforts culminated in the drilling of a 1-mile-deep, continuously sampled corehole in 2005 by an international group of scientists and agencies.

Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia

PubMed Central

Pinaya, Walter H. L.; Gadelha, Ary; Doyle, Orla M.; Noto, Cristiano; Zugman, André; Cordeiro, Quirino; Jackowski, Andrea P.; Bressan, Rodrigo A.; Sato, João R.

2016-01-01

Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging results mirrors the heterogeneity of the disorder. Machine learning methods capable of representing invariant features could circumvent this problem. In this structural MRI study, we trained a deep learning model known as deep belief network (DBN) to extract features from brain morphometry data and investigated its performance in discriminating between healthy controls (N = 83) and patients with schizophrenia (N = 143). We further analysed performance in classifying patients with a first-episode psychosis (N = 32). The DBN highlighted differences between classes, especially in the frontal, temporal, parietal, and insular cortices, and in some subcortical regions, including the corpus callosum, putamen, and cerebellum. The DBN was slightly more accurate as a classifier (accuracy = 73.6%) than the support vector machine (accuracy = 68.1%). Finally, the error rate of the DBN in classifying first-episode patients was 56.3%, indicating that the representations learned from patients with schizophrenia and healthy controls were not suitable to define these patients. Our data suggest that deep learning could improve our understanding of psychiatric disorders such as schizophrenia by improving neuromorphometric analyses. PMID:27941946

Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia

NASA Astrophysics Data System (ADS)

Pinaya, Walter H. L.; Gadelha, Ary; Doyle, Orla M.; Noto, Cristiano; Zugman, André; Cordeiro, Quirino; Jackowski, Andrea P.; Bressan, Rodrigo A.; Sato, João R.

2016-12-01

Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging results mirrors the heterogeneity of the disorder. Machine learning methods capable of representing invariant features could circumvent this problem. In this structural MRI study, we trained a deep learning model known as deep belief network (DBN) to extract features from brain morphometry data and investigated its performance in discriminating between healthy controls (N = 83) and patients with schizophrenia (N = 143). We further analysed performance in classifying patients with a first-episode psychosis (N = 32). The DBN highlighted differences between classes, especially in the frontal, temporal, parietal, and insular cortices, and in some subcortical regions, including the corpus callosum, putamen, and cerebellum. The DBN was slightly more accurate as a classifier (accuracy = 73.6%) than the support vector machine (accuracy = 68.1%). Finally, the error rate of the DBN in classifying first-episode patients was 56.3%, indicating that the representations learned from patients with schizophrenia and healthy controls were not suitable to define these patients. Our data suggest that deep learning could improve our understanding of psychiatric disorders such as schizophrenia by improving neuromorphometric analyses.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

Thermal erosion gullies, one type of thermokarst landforms, develop due to thawing of ice-rich permafrost. Mapping the location and extent of thermal erosion gullies can help understand the spatial distribution of thermokarst landforms and their temporal evolution. Remote sensing images provide an effective way for mapping thermokarst landforms, especially thermokarst lakes. However, thermal erosion gullies are challenging to map from remote sensing images due to their small sizes and significant variations in geometric/radiometric properties. It is feasible to manually identify these features, as a few previous studies have carried out. However manual methods are labor-intensive, therefore, cannot be used for a large study area. In this work, we conduct automatic mapping of thermal erosion gullies from high-resolution images by using Deep Learning. Our study area is located in Eboling Mountain (Qinghai, China). Within a 6 km2 peatland area underlain by ice-rich permafrost, at least 20 thermal erosional gullies are well developed. The image used is a 15-cm-resolution Digital Orthophoto Map (DOM) generated in July 2016. First, we extracted 14 gully patches and ten non-gully patches as training data. And we performed image augmentation. Next, we fine-tuned the pre-trained model of DeepLab, a deep-learning algorithm for semantic image segmentation based on Deep Convolutional Neural Networks. Then, we performed inference on the whole DOM and obtained intermediate results in forms of polygons for all identified gullies. At last, we removed misidentified polygons based on a few pre-set criteria on the size and shape of each polygon. Our final results include 42 polygons. Validated against field measurements using GPS, most of the gullies are detected correctly. There are 20 false detections due to the small number and low quality of training images. We also found three new gullies that missed in the field observations. This study shows that (1) despite a challenging mapping task, DeepLab can detect small, irregular-shaped thermal erosion gullies with high accuracy. (2) Automatic detection is critical for mapping thermal erosion gully since manual mapping or field work may miss some targets even in a relatively small region. (3) The quantity and quality of training data are crucial for detection accuracy.

Potential impact of global climate change on benthic deep-sea microbes.

PubMed

Danovaro, Roberto; Corinaldesi, Cinzia; Dell'Anno, Antonio; Rastelli, Eugenio

2017-12-15

Benthic deep-sea environments are the largest ecosystem on Earth, covering ∼65% of the Earth surface. Microbes inhabiting this huge biome at all water depths represent the most abundant biological components and a relevant portion of the biomass of the biosphere, and play a crucial role in global biogeochemical cycles. Increasing evidence suggests that global climate changes are affecting also deep-sea ecosystems, both directly (causing shifts in bottom-water temperature, oxygen concentration and pH) and indirectly (through changes in surface oceans' productivity and in the consequent export of organic matter to the seafloor). However, the responses of the benthic deep-sea biota to such shifts remain largely unknown. This applies particularly to deep-sea microbes, which include bacteria, archaea, microeukaryotes and their viruses. Understanding the potential impacts of global change on the benthic deep-sea microbial assemblages and the consequences on the functioning of the ocean interior is a priority to better forecast the potential consequences at global scale. Here we explore the potential changes in the benthic deep-sea microbiology expected in the coming decades using case studies on specific systems used as test models. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Deep-sea ostracods from the South Atlantic sector of the Southern ocean during the Last 370,000 years

USGS Publications Warehouse

Yasuhara, Moriaki; Cronin, T. M.; Hunt, G.; Hodell, D.A.

2009-01-01

We report changes of deep-sea ostracod fauna during the last 370,000 yr from the Ocean Drilling Program (ODP) Hole 704A in the South Atlantic sector of the Southern Ocean. The results show that faunal changes are coincident with glacial/interglacial-scale deep-water circulation changes, even though our dataset is relatively small and the waters are barren of ostracods until mid-MIS (Marine Isotope Stage) 5. Krithe and Poseidonamicus were dominant during the Holocene interglacial period and the latter part of MIS 5, when this site was under the influence of North Atlantic Deep Water (NADW). Conversely, Henryhowella and Legitimocythere were dominant during glacial periods, when this site was in the path of Circumpolar Deep Water (CPDW). Three new species (Aversovalva brandaoae, Poseidonamicus hisayoae, and Krithe mazziniae) are described herein. This is the first report of Quaternary glacial/interglacial scale deep-sea ostracod faunal changes in the Southern and South Atlantic Oceans, a key region for understanding Quaternary climate and deep-water circulation, although the paucity of Quaternary ostracods in this region necessitates further research. ?? 2009 The Paleontological Society.

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.

The disposition to understand for oneself at university: integrating learning processes with motivation and metacognition.

PubMed

Entwistle, Noel; McCune, Velda

2013-06-01

A re-analysis of several university-level interview studies has suggested that some students show evidence of a deep and stable approach to learning, along with other characteristics that support the approach. This combination, it was argued, could be seen to indicate a disposition to understand for oneself. To identify a group of students who showed high and consistent scores on deep approach, combined with equivalently high scores on effort and monitoring studying, and to explore these students' experiences of the teaching-learning environments they had experienced. Re-analysis of data from 1,896 students from 25 undergraduate courses taking four contrasting subject areas in eleven British universities. Inventories measuring approaches to studying were given at the beginning and the end of a semester, with the second inventory also exploring students' experiences of teaching. K-means cluster analysis was used to identify groups of students with differing patterns of response on the inventory scales, with a particular focus on students showing high, stable scores. One cluster clearly showed the characteristics expected of the disposition to understand and was also fairly stable over time. Other clusters also had deep approaches, but also showed either surface elements or lower scores on organized effort or monitoring their studying. Combining these findings with interview studies previously reported reinforces the idea of there being a disposition to understand for oneself that could be identified from an inventory scale or through further interviews. © 2013 The British Psychological Society.

RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2017-02-28

RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recognize the target RNAs and why they bind specific positions is still far from clear. Machine learning-based algorithms are widely acknowledged to be capable of speeding up this process. Although many automatic tools have been developed to predict the RNA-protein binding sites from the rapidly growing multi-resource data, e.g. sequence, structure, their domain specific features and formats have posed significant computational challenges. One of current difficulties is that the cross-source shared common knowledge is at a higher abstraction level beyond the observed data, resulting in a low efficiency of direct integration of observed data across domains. The other difficulty is how to interpret the prediction results. Existing approaches tend to terminate after outputting the potential discrete binding sites on the sequences, but how to assemble them into the meaningful binding motifs is a topic worth of further investigation. In viewing of these challenges, we propose a deep learning-based framework (iDeep) by using a novel hybrid convolutional neural network and deep belief network to predict the RBP interaction sites and motifs on RNAs. This new protocol is featured by transforming the original observed data into a high-level abstraction feature space using multiple layers of learning blocks, where the shared representations across different domains are integrated. To validate our iDeep method, we performed experiments on 31 large-scale CLIP-seq datasets, and our results show that by integrating multiple sources of data, the average AUC can be improved by 8% compared to the best single-source-based predictor; and through cross-domain knowledge integration at an abstraction level, it outperforms the state-of-the-art predictors by 6%. Besides the overall enhanced prediction performance, the convolutional neural network module embedded in iDeep is also able to automatically capture the interpretable binding motifs for RBPs. Large-scale experiments demonstrate that these mined binding motifs agree well with the experimentally verified results, suggesting iDeep is a promising approach in the real-world applications. The iDeep framework not only can achieve promising performance than the state-of-the-art predictors, but also easily capture interpretable binding motifs. iDeep is available at http://www.csbio.sjtu.edu.cn/bioinf/iDeep.

Deep venous thrombosis among diabetic patients in King Abdulaziz University (KAU) Hospital, Jeddah, Kingdom of Saudi Arabia.

PubMed

Alotaibi, Hanan Khalid; Abo El-Fetoh, Nagah Mohamed; MenwerAlanazi, Aseel; Alanazi, Omar Ayed; Alanazi, Abdullah Barghash; Alhowaish, Mohammed Ali; Alzahrani, Hussam Saeed Busays; Alshammari, Mashael Abdullah; ALrashidi, Rawan Fulayyih; Alblowi, Thikra Mohammed; Alqahtani, Sarah Jemal; Almaashi, Fatin Salem

2017-09-01

Deep venous thrombosis (DVT) is a major cause of morbidity and mortality among hospitalized patients worldwide and, simultaneously, the most preventable. Studies revealed several risk factors of deep venous thrombosis in hospitalized patients. to identify frequency and factors associated with occurrence of deep venous thrombosis among diabetic patients referred to King Abdulaziz University (KAU) Hospital, Jeddah, Kingdom of Saudi Arabia. This cross-sectional hospital-based study was conducted from June to December, 2016. All diabetic patients referred to the hospital departments and who were suspected to have deep venous thrombosis (DVT) and subjected to Doppler examination were included in the study. A questionnaire was designed to obtain data about deep venous thrombosis frequency among participants and factors associated with the development of deep venous thrombosis among them. Data was collected through face to face interviews with patients included in the study. We used SPSS version 16 for data analysis through descriptive statistics and Chi-square test. DVT was detected in 14.7 % of the examined patients. There were significant and positive associations between age and DVT (X 2 =10.13, p=0.03) and between ischemic heart disease and DVT (X 2 =1.628, p=0.043) with the development of deep venous thrombosis among the studied patients. On the other hand, gender, other comorbidities, history of previous DVT, being bed ridden and using orthopedic casting were not significantly associated with the occurrence of deep venous thrombosis among the participants. DVT development rate among the participants was 14.7 %. Aging was significantly associated with DVT occurrence. Most of the studied factors and comorbidities had no significant role in DVT development among participants and only ischemic heart disease was significantly associated with DVT development.

The ABC of moral development: an attachment approach to moral judgment

PubMed Central

Govrin, Aner

2014-01-01

As with other cognitive faculties, the etiology of moral judgment and its connection to early development is complex. Because research is limited, the causative and contributory factors to the development of moral judgment in preverbal infants are unclear. However, evidence is emerging from studies within both infant research and moral psychology that may contribute to our understanding of the early development of moral judgments. Though its finding are preliminary, this proposed paradigm synthesizes these findings to generate an overarching, model of the process that appears to contribute to the development of moral judgment in the first year of life. I will propose that through early interactions with the caregiver, the child acquires an internal representation of a system of rules that determine how right/wrong judgments are to be construed, used, and understood. By breaking moral situations down into their defining features, the attachment model of moral judgment outlines a framework for a universal moral faculty based on a universal, innate, deep structure that appears uniformly in the structure of almost all moral judgments regardless of their content. The implications of the model for our understanding of innateness, universal morality, and the representations of moral situations are discussed. PMID:24478739

Moving Apart and Coming Together: Discourse, Engagement, and Deep Learning

ERIC Educational Resources Information Center

Gomoll, Andrea S.; Hmelo-Silver, Cindy E.; Tolar, Erin; Šabanovic, Selma; Francisco, Matthew

2017-01-01

An important part of "doing" science is engaging in collaborative science practices. To better understand how to support these practices, we need to consider how students collaboratively construct and represent shared understanding in complex, problem-oriented, and authentic learning environments. This research presents a case study…

The Application of Peer Teaching in Digital Forensics Education

ERIC Educational Resources Information Center

Govan, Michelle

2016-01-01

The field of digital forensics requires a multidisciplinary understanding of a range of diverse subjects, but is interdisciplinary (in using principles, techniques and theories from other disciplines) encompassing both computer and forensic science. This requires that practitioners have a deep technical knowledge and understanding, but that they…

Dealing with Quantifier Scope Ambiguity in Natural Language Understanding

ERIC Educational Resources Information Center

Hafezi Manshadi, Mohammad

2014-01-01

Quantifier scope disambiguation (QSD) is one of the most challenging problems in deep natural language understanding (NLU) systems. The most popular approach for dealing with QSD is to simply leave the semantic representation (scope-) underspecified and to incrementally add constraints to filter out unwanted readings. Scope underspecification has…

Challenges in Using Analogies

ERIC Educational Resources Information Center

Lin, Shih-Yin; Singh, Chandralekha

2011-01-01

Learning physics requires understanding the applicability of fundamental principles in a variety of contexts that share deep features. One way to help students learn physics is via analogical reasoning. Students can be taught to make an analogy between situations that are more familiar or easier to understand and another situation where the same…

Deep learning of unsteady laminar flow over a cylinder

NASA Astrophysics Data System (ADS)

Lee, Sangseung; You, Donghyun

2017-11-01

Unsteady flow over a circular cylinder is reconstructed using deep learning with a particular emphasis on elucidating the potential of learning the solution of the Navier-Stokes equations. A deep neural network (DNN) is employed for deep learning, while numerical simulations are conducted to produce training database. Instantaneous and mean flow fields which are reconstructed by deep learning are compared with the simulation results. Fourier transform of flow variables has been conducted to validate the ability of DNN to capture both amplitudes and frequencies of flow motions. Basis decomposition of learned flow is performed to understand the underlying mechanisms of learning flow through DNN. The present study suggests that a deep learning technique can be utilized for reconstruction and, potentially, for prediction of fluid flow instead of solving the Navier-Stokes equations. This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(Ministry of Science, ICT and Future Planning) (No. 2014R1A2A1A11049599, No. 2015R1A2A1A15056086, No. 2016R1E1A2A01939553).

DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection.

PubMed

Ouyang, Wanli; Zeng, Xingyu; Wang, Xiaogang; Qiu, Shi; Luo, Ping; Tian, Yonglong; Li, Hongsheng; Yang, Shuo; Wang, Zhe; Li, Hongyang; Loy, Chen Change; Wang, Kun; Yan, Junjie; Tang, Xiaoou

2016-07-07

In this paper, we propose deformable deep convolutional neural networks for generic object detection. This new deep learning object detection framework has innovations in multiple aspects. In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty. A new pre-training strategy is proposed to learn feature representations more suitable for the object detection task and with good generalization capability. By changing the net structures, training strategies, adding and removing some key components in the detection pipeline, a set of models with large diversity are obtained, which significantly improves the effectiveness of model averaging. The proposed approach improves the mean averaged precision obtained by RCNN [16], which was the state-of-the-art, from 31% to 50.3% on the ILSVRC2014 detection test set. It also outperforms the winner of ILSVRC2014, GoogLeNet, by 6.1%. Detailed component-wise analysis is also provided through extensive experimental evaluation, which provides a global view for people to understand the deep learning object detection pipeline.

Deep-sea coral and hardbottom habitats on the west Florida slope, eastern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Ross, Steve W.; Rhode, Mike; Brooke, Sandra

2017-02-01

Until recently, benthic habitats dominated by deep-sea corals (DSC) appeared to be less extensive on the slope of the Gulf of Mexico (GOM) than in the northeast Atlantic Ocean or off the southeastern US. There are relatively few bioherms (i.e., coral-built mounds) in the northern GOM, and most DSCs are attached to existing hard substrata (e.g., authigenically formed carbonate). The primary structure-forming, DSC in the GOM is Lophelia pertusa, but structure is also provided by other living and dead scleractinians, antipatharians (black corals), octocorals (gorgonians, soft corals), hydrocorals and sponges, as well as abundant rocky substrata. The best development of DSCs in the GOM was previously documented within Viosca Knoll oil and gas lease blocks 826 and 862/906 (north-central GOM) and on the Campeche Bank (southern GOM in Mexican waters). This paper documents extensive deep reef ecosystems composed of DSC and rocky hard-bottom recently surveyed on the West Florida Slope (WFS, eastern GOM) during six research cruises (2008-2012). Using multibeam sonar, CTD casts, and video from underwater vehicles, we describe the physical and oceanographic characteristics of these deep reefs and provide size or area estimates of deep coral and hardground habitats. The multibeam sonar analyses revealed hundreds of mounds and ridges, some of which were subsequently surveyed using underwater vehicles. Mounds and ridges in <525 m depths were usually capped with living coral colonies, dominated by L. pertusa. An extensive rocky scarp, running roughly north-south for at least 229 km, supported lower abundances of scleractinian corals than the mounds and ridges, despite an abundance of settlement substrata. Areal comparisons suggested that the WFS may exceed other parts of the GOM slope in extent of living deep coral coverage and other deep-reef habitat (dead coral and rock). The complex WFS region warrants additional studies to better understand the influences of oceanography and geology on the occurrence of DSC and associated organisms. Protection measures are being considered to ensure the long-term integrity of this diverse ecosystem.

Reprint of - Deep-sea coral and hardbottom habitats on the west Florida slope, eastern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Ross, Steve W.; Rhode, Mike; Brooke, Sandra

2017-09-01

Until recently, benthic habitats dominated by deep-sea corals (DSC) appeared to be less extensive on the slope of the Gulf of Mexico (GOM) than in the northeast Atlantic Ocean or off the southeastern US. There are relatively few bioherms (i.e., coral-built mounds) in the northern GOM, and most DSCs are attached to existing hard substrata (e.g., authigenically formed carbonate). The primary structure-forming, DSC in the GOM is Lophelia pertusa, but structure is also provided by other living and dead scleractinians, antipatharians (black corals), octocorals (gorgonians, soft corals), hydrocorals and sponges, as well as abundant rocky substrata. The best development of DSCs in the GOM was previously documented within Viosca Knoll oil and gas lease blocks 826 and 862/906 (north-central GOM) and on the Campeche Bank (southern GOM in Mexican waters). This paper documents extensive deep reef ecosystems composed of DSC and rocky hard-bottom recently surveyed on the West Florida Slope (WFS, eastern GOM) during six research cruises (2008-2012). Using multibeam sonar, CTD casts, and video from underwater vehicles, we describe the physical and oceanographic characteristics of these deep reefs and provide size or area estimates of deep coral and hardground habitats. The multibeam sonar analyses revealed hundreds of mounds and ridges, some of which were subsequently surveyed using underwater vehicles. Mounds and ridges in <525 m depths were usually capped with living coral colonies, dominated by L. pertusa. An extensive rocky scarp, running roughly north-south for at least 229 km, supported lower abundances of scleractinian corals than the mounds and ridges, despite an abundance of settlement substrata. Areal comparisons suggested that the WFS may exceed other parts of the GOM slope in extent of living deep coral coverage and other deep-reef habitat (dead coral and rock). The complex WFS region warrants additional studies to better understand the influences of oceanography and geology on the occurrence of DSC and associated organisms. Protection measures are being considered to ensure the long-term integrity of this diverse ecosystem.

Transcriptome sequences resolve deep relationships of the grape family.

PubMed

Wen, Jun; Xiong, Zhiqiang; Nie, Ze-Long; Mao, Likai; Zhu, Yabing; Kan, Xian-Zhao; Ickert-Bond, Stefanie M; Gerrath, Jean; Zimmer, Elizabeth A; Fang, Xiao-Dong

2013-01-01

Previous phylogenetic studies of the grape family (Vitaceae) yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

NASA Astrophysics Data System (ADS)

Chang, You-Soon; Zhang, Shaoqing; Rosati, Anthony; Vecchi, Gabriel A.; Yang, Xiaosong

2018-03-01

An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, "observations" drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the "identical" twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.

North Atlantic deep water formation and AMOC in CMIP5 models

NASA Astrophysics Data System (ADS)

Heuzé, Céline

2017-07-01

Deep water formation in climate models is indicative of their ability to simulate future ocean circulation, carbon and heat uptake, and sea level rise. Present-day temperature, salinity, sea ice concentration and ocean transport in the North Atlantic subpolar gyre and Nordic Seas from 23 CMIP5 (Climate Model Intercomparison Project, phase 5) models are compared with observations to assess the biases, causes and consequences of North Atlantic deep convection in models. The majority of models convect too deep, over too large an area, too often and too far south. Deep convection occurs at the sea ice edge and is most realistic in models with accurate sea ice extent, mostly those using the CICE model. Half of the models convect in response to local cooling or salinification of the surface waters; only a third have a dynamic relationship between freshwater coming from the Arctic and deep convection. The models with the most intense deep convection have the warmest deep waters, due to a redistribution of heat through the water column. For the majority of models, the variability of the Atlantic Meridional Overturning Circulation (AMOC) is explained by the volumes of deep water produced in the subpolar gyre and Nordic Seas up to 2 years before. In turn, models with the strongest AMOC have the largest heat export to the Arctic. Understanding the dynamical drivers of deep convection and AMOC in models is hence key to realistically forecasting Arctic oceanic warming and its consequences for the global ocean circulation, cryosphere and marine life.

Comparison between infaunal communities of the deep floor and edge of the Tonga Trench: Possible effects of differences in organic matter supply

NASA Astrophysics Data System (ADS)

Leduc, Daniel; Rowden, Ashley A.; Glud, Ronnie N.; Wenzhöfer, Frank; Kitazato, Hiroshi; Clark, Malcolm R.

2016-10-01

Hadal trenches are characterised by environmental conditions not found in any other environment, thereby providing new opportunities to understand the processes that shape deep-sea benthic communities. Technological advances have led to an increase in the number of investigations in hadal trenches over the last two decades. However, more quantitative samples including the deepest parts of trenches is needed to better understand trends in benthic diversity, abundance, biomass and community structure in these extreme habitats, and how these may be shaped by environmental and/or evolutionary factors. In this study, we describe and compare the abundance, biomass, vertical distribution in the sediment, diversity, and community structure of nematodes and other infauna in sediments from the Horizon Deep ( 10 800 m) in the Tonga Trench and a site on the edge of the trench ( 6250 m). Mean nematode abundance was six times greater at the Horizon Deep site (387 ind. 10 cm-2) than at the trench edge site (65 ind. 10 cm-2). A similar pattern was observed for biomass (15 vs 2 μgDW 10 cm-2, respectively), which likely resulted from elevated organic matter supply at the Horizon Deep site. There was no significant difference in nematode species richness between the two sites, but diversity measured using rarefaction was significantly greater at the trench edge site than at the Horizon Deep site [ES(20); 13.8 vs 7.8]. Dominance was much more pronounced in the Horizon Deep, which may be due to competitive exclusion by a small number of opportunistic species. Nematode community structure differed significantly both between sites and among sediment depth layers. The presence of subsurface peaks in pigment concentrations, bacteria abundance, and nematode abundance at the Horizon Deep site is consistent with a recent turbidite event, and may also reflect high rates of bioturbation by larger fauna resulting from high food availability. Determining the relative influences of different environmental factors on hadal trench benthic communities will require further investigation based on quantitative samples encompassing the trench axis as well as the oceanic and continental slopes.

Exploring the Eastern United States Continental Shelf with the NOAA Cooperative Institute for Ocean Exploration, Research, and Technology

NASA Astrophysics Data System (ADS)

Glickson, D.; Pomponi, S. A.

2016-02-01

The Cooperative Institute for Ocean Exploration, Research, and Technology (CIOERT) serves NOAA priorities in three theme areas: exploring the eastern U.S. continental shelf, improving the understanding of coral and sponge ecosystems, and developing advanced underwater technologies. CIOERT focuses on the exploration and research of ecosystems and habitats along frontier regions of the eastern U.S. continental shelf that are of economic, scientific, or cultural importance or of natural hazards concern. One particular focus is supporting ocean exploration and research through the use of advanced underwater technologies and techniques in order to improve the understanding of vulnerable deep and shallow coral and sponge ecosystems. CIOERT expands the scope and efficiency of exploration and research by developing, testing, and applying new and/or innovative uses of existing technologies to ocean exploration and research activities. In addition, CIOERT is dedicated to expanding ocean literacy and building NOAA's technical and scientific workforce through hands-on, at-sea experiences. A recent CIOERT cruise characterized Gulf of Mexico mesophotic and deepwater reef ecosystems off the west Florida shelf, targeting northern Pulley Ridge. This project created and ground-truthed new sonar maps made with an autonomous underwater vehicle; conducted video and photographic transects of benthic habitat and fish using a remotely operated vehicle; and examined the connectivity of fauna from shallow to deep reef ecosystems. CIOERT was established in 2009 by FAU-Harbor Branch Oceanographic Institute, with University of North Carolina, Wilmington, SRI International, and the University of Miami. The primary NOAA partner is the Office of Oceanic and Atmospheric Research's Office of Ocean Exploration and Research.

Exploring the Eastern United States Continental Shelf with the NOAA Cooperative Institute for Ocean Exploration, Research, and Technology

NASA Astrophysics Data System (ADS)

Glickson, D.; Pomponi, S.

2015-12-01

The Cooperative Institute for Ocean Exploration, Research, and Technology (CIOERT) serves NOAA priorities in three theme areas: exploring the eastern U.S. continental shelf, improving the understanding of coral and sponge ecosystems, and developing advanced underwater technologies. CIOERT focuses on the exploration and research of ecosystems and habitats along frontier regions of the eastern U.S. continental shelf that are of economic, scientific, or cultural importance or of natural hazards concern. One particular focus is supporting ocean exploration and research through the use of advanced underwater technologies and techniques in order to improve the understanding of vulnerable deep and shallow coral and sponge ecosystems. CIOERT expands the scope and efficiency of exploration and research by developing, testing, and applying new and/or innovative uses of existing technologies to ocean exploration and research activities. In addition, CIOERT is dedicated to expanding ocean literacy and building NOAA's technical and scientific workforce through hands-on, at-sea experiences. A recent CIOERT cruise characterized Gulf of Mexico mesophotic and deepwater reef ecosystems off the west Florida shelf, targeting northern Pulley Ridge. This project created and ground-truthed new sonar maps made with an autonomous underwater vehicle; conducted video and photographic transects of benthic habitat and fish using a remotely operated vehicle; and examined the connectivity of fauna from shallow to deep reef ecosystems. CIOERT was established in 2009 by FAU-Harbor Branch Oceanographic Institute, with University of North Carolina, Wilmington, SRI International, and the University of Miami. The primary NOAA partner is the Office of Oceanic and Atmospheric Research's Office of Ocean Exploration and Research.

Developing a Comprehensive Model of Intensive Care Unit Processes: Concept of Operations.

PubMed

Romig, Mark; Tropello, Steven P; Dwyer, Cindy; Wyskiel, Rhonda M; Ravitz, Alan; Benson, John; Gropper, Michael A; Pronovost, Peter J; Sapirstein, Adam

2015-04-23

This study aimed to use a systems engineering approach to improve performance and stakeholder engagement in the intensive care unit to reduce several different patient harms. We developed a conceptual framework or concept of operations (ConOps) to analyze different types of harm that included 4 steps as follows: risk assessment, appropriate therapies, monitoring and feedback, as well as patient and family communications. This framework used a transdisciplinary approach to inventory the tasks and work flows required to eliminate 7 common types of harm experienced by patients in the intensive care unit. The inventory gathered both implicit and explicit information about how the system works or should work and converted the information into a detailed specification that clinicians could understand and use. Using the ConOps document, we created highly detailed work flow models to reduce harm and offer an example of its application to deep venous thrombosis. In the deep venous thrombosis model, we identified tasks that were synergistic across different types of harm. We will use a system of systems approach to integrate the variety of subsystems and coordinate processes across multiple types of harm to reduce the duplication of tasks. Through this process, we expect to improve efficiency and demonstrate synergistic interactions that ultimately can be applied across the spectrum of potential patient harms and patient locations. Engineering health care to be highly reliable will first require an understanding of the processes and work flows that comprise patient care. The ConOps strategy provided a framework for building complex systems to reduce patient harm.

3D Modeling of the Deep Groundwater System at Mount Shasta, California, Using Finite Difference and Inverse Modeling in Combination with Magnetotellurics

NASA Astrophysics Data System (ADS)

Webb, C. H.; Foglia, L.; Fogg, G. E.; McClain, J.

2017-12-01

Precipitation in mountainous systems is responsible for much of the world's freshwater supply. Volcanic mountains in particular may have the capacity to store large amounts of groundwater, due to the relatively high permeability of volcanic rocks as compared to fractured crystalline rocks. These qualities make volcanic aquifers likely candidates for laterally extensive deep groundwater systems. However, the depth extent of these aquifers is not well understood and has been little studied, due to the dearth of well data in most mountain systems. When determining a water budget, especially for mountainous regions, it is necessary to understand the extent of the entire system, including the deep components. Mount Shasta of the California cascade volcanoes is one potential case of a deep groundwater system with the capacity to store significant amounts of water. In order to develop a conceptual model of the role of deep and regional groundwater flow in the Mt. Shasta groundwater system, the region was modeled using MODFLOW_2005, the finite difference flow model developed by USGS. The model was constrained using SRTM topography data, spring flow rates, PRISM precipitation rates, and well log levels. Geologic cross sections and gravity data were referenced in order to create a realistic estimate of the aquifer's structure down to 6km in depth. The aquifer stratigraphy was then represented by using 6 layers with 2-4 zones of hydraulic conductivity per layer to account for both vertical and lateral differences in lithology as well as decreasing permeability with depth. These hydraulic conductivity parameters of the model were varied using inverse modeling (UCODE_2014) to determine which layers and zones could support flow and still produce results consistent with existing well logs. Depth of flow was also corroborated with resistivity data collected in Shasta Valley using magnetotelluric (MT) soundings. Depths with comparatively low electrical resistivity were assumed to be aquifer units, and zones with high resistivity were assumed to be aquitards. By performing MT soundings in multiple locations and dividing the model into zones, this model tests both the maximum depth of flow as well as how that depth varies with lithology and geographical location.

Stress monitoring versus microseismic ruptures in an active deep mine

NASA Astrophysics Data System (ADS)

Tonnellier, Alice; Bouffier, Christian; Bigarré, Pascal; Nyström, Anders; Österberg, Anders; Fjellström, Peter

2015-04-01

Nowadays, underground mining industry has developed high-technology mass mining methods to optimise the productivity at deep levels. Such massive extraction induces high-level stress redistribution generating seismic events around the mining works, threatening safety and economics. For this reason mining irregular deep ore bodies calls for steadily enhanced scientific practises and technologies to guarantee the mine environment to be safer and stable for the miners and the infrastructures. INERIS, within the framework of the FP7 European project I2Mine and in partnership with the Swedish mining company Boliden, has developed new methodologies in order to monitor both quasi-static stress changes and ruptures in a seismic prone area. To this purpose, a unique local permanent microseismic and stress monitoring network has been installed into the deep-working Garpenberg mine situated to the north of Uppsala (Sweden). In this mine, ore is extracted using sublevel stoping with paste fill production/distribution system and long-hole drilling method. This monitoring network has been deployed between about 1100 and 1250 meter depth. It consists in six 1-component and five 3-component microseismic probes (14-Hz geophones) deployed in the Lappberget area, in addition to three 3D stress monitoring cells that focus on a very local exploited area. Objective is three-fold: to quantify accurately quasi-static stress changes and freshly-induced stress gradients with drift development in the orebody, to study quantitatively those stress changes versus induced detected and located microseismic ruptures, and possibly to identify quasi-static stress transfer from those seismic ruptures. Geophysical and geotechnical data are acquired continuously and automatically transferred to INERIS datacenter through the web. They are made available on a secured web cloud monitoring infrastructure called e.cenaris and completed with mine data. Such interface enables the visualisation of the monitoring data coming from the mine in quasi-real time and facilitates information exchanges and decision making for experts and stakeholders. On the basis of these data acquisition and sharing, preliminary analysis has been started to highlight whether stress variations and seismic sources behaviour might be directly bound with mine working evolution and could improve the knowledge on the equilibrium states inside the mine. Knowing such parameters indeed will be a potential solution to understand better the response of deep mining activities to the exploitation solicitations and to develop, if possible, methods to prevent from major hazards such as rock bursts and other ground failure phenomena.

Deep Learning in Label-free Cell Classification

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

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Deep gluteal space problems: piriformis syndrome, ischiofemoral impingement and sciatic nerve release

PubMed Central

Carro, Luis Perez; Hernando, Moises Fernandez; Cerezal, Luis; Navarro, Ivan Saenz; Fernandez, Ana Alfonso; Castillo, Alexander Ortiz

2016-01-01

Summary Background Deep gluteal syndrome (DGS) is an underdiagnosed entity characterized by pain and/or dysesthesias in the buttock area, hip or posterior thigh and/or radicular pain due to a non-discogenic sciatic nerve entrapment in the subgluteal space. Multiple pathologies have been incorporated in this all-included “piriformis syndrome”, a term that has nothing to do with the presence of fibrous bands, obturator internus/gemellus syndrome, quadratus femoris/ischiofemoral pathology, hamstring conditions, gluteal disorders and orthopedic causes. Methods This article describes the subgluteal space anatomy, reviews known and new etiologies of DGS, and assesses the role of the radiologist and orthopaedic surgeons in the diagnosis, treatment and postoperative evaluation of sciatic nerve entrapments. Conclusion DGS is an under-recognized and multifactorial pathology. The development of periarticular hip endoscopy has led to an understanding of the pathophysiological mechanisms underlying piriformis syndrome, which has supported its further classification. The whole sciatic nerve trajectory in the deep gluteal space can be addressed by an endoscopic surgical technique. Endoscopic decompression of the sciatic nerve appears useful in improving function and diminishing hip pain in sciatic nerve entrapments, but requires significant experience and familiarity with the gross and endoscopic anatomy. Level of evidence IV. PMID:28066745

Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

PubMed

Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

2017-03-01

Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.

Deep Learning in Label-free Cell Classification

DOE PAGES

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; ...

2016-03-15

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Identification of microRNA-like RNAs from Curvularia lunata associated with maize leaf spot by bioinformation analysis and deep sequencing.

PubMed

Liu, Tong; Hu, John; Zuo, Yuhu; Jin, Yazhong; Hou, Jumei

2016-04-01

Deep sequencing of small RNAs is a useful tool to identify novel small RNAs that may be involved in fungal growth and pathogenesis. In this study, we used HiSeq deep sequencing to identify 747,487 unique small RNAs from Curvularia lunata. Among these small RNAs were 1012 microRNA-like RNAs (milRNAs), which are similar to other known microRNAs, and 48 potential novel milRNAs without homologs in other organisms have been identified using the miRBase© database. We used quantitative PCR to analyze the expression of four of these milRNAs from C. lunata at different developmental stages. The analysis revealed several changes associated with germinating conidia and mycelial growth, suggesting that these milRNAs may play a role in pathogen infection and mycelial growth. A total of 8334 target mRNAs for the 1012 milRNAs that were identified, and 256 target mRNAs for the 48 novel milRNAs were predicted by computational analysis. These target mRNAs of milRNAs were also performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. To our knowledge, this study is the first report of C. lunata's milRNA profiles. This information will provide a better understanding of pathogen development and infection mechanism.

Gamma knife radiosurgery in movement disorders: Indications and limitations.

PubMed

Higuchi, Yoshinori; Matsuda, Shinji; Serizawa, Toru

2017-01-01

Functional radiosurgery has advanced steadily during the past half century since the development of the gamma knife technique for treating intractable cancer pain. Applications of radiosurgery for intracranial diseases have increased with a focus on understanding radiobiology. Currently, the use of gamma knife radiosurgery to ablate deep brain structures is not widespread because visualization of the functional targets remains difficult despite the increased availability of advanced neuroimaging technology. Moreover, most existing reports have a small sample size or are retrospective. However, increased experience with intraoperative neurophysiological evaluations in radiofrequency thalamotomy and deep brain stimulation supports anatomical and neurophysiological approaches to the ventralis intermedius nucleus. Two recent prospective studies have promoted the clinical application of functional radiosurgery for movement disorders. For example, unilateral gamma knife thalamotomy is a potential alternative to radiofrequency thalamotomy and deep brain stimulation techniques for intractable tremor patients with contraindications for surgery. Despite the promising efficacy of gamma knife thalamotomy, however, these studies did not include sufficient follow-up to confirm long-term effects. Herein, we review the radiobiology literature, various techniques, and the treatment efficacy of gamma knife radiosurgery for patients with movement disorders. Future research should focus on randomized controlled studies and long-term effects. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Human Brain Modeling with Its Anatomical Structure and Realistic Material Properties for Brain Injury Prediction.

PubMed

Atsumi, Noritoshi; Nakahira, Yuko; Tanaka, Eiichi; Iwamoto, Masami

2018-05-01

Impairments of executive brain function after traumatic brain injury (TBI) due to head impacts in traffic accidents need to be obviated. Finite element (FE) analyses with a human brain model facilitate understanding of the TBI mechanisms. However, conventional brain FE models do not suitably describe the anatomical structure in the deep brain, which is a critical region for executive brain function, and the material properties of brain parenchyma. In this study, for better TBI prediction, a novel brain FE model with anatomical structure in the deep brain was developed. The developed model comprises a constitutive model of brain parenchyma considering anisotropy and strain rate dependency. Validation was performed against postmortem human subject test data associated with brain deformation during head impact. Brain injury analyses were performed using head acceleration curves obtained from reconstruction analysis of rear-end collision with a human whole-body FE model. The difference in structure was found to affect the regions of strain concentration, while the difference in material model contributed to the peak strain value. The injury prediction result by the proposed model was consistent with the characteristics in the neuroimaging data of TBI patients due to traffic accidents.

Self-guided training for deep brain stimulation planning using objective assessment.

PubMed

Holden, Matthew S; Zhao, Yulong; Haegelen, Claire; Essert, Caroline; Fernandez-Vidal, Sara; Bardinet, Eric; Ungi, Tamas; Fichtinger, Gabor; Jannin, Pierre

2018-04-04

Deep brain stimulation (DBS) is an increasingly common treatment for neurodegenerative diseases. Neurosurgeons must have thorough procedural, anatomical, and functional knowledge to plan electrode trajectories and thus ensure treatment efficacy and patient safety. Developing this knowledge requires extensive training. We propose a training approach with objective assessment of neurosurgeon proficiency in DBS planning. To assess proficiency, we propose analyzing both the viability of the planned trajectory and the manner in which the operator arrived at the trajectory. To improve understanding, we suggest a self-guided training course for DBS planning using real-time feedback. To validate the proposed measures of proficiency and training course, two experts and six novices followed the training course, and we monitored their proficiency measures throughout. At baseline, experts planned higher quality trajectories and did so more efficiently. As novices progressed through the training course, their proficiency measures increased significantly, trending toward expert measures. We developed and validated measures which reliably discriminate proficiency levels. These measures are integrated into a training course, which quantitatively improves trainee performance. The proposed training course can be used to improve trainees' proficiency, and the quantitative measures allow trainees' progress to be monitored.

A Procedure for the supercritical fluid extraction of coal samples, with subsequent analysis of extracted hydrocarbons

USGS Publications Warehouse

Kolak, Jonathan J.

2006-01-01

Introduction: This report provides a detailed, step-by-step procedure for conducting extractions with supercritical carbon dioxide (CO2) using the ISCO SFX220 supercritical fluid extraction system. Protocols for the subsequent separation and analysis of extracted hydrocarbons are also included in this report. These procedures were developed under the auspices of the project 'Assessment of Geologic Reservoirs for Carbon Dioxide Sequestration' (see http://pubs.usgs.gov/fs/fs026-03/fs026-03.pdf) to investigate possible environmental ramifications associated with CO2 storage (sequestration) in geologic reservoirs, such as deep (~1 km below land surface) coal beds. Supercritical CO2 has been used previously to extract contaminants from geologic matrices. Pressure-temperature conditions within deep coal beds may render CO2 supercritical. In this context, the ability of supercritical CO2 to extract contaminants from geologic materials may serve to mobilize noxious compounds from coal, possibly complicating storage efforts. There currently exists little information on the physicochemical interactions between supercritical CO2 and coal in this setting. The procedures described herein were developed to improve the understanding of these interactions and provide insight into the fate of CO2 and contaminants during simulated CO2 injections.

Deep-sea bacterial communities in sediments and guts of deposit-feeding holothurians in Portuguese canyons (NE Atlantic)

NASA Astrophysics Data System (ADS)

Amaro, Teresa; Witte, Harry; Herndl, Gerhard J.; Cunha, Marina R.; Billett, David S. M.

2009-10-01

Deposit-feeding holothurians often dominate the megafauna in bathyal deep-sea settings, in terms of both abundance and biomass. Molpadia musculus is particularly abundant at about 3400 m depth in the Nazaré Canyon on the NE Atlantic Continental Margin. However, these high abundances are unusual for burrowing species at this depth. The objective of this research was to understand the reasons of the massive occurrence of these molpadiid holothurians in the Nazaré Canyon. To address this question we investigated possible trophic interactions with bacteria at sites where the organic content of the sediment was different (Setúbal and Cascais Canyons, NE Atlantic Continental Margin). The molecular fingerprinting technique of Denaturing Gradient Gel Electrophoresis (DGGE) with band sequencing, combined with non-metric multi-dimensional scaling and statistical analyses, was used to compare the bacterial community diversity in canyon sediments and holothurian gut contents. Our results suggest that M. musculus does not need to develop a specialised gut bacterial community to aid digestion where the sediment is rich in organic matter (Nazaré Canyon); in contrast, such a community may be developed where the sediment is poorer in organic matter (Cascais Canyon).

Deep-Sea Bioluminescence Blooms after Dense Water Formation at the Ocean Surface

PubMed Central

Tamburini, Christian; Canals, Miquel; Durrieu de Madron, Xavier; Houpert, Loïc; Lefèvre, Dominique; Martini, Séverine; D'Ortenzio, Fabrizio; Robert, Anne; Testor, Pierre; Aguilar, Juan Antonio; Samarai, Imen Al; Albert, Arnaud; André, Michel; Anghinolfi, Marco; Anton, Gisela; Anvar, Shebli; Ardid, Miguel; Jesus, Ana Carolina Assis; Astraatmadja, Tri L.; Aubert, Jean-Jacques; Baret, Bruny; Basa, Stéphane; Bertin, Vincent; Biagi, Simone; Bigi, Armando; Bigongiari, Ciro; Bogazzi, Claudio; Bou-Cabo, Manuel; Bouhou, Boutayeb; Bouwhuis, Mieke C.; Brunner, Jurgen; Busto, José; Camarena, Francisco; Capone, Antonio; Cârloganu, Christina; Carminati, Giada; Carr, John; Cecchini, Stefano; Charif, Ziad; Charvis, Philippe; Chiarusi, Tommaso; Circella, Marco; Coniglione, Rosa; Costantini, Heide; Coyle, Paschal; Curtil, Christian; Decowski, Patrick; Dekeyser, Ivan; Deschamps, Anne; Donzaud, Corinne; Dornic, Damien; Dorosti, Hasankiadeh Q.; Drouhin, Doriane; Eberl, Thomas; Emanuele, Umberto; Ernenwein, Jean-Pierre; Escoffier, Stéphanie; Fermani, Paolo; Ferri, Marcelino; Flaminio, Vincenzo; Folger, Florian; Fritsch, Ulf; Fuda, Jean-Luc; Galatà, Salvatore; Gay, Pascal; Giacomelli, Giorgio; Giordano, Valentina; Gómez-González, Juan-Pablo; Graf, Kay; Guillard, Goulven; Halladjian, Garadeb; Hallewell, Gregory; van Haren, Hans; Hartman, Joris; Heijboer, Aart J.; Hello, Yann; Hernández-Rey, Juan Jose; Herold, Bjoern; Hößl, Jurgen; Hsu, Ching-Cheng; de Jong, Marteen; Kadler, Matthias; Kalekin, Oleg; Kappes, Alexander; Katz, Uli; Kavatsyuk, Oksana; Kooijman, Paul; Kopper, Claudio; Kouchner, Antoine; Kreykenbohm, Ingo; Kulikovskiy, Vladimir; Lahmann, Robert; Lamare, Patrick; Larosa, Giuseppina; Lattuada, Dario; Lim, Gordon; Presti, Domenico Lo; Loehner, Herbert; Loucatos, Sotiris; Mangano, Salvatore; Marcelin, Michel; Margiotta, Annarita; Martinez-Mora, Juan Antonio; Meli, Athina; Montaruli, Teresa; Motz, Holger; Neff, Max; Nezri, Emma nuel; Palioselitis, Dimitris; Păvălaş, Gabriela E.; Payet, Kevin; Payre, Patrice; Petrovic, Jelena; Piattelli, Paolo; Picot-Clemente, Nicolas; Popa, Vlad; Pradier, Thierry; Presani, Eleonora; Racca, Chantal; Reed, Corey; Riccobene, Giorgio; Richardt, Carsten; Richter, Roland; Rivière, Colas; Roensch, Kathrin; Rostovtsev, Andrei; Ruiz-Rivas, Joaquin; Rujoiu, Marius; Russo, Valerio G.; Salesa, Francisco; Sánchez-Losa, Augustin; Sapienza, Piera; Schöck, Friederike; Schuller, Jean-Pierre; Schussler, Fabian; Shanidze, Rezo; Simeone, Francesco; Spies, Andreas; Spurio, Maurizio; Steijger, Jos J. M.; Stolarczyk, Thierry; Taiuti, Mauro G. F.; Toscano, Simona; Vallage, Bertrand; Van Elewyck, Véronique; Vannoni, Giulia; Vecchi, Manuela; Vernin, Pascal; Wijnker, Guus; Wilms, Jorn; de Wolf, Els; Yepes, Harold; Zaborov, Dmitry; De Dios Zornoza, Juan; Zúñiga, Juan

2013-01-01

The deep ocean is the largest and least known ecosystem on Earth. It hosts numerous pelagic organisms, most of which are able to emit light. Here we present a unique data set consisting of a 2.5-year long record of light emission by deep-sea pelagic organisms, measured from December 2007 to June 2010 at the ANTARES underwater neutrino telescope in the deep NW Mediterranean Sea, jointly with synchronous hydrological records. This is the longest continuous time-series of deep-sea bioluminescence ever recorded. Our record reveals several weeks long, seasonal bioluminescence blooms with light intensity up to two orders of magnitude higher than background values, which correlate to changes in the properties of deep waters. Such changes are triggered by the winter cooling and evaporation experienced by the upper ocean layer in the Gulf of Lion that leads to the formation and subsequent sinking of dense water through a process known as “open-sea convection”. It episodically renews the deep water of the study area and conveys fresh organic matter that fuels the deep ecosystems. Luminous bacteria most likely are the main contributors to the observed deep-sea bioluminescence blooms. Our observations demonstrate a consistent and rapid connection between deep open-sea convection and bathypelagic biological activity, as expressed by bioluminescence. In a setting where dense water formation events are likely to decline under global warming scenarios enhancing ocean stratification, in situ observatories become essential as environmental sentinels for the monitoring and understanding of deep-sea ecosystem shifts. PMID:23874425

Functional reasoning in diagnostic problem solving

NASA Technical Reports Server (NTRS)

Sticklen, Jon; Bond, W. E.; Stclair, D. C.

1988-01-01

This work is one facet of an integrated approach to diagnostic problem solving for aircraft and space systems currently under development. The authors are applying a method of modeling and reasoning about deep knowledge based on a functional viewpoint. The approach recognizes a level of device understanding which is intermediate between a compiled level of typical Expert Systems, and a deep level at which large-scale device behavior is derived from known properties of device structure and component behavior. At this intermediate functional level, a device is modeled in three steps. First, a component decomposition of the device is defined. Second, the functionality of each device/subdevice is abstractly identified. Third, the state sequences which implement each function are specified. Given a functional representation and a set of initial conditions, the functional reasoner acts as a consequence finder. The output of the consequence finder can be utilized in diagnostic problem solving. The paper also discussed ways in which this functional approach may find application in the aerospace field.

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

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

Riihimaki, Laura D.; Comstock, Jennifer M.; Luke, Edward

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement (ARM) site are used to classify cloud phase within a deep convective cloud in a shallow to deep convection transitional case. The cloud cannot be fully observed by a lidar due to signal attenuation. Thus we develop an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectramore » from vertically pointing Ka band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid, indicating complexity to how ice growth and diabatic heating occurs in the vertical structure of the cloud.« less