High-resolution face verification using pore-scale facial features.

PubMed

Li, Dong; Zhou, Huiling; Lam, Kin-Man

2015-08-01

Face recognition methods, which usually represent face images using holistic or local facial features, rely heavily on alignment. Their performances also suffer a severe degradation under variations in expressions or poses, especially when there is one gallery per subject only. With the easy access to high-resolution (HR) face images nowadays, some HR face databases have recently been developed. However, few studies have tackled the use of HR information for face recognition or verification. In this paper, we propose a pose-invariant face-verification method, which is robust to alignment errors, using the HR information based on pore-scale facial features. A new keypoint descriptor, namely, pore-Principal Component Analysis (PCA)-Scale Invariant Feature Transform (PPCASIFT)-adapted from PCA-SIFT-is devised for the extraction of a compact set of distinctive pore-scale facial features. Having matched the pore-scale features of two-face regions, an effective robust-fitting scheme is proposed for the face-verification task. Experiments show that, with one frontal-view gallery only per subject, our proposed method outperforms a number of standard verification methods, and can achieve excellent accuracy even the faces are under large variations in expression and pose.

Evaluating the Invariance of Cognitive Profile Patterns Derived from Profile Analysis via Multidimensional Scaling (PAMS): A Bootstrapping Approach

ERIC Educational Resources Information Center

Kim, Se-Kang

2010-01-01

The aim of the current study is to validate the invariance of major profile patterns derived from multidimensional scaling (MDS) by bootstrapping. Profile Analysis via Multidimensional Scaling (PAMS) was employed to obtain profiles and bootstrapping was used to construct the sampling distributions of the profile coordinates and the empirical…

Distinctive Feature Extraction for Indian Sign Language (ISL) Gesture using Scale Invariant Feature Transform (SIFT)

NASA Astrophysics Data System (ADS)

Patil, Sandeep Baburao; Sinha, G. R.

2017-02-01

India, having less awareness towards the deaf and dumb peoples leads to increase the communication gap between deaf and hard hearing community. Sign language is commonly developed for deaf and hard hearing peoples to convey their message by generating the different sign pattern. The scale invariant feature transform was introduced by David Lowe to perform reliable matching between different images of the same object. This paper implements the various phases of scale invariant feature transform to extract the distinctive features from Indian sign language gestures. The experimental result shows the time constraint for each phase and the number of features extracted for 26 ISL gestures.

Investigating a link between large and small-scale chaos features on Europa

NASA Astrophysics Data System (ADS)

Tognetti, L.; Rhoden, A.; Nelson, D. M.

2017-12-01

Chaos is one of the most recognizable, and studied, features on Europa's surface. Most models of chaos formation invoke liquid water at shallow depths within the ice shell; the liquid destabilizes the overlying ice layer, breaking it into mobile rafts and destroying pre-existing terrain. This class of model has been applied to both large-scale chaos like Conamara and small-scale features (i.e. microchaos), which are typically <10 km in diameter. Currently unknown, however, is whether both large-scale and small-scale features are produced together, e.g. through a network of smaller sills linked to a larger liquid water pocket. If microchaos features do form as satellites of large-scale chaos features, we would expect a drop off in the number density of microchaos with increasing distance from the large chaos feature; the trend should not be observed in regions without large-scale chaos features. Here, we test the hypothesis that large chaos features create "satellite" systems of smaller chaos features. Either outcome will help us better understand the relationship between large-scale chaos and microchaos. We focus first on regions surrounding the large chaos features Conamara and Murias (e.g. the Mitten). We map all chaos features within 90,000 sq km of the main chaos feature and assign each one a ranking (High Confidence, Probable, or Low Confidence) based on the observed characteristics of each feature. In particular, we look for a distinct boundary, loss of preexisting terrain, the existence of rafts or blocks, and the overall smoothness of the feature. We also note features that are chaos-like but lack sufficient characteristics to be classified as chaos. We then apply the same criteria to map microchaos features in regions of similar area ( 90,000 sq km) that lack large chaos features. By plotting the distribution of microchaos with distance from the center point of the large chaos feature or the mapping region (for the cases without a large feature), we

Long-wave infrared profile feature extractor (PFx) sensor

NASA Astrophysics Data System (ADS)

Sartain, Ronald B.; Aliberti, Keith; Alexander, Troy; Chiu, David

2009-05-01

The Long Wave Infrared (LWIR) Profile Feature Extractor (PFx) sensor has evolved from the initial profiling sensor that was developed by the University of Memphis (Near IR) and the Army Research Laboratory (visible). This paper presents the initial signatures of the LWIR PFx for human with and without backpacks, human with animal (dog), and a number of other animals. The current version of the LWIR PFx sensor is a diverging optical tripwire sensor. The LWIR PFx signatures are compared to the signatures of the Profile Sensor in the visible and Near IR spectral regions. The LWIR PFx signatures were collected with two different un-cooled micro bolometer focal plane array cameras, where the individual pixels were used as stand alone detectors (a non imaging sensor). This approach results in a completely passive, much lower bandwidth, much longer battery life, low weight, small volume sensor that provides sufficient information to classify objects into human Vs non human categories with a 98.5% accuracy.

Scale Space for Camera Invariant Features.

PubMed

Puig, Luis; Guerrero, José J; Daniilidis, Kostas

2014-09-01

In this paper we propose a new approach to compute the scale space of any central projection system, such as catadioptric, fisheye or conventional cameras. Since these systems can be explained using a unified model, the single parameter that defines each type of system is used to automatically compute the corresponding Riemannian metric. This metric, is combined with the partial differential equations framework on manifolds, allows us to compute the Laplace-Beltrami (LB) operator, enabling the computation of the scale space of any central projection system. Scale space is essential for the intrinsic scale selection and neighborhood description in features like SIFT. We perform experiments with synthetic and real images to validate the generalization of our approach to any central projection system. We compare our approach with the best-existing methods showing competitive results in all type of cameras: catadioptric, fisheye, and perspective.

Evolutionary and mechanistic theories of aging.

PubMed

Hughes, Kimberly A; Reynolds, Rose M

2005-01-01

Senescence (aging) is defined as a decline in performance and fitness with advancing age. Senescence is a nearly universal feature of multicellular organisms, and understanding why it occurs is a long-standing problem in biology. Here we present a concise review of both evolutionary and mechanistic theories of aging. We describe the development of the general evolutionary theory, along with the mutation accumulation, antagonistic pleiotropy, and disposable soma versions of the evolutionary model. The review of the mechanistic theories focuses on the oxidative stress resistance, cellular signaling, and dietary control mechanisms of life span extension. We close with a discussion of how an approach that makes use of both evolutionary and molecular analyses can address a critical question: Which of the mechanisms that can cause variation in aging actually do cause variation in natural populations?

Understanding and Predicting Profile Structure and Parametric Scaling of Intrinsic Rotation

NASA Astrophysics Data System (ADS)

Wang, Weixing

2016-10-01

It is shown for the first time that turbulence-driven residual Reynolds stress can account for both the shape and magnitude of the observed intrinsic toroidal rotation profile. Nonlinear, global gyrokinetic simulations using GTS of DIII-D ECH plasmas indicate a substantial ITG fluctuation-induced non-diffusive momentum flux generated around a mid-radius-peaked intrinsic toroidal rotation profile. The non-diffusive momentum flux is dominated by the residual stress with a negligible contribution from the momentum pinch. The residual stress profile shows a robust anti-gradient, dipole structure in a set of ECH discharges with varying ECH power. Such interesting features of non-diffusive momentum fluxes, in connection with edge momentum sources and sinks, are found to be critical to drive the non-monotonic core rotation profiles in the experiments. Both turbulence intensity gradient and zonal flow ExB shear are identified as major contributors to the generation of the k∥-asymmetry needed for the residual stress generation. By balancing the residual stress and the momentum diffusion, a self-organized, steady-state rotation profile is calculated. The predicted core rotation profiles agree well with the experimentally measured main-ion toroidal rotation. The validated model is further used to investigate the characteristic dependence of global rotation profile structure in the multi-dimensional parametric space covering turbulence type, q-profile structure and collisionality with the goal of developing physics understanding needed for rotation profile control and optimization. Interesting results obtained include intrinsic rotation reversal induced by ITG-TEM transition in flat-q profile regime and by change in q-profile from weak to normal shear.. Fluctuation-generated poloidal Reynolds stress is also shown to significantly modify the neoclassical poloidal rotation in a way consistent with experimental observations. Finally, the first-principles-based model is applied

Rotation, scale, and translation invariant pattern recognition using feature extraction

NASA Astrophysics Data System (ADS)

Prevost, Donald; Doucet, Michel; Bergeron, Alain; Veilleux, Luc; Chevrette, Paul C.; Gingras, Denis J.

1997-03-01

A rotation, scale and translation invariant pattern recognition technique is proposed.It is based on Fourier- Mellin Descriptors (FMD). Each FMD is taken as an independent feature of the object, and a set of those features forms a signature. FMDs are naturally rotation invariant. Translation invariance is achieved through pre- processing. A proper normalization of the FMDs gives the scale invariance property. This approach offers the double advantage of providing invariant signatures of the objects, and a dramatic reduction of the amount of data to process. The compressed invariant feature signature is next presented to a multi-layered perceptron neural network. This final step provides some robustness to the classification of the signatures, enabling good recognition behavior under anamorphically scaled distortion. We also present an original feature extraction technique, adapted to optical calculation of the FMDs. A prototype optical set-up was built, and experimental results are presented.

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation.

PubMed

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M; Young, Vincent B; Jansson, Janet K; Fredricks, David N; Borenstein, Elhanan

2016-01-01

Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites' abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. Studies

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

PubMed Central

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.

2016-01-01

ABSTRACT Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease

Constrained clusters of gene expression profiles with pathological features.

PubMed

Sese, Jun; Kurokawa, Yukinori; Monden, Morito; Kato, Kikuya; Morishita, Shinichi

2004-11-22

Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features. We present the novel technique of 'itemset constrained clustering' (IC-Clustering), which computes the optimal cluster that maximizes the interclass variance of gene expression between groups, which are divided according to the restriction that only divisions that can be expressed using common features are allowed. This constraint automatically labels each cluster with a set of pathological features which characterize that cluster. When applied to liver cancer datasets, IC-Clustering revealed informative gene expression clusters, which could be annotated with various pathological features, such as 'tumor' and 'man', or 'except tumor' and 'normal liver function'. In contrast, the k-means method overlooked these clusters.

3D-profile measurement of advanced semiconductor features by using FIB as reference metrology

NASA Astrophysics Data System (ADS)

Takamasu, Kiyoshi; Iwaki, Yuuki; Takahashi, Satoru; Kawada, Hiroki; Ikota, Masami

2017-03-01

A novel method of sub-nanometer uncertainty for the 3D-profile measurement and LWR (Line Width Roughness) measurement by using FIB (Focused Ion Beam) processing, and TEM (Transmission Electron Microscope) and CD-SEM (Critical Dimension Scanning Electron Microscope) images measurement is proposed to standardize 3D-profile measurement through reference metrology. In this article, we apply the methodology to line profile measurements and roughness measurement of advanced FinFET (Fin-shaped Field-Effect Transistor) features. The FinFET features are horizontally sliced as a thin specimen by FIB micro sampling system. Horizontally images of the specimens are obtained then by a planar TEM. LWR is calculated from the edges positions on TEM images. Moreover, we already have demonstrated the novel on-wafer 3D-profile metrology as "FIB-to-CDSEM method" with FIB slope cut and CD-SEM measuring. Using the method, a few micrometers wide on a wafer is coated and cut by 45-degree slope using FIB tool. Then, the wafer is transferred to CD-SEM to measure the cross section image by top down CD-SEM measurement. We applied FIB-to-CDSEM method to a CMOS image sensor feature. The 45-degree slope cut surface is observed using AFM. The surface profile of slope cut surface and line profiles are analyzed for improving the accuracy of FIB-to-CDSEM method.

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

NASA Astrophysics Data System (ADS)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

"Clinical brain profiling": a neuroscientific diagnostic approach for mental disorders.

PubMed

Peled, Abraham; Geva, Amir B

2014-10-01

Clinical brain profiling is an attempt to map a descriptive nosology in psychiatry to underlying constructs in neurobiology and brain dynamics. This paper briefly reviews the motivation behind clinical brain profiling (CBP) and presents some provisional validation using clinical assessments and meta-analyses of neuroscientific publications. The paper has four sections. In the first, we review the nature and motivation for clinical brain profiling. This involves a description of the key aspects of functional anatomy that can lead to psychopathology. These features constitute the dimensions or categories for a profile of brain disorders based upon pathophysiology. The second section describes a mapping or translation matrix that maps from symptoms and signs, of a descriptive sort, to the CBP dimensions that provide a more mechanistic explanation. We will describe how this mapping engenders archetypal diagnoses, referring readers to tables and figures. The third section addresses the construct validity of clinical brain profiling by establishing correlations between profiles based on clinical ratings of symptoms and signs under classical diagnostic categories with the corresponding profiles generated automatically using archetypal diagnoses. We then provide further validation by performing a cluster analysis on the symptoms and signs and showing how they correspond to the equivalent brain profiles based upon clinical and automatic diagnosis. In the fourth section, we address the construct validity of clinical brain profiling by looking for associations between pathophysiological mechanisms (such as connectivity and plasticity) and nosological diagnoses (such as schizophrenia and depression). Based upon the mechanistic perspective offered in the first section, we test some particular hypotheses about double dissociations using a meta-analysis of PubMed searches. The final section concludes with perspectives for the future and outstanding validation issues for clinical

Modeling systems-level dynamics: Understanding without mechanistic explanation in integrative systems biology.

PubMed

MacLeod, Miles; Nersessian, Nancy J

2015-02-01

In this paper we draw upon rich ethnographic data of two systems biology labs to explore the roles of explanation and understanding in large-scale systems modeling. We illustrate practices that depart from the goal of dynamic mechanistic explanation for the sake of more limited modeling goals. These processes use abstract mathematical formulations of bio-molecular interactions and data fitting techniques which we call top-down abstraction to trade away accurate mechanistic accounts of large-scale systems for specific information about aspects of those systems. We characterize these practices as pragmatic responses to the constraints many modelers of large-scale systems face, which in turn generate more limited pragmatic non-mechanistic forms of understanding of systems. These forms aim at knowledge of how to predict system responses in order to manipulate and control some aspects of them. We propose that this analysis of understanding provides a way to interpret what many systems biologists are aiming for in practice when they talk about the objective of a "systems-level understanding." Copyright © 2014 Elsevier Ltd. All rights reserved.

Doppler Feature Based Classification of Wind Profiler Data

NASA Astrophysics Data System (ADS)

Sinha, Swati; Chandrasekhar Sarma, T. V.; Lourde. R, Mary

2017-01-01

Wind Profilers (WP) are coherent pulsed Doppler radars in UHF and VHF bands. They are used for vertical profiling of wind velocity and direction. This information is very useful for weather modeling, study of climatic patterns and weather prediction. Observations at different height and different wind velocities are possible by changing the operating parameters of WP. A set of Doppler power spectra is the standard form of WP data. Wind velocity, direction and wind velocity turbulence at different heights can be derived from it. Modern wind profilers operate for long duration and generate approximately 4 megabytes of data per hour. The radar data stream contains Doppler power spectra from different radar configurations with echoes from different atmospheric targets. In order to facilitate systematic study, this data needs to be segregated according the type of target. A reliable automated target classification technique is required to do this job. Classical techniques of radar target identification use pattern matching and minimization of mean squared error, Euclidean distance etc. These techniques are not effective for the classification of WP echoes, as these targets do not have well-defined signature in Doppler power spectra. This paper presents an effective target classification technique based on range-Doppler features.

The evolution of honey bee dance communication: a mechanistic perspective.

PubMed

Barron, Andrew B; Plath, Jenny Aino

2017-12-01

Honey bee dance has been intensively studied as a communication system, and yet we still know very little about the neurobiological mechanisms supporting how dances are produced and interpreted. Here, we discuss how new information on the functions of the central complex (CX) of the insect brain might shed some light on possible neural mechanisms of dance behaviour. We summarise the features of dance communication across the species of the genus Apis We then propose that neural mechanisms of orientation and spatial processing found to be supported by the CX may function in dance communication also, and that this mechanistic link could explain some specific features of the dance form. This is purely a hypothesis, but in proposing this hypothesis, and how it might be investigated, we hope to stimulate new mechanistic analyses of dance communication. © 2017. Published by The Company of Biologists Ltd.

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

Al-Khafaji, Suhad Lateef; Jun Zhou; Zia, Ali; Liew, Alan Wee-Chung

2018-02-01

Spectral-spatial feature extraction is an important task in hyperspectral image processing. In this paper we propose a novel method to extract distinctive invariant features from hyperspectral images for registration of hyperspectral images with different spectral conditions. Spectral condition means images are captured with different incident lights, viewing angles, or using different hyperspectral cameras. In addition, spectral condition includes images of objects with the same shape but different materials. This method, which is named spectral-spatial scale invariant feature transform (SS-SIFT), explores both spectral and spatial dimensions simultaneously to extract spectral and geometric transformation invariant features. Similar to the classic SIFT algorithm, SS-SIFT consists of keypoint detection and descriptor construction steps. Keypoints are extracted from spectral-spatial scale space and are detected from extrema after 3D difference of Gaussian is applied to the data cube. Two descriptors are proposed for each keypoint by exploring the distribution of spectral-spatial gradient magnitude in its local 3D neighborhood. The effectiveness of the SS-SIFT approach is validated on images collected in different light conditions, different geometric projections, and using two hyperspectral cameras with different spectral wavelength ranges and resolutions. The experimental results show that our method generates robust invariant features for spectral-spatial image matching.

Generative Mechanistic Explanation Building in Undergraduate Molecular and Cellular Biology

ERIC Educational Resources Information Center

Southard, Katelyn M.; Espindola, Melissa R.; Zaepfel, Samantha D.; Bolger, Molly S.

2017-01-01

When conducting scientific research, experts in molecular and cellular biology (MCB) use specific reasoning strategies to construct mechanistic explanations for the underlying causal features of molecular phenomena. We explored how undergraduate students applied this scientific practice in MCB. Drawing from studies of explanation building among…

Global scale analysis and evaluation of an improved mechanistic representation of plant nitrogen and carbon dynamics in the Community Land Model (CLM)

NASA Astrophysics Data System (ADS)

Ghimire, B.; Riley, W. J.; Koven, C. D.; Randerson, J. T.; Mu, M.; Kattge, J.; Rogers, A.; Reich, P. B.

2014-12-01

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However mechanistic representation of nitrogen uptake linked to root traits, and functional nitrogen allocation among different leaf enzymes involved in respiration and photosynthesis is currently lacking in Earth System models. The linkage between nitrogen availability and plant productivity is simplistically represented by potential photosynthesis rates, and is subsequently downregulated depending on nitrogen supply and other nitrogen consumers in the model (e.g., nitrification). This type of potential photosynthesis rate calculation is problematic for several reasons. Firstly, plants do not photosynthesize at potential rates and then downregulate. Secondly, there is considerable subjectivity on the meaning of potential photosynthesis rates. Thirdly, there exists lack of understanding on modeling these potential photosynthesis rates in a changing climate. In addition to model structural issues in representing photosynthesis rates, the role of plant roots in nutrient acquisition have been largely ignored in Earth System models. For example, in CLM4.5, nitrogen uptake is linked to leaf level processes (e.g., primarily productivity) rather than root scale process involved in nitrogen uptake. We present a new plant model for CLM with an improved mechanistic presentation of plant nitrogen uptake based on root scale Michaelis Menten kinetics, and stronger linkages between leaf nitrogen and plant productivity by inferring relationships observed in global databases of plant traits (including the TRY database and several individual studies). We also incorporate improved representation of plant nitrogen leaf allocation, especially in tropical regions where significant over-prediction of plant growth and productivity in CLM4.5 simulations exist. We evaluate our improved global model simulations using the International Land Model Benchmarking (ILAMB) framework. We conclude that

Combining correlative and mechanistic habitat suitability models to improve ecological compensation.

PubMed

Meineri, Eric; Deville, Anne-Sophie; Grémillet, David; Gauthier-Clerc, Michel; Béchet, Arnaud

2015-02-01

Only a few studies have shown positive impacts of ecological compensation on species dynamics affected by human activities. We argue that this is due to inappropriate methods used to forecast required compensation in environmental impact assessments. These assessments are mostly descriptive and only valid at limited spatial and temporal scales. However, habitat suitability models developed to predict the impacts of environmental changes on potential species' distributions should provide rigorous science-based tools for compensation planning. Here we describe the two main classes of predictive models: correlative models and individual-based mechanistic models. We show how these models can be used alone or synoptically to improve compensation planning. While correlative models are easier to implement, they tend to ignore underlying ecological processes and lack accuracy. On the contrary, individual-based mechanistic models can integrate biological interactions, dispersal ability and adaptation. Moreover, among mechanistic models, those considering animal energy balance are particularly efficient at predicting the impact of foraging habitat loss. However, mechanistic models require more field data compared to correlative models. Hence we present two approaches which combine both methods for compensation planning, especially in relation to the spatial scale considered. We show how the availability of biological databases and software enabling fast and accurate population projections could be advantageously used to assess ecological compensation requirement efficiently in environmental impact assessments. © 2014 The Authors. Biological Reviews © 2014 Cambridge Philosophical Society.

[Features of diurnal profile of blood pressure in workers having serum aromatic hydrocarbons level].

PubMed

Baĭdina, A S; Safonova, M A; Alekseev, V B

2012-01-01

Features of diurnal profile of blood pressure in workers having serum level of benzol and ethylbenzene are high systolic and diastolic arterial blood pressure during the day, index of systolic arterial pressure time and index diastolic arterial pressure time was also high. These features should be considered in anti-hypertensives prescription.

The future of primordial features with large-scale structure surveys

NASA Astrophysics Data System (ADS)

Chen, Xingang; Dvorkin, Cora; Huang, Zhiqi; Namjoo, Mohammad Hossein; Verde, Licia

2016-11-01

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial Universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopic and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.

The future of primordial features with large-scale structure surveys

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

Chen, Xingang; Namjoo, Mohammad Hossein; Dvorkin, Cora

2016-11-01

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial Universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopicmore » and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.« less

Scale-adaptive compressive tracking with feature integration

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Jicheng; Chen, Xiao; Li, Shuxin

2016-05-01

Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.

A geographic comparison of selected large-scale planetary surface features

NASA Technical Reports Server (NTRS)

Meszaros, S. P.

1984-01-01

Photographic and cartographic comparisons of geographic features on Mercury, the Moon, Earth, Mars, Ganymede, Callisto, Mimas, and Tethys are presented. Planetary structures caused by impacts, volcanism, tectonics, and other natural forces are included. Each feature is discussed individually and then those of similar origin are compared at the same scale.

Getting To Know You: Profiles of Children's Authors Featured in "Language Arts" 1985-90.

ERIC Educational Resources Information Center

Kiefer, Barbara, Comp.

This book is a selection of profiles of children's authors featured in the journal "Language Arts" over the years. The book's 12 individual profiles highlight some of the real people who contribute to children's book publishing, provide a sample of a few of the many genres of books available for children, and give an insight into the…

Cloud Detection by Fusing Multi-Scale Convolutional Features

NASA Astrophysics Data System (ADS)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Identifying marker genes in transcription profiling data using a mixture of feature relevance experts.

PubMed

Chow, M L; Moler, E J; Mian, I S

2001-03-08

Transcription profiling experiments permit the expression levels of many genes to be measured simultaneously. Given profiling data from two types of samples, genes that most distinguish the samples (marker genes) are good candidates for subsequent in-depth experimental studies and developing decision support systems for diagnosis, prognosis, and monitoring. This work proposes a mixture of feature relevance experts as a method for identifying marker genes and illustrates the idea using published data from samples labeled as acute lymphoblastic and myeloid leukemia (ALL, AML). A feature relevance expert implements an algorithm that calculates how well a gene distinguishes samples, reorders genes according to this relevance measure, and uses a supervised learning method [here, support vector machines (SVMs)] to determine the generalization performances of different nested gene subsets. The mixture of three feature relevance experts examined implement two existing and one novel feature relevance measures. For each expert, a gene subset consisting of the top 50 genes distinguished ALL from AML samples as completely as all 7,070 genes. The 125 genes at the union of the top 50s are plausible markers for a prototype decision support system. Chromosomal aberration and other data support the prediction that the three genes at the intersection of the top 50s, cystatin C, azurocidin, and adipsin, are good targets for investigating the basic biology of ALL/AML. The same data were employed to identify markers that distinguish samples based on their labels of T cell/B cell, peripheral blood/bone marrow, and male/female. Selenoprotein W may discriminate T cells from B cells. Results from analysis of transcription profiling data from tumor/nontumor colon adenocarcinoma samples support the general utility of the aforementioned approach. Theoretical issues such as choosing SVM kernels and their parameters, training and evaluating feature relevance experts, and the impact of

Profiling plasma extracellular vesicle by pluronic block-copolymer based enrichment method unveils features associated with breast cancer aggression, metastasis and invasion

PubMed Central

Rosenow, Matthew; Xiao, Nick; Spetzler, David

2018-01-01

ABSTRACT Extracellular vesicle (EV)-based liquid biopsies have been proposed to be a readily obtainable biological substrate recently for both profiling and diagnostics purposes. Development of a fast and reliable preparation protocol to enrich such small particles could accelerate the discovery of informative, disease-related biomarkers. Though multiple EV enrichment protocols are available, in terms of efficiency, reproducibility and simplicity, precipitation-based methods are most amenable to studies with large numbers of subjects. However, the selectivity of the precipitation becomes critical. Here, we present a simple plasma EV enrichment protocol based on pluronic block copolymer. The enriched plasma EV was able to be verified by multiple platforms. Our results showed that the particles enriched from plasma by the copolymer were EV size vesicles with membrane structure; proteomic profiling showed that EV-related proteins were significantly enriched, while high-abundant plasma proteins were significantly reduced in comparison to other precipitation-based enrichment methods. Next-generation sequencing confirmed the existence of various RNA species that have been observed in EVs from previous studies. Small RNA sequencing showed enriched species compared to the corresponding plasma. Moreover, plasma EVs enriched from 20 advanced breast cancer patients and 20 age-matched non-cancer controls were profiled by semi-quantitative mass spectrometry. Protein features were further screened by EV proteomic profiles generated from four breast cancer cell lines, and then selected in cross-validation models. A total of 60 protein features that highly contributed in model prediction were identified. Interestingly, a large portion of these features were associated with breast cancer aggression, metastasis as well as invasion, consistent with the advanced clinical stage of the patients. In summary, we have developed a plasma EV enrichment method with improved precipitation

Development of a Physiologically Based Pharmacokinetic Model for Sinogliatin, a First-in-Class Glucokinase Activator, by Integrating Allometric Scaling, In Vitro to In Vivo Exploration and Steady-State Concentration-Mean Residence Time Methods: Mechanistic Understanding of its Pharmacokinetics.

PubMed

Song, Ling; Zhang, Yi; Jiang, Ji; Ren, Shuang; Chen, Li; Liu, Dongyang; Chen, Xijing; Hu, Pei

2018-04-06

The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for sinogliatin (HMS-5552, dorzagliatin) by integrating allometric scaling (AS), in vitro to in vivo exploration (IVIVE), and steady-state concentration-mean residence time (C ss -MRT) methods and to provide mechanistic insight into its pharmacokinetic properties in humans. Human major pharmacokinetic parameters were analyzed using AS, IVIVE, and C ss -MRT methods with available preclinical in vitro and in vivo data to understand sinogliatin drug metabolism and pharmacokinetic (DMPK) characteristics and underlying mechanisms. On this basis, an initial mechanistic PBPK model of sinogliatin was developed. The initial PBPK model was verified using observed data from a single ascending dose (SAD) study and further optimized with various strategies. The final model was validated by simulating sinogliatin pharmacokinetics under a fed condition. The validated model was applied to support a clinical drug-drug interaction (DDI) study design and to evaluate the effects of intrinsic (hepatic cirrhosis, genetic) factors on drug exposure. The two-species scaling method using rat and dog data (TS- rat,dog ) was the best AS method in predicting human systemic clearance in the central compartment (CL). The IVIVE method confirmed that sinogliatin was predominantly metabolized by cytochrome P450 (CYP) 3A4. The C ss -MRT method suggested dog pharmacokinetic profiles were more similar to human pharmacokinetic profiles. The estimated CL using the AS and IVIVE approaches was within 1.5-fold of that observed. The C ss -MRT method in dogs also provided acceptable prediction of human pharmacokinetic characteristics. For the PBPK approach, the 90% confidence intervals (CIs) of the simulated maximum concentration (C max ), CL, and area under the plasma concentration-time curve (AUC) of sinogliatin were within those observed and the 90% CI of simulated time to C max (t max ) was closed to that

Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model.

PubMed

Guan, Li; Hao, Bibo; Cheng, Qijin; Yip, Paul Sf; Zhu, Tingshao

2015-01-01

Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field. The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data. There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric "Screening Efficiency" that were adopted to evaluate model effectiveness. Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30%. Individuals in China with high suicide

Asymmetry of bifurcated features in radio pulsar profiles

NASA Astrophysics Data System (ADS)

Dyks, J.; Rudak, B.

2012-03-01

High-quality integrated radio profiles of some pulsars contain bifurcated, highly symmetric emission components (BECs). They are observed when our line of sight traverses through a split-fan shaped emission beam. It is shown that for oblique cuts through such a beam, the features appear asymmetric at nearly all frequencies, except for a single 'frequency of symmetry'νsym, at which both peaks in the BEC have the same height. Around νsym, the ratio of flux in the two peaks of a BEC evolves in a way resembling the multifrequency behaviour of J1012+5307. Because of the inherent asymmetry resulting from the oblique traverse of the sightline, each minimum in double notches can be modelled independently. Such a composed model reproduces the double notches of B1929+10 if the fitted function is the microscopic beam of curvature radiation in the orthogonal polarization mode. These results confirm our view that some of the double components in radio pulsar profiles directly reveal the microscopic nature of the emitted radiation beam as the microbeam of the curvature radiation polarized orthogonally to the trajectory of electrons.

A global scale mechanistic model of photosynthetic capacity (LUNA V1.0)

DOE PAGES

Ali, Ashehad A.; Xu, Chonggang; Rogers, Alistair; ...

2016-02-12

Although plant photosynthetic capacity as determined by the maximum carboxylation rate (i.e., V c,max25) and the maximum electron transport rate (i.e., J max25) at a reference temperature (generally 25 °C) is known to vary considerably in space and time in response to environmental conditions, it is typically parameterized in Earth system models (ESMs) with tabulated values associated with plant functional types. In this study, we have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA) to predict photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among lightmore » capture, electron transport, carboxylation and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of photosynthetic capacity as it explains ~55 % of the global variation in observed values of V c,max25 and ~65 % of the variation in the observed values of J max25. Model simulations with LUNA under current and future climate conditions demonstrate that modeled values of V c,max25 are most affected in high-latitude regions under future climates. In conclusion, ESMs that relate the values of V c,max25 or J max25 to plant functional types only are likely to substantially overestimate future global photosynthesis.« less

Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

NASA Astrophysics Data System (ADS)

Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

2018-02-01

Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

Clinical features and endocrine profile of Laron syndrome in Indian children.

PubMed

Phanse-Gupte, Supriya R; Khadilkar, Vaman V; Khadilkar, Anuradha V

2014-11-01

Patients with growth hormone (GH) insensitivity (also known as Laron syndome) have been reported from the Mediterranean region and Southern Eucador, with few case reports from India. We present here the clinical and endocrine profile of 9 children with Laron syndrome from India. Nine children diagnosed with Laron syndrome based on clinical features of GH deficiency and biochemical profile suggestive of GH resistance were studied over a period of 5 years from January 2008 to January 2013. Age of presentation was between 2.5-11.5 years. All children were considerably short on contemporary Indian charts with mean (SD) height Z score -5.2 (1.6). However, they were within ± 2 SD on Laron charts. No child was overweight [mean (SD) BMI Z score 0.92 (1.1)]. All children had characteristic facies of GH deficiency with an added feature of prominent eyes. Three boys had micropenis and 1 had unilateral undescended testis. All children had low IGF-1 (<5 percentile) and IGFP-3 (<0.1 percentile) with high basal and stimulated GH [Basal GH mean (SD) = 13.78 (12.75) ng/ml, 1-h stimulated GH mean (SD) = 46.29 (25.68) ng/ml]. All children showed poor response to IGF generation test. Laron syndrome should be suspected in children with clinical features of GH deficiency, high GH levels and low IGF-1/IGFBP-3. These children are in a state of GH resistance and need IGF-1 therapy.

Cross Validated Temperament Scale Validities Computed Using Profile Similarity Metrics

DTIC Science & Technology

2017-04-27

true at both the item and the scale level. 6 Moreover, the correlation between conventional scores and distance scores for these types of scales...have a perfect negative correlation , r = -1.00. From this perspective, conventional and distance scores are completely redundant. Therefore, we argue... correlation between each respondent’s rating profile and the scale key: shape-scores = rx,k. 2. Rating elevation difference, which is computed as the

Local-Scale Simulations of Nucleate Boiling on Micrometer-Featured Surfaces

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

Sitaraman, Hariswaran; Moreno, Gilberto; Narumanchi, Sreekant V

2017-07-12

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulationsmore » pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.« less

Development of feature extraction analysis for a multi-functional optical profiling device applied to field engineering applications

NASA Astrophysics Data System (ADS)

Han, Xu; Xie, Guangping; Laflen, Brandon; Jia, Ming; Song, Guiju; Harding, Kevin G.

2015-05-01

In the real application environment of field engineering, a large variety of metrology tools are required by the technician to inspect part profile features. However, some of these tools are burdensome and only address a sole application or measurement. In other cases, standard tools lack the capability of accessing irregular profile features. Customers of field engineering want the next generation metrology devices to have the ability to replace the many current tools with one single device. This paper will describe a method based on the ring optical gage concept to the measurement of numerous kinds of profile features useful for the field technician. The ring optical system is composed of a collimated laser, a conical mirror and a CCD camera. To be useful for a wide range of applications, the ring optical system requires profile feature extraction algorithms and data manipulation directed toward real world applications in field operation. The paper will discuss such practical applications as measuring the non-ideal round hole with both off-centered and oblique axes. The algorithms needed to analyze other features such as measuring the width of gaps, radius of transition fillets, fall of step surfaces, and surface parallelism will also be discussed in this paper. With the assistance of image processing and geometric algorithms, these features can be extracted with a reasonable performance. Tailoring the feature extraction analysis to this specific gage offers the potential for a wider application base beyond simple inner diameter measurements. The paper will present experimental results that are compared with standard gages to prove the performance and feasibility of the analysis in real world field engineering. Potential accuracy improvement methods, a new dual ring design and future work will be discussed at the end of this paper.

A high-frequency sonar for profiling small-scale subaqueous bedforms

USGS Publications Warehouse

Dingler, J.R.; Boylls, J.C.; Lowe, R.L.

1977-01-01

A high-resolution ultrasonic profiler has been developed which permits both laboratory and field studies of small-scale subaqueous bedforms. The device uses a 2.5-cm diameter piezoelectric ceramic crystal pulsed at a frequency of 4.5 MHz to obtain vertical accuracy and resolution of at least 1 mm. Compared to other small-scale profiling methods, this ultrasonic technique profiles the bottom more accurately and more rapidly without disturbing the bedforms. These characteristics are vital in wave-dominated nearshore zones where oscillatory flow and low visibility for the most part have stymied detailed bedform studies. In the laboratory the transducer is mounted directly to an instrument carriage. For field work the transducer housing is mounted in a 2 m long aluminum frame which is situated and operated by scuba divers. Observations using the device include ripple geometry and migration, the suspension height of sand during sheet flow, and long-term erosion/deposition at a point. ?? 1977.

Individual Distinctive Features of Self-Regulation Processes Peculiar to Students of Different Profiles of Lateral Organization

ERIC Educational Resources Information Center

Korneeva, Svetlana A.; Zherebnenko, Oksana A.; Mukhamedzyanova, Flera G.; Moskalenko, Svetlana V.; Gorelikova, Olga N.

2016-01-01

The research paper presents an analysis of the interrelation between the lateral organisation profiles' indicators and self-regulation features. The existence of significant distinctions in the processes of self-regulation among respondents with different variants of lateral profiles of the interhemispheric asymmetry is proved, as well as the…

Clinical features and endocrine profile of Laron syndrome in Indian children

PubMed Central

Phanse-Gupte, Supriya R.; Khadilkar, Vaman V.; Khadilkar, Anuradha V.

2014-01-01

Introduction: Patients with growth hormone (GH) insensitivity (also known as Laron syndome) have been reported from the Mediterranean region and Southern Eucador, with few case reports from India. We present here the clinical and endocrine profile of 9 children with Laron syndrome from India. Material and Methods: Nine children diagnosed with Laron syndrome based on clinical features of GH deficiency and biochemical profile suggestive of GH resistance were studied over a period of 5 years from January 2008 to January 2013. Results and Discussion: Age of presentation was between 2.5-11.5 years. All children were considerably short on contemporary Indian charts with mean (SD) height Z score -5.2 (1.6). However, they were within ± 2 SD on Laron charts. No child was overweight [mean (SD) BMI Z score 0.92 (1.1)]. All children had characteristic facies of GH deficiency with an added feature of prominent eyes. Three boys had micropenis and 1 had unilateral undescended testis. All children had low IGF-1 (<5 percentile) and IGFP-3 (<0.1 percentile) with high basal and stimulated GH [Basal GH mean (SD) = 13.78 (12.75) ng/ml, 1-h stimulated GH mean (SD) = 46.29 (25.68) ng/ml]. All children showed poor response to IGF generation test. Conclusion: Laron syndrome should be suspected in children with clinical features of GH deficiency, high GH levels and low IGF-1/IGFBP-3. These children are in a state of GH resistance and need IGF-1 therapy. PMID:25364685

Screening for prenatal substance use: development of the Substance Use Risk Profile-Pregnancy scale.

PubMed

Yonkers, Kimberly A; Gotman, Nathan; Kershaw, Trace; Forray, Ariadna; Howell, Heather B; Rounsaville, Bruce J

2010-10-01

To report on the development of a questionnaire to screen for hazardous substance use in pregnant women and to compare the performance of the questionnaire with other drug and alcohol measures. Pregnant women were administered a modified TWEAK (Tolerance, Worried, Eye-openers, Amnesia, K[C] Cut Down) questionnaire, the 4Ps Plus questionnaire, items from the Addiction Severity Index, and two questions about domestic violence (N=2,684). The sample was divided into "training" (n=1,610) and "validation" (n=1,074) subsamples. We applied recursive partitioning class analysis to the responses from individuals in the training subsample that resulted in a three-item Substance Use Risk Profile-Pregnancy scale. We examined sensitivity, specificity, and the fit of logistic regression models in the validation subsample to compare the performance of the Substance Use Risk Profile-Pregnancy scale with the modified TWEAK and various scoring algorithms of the 4Ps. The Substance Use Risk Profile-Pregnancy scale is comprised of three informative questions that can be scored for high- or low-risk populations. The Substance Use Risk Profile-Pregnancy scale algorithm for low-risk populations was mostly highly predictive of substance use in the validation subsample (Akaike's Information Criterion=579.75, Nagelkerke R=0.27) with high sensitivity (91%) and adequate specificity (67%). The high-risk algorithm had lower sensitivity (57%) but higher specificity (88%). The Substance Use Risk Profile-Pregnancy scale is simple and flexible with good sensitivity and specificity. The Substance Use Risk Profile-Pregnancy scale can potentially detect a range of substances that may be abused. Clinicians need to further assess women with a positive screen to identify those who require treatment for alcohol or illicit substance use in pregnancy. III.

FEATURE 1, SMALL GUN POSITION, VIEW FACING NORTH, (with scale ...

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

FEATURE 1, SMALL GUN POSITION, VIEW FACING NORTH, (with scale stick). - Naval Air Station Barbers Point, Anti-Aircraft Battery Complex-Small Gun Position, East of Coral Sea Road, northwest of Hamilton Road, Ewa, Honolulu County, HI

FEATURE 2, SHELTER, NORTHNORTHEAST SIDE, VIEW FACING SOUTHSOUTHWEST (with scale ...

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

FEATURE 2, SHELTER, NORTH-NORTHEAST SIDE, VIEW FACING SOUTH-SOUTHWEST (with scale stick). - Naval Air Station Barbers Point, Anti-Aircraft Battery Complex-Shelter, East of Coral Sea Road, northwest of Hamilton Road, Ewa, Honolulu County, HI

Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model

PubMed Central

Guan, Li; Hao, Bibo; Cheng, Qijin; Yip, Paul SF

2015-01-01

Background Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field. Objective The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data. Methods There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric “Screening Efficiency” that were adopted to evaluate model effectiveness. Results Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30

Coupling machine learning with mechanistic models to study runoff production and river flow at the hillslope scale

NASA Astrophysics Data System (ADS)

Marçais, J.; Gupta, H. V.; De Dreuzy, J. R.; Troch, P. A. A.

2016-12-01

Geomorphological structure and geological heterogeneity of hillslopes are major controls on runoff responses. The diversity of hillslopes (morphological shapes and geological structures) on one hand, and the highly non linear runoff mechanism response on the other hand, make it difficult to transpose what has been learnt at one specific hillslope to another. Therefore, making reliable predictions on runoff appearance or river flow for a given hillslope is a challenge. Applying a classic model calibration (based on inverse problems technique) requires doing it for each specific hillslope and having some data available for calibration. When applied to thousands of cases it cannot always be promoted. Here we propose a novel modeling framework based on coupling process based models with data based approach. First we develop a mechanistic model, based on hillslope storage Boussinesq equations (Troch et al. 2003), able to model non linear runoff responses to rainfall at the hillslope scale. Second we set up a model database, representing thousands of non calibrated simulations. These simulations investigate different hillslope shapes (real ones obtained by analyzing 5m digital elevation model of Brittany and synthetic ones), different hillslope geological structures (i.e. different parametrizations) and different hydrologic forcing terms (i.e. different infiltration chronicles). Then, we use this model library to train a machine learning model on this physically based database. Machine learning model performance is then assessed by a classic validating phase (testing it on new hillslopes and comparing machine learning with mechanistic outputs). Finally we use this machine learning model to learn what are the hillslope properties controlling runoffs. This methodology will be further tested combining synthetic datasets with real ones.

Selective attention to temporal features on nested time scales.

PubMed

Henry, Molly J; Herrmann, Björn; Obleser, Jonas

2015-02-01

Meaningful auditory stimuli such as speech and music often vary simultaneously along multiple time scales. Thus, listeners must selectively attend to, and selectively ignore, separate but intertwined temporal features. The current study aimed to identify and characterize the neural network specifically involved in this feature-selective attention to time. We used a novel paradigm where listeners judged either the duration or modulation rate of auditory stimuli, and in which the stimulation, working memory demands, response requirements, and task difficulty were held constant. A first analysis identified all brain regions where individual brain activation patterns were correlated with individual behavioral performance patterns, which thus supported temporal judgments generically. A second analysis then isolated those brain regions that specifically regulated selective attention to temporal features: Neural responses in a bilateral fronto-parietal network including insular cortex and basal ganglia decreased with degree of change of the attended temporal feature. Critically, response patterns in these regions were inverted when the task required selectively ignoring this feature. The results demonstrate how the neural analysis of complex acoustic stimuli with multiple temporal features depends on a fronto-parietal network that simultaneously regulates the selective gain for attended and ignored temporal features. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Local-Scale Simulations of Nucleate Boiling on Micrometer Featured Surfaces: Preprint

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

Sitaraman, Hariswaran; Moreno, Gilberto; Narumanchi, Sreekant V

2017-08-03

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulationsmore » pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.« less

Decoding the spectroscopic features and time scales of aqueous proton defects

NASA Astrophysics Data System (ADS)

Napoli, Joseph A.; Marsalek, Ondrej; Markland, Thomas E.

2018-06-01

Acid solutions exhibit a variety of complex structural and dynamical features arising from the presence of multiple interacting reactive proton defects and counterions. However, disentangling the transient structural motifs of proton defects in the water hydrogen bond network and the mechanisms for their interconversion remains a formidable challenge. Here, we use simulations treating the quantum nature of both the electrons and nuclei to show how the experimentally observed spectroscopic features and relaxation time scales can be elucidated using a physically transparent coordinate that encodes the overall asymmetry of the solvation environment of the proton defect. We demonstrate that this coordinate can be used both to discriminate the extremities of the features observed in the linear vibrational spectrum and to explain the molecular motions that give rise to the interconversion time scales observed in recent nonlinear experiments. This analysis provides a unified condensed-phase picture of the proton structure and dynamics that, at its extrema, encompasses proton sharing and spectroscopic features resembling the limiting Eigen [H3O(H2O)3]+ and Zundel [H(H2O)2]+ gas-phase structures, while also describing the rich variety of interconverting environments in the liquid phase.

Fabrication of small-scale structures with non-planar features

DOEpatents

Burckel, David B.; Ten Eyck, Gregory A.

2015-11-19

The fabrication of small-scale structures is disclosed. A unit-cell of a small-scale structure with non-planar features is fabricated by forming a membrane on a suitable material. A pattern is formed in the membrane and a portion of the substrate underneath the membrane is removed to form a cavity. Resonators are then directionally deposited on the wall or sides of the cavity. The cavity may be rotated during deposition to form closed-loop resonators. The resonators may be non-planar. The unit-cells can be formed in a layer that includes an array of unit-cells.

Mechanistic Drifting Forecast Model for A Small Semi-Submersible Drifter Under Tide-Wind-Wave Conditions

NASA Astrophysics Data System (ADS)

Zhang, Wei-Na; Huang, Hui-ming; Wang, Yi-gang; Chen, Da-ke; Zhang, lin

2018-03-01

Understanding the drifting motion of a small semi-submersible drifter is of vital importance regarding monitoring surface currents and the floating pollutants in coastal regions. This work addresses this issue by establishing a mechanistic drifting forecast model based on kinetic analysis. Taking tide-wind-wave into consideration, the forecast model is validated against in situ drifting experiment in the Radial Sand Ridges. Model results show good performance with respect to the measured drifting features, characterized by migrating back and forth twice a day with daily downwind displacements. Trajectory models are used to evaluate the influence of the individual hydrodynamic forcing. The tidal current is the fundamental dynamic condition in the Radial Sand Ridges and has the greatest impact on the drifting distance. However, it loses its leading position in the field of the daily displacement of the used drifter. The simulations reveal that different hydrodynamic forces dominate the daily displacement of the used drifter at different wind scales. The wave-induced mass transport has the greatest influence on the daily displacement at Beaufort wind scale 5-6; while wind drag contributes mostly at wind scale 2-4.

Scaling laws and vortex profiles in two-dimensional decaying turbulence.

PubMed

Laval, J P; Chavanis, P H; Dubrulle, B; Sire, C

2001-06-01

We use high resolution numerical simulations over several hundred of turnover times to study the influence of small scale dissipation onto vortex statistics in 2D decaying turbulence. A scaling regime is detected when the scaling laws are expressed in units of mean vorticity and integral scale, like predicted in Carnevale et al., Phys. Rev. Lett. 66, 2735 (1991), and it is observed that viscous effects spoil this scaling regime. The exponent controlling the decay of the number of vortices shows some trends toward xi=1, in agreement with a recent theory based on the Kirchhoff model [C. Sire and P. H. Chavanis, Phys. Rev. E 61, 6644 (2000)]. In terms of scaled variables, the vortices have a similar profile with a functional form related to the Fermi-Dirac distribution.

An improved KCF tracking algorithm based on multi-feature and multi-scale

NASA Astrophysics Data System (ADS)

Wu, Wei; Wang, Ding; Luo, Xin; Su, Yang; Tian, Weiye

2018-02-01

The purpose of visual tracking is to associate the target object in a continuous video frame. In recent years, the method based on the kernel correlation filter has become the research hotspot. However, the algorithm still has some problems such as video capture equipment fast jitter, tracking scale transformation. In order to improve the ability of scale transformation and feature description, this paper has carried an innovative algorithm based on the multi feature fusion and multi-scale transform. The experimental results show that our method solves the problem that the target model update when is blocked or its scale transforms. The accuracy of the evaluation (OPE) is 77.0%, 75.4% and the success rate is 69.7%, 66.4% on the VOT and OTB datasets. Compared with the optimal one of the existing target-based tracking algorithms, the accuracy of the algorithm is improved by 6.7% and 6.3% respectively. The success rates are improved by 13.7% and 14.2% respectively.

Feature-Based Statistical Analysis of Combustion Simulation Data

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

Bennett, J; Krishnamoorthy, V; Liu, S

2011-11-18

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing andmore » reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for

A scale space feature based registration technique for fusion of satellite imagery

NASA Technical Reports Server (NTRS)

Raghavan, Srini; Cromp, Robert F.; Campbell, William C.

1997-01-01

Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.

Mechanistic Probes of Zeolitic Imidazolate Framework for Photocatalytic Application

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

Pattengale, Brian; Yang, Sizhuo; Lee, Sungsik

2017-11-07

In this work, we report a zeolitic imidazolate framework (ZIF-67) with remarkable activity for hydrogen evolution reaction (HER) of 40,500 μmol H2/g MOF, which is, to the best of our knowledge, the highest activity achieved by any MOF system. This result necessitated assessment of its atomic-scale mechanistic function for HER using advanced spectroscopy techniques including time-resolved optical (OTA) and in situ X-ray absorption (XAS) spectroscopy. Through the correlation of OTA results with catalytic performance, we demonstrated that the electron transfer (ET) rather than energy transfer (ENT) pathway between photosensitizer and ZIF-67 is the key factor that controls the efficiency ofmore » HER activity, as HER activity that undergoes ET pathway is 3 orders of magnitude higher than that of ENT process. Using in situ XAS, we unraveled the spectral features for key intermediate species which are likely responsible for the rate determining process under turn over conditions. This work represents an original approach to study porous ZIF materials at the molecular level using advanced spectroscopic techniques, providing unprecedented insights into the photoactive nature of ZIF frameworks.« less

Unsupervised Pattern Classifier for Abnormality-Scaling of Vibration Features for Helicopter Gearbox Fault Diagnosis

NASA Technical Reports Server (NTRS)

Jammu, Vinay B.; Danai, Kourosh; Lewicki, David G.

1996-01-01

A new unsupervised pattern classifier is introduced for on-line detection of abnormality in features of vibration that are used for fault diagnosis of helicopter gearboxes. This classifier compares vibration features with their respective normal values and assigns them a value in (0, 1) to reflect their degree of abnormality. Therefore, the salient feature of this classifier is that it does not require feature values associated with faulty cases to identify abnormality. In order to cope with noise and changes in the operating conditions, an adaptation algorithm is incorporated that continually updates the normal values of the features. The proposed classifier is tested using experimental vibration features obtained from an OH-58A main rotor gearbox. The overall performance of this classifier is then evaluated by integrating the abnormality-scaled features for detection of faults. The fault detection results indicate that the performance of this classifier is comparable to the leading unsupervised neural networks: Kohonen's Feature Mapping and Adaptive Resonance Theory (AR72). This is significant considering that the independence of this classifier from fault-related features makes it uniquely suited to abnormality-scaling of vibration features for fault diagnosis.

Continuously distributed magnetization profile for millimeter-scale elastomeric undulatory swimming

NASA Astrophysics Data System (ADS)

Diller, Eric; Zhuang, Jiang; Zhan Lum, Guo; Edwards, Matthew R.; Sitti, Metin

2014-04-01

We have developed a millimeter-scale magnetically driven swimming robot for untethered motion at mid to low Reynolds numbers. The robot is propelled by continuous undulatory deformation, which is enabled by the distributed magnetization profile of a flexible sheet. We demonstrate control of a prototype device and measure deformation and speed as a function of magnetic field strength and frequency. Experimental results are compared with simple magnetoelastic and fluid propulsion models. The presented mechanism provides an efficient remote actuation method at the millimeter scale that may be suitable for further scaling down in size for micro-robotics applications in biotechnology and healthcare.

Mechanistic Lake Modeling to Understand and Predict Heterogeneous Responses to Climate Warming

NASA Astrophysics Data System (ADS)

Read, J. S.; Winslow, L. A.; Rose, K. C.; Hansen, G. J.

2016-12-01

Substantial warming has been documented for of hundreds globally distributed lakes, with likely impacts on ecosystem processes. Despite a clear pattern of widespread warming, thermal responses of individual lakes to climate change are often heterogeneous, with the warming rates of neighboring lakes varying across depths and among seasons. We aggregated temperature observations and parameterized mechanistic models for 9,000 lakes in the U.S. states of Minnesota, Wisconsin, and Michigan to examine broad-scale lake warming trends and among-lake diversity. Daily lake temperature profiles and ice-cover dynamics were simulated using the General Lake Model for the contemporary period (1979-2015) using drivers from the North American Land Data Assimilation System (NLDAS-2) and for contemporary and future periods (1980-2100) using downscaled data from six global circulation models driven by the Representative Climate Pathway 8.5 scenario. For the contemporary period, modeled vs observed summer mean surface temperatures had a root mean squared error of 0.98°C with modeled warming trends similar to observed trends. Future simulations under the extreme 8.5 scenario predicted a median lake summer surface warming rate of 0.57°C/decade until mid-century, with slower rates in the later half of the 21st century (0.35°C/decade). Modeling scenarios and analysis of field data suggest that the lake-specific properties of size, water clarity, and depth are strong controls on the sensitivity of lakes to climate change. For example, a simulated 1% annual decline in water clarity was sufficient to override the effects of climate warming on whole lake water temperatures in some - but not all - study lakes. Understanding heterogeneous lake responses to climate variability can help identify lake-specific features that influence resilience to climate change.

Scaling of confinement and profiles in the EXTRAP T2 reversed-field pinch

NASA Astrophysics Data System (ADS)

Welander, A.

1999-01-01

In the EXTRAP T2 reversed-field pinch the diagnostic techniques for the measurement of electron density and temperature include; Thomson scattering which gives values at three radial positions in the core (r/a = 0, 0.28, 0.56), Langmuir probes which give values at the edge (r/a > 0.9) and interferometry which gives a line-averaged density. The empirical scaling of electron density and temperature including profile information with global plasma parameters has been studied. The density profile is subject to large variations, with an average parabolic shape when the density is low and flatter shapes when the density is increased. The change in the profile shape can be attributed to a shift in the penetration length of neutrals from the vicinity of the wall. The temperature scales roughly as I/n1/2 where I is the plasma current and n is the density. The temperature profile is always quite flat with lower variations and there is a tendency for a flatter profile at higher temperatures.

A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism.

PubMed

Mih, Nathan; Brunk, Elizabeth; Bordbar, Aarash; Palsson, Bernhard O

2016-07-01

Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein's structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism.

Thermal Analysis of Unusual Local-scale Features on the Surface of Vesta

NASA Technical Reports Server (NTRS)

Tosi, F.; Capria, M. T.; DeSanctis, M. C.; Capaccioni, F.; Palomba, E.; Zambon, F.; Ammannito, E.; Blewett, D. T.; Combe, J.-Ph.; Denevi, B. W.;

Genome-scale approaches to the epigenetics of common human disease

PubMed Central

2011-01-01

Traditionally, the pathology of human disease has been focused on microscopic examination of affected tissues, chemical and biochemical analysis of biopsy samples, other available samples of convenience, such as blood, and noninvasive or invasive imaging of varying complexity, in order to classify disease and illuminate its mechanistic basis. The molecular age has complemented this armamentarium with gene expression arrays and selective analysis of individual genes. However, we are entering a new era of epigenomic profiling, i.e., genome-scale analysis of cell-heritable nonsequence genetic change, such as DNA methylation. The epigenome offers access to stable measurements of cellular state and to biobanked material for large-scale epidemiological studies. Some of these genome-scale technologies are beginning to be applied to create the new field of epigenetic epidemiology. PMID:19844740

Whole-body iron transport and metabolism: Mechanistic, multi-scale model to improve treatment of anemia in chronic kidney disease

PubMed Central

Sarkar, Joydeep

2018-01-01

Iron plays vital roles in the human body including enzymatic processes, oxygen-transport via hemoglobin and immune response. Iron metabolism is characterized by ~95% recycling and minor replenishment through diet. Anemia of chronic kidney disease (CKD) is characterized by a lack of synthesis of erythropoietin leading to reduced red blood cell (RBC) formation and aberrant iron recycling. Treatment of CKD anemia aims to normalize RBC count and serum hemoglobin. Clinically, the various fluxes of iron transport and accumulation are not measured so that changes during disease (e.g., CKD) and treatment are unknown. Unwanted iron accumulation in patients is known to lead to adverse effects. Current whole-body models lack the mechanistic details of iron transport related to RBC maturation, transferrin (Tf and TfR) dynamics and assume passive iron efflux from macrophages. Hence, they are not predictive of whole-body iron dynamics and cannot be used to design individualized patient treatment. For prediction, we developed a mechanistic, multi-scale computational model of whole-body iron metabolism incorporating four compartments containing major pools of iron and RBC generation process. The model accounts for multiple forms of iron in vivo, mechanisms involved in iron uptake and release and their regulation. Furthermore, the model is interfaced with drug pharmacokinetics to allow simulation of treatment dynamics. We calibrated our model with experimental and clinical data from peer-reviewed literature to reliably simulate CKD anemia and the effects of current treatment involving combination of epoietin-alpha and iron dextran. This in silico whole-body model of iron metabolism predicts that a year of treatment can potentially lead to 90% downregulation of ferroportin (FPN) levels, 15-fold increase in iron stores with only a 20% increase in iron flux from the reticulo-endothelial system (RES). Model simulations quantified unmeasured iron fluxes, previously unknown effects of

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http

Gene Profiling in Experimental Models of Eye Growth: Clues to Myopia Pathogenesis

PubMed Central

Stone, Richard A.; Khurana, Tejvir S.

2010-01-01

To understand the complex regulatory pathways that underlie the development of refractive errors, expression profiling has evaluated gene expression in ocular tissues of well-characterized experimental models that alter postnatal eye growth and induce refractive errors. Derived from a variety of platforms (e.g. differential display, spotted microarrays or Affymetrix GeneChips), gene expression patterns are now being identified in species that include chicken, mouse and primate. Reconciling available results is hindered by varied experimental designs and analytical/statistical features. Continued application of these methods offers promise to provide the much-needed mechanistic framework to develop therapies to normalize refractive development in children. PMID:20363242

Application of a mechanistic model as a tool for on-line monitoring of pilot scale filamentous fungal fermentation processes-The importance of evaporation effects.

PubMed

Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Sin, Gürkan; Gernaey, Krist V

2017-03-01

A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate, dissolved oxygen and mass, as well as other process parameters including k L a, viscosity and partial pressure of CO 2 . State estimation at this scale requires a robust mass model including evaporation, which is a factor not often considered at smaller scales of operation. The model is developed using a historical data set of 11 batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on 14 new batches utilizing a new strain. The product concentration in the validation batches was predicted with an average root mean sum of squared error (RMSSE) of 16.6%. In addition, calculation of the Janus coefficient for the validation batches shows a suitably calibrated model. The robustness of the model prediction is assessed with respect to the accuracy of the input data. Parameter estimation uncertainty is also carried out. The application of this on-line state estimator allows for on-line monitoring of pilot scale batches, including real-time estimates of multiple parameters which are not able to be monitored on-line. With successful application of a soft sensor at this scale, this allows for improved process monitoring, as well as opening up further possibilities for on-line control algorithms, utilizing these on-line model outputs

Kilometer-Scale Topographic Roughness of Mercury: Correlation with Geologic Features and Units

NASA Technical Reports Server (NTRS)

Kreslavsky, Mikhail A.; Head, James W.; Neumann, Gregory A.; Zuber, Maria T.; Smith, David E.

2014-01-01

We present maps of the topographic roughness of the northern circumpolar area of Mercury at kilometer scales. The maps are derived from range profiles obtained by the Mercury Laser Altimeter (MLA) instrument onboard the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission. As measures of roughness, we used the interquartile range of profile curvature at three baselines: 0.7 kilometers, 2.8 kilometers, and 11 kilometers. The maps provide a synoptic overview of variations of typical topographic textures. They show a dichotomy between the smooth northern plains and rougher, more heavily cratered terrains. Analysis of the scale dependence of roughness indicates that the regolith on Mercury is thicker than on the Moon by approximately a factor of three. Roughness contrasts within northern volcanic plains of Mercury indicate a younger unit inside Goethe basin and inside another unnamed stealth basin. These new data permit interplanetary comparisons of topographic roughness.

Supporting Mechanistic Reasoning in Domain-Specific Contexts

ERIC Educational Resources Information Center

Weinberg, Paul J.

2017-01-01

Mechanistic reasoning is an epistemic practice central within science, technology, engineering, and mathematics disciplines. Although there has been some work on mechanistic reasoning in the research literature and standards documents, much of this work targets domain-general characterizations of mechanistic reasoning; this study provides…

Subsynoptic-scale features associated with extreme surface gusts in UK extratropical cyclone events

NASA Astrophysics Data System (ADS)

Earl, N.; Dorling, S.; Starks, M.; Finch, R.

2017-04-01

Numerous studies have addressed the mesoscale features within extratropical cyclones (ETCs) that are responsible for the most destructive winds, though few have utilized surface observation data, and most are based on case studies. By using a 39-station UK surface observation network, coupled with in-depth analysis of the causes of extreme gusts during the period 2008-2014, we show that larger-scale features (warm and cold conveyer belts) are most commonly associated with the top 1% of UK gusts but smaller-scale features generate the most extreme winds. The cold conveyor belt is far more destructive when joining the momentum of the ETC, rather than earlier in its trajectory, ahead of the approaching warm front. Sting jets and convective lines account for two thirds of severe surface gusts in the UK.

Whole-genome phylogeny of Escherichia coli/Shigella group by feature frequency profiles (FFPs)

PubMed Central

Sims, Gregory E.; Kim, Sung-Hou

2011-01-01

A whole-genome phylogeny of the Escherichia coli/Shigella group was constructed by using the feature frequency profile (FFP) method. This alignment-free approach uses the frequencies of l-mer features of whole genomes to infer phylogenic distances. We present two phylogenies that accentuate different aspects of E. coli/Shigella genomic evolution: (i) one based on the compositions of all possible features of length l = 24 (∼8.4 million features), which are likely to reveal the phenetic grouping and relationship among the organisms and (ii) the other based on the compositions of core features with low frequency and low variability (∼0.56 million features), which account for ∼69% of all commonly shared features among 38 taxa examined and are likely to have genome-wide lineal evolutionary signal. Shigella appears as a single clade when all possible features are used without filtering of noncore features. However, results using core features show that Shigella consists of at least two distantly related subclades, implying that the subclades evolved into a single clade because of a high degree of convergence influenced by mobile genetic elements and niche adaptation. In both FFP trees, the basal group of the E. coli/Shigella phylogeny is the B2 phylogroup, which contains primarily uropathogenic strains, suggesting that the E. coli/Shigella ancestor was likely a facultative or opportunistic pathogen. The extant commensal strains diverged relatively late and appear to be the result of reductive evolution of genomes. We also identify clade distinguishing features and their associated genomic regions within each phylogroup. Such features may provide useful information for understanding evolution of the groups and for quick diagnostic identification of each phylogroup. PMID:21536867

Train axle bearing fault detection using a feature selection scheme based multi-scale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin

2018-02-01

This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.

On the scaling features of high-latitude geomagnetic field fluctuations during a large geomagnetic storm

NASA Astrophysics Data System (ADS)

De Michelis, Paola; Federica Marcucci, Maria; Consolini, Giuseppe

2015-04-01

Recently we have investigated the spatial distribution of the scaling features of short-time scale magnetic field fluctuations using measurements from several ground-based geomagnetic observatories distributed in the northern hemisphere. We have found that the scaling features of fluctuations of the horizontal magnetic field component at time scales below 100 minutes are correlated with the geomagnetic activity level and with changes in the currents flowing in the ionosphere. Here, we present a detailed analysis of the dynamical changes of the magnetic field scaling features as a function of the geomagnetic activity level during the well-known large geomagnetic storm occurred on July, 15, 2000 (the Bastille event). The observed dynamical changes are discussed in relationship with the changes of the overall ionospheric polar convection and potential structure as reconstructed using SuperDARN data. This work is supported by the Italian National Program for Antarctic Research (PNRA) - Research Project 2013/AC3.08 and by the European Community's Seventh Framework Programme ([FP7/2007-2013]) under Grant no. 313038/STORM and

An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images

NASA Astrophysics Data System (ADS)

Bhardwaj, Kaushal; Patra, Swarnajyoti

2018-04-01

Inclusion of spatial information along with spectral features play a significant role in classification of remote sensing images. Attribute profiles have already proved their ability to represent spatial information. In order to incorporate proper spatial information, multiple attributes are required and for each attribute large profiles need to be constructed by varying the filter parameter values within a wide range. Thus, the constructed profiles that represent spectral-spatial information of an hyperspectral image have huge dimension which leads to Hughes phenomenon and increases computational burden. To mitigate these problems, this work presents an unsupervised feature selection technique that selects a subset of filtered image from the constructed high dimensional multi-attribute profile which are sufficiently informative to discriminate well among classes. In this regard the proposed technique exploits genetic algorithms (GAs). The fitness function of GAs are defined in an unsupervised way with the help of mutual information. The effectiveness of the proposed technique is assessed using one-against-all support vector machine classifier. The experiments conducted on three hyperspectral data sets show the robustness of the proposed method in terms of computation time and classification accuracy.

A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism

PubMed Central

Bordbar, Aarash; Palsson, Bernhard O.

2016-01-01

Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein’s structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism. PMID:27467583

Fabrication method for small-scale structures with non-planar features

DOEpatents

Burckel, David Bruce; Ten Eyck, Gregory A.

2016-09-20

The fabrication of small-scale structures is disclosed. A unit-cell of a small-scale structure with non-planar features is fabricated by forming a membrane on a suitable material. A pattern is formed in the membrane and a portion of the substrate underneath the membrane is removed to form a cavity. Resonators are then directionally deposited on the wall or sides of the cavity. The cavity may be rotated during deposition to form closed-loop resonators. The resonators may be non-planar. The unit-cells can be formed in a layer that includes an array of unit-cells.

Kilometer-scale topographic roughness of Mercury: Correlation with geologic features and units

NASA Astrophysics Data System (ADS)

Kreslavsky, Mikhail A.; Head, James W.; Neumann, Gregory A.; Zuber, Maria T.; Smith, David E.

2014-12-01

We present maps of the topographic roughness of the northern circumpolar area of 30 Mercury at kilometer scales. The maps are derived from range profiles obtained by the 31 Mercury Laser Altimeter (MLA) instrument onboard the MErcury Surface, Space 32 ENvironment, Geochemistry, and Ranging (MESSENGER) mission. As measures of 33 roughness, we used the interquartile range of profile curvature at three baselines: 0.7 km, 34 2.8 km, and 11 km. The maps provide a synoptic overview of variations of typical 35 topographic textures. They show a dichotomy between the smooth northern plains and 36 rougher, more heavily cratered terrains. Analysis of the scale dependence of roughness 37 indicates that the regolith on Mercury is thicker than on the Moon by approximately a 38 factor of three. Roughness contrasts within northern volcanic plains of Mercury indicate a 39 younger unit inside Goethe basin and inside another unnamed stealth basin. These new 40 data permit interplanetary comparisons of topographic roughness.

Mechanistic-empirical Pavement Design Guide Implementation

DOT National Transportation Integrated Search

2010-06-01

The recently introduced Mechanistic-Empirical Pavement Design Guide (MEPDG) and associated computer software provides a state-of-practice mechanistic-empirical highway pavement design methodology. The MEPDG methodology is based on pavement responses ...

Nanometer-scale features in dolomite from Pennsylvanian rocks, Paradox Basin, Utah

NASA Astrophysics Data System (ADS)

Gournay, Jonas P.; Kirkland, Brenda L.; Folk, Robert L.; Lynch, F. Leo

1999-07-01

Scanning electron microscopy reveals an association between early dolomite in the Pennsylvanian Desert Creek (Paradox Fm.) and small (approximately 0.1 μm) nanometer-scale textures, termed `nannobacteria'. Three diagenetically distinct dolomites are present: early dolomite, limpid dolomite, and baroque dolomite. In this study, only the early dolomite contained nanometer-scale features. These textures occur as discrete balls and rods, clumps of balls, and chains of balls. Precipitation experiments demonstrate that these textures may be the result of precipitation in an organic-rich micro-environment. The presence of these nanometer-scale textures in Pennsylvanian rocks suggests that these early dolomites precipitated in organic-rich, bacterial environments.

Assessing uncertainty in mechanistic models

Treesearch

Edwin J. Green; David W. MacFarlane; Harry T. Valentine

2000-01-01

Concern over potential global change has led to increased interest in the use of mechanistic models for predicting forest growth. The rationale for this interest is that empirical models may be of limited usefulness if environmental conditions change. Intuitively, we expect that mechanistic models, grounded as far as possible in an understanding of the biology of tree...

Profiles of Teacher-Child Interaction Quality in Preschool Classrooms and Teachers' Professional Competence Features

ERIC Educational Resources Information Center

Hu, Bi Ying; Chen, Liang; Fan, Xitao

2018-01-01

This paper investigates early childhood education (ECE) teachers' self-reported and observed teacher-child interaction quality (TIQ) and the associated teachers' professional competence features using a latent profile analysis (LPA) approach to identify the variations in the quality of classroom experiences in Chinese preschools. A total of 164…

Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity

PubMed Central

Fjodorova, Natalja; Novič, Marjana

2012-01-01

The knowledge-based Toxtree expert system (SAR approach) was integrated with the statistically based counter propagation artificial neural network (CP ANN) model (QSAR approach) to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs) for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats) within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals. PMID:24688639

Development of a Mechanistically Based, Basin-Scale Stream Temperature Model: Applications to Cumulative Effects Modeling

Treesearch

Douglas Allen; William Dietrich; Peter Baker; Frank Ligon; Bruce Orr

2007-01-01

We describe a mechanistically-based stream model, BasinTemp, which assumes that direct shortwave radiation moderated by riparian and topographic shading, controls stream temperatures during the hottest part of the year. The model was developed to support a temperature TMDL for the South Fork Eel basin in Northern California and couples a GIS and a 1-D energy balance...

Computational Modeling of Multi-Scale Material Features in Cement Paste - An Overview

DTIC Science & Technology

2015-05-25

and concrete ; though commonly used are one of the most complex in terms of material morphology and structure than most materials, for example...across the multiple scales are required. In this paper, recent work from our research group on the nano to continuum level modeling of cementitious...of our research work consisting of, • Molecular Dynamics (MD) modeling for the nano scale features of the cementitious material chemistry. • Micro

Assessment of Borderline Personality Features in Population Samples: Is the Personality Assessment Inventory-Borderline Features Scale Measurement Invariant across Sex and Age?

ERIC Educational Resources Information Center

De Moor, Marleen H. M.; Distel, Marijn A.; Trull, Timothy J.; Boomsma, Dorret I.

2009-01-01

Borderline personality disorder (BPD) is more often diagnosed in women than in men, and symptoms tend to decline with age. Using a large community sample, the authors investigated whether sex and age differences in four main features of BPD, measured with the "Personality Assessment Inventory-Borderline Features" scale (PAI-BOR; Morey,…

Form drag in rivers due to small-scale natural topographic features: 1. Regular sequences

USGS Publications Warehouse

Kean, J.W.; Smith, J.D.

2006-01-01

Small-scale topographic features are commonly found on the boundaries of natural rivers, streams, and floodplains. A simple method for determining the form drag on these features is presented, and the results of this model are compared to laboratory measurements. The roughness elements are modeled as Gaussian-shaped features defined in terms of three parameters: a protrusion height, H; a streamwise length scale, ??; and a spacing between crests, ??. This shape is shown to be a good approximation to a wide variety of natural topographic bank features. The form drag on an individual roughness element embedded in a series of identical elements is determined using the drag coefficient of the individual element and a reference velocity that includes the effects of roughness elements further upstream. In addition to calculating the drag on each element, the model determines the spatially averaged total stress, skin friction stress, and roughness height of the boundary. The effects of bank roughness on patterns of velocity and boundary shear stress are determined by combining the form drag model with a channel flow model. The combined model shows that drag on small-scale topographic features substantially alters the near-bank flow field. These methods can be used to improve predictions of flow resistance in rivers and to form the basis for fully predictive (no empirically adjusted parameters) channel flow models. They also provide a foundation for calculating the near-bank boundary shear stress fields necessary for determining rates of sediment transport and lateral erosion.

Mechanistic species distribution modeling reveals a niche shift during invasion.

PubMed

Chapman, Daniel S; Scalone, Romain; Štefanić, Edita; Bullock, James M

2017-06-01

Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern-origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual

Rational and mechanistic perspectives on reinforcement learning.

PubMed

Chater, Nick

2009-12-01

This special issue describes important recent developments in applying reinforcement learning models to capture neural and cognitive function. But reinforcement learning, as a theoretical framework, can apply at two very different levels of description: mechanistic and rational. Reinforcement learning is often viewed in mechanistic terms--as describing the operation of aspects of an agent's cognitive and neural machinery. Yet it can also be viewed as a rational level of description, specifically, as describing a class of methods for learning from experience, using minimal background knowledge. This paper considers how rational and mechanistic perspectives differ, and what types of evidence distinguish between them. Reinforcement learning research in the cognitive and brain sciences is often implicitly committed to the mechanistic interpretation. Here the opposite view is put forward: that accounts of reinforcement learning should apply at the rational level, unless there is strong evidence for a mechanistic interpretation. Implications of this viewpoint for reinforcement-based theories in the cognitive and brain sciences are discussed.

The Splashback Feature around DES Galaxy Clusters: Galaxy Density and Weak Lensing Profiles

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

Chang, Chihway; et al.

Splashback refers to the process of matter that is accreting onto a dark matter halo reaching its first orbital apocenter and turning around in its orbit. The cluster-centric radius at which this process occurs, r_sp, defines a halo boundary that is connected to the dynamics of the cluster, in contrast with other common halo boundary definitions such as R_200. A rapid decline in the matter density profile of the halo is expected near r_sp. We measure the galaxy number density and weak lensing mass profiles around RedMapper galaxy clusters in the first year Dark Energy Survey (DES) data. For amore » cluster sample with mean mass ~2.5 x 10^14 solar masses, we find strong evidence of a splashback-like steepening of the galaxy density profile and measure r_sp=1.16 +/- 0.08 Mpc/h, consistent with earlier SDSS measurements of More et al. (2016) and Baxter et al. (2017). Moreover, our weak lensing measurement demonstrates for the first time the existence of a splashback-like steepening of the matter profile of galaxy clusters. We measure r_sp=1.28 +/- 0.18 Mpc/h from the weak lensing data, in good agreement with our galaxy density measurements. Applying our analysis to different cluster and galaxy samples, we find that consistent with LambdaCDM simulations, r_sp scales with R_200m and does not evolve with redshift over the redshift range of 0.3--0.6. We also find that potential systematic effects associated with the RedMapper algorithm may impact the location of r_sp, in particular the choice of scale used to estimate cluster richness. We discuss progress needed to understand the systematic uncertainties and fully exploit forthcoming data from DES and future surveys, emphasizing the importance of more realistic mock catalogs and independent cluster samples.« less

Microbial community dynamics in soil aggregates shape biogeochemical gas fluxes from soil profiles - upscaling an aggregate biophysical model.

PubMed

Ebrahimi, Ali; Or, Dani

2016-09-01

Microbial communities inhabiting soil aggregates dynamically adjust their activity and composition in response to variations in hydration and other external conditions. These rapid dynamics shape signatures of biogeochemical activity and gas fluxes emitted from soil profiles. Recent mechanistic models of microbial processes in unsaturated aggregate-like pore networks revealed a highly dynamic interplay between oxic and anoxic microsites jointly shaped by hydration conditions and by aerobic and anaerobic microbial community abundance and self-organization. The spatial extent of anoxic niches (hotspots) flicker in time (hot moments) and support substantial anaerobic microbial activity even in aerated soil profiles. We employed an individual-based model for microbial community life in soil aggregate assemblies represented by 3D angular pore networks. Model aggregates of different sizes were subjected to variable water, carbon and oxygen contents that varied with soil depth as boundary conditions. The study integrates microbial activity within aggregates of different sizes and soil depth to obtain estimates of biogeochemical fluxes from the soil profile. The results quantify impacts of dynamic shifts in microbial community composition on CO2 and N2 O production rates in soil profiles in good agreement with experimental data. Aggregate size distribution and the shape of resource profiles in a soil determine how hydration dynamics shape denitrification and carbon utilization rates. Results from the mechanistic model for microbial activity in aggregates of different sizes were used to derive parameters for analytical representation of soil biogeochemical processes across large scales of practical interest for hydrological and climate models. © 2016 John Wiley & Sons Ltd.

Retinal identification based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform.

PubMed

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-07-18

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

PubMed Central

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-01-01

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes. PMID:23873409

Report on the ALPO LTP observing program. [for establishing albedo scale for lunar features

NASA Technical Reports Server (NTRS)

Cameron, W. S.

1974-01-01

Observations of lunar transient phenomena for the Association of Lunar and Planetary Observers (ALPO) are reported. The procedures for making visual observations for estimating albedo are described, and the reported albedo analyzed for lunar topographic features. It is shown that a catalog or scale of albedos can be established for each feature.

Features of tropospheric and stratospheric dust.

PubMed

Elterman, L; Wexler, R; Chang, D T

1969-05-01

A series of 119 profiles obtained over New Mexico comprise aerosol attenuation coefficients vs altitude to about 35 km. These profiles show the existence of several features. A surface convective dust layer extending up to about 5 km is seasonally dependent. Also, a turbidity maximum exists below the tropopause. The altitude of an aerosol maximum in the lower stratosphere is located just below that of the minimum temperature. The colder the minimum temperature, the greater is the aerosol content of the layer. This relationship suggests that the 20-km dust layer is due to convection in tropical air and advection to higher latitudes. Computed averages of optical thickness show that abatement of stratospheric dust from the Mt. Agung eruption became evident in April 1964. Results based on seventy-nine profiles characterizing volcanic dust abatement indicate that above 26 km, the aerosol scale height averages 3.75 km. Extrapolating with this scale height, tabulations are developed for uv, visible, and ir attenuation to 50 km. Optical mixing ratios are used to examine the aerosol concentrations at various altitudes, including a layer at 26 km having an optical thickness 10(-3) for 0.55-micro wavelength.

Lithospheric strength of Ganymede: Clues to early thermal profiles from extensional tectonic features

NASA Technical Reports Server (NTRS)

Golombek, M. P.; Banerdt, W. B.

1985-01-01

While it is generally agreed that the strength of a planet's lithosphere is controlled by a combination of brittle sliding and ductile flow laws, predicting the geometry and initial characteristics of faults due to failure from stresses imposed on the lithospheric strength envelope has not been thoroughly explored. Researchers used lithospheric strength envelopes to analyze the extensional features found on Ganymede. This application provides a quantitative means of estimating early thermal profiles on Ganymede, thereby constraining its early thermal evolution.

LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

PubMed

Magnusson, Rasmus; Mariotti, Guido Pio; Köpsén, Mattias; Lövfors, William; Gawel, Danuta R; Jörnsten, Rebecka; Linde, Jörg; Nordling, Torbjörn E M; Nyman, Elin; Schulze, Sylvie; Nestor, Colm E; Zhang, Huan; Cedersund, Gunnar; Benson, Mikael; Tjärnberg, Andreas; Gustafsson, Mika

2017-06-01

Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present large-scale simulation modeling (LASSIM), which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE) for gene regulatory networks (GRNs). LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. The LASSIM method is implemented as a general-purpose toolbox using the PyGMO Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim. As a method, LASSIM works in two steps, where it first infers a non-linear ODE system of the pre-specified core gene expression. Second, LASSIM in parallel optimizes the parameters that model the regulation of peripheral genes by core system genes. We showed the usefulness of this method by applying LASSIM to infer a large-scale non-linear model of naïve Th2 cell differentiation, made possible by integrating Th2 specific bindings, time-series together with six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models with truly

Lithologic influences on groundwater recharge through incised glacial till from profile to regional scales: Evidence from glaciated Eastern Nebraska

USGS Publications Warehouse

Gates, John B.; Steele, Gregory V.; Nasta, Paolo; Szilagyi, Jozsef

2014-01-01

Variability in sediment hydraulic properties associated with landscape depositional and erosional features can influence groundwater recharge processes by affecting soil-water storage and transmission. This study considers recharge to aquifers underlying river-incised glaciated terrain where the distribution of clay-rich till is largely intact in upland locations but has been removed by alluvial erosion in stream valleys. In a stream-dissected glacial region in eastern Nebraska (Great Plains region of the United States), recharge estimates were developed for nested profile, aquifer, and regional scales using unsaturated zone profile measurements (matric potentials, Cl- and 3H), groundwater tracers (CFC-12 and SF6), and a remote sensing-assisted water balance model. Results show a consistent influence of till lithology on recharge rates across nested spatial scales despite substantial uncertainty in all recharge estimation methods, suggesting that minimal diffuse recharge occurs through upland glacial till lithology whereas diffuse recharge occurs in river valleys where till is locally absent. Diffuse recharge is estimated to account for a maximum of 61% of total recharge based on comparison of diffuse recharge estimated from the unsaturated zone (0-43 mm yr-1) and total recharge estimated from groundwater tracers (median 58 mm yr-1) and water balance modeling (median 56 mm yr-1). The results underscore the importance of lithologic controls on the distributions of both recharge rates and mechanisms.

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

PubMed

Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S

2017-04-01

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Mechanistic ecohydrological modeling with Tethys-Chloris: an attempt to unravel complexity

NASA Astrophysics Data System (ADS)

Fatichi, S.; Ivanov, V. Y.; Caporali, E.

2010-12-01

The role of vegetation in controlling and mediating hydrological states and fluxes at the level of individual processes has been largely explored, which has lead to the improvement of our understanding of mechanisms and patterns in ecohydrological systems. Nonetheless, relatively few efforts have been directed toward the development of continuous, complex, mechanistic ecohydrological models operating at the watershed-scale. This study presents a novel ecohydrological model Tethys-Chloris (T&C) and aims to discuss current limitations and perspectives of the mechanistic approach in ecohydrology. The model attempts to synthesize the state-of-the-art knowledge on individual processes and mechanisms drawn from various disciplines such as hydrology, plant physiology, ecology, and biogeochemistry. The model reproduces all essential components of hydrological cycle resolving the mass and energy budgets at the hourly scale; it includes energy and mass exchanges in the atmospheric boundary layer; a module of saturated and unsaturated soil water dynamics; two layers of vegetation, and a module of snowpack evolution. The vegetation component parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, tissues turnover, and soil biogeochemistry. Quantitative metrics of model performance are discussed and highlight the capabilities of T&C in reproducing ecohydrological dynamics. The simulated patterns mimic the outcome of hydrological dynamics with high realism, given the uncertainty of imposed boundary conditions and limited data availability. Furthermore, highly satisfactory results are obtained without significant (e.g., automated) calibration efforts despite the large phase-space dimensionality of the model. A significant investment into model design and development leads to such desirable behavior. This suggests that while using the presented tool for high-precision predictions can be still problematic, the

Model-Based Analysis of Biopharmaceutic Experiments To Improve Mechanistic Oral Absorption Modeling: An Integrated in Vitro in Vivo Extrapolation Perspective Using Ketoconazole as a Model Drug.

PubMed

Pathak, Shriram M; Ruff, Aaron; Kostewicz, Edmund S; Patel, Nikunjkumar; Turner, David B; Jamei, Masoud

2017-12-04

Mechanistic modeling of in vitro data generated from metabolic enzyme systems (viz., liver microsomes, hepatocytes, rCYP enzymes, etc.) facilitates in vitro-in vivo extrapolation (IVIV_E) of metabolic clearance which plays a key role in the successful prediction of clearance in vivo within physiologically-based pharmacokinetic (PBPK) modeling. A similar concept can be applied to solubility and dissolution experiments whereby mechanistic modeling can be used to estimate intrinsic parameters required for mechanistic oral absorption simulation in vivo. However, this approach has not widely been applied within an integrated workflow. We present a stepwise modeling approach where relevant biopharmaceutics parameters for ketoconazole (KTZ) are determined and/or confirmed from the modeling of in vitro experiments before being directly used within a PBPK model. Modeling was applied to various in vitro experiments, namely: (a) aqueous solubility profiles to determine intrinsic solubility, salt limiting solubility factors and to verify pK a ; (b) biorelevant solubility measurements to estimate bile-micelle partition coefficients; (c) fasted state simulated gastric fluid (FaSSGF) dissolution for formulation disintegration profiling; and (d) transfer experiments to estimate supersaturation and precipitation parameters. These parameters were then used within a PBPK model to predict the dissolved and total (i.e., including the precipitated fraction) concentrations of KTZ in the duodenum of a virtual population and compared against observed clinical data. The developed model well characterized the intraluminal dissolution, supersaturation, and precipitation behavior of KTZ. The mean simulated AUC 0-t of the total and dissolved concentrations of KTZ were comparable to (within 2-fold of) the corresponding observed profile. Moreover, the developed PBPK model of KTZ successfully described the impact of supersaturation and precipitation on the systemic plasma concentration profiles of

A mechanistic modeling system for estimating large scale emissions and transport of pollen and co-allergens

PubMed Central

Efstathiou, Christos; Isukapalli, Sastry

2011-01-01

Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen

A mechanistic modeling system for estimating large-scale emissions and transport of pollen and co-allergens

NASA Astrophysics Data System (ADS)

Efstathiou, Christos; Isukapalli, Sastry; Georgopoulos, Panos

2011-04-01

Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen

Whole Tumor Histogram-profiling of Diffusion-Weighted Magnetic Resonance Images Reflects Tumorbiological Features of Primary Central Nervous System Lymphoma.

PubMed

Schob, Stefan; Münch, Benno; Dieckow, Julia; Quäschling, Ulf; Hoffmann, Karl-Titus; Richter, Cindy; Garnov, Nikita; Frydrychowicz, Clara; Krause, Matthias; Meyer, Hans-Jonas; Surov, Alexey

2018-04-01

Diffusion weighted imaging (DWI) quantifies motion of hydrogen nuclei in biological tissues and hereby has been used to assess the underlying tissue microarchitecture. Histogram-profiling of DWI provides more detailed information on diffusion characteristics of a lesion than the standardly calculated values of the apparent diffusion coefficient (ADC)-minimum, mean and maximum. Hence, the aim of our study was to investigate, which parameters of histogram-profiling of DWI in primary central nervous system lymphoma can be used to specifically predict features like cellular density, chromatin content and proliferative activity. Pre-treatment ADC maps of 21 PCNSL patients (8 female, 13 male, 28-89 years) from a 1.5T system were used for Matlab-based histogram profiling. Results of histopathology (H&E staining) and immunohistochemistry (Ki-67 expression) were quantified. Correlations between histogram-profiling parameters and neuropathologic examination were calculated using SPSS 23.0. The lower percentiles (p10 and p25) showed significant correlations with structural parameters of the neuropathologic examination (cellular density, chromatin content). The highest percentile, p90, correlated significantly with Ki-67 expression, resembling proliferative activity. Kurtosis of the ADC histogram correlated significantly with cellular density. Histogram-profiling of DWI in PCNSL provides a comprehensible set of parameters, which reflect distinct tumor-architectural and tumor-biological features, and hence, are promising biomarkers for treatment response and prognosis. Copyright © 2018. Published by Elsevier Inc.

Efficient and Robust Model-to-Image Alignment using 3D Scale-Invariant Features

PubMed Central

Toews, Matthew; Wells, William M.

2013-01-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a-posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. PMID:23265799

Large-scale feature searches of collections of medical imagery

NASA Astrophysics Data System (ADS)

Hedgcock, Marcus W.; Karshat, Walter B.; Levitt, Tod S.; Vosky, D. N.

1993-09-01

Large scale feature searches of accumulated collections of medical imagery are required for multiple purposes, including clinical studies, administrative planning, epidemiology, teaching, quality improvement, and research. To perform a feature search of large collections of medical imagery, one can either search text descriptors of the imagery in the collection (usually the interpretation), or (if the imagery is in digital format) the imagery itself. At our institution, text interpretations of medical imagery are all available in our VA Hospital Information System. These are downloaded daily into an off-line computer. The text descriptors of most medical imagery are usually formatted as free text, and so require a user friendly database search tool to make searches quick and easy for any user to design and execute. We are tailoring such a database search tool (Liveview), developed by one of the authors (Karshat). To further facilitate search construction, we are constructing (from our accumulated interpretation data) a dictionary of medical and radiological terms and synonyms. If the imagery database is digital, the imagery which the search discovers is easily retrieved from the computer archive. We describe our database search user interface, with examples, and compare the efficacy of computer assisted imagery searches from a clinical text database with manual searches. Our initial work on direct feature searches of digital medical imagery is outlined.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Rational and Mechanistic Perspectives on Reinforcement Learning

ERIC Educational Resources Information Center

Chater, Nick

2009-01-01

This special issue describes important recent developments in applying reinforcement learning models to capture neural and cognitive function. But reinforcement learning, as a theoretical framework, can apply at two very different levels of description: "mechanistic" and "rational." Reinforcement learning is often viewed in mechanistic terms--as…

On Feature Extraction from Large Scale Linear LiDAR Data

NASA Astrophysics Data System (ADS)

Acharjee, Partha Pratim

Airborne light detection and ranging (LiDAR) can generate co-registered elevation and intensity map over large terrain. The co-registered 3D map and intensity information can be used efficiently for different feature extraction application. In this dissertation, we developed two algorithms for feature extraction, and usages of features for practical applications. One of the developed algorithms can map still and flowing waterbody features, and another one can extract building feature and estimate solar potential on rooftops and facades. Remote sensing capabilities, distinguishing characteristics of laser returns from water surface and specific data collection procedures provide LiDAR data an edge in this application domain. Furthermore, water surface mapping solutions must work on extremely large datasets, from a thousand square miles, to hundreds of thousands of square miles. National and state-wide map generation/upgradation and hydro-flattening of LiDAR data for many other applications are two leading needs of water surface mapping. These call for as much automation as possible. Researchers have developed many semi-automated algorithms using multiple semi-automated tools and human interventions. This reported work describes a consolidated algorithm and toolbox developed for large scale, automated water surface mapping. Geometric features such as flatness of water surface, higher elevation change in water-land interface and, optical properties such as dropouts caused by specular reflection, bimodal intensity distributions were some of the linear LiDAR features exploited for water surface mapping. Large-scale data handling capabilities are incorporated by automated and intelligent windowing, by resolving boundary issues and integrating all results to a single output. This whole algorithm is developed as an ArcGIS toolbox using Python libraries. Testing and validation are performed on a large datasets to determine the effectiveness of the toolbox and results are

Engineering properties of resin modified pavement (RMP) for mechanistic design

NASA Astrophysics Data System (ADS)

Anderton, Gary Lee

1997-11-01

The research study described in this report focuses on determining the engineering properties of the resin modified pavement (RMP) material relating to pavement performance, and then developing a rational mechanistic design procedure to replace the current empirical design procedure. A detailed description of RMP is provided, including a review of the available literature on this relatively new pavement technology. Field evaluations of four existing and two new RMP project sites were made to assess critical failure modes and to obtain pavement samples for subsequent laboratory testing. Various engineering properties of laboratory-produced and field-recovered samples of RMP were measured and analyzed. The engineering properties evaluated included those relating to the material's stiffness, strength, thermal properties, and traffic-related properties. Comparisons of these data to typical values for asphalt concrete and portland cement concrete were made to relate the physical nature of RMP to more common pavement surfacing materials. A mechanistic design procedure was developed to determine appropriate thickness profiles of RMP, using stiffness and fatigue properties determined by this study. The design procedure is based on the U.S. Army Corps of Engineers layered elastic method for airfield flexible pavements. The WESPAVE computer program was used to demonstrate the new design procedure for a hypothetical airfield apron design. The results of the study indicated that RMP is a relatively stiff, viscoelastic pavement surfacing material with many of its strength and stiffness properties falling between those of typical asphalt concrete and portland cement concrete. The RMP's thermal and traffic-related properties indicated favorable field performance. The layered elastic design approach appeared to be a reasonable and practical method for RMP mechanistic pavement design, and this design procedure was recommended for future use and development.

Research on Optimal Observation Scale for Damaged Buildings after Earthquake Based on Optimal Feature Space

NASA Astrophysics Data System (ADS)

Chen, J.; Chen, W.; Dou, A.; Li, W.; Sun, Y.

2018-04-01

A new information extraction method of damaged buildings rooted in optimal feature space is put forward on the basis of the traditional object-oriented method. In this new method, ESP (estimate of scale parameter) tool is used to optimize the segmentation of image. Then the distance matrix and minimum separation distance of all kinds of surface features are calculated through sample selection to find the optimal feature space, which is finally applied to extract the image of damaged buildings after earthquake. The overall extraction accuracy reaches 83.1 %, the kappa coefficient 0.813. The new information extraction method greatly improves the extraction accuracy and efficiency, compared with the traditional object-oriented method, and owns a good promotional value in the information extraction of damaged buildings. In addition, the new method can be used for the information extraction of different-resolution images of damaged buildings after earthquake, then to seek the optimal observation scale of damaged buildings through accuracy evaluation. It is supposed that the optimal observation scale of damaged buildings is between 1 m and 1.2 m, which provides a reference for future information extraction of damaged buildings.

Intriguing mechanistic labyrinths in gold(i) catalysis

PubMed Central

Obradors, Carla

2014-01-01

Many mechanistically intriguing reactions have been developed in the last decade using gold(i) as catalyst. Here we review the main mechanistic proposals in gold-catalysed activation of alkynes and allenes, in which this metal plays a central role by stabilising a variety of complex cationic intermediates. PMID:24176910

Efficient and robust model-to-image alignment using 3D scale-invariant features.

PubMed

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

The use of mechanistic evidence in drug approval.

PubMed

Aronson, Jeffrey K; La Caze, Adam; Kelly, Michael P; Parkkinen, Veli-Pekka; Williamson, Jon

2018-06-11

The role of mechanistic evidence tends to be under-appreciated in current evidence-based medicine (EBM), which focusses on clinical studies, tending to restrict attention to randomized controlled studies (RCTs) when they are available. The EBM+ programme seeks to redress this imbalance, by suggesting methods for evaluating mechanistic studies alongside clinical studies. Drug approval is a problematic case for the view that mechanistic evidence should be taken into account, because RCTs are almost always available. Nevertheless, we argue that mechanistic evidence is central to all the key tasks in the drug approval process: in drug discovery and development; assessing pharmaceutical quality; devising dosage regimens; assessing efficacy, harms, external validity, and cost-effectiveness; evaluating adherence; and extending product licences. We recommend that, when preparing for meetings in which any aspect of drug approval is to be discussed, mechanistic evidence should be systematically analysed and presented to the committee members alongside analyses of clinical studies. © 2018 The Authors Journal of Evaluation in Clinical Practice Published by John Wiley & Sons Ltd.

Transitioning from AOP to IATA - Exploiting mechanistic ...

EPA Pesticide Factsheets

Slide presentation at satellite meeting of the QSAR2016 Meeting on How to Transition from AOP to IATA-Exploiting mechanistic insight for practical decision making. . Slide presentation at satellite meeting of the QSAR2016 Meeting on How to Transition from AOP to IATA-Exploiting mechanistic insight for practical decision making. .

Suppression effects in feature-based attention

PubMed Central

Wang, Yixue; Miller, James; Liu, Taosheng

2015-01-01

Attending to a feature enhances visual processing of that feature, but it is less clear what occurs to unattended features. Single-unit recording studies in middle temporal (MT) have shown that neuronal modulation is a monotonic function of the difference between the attended and neuron's preferred direction. Such a relationship should predict a monotonic suppressive effect in psychophysical performance. However, past research on suppressive effects of feature-based attention has remained inconclusive. We investigated the suppressive effect for motion direction, orientation, and color in three experiments. We asked participants to detect a weak signal among noise and provided a partially valid feature cue to manipulate attention. We measured performance as a function of the offset between the cued and signal feature. We also included neutral trials where no feature cues were presented to provide a baseline measure of performance. Across three experiments, we consistently observed enhancement effects when the target feature and cued feature coincided and suppression effects when the target feature deviated from the cued feature. The exact profile of suppression was different across feature dimensions: Whereas the profile for direction exhibited a “rebound” effect, the profiles for orientation and color were monotonic. These results demonstrate that unattended features are suppressed during feature-based attention, but the exact suppression profile depends on the specific feature. Overall, the results are largely consistent with neurophysiological data and support the feature-similarity gain model of attention. PMID:26067533

Large-scale image-based profiling of single-cell phenotypes in arrayed CRISPR-Cas9 gene perturbation screens.

PubMed

de Groot, Reinoud; Lüthi, Joel; Lindsay, Helen; Holtackers, René; Pelkmans, Lucas

2018-01-23

High-content imaging using automated microscopy and computer vision allows multivariate profiling of single-cell phenotypes. Here, we present methods for the application of the CISPR-Cas9 system in large-scale, image-based, gene perturbation experiments. We show that CRISPR-Cas9-mediated gene perturbation can be achieved in human tissue culture cells in a timeframe that is compatible with image-based phenotyping. We developed a pipeline to construct a large-scale arrayed library of 2,281 sequence-verified CRISPR-Cas9 targeting plasmids and profiled this library for genes affecting cellular morphology and the subcellular localization of components of the nuclear pore complex (NPC). We conceived a machine-learning method that harnesses genetic heterogeneity to score gene perturbations and identify phenotypically perturbed cells for in-depth characterization of gene perturbation effects. This approach enables genome-scale image-based multivariate gene perturbation profiling using CRISPR-Cas9. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

PubMed

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

Time scale variation of NV resonance line profiles of HD203064

NASA Astrophysics Data System (ADS)

Strantzalis, A.

2012-01-01

Hot emission star, such as Be and Oe, present many spectral lines with very complex and peculiar profiles. Therefore, we cannot find a classical distribution to fit theoretically those physical line profiles. So, many physical parameters of the regions, where spectral lines are created, are difficult to estimate. Here, in this poster paper we study the UV NV (λλ 1238.821, 1242.804 A) resonance lines of the Be star HD203064 at three different dates. We using the Gauss-Rotation model, that proposed the idea that these complex profiles consist of a number of independent Discrete or Satellite Absorption Components (DACs, SACs). Our purpose is to calculate the values of a group of physical parameters as the apparent rotational, radial, and random velocities of the thermal motions of the ions. Also the Full Width at Half Maximum (FWHM) and the column density, as well as the absorbed energy of the independent regions of matter, which produce the main and the satellite components of the studied spectral lines. In addition, we determine the time scale variations of the above physical parameters.

Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features.

PubMed

Li, Hongyang; Panwar, Bharat; Omenn, Gilbert S; Guan, Yuanfang

2018-02-01

The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge. We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction. Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

Melancholic depression prediction by identifying representative features in metabolic and microarray profiles with missing values.

PubMed

Nie, Zhi; Yang, Tao; Liu, Yashu; Li, Qingyang; Narayan, Vaibhav A; Wittenberg, Gayle; Ye, Jieping

2015-01-01

Recent studies have revealed that melancholic depression, one major subtype of depression, is closely associated with the concentration of some metabolites and biological functions of certain genes and pathways. Meanwhile, recent advances in biotechnologies have allowed us to collect a large amount of genomic data, e.g., metabolites and microarray gene expression. With such a huge amount of information available, one approach that can give us new insights into the understanding of the fundamental biology underlying melancholic depression is to build disease status prediction models using classification or regression methods. However, the existence of strong empirical correlations, e.g., those exhibited by genes sharing the same biological pathway in microarray profiles, tremendously limits the performance of these methods. Furthermore, the occurrence of missing values which are ubiquitous in biomedical applications further complicates the problem. In this paper, we hypothesize that the problem of missing values might in some way benefit from the correlation between the variables and propose a method to learn a compressed set of representative features through an adapted version of sparse coding which is capable of identifying correlated variables and addressing the issue of missing values simultaneously. An efficient algorithm is also developed to solve the proposed formulation. We apply the proposed method on metabolic and microarray profiles collected from a group of subjects consisting of both patients with melancholic depression and healthy controls. Results show that the proposed method can not only produce meaningful clusters of variables but also generate a set of representative features that achieve superior classification performance over those generated by traditional clustering and data imputation techniques. In particular, on both datasets, we found that in comparison with the competing algorithms, the representative features learned by the proposed

Lensing Constraints on the Mass Profile Shape and the Splashback Radius of Galaxy Clusters

NASA Astrophysics Data System (ADS)

Umetsu, Keiichi; Diemer, Benedikt

2017-02-01

The lensing signal around galaxy clusters can, in principle, be used to test detailed predictions for their average mass profile from numerical simulations. However, the intrinsic shape of the profiles can be smeared out when a sample that spans a wide range of cluster masses is averaged in physical length units. This effect especially conceals rapid changes in gradient such as the steep drop associated with the splashback radius, a sharp edge corresponding to the outermost caustic in accreting halos. We optimize the extraction of such local features by scaling individual halo profiles to a number of spherical overdensity radii, and apply this method to 16 X-ray-selected, high-mass clusters targeted in the Cluster Lensing And Supernova survey with Hubble. By forward-modeling the weak- and strong-lensing data presented by Umetsu et al., we show that, regardless of the scaling overdensity, the projected ensemble density profile is remarkably well described by a Navarro-Frenk-White (NFW) or Einasto profile out to R˜ 2.5 {h}-1 {Mpc}, beyond which the profiles flatten. We constrain the NFW concentration to {c}200{{c}}=3.66+/- 0.11 at {M}200{{c}}≃ 1.0× {10}15 {h}-1 {M}⊙ , consistent with and improved from previous work that used conventionally stacked lensing profiles, and in excellent agreement with theoretical expectations. Assuming the profile form of Diemer & Kravtsov and generic priors calibrated from numerical simulations, we place a lower limit on the splashback radius of the cluster halos, if it exists, of {R}{sp}3{{D}}/{r}200{{m}}> 0.89 ({R}{sp}3{{D}}> 1.83 {h}-1 {Mpc}) at 68% confidence. The corresponding density feature is most pronounced when the cluster profiles are scaled by {r}200{{m}}, and smeared out when scaled to higher overdensities. Based in part on data collected at the Subaru Telescope, which is operated by the National Astronomical Society of Japan.

Psychological Features and Their Relationship to Movement-Based Subgroups in People Living With Low Back Pain.

PubMed

Karayannis, Nicholas V; Jull, Gwendolen A; Nicholas, Michael K; Hodges, Paul W

2018-01-01

To determine the distribution of higher psychological risk features within movement-based subgroups for people with low back pain (LBP). Cross-sectional observational study. Participants were recruited from physiotherapy clinics and community advertisements. Measures were collected at a university outpatient-based physiotherapy clinic. People (N=102) seeking treatment for LBP. Participants were subgrouped according to 3 classification schemes: Mechanical Diagnosis and Treatment (MDT), Treatment-Based Classification (TBC), and O'Sullivan Classification (OSC). Questionnaires were used to categorize low-, medium-, and high-risk features based on depression, anxiety, and stress (Depression, Anxiety, and Stress Scale-21 Items); fear avoidance (Fear-Avoidance Beliefs Questionnaire); catastrophizing and coping (Pain-Related Self-Symptoms Scale); and self-efficacy (Pain Self-Efficacy Questionnaire). Psychological risk profiles were compared between movement-based subgroups within each scheme. Scores across all questionnaires revealed that most patients had low psychological risk profiles, but there were instances of higher (range, 1%-25%) risk profiles within questionnaire components. The small proportion of individuals with higher psychological risk scores were distributed between subgroups across TBC, MDT, and OSC schemes. Movement-based subgrouping alone cannot inform on individuals with higher psychological risk features. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Unified superresolution experiments and stochastic theory provide mechanistic insight into protein ion-exchange adsorptive separations

PubMed Central

Kisley, Lydia; Chen, Jixin; Mansur, Andrea P.; Shuang, Bo; Kourentzi, Katerina; Poongavanam, Mohan-Vivekanandan; Chen, Wen-Hsiang; Dhamane, Sagar; Willson, Richard C.; Landes, Christy F.

2014-01-01

Chromatographic protein separations, immunoassays, and biosensing all typically involve the adsorption of proteins to surfaces decorated with charged, hydrophobic, or affinity ligands. Despite increasingly widespread use throughout the pharmaceutical industry, mechanistic detail about the interactions of proteins with individual chromatographic adsorbent sites is available only via inference from ensemble measurements such as binding isotherms, calorimetry, and chromatography. In this work, we present the direct superresolution mapping and kinetic characterization of functional sites on ion-exchange ligands based on agarose, a support matrix routinely used in protein chromatography. By quantifying the interactions of single proteins with individual charged ligands, we demonstrate that clusters of charges are necessary to create detectable adsorption sites and that even chemically identical ligands create adsorption sites of varying kinetic properties that depend on steric availability at the interface. Additionally, we relate experimental results to the stochastic theory of chromatography. Simulated elution profiles calculated from the molecular-scale data suggest that, if it were possible to engineer uniform optimal interactions into ion-exchange systems, separation efficiencies could be improved by as much as a factor of five by deliberately exploiting clustered interactions that currently dominate the ion-exchange process only accidentally. PMID:24459184

Unified superresolution experiments and stochastic theory provide mechanistic insight into protein ion-exchange adsorptive separations.

PubMed

Kisley, Lydia; Chen, Jixin; Mansur, Andrea P; Shuang, Bo; Kourentzi, Katerina; Poongavanam, Mohan-Vivekanandan; Chen, Wen-Hsiang; Dhamane, Sagar; Willson, Richard C; Landes, Christy F

2014-02-11

Chromatographic protein separations, immunoassays, and biosensing all typically involve the adsorption of proteins to surfaces decorated with charged, hydrophobic, or affinity ligands. Despite increasingly widespread use throughout the pharmaceutical industry, mechanistic detail about the interactions of proteins with individual chromatographic adsorbent sites is available only via inference from ensemble measurements such as binding isotherms, calorimetry, and chromatography. In this work, we present the direct superresolution mapping and kinetic characterization of functional sites on ion-exchange ligands based on agarose, a support matrix routinely used in protein chromatography. By quantifying the interactions of single proteins with individual charged ligands, we demonstrate that clusters of charges are necessary to create detectable adsorption sites and that even chemically identical ligands create adsorption sites of varying kinetic properties that depend on steric availability at the interface. Additionally, we relate experimental results to the stochastic theory of chromatography. Simulated elution profiles calculated from the molecular-scale data suggest that, if it were possible to engineer uniform optimal interactions into ion-exchange systems, separation efficiencies could be improved by as much as a factor of five by deliberately exploiting clustered interactions that currently dominate the ion-exchange process only accidentally.

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

NASA Astrophysics Data System (ADS)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

Fast Localization in Large-Scale Environments Using Supervised Indexing of Binary Features.

PubMed

Youji Feng; Lixin Fan; Yihong Wu

2016-01-01

The essence of image-based localization lies in matching 2D key points in the query image and 3D points in the database. State-of-the-art methods mostly employ sophisticated key point detectors and feature descriptors, e.g., Difference of Gaussian (DoG) and Scale Invariant Feature Transform (SIFT), to ensure robust matching. While a high registration rate is attained, the registration speed is impeded by the expensive key point detection and the descriptor extraction. In this paper, we propose to use efficient key point detectors along with binary feature descriptors, since the extraction of such binary features is extremely fast. The naive usage of binary features, however, does not lend itself to significant speedup of localization, since existing indexing approaches, such as hierarchical clustering trees and locality sensitive hashing, are not efficient enough in indexing binary features and matching binary features turns out to be much slower than matching SIFT features. To overcome this, we propose a much more efficient indexing approach for approximate nearest neighbor search of binary features. This approach resorts to randomized trees that are constructed in a supervised training process by exploiting the label information derived from that multiple features correspond to a common 3D point. In the tree construction process, node tests are selected in a way such that trees have uniform leaf sizes and low error rates, which are two desired properties for efficient approximate nearest neighbor search. To further improve the search efficiency, a probabilistic priority search strategy is adopted. Apart from the label information, this strategy also uses non-binary pixel intensity differences available in descriptor extraction. By using the proposed indexing approach, matching binary features is no longer much slower but slightly faster than matching SIFT features. Consequently, the overall localization speed is significantly improved due to the much faster key

Probing features in the primordial perturbation spectrum with large-scale structure data

NASA Astrophysics Data System (ADS)

L'Huillier, Benjamin; Shafieloo, Arman; Hazra, Dhiraj Kumar; Smoot, George F.; Starobinsky, Alexei A.

2018-06-01

The form of the primordial power spectrum (PPS) of cosmological scalar (matter density) perturbations is not yet constrained satisfactorily in spite of the tremendous amount of information from the Cosmic Microwave Background (CMB) data. While a smooth power-law-like form of the PPS is consistent with the CMB data, some PPSs with small non-smooth features at large scales can also fit the CMB temperature and polarization data with similar statistical evidence. Future CMB surveys cannot help distinguish all such models due to the cosmic variance at large angular scales. In this paper, we study how well we can differentiate between such featured forms of the PPS not otherwise distinguishable using CMB data. We ran 15 N-body DESI-like simulations of these models to explore this approach. Showing that statistics such as the halo mass function and the two-point correlation function are not able to distinguish these models in a DESI-like survey, we advocate to avoid reducing the dimensionality of the problem by demonstrating that the use of a simple three-dimensional count-in-cell density field can be much more effective for the purpose of model distinction.

The Prandtl Plus Scaling Parameters and Velocity Profile Similarity: Part 2

DTIC Science & Technology

2012-12-01

a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1...ABSTRACT In a previous report (Weyburne, AFRL-RY-WP-TR-2012-0227) it was pointed out that the momentum balance type approach to velocity profile...were NOT similar. It was concluded that the scaling variables discovered by the momentum balance type approach as presently constituted are a

Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan

USGS Publications Warehouse

Safaie, Ammar; Wendzel, Aaron; Ge, Zhongfu; Nevers, Meredith; Whitman, Richard L.; Corsi, Steven R.; Phanikumar, Mantha S.

2016-01-01

Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models are developed, tested, and used. We describe a cooperative modeling approach for freshwater beaches impacted by point sources in which insights derived from mechanistic modeling were used to further improve the statistical models and vice versa. The statistical models provided a basis for assessing the mechanistic models which were further improved using probability distributions to generate high-resolution time series data at the source, long-term “tracer” transport modeling based on observed electrical conductivity, better assimilation of meteorological data, and the use of unstructured-grids to better resolve nearshore features. This approach resulted in improved models of comparable performance for both classes including a parsimonious statistical model suitable for real-time predictions based on an easily measurable environmental variable (turbidity). The modeling approach outlined here can be used at other sites impacted by point sources and has the potential to improve water quality predictions resulting in more accurate estimates of beach closures.

Synoptic evaluation of scale-dependent metrics for hydrographic line feature geometry

USGS Publications Warehouse

Stanislawski, Larry V.; Buttenfield, Barbara P.; Raposo, Paulo; Cameron, Madeline; Falgout, Jeff T.

2015-01-01

Methods of acquisition and feature simplification for vector feature data impact cartographic representations and scientific investigations of these data, and are therefore important considerations for geographic information science (Haunert and Sester 2008). After initial collection, linear features may be simplified to reduce excessive detail or to furnish a reduced-scale version of the features through cartographic generalization (Regnauld and McMaster 2008, Stanislawski et al. 2014). A variety of algorithms exist to simplify linear cartographic features, and all of the methods affect the positional accuracy of the features (Shahriari and Tao 2002, Regnauld and McMaster 2008, Stanislawski et al. 2012). In general, simplification operations are controlled by one or more tolerance parameters that limit the amount of positional change the operation can make to features. Using a single tolerance value can have varying levels of positional change on features; depending on local shape, texture, or geometric characteristics of the original features (McMaster and Shea 1992, Shahriari and Tao 2002, Buttenfield et al. 2010). Consequently, numerous researchers have advocated calibration of simplification parameters to control quantifiable properties of resulting changes to the features (Li and Openshaw 1990, Raposo 2013, Tobler 1988, Veregin 2000, and Buttenfield, 1986, 1989).This research identifies relations between local topographic conditions and geometric characteristics of linear features that are available in the National Hydrography Dataset (NHD). The NHD is a comprehensive vector dataset of surface 18 th ICA Workshop on Generalisation and Multiple Representation, Rio de Janiero, Brazil 2015 2 water features within the United States that is maintained by the U.S. Geological Survey (USGS). In this paper, geometric characteristics of cartographic representations for natural stream and river features are summarized for subbasin watersheds within entire regions of the

Learning relevant features of data with multi-scale tensor networks

NASA Astrophysics Data System (ADS)

Miles Stoudenmire, E.

2018-07-01

Inspired by coarse-graining approaches used in physics, we show how similar algorithms can be adapted for data. The resulting algorithms are based on layered tree tensor networks and scale linearly with both the dimension of the input and the training set size. Computing most of the layers with an unsupervised algorithm, then optimizing just the top layer for supervised classification of the MNIST and fashion MNIST data sets gives very good results. We also discuss mixing a prior guess for supervised weights together with an unsupervised representation of the data, yielding a smaller number of features nevertheless able to give good performance.

A mechanistic modeling and data assimilation framework for Mojave Desert ecohydrology

USGS Publications Warehouse

Ng, Gene-Hua Crystal.; Bedford, David; Miller, David

2014-01-01

This study demonstrates and addresses challenges in coupled ecohydrological modeling in deserts, which arise due to unique plant adaptations, marginal growing conditions, slow net primary production rates, and highly variable rainfall. We consider model uncertainty from both structural and parameter errors and present a mechanistic model for the shrub Larrea tridentata (creosote bush) under conditions found in the Mojave National Preserve in southeastern California (USA). Desert-specific plant and soil features are incorporated into the CLM-CN model by Oleson et al. (2010). We then develop a data assimilation framework using the ensemble Kalman filter (EnKF) to estimate model parameters based on soil moisture and leaf-area index observations. A new implementation procedure, the “multisite loop EnKF,” tackles parameter estimation difficulties found to affect desert ecohydrological applications. Specifically, the procedure iterates through data from various observation sites to alleviate adverse filter impacts from non-Gaussianity in small desert vegetation state values. It also readjusts inconsistent parameters and states through a model spin-up step that accounts for longer dynamical time scales due to infrequent rainfall in deserts. Observation error variance inflation may also be needed to help prevent divergence of estimates from true values. Synthetic test results highlight the importance of adequate observations for reducing model uncertainty, which can be achieved through data quality or quantity.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Self adaptive multi-scale morphology AVG-Hat filter and its application to fault feature extraction for wheel bearing

NASA Astrophysics Data System (ADS)

Deng, Feiyue; Yang, Shaopu; Tang, Guiji; Hao, Rujiang; Zhang, Mingliang

2017-04-01

Wheel bearings are essential mechanical components of trains, and fault detection of the wheel bearing is of great significant to avoid economic loss and casualty effectively. However, considering the operating conditions, detection and extraction of the fault features hidden in the heavy noise of the vibration signal have become a challenging task. Therefore, a novel method called adaptive multi-scale AVG-Hat morphology filter (MF) is proposed to solve it. The morphology AVG-Hat operator not only can suppress the interference of the strong background noise greatly, but also enhance the ability of extracting fault features. The improved envelope spectrum sparsity (IESS), as a new evaluation index, is proposed to select the optimal filtering signal processed by the multi-scale AVG-Hat MF. It can present a comprehensive evaluation about the intensity of fault impulse to the background noise. The weighted coefficients of the different scale structural elements (SEs) in the multi-scale MF are adaptively determined by the particle swarm optimization (PSO) algorithm. The effectiveness of the method is validated by analyzing the real wheel bearing fault vibration signal (e.g. outer race fault, inner race fault and rolling element fault). The results show that the proposed method could improve the performance in the extraction of fault features effectively compared with the multi-scale combined morphological filter (CMF) and multi-scale morphology gradient filter (MGF) methods.

Adaptation to the Spanish population of the Substance Use Risk Profile Scale (SURPS) and psychometric properties.

PubMed

Fernández-Calderón, Fermín; Díaz-Batanero, Carmen; Rojas-Tejada, Antonio J; Castellanos-Ryan, Natalie; Lozano-Rojas, Óscar M

2017-07-14

The identification of different personality risk profiles for substance misuse is useful in preventing substance-related problems. This study aims to test the psychometric properties of a new version of the Substance Use Risk Profile Scale (SURPS) for Spanish college students. Cross-sectional study with 455 undergraduate students from four Spanish universities. A new version of the SURPS, adapted to the Spanish population, was administered with the Beck Hopelessness Scale, the UPPS-P Impulsive Behavior Scale, the State-Trait Anxiety Inventory (STAI) and the Alcohol Use Disorders Identification Test (AUDIT). Internal consistency reliability ranged between 0.652 and 0.806 for the four SURPS subscales, while reliability estimated by split-half coefficients varied from 0.686 to 0.829. The estimated test-retest reliability ranged between 0.733 and 0.868. The expected four-factor structure of the original scale was replicated. As evidence of convergent validity, we found that the SURPS subscales were significantly associated with other conceptually-relevant personality scales and significantly associated with alcohol use measures in theoretically-expected ways. This SURPS version may be a useful instrument for measuring personality traits related to vulnerability to substance use and misuse when targeting personality with preventive interventions.

Bird Migration Under Climate Change - A Mechanistic Approach Using Remote Sensing

NASA Technical Reports Server (NTRS)

Smith, James A.; Blattner, Tim; Messmer, Peter

2010-01-01

The broad-scale reductions and shifts that may be expected under climate change in the availability and quality of stopover habitat for long-distance migrants is an area of increasing concern for conservation biologists. Researchers generally have taken two broad approaches to the modeling of migration behaviour to understand the impact of these changes on migratory bird populations. These include models based on causal processes and their response to environmental stimulation, "mechanistic models", or models that primarily are based on observed animal distribution patterns and the correlation of these patterns with environmental variables, i.e. "data driven" models. Investigators have applied the latter technique to forecast changes in migration patterns with changes in the environment, for example, as might be expected under climate change, by forecasting how the underlying environmental data layers upon which the relationships are built will change over time. The learned geostatstical correlations are then applied to the modified data layers.. However, this is problematic. Even if the projections of how the underlying data layers will change are correct, it is not evident that the statistical relationships will remain the same, i.e. that the animal organism may not adapt its' behaviour to the changing conditions. Mechanistic models that explicitly take into account the physical, biological, and behaviour responses of an organism as well as the underlying changes in the landscape offer an alternative to address these shortcomings. The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies enable the application of the mechanistic models to predict how continental bird migration patterns may change in response to environmental change. In earlier work, we simulated the impact of effects of wetland loss and inter-annual variability on the fitness of

Multiclass cancer classification using a feature subset-based ensemble from microRNA expression profiles.

PubMed

Piao, Yongjun; Piao, Minghao; Ryu, Keun Ho

2017-01-01

Cancer classification has been a crucial topic of research in cancer treatment. In the last decade, messenger RNA (mRNA) expression profiles have been widely used to classify different types of cancers. With the discovery of a new class of small non-coding RNAs; known as microRNAs (miRNAs), various studies have shown that the expression patterns of miRNA can also accurately classify human cancers. Therefore, there is a great demand for the development of machine learning approaches to accurately classify various types of cancers using miRNA expression data. In this article, we propose a feature subset-based ensemble method in which each model is learned from a different projection of the original feature space to classify multiple cancers. In our method, the feature relevance and redundancy are considered to generate multiple feature subsets, the base classifiers are learned from each independent miRNA subset, and the average posterior probability is used to combine the base classifiers. To test the performance of our method, we used bead-based and sequence-based miRNA expression datasets and conducted 10-fold and leave-one-out cross validations. The experimental results show that the proposed method yields good results and has higher prediction accuracy than popular ensemble methods. The Java program and source code of the proposed method and the datasets in the experiments are freely available at https://sourceforge.net/projects/mirna-ensemble/. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sensory subtypes in children with autism spectrum disorder: latent profile transition analysis using a national survey of sensory features.

PubMed

Ausderau, Karla K; Furlong, Melissa; Sideris, John; Bulluck, John; Little, Lauren M; Watson, Linda R; Boyd, Brian A; Belger, Aysenil; Dickie, Virginia A; Baranek, Grace T

2014-08-01

Sensory features are highly prevalent and heterogeneous among children with ASD. There is a need to identify homogenous groups of children with ASD based on sensory features (i.e., sensory subtypes) to inform research and treatment. Sensory subtypes and their stability over 1 year were identified through latent profile transition analysis (LPTA) among a national sample of children with ASD. Data were collected from caregivers of children with ASD ages 2-12 years at two time points (Time 1 N = 1294; Time 2 N = 884). Four sensory subtypes (Mild; Sensitive-Distressed; Attenuated-Preoccupied; Extreme-Mixed) were identified, which were supported by fit indices from the LPTA as well as current theoretical models that inform clinical practice. The Mild and Extreme-Mixed subtypes reflected quantitatively different sensory profiles, while the Sensitive-Distressed and Attenuated-Preoccupied subtypes reflected qualitatively different profiles. Further, subtypes reflected differential child (i.e., gender, developmental age, chronological age, autism severity) and family (i.e., income, mother's education) characteristics. Ninety-one percent of participants remained stable in their subtypes over 1 year. Characterizing the nature of homogenous sensory subtypes may facilitate assessment and intervention, as well as potentially inform biological mechanisms. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.

Validation of the Substance Use Risk Profile Scale for Adolescents in Hong Kong

ERIC Educational Resources Information Center

Siu, Angela F. Y.

2011-01-01

This study examines the reliability and validity of a Chinese-translated version of the Substance Use Risk Profile Scale (SURPS) and explores the effect of gender and age on each of the subscales. The sensitivity of SURPS in differentiating substance users and nonusers using the SURPS is also investigated. Data were collected from a convenience…

Testing mechanistic models of growth in insects.

PubMed

Maino, James L; Kearney, Michael R

2015-11-22

Insects are typified by their small size, large numbers, impressive reproductive output and rapid growth. However, insect growth is not simply rapid; rather, insects follow a qualitatively distinct trajectory to many other animals. Here we present a mechanistic growth model for insects and show that increasing specific assimilation during the growth phase can explain the near-exponential growth trajectory of insects. The presented model is tested against growth data on 50 insects, and compared against other mechanistic growth models. Unlike the other mechanistic models, our growth model predicts energy reserves per biomass to increase with age, which implies a higher production efficiency and energy density of biomass in later instars. These predictions are tested against data compiled from the literature whereby it is confirmed that insects increase their production efficiency (by 24 percentage points) and energy density (by 4 J mg(-1)) between hatching and the attainment of full size. The model suggests that insects achieve greater production efficiencies and enhanced growth rates by increasing specific assimilation and increasing energy reserves per biomass, which are less costly to maintain than structural biomass. Our findings illustrate how the explanatory and predictive power of mechanistic growth models comes from their grounding in underlying biological processes. © 2015 The Author(s).

Featured Invention: Laser Scaling Device

NASA Technical Reports Server (NTRS)

Dunn, Carol Anne

2008-01-01

In September 2003, NASA signed a nonexclusive license agreement with Armor Forensics, a subsidiary of Armor Holdings, Inc., for the laser scaling device under the Innovative Partnerships Program. Coupled with a measuring program, also developed by NASA, the unit provides crime scene investigators with the ability to shoot photographs at scale without having to physically enter the scene, analyzing details such as bloodspatter patterns and graffiti. This ability keeps the scene's components intact and pristine for the collection of information and evidence. The laser scaling device elegantly solved a pressing problem for NASA's shuttle operations team and also provided industry with a useful tool. For NASA, the laser scaling device is still used to measure divots or damage to the shuttle's external tank and other structures around the launchpad. When the invention also met similar needs within industry, the Innovative Partnerships Program provided information to Armor Forensics for licensing and marketing the laser scaling device. Jeff Kohler, technology transfer agent at Kennedy, added, "We also invited a representative from the FBI's special photography unit to Kennedy to meet with Armor Forensics and the innovator. Eventually the FBI ended up purchasing some units. Armor Forensics is also beginning to receive interest from DoD [Department of Defense] for use in military crime scene investigations overseas."

Metabolic profiling reveals that time related physiological changes in mammalian cell perfusion cultures are bioreactor scale independent.

PubMed

Vernardis, Spyros I; Goudar, Chetan T; Klapa, Maria I

2013-09-01

Metabolic profiling was used to characterize the time course of cell physiology both in laboratory- and manufacturing-scale mammalian cell perfusion cultures. Two independent experiments were performed involving three vials from the same BHK cell bank, used to inoculate three laboratory-scale bioreactors, from which four manufacturing-scale cultures were initiated. It was shown that metabolomic analysis can indeed enhance the prime variable dataset for the monitoring of perfusion cultures by providing a higher resolution view of the metabolic state. Metabolic profiles could capture physiological state shifts over the course of the perfusion cultures and indicated a metabolic "signature" of the phase transitions, which was not observable from prime variable data. Specifically, the vast majority of metabolites had lower concentrations in the middle compared to the other two phases. Notably, metabolomics provided orthogonal (to prime variables) evidence that all cultures followed this same metabolic state shift with cell age, independently of bioreactor scale. © 2013 Elsevier Inc. All rights reserved.

[A method for obtaining redshifts of quasars based on wavelet multi-scaling feature matching].

PubMed

Liu, Zhong-Tian; Li, Xiang-Ru; Wu, Fu-Chao; Zhao, Yong-Heng

2006-09-01

The LAMOST project, the world's largest sky survey project being implemented in China, is expected to obtain 10(5) quasar spectra. The main objective of the present article is to explore methods that can be used to estimate the redshifts of quasar spectra from LAMOST. Firstly, the features of the broad emission lines are extracted from the quasar spectra to overcome the disadvantage of low signal-to-noise ratio. Then the redshifts of quasar spectra can be estimated by using the multi-scaling feature matching. The experiment with the 15, 715 quasars from the SDSS DR2 shows that the correct rate of redshift estimated by the method is 95.13% within an error range of 0. 02. This method was designed to obtain the redshifts of quasar spectra with relative flux and a low signal-to-noise ratio, which is applicable to the LAMOST data and helps to study quasars and the large-scale structure of the universe etc.

Theory and discretization of ideal magnetohydrodynamic equilibria with fractal pressure profiles

NASA Astrophysics Data System (ADS)

Kraus, B. F.; Hudson, S. R.

2017-09-01

In three-dimensional ideal magnetohydrodynamics, closed flux surfaces cannot maintain both rational rotational-transform and pressure gradients, as these features together produce unphysical, infinite currents. A proposed set of equilibria nullifies these currents by flattening the pressure on sufficiently wide intervals around each rational surface. Such rational surfaces exist at every scale, which characterizes the pressure profile as self-similar and thus fractal. The pressure profile is approximated numerically by considering a finite number of rational regions and analyzed mathematically by classifying the irrational numbers that support gradients into subsets. Applying these results to a given rotational-transform profile in cylindrical geometry, we find magnetic field and current density profiles compatible with the fractal pressure.

Scaling Features of High-Latitude Geomagnetic Field Fluctuations at Swarm Altitude: Impact of IMF Orientation

NASA Astrophysics Data System (ADS)

De Michelis, Paola; Consolini, Giuseppe; Tozzi, Roberta; Marcucci, Maria Federica

2017-10-01

This paper attempts to explore the statistical scaling features of high-latitude geomagnetic field fluctuations at Swarm altitude. Data for this study are low-resolution (1 Hz) magnetic data recorded by the vector field magnetometer on board Swarm A satellite over 1 year (from 15 April 2014 to 15 April 2015). The first- and second-order structure function scaling exponents and the degree of intermittency of the fluctuations of the intensity of the horizontal component of the magnetic field at high northern latitudes have been evaluated for different interplanetary magnetic field orientations in the GSM Y-Z plane and seasons. In the case of the first-order structure function scaling exponent, a comparison between the average spatial distributions of the obtained values and the statistical convection patterns obtained using a Super Dual Auroral Radar Network dynamic model (CS10 model) has been also considered. The obtained results support the idea that the knowledge of the scaling features of the geomagnetic field fluctuations can help in the characterization of the different ionospheric turbulence regimes of the medium crossed by Swarm A satellite. This study shows that different turbulent regimes of the geomagnetic field fluctuations exist in the regions characterized by a double-cell convection pattern and in those regions near the border of the convective structures.

Data-Science Analysis of the Macro-scale Features Governing the Corrosion to Crack Transition in AA7050-T7451

NASA Astrophysics Data System (ADS)

Co, Noelle Easter C.; Brown, Donald E.; Burns, James T.

2018-05-01

This study applies data science approaches (random forest and logistic regression) to determine the extent to which macro-scale corrosion damage features govern the crack formation behavior in AA7050-T7451. Each corrosion morphology has a set of corresponding predictor variables (pit depth, volume, area, diameter, pit density, total fissure length, surface roughness metrics, etc.) describing the shape of the corrosion damage. The values of the predictor variables are obtained from white light interferometry, x-ray tomography, and scanning electron microscope imaging of the corrosion damage. A permutation test is employed to assess the significance of the logistic and random forest model predictions. Results indicate minimal relationship between the macro-scale corrosion feature predictor variables and fatigue crack initiation. These findings suggest that the macro-scale corrosion features and their interactions do not solely govern the crack formation behavior. While these results do not imply that the macro-features have no impact, they do suggest that additional parameters must be considered to rigorously inform the crack formation location.

From patterns to emerging processes in mechanistic urban ecology.

PubMed

Shochat, Eyal; Warren, Paige S; Faeth, Stanley H; McIntyre, Nancy E; Hope, Diane

2006-04-01

Rapid urbanization has become an area of crucial concern in conservation owing to the radical changes in habitat structure and loss of species engendered by urban and suburban development. Here, we draw on recent mechanistic ecological studies to argue that, in addition to altered habitat structure, three major processes contribute to the patterns of reduced species diversity and elevated abundance of many species in urban environments. These activities, in turn, lead to changes in animal behavior, morphology and genetics, as well as in selection pressures on animals and plants. Thus, the key to understanding urban patterns is to balance studying processes at the individual level with an integrated examination of environmental forces at the ecosystem scale.

X-ray signatures: New time scales and spectral features

NASA Technical Reports Server (NTRS)

Boldt, E. A.

1977-01-01

The millisecond bursts from Cyg X-1 are investigated and the overall chaotic variability for the bulk of the Cyg X-1 emission is compared to that of Sco X-1, showing that the essential character is remarkably similar (i.e. shot noise) although the fundamental time scales involved differ widely, from a fraction of a second (for Cyg X-1) to a fraction of a day (for Sco X-1). Recent OSO-8 observations of spectra features attributable to iron are reviewed. In particular, line emission is discussed within the context of a model for thermal radiation by a hot evolved gas in systems as different as supernova remnants and clusters of galaxies. Newly observed spectral structure in the emission from the X-ray pulsar Her X-1 is reported.

Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts

PubMed Central

2016-01-01

We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obtained better results when performing the data preprocessing using the developed lexical resource. The resource includes dictionaries of slang words, contractions, abbreviations, and emoticons commonly used in social media. Each of the dictionaries was built for the English, Spanish, Dutch, and Italian languages. The resource is freely available. PMID:27795703

Feature integration, attention, and fixations during visual search.

PubMed

Khani, Abbas; Ordikhani-Seyedlar, Mehdi

2017-01-01

We argue that mechanistic premises of "item-based" theories are not invalidated by the fixation-based approach. We use item-based theories to propose an account that does not advocate strict serial item processing and integrates fixations. The main focus of this account is feature integration within fixations. We also suggest that perceptual load determines the size of the fixations.

Bridging paradigms: hybrid mechanistic-discriminative predictive models.

PubMed

Doyle, Orla M; Tsaneva-Atansaova, Krasimira; Harte, James; Tiffin, Paul A; Tino, Peter; Díaz-Zuccarini, Vanessa

2013-03-01

Many disease processes are extremely complex and characterized by multiple stochastic processes interacting simultaneously. Current analytical approaches have included mechanistic models and machine learning (ML), which are often treated as orthogonal viewpoints. However, to facilitate truly personalized medicine, new perspectives may be required. This paper reviews the use of both mechanistic models and ML in healthcare as well as emerging hybrid methods, which are an exciting and promising approach for biologically based, yet data-driven advanced intelligent systems.

Physiologically induced color-pattern changes in butterfly wings: mechanistic and evolutionary implications.

PubMed

Otaki, Joji M

2008-07-01

A mechanistic understanding of the butterfly wing color-pattern determination can be facilitated by experimental pattern changes. Here I review physiologically induced color-pattern changes in nymphalid butterflies and their mechanistic and evolutionary implications. A type of color-pattern change can be elicited by elemental changes in size and position throughout the wing, as suggested by the nymphalid groundplan. These changes of pattern elements are bi-directional and bi-sided dislocation toward or away from eyespot foci and in both proximal and distal sides of the foci. The peripheral elements are dislocated even in the eyespot-less compartments. Anterior spots are more severely modified, suggesting the existence of an anterior-posterior gradient. In one species, eyespots are transformed into white spots with remnant-like orange scales, and such patterns emerge even at the eyespot-less "imaginary" foci. A series of these color-pattern modifications probably reveal "snap-shots" of a dynamic morphogenic signal due to heterochronic uncoupling between the signaling and reception steps. The conventional gradient model can be revised to account for these observed color-pattern changes.

Evaluation of forest nutrition based on large-scale foliar surveys: are nutrition profiles the way of the future?

PubMed

Luyssaert, Sebastiaan; Sulkava, Mika; Raitio, Hannu; Hollmén, Jaakko

2004-02-01

This paper introduces the use of nutrition profiles as a first step in the development of a concept that is suitable for evaluating forest nutrition on the basis of large-scale foliar surveys. Nutrition profiles of a tree or stand were defined as the nutrient status, which accounts for all element concentrations, contents and interactions between two or more elements. Therefore a nutrition profile overcomes the shortcomings associated with the commonly used concepts for evaluating forest nutrition. Nutrition profiles can be calculated by means of a neural network, i.e. a self-organizing map, and an agglomerative clustering algorithm with pruning. As an example, nutrition profiles were calculated to describe the temporal variation in the mineral composition of Scots pine and Norway spruce needles in Finland between 1987 and 2000. The temporal trends in the frequency distribution of the nutrition profiles of Scots pine indicated that, between 1987 and 2000, the N, S, P, K, Ca, Mg and Al decreased, whereas the needle mass (NM) increased or remained unchanged. As there were no temporal trends in the frequency distribution of the nutrition profiles of Norway spruce, the mineral composition of the needles of Norway spruce needles subsequently did not change. Interpretation of the (lack of) temporal trends was outside the scope of this example. However, nutrition profiles prove to be a new and better concept for the evaluation of the mineral composition of large-scale surveys only when a biological interpretation of the nutrition profiles can be provided.

Dynamic and accurate assessment of acetaminophen-induced hepatotoxicity by integrated photoacoustic imaging and mechanistic biomarkers in vivo.

PubMed

Brillant, Nathalie; Elmasry, Mohamed; Burton, Neal C; Rodriguez, Josep Monne; Sharkey, Jack W; Fenwick, Stephen; Poptani, Harish; Kitteringham, Neil R; Goldring, Christopher E; Kipar, Anja; Park, B Kevin; Antoine, Daniel J

2017-10-01

The prediction and understanding of acetaminophen (APAP)-induced liver injury (APAP-ILI) and the response to therapeutic interventions is complex. This is due in part to sensitivity and specificity limitations of currently used assessment techniques. Here we sought to determine the utility of integrating translational non-invasive photoacoustic imaging of liver function with mechanistic circulating biomarkers of hepatotoxicity with histological assessment to facilitate the more accurate and precise characterization of APAP-ILI and the efficacy of therapeutic intervention. Perturbation of liver function and cellular viability was assessed in C57BL/6J male mice by Indocyanine green (ICG) clearance (Multispectral Optoacoustic Tomography (MSOT)) and by measurement of mechanistic (miR-122, HMGB1) and established (ALT, bilirubin) circulating biomarkers in response to the acetaminophen and its treatment with acetylcysteine (NAC) in vivo. We utilised a 60% partial hepatectomy model as a situation of defined hepatic functional mass loss to compared acetaminophen-induced changes to. Integration of these mechanistic markers correlated with histological features of APAP hepatotoxicity in a time-dependent manner. They accurately reflected the onset and recovery from hepatotoxicity compared to traditional biomarkers and also reported the efficacy of NAC with high sensitivity. ICG clearance kinetics correlated with histological scores for acute liver damage for APAP (i.e. 3h timepoint; r=0.90, P<0.0001) and elevations in both of the mechanistic biomarkers, miR-122 (e.g. 6h timepoint; r=0.70, P=0.005) and HMGB1 (e.g. 6h timepoint; r=0.56, P=0.04). For the first time we report the utility of this non-invasive longitudinal imaging approach to provide direct visualisation of the liver function coupled with mechanistic biomarkers, in the same animal, allowing the investigation of the toxicological and pharmacological aspects of APAP-ILI and hepatic regeneration. Copyright © 2017

Production of a national 1:1,000,000-scale hydrography dataset for the United States: feature selection, simplification, and refinement

USGS Publications Warehouse

Gary, Robin H.; Wilson, Zachary D.; Archuleta, Christy-Ann M.; Thompson, Florence E.; Vrabel, Joseph

2009-01-01

During 2006-09, the U.S. Geological Survey, in cooperation with the National Atlas of the United States, produced a 1:1,000,000-scale (1:1M) hydrography dataset comprising streams and waterbodies for the entire United States, including Puerto Rico and the U.S. Virgin Islands, for inclusion in the recompiled National Atlas. This report documents the methods used to select, simplify, and refine features in the 1:100,000-scale (1:100K) (1:63,360-scale in Alaska) National Hydrography Dataset to create the national 1:1M hydrography dataset. Custom tools and semi-automated processes were created to facilitate generalization of the 1:100K National Hydrography Dataset (1:63,360-scale in Alaska) to 1:1M on the basis of existing small-scale hydrography datasets. The first step in creating the new 1:1M dataset was to address feature selection and optimal data density in the streams network. Several existing methods were evaluated. The production method that was established for selecting features for inclusion in the 1:1M dataset uses a combination of the existing attributes and network in the National Hydrography Dataset and several of the concepts from the methods evaluated. The process for creating the 1:1M waterbodies dataset required a similar approach to that used for the streams dataset. Geometric simplification of features was the next step. Stream reaches and waterbodies indicated in the feature selection process were exported as new feature classes and then simplified using a geographic information system tool. The final step was refinement of the 1:1M streams and waterbodies. Refinement was done through the use of additional geographic information system tools.

Construct Validation of Analytic Rating Scales in a Speaking Assessment: Reporting a Score Profile and a Composite

ERIC Educational Resources Information Center

Sawaki, Yasuyo

2007-01-01

This is a construct validation study of a second language speaking assessment that reported a language profile based on analytic rating scales and a composite score. The study addressed three key issues: score dependability, convergent/discriminant validity of analytic rating scales and the weighting of analytic ratings in the composite score.…

Predicting lysine glycation sites using bi-profile bayes feature extraction.

PubMed

Ju, Zhe; Sun, Juhe; Li, Yanjie; Wang, Li

2017-12-01

Glycation is a nonenzymatic post-translational modification which has been found to be involved in various biological processes and closely associated with many metabolic diseases. The accurate identification of glycation sites is important to understand the underlying molecular mechanisms of glycation. As the traditional experimental methods are often labor-intensive and time-consuming, it is desired to develop computational methods to predict glycation sites. In this study, a novel predictor named BPB_GlySite is proposed to predict lysine glycation sites by using bi-profile bayes feature extraction and support vector machine algorithm. As illustrated by 10-fold cross-validation, BPB_GlySite achieves a satisfactory performance with a Sensitivity of 63.68%, a Specificity of 72.60%, an Accuracy of 69.63% and a Matthew's correlation coefficient of 0.3499. Experimental results also indicate that BPB_GlySite significantly outperforms three existing glycation sites predictors: NetGlycate, PreGly and Gly-PseAAC. Therefore, BPB_GlySite can be a useful bioinformatics tool for the prediction of glycation sites. A user-friendly web-server for BPB_GlySite is established at 123.206.31.171/BPB_GlySite/. Copyright © 2017 Elsevier Ltd. All rights reserved.

Model-Independent Phenotyping of C. elegans Locomotion Using Scale-Invariant Feature Transform

PubMed Central

Koren, Yelena; Sznitman, Raphael; Arratia, Paulo E.; Carls, Christopher; Krajacic, Predrag; Brown, André E. X.; Sznitman, Josué

2015-01-01

To uncover the genetic basis of behavioral traits in the model organism C. elegans, a common strategy is to study locomotion defects in mutants. Despite efforts to introduce (semi-)automated phenotyping strategies, current methods overwhelmingly depend on worm-specific features that must be hand-crafted and as such are not generalizable for phenotyping motility in other animal models. Hence, there is an ongoing need for robust algorithms that can automatically analyze and classify motility phenotypes quantitatively. To this end, we have developed a fully-automated approach to characterize C. elegans’ phenotypes that does not require the definition of nematode-specific features. Rather, we make use of the popular computer vision Scale-Invariant Feature Transform (SIFT) from which we construct histograms of commonly-observed SIFT features to represent nematode motility. We first evaluated our method on a synthetic dataset simulating a range of nematode crawling gaits. Next, we evaluated our algorithm on two distinct datasets of crawling C. elegans with mutants affecting neuromuscular structure and function. Not only is our algorithm able to detect differences between strains, results capture similarities in locomotory phenotypes that lead to clustering that is consistent with expectations based on genetic relationships. Our proposed approach generalizes directly and should be applicable to other animal models. Such applicability holds promise for computational ethology as more groups collect high-resolution image data of animal behavior. PMID:25816290

ACER Mathematics Profile Series: Number Test. (Test Booklet, Answer and Record Sheet, Score Key, and Teachers Handbook).

ERIC Educational Resources Information Center

Cornish, Greg; Wines, Robin

The Number Test of the ACER Mathematics Profile Series, contains 30 items, for each of three suggested grade levels: 7-8, 8-9, and 9-10. Raw scores on all tests in the ACER Mathematics Profile Series (Number, Operations, Space and Measurement) are converted to a common scale called MAPS, a major feature of the Series. Based on the Rasch Model,…

Theory and discretization of ideal magnetohydrodynamic equilibria with fractal pressure profiles

DOE PAGES

Kraus, B. F.; Hudson, S. R.

2017-09-29

In three-dimensional ideal magnetohydrodynamics, closed flux surfaces cannot maintain both rational rotational-transform and pressure gradients, as these features together produce unphysical, infinite currents. A proposed set of equilibria nullifies these currents by flattening the pressure on sufficiently wide intervals around each rational surface. Such rational surfaces exist at every scale, which characterizes the pressure profile as self-similar and thus fractal. The pressure profile is approximated numerically by considering a finite number of rational regions and analyzed mathematically by classifying the irrational numbers that support gradients into subsets. As a result, applying these results to a given rotational-transform profile in cylindricalmore » geometry, we find magnetic field and current density profiles compatible with the fractal pressure.« less

Theory and discretization of ideal magnetohydrodynamic equilibria with fractal pressure profiles

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

Kraus, B. F.; Hudson, S. R.

In three-dimensional ideal magnetohydrodynamics, closed flux surfaces cannot maintain both rational rotational-transform and pressure gradients, as these features together produce unphysical, infinite currents. A proposed set of equilibria nullifies these currents by flattening the pressure on sufficiently wide intervals around each rational surface. Such rational surfaces exist at every scale, which characterizes the pressure profile as self-similar and thus fractal. The pressure profile is approximated numerically by considering a finite number of rational regions and analyzed mathematically by classifying the irrational numbers that support gradients into subsets. As a result, applying these results to a given rotational-transform profile in cylindricalmore » geometry, we find magnetic field and current density profiles compatible with the fractal pressure.« less

Statistical evolution of quiet-Sun small-scale magnetic features using Sunrise observations

NASA Astrophysics Data System (ADS)

Anusha, L. S.; Solanki, S. K.; Hirzberger, J.; Feller, A.

2017-02-01

The evolution of small magnetic features in quiet regions of the Sun provides a unique window for probing solar magneto-convection. Here we analyze small-scale magnetic features in the quiet Sun, using the high resolution, seeing-free observations from the Sunrise balloon borne solar observatory. Our aim is to understand the contribution of different physical processes, such as splitting, merging, emergence and cancellation of magnetic fields to the rearrangement, addition and removal of magnetic flux in the photosphere. We have employed a statistical approach for the analysis and the evolution studies are carried out using a feature-tracking technique. In this paper we provide a detailed description of the feature-tracking algorithm that we have newly developed and we present the results of a statistical study of several physical quantities. The results on the fractions of the flux in the emergence, appearance, splitting, merging, disappearance and cancellation qualitatively agrees with other recent studies. To summarize, the total flux gained in unipolar appearance is an order of magnitude larger than the total flux gained in emergence. On the other hand, the bipolar cancellation contributes nearly an equal amount to the loss of magnetic flux as unipolar disappearance. The total flux lost in cancellation is nearly six to eight times larger than the total flux gained in emergence. One big difference between our study and previous similar studies is that, thanks to the higher spatial resolution of Sunrise, we can track features with fluxes as low as 9 × 1014 Mx. This flux is nearly an order of magnitude lower than the smallest fluxes of the features tracked in the highest resolution previous studies based on Hinode data. The area and flux of the magnetic features follow power-law type distribution, while the lifetimes show either power-law or exponential type distribution depending on the exact definitions used to define various birth and death events. We have

Copper-Catalysed Aminoboration of Vinylarenes with Hydroxylamine Esters-A Computational Mechanistic Study.

PubMed

Tobisch, Sven

2017-12-14

An in-depth computational probe of the copper-mediated formal aminoboration of β-alkylstyrenes with bis(pinacolato)diboron B 2 pin 2 and an archetype hydroxylamine ester by a dppbz-ligated {P^P}Cu I boryl catalyst (dppbz≡{P^P}≡1,2-bis(diphenylphosphino)benzene) is presented. This first comprehensive computational study of the copper-mediated formal aminoboration utilising an electrophilic strategy has identified the most accessible pathway for productive catalysis. The mechanistic picture derived from smooth energy profiles acquired by employing a reliable computational protocol applied to a realistic catalyst model conforms to all available experimental data. The high degree of regio- and stereoselectivity achieved in syn-borylcupration and Umpolung electrophilic amination is instrumental to the exclusive generation of the (syn)-β-aminoalkylborane product. On the one hand, syn-borylcupration furnishes exclusively β-borylalkylcopper nucleophile upon boryl addition onto the vinylarene β-carbon. Its subsequent approach by the hydroxylamine electrophile to deliver the product with the release of {P^P}Cu I benzoate favours a stepwise stereoretentive S N 2-type oxidative addition/N-C bond-forming reductive elimination sequence. The copper benzoate species represents the catalyst resting state, and its transformation into the catalytically active borylcopper species upon salt metathesis with Li(OtBu) base and transmetallation with B 2 pin 2 is turnover limiting. Electronically modified β-alkylstyrenes featuring a para-CF 3 substituted phenyl ring render the borylcupration faster, and more electron-rich hydroxylamine agents decelerate the electrophilic amination. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mechanistic study of manganese-substituted glycerol dehydrogenase using a kinetic and thermodynamic analysis.

PubMed

Fang, Baishan; Niu, Jin; Ren, Hong; Guo, Yingxia; Wang, Shizhen

2014-01-01

Mechanistic insights regarding the activity enhancement of dehydrogenase by metal ion substitution were investigated by a simple method using a kinetic and thermodynamic analysis. By profiling the binding energy of both the substrate and product, the metal ion's role in catalysis enhancement was revealed. Glycerol dehydrogenase (GDH) from Klebsiella pneumoniae sp., which demonstrated an improvement in activity by the substitution of a zinc ion with a manganese ion, was used as a model for the mechanistic study of metal ion substitution. A kinetic model based on an ordered Bi-Bi mechanism was proposed considering the noncompetitive product inhibition of dihydroxyacetone (DHA) and the competitive product inhibition of NADH. By obtaining preliminary kinetic parameters of substrate and product inhibition, the number of estimated parameters was reduced from 10 to 4 for a nonlinear regression-based kinetic parameter estimation. The simulated values of time-concentration curves fit the experimental values well, with an average relative error of 11.5% and 12.7% for Mn-GDH and GDH, respectively. A comparison of the binding energy of enzyme ternary complex for Mn-GDH and GDH derived from kinetic parameters indicated that metal ion substitution accelerated the release of dioxyacetone. The metal ion's role in catalysis enhancement was explicated.

Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

PubMed

Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

2016-09-01

We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. Copyright © 2016 Elsevier Ltd. All rights reserved.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

A mechanistic physicochemical model of carbon dioxide transport in blood.

PubMed

O'Neill, David P; Robbins, Peter A

2017-02-01

A number of mathematical models have been produced that, given the Pco 2 and Po 2 of blood, will calculate the total concentrations for CO 2 and O 2 in blood. However, all these models contain at least some empirical features, and thus do not represent all of the underlying physicochemical processes in an entirely mechanistic manner. The aim of this study was to develop a physicochemical model of CO 2 carriage by the blood to determine whether our understanding of the physical chemistry of the major chemical components of blood together with their interactions is sufficiently strong to predict the physiological properties of CO 2 carriage by whole blood. Standard values are used for the ionic composition of the blood, the plasma albumin concentration, and the hemoglobin concentration. All K m values required for the model are taken from the literature. The distribution of bicarbonate, chloride, and H + ions across the red blood cell membrane follows that of a Gibbs-Donnan equilibrium. The system of equations that results is solved numerically using constraints for mass balance and electroneutrality. The model reproduces the phenomena associated with CO 2 carriage, including the magnitude of the Haldane effect, very well. The structural nature of the model allows various hypothetical scenarios to be explored. Here we examine the effects of 1) removing the ability of hemoglobin to form carbamino compounds; 2) allowing a degree of Cl - binding to deoxygenated hemoglobin; and 3) removing the chloride (Hamburger) shift. The insights gained could not have been obtained from empirical models. This study is the first to incorporate a mechanistic model of chloride-bicarbonate exchange between the erythrocyte and plasma into a full physicochemical model of the carriage of carbon dioxide in blood. The mechanistic nature of the model allowed a theoretical study of the quantitative significance for carbon dioxide transport of carbamino compound formation; the putative binding

A mechanistic physicochemical model of carbon dioxide transport in blood

PubMed Central

O’Neill, David P.

2017-01-01

A number of mathematical models have been produced that, given the Pco2 and Po2 of blood, will calculate the total concentrations for CO2 and O2 in blood. However, all these models contain at least some empirical features, and thus do not represent all of the underlying physicochemical processes in an entirely mechanistic manner. The aim of this study was to develop a physicochemical model of CO2 carriage by the blood to determine whether our understanding of the physical chemistry of the major chemical components of blood together with their interactions is sufficiently strong to predict the physiological properties of CO2 carriage by whole blood. Standard values are used for the ionic composition of the blood, the plasma albumin concentration, and the hemoglobin concentration. All Km values required for the model are taken from the literature. The distribution of bicarbonate, chloride, and H+ ions across the red blood cell membrane follows that of a Gibbs-Donnan equilibrium. The system of equations that results is solved numerically using constraints for mass balance and electroneutrality. The model reproduces the phenomena associated with CO2 carriage, including the magnitude of the Haldane effect, very well. The structural nature of the model allows various hypothetical scenarios to be explored. Here we examine the effects of 1) removing the ability of hemoglobin to form carbamino compounds; 2) allowing a degree of Cl− binding to deoxygenated hemoglobin; and 3) removing the chloride (Hamburger) shift. The insights gained could not have been obtained from empirical models. NEW & NOTEWORTHY This study is the first to incorporate a mechanistic model of chloride-bicarbonate exchange between the erythrocyte and plasma into a full physicochemical model of the carriage of carbon dioxide in blood. The mechanistic nature of the model allowed a theoretical study of the quantitative significance for carbon dioxide transport of carbamino compound formation; the putative

Cosmology and astrophysics from relaxed galaxy clusters - III. Thermodynamic profiles and scaling relations

NASA Astrophysics Data System (ADS)

Mantz, A. B.; Allen, S. W.; Morris, R. G.; Schmidt, R. W.

2016-03-01

This is the third in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot (I.e. massive) in Papers I and II of this series. Here we consider the thermodynamics of the intracluster medium, in particular the profiles of density, temperature and related quantities, as well as integrated measurements of gas mass, average temperature, total luminosity and centre-excluded luminosity. We fit power-law scaling relations of each of these quantities as a function of redshift and cluster mass, which can be measured precisely and with minimal bias for these relaxed clusters using hydrostatic arguments. For the thermodynamic profiles, we jointly model the density and temperature and their intrinsic scatter as a function of radius, thus also capturing the behaviour of the gas pressure and entropy. For the integrated quantities, we also jointly fit a multidimensional intrinsic covariance. Our results reinforce the view that simple hydrodynamical models provide a good description of relaxed clusters outside their centres, but that additional heating and cooling processes are important in the inner regions (radii r ≲ 0.5 r2500 ≈ 0.15 r500). The thermodynamic profiles remain regular, with small intrinsic scatter, down to the smallest radii where deprojection is straightforward (˜20 kpc); within this radius, even the most relaxed systems show clear departures from spherical symmetry. Our results suggest that heating and cooling are continuously regulated in a tight feedback loop, allowing the cluster atmosphere to remain stratified on these scales.

Observed large-scale structures and diabatic heating and drying profiles during TWP-ICE

DOE PAGES

Xie, Shaocheng; Hume, Timothy; Jakob, Christian; ...

2010-01-01

This study documents the characteristics of the large-scale structures and diabatic heating and drying profiles observed during the Tropical Warm Pool–International Cloud Experiment (TWP-ICE), which was conducted in January–February 2006 in Darwin during the northern Australian monsoon season. The examined profiles exhibit significant variations between four distinct synoptic regimes that were observed during the experiment. The active monsoon period is characterized by strong upward motion and large advective cooling and moistening throughout the entire troposphere, while the suppressed and clear periods are dominated by moderate midlevel subsidence and significant low- to midlevel drying through horizontal advection. The midlevel subsidence andmore » horizontal dry advection are largely responsible for the dry midtroposphere observed during the suppressed period and limit the growth of clouds to low levels. During the break period, upward motion and advective cooling and moistening located primarily at midlevels dominate together with weak advective warming and drying (mainly from horizontal advection) at low levels. The variations of the diabatic heating and drying profiles with the different regimes are closely associated with differences in the large-scale structures, cloud types, and rainfall rates between the regimes. Strong diabatic heating and drying are seen throughout the troposphere during the active monsoon period while they are moderate and only occur above 700 hPa during the break period. The diabatic heating and drying tend to have their maxima at low levels during the suppressed periods. Furthermore, the diurnal variations of these structures between monsoon systems, continental/coastal, and tropical inland-initiated convective systems are also examined.« less

Emergent Global Patterns of Ecosystem Structure and Function from a Mechanistic General Ecosystem Model

PubMed Central

Emmott, Stephen; Hutton, Jon; Lyutsarev, Vassily; Smith, Matthew J.; Scharlemann, Jörn P. W.; Purves, Drew W.

2014-01-01

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures. PMID:24756001

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model.

PubMed

Harfoot, Michael B J; Newbold, Tim; Tittensor, Derek P; Emmott, Stephen; Hutton, Jon; Lyutsarev, Vassily; Smith, Matthew J; Scharlemann, Jörn P W; Purves, Drew W

2014-04-01

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures.

Productivity of "collisions generate heat" for reconciling an energy model with mechanistic reasoning: A case study

NASA Astrophysics Data System (ADS)

Scherr, Rachel E.; Robertson, Amy D.

2015-06-01

We observe teachers in professional development courses about energy constructing mechanistic accounts of energy transformations. We analyze a case in which teachers investigating adiabatic compression develop a model of the transformation of kinetic energy to thermal energy. Among their ideas is the idea that thermal energy is generated as a byproduct of individual particle collisions, which is represented in science education research literature as an obstacle to learning. We demonstrate that in this instructional context, the idea that individual particle collisions generate thermal energy is not an obstacle to learning, but instead is productive: it initiates intellectual progress. Specifically, this idea initiates the reconciliation of the teachers' energy model with mechanistic reasoning about adiabatic compression, and leads to a canonically correct model of the transformation of kinetic energy into thermal energy. We claim that the idea's productivity is influenced by features of our particular instructional context, including the instructional goals of the course, the culture of collaborative sense making, and the use of certain representations of energy.

Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes.

PubMed

Nelms, M D; Ates, G; Madden, J C; Vinken, M; Cronin, M T D; Rogiers, V; Enoch, S J

2015-05-01

This study outlines the analysis of 94 chemicals with repeat dose toxicity data taken from Scientific Committee on Consumer Safety opinions for commonly used hair dyes in the European Union. Structural similarity was applied to group these chemicals into categories. Subsequent mechanistic analysis suggested that toxicity to mitochondria is potentially a key driver of repeat dose toxicity for chemicals within each of the categories. The mechanistic hypothesis allowed for an in silico profiler consisting of four mechanism-based structural alerts to be proposed. These structural alerts related to a number of important chemical classes such as quinones, anthraquinones, substituted nitrobenzenes and aromatic azos. This in silico profiler is intended for grouping chemicals into mechanism-based categories within the adverse outcome pathway paradigm.

Strong orientation dependence of surface mass density profiles of dark haloes at large scales

NASA Astrophysics Data System (ADS)

Osato, Ken; Nishimichi, Takahiro; Oguri, Masamune; Takada, Masahiro; Okumura, Teppei

2018-06-01

We study the dependence of surface mass density profiles, which can be directly measured by weak gravitational lensing, on the orientation of haloes with respect to the line-of-sight direction, using a suite of N-body simulations. We find that, when major axes of haloes are aligned with the line-of-sight direction, surface mass density profiles have higher amplitudes than those averaged over all halo orientations, over all scales from 0.1 to 100 Mpc h-1 we studied. While the orientation dependence at small scales is ascribed to the halo triaxiality, our results indicate even stronger orientation dependence in the so-called two-halo regime, up to 100 Mpc h-1. The orientation dependence for the two-halo term is well approximated by a multiplicative shift of the amplitude and therefore a shift in the halo bias parameter value. The halo bias from the two-halo term can be overestimated or underestimated by up to ˜ 30 per cent depending on the viewing angle, which translates into the bias in estimated halo masses by up to a factor of 2 from halo bias measurements. The orientation dependence at large scales originates from the anisotropic halo-matter correlation function, which has an elliptical shape with the axis ratio of ˜0.55 up to 100 Mpc h-1. We discuss potential impacts of halo orientation bias on other observables such as optically selected cluster samples and a clustering analysis of large-scale structure tracers such as quasars.

Assessment of Error in Synoptic-Scale Diagnostics Derived from Wind Profiler and Radiosonde Network Data

NASA Technical Reports Server (NTRS)

Mace, Gerald G.; Ackerman, Thomas P.

1996-01-01

A topic of current practical interest is the accurate characterization of the synoptic-scale atmospheric state from wind profiler and radiosonde network observations. We have examined several related and commonly applied objective analysis techniques for performing this characterization and considered their associated level of uncertainty both from a theoretical and a practical standpoint. A case study is presented where two wind profiler triangles with nearly identical centroids and no common vertices produced strikingly different results during a 43-h period. We conclude that the uncertainty in objectively analyzed quantities can easily be as large as the expected synoptic-scale signal. In order to quantify the statistical precision of the algorithms, we conducted a realistic observing system simulation experiment using output from a mesoscale model. A simple parameterization for estimating the uncertainty in horizontal gradient quantities in terms of known errors in the objectively analyzed wind components and temperature is developed from these results.

Profiles of Personal Resiliency for Normative and Clinical Samples of Youth Assessed by the Resiliency Scales for Children and Adolescents[TM

ERIC Educational Resources Information Center

Prince-Embury, Sandra; Steer, Robert A.

2010-01-01

Cluster analyses with the three global scores of the Resiliency Scales for Children and Adolescents[TM] (RSCA) were used to determine personal resiliency profiles within normative (641) and outpatient clinical (285) samples of youth aged 9 to 18 years. Normative and clinical profiles were compared with each other and the clinical profiles were…

Putting the psychology back into psychological models: mechanistic versus rational approaches.

PubMed

Sakamoto, Yasuaki; Jones, Mattr; Love, Bradley C

2008-09-01

Two basic approaches to explaining the nature of the mind are the rational and the mechanistic approaches. Rational analyses attempt to characterize the environment and the behavioral outcomes that humans seek to optimize, whereas mechanistic models attempt to simulate human behavior using processes and representations analogous to those used by humans. We compared these approaches with regard to their accounts of how humans learn the variability of categories. The mechanistic model departs in subtle ways from rational principles. In particular, the mechanistic model incrementally updates its estimates of category means and variances through error-driven learning, based on discrepancies between new category members and the current representation of each category. The model yields a prediction, which we verify, regarding the effects of order manipulations that the rational approach does not anticipate. Although both rational and mechanistic models can successfully postdict known findings, we suggest that psychological advances are driven primarily by consideration of process and representation and that rational accounts trail these breakthroughs.

Integrating depth functions and hyper-scale terrain analysis for 3D soil organic carbon modeling in agricultural fields at regional scale

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, L.; van Wesemael, B.; Stevens, A.; Doetterl, S.; Van Oost, K.; Behrens, T.; Schmidt, K.

2012-04-01

Soil Organic Carbon (SOC) represents a key component in the global C cycle and has an important influence on the global CO2 fluxes between terrestrial biosphere and atmosphere. In the context of agricultural landscapes, SOC inventories are important since soil management practices have a strong influence on CO2 fluxes and SOC stocks. However, there is lack of accurate and cost-effective methods for producing high spatial resolution of SOC information. In this respect, our work is focused on the development of a three dimensional modeling approach for SOC monitoring in agricultural fields. The study area comprises ~420 km2 and includes 4 of the 5 agro-geological regions of the Grand-Duchy of Luxembourg. The soil dataset consist of 172 profiles (1033 samples) which were not sampled specifically for this study. This dataset is a combination of profile samples collected in previous soil surveys and soil profiles sampled for other research purposes. The proposed strategy comprises two main steps. In the first step the SOC distribution within each profile (vertical distribution) is modeled. Depth functions for are fitted in order to summarize the information content in the profile. By using these functions the SOC can be interpolated at any depth within the profiles. The second step involves the use of contextual terrain (ConMap) features (Behrens et al., 2010). These features are based on the differences in elevation between a given point location in the landscape and its circular neighbourhoods at a given set of different radius. One of the main advantages of this approach is that it allows the integration of several spatial scales (eg. local and regional) for soil spatial analysis. In this work the ConMap features are derived from a digital elevation model of the area and are used as predictors for spatial modeling of the parameters of the depth functions fitted in the previous step. In this poster we present some preliminary results in which we analyze: i. The use of

Mechanistic species distribution modelling as a link between physiology and conservation.

PubMed

Evans, Tyler G; Diamond, Sarah E; Kelly, Morgan W

2015-01-01

Climate change conservation planning relies heavily on correlative species distribution models that estimate future areas of occupancy based on environmental conditions encountered in present-day ranges. The approach benefits from rapid assessment of vulnerability over a large number of organisms, but can have poor predictive power when transposed to novel environments and reveals little in the way of causal mechanisms that define changes in species distribution or abundance. Having conservation planning rely largely on this single approach also increases the risk of policy failure. Mechanistic models that are parameterized with physiological information are expected to be more robust when extrapolating distributions to future environmental conditions and can identify physiological processes that set range boundaries. Implementation of mechanistic species distribution models requires knowledge of how environmental change influences physiological performance, and because this information is currently restricted to a comparatively small number of well-studied organisms, use of mechanistic modelling in the context of climate change conservation is limited. In this review, we propose that the need to develop mechanistic models that incorporate physiological data presents an opportunity for physiologists to contribute more directly to climate change conservation and advance the field of conservation physiology. We begin by describing the prevalence of species distribution modelling in climate change conservation, highlighting the benefits and drawbacks of both mechanistic and correlative approaches. Next, we emphasize the need to expand mechanistic models and discuss potential metrics of physiological performance suitable for integration into mechanistic models. We conclude by summarizing other factors, such as the need to consider demography, limiting broader application of mechanistic models in climate change conservation. Ideally, modellers, physiologists and

Extracting body image symptom dimensions among eating disorder patients: the Profile Analysis via Multidimensional Scaling (PAMS) approach.

PubMed

Olatunji, Bunmi O; Kim, Se-Kang; Wall, David

2015-09-01

The present study employs Profile Analysis via Multidimensional Scaling (PAMS), a procedure for extracting dimensions, in order to identify core eating disorder symptoms in a clinical sample. A large sample of patients with eating disorders (N=5193) presenting for treatment completed the Eating Disorders Inventory-2 (EDI-2; Garner, 1991), and PAMS was then employed to estimate individual profile weights that reflect the degree to which an individual's observed symptom profile approximates the pattern of the dimensions. The findings revealed three symptom dimensions: Body Thinness, Body Perfectionism, and Body Awareness. Subsequent analysis using individual level data illustrate that the PAMS profiles properly operate as prototypical profiles that encapsulate all individuals' response patterns. The implications of these dimensional findings for the assessment and diagnosis of eating disorders are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computer-aided mass detection in mammography: False positive reduction via gray-scale invariant ranklet texture features

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

Masotti, Matteo; Lanconelli, Nico; Campanini, Renato

In this work, gray-scale invariant ranklet texture features are proposed for false positive reduction (FPR) in computer-aided detection (CAD) of breast masses. Two main considerations are at the basis of this proposal. First, false positive (FP) marks surviving our previous CAD system seem to be characterized by specific texture properties that can be used to discriminate them from masses. Second, our previous CAD system achieves invariance to linear/nonlinear monotonic gray-scale transformations by encoding regions of interest into ranklet images through the ranklet transform, an image transformation similar to the wavelet transform, yet dealing with pixels' ranks rather than with theirmore » gray-scale values. Therefore, the new FPR approach proposed herein defines a set of texture features which are calculated directly from the ranklet images corresponding to the regions of interest surviving our previous CAD system, hence, ranklet texture features; then, a support vector machine (SVM) classifier is used for discrimination. As a result of this approach, texture-based information is used to discriminate FP marks surviving our previous CAD system; at the same time, invariance to linear/nonlinear monotonic gray-scale transformations of the new CAD system is guaranteed, as ranklet texture features are calculated from ranklet images that have this property themselves by construction. To emphasize the gray-scale invariance of both the previous and new CAD systems, training and testing are carried out without any in-between parameters' adjustment on mammograms having different gray-scale dynamics; in particular, training is carried out on analog digitized mammograms taken from a publicly available digital database, whereas testing is performed on full-field digital mammograms taken from an in-house database. Free-response receiver operating characteristic (FROC) curve analysis of the two CAD systems demonstrates that the new approach achieves a higher reduction of FP

The substance use risk profile scale: a scale measuring traits linked to reinforcement-specific substance use profiles.

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

Woicik, P.A.; Stewart, S.H.; Pihl, R.O.

The Substance Use Risk Profile Scale (SURPS) is based on a model of personality risk for substance abuse in which four personality dimensions (hopelessness, anxiety sensitivity, impulsivity, and sensation seeking) are hypothesized to differentially relate to specific patterns of substance use. The current series of studies is a preliminary exploration of the psychometric properties of the SURPS in two populations (undergraduate and high school students). In study 1, an analysis of the internal structure of two versions of the SURPS shows that the abbreviated version best reflects the 4-factor structure. Concurrent, discriminant, and incremental validity of the SURPS is supportedmore » by convergent/divergent relationships between the SURPS subscales and other theoretically relevant personality and drug use criterion measures. In Study 2, the factorial structure of the SURPS is confirmed and evidence is provided for its test-retest reliability and validity with respect to measuring personality vulnerability to reinforcement-specific substance use patterns. In Study 3, the SURPS was administered in a more youthful population to test its sensitivity in identifying younger problematic drinkers. The results from the current series of studies demonstrate support for the reliability and construct validity of the SURPS, and suggest that four personality dimensions may be linked to substance-related behavior through different reinforcement processes. This brief assessment tool may have important implications for clinicians and future research.« less

The Substance Use Risk Profile Scale: a scale measuring traits linked to reinforcement-specific substance use profiles.

PubMed

Woicik, Patricia A; Stewart, Sherry H; Pihl, Robert O; Conrod, Patricia J

2009-12-01

The Substance Use Risk Profile Scale (SURPS) is based on a model of personality risk for substance abuse in which four personality dimensions (hopelessness, anxiety sensitivity, impulsivity, and sensation seeking) are hypothesized to differentially relate to specific patterns of substance use. The current series of studies is a preliminary exploration of the psychometric properties of the SURPS in two populations (undergraduate and high school students). In study 1, an analysis of the internal structure of two versions of the SURPS shows that the abbreviated version best reflects the 4-factor structure. Concurrent, discriminant, and incremental validity of the SURPS is supported by convergent/divergent relationships between the SURPS subscales and other theoretically relevant personality and drug use criterion measures. In Study 2, the factorial structure of the SURPS is confirmed and evidence is provided for its test-retest reliability and validity with respect to measuring personality vulnerability to reinforcement-specific substance use patterns. In Study 3, the SURPS was administered in a more youthful population to test its sensitivity in identifying younger problematic drinkers. The results from the current series of studies demonstrate support for the reliability and construct validity of the SURPS, and suggest that four personality dimensions may be linked to substance-related behavior through different reinforcement processes. This brief assessment tool may have important implications for clinicians and future research.

Geomorphometric multi-scale analysis for the recognition of Moon surface features using multi-resolution DTMs

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Jianping; Sofia, Giulia; Tarolli, Paolo

2014-05-01

Moon surface features have great significance in understanding and reconstructing the lunar geological evolution. Linear structures like rilles and ridges are closely related to the internal forced tectonic movement. The craters widely distributed on the moon are also the key research targets for external forced geological evolution. The extremely rare availability of samples and the difficulty for field works make remote sensing the most important approach for planetary studies. New and advanced lunar probes launched by China, U.S., Japan and India provide nowadays a lot of high-quality data, especially in the form of high-resolution Digital Terrain Models (DTMs), bringing new opportunities and challenges for feature extraction on the moon. The aim of this study is to recognize and extract lunar features using geomorphometric analysis based on multi-scale parameters and multi-resolution DTMs. The considered digital datasets include CE1-LAM (Chang'E One, Laser AltiMeter) data with resolution of 500m/pix, LRO-WAC (Lunar Reconnaissance Orbiter, Wide Angle Camera) data with resolution of 100m/pix, LRO-LOLA (Lunar Reconnaissance Orbiter, Lunar Orbiter Laser Altimeter) data with resolution of 60m/pix, and LRO-NAC (Lunar Reconnaissance Orbiter, Narrow Angle Camera) data with resolution of 2-5m/pix. We considered surface derivatives to recognize the linear structures including Rilles and Ridges. Different window scales and thresholds for are considered for feature extraction. We also calculated the roughness index to identify the erosion/deposits area within craters. The results underline the suitability of the adopted methods for feature recognition on the moon surface. The roughness index is found to be a useful tool to distinguish new craters, with higher roughness, from the old craters, which present a smooth and less rough surface.

A Divergent Mechanistic Course of Pd(0)-Catalyzed Aza-Claisen Rearrangement and Aza-Rautenstrauch-Type Cyclization of N-Allyl-Ynamides

PubMed Central

DeKorver, Kyle A.; Hsung, Richard P.; Lohse, Andrew G.; Zhang, Yu

2010-01-01

A fascinating mechanistic study of ynamido-palladium-π-allyl complexes is described that features isolation of a unique silyl-ketenimine via aza-Claisen rearrangement, which can be accompanied by an unusual thermal N-to-C 1,3-Ts shift in the formation of tertiary nitriles, and a novel cyclopentenimine formation via a palladium catalyzed aza-Rautenstrauch-type cyclization pathway. PMID:20337418

Extraction of Molecular Features through Exome to Transcriptome Alignment

PubMed Central

Mudvari, Prakriti; Kowsari, Kamran; Cole, Charles; Mazumder, Raja; Horvath, Anelia

2014-01-01

Integrative Next Generation Sequencing (NGS) DNA and RNA analyses have very recently become feasible, and the published to date studies have discovered critical disease implicated pathways, and diagnostic and therapeutic targets. A growing number of exomes, genomes and transcriptomes from the same individual are quickly accumulating, providing unique venues for mechanistic and regulatory features analysis, and, at the same time, requiring new exploration strategies. In this study, we have integrated variation and expression information of four NGS datasets from the same individual: normal and tumor breast exomes and transcriptomes. Focusing on SNPcentered variant allelic prevalence, we illustrate analytical algorithms that can be applied to extract or validate potential regulatory elements, such as expression or growth advantage, imprinting, loss of heterozygosity (LOH), somatic changes, and RNA editing. In addition, we point to some critical elements that might bias the output and recommend alternative measures to maximize the confidence of findings. The need for such strategies is especially recognized within the growing appreciation of the concept of systems biology: integrative exploration of genome and transcriptome features reveal mechanistic and regulatory insights that reach far beyond linear addition of the individual datasets. PMID:24791251

Noncircular features in Saturn's rings IV: Absolute radius scale and Saturn's pole direction

NASA Astrophysics Data System (ADS)

French, Richard G.; McGhee-French, Colleen A.; Lonergan, Katherine; Sepersky, Talia; Jacobson, Robert A.; Nicholson, Philip D.; Hedman, Mathew M.; Marouf, Essam A.; Colwell, Joshua E.

2017-07-01

We present a comprehensive solution for the geometry of Saturn's ring system, based on orbital fits to an extensive set of occultation observations of 122 individual ring edges and gaps. We begin with a restricted set of very high quality Cassini VIMS, UVIS, and RSS measurements for quasi-circular features in the C and B rings and the Cassini Division, and then successively add suitably weighted additional Cassini and historical occultation measurements (from Voyager, HST and the widely-observed 28 Sgr occultation of 3 Jul 1989) for additional non-circular features, to derive an absolute radius scale applicable across the entire classical ring system. As part of our adopted solution, we determine first-order corrections to the spacecraft trajectories used to determine the geometry of individual occultation chords. We adopt a simple linear model for Saturn's precession, and our favored solution yields a precession rate on the sky n^˙P = 0.207 ± 0 .006‧‧yr-1 , equivalent to an angular rate of polar motion ΩP = 0.451 ± 0 .014‧‧yr-1 . The 3% formal uncertainty in the fitted precession rate is approaching the point where it can provide a useful constraint on models of Saturn's interior, although realistic errors are likely to be larger, given the linear approximation of the precession model and possible unmodeled systematic errors in the spacecraft ephemerides. Our results are largely consistent with independent estimates of the precession rate based on historical RPX times (Nicholson et al., 1999 AAS/Division for Planetary Sciences Meeting Abstracts #31 31, 44.01) and from theoretical expectations that account for Titan's 700-yr precession period (Vienne and Duriez 1992, Astronomy and Astrophysics 257, 331-352). The fitted precession rate based on Cassini data only is somewhat lower, which may be an indication of unmodeled shorter term contributions to Saturn's polar motion from other satellites, or perhaps the result of inconsistencies in the assumed

Channel microband electrode arrays for mechanistic electrochemistry. Two-dimensional voltammetry:  transport-limited currents.

PubMed

Alden, J A; Feldman, M A; Hill, E; Prieto, F; Oyama, M; Coles, B A; Compton, R G; Dobson, P J; Leigh, P A

1998-05-01

A channel electrode array, with electrodes ranging in size from the millimeter to the submicrometer scale, is used for the amperometric interrogation of mechanistically complex electrode processes. In this way, the transport-limited current, measured as a function of both electrode size and electrolyte flow rate (convection), is shown to provide a highly sensitive probe of mechanism and kinetics. The application of "two-dimensional voltammetry" to diverse electrode processes, including E, ECE, ECEE, EC', and DISP2 reactions, is reported.

Using the Personality Assessment Inventory Antisocial and Borderline Features Scales to Predict Behavior Change.

PubMed

Penson, Brittany N; Ruchensky, Jared R; Morey, Leslie C; Edens, John F

2016-11-01

A substantial amount of research has examined the developmental trajectory of antisocial behavior and, in particular, the relationship between antisocial behavior and maladaptive personality traits. However, research typically has not controlled for previous behavior (e.g., past violence) when examining the utility of personality measures, such as self-report scales of antisocial and borderline traits, in predicting future behavior (e.g., subsequent violence). Examination of the potential interactive effects of measures of both antisocial and borderline traits also is relatively rare in longitudinal research predicting adverse outcomes. The current study utilizes a large sample of youthful offenders ( N = 1,354) from the Pathways to Desistance project to examine the separate effects of the Personality Assessment Inventory Antisocial Features (ANT) and Borderline Features (BOR) scales in predicting future offending behavior as well as trends in other negative outcomes (e.g., substance abuse, violence, employment difficulties) over a 1-year follow-up period. In addition, an ANT × BOR interaction term was created to explore the predictive effects of secondary psychopathy. ANT and BOR both explained unique variance in the prediction of various negative outcomes even after controlling for past indicators of those same behaviors during the preceding year.

An item response theory analysis of Harter's Self-Perception Profile for children or why strong clinical scales should be distrusted.

PubMed

Egberink, Iris J L; Meijer, Rob R

2011-06-01

The authors investigated the psychometric properties of the subscales of the Self-Perception Profile for Children with item response theory (IRT) models using a sample of 611 children. Results from a nonparametric Mokken analysis and a parametric IRT approach for boys (n = 268) and girls (n = 343) were compared. The authors found that most scales formed weak scales and that measurement precision was relatively low and only present for latent trait values indicating low self-perception. The subscales Physical Appearance and Global Self-Worth formed one strong scale. Children seem to interpret Global Self-Worth items as if they measure Physical Appearance. Furthermore, the authors found that strong Mokken scales (such as Global Self-Worth) consisted mostly of items that repeat the same item content. They conclude that researchers should be very careful in interpreting the total scores on the different Self-Perception Profile for Children scales. Finally, implications for further research are discussed.

[FEATURES OF MASS-SPECTROMETRIC PROTEIN PROFILES OF STRAINS OF BRUCELLOSIS CAUSATIVE AGENT DURING PREPARATION OF CULTURE ON VARIOUS NUTRIENT MEDIA].

PubMed

Ulshina, D V; Kovalev, D A; Zhirov, A M; Zharinova, N V; Khudoleev, A A; Kogotkova, O I; Efremenko, V I; Evchenko, N I; Kulichenko, A N

2016-01-01

Carry out comparative analysis using time-of-flight mass-spectrometry with matrix laser desorption/ionization (MALDI-TOF MS) of protein profiles of brucellosis causative agents (Brucella melitensis Rev-1 and Brucella abortus 19BA), cultivated in various nutrient media: Albimi agar, brucellagar and erythrit-agar. Vaccine,strains: Brucella melitensis Rev-1 and Brucella abortus 19BA. Protein profiling in linear mode on Microflex "Bruker Daltonics" MALDI-TOF mass-spectrometer. A number of characteristic features of brucella mass-spectra was detected: in particular, preservation of the total qualitative composition of protein profiles of cultures and significant differences in the intensity of separate peaks depending on the nutrient medium used. Based on the analysis of the data obtained, use of Albimi agar as the nutrient medium for preparation of brucella culture samples for mass-spectrometric analysis was shown to be optimal.

GPU based 3D feature profile simulation of high-aspect ratio contact hole etch process under fluorocarbon plasmas

NASA Astrophysics Data System (ADS)

Chun, Poo-Reum; Lee, Se-Ah; Yook, Yeong-Geun; Choi, Kwang-Sung; Cho, Deog-Geun; Yu, Dong-Hun; Chang, Won-Seok; Kwon, Deuk-Chul; Im, Yeon-Ho

2013-09-01

Although plasma etch profile simulation has been attracted much interest for developing reliable plasma etching, there still exist big gaps between current research status and predictable modeling due to the inherent complexity of plasma process. As an effort to address this issue, we present 3D feature profile simulation coupled with well-defined plasma-surface kinetic model for silicon dioxide etching process under fluorocarbon plasmas. To capture the realistic plasma surface reaction behaviors, a polymer layer based surface kinetic model was proposed to consider the simultaneous polymer deposition and oxide etching. Finally, the realistic plasma surface model was used for calculation of speed function for 3D topology simulation, which consists of multiple level set based moving algorithm, and ballistic transport module. In addition, the time consumable computations in the ballistic transport calculation were improved drastically by GPU based numerical computation, leading to the real time computation. Finally, we demonstrated that the surface kinetic model could be coupled successfully for 3D etch profile simulations in high-aspect ratio contact hole plasma etching.

Flow-mediated dilation: can new approaches provide greater mechanistic insight into vascular dysfunction in preeclampsia and other diseases?

PubMed

Weissgerber, Tracey L

2014-11-01

Endothelial dysfunction is a key feature of preeclampsia and may contribute to increased cardiovascular disease risk years after pregnancy. Flow-mediated dilation (FMD) is a non-invasive endothelial function test that predicts cardiovascular event risk. New protocols allow researchers to measure three components of the FMD response: FMD, low flow-mediated constriction, and shear stimulus. This review encourages researchers to think beyond "low FMD" by examining how these three components may provide additional insights into the mechanisms and location of vascular dysfunction. The review then examines what FMD studies reveal about vascular dysfunction in preeclampsia while highlighting opportunities to gain greater mechanistic insight from new protocols. Studies using traditional protocols show that FMD is low in mid-pregnancy prior to preeclampsia, at diagnosis, and for 3 years post-partum. However, FMD returns to normal by 10 years post-partum. Studies using new protocols are needed to gain more mechanistic insight.

Plasma amino acid and urine organic acid profiles of Filipino patients with maple syrup urine disease (MSUD) and correlation with their neurologic features.

PubMed

Chiong, Mary Anne D; Tan, Marilyn A; Cordero, Cynthia P; Fodra, Esphie Grace D; Manliguis, Judy S; Lopez, Cristine P; Dalmacio, Leslie Michelle M

2016-12-01

Maple syrup urine disease (MSUD) is the most common inborn error of metabolism in the country. The cause of the neuropathology is still not well established although accumulation of branched chain amino acids (BCAA) and alteration in large neutral amino acids (LNAA) as well as energy deprivation are suggested. It is therefore the aim of this study to determine the plasma amino acid and urine organic acid profiles of patients with MSUD and correlate the findings with their neurologic features. Twenty six Filipino patients with MSUD were studied in terms of their plasma amino acid and urine organic acid profiles. Their results were compared with 26 age and sex matched controls. The neurologic features were correlated with the results of the plasma amino acids and urine organic acids. Majority of the patients with MSUD had developmental delay/intellectual disability (88%), speech delay (69%), and seizures (65%). Their amino acid profiles revealed low glutamine and alanine with high levels of leucine, isoleucine, phenylalanine, threonine and alloisoleucine compared to controls (p < 0.05). The urine organic acids showed significantly elevated excretion of the branched chain ketoacids and succinate (p < 0.05). However there were no biochemical markers that correlated significantly with the neurologic features. The findings suggest that there could still be altered LNAA metabolism among patients with MSUD when the BCAAs are elevated. Although the biochemical findings were not significantly correlated with the neurologic features, the study showed that prevention and avoidance of neurologic disturbances may still rely primarily on early diagnosis and prompt institution of treatment, along with strict compliance with the dietary regimen and maintenance of good metabolic control over time.

Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach

NASA Astrophysics Data System (ADS)

Dorrestijn, Jesse; Kahn, Brian H.; Teixeira, João; Irion, Fredrick W.

2018-05-01

Satellite observations are used to obtain vertical profiles of variance scaling of temperature (T) and specific humidity (q) in the atmosphere. A higher spatial resolution nadir retrieval at 13.5 km complements previous Atmospheric Infrared Sounder (AIRS) investigations with 45 km resolution retrievals and enables the derivation of power law scaling exponents to length scales as small as 55 km. We introduce a variable-sized circular-area Monte Carlo methodology to compute exponents instantaneously within the swath of AIRS that yields additional insight into scaling behavior. While this method is approximate and some biases are likely to exist within non-Gaussian portions of the satellite observational swaths of T and q, this method enables the estimation of scale-dependent behavior within instantaneous swaths for individual tropical and extratropical systems of interest. Scaling exponents are shown to fluctuate between β = -1 and -3 at scales ≥ 500 km, while at scales ≤ 500 km they are typically near β ≈ -2, with q slightly lower than T at the smallest scales observed. In the extratropics, the large-scale β is near -3. Within the tropics, however, the large-scale β for T is closer to -1 as small-scale moist convective processes dominate. In the tropics, q exhibits large-scale β between -2 and -3. The values of β are generally consistent with previous works of either time-averaged spatial variance estimates, or aircraft observations that require averaging over numerous flight observational segments. The instantaneous variance scaling methodology is relevant for cloud parameterization development and the assessment of time variability of scaling exponents.

Linking spring phenology with mechanistic models of host movement to predict disease transmission risk

USGS Publications Warehouse

Merkle, Jerod A.; Cross, Paul C.; Scurlock, Brandon M.; Cole, Eric K.; Courtemanch, Alyson B.; Dewey, Sarah R.; Kauffman, Matthew J.

2018-01-01

Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission.Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [Cervus Canadensis] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem.Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts.Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands.Synthesis and applications. Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate

Spatial Scaling of the Profile of Selective Attention in the Visual Field.

PubMed

Gannon, Matthew A; Knapp, Ashley A; Adams, Thomas G; Long, Stephanie M; Parks, Nathan A

2016-01-01

Neural mechanisms of selective attention must be capable of adapting to variation in the absolute size of an attended stimulus in the ever-changing visual environment. To date, little is known regarding how attentional selection interacts with fluctuations in the spatial expanse of an attended object. Here, we use event-related potentials (ERPs) to investigate the scaling of attentional enhancement and suppression across the visual field. We measured ERPs while participants performed a task at fixation that varied in its attentional demands (attentional load) and visual angle (1.0° or 2.5°). Observers were presented with a stream of task-relevant stimuli while foveal, parafoveal, and peripheral visual locations were probed by irrelevant distractor stimuli. We found two important effects in the N1 component of visual ERPs. First, N1 modulations to task-relevant stimuli indexed attentional selection of stimuli during the load task and further correlated with task performance. Second, with increased task size, attentional modulation of the N1 to distractor stimuli showed a differential pattern that was consistent with a scaling of attentional selection. Together, these results demonstrate that the size of an attended stimulus scales the profile of attentional selection across the visual field and provides insights into the attentional mechanisms associated with such spatial scaling.

"Ratio via Machina": Three Standards of Mechanistic Explanation in Sociology

ERIC Educational Resources Information Center

Aviles, Natalie B.; Reed, Isaac Ariail

2017-01-01

Recently, sociologists have expended much effort in attempts to define social mechanisms. We intervene in these debates by proposing that sociologists in fact have a choice to make between three standards of what constitutes a good mechanistic explanation: substantial, formal, and metaphorical mechanistic explanation. All three standards are…

A new mechanistic framework to predict OCS fluxes in soils

NASA Astrophysics Data System (ADS)

Sauze, Joana; Ogee, Jérôme; Launois, Thomas; Kesselmeier, Jürgen; Van Diest, Heidi; Wingate, Lisa

2015-04-01

A better description of the amplitude of photosynthetic and respiratory gross CO2 fluxes at large scales is needed to improve our predictions of the current and future global CO2 cycle. Carbonyl sulfide (COS) is the most abundant sulphur gas in the atmosphere and has been proposed as a new tracer of gross photosynthesis, as the uptake of COS from the atmosphere is dominated by the activity of carbonic anhydrase (CA), an enzyme abundant in leaves that also catalyses CO2 hydration during photosynthesis. However, soils also exchange COS with the atmosphere and there is growing evidence that this flux must also be accounted for in atmospheric budgets. In this context a new mechanistic description of soil-atmosphere COS exchange is clearly needed. Soils can take up COS from the atmosphere as the soil biota also contain CA, and COS emissions from soils have also been reported in agricultural fields or anoxic soils. Previous studies have also shown that soil COS fluxes present an optimum soil water content and soil temperature. Here we propose a new mechanistic framework to predict the fluxes of COS between the soils and the atmosphere. We describe the COS soil budget by a first-order reaction-diffusion-production equation, assuming that the hydrolysis of COS by CA is total and irreversible. To describe COS diffusion through the soil matrix, we use different formulations of soil air-filled pore space and temperature, depending on the turbulence level above the soil surface. Using this model we are able to explain the observed presence of an optimum temperature for soil COS uptake and show how this optimum can shift to cooler temperatures in the presence of soil COS emissions. Our model can also explain the observed optimum with soil moisture content previously described in the literature (e.g. Van Diest & Kesselmeier, 2008) as a result of diffusional constraints on COS hydrolysis. These diffusional constraints are also responsible for the response of COS uptake to soil

Profiling medical school learning environments in Malaysia: a validation study of the Johns Hopkins Learning Environment Scale.

PubMed

Tackett, Sean; Bakar, Hamidah Abu; Shilkofski, Nicole A; Coady, Niamh; Rampal, Krishna; Wright, Scott

2015-01-01

While a strong learning environment is critical to medical student education, the assessment of medical school learning environments has confounded researchers. Our goal was to assess the validity and utility of the Johns Hopkins Learning Environment Scale (JHLES) for preclinical students at three Malaysian medical schools with distinct educational and institutional models. Two schools were new international partnerships, and the third was school leaver program established without international partnership. First- and second-year students responded anonymously to surveys at the end of the academic year. The surveys included the JHLES, a 28-item survey using five-point Likert scale response options, the Dundee Ready Educational Environment Measure (DREEM), the most widely used method to assess learning environments internationally, a personal growth scale, and single-item global learning environment assessment variables. The overall response rate was 369/429 (86%). After adjusting for the medical school year, gender, and ethnicity of the respondents, the JHLES detected differences across institutions in four out of seven domains (57%), with each school having a unique domain profile. The DREEM detected differences in one out of five categories (20%). The JHLES was more strongly correlated than the DREEM to two thirds of the single-item variables and the personal growth scale. The JHLES showed high internal reliability for the total score (α=0.92) and the seven domains (α, 0.56-0.85). The JHLES detected variation between learning environment domains across three educational settings, thereby creating unique learning environment profiles. Interpretation of these profiles may allow schools to understand how they are currently supporting trainees and identify areas needing attention.

Profiling medical school learning environments in Malaysia: a validation study of the Johns Hopkins Learning Environment Scale

PubMed Central

Tackett, Sean; Bakar, Hamidah Abu; Shilkofski, Nicole A.; Coady, Niamh; Rampal, Krishna; Wright, Scott

2015-01-01

Purpose: While a strong learning environment is critical to medical student education, the assessment of medical school learning environments has confounded researchers. Our goal was to assess the validity and utility of the Johns Hopkins Learning Environment Scale (JHLES) for preclinical students at three Malaysian medical schools with distinct educational and institutional models. Two schools were new international partnerships, and the third was school leaver program established without international partnership. Methods: First- and second-year students responded anonymously to surveys at the end of the academic year. The surveys included the JHLES, a 28-item survey using five-point Likert scale response options, the Dundee Ready Educational Environment Measure (DREEM), the most widely used method to assess learning environments internationally, a personal growth scale, and single-item global learning environment assessment variables. Results: The overall response rate was 369/429 (86%). After adjusting for the medical school year, gender, and ethnicity of the respondents, the JHLES detected differences across institutions in four out of seven domains (57%), with each school having a unique domain profile. The DREEM detected differences in one out of five categories (20%). The JHLES was more strongly correlated than the DREEM to two thirds of the single-item variables and the personal growth scale. The JHLES showed high internal reliability for the total score (α=0.92) and the seven domains (α, 0.56-0.85). Conclusion: The JHLES detected variation between learning environment domains across three educational settings, thereby creating unique learning environment profiles. Interpretation of these profiles may allow schools to understand how they are currently supporting trainees and identify areas needing attention. PMID:26165949

Classification of Features of Pavement Profiles Using Empirical Mode Decomposition

DOT National Transportation Integrated Search

2014-12-01

The Long-Term Pavement Performance (LTPP) database contains surface profile data for numerous pavements that are used mainly for computing International Roughness Index (IRI).(2) In order to obtain more information from these surface profiles, a Hilb...

Small blob identification in medical images using regional features from optimum scale.

PubMed

Zhang, Min; Wu, Teresa; Bennett, Kevin M

2015-04-01

Recent advances in medical imaging technology have greatly enhanced imaging-based diagnosis which requires computational effective and accurate algorithms to process the images (e.g., measure the objects) for quantitative assessment. In this research, we are interested in one type of imaging objects: small blobs. Examples of small blob objects are cells in histopathology images, glomeruli in MR images, etc. This problem is particularly challenging because the small blobs often have in homogeneous intensity distribution and an indistinct boundary against the background. Yet, in general, these blobs have similar sizes. Motivated by this finding, we propose a novel detector termed Hessian-based Laplacian of Gaussian (HLoG) using scale space theory as the foundation. Like most imaging detectors, an image is first smoothed via LoG. Hessian analysis is then launched to identify the single optimal scale on which a presegmentation is conducted. The advantage of the Hessian process is that it is capable of delineating the blobs. As a result, regional features can be retrieved. These features enable an unsupervised clustering algorithm for postpruning which should be more robust and sensitive than the traditional threshold-based postpruning commonly used in most imaging detectors. To test the performance of the proposed HLoG, two sets of 2-D grey medical images are studied. HLoG is compared against three state-of-the-art detectors: generalized LoG, Radial-Symmetry and LoG using precision, recall, and F-score metrics.We observe that HLoG statistically outperforms the compared detectors.

Discriminating precursors of common fragments for large-scale metabolite profiling by triple quadrupole mass spectrometry.

PubMed

Nikolskiy, Igor; Siuzdak, Gary; Patti, Gary J

2015-06-15

The goal of large-scale metabolite profiling is to compare the relative concentrations of as many metabolites extracted from biological samples as possible. This is typically accomplished by measuring the abundances of thousands of ions with high-resolution and high mass accuracy mass spectrometers. Although the data from these instruments provide a comprehensive fingerprint of each sample, identifying the structures of the thousands of detected ions is still challenging and time intensive. An alternative, less-comprehensive approach is to use triple quadrupole (QqQ) mass spectrometry to analyze predetermined sets of metabolites (typically fewer than several hundred). This is done using authentic standards to develop QqQ experiments that specifically detect only the targeted metabolites, with the advantage that the need for ion identification after profiling is eliminated. Here, we propose a framework to extend the application of QqQ mass spectrometers to large-scale metabolite profiling. We aim to provide a foundation for designing QqQ multiple reaction monitoring (MRM) experiments for each of the 82 696 metabolites in the METLIN metabolite database. First, we identify common fragmentation products from the experimental fragmentation data in METLIN. Then, we model the likelihoods of each precursor structure in METLIN producing each common fragmentation product. With these likelihood estimates, we select ensembles of common fragmentation products that minimize our uncertainty about metabolite identities. We demonstrate encouraging performance and, based on our results, we suggest how our method can be integrated with future work to develop large-scale MRM experiments. Our predictions, Supplementary results, and the code for estimating likelihoods and selecting ensembles of fragmentation reactions are made available on the lab website at http://pattilab.wustl.edu/FragPred. © The Author 2015. Published by Oxford University Press. All rights reserved. For

Four Mechanistic Models of Peer Influence on Adolescent Cannabis Use.

PubMed

Caouette, Justin D; Feldstein Ewing, Sarah W

2017-06-01

Most adolescents begin exploring cannabis in peer contexts, but the neural mechanisms that underlie peer influence on adolescent cannabis use are still unknown. This theoretical overview elucidates the intersecting roles of neural function and peer factors in cannabis use in adolescents. Novel paradigms using functional magnetic resonance imaging (fMRI) in adolescents have identified distinct neural mechanisms of risk decision-making and incentive processing in peer contexts, centered on reward-motivation and affect regulatory neural networks; these findings inform a theoretical model of peer-driven cannabis use decisions in adolescents. We propose four "mechanistic profiles" of social facilitation of cannabis use in adolescents: (1) peer influence as the primary driver of use; (2) cannabis exploration as the primary driver, which may be enhanced in peer contexts; (3) social anxiety; and (4) negative peer experiences. Identification of "neural targets" involved in motivating cannabis use may inform clinicians about which treatment strategies work best in adolescents with cannabis use problems, and via which social and neurocognitive processes.

A new scaling law for temperature variance profile in the mixing zone of turbulent Rayleigh-Bénard convection

NASA Astrophysics Data System (ADS)

Wang, Yin; Xu, Wei; He, Xiao-Zhou; Yik, Hiu-Fai; Wang, Xiao-Ping; Schumacher, Jorg; Tong, Penger

2017-11-01

We report a combined experimental and numerical study of the scaling properties of the temperature variance profile η(z) along the central z axis of turbulent Rayleigh-Bénard convection in a thin disk cell and an upright cylinder of aspect ratio unity. In the mixing zone outside the thermal boundary layer region, the measured η(z) is found to scale with the cell height H in both cells and obey a power law, η(z) (z/H)ɛ, with the obtained values of ɛ being very close to -1. Based on the experimental and numerical findings, we derive a new equation for η(z) in the mixing zone, which has a power-law solution in good agreement with the experimental and numerical results. Our work thus provides a common framework for understanding the effect of boundary layer fluctuations on the scaling properties of the temperature variance profile in turbulent Rayleigh-Bénard convection. This work was supported in part by Hong Kong Research Grants Council.

Chromatin Landscapes of Retroviral and Transposon Integration Profiles

PubMed Central

Badhai, Jitendra; Rust, Alistair G.; Rad, Roland; Hilkens, John; Berns, Anton; van Lohuizen, Maarten; Wessels, Lodewyk F. A.; de Ridder, Jeroen

2014-01-01

The ability of retroviruses and transposons to insert their genetic material into host DNA makes them widely used tools in molecular biology, cancer research and gene therapy. However, these systems have biases that may strongly affect research outcomes. To address this issue, we generated very large datasets consisting of to unselected integrations in the mouse genome for the Sleeping Beauty (SB) and piggyBac (PB) transposons, and the Mouse Mammary Tumor Virus (MMTV). We analyzed (epi)genomic features to generate bias maps at both local and genome-wide scales. MMTV showed a remarkably uniform distribution of integrations across the genome. More distinct preferences were observed for the two transposons, with PB showing remarkable resemblance to bias profiles of the Murine Leukemia Virus. Furthermore, we present a model where target site selection is directed at multiple scales. At a large scale, target site selection is similar across systems, and defined by domain-oriented features, namely expression of proximal genes, proximity to CpG islands and to genic features, chromatin compaction and replication timing. Notable differences between the systems are mainly observed at smaller scales, and are directed by a diverse range of features. To study the effect of these biases on integration sites occupied under selective pressure, we turned to insertional mutagenesis (IM) screens. In IM screens, putative cancer genes are identified by finding frequently targeted genomic regions, or Common Integration Sites (CISs). Within three recently completed IM screens, we identified 7%–33% putative false positive CISs, which are likely not the result of the oncogenic selection process. Moreover, results indicate that PB, compared to SB, is more suited to tag oncogenes. PMID:24721906

Speckle-reducing scale-invariant feature transform match for synthetic aperture radar image registration

NASA Astrophysics Data System (ADS)

Wang, Xianmin; Li, Bo; Xu, Qizhi

2016-07-01

The anisotropic scale space (ASS) is often used to enhance the performance of a scale-invariant feature transform (SIFT) algorithm in the registration of synthetic aperture radar (SAR) images. The existing ASS-based methods usually suffer from unstable keypoints and false matches, since the anisotropic diffusion filtering has limitations in reducing the speckle noise from SAR images while building the ASS image representation. We proposed a speckle reducing SIFT match method to obtain stable keypoints and acquire precise matches for the SAR image registration. First, the keypoints are detected in a speckle reducing anisotropic scale space constructed by the speckle reducing anisotropic diffusion, so that speckle noise is greatly reduced and prominent structures of the images are preserved, consequently the stable keypoints can be derived. Next, the probabilistic relaxation labeling approach is employed to establish the matches of the keypoints then the correct match rate of the keypoints is significantly increased. Experiments conducted on simulated speckled images and real SAR images demonstrate the effectiveness of the proposed method.

Pharmacokinetic Modeling to Simulate the Concentration-Time Profiles After Dermal Application of Rivastigmine Patch.

PubMed

Nozaki, Sachiko; Yamaguchi, Masayuki; Lefèvre, Gilbert

2016-07-01

Rivastigmine is an inhibitor of acetylcholinesterases and butyrylcholinesterases for symptomatic treatment of Alzheimer disease and is available as oral and transdermal patch formulations. A dermal absorption pharmacokinetic (PK) model was developed to simulate the plasma concentration-time profile of rivastigmine to answer questions relative to the efficacy and safety risks after misuse of the patch (e.g., longer application than 24 h, multiple patches applied at the same time, and so forth). The model comprised 2 compartments which was a combination of mechanistic dermal absorption model and a basic 1-compartment model. The initial values for the model were determined based on the physicochemical characteristics of rivastigmine and PK parameters after intravenous administration. The model was fitted to the clinical PK profiles after single application of rivastigmine patch to obtain model parameters. The final model was validated by confirming that the simulated concentration-time curves and PK parameters (Cmax and area under the drug plasma concentration-time curve) conformed to the observed values and then was used to simulate the PK profiles of rivastigmine. This work demonstrated that the mechanistic dermal PK model fitted the clinical data well and was able to simulate the PK profile after patch misuse. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Explanation and inference: mechanistic and functional explanations guide property generalization.

PubMed

Lombrozo, Tania; Gwynne, Nicholas Z

2014-01-01

The ability to generalize from the known to the unknown is central to learning and inference. Two experiments explore the relationship between how a property is explained and how that property is generalized to novel species and artifacts. The experiments contrast the consequences of explaining a property mechanistically, by appeal to parts and processes, with the consequences of explaining the property functionally, by appeal to functions and goals. The findings suggest that properties that are explained functionally are more likely to be generalized on the basis of shared functions, with a weaker relationship between mechanistic explanations and generalization on the basis of shared parts and processes. The influence of explanation type on generalization holds even though all participants are provided with the same mechanistic and functional information, and whether an explanation type is freely generated (Experiment 1), experimentally provided (Experiment 2), or experimentally induced (Experiment 2). The experiments also demonstrate that explanations and generalizations of a particular type (mechanistic or functional) can be experimentally induced by providing sample explanations of that type, with a comparable effect when the sample explanations come from the same domain or from a different domains. These results suggest that explanations serve as a guide to generalization, and contribute to a growing body of work supporting the value of distinguishing mechanistic and functional explanations.

Somatodendritic dopamine release: recent mechanistic insights

PubMed Central

Rice, Margaret E.; Patel, Jyoti C.

2015-01-01

Dopamine (DA) is a key transmitter in motor, reward and cogitative pathways, with DA dysfunction implicated in disorders including Parkinson's disease and addiction. Located in midbrain, DA neurons of the substantia nigra pars compacta project via the medial forebrain bundle to the dorsal striatum (caudate putamen), and DA neurons in the adjacent ventral tegmental area project to the ventral striatum (nucleus accumbens) and prefrontal cortex. In addition to classical vesicular release from axons, midbrain DA neurons exhibit DA release from their cell bodies and dendrites. Somatodendritic DA release leads to activation of D2 DA autoreceptors on DA neurons that inhibit their firing via G-protein-coupled inwardly rectifying K+ channels. This helps determine patterns of DA signalling at distant axonal release sites. Somatodendritically released DA also acts via volume transmission to extrasynaptic receptors that modulate local transmitter release and neuronal activity in the midbrain. Thus, somatodendritic release is a pivotal intrinsic feature of DA neurons that must be well defined in order to fully understand the physiology and pathophysiology of DA pathways. Here, we review recent mechanistic aspects of somatodendritic DA release, with particular emphasis on the Ca2+ dependence of release and the potential role of exocytotic proteins. PMID:26009764

Recursive feature elimination for biomarker discovery in resting-state functional connectivity.

PubMed

Ravishankar, Hariharan; Madhavan, Radhika; Mullick, Rakesh; Shetty, Teena; Marinelli, Luca; Joel, Suresh E

2016-08-01

Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensionality of images, inter-subject and intra-subject variability and small numbers of subjects compared to the number of derived features. Traditional univariate analysis suffers from the problem of multiple comparisons. Here, we adopt an alternative data-driven method for identifying population differences in functional connectivity. We propose a machine-learning approach to down-select functional connectivity features associated with symptom severity in mild traumatic brain injury (mTBI). Using this approach, we identified functional regions with altered connectivity in mTBI. including the executive control, visual and precuneus networks. We compared functional connections at multiple resolutions to determine which scale would be more sensitive to changes related to patient recovery. These modular network-level features can be used as diagnostic tools for predicting disease severity and recovery profiles.

Form drag in rivers due to small-scale natural topographic features: 2. Irregular sequences

USGS Publications Warehouse

Kean, J.W.; Smith, J.D.

2006-01-01

The size, shape, and spacing of small-scale topographic features found on the boundaries of natural streams, rivers, and floodplains can be quite variable. Consequently, a procedure for determining the form drag on irregular sequences of different-sized topographic features is essential for calculating near-boundary flows and sediment transport. A method for carrying out such calculations is developed in this paper. This method builds on the work of Kean and Smith (2006), which describes the flow field for the simpler case of a regular sequence of identical topographic features. Both approaches model topographic features as two-dimensional elements with Gaussian-shaped cross sections defined in terms of three parameters. Field measurements of bank topography are used to show that (1) the magnitude of these shape parameters can vary greatly between adjacent topographic features and (2) the variability of these shape parameters follows a lognormal distribution. Simulations using an irregular set of topographic roughness elements show that the drag on an individual element is primarily controlled by the size and shape of the feature immediately upstream and that the spatial average of the boundary shear stress over a large set of randomly ordered elements is relatively insensitive to the sequence of the elements. In addition, a method to transform the topography of irregular surfaces into an equivalently rough surface of regularly spaced, identical topographic elements also is given. The methods described in this paper can be used to improve predictions of flow resistance in rivers as well as quantify bank roughness.

Mechanistic analysis of challenge-response experiments.

PubMed

Shotwell, M S; Drake, K J; Sidorov, V Y; Wikswo, J P

2013-09-01

We present an application of mechanistic modeling and nonlinear longitudinal regression in the context of biomedical response-to-challenge experiments, a field where these methods are underutilized. In this type of experiment, a system is studied by imposing an experimental challenge, and then observing its response. The combination of mechanistic modeling and nonlinear longitudinal regression has brought new insight, and revealed an unexpected opportunity for optimal design. Specifically, the mechanistic aspect of our approach enables the optimal design of experimental challenge characteristics (e.g., intensity, duration). This article lays some groundwork for this approach. We consider a series of experiments wherein an isolated rabbit heart is challenged with intermittent anoxia. The heart responds to the challenge onset, and recovers when the challenge ends. The mean response is modeled by a system of differential equations that describe a candidate mechanism for cardiac response to anoxia challenge. The cardiac system behaves more variably when challenged than when at rest. Hence, observations arising from this experiment exhibit complex heteroscedasticity and sharp changes in central tendency. We present evidence that an asymptotic statistical inference strategy may fail to adequately account for statistical uncertainty. Two alternative methods are critiqued qualitatively (i.e., for utility in the current context), and quantitatively using an innovative Monte-Carlo method. We conclude with a discussion of the exciting opportunities in optimal design of response-to-challenge experiments. © 2013, The International Biometric Society.

Revisiting sesquiterpene biosynthetic pathways leading to santalene and its analogues: a comprehensive mechanistic study.

PubMed

Jindal, Garima; Sunoj, Raghavan B

2012-10-21

Santalene and bergamotene are the major olefinic sesquiterpenes responsible for the fragrance of sandalwood oil. Herein we report the details of density functional theory investigations on the biosynthetic pathway of this important class of terpenes. The mechanistic study has been found to be effective toward gaining significant new insight into different possibilities for the formation of the key intermediates involved in santalene and bergamotene biosynthesis. The stereoelectronic features of the transition states and intermediates for (i) ring closure of the initial bisabolyl cation, and (ii) skeletal rearrangements in the ensuing bicyclic carbocationic intermediates leading to (-)-epi-β-santalene, (-)-β-santalene, (-)-α-santalene, (+)-epi-β-santalene, exo-β-bergamotene, endo-β-bergamotene, exo-α-bergamotene, and endo-α-bergamotene are presented. Interesting structural features pertaining to certain new carbocationic intermediates (such as b) resulting from the ring closure of bisabolyl cation are discussed. Extensive conformational sampling of all key intermediates along the biosynthetic pathway offered new insight into the role of the isoprenyl side chain conformation in the formation of santalene and its analogues. Although the major bicyclic products in Santalum album appear to arise from the right or left handed helical form of farnesyl pyrophosphate (FPP), different alternatives for their formation are found to be energetically feasible. The interconversion of the exo and endo isomers of bisabolyl cation and a likely epimerization, both with interesting mechanistic implications, are presented. The exo to endo conversion is identified to be energetically more favorable than another pathway emanating from the left handed helical FPP. The role of pyrophosphate (OPP(-)) in the penultimate deprotonation step leading to olefinic sesquiterpenes is also examined.

Flow-mediated Dilation: Can New Approaches Provide Greater Mechanistic Insight into Vascular Dysfunction in Preeclampsia and Other Diseases?

PubMed Central

Weissgerber, Tracey L.

2015-01-01

Endothelial dysfunction is a key feature of preeclampsia, and may contribute to increased cardiovascular disease risk years after pregnancy. Flow-mediated dilation (FMD) is a non-invasive endothelial function test that predicts cardiovascular event risk. New protocols allow researchers to measure three components of the FMD response: FMD, low flow-mediated constriction and the shear stimulus. This review encourages researchers to think beyond “low FMD” by examining how these three components may provide additional insights into the mechanisms and location of vascular dysfunction. The review then examines what FMD studies reveal about vascular dysfunction in preeclampsia, while highlighting opportunities to gain greater mechanistic insight from new protocols. Studies using traditional protocols show that FMD is low in mid-pregnancy prior to preeclampsia, at diagnosis, and for three years post-partum. However, FMD returns to normal by ten years post-partum. Studies using new protocols are needed to gain more mechanistic insight. PMID:25182159

MECHANISTIC INDICATORS OF CHILDHOOD ASTHMA (MICA)

EPA Science Inventory

The US Environmental Protection Agency (EPA) is interested in the interplay of environmental and genetic factors on the development and exacerbation of asthma. The Mechanistic Indicators of Childhood Asthma (MICA) study will use exposure measurements and markers of environmental ...

Phenomenological features of dreams: Results from dream log studies using the Subjective Experiences Rating Scale (SERS).

PubMed

Kahan, Tracey L; Claudatos, Stephanie

2016-04-01

Self-ratings of dream experiences were obtained from 144 college women for 788 dreams, using the Subjective Experiences Rating Scale (SERS). Consistent with past studies, dreams were characterized by a greater prevalence of vision, audition, and movement than smell, touch, or taste, by both positive and negative emotion, and by a range of cognitive processes. A Principal Components Analysis of SERS ratings revealed ten subscales: four sensory, three affective, one cognitive, and two structural (events/actions, locations). Correlations (Pearson r) among subscale means showed a stronger relationship among the process-oriented features (sensory, cognitive, affective) than between the process-oriented and content-centered (structural) features--a pattern predicted from past research (e.g., Bulkeley & Kahan, 2008). Notably, cognition and positive emotion were associated with a greater number of other phenomenal features than was negative emotion; these findings are consistent with studies of the qualitative features of waking autobiographical memory (e.g., Fredrickson, 2001). Copyright © 2016 Elsevier Inc. All rights reserved.

Possibilities of LA-ICP-MS technique for the spatial elemental analysis of the recent fish scales: Line scan vs. depth profiling

NASA Astrophysics Data System (ADS)

Holá, Markéta; Kalvoda, Jiří; Nováková, Hana; Škoda, Radek; Kanický, Viktor

2011-01-01

LA-ICP-MS and solution based ICP-MS in combination with electron microprobe are presented as a method for the determination of the elemental spatial distribution in fish scales which represent an example of a heterogeneous layered bone structure. Two different LA-ICP-MS techniques were tested on recent common carp ( Cyprinus carpio) scales: A line scan through the whole fish scale perpendicular to the growth rings. The ablation crater of 55 μm width and 50 μm depth allowed analysis of the elemental distribution in the external layer. Suitable ablation conditions providing a deeper ablation crater gave average values from the external HAP layer and the collagen basal plate. Depth profiling using spot analysis was tested in fish scales for the first time. Spot analysis allows information to be obtained about the depth profile of the elements at the selected position on the sample. The combination of all mentioned laser ablation techniques provides complete information about the elemental distribution in the fish scale samples. The results were compared with the solution based ICP-MS and EMP analyses. The fact that the results of depth profiling are in a good agreement both with EMP and PIXE results and, with the assumed ways of incorporation of the studied elements in the HAP structure, suggests a very good potential for this method.

The Personality Assessment Inventory as a Proxy for the Psychopathy Checklist-Revised: Testing the Incremental Validity and Cross-Sample Robustness of the Antisocial Features Scale

ERIC Educational Resources Information Center

Douglas, Kevin S.; Guy, Laura S.; Edens, John F.; Boer, Douglas P.; Hamilton, Jennine

2007-01-01

The Personality Assessment Inventory's (PAI's) ability to predict psychopathic personality features, as assessed by the Psychopathy Checklist-Revised (PCL-R), was examined. To investigate whether the PAI Antisocial Features (ANT) Scale and subscales possessed incremental validity beyond other theoretically relevant PAI scales, optimized regression…

The Rosenberg Self-Esteem Scale and Harter's Self-Perception Profile for Adolescents: A Concurrent Validity Study.

ERIC Educational Resources Information Center

Hagborg, Winston J.

1993-01-01

Administered Rosenberg Self-Esteem Scale (RSE) and Harter's Self-Perception Profile for Adolescents to 150 adolescents in grades 8 through 12. Correlational and cross-validation multiple regression analyses found that RSE total score and both its factor scores were strongly related to Global Self-Worth. Females reported significantly lower RSE…

Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

PubMed

Schob, Stefan; Beeskow, Anne; Dieckow, Julia; Meyer, Hans-Jonas; Krause, Matthias; Frydrychowicz, Clara; Hirsch, Franz-Wolfgang; Surov, Alexey

2018-05-31

Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

Small-scale structure and the Lyman-α forest baryon acoustic oscillation feature

NASA Astrophysics Data System (ADS)

Hirata, Christopher M.

2018-02-01

The baryon-acoustic oscillation (BAO) feature in the Lyman-α forest is a key probe of the cosmic expansion rate at redshifts z ˜ 2.5, well before dark energy is believed to have become significant. A key advantage of the BAO as a standard ruler is that it is a sharp feature and hence is more robust against broad-band systematic effects than other cosmological probes. However, if the Lyman-α forest transmission is sensitive to the initial streaming velocity of the baryons relative to the dark matter, then the BAO peak position can be shifted. Here we investigate this sensitivity using a suite of hydrodynamic simulations of small regions of the intergalactic medium with a range of box sizes and physics assumptions; each simulation starts from initial conditions at the kinematic decoupling era (z ˜ 1059), undergoes a discrete change from neutral gas to ionized gas thermal evolution at reionization (z ˜ 8), and is finally processed into a Lyman-α forest transmitted flux cube. Streaming velocities suppress small-scale structure, leading to less violent relaxation after reionization. The changes in the gas distribution and temperature-density relation at low redshift are more subtle, due to the convergent temperature evolution in the ionized phase. The change in the BAO scale is estimated to be of the order of 0.12 per cent at z = 2.5; some of the major uncertainties and avenues for future improvement are discussed. The predicted streaming velocity shift would be a subdominant but not negligible effect (of order 0.26σ) for the upcoming DESI Lyman-α forest survey, and exceeds the cosmic variance floor.

The relationship between personality organization as assessed by theory-driven profiles of the Dutch Short Form of the MMPI and self-reported features of personality organization.

PubMed

Eurelings-Bontekoe, Elisabeth H M; Luyten, Patrick; Remijsen, Mila; Koelen, Jurrijn

2010-11-01

In this study, we investigated the relationships between features of personality organization (PO) as assessed by theory driven profiles of the Dutch Short Form of the MMPI (DSFM; Luteijn & Kok, 1985) and 2 self-report measures of personality pathology, that is, the Dutch Inventory of Personality Organization (Berghuis, Kamphuis, Boedijn, & Verheul, 2009) and the Dutch Schizotypy Personality Questionnaire-Revised (Vollema & Hoijtink, 2000), in a sample of 190 outpatient psychiatric patients. Results showed that the single scales of all 3 measures segregated into 2 theoretically expected and meaningful dimensions, that is, a dimension assessing severity of personality pathology and an introversion/extraversion dimension. Theory-driven combinations of single DSFM subscales as a measure of level of PO distinguished characteristics of patients at various levels of PO in theoretically predicted ways. Results also suggest that structural personality pathology may not be fully captured by self-report measures.

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

Topographic Comparisons of Uplift Features on Venus and Earth

NASA Astrophysics Data System (ADS)

Stoddard, P. R.; Jurdy, D. M.

2009-12-01

Earth and Venus, nearly twins, have very different resurfacing histories. Like the Earth, Venus has a global rift system, often cited as evidence of tectonic activity, despite the apparent lack of Earth-style plate tectonics. Both systems are marked by large ridges, usually with central grabens. On Earth, the topography of the rifts can be modeled well by a cooling half-space and the spreading of two divergent plates. The origin of the topographic signature on Venus, however, remains enigmatic. Venus and Earth also both have regions of apparent upwelling: hotspots on Earth, and regiones on Venus. Both are marked by broad topographic and geoid highs as well as evidence of volcanic activity. We use topographic profiles to compare well-understood terrestrial analogs to venusian features. Specifically, we cross-correlate average profiles for terrestrial rifts (slow, fast, incipient and extinct) and hotspots (oceanic and continental) with those for venusian chasmata and regiones. We perform a principal component analysis to objectively assess degrees of similarity and differences to draw inferences as to the processes responsible for shaping Venus' surface. We analyze profiles of the Labrador Ridge, East African Rift, slow-spreading Mid-Atlantic Ridge and the fast-spreading East Pacific Rise for comparison with profiles for several venusian chasmata in different settings. For upwelling regions, we look at the Hawaii, Iceland, Reunion, and Yellowstone hotspots and Atla, Beta, and W. Eistla regiones on Venus. For ridge features, we take profiles perpendicular to the ridge trend every half-degree or so. For uplift features, we take 36 radial profiles through the center of the feature at 10 degree intervals. We use profiles from 800 to 1200 km long. For each feature, we average all profiles, then cross-correlate the individual profiles with the resulting average. Next, we cross-correlate the average profiles of each feature with those of the other features. Thus we obtain a

IRIS Si iv LINE PROFILES: AN INDICATION FOR THE PLASMOID INSTABILITY DURING SMALL-SCALE MAGNETIC RECONNECTION ON THE SUN

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

Innes, D. E.; Guo, L.-J.; Huang, Y.-M.

Our understanding of the process of fast reconnection has undergone a dramatic change in the last 10 years driven, in part, by the availability of high-resolution numerical simulations that have consistently demonstrated the break-up of current sheets into magnetic islands, with reconnection rates that become independent of Lundquist number, challenging the belief that fast magnetic reconnection in flares proceeds via the Petschek mechanism which invokes pairs of slow-mode shocks connected to a compact diffusion region. The reconnection sites are too small to be resolved with images, but these reconnection mechanisms, Petschek and the plasmoid instability, have reconnection sites with verymore » different density and velocity structures and so can be distinguished by high-resolution line-profile observations. Using IRIS spectroscopic observations we obtain a survey of typical line profiles produced by small-scale events thought to be reconnection sites on the Sun. Slit-jaw images are used to investigate the plasma heating and re-configuration at the sites. A sample of 15 events from 2 active regions is presented. The line profiles are complex with bright cores and broad wings extending to over 300 km s{sup −1}. The profiles can be reproduced with the multiple magnetic islands and acceleration sites that characterize the plasmoid instability but not by bi-directional jets that characterize the Petschek mechanism. This result suggests that if these small-scale events are reconnection sites, then fast reconnection proceeds via the plasmoid instability, rather than the Petschek mechanism during small-scale reconnection on the Sun.« less

Managing mechanistic and organic structure in health care organizations.

PubMed

Olden, Peter C

2012-01-01

Managers at all levels in a health care organization must organize work to achieve the organization's mission and goals. This requires managers to decide the organization structure, which involves dividing the work among jobs and departments and then coordinating them all toward the common purpose. Organization structure, which is reflected in an organization chart, may range on a continuum from very mechanistic to very organic. Managers must decide how mechanistic versus how organic to make the entire organization and each of its departments. To do this, managers should carefully consider 5 factors for the organization and for each individual department: external environment, goals, work production, size, and culture. Some factors may push toward more mechanistic structure, whereas others may push in the opposite direction toward more organic structure. Practical advice can help managers at all levels design appropriate structure for their departments and organization.

Cognitive science as an interface between rational and mechanistic explanation.

PubMed

Chater, Nick

2014-04-01

Cognitive science views thought as computation; and computation, by its very nature, can be understood in both rational and mechanistic terms. In rational terms, a computation solves some information processing problem (e.g., mapping sensory information into a description of the external world; parsing a sentence; selecting among a set of possible actions). In mechanistic terms, a computation corresponds to causal chain of events in a physical device (in engineering context, a silicon chip; in biological context, the nervous system). The discipline is thus at the interface between two very different styles of explanation--as the papers in the current special issue well illustrate, it explores the interplay of rational and mechanistic forces. Copyright © 2014 Cognitive Science Society, Inc.

Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization

PubMed Central

Huang, Ruili; Xia, Menghang; Sakamuru, Srilatha; Zhao, Jinghua; Shahane, Sampada A.; Attene-Ramos, Matias; Zhao, Tongan; Austin, Christopher P.; Simeonov, Anton

2016-01-01

Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure–activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing. PMID:26811972

GHEP-ISFG collaborative simulated exercise for DVI/MPI: Lessons learned about large-scale profile database comparisons.

PubMed

Vullo, Carlos M; Romero, Magdalena; Catelli, Laura; Šakić, Mustafa; Saragoni, Victor G; Jimenez Pleguezuelos, María Jose; Romanini, Carola; Anjos Porto, Maria João; Puente Prieto, Jorge; Bofarull Castro, Alicia; Hernandez, Alexis; Farfán, María José; Prieto, Victoria; Alvarez, David; Penacino, Gustavo; Zabalza, Santiago; Hernández Bolaños, Alejandro; Miguel Manterola, Irati; Prieto, Lourdes; Parsons, Thomas

2016-03-01

The GHEP-ISFG Working Group has recognized the importance of assisting DNA laboratories to gain expertise in handling DVI or missing persons identification (MPI) projects which involve the need for large-scale genetic profile comparisons. Eleven laboratories participated in a DNA matching exercise to identify victims from a hypothetical conflict with 193 missing persons. The post mortem database was comprised of 87 skeletal remain profiles from a secondary mass grave displaying a minimal number of 58 individuals with evidence of commingling. The reference database was represented by 286 family reference profiles with diverse pedigrees. The goal of the exercise was to correctly discover re-associations and family matches. The results of direct matching for commingled remains re-associations were correct and fully concordant among all laboratories. However, the kinship analysis for missing persons identifications showed variable results among the participants. There was a group of laboratories with correct, concordant results but nearly half of the others showed discrepant results exhibiting likelihood ratio differences of several degrees of magnitude in some cases. Three main errors were detected: (a) some laboratories did not use the complete reference family genetic data to report the match with the remains, (b) the identity and/or non-identity hypotheses were sometimes wrongly expressed in the likelihood ratio calculations, and (c) many laboratories did not properly evaluate the prior odds for the event. The results suggest that large-scale profile comparisons for DVI or MPI is a challenge for forensic genetics laboratories and the statistical treatment of DNA matching and the Bayesian framework should be better standardized among laboratories. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Structural Basis of IKs Ion-Channel Activation: Mechanistic Insights from Molecular Simulations.

PubMed

Ramasubramanian, Smiruthi; Rudy, Yoram

2018-06-05

Relating ion channel (iCh) structural dynamics to physiological function remains a challenge. Current experimental and computational techniques have limited ability to explore this relationship in atomistic detail over physiological timescales. A framework associating iCh structure to function is necessary for elucidating normal and disease mechanisms. We formulated a modeling schema that overcomes the limitations of current methods through applications of artificial intelligence machine learning. Using this approach, we studied molecular processes that underlie human IKs voltage-mediated gating. IKs malfunction underlies many debilitating and life-threatening diseases. Molecular components of IKs that underlie its electrophysiological function include KCNQ1 (a pore-forming tetramer) and KCNE1 (an auxiliary subunit). Simulations, using the IKs structure-function model, reproduced experimentally recorded saturation of gating-charge displacement at positive membrane voltages, two-step voltage sensor (VS) movement shown by fluorescence, iCh gating statistics, and current-voltage relationship. Mechanistic insights include the following: 1) pore energy profile determines iCh subconductance; 2) the entire protein structure, not limited to the pore, contributes to pore energy and channel subconductance; 3) interactions with KCNE1 result in two distinct VS movements, causing gating-charge saturation at positive membrane voltages and current activation delay; and 4) flexible coupling between VS and pore permits pore opening at lower VS positions, resulting in sequential gating. The new modeling approach is applicable to atomistic scale studies of other proteins on timescales of physiological function. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Modeling Bird Migration under Climate Change: A Mechanistic Approach

NASA Technical Reports Server (NTRS)

Smith, James A.

2009-01-01

How will migrating birds respond to changes in the environment under climate change? What are the implications for migratory success under the various accelerated climate change scenarios as forecast by the Intergovernmental Panel on Climate Change? How will reductions or increased variability in the number or quality of wetland stop-over sites affect migratory bird species? The answers to these questions have important ramifications for conservation biology and wildlife management. Here, we describe the use of continental scale simulation modeling to explore how spatio-temporal changes along migratory flyways affect en-route migration success. We use an individually based, biophysical, mechanistic, bird migration model to simulate the movement of shorebirds in North America as a tool to study how such factors as drought and wetland loss may impact migratory success and modify migration patterns. Our model is driven by remote sensing and climate data and incorporates important landscape variables. The energy budget components of the model include resting, foraging, and flight, but presently predation is ignored. Results/Conclusions We illustrate our model by studying the spring migration of sandpipers through the Great Plains to their Arctic breeding grounds. Why many species of shorebirds have shown significant declines remains a puzzle. Shorebirds are sensitive to stop-over quality and spacing because of their need for frequent refueling stops and their opportunistic feeding patterns. We predict bird "hydrographs that is, stop-over frequency with latitude, that are in agreement with the literature. Mean stop-over durations predicted from our model for nominal cases also are consistent with the limited, but available data. For the shorebird species simulated, our model predicts that shorebirds exhibit significant plasticity and are able to shift their migration patterns in response to changing drought conditions. However, the question remains as to whether this

Taxometric Analysis of the Antisocial Features Scale of the Personality Assessment Inventory in Federal Prison Inmates

ERIC Educational Resources Information Center

Walters, Glenn D.; Diamond, Pamela M.; Magaletta, Philip R.; Geyer, Matthew D.; Duncan, Scott A.

2007-01-01

The Antisocial Features (ANT) scale of the Personality Assessment Inventory (PAI) was subjected to taxometric analysis in a group of 2,135 federal prison inmates. Scores on the three ANT subscales--Antisocial Behaviors (ANT-A), Egocentricity (ANT-E), and Stimulus Seeking (ANT-S)--served as indicators in this study and were evaluated using the…

Cross Racial Identity Scale (CRIS) scores and profiles in African American adolescents involved with the juvenile justice system.

PubMed

Worrell, Frank C; Andretta, James R; Woodland, Malcolm H

2014-10-01

In this study, we examined the internal consistency and structural validity of Cross Racial Identity Scale (CRIS) scores in a sample of 477 African American adolescents who had been arrested in a city in the mid-Atlantic. Using cluster analysis, we also identified profiles of CRIS scores and compared adolescents with different profiles on Major Depressive Episode, Manic Episode, Generalized Anxiety Disorder, and Obsessive-Compulsive Disorder scores. Results indicated that CRIS subscale scores were reliable, and the 6-factor structure of the CRIS was supported. Five nigrescence profiles were identified: Miseducation-Pro-Black, Conflicted-Self-Hatred, Multiculturalist, Low Race Salience, and Conflicted-Anti-White. Individuals with Conflicted-Self-Hatred profiles reported significantly and meaningfully higher scores on the 4 syndromes than did their peers, and individuals with the Multiculturalist and Low Race Salience profiles reported the lowest scores. A greater percentage of individuals with Conflicted racial identity profiles had syndrome scores in the clinically significant range. The results of this study demonstrate that some of the nigrescence profiles found in college-age students generalize to adolescents. The implications of the findings for theory, research, and practice are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Development of Alabama traffic factors for use in mechanistic-empirical pavement design.

DOT National Transportation Integrated Search

2015-02-01

The pavement engineering community is moving toward design practices that use mechanistic-empirical (M-E) approaches to the design and analysis of pavement structures. This effort is : embodied in the Mechanistic-Empirical Pavement Design Guide (MEPD...

Scaling up spike-and-slab models for unsupervised feature learning.

PubMed

Goodfellow, Ian J; Courville, Aaron; Bengio, Yoshua

2013-08-01

We describe the use of two spike-and-slab models for modeling real-valued data, with an emphasis on their applications to object recognition. The first model, which we call spike-and-slab sparse coding (S3C), is a preexisting model for which we introduce a faster approximate inference algorithm. We introduce a deep variant of S3C, which we call the partially directed deep Boltzmann machine (PD-DBM) and extend our S3C inference algorithm for use on this model. We describe learning procedures for each. We demonstrate that our inference procedure for S3C enables scaling the model to unprecedented large problem sizes, and demonstrate that using S3C as a feature extractor results in very good object recognition performance, particularly when the number of labeled examples is low. We show that the PD-DBM generates better samples than its shallow counterpart, and that unlike DBMs or DBNs, the PD-DBM may be trained successfully without greedy layerwise training.

Mechanistic materials modeling for nuclear fuel performance

DOE PAGES

Tonks, Michael R.; Andersson, David; Phillpot, Simon R.; ...

2017-03-15

Fuel performance codes are critical tools for the design, certification, and safety analysis of nuclear reactors. However, their ability to predict fuel behavior under abnormal conditions is severely limited by their considerable reliance on empirical materials models correlated to burn-up (a measure of the number of fission events that have occurred, but not a unique measure of the history of the material). In this paper, we propose a different paradigm for fuel performance codes to employ mechanistic materials models that are based on the current state of the evolving microstructure rather than burn-up. In this approach, a series of statemore » variables are stored at material points and define the current state of the microstructure. The evolution of these state variables is defined by mechanistic models that are functions of fuel conditions and other state variables. The material properties of the fuel and cladding are determined from microstructure/property relationships that are functions of the state variables and the current fuel conditions. Multiscale modeling and simulation is being used in conjunction with experimental data to inform the development of these models. Finally, this mechanistic, microstructure-based approach has the potential to provide a more predictive fuel performance capability, but will require a team of researchers to complete the required development and to validate the approach.« less

Association between traditional clinical high-risk features and gene expression profile classification in uveal melanoma.

PubMed

Nguyen, Brandon T; Kim, Ryan S; Bretana, Maria E; Kegley, Eric; Schefler, Amy C

2018-02-01

To evaluate the association between traditional clinical high-risk features of uveal melanoma patients and gene expression profile (GEP). This was a retrospective, single-center, case series of patients with uveal melanoma. Eighty-three patients met inclusion criteria for the study. Patients were examined for the following clinical risk factors: drusen/retinal pigment epithelium (RPE) changes, vascularity on B-scan, internal reflectivity on A-scan, subretinal fluid (SRF), orange pigment, apical tumor height/thickness, and largest basal dimensions (LBD). A novel point system was created to grade the high-risk clinical features of each tumor. Further analyses were performed to assess the degree of association between GEP and each individual risk factor, total clinical risk score, vascularity, internal reflectivity, American Joint Committee on Cancer (AJCC) tumor stage classification, apical tumor height/thickness, and LBD. Of the 83 total patients, 41 were classified as GEP class 1A, 17 as class 1B, and 25 as class 2. The presence of orange pigment, SRF, low internal reflectivity and vascularity on ultrasound, and apical tumor height/thickness ≥ 2 mm were not statistically significantly associated with GEP class. Lack of drusen/RPE changes demonstrated a trend toward statistical association with GEP class 2 compared to class 1A/1B. LBD and advancing AJCC stage was statistically associated with higher GEP class. In this cohort, AJCC stage classification and LBD were the only clinical features statistically associated with GEP class. Clinicians should use caution when inferring the growth potential of melanocytic lesions solely from traditional funduscopic and ultrasonographic risk factors without GEP data.

Improving sub-grid scale accuracy of boundary features in regional finite-difference models

USGS Publications Warehouse

Panday, Sorab; Langevin, Christian D.

2012-01-01

As an alternative to grid refinement, the concept of a ghost node, which was developed for nested grid applications, has been extended towards improving sub-grid scale accuracy of flow to conduits, wells, rivers or other boundary features that interact with a finite-difference groundwater flow model. The formulation is presented for correcting the regular finite-difference groundwater flow equations for confined and unconfined cases, with or without Newton Raphson linearization of the nonlinearities, to include the Ghost Node Correction (GNC) for location displacement. The correction may be applied on the right-hand side vector for a symmetric finite-difference Picard implementation, or on the left-hand side matrix for an implicit but asymmetric implementation. The finite-difference matrix connectivity structure may be maintained for an implicit implementation by only selecting contributing nodes that are a part of the finite-difference connectivity. Proof of concept example problems are provided to demonstrate the improved accuracy that may be achieved through sub-grid scale corrections using the GNC schemes.

Mechanistic Links Between PARP, NAD, and Brain Inflammation After TBI

DTIC Science & Technology

2015-10-01

1 AWARD NUMBER: W81XWH-13-2-0091 TITLE: Mechanistic Links Between PARP, NAD , and Brain Inflammation After TBI PRINCIPAL INVESTIGATOR...COVERED 25 Sep 2014 - 24 Sep 2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Mechanistic Links Between PARP, NAD , and Brain Inflammation After TBI 5b. GRANT...efficacy of veliparib and NAD as agents for suppressing inflammation and improving outcomes after traumatic brain injury. The animal models include

Fine flow structures in the transition region small-scale loops

NASA Astrophysics Data System (ADS)

Yan, L.; Peter, H.; He, J.; Wei, Y.

2016-12-01

The observation and model have suggested that the transition region EUV emission from the quiet sun region is contributed by very small scale loops which have not been resolved. Recently, the observation from IRIS has revealed that this kind of small scale loops. Based on the high resolution spectral and imaging observation from IRIS, much more detail work needs to be done to reveal the fine flow features in this kind of loop to help us understand the loop heating. Here, we present a detail statistical study of the spatial and temporal evolution of Si IV line profiles of small scale loops and report the spectral features: there is a transition from blue (red) wing enhancement dominant to red (blue) wing enhancement dominant along the cross-section of the loop, which is independent of time. This feature appears as the loop appear and disappear as the loop un-visible. This is probably the signature of helical flow along the loop. The result suggests that the brightening of this kind of loop is probably due to the current dissipation heating in the twisted magnetic field flux tube.

Feature detection on 3D images of dental imprints

NASA Astrophysics Data System (ADS)

Mokhtari, Marielle; Laurendeau, Denis

1994-09-01

A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

Investigation of mesoscale cloud features viewed by LANDSAT

NASA Technical Reports Server (NTRS)

Sherr, P. E. (Principal Investigator); Feteris, P. J.; Lisa, A. S.; Bowley, C. J.; Fowler, M. G.; Barnes, J. C.

1976-01-01

The author has identified the following significant results. Some 50 LANDSAT images displaying mesoscale cloud features were analyzed. This analysis was based on the Rayleigh-Kuettner model describing the formation of that type of mesoscale cloud feature. This model lends itself to computation of the average wind speed in northerly flow from the dimensions of the cloud band configurations measured from a LANDSAT image. In nearly every case, necessary conditions of a curved wind profile and orientation of the cloud streets within 20 degrees of the direction of the mean wind in the convective layer were met. Verification of the results by direct observation was hampered, however, by the incompatibility of the resolution of conventional rawinsonde observations with the scale of the banded cloud patterns measured from LANDSAT data. Comparison seems to be somewhat better in northerly flows than in southerly flows, with the largest discrepancies in wind speed being within 8m/sec, or a factor of two.

Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up.

PubMed

Muhamadali, Howbeer; Xu, Yun; Ellis, David I; Allwood, J William; Rattray, Nicholas J W; Correa, Elon; Alrabiah, Haitham; Lloyd, Jonathan R; Goodacre, Royston

2015-05-15

During the industrial scale-up of bioprocesses it is important to establish that the biological system has not changed significantly when moving from small laboratory-scale shake flasks or culturing bottles to an industrially relevant production level. Therefore, during upscaling of biomass production for a range of metal transformations, including the production of biogenic magnetite nanoparticles by Geobacter sulfurreducens, from 100-ml bench-scale to 5-liter fermentors, we applied Fourier transform infrared (FTIR) spectroscopy as a metabolic fingerprinting approach followed by the analysis of bacterial cell extracts by gas chromatography-mass spectrometry (GC-MS) for metabolic profiling. FTIR results clearly differentiated between the phenotypic changes associated with different growth phases as well as the two culturing conditions. Furthermore, the clustering patterns displayed by multivariate analysis were in agreement with the turbidimetric measurements, which displayed an extended lag phase for cells grown in a 5-liter bioreactor (24 h) compared to those grown in 100-ml serum bottles (6 h). GC-MS analysis of the cell extracts demonstrated an overall accumulation of fumarate during the lag phase under both culturing conditions, coinciding with the detected concentrations of oxaloacetate, pyruvate, nicotinamide, and glycerol-3-phosphate being at their lowest levels compared to other growth phases. These metabolites were overlaid onto a metabolic network of G. sulfurreducens, and taking into account the levels of these metabolites throughout the fermentation process, the limited availability of oxaloacetate and nicotinamide would seem to be the main metabolic bottleneck resulting from this scale-up process. Additional metabolite-feeding experiments were carried out to validate the above hypothesis. Nicotinamide supplementation (1 mM) did not display any significant effects on the lag phase of G. sulfurreducens cells grown in the 100-ml serum bottles. However

Gas-solid fluidized bed reactors: Scale-up, flow regimes identification and hydrodynamics

NASA Astrophysics Data System (ADS)

Zaid, Faraj Muftah

This research studied the scale-up, flow regimes identification and hydrodynamics of fluidized beds using 6-inch and 18- inch diameter columns and different particles. One of the objectives was to advance the scale-up of gas-solid fluidized bed reactors by developing a new mechanistic methodology for hydrodynamic similarity based on matching the radial or diameter profile of gas phase holdup, since gas dynamics dictate the hydrodynamics of these reactors. This has been successfully achieved. However, the literature reported scale-up methodology based on matching selected dimensionless groups was examined and it was found that it was not easy to match the dimensionless groups and hence, there was some deviation in the hydrodynamics of the studied two different fluidized beds. A new technique based on gamma ray densitometry (GRD) was successfully developed and utilized to on-line monitor the implementation of scale-up, to identify the flow regime, and to measure the radial or diameter profiles of gas and solids holdups. CFD has been demonstrated as a valuable tool to enable the implementation of the newly developed scale-up methodology based on finding the conditions that provide similar or closer radial profile or cross sectional distribution of the gas holdup. As gas velocity increases, solids holdup in the center region of the column decreases in the fully developed region of both 6 inch and 18 inch diameter columns. Solids holdup increased with the increase in the particles size and density. Upflowing particles velocity increased with the gas velocity and became steeper at high superficial gas velocity at all axial heights where the center line velocity became higher than that in the wall region. Smaller particles size and lower density gave larger upflowing particles velocity. Minimum fluidization velocity and transition velocity from bubbly to churn turbulent flow regimes were found to be lower in 18 inch diameter column compared to those obtained in 6 inch

The Newtonian Mechanistic Paradigm, Special Education, and Contours of Alternatives: An Overview.

ERIC Educational Resources Information Center

Heshusius, Lous

1989-01-01

The article examines theoretical reorientations in special education away from the Newtonian mechanistic paradigm toward an emerging holistic paradigm. Recent literature is critiqued for renaming theories as paradigms, thereby providing an illusion of change while leaving fundamental mechanistic assumptions in place. (Author/DB)

A comparative analysis of rawinsonde and NIMBUS 6 and TIROS N satellite profile data

NASA Technical Reports Server (NTRS)

Scoggins, J. R.; Carle, W. E.; Knight, K.; Moyer, V.; Cheng, N. M.

1981-01-01

Comparisons are made between rawinsonde and satellite profiles in seven areas for a wide range of surface and weather conditions. Variables considered include temperature, dewpoint temperature, thickness, precipitable water, lapse rate of temperature, stability, geopotential height, mixing ratio, wind direction, wind speed, and kinematic parameters, including vorticity and the advection of vorticity and temperature. In addition, comparisons are made in the form of cross sections and synoptic fields for selected variables. Sounding data from the NIMBUS 6 and TIROS N satellites were used. Geostrophic wind computed from smoothed geopotential heights provided large scale flow patterns that agreed well with the rawinsonde wind fields. Surface wind patterns as well as magnitudes computed by use of the log law to extrapolate wind to a height of 10 m agreed with observations. Results of this study demonstrate rather conclusively that satellite profile data can be used to determine characteristics of large scale systems but that small scale features, such as frontal zones, cannot yet be resolved.

Refined pipe theory for mechanistic modeling of wood development.

PubMed

Deckmyn, Gaby; Evans, Sam P; Randle, Tim J

2006-06-01

We present a mechanistic model of wood tissue development in response to changes in competition, management and climate. The model is based on a refinement of the pipe theory, where the constant ratio between sapwood and leaf area (pipe theory) is replaced by a ratio between pipe conductivity and leaf area. Simulated pipe conductivity changes with age, stand density and climate in response to changes in allocation or pipe radius, or both. The central equation of the model, which calculates the ratio of carbon (C) allocated to leaves and pipes, can be parameterized to describe the contrasting stem conductivity behavior of different tree species: from constant stem conductivity (functional homeostasis hypothesis) to height-related reduction in stem conductivity with age (hydraulic limitation hypothesis). The model simulates the daily growth of pipes (vessels or tracheids), fibers and parenchyma as well as vessel size and simulates the wood density profile and the earlywood to latewood ratio from these data. Initial runs indicate the model yields realistic seasonal changes in pipe radius (decreasing pipe radius from spring to autumn) and wood density, as well as realistic differences associated with the competitive status of trees (denser wood in suppressed trees).

Numerical Simulation of The Mediterranean Sea Using Diecast: Interaction Between Basin, Sub-basin and Local Scale Features and Natural Variability.

NASA Astrophysics Data System (ADS)

Fernández, V.; Dietrich, D. E.; Haney, R. L.; Tintoré, J.

In situ and satellite data obtained during the last ten years have shown that the circula- tion in the Mediterranean Sea is extremely complex in space, with significant features ranging from mesoscale to sub-basin and basin scale, and highly variable in time, with mesoscale to seasonal and interannual signals. Also, the steep bottom topography and the variable atmospheric conditions from one sub-basin to another, make the circula- tion to be composed of numerous energetic and narrow coastal currents, density fronts and mesoscale structures that interact at sub-basin scale with the large scale circula- tion. To simulate numerically and better understand these features, besides high grid resolution, a low numerical dispersion and low physical dissipation ocean model is required. We present the results from a 1/8z horizontal resolution numerical simula- tion of the Mediterranean Sea using DieCAST ocean model, which meets the above requirements since it is stable with low general dissipation and uses accurate fourth- order-accurate approximations with low numerical dispersion. The simulations are carried out with climatological surface forcing using monthly mean winds and relax- ation towards climatological values of temperature and salinity. The model reproduces the main features of the large basin scale circulation, as well as the seasonal variabil- ity of sub-basin scale currents that are well documented by observations in straits and channels. In addition, DieCAST brings out natural fronts and eddies that usually do not appear in numerical simulations of the Mediterranean and that lead to a natural interannual variability. The role of this intrinsic variability in the general circulation will be discussed.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information.

PubMed

Waldner, François; Hansen, Matthew C; Potapov, Peter V; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information

PubMed Central

Hansen, Matthew C.; Potapov, Peter V.; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring. PMID:28817618

A new scoring model for characterization of adnexal masses based on two-dimensional gray-scale and colour Doppler sonographic features

PubMed Central

Abbas, A.M.; Zahran, K.M.; Nasr, A.; Kamel, H.S.

2014-01-01

Objective: To determine the most discriminating two-dimensional gray-scale and colour Doppler sonographic features that allow differentiation between malignant and benign adnexal masses, and to develop a scoring model that would enable more accurate diagnosis with those features. Methods: A cross sectional prospective study was conducted on patients scheduled for surgery due to presence of adnexal masses at Woman’s Health Center, Assiut University, Egypt between October 2012 and October 2013. All patients were evaluated by 2D ultrasound for morphological features of the masses combined with colour Doppler examination of their vessels. The final diagnosis, based on histopathological analysis, was used as a gold standard. Results: One hundred forty-six patients were recruited, 104 with benign masses, 42 with malignant masses. Features that allowed statistically significant discrimination of benignity from malignancy were; volume of mass, type of mass, presence and thickness of septae, presence and length of papillary projections, location of vessels at colour Doppler and colour score. A scoring model was formulated combining these features together; Assiut Scoring Model (ASM). The cut-off level with the highest accuracy in detection of malignancy, was ≥6, had a sensitivity of 93.5% and specificity of 92.2%. Conclusion: Our Scoring Model; a multiparameter scoring using four gray-scale ultrasound and two colour Doppler features, had shown a high sensitivity and specificity for prediction of malignancy in adnexal masses compared with previous scoring systems. PMID:25009729

Mechanistic model for catalytic recombination during aerobraking maneuvers

NASA Technical Reports Server (NTRS)

Willey, Ronald J.

1989-01-01

Several mechanistic models are developed to predict recombination coefficients for use in heat shield design for reusable surface insulation (RSI) on aerobraking vehicles such as space shuttles. The models are applied over a temperature range of 300 to 1800 K and a stagnation pressure range of 0 to 3,000 Pa. A four parameter model in temperature was found to work best; however, several models (including those with atom concentrations at the surface) were also investigated. Mechanistic models developed with atom concentration terms may be applicable when sufficient data becomes available. The requirement is shown for recombination experiments in the 300 to 1000 K and 1500 to 1850 K temperature range, with deliberate concentration variations.

Specialists without spirit: limitations of the mechanistic biomedical model.

PubMed

Hewa, S; Hetherington, R W

1995-06-01

This paper examines the origin and the development of the mechanistic model of the human body and health in terms of Max Weber's theory of rationalization. It is argued that the development of Western scientific medicine is a part of the broad process of rationalization that began in sixteenth century Europe as a result of the Reformation. The development of the mechanistic view of the human body in Western medicine is consistent with the ideas of calculability, predictability, and control-the major tenets of the process of rationalization as described by Weber. In recent years, however, the limitations of the mechanistic model have been the topic of many discussions. George Engel, a leading advocate of general systems theory, is one of the leading proponents of a new medical model which includes the general quality of life, clean environment, and psychological, or spiritual stability of life. The paper concludes with consideration of the potential of Engel's proposed new model in the context of the current state of rationalization in modern industrialized society.

A Biologically Informed, Mechanistic Model of Desert Shrub Population Dynamics Bearing on Arid Landscape Evolution

NASA Astrophysics Data System (ADS)

Worman, Stacey; Furbish, David; Fathel, Siobhan

2014-05-01

In arid landscapes, desert shrubs individually and collectively modify how sediment is transported (e.g by wind, overland-flow, and rain-splash). Addressing how desert shrubs modify landscapes on geomorphic timescales therefore necessitates spanning multiple shrub lifetimes and accounting for how processes affecting shrub dynamics on these longer timescales (e.g. fire, grazing, drought, and climate change) may in turn impact sediment transport. To fulfill this need, we present a mechanistic model of the spatiotemporal dynamics of a desert-shrub population that uses a simple accounting framework and tracks individual shrubs as they enter, age, and exit the population (via recruitment, growth, and mortality). Our model is novel insomuch as it (1) features a strong biophysical foundation, (2) mimics well-documented aspects of how shrub populations respond to changes in precipitation, and (3) possesses the process granularity appropriate for use in geomorphic simulations. In a complimentary abstract (Fathel et al. 2014), we demonstrate the potential of this biological model by coupling it to a physical model of rain-splash sediment transport: We mechanistically reproduce the empirical observation that the erosion rate of a hillslope decreases as its vegetation coverage increases and we predict erosion rates under different climate-change scenarios.

From the exposome to mechanistic understanding of chemical ...

EPA Pesticide Factsheets

BACKGROUND: Current definitions of the exposome expand beyond the initial idea to consider the totality of exposure and aim to relate to biological effects. While the exposome has been established for human health, its principles can be extended to include broader ecological issues. The assessment of exposure is tightly interlinked with hazard assessment. OBJECTIVES: We explore if mechanistic understanding of the causal links between exposure and adverse effects on human health and the environment can be improved by integrating the exposome approach with the adverse outcome pathway (AOP) concept - a framework to structure and organize the sequence of toxicological events from an initial molecular interaction of a chemical to an adverse outcome.METHODS: This review was informed by a Workshop organized by the Integrated Project EXPOSOME at the UFZ Helmholtz Centre for Environmental Research in Leipzig, Germany. DISCUSSION: The exposome encompasses all chemicals, including exogenous chemicals and endogenous compounds that are produced in response to external factors. By complementing the exposome research with the AOP concept, we can achieve a better mechanistic understanding, weigh the importance of various components of the exposome, and determine primary risk drivers. The ability to interpret multiple exposures and mixture effects at the mechanistic level requires a more holistic approach facilitated by the exposome concept.CONCLUSION: Incorporating the AOP conc

Why did Jacques Monod make the choice of mechanistic determinism?

PubMed

Loison, Laurent

2015-06-01

The development of molecular biology placed in the foreground a mechanistic and deterministic conception of the functioning of macromolecules. In this article, I show that this conception was neither obvious, nor necessary. Taking Jacques Monod as a case study, I detail the way he gradually came loose from a statistical understanding of determinism to finally support a mechanistic understanding. The reasons of the choice made by Monod at the beginning of the 1950s can be understood only in the light of the general theoretical schema supported by the concept of mechanistic determinism. This schema articulates three fundamental notions for Monod, namely that of the rigidity of the sequence of the genetic program, that of the intrinsic stability of macromolecules (DNA and proteins), and that of the specificity of molecular interactions. Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Kinetic and mechanistic reactivity. Isoprene impact on ozone levels in an urban area near Tijuca Forest, Rio de Janeiro.

PubMed

da Silva, Cleyton Martins; da Silva, Luane Lima; Corrêa, Sergio Machado; Arbilla, Graciela

2016-12-01

Volatile organic compounds (VOCs) play a central role in atmospheric chemistry. In this work, the kinetic and mechanistic reactivities of VOCs are analyzed, and the contribution of the organic compounds emitted by anthropogenic and natural sources is estimated. VOCs react with hydroxyl radicals and other photochemical oxidants, such as ozone and nitrate radicals, which cause the conversion of NO to NO 2 in various potential reaction paths, including photolysis, to form oxygen atoms, which generate ozone. The kinetic reactivity was evaluated based on the reaction coefficients for hydroxyl radicals with VOCs. The mechanistic reactivity was estimated using a detailed mechanism and the incremental reactivity scale that Carter proposed. Different scenarios were proposed and discussed, and a minimum set of compounds, which may describe the tropospheric reactivity in the studied area, was determined. The role of isoprene was analyzed in terms of its contribution to ozone formation.

Emphasizing Social Features in Information Portals: Effects on New Member Engagement

PubMed Central

Sharma, Nikhil; Butler, Brian S.; Irwin, Jeannie; Spallek, Heiko

2013-01-01

Many information portals are adding social features with hopes of enhancing the overall user experience. Invitations to join and welcome pages that highlight these social features are expected to encourage use and participation. While this approach is widespread and seems plausible, the effect of providing and highlighting social features remains to be tested. We studied the effects of emphasizing social features on users' response to invitations, their decisions to join, their willingness to provide profile information, and their engagement with the portal's social features. The results of a quasi-experiment found no significant effect of social emphasis in invitations on receivers' responsiveness. However, users receiving invitations highlighting social benefits were less likely to join the portal and provide profile information. Social emphasis in the initial welcome page for the site also was found to have a significant effect on whether individuals joined the portal, how much profile information they provided and shared, and how much they engaged with social features on the site. Unexpectedly, users who were welcomed in a social manner were less likely to join and provided less profile information; they also were less likely to engage with social features of the portal. This suggests that even in online contexts where social activity is an increasingly common feature, highlighting the presence of social features may not always be the optimal presentation strategy. PMID:23626487

MECHANISTIC-BASED DISINFECTION AND DISINFECTION BYPRODUCT MODELS

EPA Science Inventory

We propose developing a mechanistic-based numerical model for chlorine decay and regulated DBP (THM and HAA) formation derived from (free) chlorination; the model framework will allow future modifications for other DBPs and chloramination. Predicted chlorine residual and DBP r...

Mechanistic Indicators of Childhood Asthma (MICA) Study

EPA Science Inventory

The Mechanistic Indicators of Childhood Asthma (MICA) Study has been designed to incorporate state-of-the-art technologies to examine the physiological and environmental factors that interact to increase the risk of asthmatic responses. MICA is primarily a clinically-bases obser...

Scaling laws describe memories of host-pathogen riposte in the HIV population.

PubMed

Barton, John P; Kardar, Mehran; Chakraborty, Arup K

2015-02-17

The enormous genetic diversity and mutability of HIV has prevented effective control of this virus by natural immune responses or vaccination. Evolution of the circulating HIV population has thus occurred in response to diverse, ultimately ineffective, immune selection pressures that randomly change from host to host. We show that the interplay between the diversity of human immune responses and the ways that HIV mutates to evade them results in distinct sets of sequences defined by similar collectively coupled mutations. Scaling laws that relate these sets of sequences resemble those observed in linguistics and other branches of inquiry, and dynamics reminiscent of neural networks are observed. Like neural networks that store memories of past stimulation, the circulating HIV population stores memories of host-pathogen combat won by the virus. We describe an exactly solvable model that captures the main qualitative features of the sets of sequences and a simple mechanistic model for the origin of the observed scaling laws. Our results define collective mutational pathways used by HIV to evade human immune responses, which could guide vaccine design.

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

SMOOTHING ROTATION CURVES AND MASS PROFILES

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

Berrier, Joel C.; Sellwood, J. A.

2015-02-01

We show that spiral activity can erase pronounced features in disk galaxy rotation curves. We present simulations of growing disks, in which the added material has a physically motivated distribution, as well as other examples of physically less realistic accretion. In all cases, attempts to create unrealistic rotation curves were unsuccessful because spiral activity rapidly smoothed away features in the disk mass profile. The added material was redistributed radially by the spiral activity, which was itself provoked by the density feature. In the case of a ridge-like feature in the surface density profile, we show that two unstable spiral modesmore » develop, and the associated angular momentum changes in horseshoe orbits remove particles from the ridge and spread them both inward and outward. This process rapidly erases the density feature from the disk. We also find that the lack of a feature when transitioning from disk to halo dominance in the rotation curves of disk galaxies, the so called ''disk-halo conspiracy'', could also be accounted for by this mechanism. We do not create perfectly exponential mass profiles in the disk, but suggest that this mechanism contributes to their creation.« less

OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.

PubMed

Jia, Cang-Zhi; He, Wen-Ying; Yao, Yu-Hua

2017-03-01

Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

Long-term changes in ultraviolet P Cygni profiles observed with Copernicus

NASA Technical Reports Server (NTRS)

Snow, T. P., Jr.

1977-01-01

The incidence and nature of variability occurring on time scales of years in the ultraviolet P Cygni profiles of 15 O and B stars are investigated using spectrophotometric data obtained with the Copernicus satellite. It is found that some change in at least a few details of the P Cygni profiles is evident in almost every case, that the changes in a few stars appear to represent substantial variations in the column densities of the particular ions observed, and that the changes in other stars are minor in nature and do not result from significant alterations in the quantity of material in the stellar winds. Most of the narrow absorption features are shown to be invariant in velocity, although their strengths have apparently changed in certain cases. The nature of the changes observed in each of the program stars is briefly described, the time scale for variability in the stellar winds is considered, and two stars (Zeta Pup and Delta Ori A) are identified for which some alteration in the total amount of material in the stellar wind has taken place. It is suggested that the narrow absorption features probably represent temperature gradients or plateaus in the stellar-wind velocity fields or may be caused by flat regions in the height dependence of the wind velocity.

A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection

NASA Astrophysics Data System (ADS)

Li, Yongbo; Yang, Yuantao; Li, Guoyan; Xu, Minqiang; Huang, Wenhu

2017-07-01

Health condition identification of planetary gearboxes is crucial to reduce the downtime and maximize productivity. This paper aims to develop a novel fault diagnosis method based on modified multi-scale symbolic dynamic entropy (MMSDE) and minimum redundancy maximum relevance (mRMR) to identify the different health conditions of planetary gearbox. MMSDE is proposed to quantify the regularity of time series, which can assess the dynamical characteristics over a range of scales. MMSDE has obvious advantages in the detection of dynamical changes and computation efficiency. Then, the mRMR approach is introduced to refine the fault features. Lastly, the obtained new features are fed into the least square support vector machine (LSSVM) to complete the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault types of planetary gearboxes.

Measuring Child Poverty in South Africa: Sensitivity to the Choice of Equivalence Scale and an Updated Profile

ERIC Educational Resources Information Center

Streak, Judith Christine; Yu, Derek; Van der Berg, Servaas

2009-01-01

This paper offers evidence on the sensitivity of child poverty in South Africa to changes in the adult equivalence scale (AES) and updates the child poverty profile based on the Income and Expenditure Survey 2005/06. Setting the poverty line at the 40th percentile of households calculated with different AESs the scope and composition of child…

Projective rectification of infrared images from air-cooled condenser temperature measurement by using projection profile features and cross-ratio invariability.

PubMed

Xu, Lijun; Chen, Lulu; Li, Xiaolu; He, Tao

2014-10-01

In this paper, we propose a projective rectification method for infrared images obtained from the measurement of temperature distribution on an air-cooled condenser (ACC) surface by using projection profile features and cross-ratio invariability. In the research, the infrared (IR) images acquired by the four IR cameras utilized are distorted to different degrees. To rectify the distorted IR images, the sizes of the acquired images are first enlarged by means of bicubic interpolation. Then, uniformly distributed control points are extracted in the enlarged images by constructing quadrangles with detected vertical lines and detected or constructed horizontal lines. The corresponding control points in the anticipated undistorted IR images are extracted by using projection profile features and cross-ratio invariability. Finally, a third-order polynomial rectification model is established and the coefficients of the model are computed with the mapping relationship between the control points in the distorted and anticipated undistorted images. Experimental results obtained from an industrial ACC unit show that the proposed method performs much better than any previous method we have adopted. Furthermore, all rectified images are stitched together to obtain a complete image of the whole ACC surface with a much higher spatial resolution than that obtained by using a single camera, which is not only useful but also necessary for more accurate and comprehensive analysis of ACC performance and more reliable optimization of ACC operations.

Mechanistic models of biofilm growth in porous media

NASA Astrophysics Data System (ADS)

Jaiswal, Priyank; Al-Hadrami, Fathiya; Atekwana, Estella A.; Atekwana, Eliot A.

2014-07-01

Nondestructive acoustics methods can be used to monitor in situ biofilm growth in porous media. In practice, however, acoustic methods remain underutilized due to the lack of models that can translate acoustic data into rock properties in the context of biofilm. In this paper we present mechanistic models of biofilm growth in porous media. The models are used to quantitatively interpret arrival times and amplitudes recorded in the 29 day long Davis et al. (2010) physical scale biostimulation experiment in terms of biofilm morphologies and saturation. The model pivots on addressing the sediment elastic behavior using the lower Hashin-Shtrikman bounds for grain mixing and Gassmann substitution for fluid saturation. The time-lapse P wave velocity (VP; a function of arrival times) is explained by a combination of two rock models (morphologies); "load bearing" which assumes the biofilm as an additional mineral in the rock matrix and "pore filling" which assumes the biofilm as an additional fluid phase in the pores. The time-lapse attenuation (QP-1; a function of amplitudes), on the other hand, can be explained adequately in two ways; first, through squirt flow where energy is lost from relative motion between rock matrix and pore fluid, and second, through an empirical function of porosity (φ), permeability (κ), and grain size. The squirt flow model-fitting results in higher internal φ (7% versus 5%) and more oblate pores (0.33 versus 0.67 aspect ratio) for the load-bearing morphology versus the pore-filling morphology. The empirical model-fitting results in up to 10% increase in κ at the initial stages of the load-bearing morphology. The two morphologies which exhibit distinct mechanical and hydraulic behavior could be a function of pore throat size. The biofilm mechanistic models developed in this study can be used for the interpretation of seismic data critical for the evaluation of biobarriers in bioremediation, microbial enhanced oil recovery, and CO2

Terrain profiling from Seasat altimetry

NASA Technical Reports Server (NTRS)

Brooks, R. L.

1981-01-01

To determine their applicability for terrain profiling, Seasat altimeter measurements were analyzed for the following geographic areas: (1) Andean salars of southern Bolivia; (2) Alaska; (3) south-central Arizona; (4) imperial Valley of California; (5) Yuma Valley of Arizona; and (6) Great Salt Lake Desert. Analysis of the data over all of these geographic areas shows that the satellite altimeter servo did not respond quickly enough to changing terrain features. However, it is demonstrated that retracking of the archived surface return waveforms yields surface elevations over smooth terrain accurate to + or - 1 m when correlated with large scale maps. The retracking algorithm used and its verification over the salars of southern Bolivia are described. Results are presented for each of the six geographic areas.

Simulated cosmic microwave background maps at 0.5 deg resolution: Unresolved features

NASA Technical Reports Server (NTRS)

Kogut, A.; Hinshaw, G.; Bennett, C. L.

1995-01-01

High-contrast peaks in the cosmic microwave background (CMB) anisotropy can appear as unresolved sources to observers. We fit simluated CMB maps generated with a cold dark matter model to a set of unresolved features at instrumental resolution 0.5 deg-1.5 deg to derive the integral number density per steradian n (greater than absolute value of T) of features brighter than threshold temperature absolute value of T and compare the results to recent experiments. A typical medium-scale experiment observing 0.001 sr at 0.5 deg resolution would expect to observe one feature brighter than 85 micro-K after convolution with the beam profile, with less than 5% probability to observe a source brighter than 150 micro-K. Increasing the power-law index of primordial density perturbations n from 1 to 1.5 raises these temperature limits absolute value of T by a factor of 2. The MSAM features are in agreement with standard cold dark matter models and are not necessarily evidence for processes beyond the standard model.

Surface layer and bloom dynamics observed with the Prince William Sound Autonomous Profiler

NASA Astrophysics Data System (ADS)

Campbell, R. W.

2016-02-01

As part of a recent long term monitoring effort, deployments of a WETLabs Autonomous Moored Profiler (AMP) began Prince William Sound (PWS) in 2013. The PWS AMP consists of a positively buoyant instrument frame, with a winch and associated electronics that profiles the frame from a park depth (usually 55 m) to the surface by releasing and retrieving a thin UHMWPE tether; it generally conducts a daily cast and measures temperature, salinity, chlorophyll-a fluorescence, turbidity, and oxygen and nitrate concentrations. Upward and downward looking ADCPs are mounted on a float below the profiler, and an in situ plankton imager is in development and will be installed in 2016. Autonomous profilers are a relatively new technology, and early deployments experienced a number of failures from which valuable lessons may be learned. Nevertheless, an unprecedented time series of the seasonal biogeochemical procession in the surface waters coastal Gulf of Alaska was collected in 2014 and 2015. The northern Gulf of Alaska has experienced a widespread warm anomaly since early 2014, and surface layer temperature anomalies in PWS were strongly positive during winter 2014. The spring bloom observed by the profiler began 2-3 weeks earlier than average, with surface nitrate depleted by late April. Although surface temperatures were still above average in 2015, bloom timing was much later, with a short vigorous bloom in late April and a subsurface bloom in late May that coincided with significant nitrate drawdown. As well as the vernal blooms, wind-driven upwelling events lead to several small productivity pulses that were evident in changes in nitrate and oxygen concentrations, and chlorophyll-a fluorescence. As well as providing a mechanistic understanding of surface layer biogeochemistry, high frequency observations such as these put historical observations in context, and provide new insights into the scales of variability in the annual cycles of the surface ocean in the North

Target biomarker profile for the clinical management of paracetamol overdose

PubMed Central

Vliegenthart, A D Bastiaan; Antoine, Daniel J; Dear, James W

2015-01-01

Paracetamol (acetaminophen) overdose is one of the most common causes of acute liver injury in the Western world. To improve patient care and reduce pressure on already stretched health care providers new biomarkers are needed that identify or exclude liver injury soon after an overdose of paracetamol is ingested. This review highlights the current state of paracetamol poisoning management and how novel biomarkers could improve patient care and save healthcare providers money. Based on the widely used concept of defining a target product profile, a target biomarker profile is proposed that identifies desirable and acceptable key properties for a biomarker in development to enable the improved treatment of this patient population. The current biomarker candidates, with improved hepatic specificity and based on the fundamental mechanistic basis of paracetamol-induced liver injury, are reviewed and their performance compared with our target profile. PMID:26076366

The Basic Metabolic Profile in Heart Failure-Marker and Modifier.

PubMed

Elfar, Ahmed; Sambandam, Kamalanathan K

2017-08-01

The physiologic determinants of each of the components of the basic metabolic profile in patients with heart failure will be explored. Additionally, the review will discuss the prognostic value of alterations in the basic metabolic profile as well as their effects on management. Abnormalities in the basic metabolic profile have significant correlation with clinical outcomes and can modify treatment in heart failure. Hypochloremia has recently received increased attention for these reasons. Elevated creatinine, increased blood urea nitrogen, hyponatremia, and hypochloremia correlate with worse mortality and diuretic resistance in heart failure. Hypokalemia, even when mild, has proven to be a worse clinical indicator than modest elevations in serum potassium. Hypochloremia is mechanistically linked to hyponatremia and metabolic alkalosis, but recent compelling data suggests that it can provide more discriminating prognostic information. Knowledge of the physiologic basis for each of these alterations informs their management.

In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features.

PubMed

Ding, Yiliang; Tang, Yin; Kwok, Chun Kit; Zhang, Yu; Bevilacqua, Philip C; Assmann, Sarah M

2014-01-30

RNA structure has critical roles in processes ranging from ligand sensing to the regulation of translation, polyadenylation and splicing. However, a lack of genome-wide in vivo RNA structural data has limited our understanding of how RNA structure regulates gene expression in living cells. Here we present a high-throughput, genome-wide in vivo RNA structure probing method, structure-seq, in which dimethyl sulphate methylation of unprotected adenines and cytosines is identified by next-generation sequencing. Application of this method to Arabidopsis thaliana seedlings yielded the first in vivo genome-wide RNA structure map at nucleotide resolution for any organism, with quantitative structural information across more than 10,000 transcripts. Our analysis reveals a three-nucleotide periodic repeat pattern in the structure of coding regions, as well as a less-structured region immediately upstream of the start codon, and shows that these features are strongly correlated with translation efficiency. We also find patterns of strong and weak secondary structure at sites of alternative polyadenylation, as well as strong secondary structure at 5' splice sites that correlates with unspliced events. Notably, in vivo structures of messenger RNAs annotated for stress responses are poorly predicted in silico, whereas mRNA structures of genes related to cell function maintenance are well predicted. Global comparison of several structural features between these two categories shows that the mRNAs associated with stress responses tend to have more single-strandedness, longer maximal loop length and higher free energy per nucleotide, features that may allow these RNAs to undergo conformational changes in response to environmental conditions. Structure-seq allows the RNA structurome and its biological roles to be interrogated on a genome-wide scale and should be applicable to any organism.

Searching for a neurologic injury's Wechsler Adult Intelligence Scale-Third Edition profile.

PubMed

Gonçalves, Marta A; Moura, Octávio; Castro-Caldas, Alexandre; Simões, Mário R

2017-01-01

This study aimed to investigate the presence of a Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) cognitive profile in a Portuguese neurologic injured sample. The Portuguese WAIS-III was administered to 81 mixed neurologic patients and 81 healthy matched controls selected from the Portuguese standardization sample. Although the mixed neurologic injury group performed significantly lower than the healthy controls for the majority of the WAIS-III scores (i.e., composite measures, discrepancies, and subtests), the mean scores were within the normal range and, therefore, at risk of being unobserved in a clinical evaluation. ROC curves analysis showed poor to acceptable diagnostic accuracy for the WAIS-III composite measures and subtests (Working Memory Index and Digit Span revealed the highest accuracy for discriminating between participants, respectively). Multiple regression analysis showed that both literacy and the presence of brain injury were significant predictors for all of the composite measures. In addition, multiple regression analysis also showed that literacy, age of injury onset, and years of survival predicted all seven composite measures for the mixed neurologic injured group. Despite the failure to find a WAIS-III cognitive profile for mixed neurologic patients, the results showed a significant influence of brain lesion and literacy in the performance of the WAIS-III.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Exploring Organic Mechanistic Puzzles with Molecular Modeling

ERIC Educational Resources Information Center

Horowitz, Gail; Schwartz, Gary

2004-01-01

The molecular modeling was used to reinforce more general skills such as deducing and drawing reaction mechanisms, analyzing reaction kinetics and thermodynamics and drawing reaction coordinate energy diagrams. This modeling was done through the design of mechanistic puzzles, involving reactions not familiar to the students.

Performance assessment and calibration of a profiling lab-scale acoustic Doppler velocimeter for application over mixed sand-gravel beds

USDA-ARS?s Scientific Manuscript database

Acoustic Doppler velocimetry has made high-resolution turbulence measurements in sediment-laden flows possible. Recent developments have resulted in a commercially available lab-scale acoustic Doppler profiling device, a Nortek Vectrino II, that allows for three-dimensional velocity data to be colle...

Data on morphological features of mycosis induced by Colletotrichum nymphaeae and Lecanicillium longisporum on citrus orthezia scale.

PubMed

Mascarin, Gabriel Moura; Guarín-Molina, Juan Humberto; Arthurs, Steven Paul; Humber, Richard Alan; de Andrade Moral, Rafael; Demétrio, Clarice Garcia Borges; Delalibera, Ítalo

2016-09-01

We describe symptoms of mycosis induced by two native fungal entomopathogens of the citrus orthezia scale, Praelongorthezia praelonga (Hemiptera: Ortheziidae), an important pest of citrus orchards. The data presented in this article are related to the article entitled "Seasonal prevalence of the insect pathogenic fungus Colletotrichum nymphaeae in Brazilian citrus groves under different chemical pesticide regimes" [1]. The endemic fungal pathogen, C. nymphaeae, emerges through the thin cuticular intersegmental regions of the citrus orthezia scale body revealing orange salmon-pigmented conidiophores bearing conidial masses, as well as producing rhizoid-like hyphae that extend over the citrus leaf. By contrast, nymphs or adult females of this scale insect infected with Lecanicillium longisporum exhibit profuse outgrowth of bright white-pigmented conidiophores with clusters of conidia emerging from the insect intersegmental membranes, and mycosed cadavers are commonly observed attached to the leaf surface by hyphal extensions. These morphological differences are important features to discriminate these fungal entomopathogens in citrus orthezia scales.

Mechanistically linked serum miRNAs distinguish between drug induced and fatty liver disease of different grades.

PubMed

Liu, Zhichao; Wang, Yuping; Borlak, Jürgen; Tong, Weida

2016-04-05

Hepatic steatosis is characterised by excessive triglyceride accumulation in the form of lipid droplets (LD); however, mechanisms differ in drug induced (DIS) and/or non-alcoholic fatty liver disease (NAFLD). Here we hypothesized distinct molecular circuits of microRNA/LD-associated target genes and searched for mechanistically linked serum and tissue biomarkers that would distinguish between DIS and human NAFLD of different grades. We analysed >800 rat hepatic whole genome data for 17 steatotic drugs and identified 157 distinct miRNAs targeting 77 DIS regulated genes. Subsequently, genomic data of N = 105 cases of human NAFLD and N = 32 healthy controls were compared to serum miRNA profiles of N = 167 NAFLD patients. This revealed N = 195 tissue-specific miRNAs being mechanistically linked to LD-coding genes and 24 and 9 miRNAs were commonly regulated in serum and tissue of advanced and mild NAFLD, respectively. The NASH serum regulated miRNAs informed on hepatic inflammation, adipocytokine and insulin signalling, ER-and caveolae associated activities and altered glycerolipid metabolism. Conversely, serum miRNAs associated with blunt steatosis specifically highlighted activity of FOXO1&HNF4α on CPT2, the lipid droplet and ER-lipid-raft associated PLIN3 and Erlin1. Altogether, serum miRNAs informed on the molecular pathophysiology of NAFLD and permitted differentiation between DIS and NAFLD of different grades.

A preliminary study of mechanistic approach in pavement design to accommodate climate change effects

NASA Astrophysics Data System (ADS)

Harnaeni, S. R.; Pramesti, F. P.; Budiarto, A.; Setyawan, A.

2018-03-01

Road damage is caused by some factors, including climate changes, overload, and inappropriate procedure for material and development process. Meanwhile, climate change is a phenomenon which cannot be avoided. The effects observed include air temperature rise, sea level rise, rainfall changes, and the intensity of extreme weather phenomena. Previous studies had shown the impacts of climate changes on road damage. Therefore, several measures to anticipate the damage should be considered during the planning and construction in order to reduce the cost of road maintenance. There are three approaches generally applied in the design of flexible pavement thickness, namely mechanistic approach, mechanistic-empirical (ME) approach and empirical approach. The advantages of applying mechanistic approach or mechanistic-empirical (ME) approaches are its efficiency and reliability in the design of flexible pavement thickness as well as its capacity to accommodate climate changes in compared to empirical approach. However, generally, the design of flexible pavement thickness in Indonesia still applies empirical approach. This preliminary study aimed to emphasize the importance of the shifting towards a mechanistic approach in the design of flexible pavement thickness.

The global reference atmospheric model, mod 2 (with two scale perturbation model)

NASA Technical Reports Server (NTRS)

Justus, C. G.; Hargraves, W. R.

1976-01-01

The Global Reference Atmospheric Model was improved to produce more realistic simulations of vertical profiles of atmospheric parameters. A revised two scale random perturbation model using perturbation magnitudes which are adjusted to conform to constraints imposed by the perfect gas law and the hydrostatic condition is described. The two scale perturbation model produces appropriately correlated (horizontally and vertically) small scale and large scale perturbations. These stochastically simulated perturbations are representative of the magnitudes and wavelengths of perturbations produced by tides and planetary scale waves (large scale) and turbulence and gravity waves (small scale). Other new features of the model are: (1) a second order geostrophic wind relation for use at low latitudes which does not "blow up" at low latitudes as the ordinary geostrophic relation does; and (2) revised quasi-biennial amplitudes and phases and revised stationary perturbations, based on data through 1972.

Understanding the influence of biofilm accumulation on the hydraulic properties of soils: a mechanistic approach based on experimental data

NASA Astrophysics Data System (ADS)

Carles Brangarí, Albert; Sanchez-Vila, Xavier; Freixa, Anna; Romaní, Anna M.; Fernàndez-Garcia, Daniel

2017-04-01

hydraulic properties of bio-amended variably saturated soils. The new mechanistic model provides analytical equations for the water retention curve and the relative permeability. The approach consists in assuming that the porous media behaves as an ensemble of capillary tubes, which may be obtained from the experimental saturation profile. This premise is extended by considering the existence of biofilm bodies composed of bacteria and EPS. These compounds display a channeled geometry that reshapes the pore space at the pore-scale following specific geometrical patterns and changes its volume with suction. The hydraulic properties of the bio-amended soil can then be derived from the integrate contribution of the two biofilm compounds separately. Model can successfully reproduce displacements of the soil-water retention curve towards higher saturations and permeability reductions of distinct orders of magnitude.

Surface profiling interferometer

DOEpatents

Takacs, Peter Z.; Qian, Shi-Nan

1989-01-01

The design of a long-trace surface profiler for the non-contact measurement of surface profile, slope error and curvature on cylindrical synchrotron radiation (SR) mirrors. The optical system is based upon the concept of a pencil-beam interferometer with an inherent large depth-of-field. The key feature of the optical system is the zero-path-difference beam splitter, which separates the laser beam into two colinear, variable-separation probe beams. A linear array detector is used to record the interference fringe in the image, and analysis of the fringe location as a function of scan position allows one to reconstruct the surface profile. The optical head is mounted on an air bearing slide with the capability to measure long aspheric optics, typical of those encountered in SR applications. A novel feature of the optical system is the use of a transverse "outrigger" beam which provides information on the relative alignment of the scan axis to the cylinder optic symmetry axis.

Food for Thought ... Mechanistic Validation

PubMed Central

Hartung, Thomas; Hoffmann, Sebastian; Stephens, Martin

2013-01-01

Summary Validation of new approaches in regulatory toxicology is commonly defined as the independent assessment of the reproducibility and relevance (the scientific basis and predictive capacity) of a test for a particular purpose. In large ring trials, the emphasis to date has been mainly on reproducibility and predictive capacity (comparison to the traditional test) with less attention given to the scientific or mechanistic basis. Assessing predictive capacity is difficult for novel approaches (which are based on mechanism), such as pathways of toxicity or the complex networks within the organism (systems toxicology). This is highly relevant for implementing Toxicology for the 21st Century, either by high-throughput testing in the ToxCast/ Tox21 project or omics-based testing in the Human Toxome Project. This article explores the mostly neglected assessment of a test's scientific basis, which moves mechanism and causality to the foreground when validating/qualifying tests. Such mechanistic validation faces the problem of establishing causality in complex systems. However, pragmatic adaptations of the Bradford Hill criteria, as well as bioinformatic tools, are emerging. As critical infrastructures of the organism are perturbed by a toxic mechanism we argue that by focusing on the target of toxicity and its vulnerability, in addition to the way it is perturbed, we can anchor the identification of the mechanism and its verification. PMID:23665802

BIOMAP A Daily Time Step, Mechanistic Model for the Study of Ecosystem Dynamics

NASA Astrophysics Data System (ADS)

Wells, J. R.; Neilson, R. P.; Drapek, R. J.; Pitts, B. S.

2010-12-01

BIOMAP simulates competition between two Plant Functional Types (PFT) at any given point in the conterminous U.S. using a time series of daily temperature (mean, minimum, maximum), precipitation, humidity, light and nutrients, with PFT-specific rooting within a multi-layer soil. The model employs a 2-layer canopy biophysics, Farquhar photosynthesis, the Beer-Lambert Law for light attenuation and a mechanistic soil hydrology. In essence, BIOMAP is a re-built version of the biogeochemistry model, BIOME-BGC, into the form of the MAPSS biogeography model. Specific enhancements are: 1) the 2-layer canopy biophysics of Dolman (1993); 2) the unique MAPSS-based hydrology, which incorporates canopy evaporation, snow dynamics, infiltration and saturated and unsaturated percolation with ‘fast’ flow and base flow and a ‘tunable aquifer’ capacity, a metaphor of D’Arcy’s Law; and, 3) a unique MAPSS-based stomatal conductance algorithm, which simultaneously incorporates vapor pressure and soil water potential constraints, based on physiological information and many other improvements. Over small domains the PFTs can be parameterized as individual species to investigate fundamental vs. potential niche theory; while, at more coarse scales the PFTs can be rendered as more general functional groups. Since all of the model processes are intrinsically leaf to plot scale (physiology to PFT competition), it essentially has no ‘intrinsic’ scale and can be implemented on a grid of any size, taking on the characteristics defined by the homogeneous climate of each grid cell. Currently, the model is implemented on the VEMAP 1/2 degree, daily grid over the conterminous U.S. Although both the thermal and water-limited ecotones are dynamic, following climate variability, the PFT distributions remain fixed. Thus, the model is currently being fitted with a ‘reproduction niche’ to allow full dynamic operation as a Dynamic General Vegetation Model (DGVM). While global simulations

Traffic sign recognition based on a context-aware scale-invariant feature transform approach

NASA Astrophysics Data System (ADS)

Yuan, Xue; Hao, Xiaoli; Chen, Houjin; Wei, Xueye

2013-10-01

A new context-aware scale-invariant feature transform (CASIFT) approach is proposed, which is designed for the use in traffic sign recognition (TSR) systems. The following issues remain in previous works in which SIFT is used for matching or recognition: (1) SIFT is unable to provide color information; (2) SIFT only focuses on local features while ignoring the distribution of global shapes; (3) the template with the maximum number of matching points selected as the final result is instable, especially for images with simple patterns; and (4) SIFT is liable to result in errors when different images share the same local features. In order to resolve these problems, a new CASIFT approach is proposed. The contributions of the work are as follows: (1) color angular patterns are used to provide the color distinguishing information; (2) a CASIFT which effectively combines local and global information is proposed; and (3) a method for computing the similarity between two images is proposed, which focuses on the distribution of the matching points, rather than using the traditional SIFT approach of selecting the template with maximum number of matching points as the final result. The proposed approach is particularly effective in dealing with traffic signs which have rich colors and varied global shape distribution. Experiments are performed to validate the effectiveness of the proposed approach in TSR systems, and the experimental results are satisfying even for images containing traffic signs that have been rotated, damaged, altered in color, have undergone affine transformations, or images which were photographed under different weather or illumination conditions.

Data Exploration using Unsupervised Feature Extraction for Mixed Micro-Seismic Signals

NASA Astrophysics Data System (ADS)

Meyer, Matthias; Weber, Samuel; Beutel, Jan

2017-04-01

We present a system for the analysis of data originating in a multi-sensor and multi-year experiment focusing on slope stability and its underlying processes in fractured permafrost rock walls undertaken at 3500m a.s.l. on the Matterhorn Hörnligrat, (Zermatt, Switzerland). This system incorporates facilities for the transmission, management and storage of large-scales of data ( 7 GB/day), preprocessing and aggregation of multiple sensor types, machine-learning based automatic feature extraction for micro-seismic and acoustic emission data and interactive web-based visualization of the data. Specifically, a combination of three types of sensors are used to profile the frequency spectrum from 1 Hz to 80 kHz with the goal to identify the relevant destructive processes (e.g. micro-cracking and fracture propagation) leading to the eventual destabilization of large rock masses. The sensors installed for this profiling experiment (2 geophones, 1 accelerometers and 2 piezo-electric sensors for detecting acoustic emission), are further augmented with sensors originating from a previous activity focusing on long-term monitoring of temperature evolution and rock kinematics with the help of wireless sensor networks (crackmeters, cameras, weather station, rock temperature profiles, differential GPS) [Hasler2012]. In raw format, the data generated by the different types of sensors, specifically the micro-seismic and acoustic emission sensors, is strongly heterogeneous, in part unsynchronized and the storage and processing demand is large. Therefore, a purpose-built signal preprocessing and event-detection system is used. While the analysis of data from each individual sensor follows established methods, the application of all these sensor types in combination within a field experiment is unique. Furthermore, experience and methods from using such sensors in laboratory settings cannot be readily transferred to the mountain field site setting with its scale and full exposure to

Classification of Urban Feature from Unmanned Aerial Vehicle Images Using Gasvm Integration and Multi-Scale Segmentation

NASA Astrophysics Data System (ADS)

Modiri, M.; Salehabadi, A.; Mohebbi, M.; Hashemi, A. M.; Masumi, M.

2015-12-01

The use of UAV in the application of photogrammetry to obtain cover images and achieve the main objectives of the photogrammetric mapping has been a boom in the region. The images taken from REGGIOLO region in the province of, Italy Reggio -Emilia by UAV with non-metric camera Canon Ixus and with an average height of 139.42 meters were used to classify urban feature. Using the software provided SURE and cover images of the study area, to produce dense point cloud, DSM and Artvqvtv spatial resolution of 10 cm was prepared. DTM area using Adaptive TIN filtering algorithm was developed. NDSM area was prepared with using the difference between DSM and DTM and a separate features in the image stack. In order to extract features, using simultaneous occurrence matrix features mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation for each of the RGB band image was used Orthophoto area. Classes used to classify urban problems, including buildings, trees and tall vegetation, grass and vegetation short, paved road and is impervious surfaces. Class consists of impervious surfaces such as pavement conditions, the cement, the car, the roof is stored. In order to pixel-based classification and selection of optimal features of classification was GASVM pixel basis. In order to achieve the classification results with higher accuracy and spectral composition informations, texture, and shape conceptual image featureOrthophoto area was fencing. The segmentation of multi-scale segmentation method was used.it belonged class. Search results using the proposed classification of urban feature, suggests the suitability of this method of classification complications UAV is a city using images. The overall accuracy and kappa coefficient method proposed in this study, respectively, 47/93% and 84/91% was.

Feature-based attention elicits surround suppression in feature space.

PubMed

Störmer, Viola S; Alvarez, George A

2014-09-08

It is known that focusing attention on a particular feature (e.g., the color red) facilitates the processing of all objects in the visual field containing that feature [1-7]. Here, we show that such feature-based attention not only facilitates processing but also actively inhibits processing of similar, but not identical, features globally across the visual field. We combined behavior and electrophysiological recordings of frequency-tagged potentials in human observers to measure this inhibitory surround in feature space. We found that sensory signals of an attended color (e.g., red) were enhanced, whereas sensory signals of colors similar to the target color (e.g., orange) were suppressed relative to colors more distinct from the target color (e.g., yellow). Importantly, this inhibitory effect spreads globally across the visual field, thus operating independently of location. These findings suggest that feature-based attention comprises an excitatory peak surrounded by a narrow inhibitory zone in color space to attenuate the most distracting and potentially confusable stimuli during visual perception. This selection profile is akin to what has been reported for location-based attention [8-10] and thus suggests that such center-surround mechanisms are an overarching principle of attention across different domains in the human brain. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genome-wide Gene Expression Profiling of Acute Metal Exposures in Male Zebrafish

DTIC Science & Technology

2014-10-23

Data in Brief Genome-wide gene expression profiling of acute metal exposures in male zebrafish Christine E. Baer a,⁎, Danielle L. Ippolito b, Naissan... Zebrafish Whole organism Nickel Chromium Cobalt Toxicogenomics To capture global responses to metal poisoning and mechanistic insights into metal...toxicity, gene expression changes were evaluated in whole adult male zebrafish following acute 24 h high dose exposure to three metals with known human

Detection of Neuron Membranes in Electron Microscopy Images Using Multi-scale Context and Radon-Like Features

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

Seyedhosseini, Mojtaba; Kumar, Ritwik; Jurrus, Elizabeth R.

2011-10-01

Automated neural circuit reconstruction through electron microscopy (EM) images is a challenging problem. In this paper, we present a novel method that exploits multi-scale contextual information together with Radon-like features (RLF) to learn a series of discriminative models. The main idea is to build a framework which is capable of extracting information about cell membranes from a large contextual area of an EM image in a computationally efficient way. Toward this goal, we extract RLF that can be computed efficiently from the input image and generate a scale-space representation of the context images that are obtained at the output ofmore » each discriminative model in the series. Compared to a single-scale model, the use of a multi-scale representation of the context image gives the subsequent classifiers access to a larger contextual area in an effective way. Our strategy is general and independent of the classifier and has the potential to be used in any context based framework. We demonstrate that our method outperforms the state-of-the-art algorithms in detection of neuron membranes in EM images.« less

Atopic Dermatitis According to GARP: New Mechanistic Insights in Disease Pathogenesis.

PubMed

Nousbeck, Janna; Irvine, Alan D

2016-12-01

In complex disease such as atopic dermatitis, the journey from identification of strong risk loci to profound functional and mechanistic insights can take several years. Here, Manz et al. have elegantly deciphered the mechanistic pathways in the well-established 11q13.5 atopic dermatitis risk locus. Their genetic and functional insights emphasize a role for T regulatory cells in atopic dermatitis pathogenesis. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Hepatic signaling by the mechanistic target of rapamycin complex 2 (mTORC2)

PubMed Central

Lamming, Dudley W.; Demirkan, Gokhan; Boylan, Joan M.; Mihaylova, Maria M.; Peng, Tao; Ferreira, Jonathan; Neretti, Nicola; Salomon, Arthur; Sabatini, David M.; Gruppuso, Philip A.

2014-01-01

The mechanistic target of rapamycin (mTOR) exists in two complexes that regulate diverse cellular processes. mTOR complex 1 (mTORC1), the canonical target of rapamycin, has been well studied, whereas the physiological role of mTORC2 remains relatively uncharacterized. In mice in which the mTORC2 component Rictor is deleted in liver [Rictor-knockout (RKO) mice], we used genomic and phosphoproteomic analyses to characterize the role of hepatic mTORC2 in vivo. Overnight food withdrawal followed by refeeding was used to activate mTOR signaling. Rapamycin was administered before refeeding to specify mTORC2-mediated events. Hepatic mTORC2 regulated a complex gene expression and post-translational network that affects intermediary metabolism, ribosomal biogenesis, and proteasomal biogenesis. Nearly all changes in genes related to intermediary metabolic regulation were replicated in cultured fetal hepatocytes, indicating a cell-autonomous effect of mTORC2 signaling. Phosphoproteomic profiling identified mTORC2-related signaling to 144 proteins, among which were metabolic enzymes and regulators. A reduction of p38 MAPK signaling in the RKO mice represents a link between our phosphoproteomic and gene expression results. We conclude that hepatic mTORC2 exerts a broad spectrum of biological effects under physiological conditions. Our findings provide a context for the development of targeted therapies to modulate mTORC2 signaling.—Lamming, D. W., Demirkan, G., Boylan, J. M., Mihaylova, M. M., Peng, T., Ferreira, J., Neretti, N., Salomon, A., Sabatini, D. M., Gruppuso, P. A. Hepatic signaling by the mechanistic target of rapamycin complex 2 (mTORC2). PMID:24072782

AASHTO mechanistic-empirical pavement design guide parametric study.

DOT National Transportation Integrated Search

2012-03-01

This study focuses on assessing the robustness of the AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG v 1.1) for rigid pavement : design projects in Wisconsin. The primary tasks conducted in this study included performing sensitivity analys...

Automated Image Registration Using Morphological Region of Interest Feature Extraction

NASA Technical Reports Server (NTRS)

Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2005-01-01

With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

Auditory Profiles of Classical, Jazz, and Rock Musicians: Genre-Specific Sensitivity to Musical Sound Features.

PubMed

Tervaniemi, Mari; Janhunen, Lauri; Kruck, Stefanie; Putkinen, Vesa; Huotilainen, Minna

2015-01-01

When compared with individuals without explicit training in music, adult musicians have facilitated neural functions in several modalities. They also display structural changes in various brain areas, these changes corresponding to the intensity and duration of their musical training. Previous studies have focused on investigating musicians with training in Western classical music. However, musicians involved in different musical genres may display highly differentiated auditory profiles according to the demands set by their genre, i.e., varying importance of different musical sound features. This hypothesis was tested in a novel melody paradigm including deviants in tuning, timbre, rhythm, melody transpositions, and melody contour. Using this paradigm while the participants were watching a silent video and instructed to ignore the sounds, we compared classical, jazz, and rock musicians' and non-musicians' accuracy of neural encoding of the melody. In all groups of participants, all deviants elicited an MMN response, which is a cortical index of deviance discrimination. The strength of the MMN and the subsequent attentional P3a responses reflected the importance of various sound features in each music genre: these automatic brain responses were selectively enhanced to deviants in tuning (classical musicians), timing (classical and jazz musicians), transposition (jazz musicians), and melody contour (jazz and rock musicians). Taken together, these results indicate that musicians with different training history have highly specialized cortical reactivity to sounds which violate the neural template for melody content.

Auditory Profiles of Classical, Jazz, and Rock Musicians: Genre-Specific Sensitivity to Musical Sound Features

PubMed Central

Tervaniemi, Mari; Janhunen, Lauri; Kruck, Stefanie; Putkinen, Vesa; Huotilainen, Minna

2016-01-01

When compared with individuals without explicit training in music, adult musicians have facilitated neural functions in several modalities. They also display structural changes in various brain areas, these changes corresponding to the intensity and duration of their musical training. Previous studies have focused on investigating musicians with training in Western classical music. However, musicians involved in different musical genres may display highly differentiated auditory profiles according to the demands set by their genre, i.e., varying importance of different musical sound features. This hypothesis was tested in a novel melody paradigm including deviants in tuning, timbre, rhythm, melody transpositions, and melody contour. Using this paradigm while the participants were watching a silent video and instructed to ignore the sounds, we compared classical, jazz, and rock musicians' and non-musicians' accuracy of neural encoding of the melody. In all groups of participants, all deviants elicited an MMN response, which is a cortical index of deviance discrimination. The strength of the MMN and the subsequent attentional P3a responses reflected the importance of various sound features in each music genre: these automatic brain responses were selectively enhanced to deviants in tuning (classical musicians), timing (classical and jazz musicians), transposition (jazz musicians), and melody contour (jazz and rock musicians). Taken together, these results indicate that musicians with different training history have highly specialized cortical reactivity to sounds which violate the neural template for melody content. PMID:26779055

Exploring the pros and cons of mechanistic case diagrams for problem-based learning

PubMed Central

2017-01-01

Purpose Mechanistic case diagram (MCD) was recommended for increasing the depth of understanding of disease, but with few articles on its specific methods. We address the experience of making MCD in the fullest depth to identify the pros and cons of using MCDs in such ways. Methods During problem-based learning, we gave guidelines of MCD for its mechanistic exploration from subcellular processes to clinical features, being laid out in as much detail as possible. To understand the students’ attitudes and depth of study using MCDs, we analyzed the results of a questionnaire in an open format about experiencing MCDs and examined the resulting products. Results Through the responses to questionnaire, we found several favorable outcomes, major of which was deeper insight and comprehensive understanding of disease facilitated by the process of making well-organized diagram. The main disadvantages of these guidelines were the feeling of too much workload and difficulty of finding mechanisms. Students gave suggestions to overcome these problems: cautious reading of comprehensive texts, additional guidance from staff about depth and focus of mechanisms, and cooperative group work. From the analysis of maps, we recognized there should be allowance of diversities in the appearance of maps and many hypothetical connections, which could be related to an insufficient understanding of mechanisms in nature. Conclusion The more detailed an MCD task is, the better students can become acquainted with deep knowledges. However, this advantage should be balanced by the results that there are many ensuing difficulties for the work and deliberate help plans should be prepared. PMID:28870018

Bioinforrnatics of Gene Expression Profiling Data Provide Mechanistic Understanding of Acute Ozone-Induced Lung injury

EPA Science Inventory

Acute ozone-induced pulmonary injury and inflammation are well characterized. A few studies have used gene expression profiling to determine the types of changes induced by ozone; however the mechanisms or the pathways involved are less well understood. We presumed that robust bi...

A large-scale dataset of solar event reports from automated feature recognition modules

NASA Astrophysics Data System (ADS)

Schuh, Michael A.; Angryk, Rafal A.; Martens, Petrus C.

2016-05-01

The massive repository of images of the Sun captured by the Solar Dynamics Observatory (SDO) mission has ushered in the era of Big Data for Solar Physics. In this work, we investigate the entire public collection of events reported to the Heliophysics Event Knowledgebase (HEK) from automated solar feature recognition modules operated by the SDO Feature Finding Team (FFT). With the SDO mission recently surpassing five years of operations, and over 280,000 event reports for seven types of solar phenomena, we present the broadest and most comprehensive large-scale dataset of the SDO FFT modules to date. We also present numerous statistics on these modules, providing valuable contextual information for better understanding and validating of the individual event reports and the entire dataset as a whole. After extensive data cleaning through exploratory data analysis, we highlight several opportunities for knowledge discovery from data (KDD). Through these important prerequisite analyses presented here, the results of KDD from Solar Big Data will be overall more reliable and better understood. As the SDO mission remains operational over the coming years, these datasets will continue to grow in size and value. Future versions of this dataset will be analyzed in the general framework established in this work and maintained publicly online for easy access by the community.

From coastal barriers to mountain belts - commonalities in fundamental geomorphic scaling laws

NASA Astrophysics Data System (ADS)

Lazarus, E.

2016-12-01

Overwash is a sediment-transport process essential to the form and resilience of coastal barrier landscapes. Driven by storm events, overwash leaves behind distinctive sedimentary features that, although intensively studied, have lacked unifying quantitative descriptions with which to compare their morphological attributes across documented examples or relate them to other morphodynamic phenomena. Geomorphic scaling laws quantify how measures of shape and size change with respect to another - information that helps to constrain predictions of future change and reconstructions of past environmental conditions. Here, a physical model of erosional and depositional overwash morphology yields intrinsic, allometric scaling laws involving length, width, area, volume, and alongshore spacing. Corroborative comparisons with natural washover morphology indicate scale invariance spanning several orders of magnitude. Several observers of the physical model remarked that the overwashed barrier resembled a dissected linear mountain front with an alluvial apron - an intriguing reimagining of the intended analog. Indeed, that resemblance is reflected quantitatively in these new scaling relationships, which align with canonical scaling laws for terrestrial and marine drainage basins and alluvial fans on Earth and Mars. This finding suggests disparate geomorphic systems that share common allometric properties may be related dynamically, perhaps by an influence more fundamental than characteristic erosion and deposition processes. Such an influence could come from emergent behavior at the intersection of advection and diffusion. Geomorphic behaviors at advection-diffusion transitions (and vice versa), specifically, could be the key to disentangling mechanistic causality from acausality in physical landscape patterns.

MECHANISTIC AND SOURCE UNDERSTANDING OF PCDD/F FORMATION

EPA Science Inventory

The paper discusses mechanistic and source understanding of polychlorinated dibenzo-p-dioxin and dibenzofuran (PCDD/F) formation. (NOTE: Considerable research effort has been expended over the last 15-plus years to understand how combustion sources result in formation of PCDDs/F...

Computational phenotype discovery using unsupervised feature learning over noisy, sparse, and irregular clinical data.

PubMed

Lasko, Thomas A; Denny, Joshua C; Levy, Mia A

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don't think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data - Electronic Medical Records - typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data

Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data

PubMed Central

Lasko, Thomas A.; Denny, Joshua C.; Levy, Mia A.

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don’t think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data – Electronic Medical Records – typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data

Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

DTIC Science & Technology

2010-07-01

1-0431 TITLE: Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches PRINCIPAL INVESTIGATOR...June 2010 4. TITLE AND SUBTITLE Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic 5a. CONTRACT NUMBER...1-0430; W81XWH-08-1-0431; Grant sponsor: NIH/NCRR COBRE Grant; Grant number: 1P20RR020171; Grant sponsor: NIH/NIDDK Grant; Grant number: R01DK053525

Multiscaling behavior of atomic-scale friction

NASA Astrophysics Data System (ADS)

Jannesar, M.; Jamali, T.; Sadeghi, A.; Movahed, S. M. S.; Fesler, G.; Meyer, E.; Khoshnevisan, B.; Jafari, G. R.

2017-06-01

The scaling behavior of friction between rough surfaces is a well-known phenomenon. It might be asked whether such a scaling feature also exists for friction at an atomic scale despite the absence of roughness on atomically flat surfaces. Indeed, other types of fluctuations, e.g., thermal and instrumental fluctuations, become appreciable at this length scale and can lead to scaling behavior of the measured atomic-scale friction. We investigate this using the lateral force exerted on the tip of an atomic force microscope (AFM) when the tip is dragged over the clean NaCl (001) surface in ultra-high vacuum at room temperature. Here the focus is on the fluctuations of the lateral force profile rather than its saw-tooth trend; we first eliminate the trend using the singular value decomposition technique and then explore the scaling behavior of the detrended data, which contains only fluctuations, using the multifractal detrended fluctuation analysis. The results demonstrate a scaling behavior for the friction data ranging from 0.2 to 2 nm with the Hurst exponent H =0.61 ±0.02 at a 1 σ confidence interval. Moreover, the dependence of the generalized Hurst exponent, h (q ) , on the index variable q confirms the multifractal or multiscaling behavior of the nanofriction data. These results prove that fluctuation of nanofriction empirical data has a multifractal behavior which deviates from white noise.

Measuring the Interactive Skills of Caregivers in Child Care Centers: Development and Validation of the Caregiver Interaction Profile Scales

ERIC Educational Resources Information Center

Helmerhorst, Katrien O. W.; Riksen-Walraven, J. Marianne; Vermeer, Harriet J.; Fukkink, Ruben G.; Tavecchio, Louis W. C.

2014-01-01

Research Findings: High-quality caregiver-child interactions constitute the core of high-quality child care for young children. This article describes the background and development of the Caregiver Interaction Profile (CIP) scales to rate 6 key skills of caregivers for interacting with 0-to 4-year-old children in child care centers: sensitive…

Ground-based observation of the cyclic nature and temporal variability of planetary-scale UV features at the Venus cloud top level

NASA Astrophysics Data System (ADS)

Imai, Masataka; Takahashi, Yukihiro; Watanabe, Makoto; Kouyama, Toru; Watanabe, Shigeto; Gouda, Shuhei; Gouda, Yuya

2016-11-01

A planetary-scale bright and dark UV feature, known as the ;Y-feature,; rotates around Venus with a period of 4-5 days and has been long-time interpreted as planetary waves. When assuming this, its rotation period and spatial structure might help to understand the propagation of the planetary-scale waves and find out their role in the acceleration-deceleration of the zonal wind speed, which is essential for understanding the super-rotation of the planet. The rotation period of the UV feature varied over the course of observation by the Pioneer Venus orbiter. However, in previous explorations of Venus such as Pioneer Venus and Venus Express, the spacecraft were operated in nearly fixed inertial space. As a result, the periodicity variations on sub-yearly timescales (one Venusian year is ∼224 Earth days) were obscured by the limitations of continuous dayside observations. We newly conducted six periods of ground-based Venus imaging observations at 365 nm from mid-August 2013 to the end of June 2014. Each observation period spanned over half or one month, enabling long-term monitoring of Venus' atmosphere above the equator region. Distributions of the relative brightness were obtained from the equatorial (EQ) to mid-latitudinal regions in both hemispheres, and from the cyclical variations of these distributions we deduced the rotation periods of the UV features of the cloud tops brightness. The relative brightness exhibited periods of 5.2 and 3.5 days above 90% of significance. The relative intensities of these two significant components also seemed subject to temporal variations. Although the 3.5-day component considered persists throughout the observation periods, its dominance over the longer period varied in a cyclic fashion. The prevailing first significant mode seems to change from 5.2-day waves to 3.5-day waves in about nine months, which is clearly inconsistent with the Venusian year. Clear periodic perturbations, indicating stability of the planetary-scale

Mechanistic Parameters of Electrocatalytic Water Oxidation on LiMn2 O4 in Comparison to Natural Photosynthesis.

PubMed

Köhler, Lennart; Ebrahimizadeh Abrishami, Majid; Roddatis, Vladimir; Geppert, Janis; Risch, Marcel

2017-11-23

Targeted improvement of the low efficiency of water oxidation during the oxygen evolution reaction (OER) is severely hindered by insufficient knowledge of the electrocatalytic mechanism on heterogeneous surfaces. We chose LiMn 2 O 4 as a model system for mechanistic investigations as it shares the cubane structure with the active site of photosystem II and the valence of Mn 3.5+ with the dark-stable S1 state in the mechanism of natural photosynthesis. The investigated LiMn 2 O 4 nanoparticles are electrochemically stable in NaOH electrolytes and show respectable activity in any of the main metrics. At low overpotential, the key mechanistic parameters of Tafel slope, Nernst slope, and reaction order have constant values on the RHE scale of 62(1) mV dec -1 , 1(1) mV pH -1 , -0.04(2), respectively. These values are interpreted in the context of the well-studied mechanism of natural photosynthesis. The uncovered difference in the reaction sequence is important for the design of efficient bio-inspired electrocatalysts. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

The quest for a mechanistic understanding of biodiversity–ecosystem services relationships

PubMed Central

Duncan, Clare; Thompson, Julian R.; Pettorelli, Nathalie

2015-01-01

Ecosystem services (ES) approaches to biodiversity conservation are currently high on the ecological research and policy agendas. However, despite a wealth of studies into biodiversity's role in maintaining ES (B–ES relationships) across landscapes, we still lack generalities in the nature and strengths of these linkages. Reasons for this are manifold, but can largely be attributed to (i) a lack of adherence to definitions and thus a confusion between final ES and the ecosystem functions (EFs) underpinning them, (ii) a focus on uninformative biodiversity indices and singular hypotheses and (iii) top-down analyses across large spatial scales and overlooking of context-dependency. The biodiversity–ecosystem functioning (B–EF) field provides an alternate context for examining biodiversity's mechanistic role in shaping ES, focusing on species' characteristics that may drive EFs via multiple mechanisms across contexts. Despite acknowledgements of a need for B–ES research to look towards underlying B–EF linkages, the connections between these areas of research remains weak. With this review, we pull together recent B–EF findings to identify key areas for future developments in B–ES research. We highlight a means by which B–ES research may begin to identify how and when multiple underlying B–EF relationships may scale to final ES delivery and trade-offs. PMID:26468240

The quest for a mechanistic understanding of biodiversity-ecosystem services relationships.

PubMed

Duncan, Clare; Thompson, Julian R; Pettorelli, Nathalie

2015-10-22

Ecosystem services (ES) approaches to biodiversity conservation are currently high on the ecological research and policy agendas. However, despite a wealth of studies into biodiversity's role in maintaining ES (B-ES relationships) across landscapes, we still lack generalities in the nature and strengths of these linkages. Reasons for this are manifold, but can largely be attributed to (i) a lack of adherence to definitions and thus a confusion between final ES and the ecosystem functions (EFs) underpinning them, (ii) a focus on uninformative biodiversity indices and singular hypotheses and (iii) top-down analyses across large spatial scales and overlooking of context-dependency. The biodiversity-ecosystem functioning (B-EF) field provides an alternate context for examining biodiversity's mechanistic role in shaping ES, focusing on species' characteristics that may drive EFs via multiple mechanisms across contexts. Despite acknowledgements of a need for B-ES research to look towards underlying B-EF linkages, the connections between these areas of research remains weak. With this review, we pull together recent B-EF findings to identify key areas for future developments in B-ES research. We highlight a means by which B-ES research may begin to identify how and when multiple underlying B-EF relationships may scale to final ES delivery and trade-offs. © 2015 The Author(s).

Very high resolution Earth observation features for monitoring plant and animal community structure across multiple spatial scales in protected areas

NASA Astrophysics Data System (ADS)

Mairota, Paola; Cafarelli, Barbara; Labadessa, Rocco; Lovergine, Francesco; Tarantino, Cristina; Lucas, Richard M.; Nagendra, Harini; Didham, Raphael K.

2015-05-01

Monitoring the status and future trends in biodiversity can be prohibitively expensive using ground-based surveys. Consequently, significant effort is being invested in the use of satellite remote sensing to represent aspects of the proximate mechanisms (e.g., resource availability) that can be related to biodiversity surrogates (BS) such as species community descriptors. We explored the potential of very high resolution (VHR) satellite Earth observation (EO) features as proxies for habitat structural attributes that influence spatial variation in habitat quality and biodiversity change. In a semi-natural grassland mosaic of conservation concern in southern Italy, we employed a hierarchical nested sampling strategy to collect field and VHR-EO data across three spatial extent levels (landscape, patch and plot). Species incidence and abundance data were collected at the plot level for plant, insect and bird functional groups. Spectral and textural VHR-EO image features were derived from a Worldview-2 image. Three window sizes (grains) were tested for analysis and computation of textural features, guided by the perception limits of different organisms. The modelled relationships between VHR-EO features and BS responses differed across scales, suggesting that landscape, patch and plot levels are respectively most appropriate when dealing with birds, plants and insects. This research demonstrates the potential of VHR-EO for biodiversity mapping and habitat modelling, and highlights the importance of identifying the appropriate scale of analysis for specific taxonomic groups of interest. Further, textural features are important in the modelling of functional group-specific indices which represent BS in high conservation value habitat types, and provide a more direct link to species interaction networks and ecosystem functioning, than provided by traditional taxonomic diversity indices.

a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

NASA Astrophysics Data System (ADS)

Haigang, Sui; Zhina, Song

2016-06-01

Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

The structural basis for enhanced silver reflectance in Koi fish scale and skin.

PubMed

Gur, Dvir; Leshem, Ben; Oron, Dan; Weiner, Steve; Addadi, Lia

2014-12-10

Fish have evolved biogenic multilayer reflectors composed of stacks of intracellular anhydrous guanine crystals separated by cytoplasm, to produce the silvery luster of their skin and scales. Here we compare two different variants of the Japanese Koi fish; one of them with enhanced reflectivity. Our aim is to determine how biology modulates reflectivity, and from this to obtain a mechanistic understanding of the structure and properties governing the intensity of silver reflectance. We measured the reflectance of individual scales with a custom-made microscope, and then for each individual scale we characterized the structure of the guanine crystal/cytoplasm layers using high-resolution cryo-SEM. The measured reflectance and the structural-geometrical parameters were used to calculate the reflectance of each scale, and the results were compared to the experimental measurements. We show that enhanced reflectivity is obtained with the same basic guanine crystal/cytoplasm stacks, but the structural arrangement between the stack, inside the stacks, and relative to the scale surface is varied when reflectivity is enhanced. Finally, we propose a model that incorporates the basic building block parameters, the crystal orientation inside the tissue, and the resulting reflectance and explains the mechanistic basis for reflectance enhancement.

The influence of fine-scale habitat features on regional variation in population performance of alpine White-tailed Ptarmigan

USGS Publications Warehouse

Fedy, B.; Martin, K.

2011-01-01

It is often assumed (explicitly or implicitly) that animals select habitat features to maximize fitness. However, there is often a mismatch between preferred habitats and indices of individual and population measures of performance. We examined the influence of fine-scale habitat selection on the overall population performance of the White-tailed Ptarmigan (Lagopus leucura), an alpine specialist, in two subdivided populations whose habitat patches are configured differently. The central region of Vancouver Island, Canada, has more continuous and larger habitat patches than the southern region. In 2003 and 2004, using paired logistic regression between used (n = 176) and available (n = 324) sites, we identified food availability, distance to standing water, and predator cover as preferred habitat components . We then quantified variation in population performance in the two regions in terms of sex ratio, age structure (n = 182 adults and yearlings), and reproductive success (n = 98 females) on the basis of 8 years of data (1995-1999, 2002-2004). Region strongly influenced females' breeding success, which, unsuccessful hens included, was consistently higher in the central region (n = 77 females) of the island than in the south (n = 21 females, P = 0.01). The central region also had a much higher proportion of successful hens (87%) than did the south (55%, P < 0.001). In light of our findings, we suggest that population performance is influenced by a combination of fine-scale habitat features and coarse-scale habitat configuration. ?? The Cooper Ornithological Society 2011.

Calibrating the mechanistic-empirical pavement design guide for Kansas.

DOT National Transportation Integrated Search

2015-04-01

The Kansas Department of Transportation (KDOT) is moving toward the implementation of the new American : Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) : for pavement design. The...

Chemical kinetic mechanistic models to investigate cancer biology and impact cancer medicine.

PubMed

Stites, Edward C

2013-04-01

Traditional experimental biology has provided a mechanistic understanding of cancer in which the malignancy develops through the acquisition of mutations that disrupt cellular processes. Several drugs developed to target such mutations have now demonstrated clinical value. These advances are unequivocal testaments to the value of traditional cellular and molecular biology. However, several features of cancer may limit the pace of progress that can be made with established experimental approaches alone. The mutated genes (and resultant mutant proteins) function within large biochemical networks. Biochemical networks typically have a large number of component molecules and are characterized by a large number of quantitative properties. Responses to a stimulus or perturbation are typically nonlinear and can display qualitative changes that depend upon the specific values of variable system properties. Features such as these can complicate the interpretation of experimental data and the formulation of logical hypotheses that drive further research. Mathematical models based upon the molecular reactions that define these networks combined with computational studies have the potential to deal with these obstacles and to enable currently available information to be more completely utilized. Many of the pressing problems in cancer biology and cancer medicine may benefit from a mathematical treatment. As work in this area advances, one can envision a future where such models may meaningfully contribute to the clinical management of cancer patients.

Visual Aggregate Analysis of Eligibility Features of Clinical Trials

PubMed Central

He, Zhe; Carini, Simona; Sim, Ida; Weng, Chunhua

2015-01-01

Objective To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. Methods Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggregate analysis of clinical trial eligibility features. This method consists of four modules for eligibility feature frequency analysis, query builder, distribution analysis, and visualization, respectively. This method is capable of analyzing (1) frequently used qualitative and quantitative features for recruiting subjects for a selected medical condition, (2) distribution of study enrollment on consecutive value points or value intervals of each quantitative feature, and (3) distribution of studies on the boundary values, permissible value ranges, and value range widths of each feature. All analysis results were visualized using Google Charts API. Five recruited potential users assessed the usefulness of this method for identifying common patterns in any selected eligibility feature for clinical trial participant selection. Results We implemented this method as a Web-based analytical system called VITTA (Visual Analysis Tool of Clinical Study Target Populations). We illustrated the functionality of VITTA using two sample queries involving quantitative features BMI and HbA1c for conditions “hypertension” and “Type 2 diabetes”, respectively. The recruited potential users rated the user-perceived usefulness of VITTA with an average score of 86.4/100. Conclusions We contributed a novel aggregate analysis method to enable the interrogation of common patterns in quantitative eligibility criteria and the collective target populations of multiple related clinical studies. A larger-scale study is warranted to formally assess the usefulness of VITTA among clinical investigators and sponsors in various therapeutic areas. PMID:25615940

Visual aggregate analysis of eligibility features of clinical trials.

PubMed

He, Zhe; Carini, Simona; Sim, Ida; Weng, Chunhua

2015-04-01

To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggregate analysis of clinical trial eligibility features. This method consists of four modules for eligibility feature frequency analysis, query builder, distribution analysis, and visualization, respectively. This method is capable of analyzing (1) frequently used qualitative and quantitative features for recruiting subjects for a selected medical condition, (2) distribution of study enrollment on consecutive value points or value intervals of each quantitative feature, and (3) distribution of studies on the boundary values, permissible value ranges, and value range widths of each feature. All analysis results were visualized using Google Charts API. Five recruited potential users assessed the usefulness of this method for identifying common patterns in any selected eligibility feature for clinical trial participant selection. We implemented this method as a Web-based analytical system called VITTA (Visual Analysis Tool of Clinical Study Target Populations). We illustrated the functionality of VITTA using two sample queries involving quantitative features BMI and HbA1c for conditions "hypertension" and "Type 2 diabetes", respectively. The recruited potential users rated the user-perceived usefulness of VITTA with an average score of 86.4/100. We contributed a novel aggregate analysis method to enable the interrogation of common patterns in quantitative eligibility criteria and the collective target populations of multiple related clinical studies. A larger-scale study is warranted to formally assess the usefulness of VITTA among clinical investigators and sponsors in various therapeutic areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Roughness Versus Charge Contributions to Representative Discrete Heterogeneity Underlying Mechanistic Prediction of Colloid Attachment, Detachment and Breakthrough-Elution Behavior Under Environmental Conditions.

NASA Astrophysics Data System (ADS)

Johnson, William; Farnsworth, Anna; Vanness, Kurt; Hilpert, Markus

2017-04-01

The key element of a mechanistic theory to predict colloid attachment in porous media under environmental conditions where colloid-collector repulsion exists (unfavorable conditions for attachment) is representation of the nano-scale surface heterogeneity (herein called discrete heterogeneity) that drives colloid attachment under unfavorable conditions. The observed modes of colloid attachment under unfavorable conditions emerge from simulations that incorporate discrete heterogeneity. Quantitative prediction of attachment (and detachment) requires capturing the sizes, spatial frequencies, and other properties of roughness asperities and charge heterodomains in discrete heterogeneity representations of different surfaces. The fact that a given discrete heterogeneity representation will interact differently with different-sized colloids as well as different ionic strengths for a given sized colloid allows backing out representative discrete heterogeneity via comparison of simulations to experiments performed across a range of colloid size, solution IS, and fluid velocity. This has been achieved on unfavorable smooth surfaces yielding quantitative prediction of attachment, and qualitative prediction of detachment in response to ionic strength or flow perturbations. Extending this treatment to rough surfaces, and representing the contributions of nanoscale roughness as well as charge heterogeneity is a focus of this talk. Another focus of this talk is the upscaling the pore scale simulations to produce contrasting breakthrough-elution behaviors at the continuum (column) scale that are observed, for example, for different-sized colloids, or same-sized colloids under different ionic strength conditions. The outcome of mechanistic pore scale simulations incorporating discrete heterogeneity and subsequent upscaling is that temporal processes such as blocking and ripening will emerge organically from these simulations, since these processes fundamentally stem from the

[Quality of life and psychologic features of subjects with chronic respiratory diseases].

PubMed

Frassanito, M; Massari, G; Aversa, C; Meo, D C; Sinisi, M P

1992-01-01

The aim of this study is to verify the psychological attitude and the quality of life in patients suffering from chronic respiratory insufficiency. Taking for granted that a bad quality of life is connected with the symptom of a depressed state (loss of appetite, quality of sleep, sexuality, psychomotor slowing down, loss of energy, weariness, reduced interest for the external world, feelings of self-devaluation, reduced working and concentration capacity, complainings of turning over type) we have taken as index of "normal quality of life" the lack of these attitudes correlating them to the clinical symptoms and/or the patient's functional troubles and verifying how much they can affect the psychological features and how much the deterioration of the quality of life. For this reason a questionnaire, taken from the MMPI test (Minnesota Multiphasic Personality Inventory), restricted to the items related to the D scale (depression scale), has been given to one hundred COPD patients who had been examined previously from a clinical functional point of view. In the end, we have drawn our results both on the ground of the answers given by the patients to the single questions and on the grounds of the total score D (= depression index) and relating the previous data with the clinical-functional ones. Finally we have compareted these data with those ones connected with non selected population. So we have succeeded in outlining a psychophysical profile of the patient suffering from chronic respiratory diseases. Such a profile is marked by an objective element, that is pathology, and by a psychological element inserted into the organic one as there is an inter-dependence between pathology and psychological features. From the collected data, we have noted the behavioural spheres which are more upset are working capacities, sleep and mood and these features are directly proportional to the seriousness of the pathology. From a practical and therapeutic point of view, all this

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE PAGES

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...

2015-08-07

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

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

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Online estimation of the wavefront outer scale profile from adaptive optics telemetry

NASA Astrophysics Data System (ADS)

Guesalaga, A.; Neichel, B.; Correia, C. M.; Butterley, T.; Osborn, J.; Masciadri, E.; Fusco, T.; Sauvage, J.-F.

2017-02-01

We describe an online method to estimate the wavefront outer scale profile, L0(h), for very large and future extremely large telescopes. The stratified information on this parameter impacts the estimation of the main turbulence parameters [turbulence strength, Cn2(h); Fried's parameter, r0; isoplanatic angle, θ0; and coherence time, τ0) and determines the performance of wide-field adaptive optics (AO) systems. This technique estimates L0(h) using data from the AO loop available at the facility instruments by constructing the cross-correlation functions of the slopes between two or more wavefront sensors, which are later fitted to a linear combination of the simulated theoretical layers having different altitudes and outer scale values. We analyse some limitations found in the estimation process: (I) its insensitivity to large values of L0(h) as the telescope becomes blind to outer scales larger than its diameter; (II) the maximum number of observable layers given the limited number of independent inputs that the cross-correlation functions provide and (III) the minimum length of data required for a satisfactory convergence of the turbulence parameters without breaking the assumption of statistical stationarity of the turbulence. The method is applied to the Gemini South multiconjugate AO system that comprises five wavefront sensors and two deformable mirrors. Statistics of L0(h) at Cerro Pachón from data acquired during 3 yr of campaigns show interesting resemblance to other independent results in the literature. A final analysis suggests that the impact of error sources will be substantially reduced in instruments of the next generation of giant telescopes.

Characterizing Students' Mechanistic Reasoning about London Dispersion Forces

ERIC Educational Resources Information Center

Becker, Nicole; Noyes, Keenan; Cooper, Melanie

2016-01-01

Characterizing how students construct causal mechanistic explanations for chemical phenomena can provide us with important insights into the ways that students develop understanding of chemistry concepts. Here, we present two qualitative studies of undergraduate general chemistry students' reasoning about the causes of London dispersion forces in…

Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

PubMed

Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

2013-01-01

Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

Antimalarial benzoheterocyclic 4-aminoquinolines: Structure-activity relationship, in vivo evaluation, mechanistic and bioactivation studies.

PubMed

Ongarora, Dennis S B; Strydom, Natasha; Wicht, Kathryn; Njoroge, Mathew; Wiesner, Lubbe; Egan, Timothy J; Wittlin, Sergio; Jurva, Ulrik; Masimirembwa, Collen M; Chibale, Kelly

2015-09-01

A novel class of benzoheterocyclic analogues of amodiaquine designed to avoid toxic reactive metabolite formation was synthesized and evaluated for antiplasmodial activity against K1 (multidrug resistant) and NF54 (sensitive) strains of the malaria parasite Plasmodium falciparum. Structure-activity relationship studies led to the identification of highly promising analogues, the most potent of which had IC50s in the nanomolar range against both strains. The compounds further demonstrated good in vitro microsomal metabolic stability while those subjected to in vivo pharmacokinetic studies had desirable pharmacokinetic profiles. In vivo antimalarial efficacy in Plasmodium berghei infected mice was evaluated for four compounds, all of which showed good activity following oral administration. In particular, compound 19 completely cured treated mice at a low multiple dose of 4×10mg/kg. Mechanistic and bioactivation studies suggest hemozoin formation inhibition and a low likelihood of forming quinone-imine reactive metabolites, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factor Structure and Reliability of the Dutch Version of Seven Scales of the Communication Profile for the Hearing Impaired (CPHI)

ERIC Educational Resources Information Center

Mokkink, Lidwine B.; Knol, Dirk L.; Zekveld, Adriana A.; Goverts, S. Theo; Kramer, Sophia E.

2009-01-01

Purpose: Seven scales of the Communication Profile for the Hearing Impaired (CPHI; M. E. Demorest & S. A. Erdman, 1987) were translated into Dutch: Maladaptive Behavior, Verbal Strategies, and Nonverbal Strategies (within the area of Communication Strategies) and Self-Acceptance, Acceptance of Loss, Stress, and Withdrawal (within the area of…

Features of resilience

DOE PAGES

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; ...

2017-02-20

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. As a result, the proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Features of resilience

USGS Publications Warehouse

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; Palma-Oliveira, José M.; Woods, David D.; Linkov, Igor

2017-01-01

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. The proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Polymerization kinetics of wheat gluten upon thermosetting. A mechanistic model.

PubMed

Domenek, Sandra; Morel, Marie-Hélène; Bonicel, Joëlle; Guilbert, Stéphane

2002-10-09

Size exclusion high-performance liquid chromatography analysis was carried out on wheat gluten-glycerol blends subjected to different heat treatments. The elution profiles were analyzed in order to follow the solubility loss of protein fractions with specific molecular size. Owing to the known biochemical changes involved during the heat denaturation of gluten, a mechanistic mathematical model was developed, which divided the protein denaturation into two distinct reaction steps: (i) reversible change in protein conformation and (ii) protein precipitation through disulfide bonding between initially SDS-soluble and SDS-insoluble reaction partners. Activation energies of gluten unfolding, refolding, and precipitation were calculated with the Arrhenius law to 53.9 kJ x mol(-1), 29.5 kJ x mol(-1), and 172 kJ x mol(-1), respectively. The rate of protein solubility loss decreased as the cross-linking reaction proceeded, which may be attributed to the formation of a three-dimensional network progressively hindering the reaction. The enhanced susceptibility to aggregation of large molecules was assigned to a risen reaction probability due to their higher number of cysteine residues and to the increased percentage of unfolded and thereby activated proteins as complete protein refolding seemed to be an anticooperative process.

Mechanistic-empirical pavement design guide calibration for pavement rehabilitation.

DOT National Transportation Integrated Search

2013-01-01

The Oregon Department of Transportation (ODOT) is in the process of implementing the recently introduced AASHTO : Mechanistic-Empirical Pavement Design Guide (MEPDG) for new pavement sections. The majority of pavement work : conducted by ODOT involve...

Draft user's guide for UDOT mechanistic-empirical pavement design.

DOT National Transportation Integrated Search

2009-10-01

Validation of the new AASHTO Mechanistic-Empirical Pavement Design Guides (MEPDG) nationally calibrated pavement distress and smoothness prediction models when applied under Utah conditions, and local calibration of the new hot-mix asphalt (HMA) p...

Wechsler Adult Intelligence Scale-Third Edition profiles and their relationship to self-reported outcome following traumatic brain injury.

PubMed

Harman-Smith, Yasmin E; Mathias, Jane L; Bowden, Stephen C; Rosenfeld, Jeffrey V; Bigler, Erin D

2013-01-01

Neuropsychological assessments of outcome after traumatic brain injury (TBI) are often unrelated to self-reported problems after TBI. The current study cluster-analyzed the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) subtest scores from mild, moderate, and severe TBI (n=220) and orthopedic injury control (n=95) groups, to determine whether specific cognitive profiles are related to people's perceived outcomes after TBI. A two-stage cluster analysis produced 4- and 6-cluster solutions, with the 6-cluster solution better capturing subtle variations in cognitive functioning. The 6 clusters differed in the levels and profiles of cognitive performance, self-reported recovery, and education and injury severity. The findings suggest that subtle cognitive impairments after TBI should be interpreted in conjunction with patient's self-reported problems.

Distinct neurohumoral biomarker profiles in children with hemodynamically defined orthostatic intolerance may predict treatment options

PubMed Central

Wagoner, Ashley L.; Shaltout, Hossam A.; Fortunato, John E.

2015-01-01

Studies of adults with orthostatic intolerance (OI) have revealed altered neurohumoral responses to orthostasis, which provide mechanistic insights into the dysregulation of blood pressure control. Similar studies in children with OI providing a thorough neurohumoral profile are lacking. The objective of the present study was to determine the cardiovascular and neurohumoral profile in adolescent subjects presenting with OI. Subjects at 10–18 yr of age were prospectively recruited if they exhibited two or more traditional OI symptoms and were referred for head-up tilt (HUT) testing. Circulating catecholamines, vasopressin, aldosterone, renin, and angiotensins were measured in the supine position and after 15 min of 70° tilt. Heart rate and blood pressure were continuously measured. Of the 48 patients, 30 patients had an abnormal tilt. Subjects with an abnormal tilt had lower systolic, diastolic, and mean arterial blood pressures during tilt, significantly higher levels of vasopressin during HUT, and relatively higher catecholamines and ANG II during HUT than subjects with a normal tilt. Distinct neurohumoral profiles were observed when OI subjects were placed into the following groups defined by the hemodynamic response: postural orthostatic tachycardia syndrome (POTS), orthostatic hypotension (OH), syncope, and POTS/syncope. Key characteristics included higher HUT-induced norepinephrine in POTS subjects, higher vasopressin in OH and syncope subjects, and higher supine and HUT aldosterone in OH subjects. In conclusion, children with OI and an abnormal response to tilt exhibit distinct neurohumoral profiles associated with the type of the hemodynamic response during orthostatic challenge. Elevated arginine vasopressin levels in syncope and OH groups are likely an exaggerated response to decreased blood flow not compensated by higher norepinephrine levels, as observed in POTS subjects. These different compensatory mechanisms support the role of measuring

Regulatory Technology Development Plan - Sodium Fast Reactor: Mechanistic Source Term – Trial Calculation

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

Grabaskas, David; Bucknor, Matthew; Jerden, James

2016-10-01

The potential release of radioactive material during a plant incident, referred to as the source term, is a vital design metric and will be a major focus of advanced reactor licensing. The U.S. Nuclear Regulatory Commission has stated an expectation for advanced reactor vendors to present a mechanistic assessment of the potential source term in their license applications. The mechanistic source term presents an opportunity for vendors to realistically assess the radiological consequences of an incident, and may allow reduced emergency planning zones and smaller plant sites. However, the development of a mechanistic source term for advanced reactors is notmore » without challenges, as there are often numerous phenomena impacting the transportation and retention of radionuclides. This project sought to evaluate U.S. capabilities regarding the mechanistic assessment of radionuclide release from core damage incidents at metal fueled, pool-type sodium fast reactors (SFRs). The purpose of the analysis was to identify, and prioritize, any gaps regarding computational tools or data necessary for the modeling of radionuclide transport and retention phenomena. To accomplish this task, a parallel-path analysis approach was utilized. One path, led by Argonne and Sandia National Laboratories, sought to perform a mechanistic source term assessment using available codes, data, and models, with the goal to identify gaps in the current knowledge base. The second path, performed by an independent contractor, performed sensitivity analyses to determine the importance of particular radionuclides and transport phenomena in regards to offsite consequences. The results of the two pathways were combined to prioritize gaps in current capabilities.« less

Atomic-Scale Lightning Rod Effect in Plasmonic Picocavities: A Classical View to a Quantum Effect.

PubMed

Urbieta, Mattin; Barbry, Marc; Zhang, Yao; Koval, Peter; Sánchez-Portal, Daniel; Zabala, Nerea; Aizpurua, Javier

2018-01-23

Plasmonic gaps are known to produce nanoscale localization and enhancement of optical fields, providing small effective mode volumes of about a few hundred nm 3 . Atomistic quantum calculations based on time-dependent density functional theory reveal the effect of subnanometric localization of electromagnetic fields due to the presence of atomic-scale features at the interfaces of plasmonic gaps. Using a classical model, we explain this as a nonresonant lightning rod effect at the atomic scale that produces an extra enhancement over that of the plasmonic background. The near-field distribution of atomic-scale hot spots around atomic features is robust against dynamical screening and spill-out effects and follows the potential landscape determined by the electron density around the atomic sites. A detailed comparison of the field distribution around atomic hot spots from full quantum atomistic calculations and from the local classical approach considering the geometrical profile of the atoms' electronic density validates the use of a classical framework to determine the effective mode volume in these extreme subnanometric optical cavities. This finding is of practical importance for the community of surface-enhanced molecular spectroscopy and quantum nanophotonics, as it provides an adequate description of the local electromagnetic fields around atomic-scale features with use of simplified classical methods.

A Unifying Mechanistic Model of Selective Attention in Spiking Neurons

PubMed Central

Bobier, Bruce; Stewart, Terrence C.; Eliasmith, Chris

2014-01-01

Visuospatial attention produces myriad effects on the activity and selectivity of cortical neurons. Spiking neuron models capable of reproducing a wide variety of these effects remain elusive. We present a model called the Attentional Routing Circuit (ARC) that provides a mechanistic description of selective attentional processing in cortex. The model is described mathematically and implemented at the level of individual spiking neurons, with the computations for performing selective attentional processing being mapped to specific neuron types and laminar circuitry. The model is used to simulate three studies of attention in macaque, and is shown to quantitatively match several observed forms of attentional modulation. Specifically, ARC demonstrates that with shifts of spatial attention, neurons may exhibit shifting and shrinking of receptive fields; increases in responses without changes in selectivity for non-spatial features (i.e. response gain), and; that the effect on contrast-response functions is better explained as a response-gain effect than as contrast-gain. Unlike past models, ARC embodies a single mechanism that unifies the above forms of attentional modulation, is consistent with a wide array of available data, and makes several specific and quantifiable predictions. PMID:24921249

Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles

PubMed Central

Brender, Jeffrey R.; Zhang, Yang

2015-01-01

The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies. PMID:26506533

Comparing the topographic long profiles of gullies on Earth and Mars

NASA Astrophysics Data System (ADS)

Conway, Susan; Balme, Matthew; Murray, John; Towner, Martin

2014-05-01

Liquid water is not stable under the present atmospheric conditions on the martian surface. Hence, the discovery of widespread recently active kilometre-scale gullies that resemble those carved by water on Earth [1,2], was extremely surprising. Some authors suggest that either carbon dioxide driven processes or dry mass wasting could explain these features [3-6]. However, recent work has shown that some aspects of gully-morphology, such as braiding and streamlined features, are hard to explain with these mechanisms [e.g., 7,8]. In this study we have used topographic long profiles to investigate the formation mechanism of martian gullies. On Earth it is recognised that certain forms of long-profiles can be linked to a particular process, for example, at equilibrium fluvial systems have a profile curve of exponential decay [9]. However, these shapes have not been generalised for kilometre-scale landforms, such as gullies. We used differential GPS data and airborne laser altimeter data on Earth (LiDAR) from NSA-funded NCALM and UK's NERC ARSF to generate profile-data for gullies with a fluvial and debris flow origin. On Mars we used stereo-images from the HiRISE camera (25 cm/pix) and generated the gully-profiles using the manual point-matching method of Kreslavsky [10]. We found that the shape of gully long profiles on Mars is similar to that of both fluvial and debris flow gullies on Earth. However, more of the martian gullies we have studied are similar to fluvial gullies than to debris flow gullies. The slopes of the gully long profiles on Mars tend to be shallower than fluvial gullies on Earth, but this can be accounted for by the difference in gravity between Earth and Mars. References cited: [1] M.C. Malin and K.S. Edgett, Science, (2000), 288,2330-2335.[2] M.C. Malin et al., Science, (2006), 314,1573-1577. [3] T. Shinbrot et al., Proc Natl Acad Sci U A, (2004), 101,8542-8546. [4] S. Diniega et al., Icarus, (2013), 225,526-537. [5] T. Ishii and S. Sasaki, Lunar

Response of Moist Convection to Multi-scale Surface Flux Heterogeneity

NASA Astrophysics Data System (ADS)

Kang, S. L.; Ryu, J. H.

2015-12-01

We investigate response of moist convection to multi-scale feature of the spatial variation of surface sensible heat fluxes (SHF) in the afternoon evolution of the convective boundary layer (CBL), utilizing a mesoscale-domain large eddy simulation (LES) model. The multi-scale surface heterogeneity feature is analytically created as a function of the spectral slope in the wavelength range from a few tens of km to a few hundreds of m in the spectrum of surface SHF on a log-log scale. The response of moist convection to the κ-3 - slope (where κ is wavenumber) surface SHF field is compared with that to the κ-2 - slope surface, which has a relatively weak mesoscale feature, and the homogeneous κ0 - slope surface. Given the surface energy balance with a spatially uniform available energy, the prescribed SHF has a 180° phase lag with the latent heat flux (LHF) in a horizontal domain of (several tens of km)2. Thus, warmer (cooler) surface is relatively dry (moist). For all the cases, the same observation-based sounding is prescribed for the initial condition. For all the κ-3 - slope surface heterogeneity cases, early non-precipitating shallow clouds further develop into precipitating deep thunderstorms. But for all the κ-2 - slope cases, only shallow clouds develop. We compare the vertical profiles of domain-averaged fluxes and variances, and the contribution of the mesoscale and turbulence contributions to the fluxes and variances, between the κ-3 versus κ-2 slope cases. Also the cross-scale processes are investigated.

Aesthetic evaluation of profile incisor inclination.

PubMed

Ghaleb, Nathalie; Bouserhal, Joseph; Bassil-Nassif, Nayla

2011-06-01

The objectives of this study were to evaluate (1) the impact of maxillary incisor inclination on the aesthetics of the profile view of a smile, (2) to determine the most aesthetic inclination in the profile view of a smile and correlate it with facial features, and (3) to determine if dentists, orthodontists, and laypeople appreciate differently incisor inclination in smile aesthetics. A smiling profile photograph of a female subject (22 years of age) who fulfilled the criteria of soft tissue normative values and a balanced smile was obtained. The photograph was manipulated to simulate six lingual and labial inclinations at 5 degree increments to a maximum of 15 degrees. The seven photographs were randomly distributed in a binder to three groups of raters (30 dentists, 30 orthodontists, and 30 laypeople) who scored the attractiveness of the photographic variations using a visual analogue scale. Comparison of the mean scores was carried out by repeated analysis of variance, univariate tests, and multiple Bonferroni comparisons. The results showed a statistically significant interaction between the rater's profession and the aesthetic preference of incisor inclination (P = 0.013). The profile smile corresponding to an increase of 5 degrees in a labial direction had the highest score among all professions and among male and female raters. Orthodontists preferred labial crown torque; dentists and laypeople did not appreciate excessive incisor inclination in either the lingual or the labial directions. The most preferred smile matched with a maxillary incisor inclined 93 degrees to the horizontal line and +7 degrees to the lower facial third.

Mechanistic Studies of Human Spermine Oxidase: Kinetic Mechanism and pH Effects†

PubMed Central

Adachi, Maria S.; Juarez, Paul R.; Fitzpatrick, Paul F.

2009-01-01

In mammalian cells, the flavoprotein spermine oxidase (SMO) catalyzes the oxidation of spermine to spermidine and 3-aminopropanal. Mechanistic studies have been carried out with the recombinant human enzyme. The initial velocity pattern when the ratio between the concentrations of spermine and oxygen is kept constant establishes the steady-state kinetic pattern as ping-pong. Reduction of SMO by spermine in the absence of oxygen is biphasic. The rate constant for the rapid phase varies with the substrate concentration, with a limiting value (k3) of 49 s−1 and an apparent Kd value of 48 µM at pH 8.3. The rate constant for the slow step is independent of the spermine concentration, with a value of 5.5 s−1, comparable to the kcat value of 6.6 s−1. The kinetics of the oxidative half-reaction depend on the aging time after spermine and enzyme are mixed in a double mixing experiment. At an aging time of 6 s the reaction is monophasic with a second order rate constant of 4.2 mM−1 s−1. At an aging time of 0.3 s the reaction is biphasic with two second order constants equal to 4.0 and 40 mM−1 s−1. Neither is equal to the kcat/KO2 value of 13 mM−1s−1. These results establish the existence of more than one pathway for the reaction of the reduced flavin intermediate with oxygen. The kcat/KM value for spermine exhibits a bell-shaped pH-profile, with an average pKa value of 8.3. This profile is consistent with the active form of spermine having three charged nitrogens. The pH profile for k3 shows a pKa value of 7.4 for a group that must be unprotonated. The pKi-pH profiles for the competitive inhibitors N,N’-dibenzylbutane-1,4-diamine and spermidine show that the fully protonated forms of the inhibitors and the unprotonated form of an amino acid residue with a pKa of about 7.4 in the active site are preferred for binding. PMID:20000632

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

DTIC Science & Technology

2012-07-01

1-0431 TITLE: Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches PRINCIPAL INVESTIGATOR...July 2012 2. REPORT TYPE Final 3. DATES COVERED (From - To) 1 July 2008 – 30 June 2012 4. TITLE AND SUBTITLE Biomarker Discovery and Mechanistic...Department of Defense Synergistic Idea Development Award W81XWH-08-1-0430 (to H.Z) and W81XWH-08-1-0431 (to N.K.), an NIH/NCRR COBRE grant 1P20RR020171 (to

Fine-scale features on bioreplicated decoys of the emerald ash borer provide necessary visual verisimilitude

NASA Astrophysics Data System (ADS)

Domingue, Michael J.; Pulsifer, Drew P.; Narkhede, Mahesh S.; Engel, Leland G.; Martín-Palma, Raúl J.; Kumar, Jayant; Baker, Thomas C.; Lakhtakia, Akhlesh

2014-03-01

The emerald ash borer (EAB), Agrilus planipennis, is an invasive tree-killing pest in North America. Like other buprestid beetles, it has an iridescent coloring, produced by a periodically layered cuticle whose reflectance peaks at 540 nm wavelength. The males perform a visually mediated ritualistic mating flight directly onto females poised on sunlit leaves. We attempted to evoke this behavior using artificial visual decoys of three types. To fabricate decoys of the first type, a polymer sheet coated with a Bragg-stack reflector was loosely stamped by a bioreplicating die. For decoys of the second type, a polymer sheet coated with a Bragg-stack reflector was heavily stamped by the same die and then painted green. Every decoy of these two types had an underlying black absorber layer. Decoys of the third type were produced by a rapid prototyping machine and painted green. Fine-scale features were absent on the third type. Experiments were performed in an American ash forest infested with EAB, and a European oak forest home to a similar pest, the two-spotted oak borer (TSOB), Agrilus biguttatus. When pinned to leaves, dead EAB females, dead TSOB females, and bioreplicated decoys of both types often evoked the complete ritualized flight behavior. Males also initiated approaches to the rapidly prototyped decoy, but would divert elsewhere without making contact. The attraction of the bioreplicated decoys was also demonstrated by providing a high dc voltage across the decoys that stunned and killed approaching beetles. Thus, true bioreplication with fine-scale features is necessary to fully evoke ritualized visual responses in insects, and provides an opportunity for developing insecttrapping technologies.

A Mechanistic Model of the Actin Cycle

PubMed Central

Bindschadler, M.; Osborn, E. A.; Dewey, C. F.; McGrath, J. L.

2004-01-01

We have derived a broad, deterministic model of the steady-state actin cycle that includes its major regulatory mechanisms. Ours is the first model to solve the complete nucleotide profile within filaments, a feature that determines the dynamics and geometry of actin networks at the leading edges of motile cells, and one that has challenged investigators developing models to interpret steady-state experiments. We arrived at the nucleotide profile through analytic and numerical approaches that completely agree. Our model reproduces behaviors seen in numerous experiments with purified proteins, but allows a detailed inspection of the concentrations and fluxes that might exist in these experiments. These inspections provide new insight into the mechanisms that determine the rate of actin filament treadmilling. Specifically, we find that mechanisms for enhancing Pi release from the ADP·Pi intermediate on filaments, for increasing the off rate of ADP-bound subunits at pointed ends, and the multiple, simultaneous functions of profilin, make unique and essential contributions to increased treadmilling. In combination, these mechanisms have a theoretical capacity to increase treadmilling to levels limited only by the amount of available actin. This limitation arises because as the cycle becomes more dynamic, it tends toward the unpolymerized state. PMID:15111391

Sagittal Thoracic and Lumbar Spine Profiles in Upright Standing and Lying Prone Positions Among Healthy Subjects: Influence of Various Biometric Features.

PubMed

Salem, Walid; Coomans, Ysaline; Brismée, Jean-Michel; Klein, Paul; Sobczak, Stéphane; Dugailly, Pierre-Michel

2015-08-01

A prospective study was performed on the assessment of both thoracic and lumbar spine sagittal profiles (from C7 to S1). To propose a new noninvasive method for measuring the spine curvatures in standing and lying prone positions and to analyze their relationship with various biometric characteristics. Modifications of spine curvatures (i.e. lordosis or kyphosis) are of importance in the development of spinal disorders. Studies have emphasized the development of new devices to measure the spine sagittal profiles using a noninvasive and low-cost method. To date, it has not been applied for analyzing both lumbar and thoracic alterations for various positioning. Seventy-five healthy subjects (mean 22.6 ± 4.3 yr) were recruited to participate in this study. Thoracic and lumbar sagittal profiles were assessed in standing and lying prone positions using a 3D digitizer. In addition, several biometric data were collected including maximal trunk isometric strength for flexion and extension movement. Statistical analysis consisted in data comparisons of spine profiles and a multivariate analysis including biometric features, to classify individuals considering low within- and high between-variability. Kyphosis and lordosis angles decreased significantly from standing to lying prone position by an average of 13.4° and 16.6°, respectively. Multivariate analysis showed a sample clustering of 3 homogenous subgroups. The first group displayed larger lordosis and flexibility, and had low data values for height, weight, and strength. The second group had lower values than the overall trend of the whole sample, whereas the third group had larger score values for the torques, height, weight, waist, body mass index, and kyphosis angle but a reduced flexibility. The present results demonstrate a significant effect of the positioning on both thoracic and lumbar spine sagittal profiles and highlight the use of cluster analysis to categorize subgroups after biometric characteristics

Application of Mechanistic Toxicology Data to Ecological Risk Assessments

EPA Science Inventory

The ongoing evolution of knowledge and tools in the areas of molecular biology, bioinformatics, and systems biology holds significant promise for reducing uncertainties associated with ecological risk assessment. As our understanding of the mechanistic basis of responses of organ...

Implementation of mechanistic pavement design : field and laboratory implementation.

DOT National Transportation Integrated Search

2006-12-01

One of the most important parameters needed for 2002 Mechanistic Pavement Design Guide is the dynamic modulus (E*). : The dynamic modulus (E*) describes the relationship between stress and strain for a linear viscoelastic material. The E* is the : pr...

Fast multi-scale feature fusion for ECG heartbeat classification

NASA Astrophysics Data System (ADS)

Ai, Danni; Yang, Jian; Wang, Zeyu; Fan, Jingfan; Ai, Changbin; Wang, Yongtian

2015-12-01

Electrocardiogram (ECG) is conducted to monitor the electrical activity of the heart by presenting small amplitude and duration signals; as a result, hidden information present in ECG data is difficult to determine. However, this concealed information can be used to detect abnormalities. In our study, a fast feature-fusion method of ECG heartbeat classification based on multi-linear subspace learning is proposed. The method consists of four stages. First, baseline and high frequencies are removed to segment heartbeat. Second, as an extension of wavelets, wavelet-packet decomposition is conducted to extract features. With wavelet-packet decomposition, good time and frequency resolutions can be provided simultaneously. Third, decomposed confidences are arranged as a two-way tensor, in which feature fusion is directly implemented with generalized N dimensional ICA (GND-ICA). In this method, co-relationship among different data information is considered, and disadvantages of dimensionality are prevented; this method can also be used to reduce computing compared with linear subspace-learning methods (PCA). Finally, support vector machine (SVM) is considered as a classifier in heartbeat classification. In this study, ECG records are obtained from the MIT-BIT arrhythmia database. Four main heartbeat classes are used to examine the proposed algorithm. Based on the results of five measurements, sensitivity, positive predictivity, accuracy, average accuracy, and t-test, our conclusion is that a GND-ICA-based strategy can be used to provide enhanced ECG heartbeat classification. Furthermore, large redundant features are eliminated, and classification time is reduced.

Understanding and predicting profile structure and parametric scaling of intrinsic rotation

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

Wang, W. X.; Grierson, B. A.; Ethier, S.

2017-08-10

This study reports on a recent advance in developing physical understanding and a first-principles-based model for predicting intrinsic rotation profiles in magnetic fusion experiments. It is shown for the first time that turbulent fluctuation-driven residual stress (a non-diffusive component of momentum flux) along with diffusive momentum flux can account for both the shape and magnitude of the observed intrinsic toroidal rotation profile. Both the turbulence intensity gradient and zonal flow E×B shear are identified as major contributors to the generation of the k ∥-asymmetry needed for the residual stress generation. The model predictions of core rotation based on global gyrokineticmore » simulations agree well with the experimental measurements of main ion toroidal rotation for a set of DIII-D ECH discharges. The validated model is further used to investigate the characteristic dependence of residual stress and intrinsic rotation profile structure on the multi-dimensional parametric space covering the turbulence type, q-profile structure, and up-down asymmetry in magnetic geometry with the goal of developing the physics understanding needed for rotation profile control and optimization. It is shown that in the flat-q profile regime, intrinsic rotations driven by ITG and TEM turbulence are in the opposite direction (i.e., intrinsic rotation reverses). The predictive model also produces reversed intrinsic rotation for plasmas with weak and normal shear q-profiles.« less

The Profile of Academic Offenders: Features of Students Who Admit to Academic Dishonesty.

PubMed

Korn, Liat; Davidovitch, Nitza

2016-08-29

Dishonesty in academic settings is a reckless behavior that is unique to students and is associated with cheat    ing and plagiarism of academic tasks. Incidents involving dishonesty in higher education have increased considerably in the past decade, with regard to the extent of these practices, the types of dishonesty employed, and their prevalence. The current study examines the profile of "academic offenders". Which types are more prone to commit academic offenses? To what degree are they "normative" and do they represent the average student with regard to personal traits, personal perceptions, features of their academic studies, risk behaviors, and health risks. The study is based on a structured anonymous questionnaire. The sample consisted of 1,432 students, of whom 899 were female (63%) and 533 male (37%). The research findings indicate a common tendency among more than one quarter of the sample reported cheating on homework and 12.5% reported cheating on tests. Strong associations were found between academic dishonesty and various personal perceptions, the academic study experience, and involvement in other risky and deviant behaviors. Significant predictors of academic dishonesty were found, i.e., self-image, ethics, grades, time devoted to homework, and deviant and daring behaviors. The research findings might help indicate policies for optimally dealing with dishonesty, maybe even before the offense is committed, by means of cooperation between academic forces.

The Profile of Academic Offenders: Features of Students Who Admit to Academic Dishonesty

PubMed Central

Korn, Liat; Davidovitch, Nitza

2016-01-01

Dishonesty in academic settings is a reckless behavior that is unique to students and is associated with cheat ing and plagiarism of academic tasks. Incidents involving dishonesty in higher education have increased considerably in the past decade, with regard to the extent of these practices, the types of dishonesty employed, and their prevalence. The current study examines the profile of “academic offenders”. Which types are more prone to commit academic offenses? To what degree are they “normative” and do they represent the average student with regard to personal traits, personal perceptions, features of their academic studies, risk behaviors, and health risks. The study is based on a structured anonymous questionnaire. The sample consisted of 1,432 students, of whom 899 were female (63%) and 533 male (37%). The research findings indicate a common tendency among more than one quarter of the sample reported cheating on homework and 12.5% reported cheating on tests. Strong associations were found between academic dishonesty and various personal perceptions, the academic study experience, and involvement in other risky and deviant behaviors. Significant predictors of academic dishonesty were found, i.e., self-image, ethics, grades, time devoted to homework, and deviant and daring behaviors. The research findings might help indicate policies for optimally dealing with dishonesty, maybe even before the offense is committed, by means of cooperation between academic forces. PMID:27569198

Mapping beneath the seafloor: AUV sub-bottom profilers, sediment thickness and resource potential

NASA Astrophysics Data System (ADS)

Yeo, I. A.; Vardy, M. E.; Holwell, D.; North, L.; Murton, B. J.

2017-12-01

Most AUV seafloor exploration focuses primarily on collecting high-resolution bathymetric and backscatter data in order to identify and map features of interest. Sub-bottom profiler data provides an essential third dimension that can illuminate not only the thickness of overlying sediment packets, but also the scale and tectonic setting of surface features. In this study we present results of high-resolution sub-bottom profiler surveys of Tropic Seamount, a 3000m tall, 40km wide, flat-topped gyot located 400km south of the Canary Islands. We show how the application of AUV derived sub-bottom profiler data can be used to assess the thickness and extent of ferromanganese crusts covering the summit and underlying thin pelagic sediment cover. Bespoke chirp signals at two altitudes were used to increase the likelihood of resolving thin (tens of cm) layers of crust. Drill cores were obtained from an ROV and used to constrain and calibrate the profiler data. The cores show variable crustal thicknesses of zero to 14 cm of FeMn crustal cover over a partially phosphoritised, vuggy, often poorly lithified limestone basement. Initial measurements of sound velocities suggest differences between the limestone basement and the crust of only a few hundred meters per second. Sub-cores, drilled from large samples collected during the cruise were analysed in the NOC Acoustic Pulse Tube and with X-Ray Computer Tomography to better understand how variations in lithology, crustal thickness, surface texture and internal structure affect the returning geoacoustic signal. We discuss the pros and cons of different surveying patterns, altitudes and chirps, the relative usefulness of sub-bottom profiler data in different environments, and the value added by sub-bottom profiler surveying as opposed to bathymetric surveying alone.

Cognitive Profiles in Youth with Autism Spectrum Disorder: An Investigation of Base Rate Discrepancies Using the Differential Ability Scales-Second Edition

ERIC Educational Resources Information Center

Nowell, Kerri P.; Schanding, G. Thomas, Jr.; Kanne, Stephen M.; Goin-Kochel, Robin P.

2015-01-01

Extant data suggest that the cognitive profiles of individuals with ASD may be characterized by variability, particularly in terms of verbal intellectual functioning (VIQ) and non-verbal intellectual functioning (NVIQ) discrepancies. The "Differential Ability Scales, Second Edition" (DAS-II) has limited data available on its use with…

Affective Video Retrieval: Violence Detection in Hollywood Movies by Large-Scale Segmental Feature Extraction

PubMed Central

Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

2013-01-01

Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology “out of the lab” to real-world, diverse data. In this contribution, we address the problem of finding “disturbing” scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis. PMID:24391704

The global mechanical properties and multi-scale failure mechanics of heterogeneous human stratum corneum.

PubMed

Liu, X; Cleary, J; German, G K

2016-10-01

The outermost layer of skin, or stratum corneum, regulates water loss and protects underlying living tissue from environmental pathogens and insults. With cracking, chapping or the formation of exudative lesions, this functionality is lost. While stratum corneum exhibits well defined global mechanical properties, macroscopic mechanical testing techniques used to measure them ignore the structural heterogeneity of the tissue and cannot provide any mechanistic insight into tissue fracture. As such, a mechanistic understanding of failure in this soft tissue is lacking. This insight is critical to predicting fracture risk associated with age or disease. In this study, we first quantify previously unreported global mechanical properties of isolated stratum corneum including the Poisson's ratio and mechanical toughness. African American breast stratum corneum is used for all assessments. We show these parameters are highly dependent on the ambient humidity to which samples are equilibrated. A multi-scale investigation assessing the influence of structural heterogeneities on the microscale nucleation and propagation of cracks is then performed. At the mesoscale, spatially resolved equivalent strain fields within uniaxially stretched stratum corneum samples exhibit a striking heterogeneity, with localized peaks correlating closely with crack nucleation sites. Subsequent crack propagation pathways follow inherent topographical features in the tissue and lengthen with increased tissue hydration. At the microscale, intact corneocytes and polygonal shaped voids at crack interfaces highlight that cracks propagate in superficial cell layers primarily along intercellular junctions. Cellular fracture does occur however, but is uncommon. Human stratum corneum protects the body against harmful environmental pathogens and insults. Upon mechanical failure, this barrier function is lost. Previous studies characterizing the mechanics of stratum corneum have used macroscopic testing

Extracting physicochemical features to predict protein secondary structure.

PubMed

Huang, Yin-Fu; Chen, Shu-Ying

2013-01-01

We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we train the SVM using the PSSM profiles generated from PSI-BLAST and the physicochemical features extracted from the CB513 data set. Finally, we use the filter to refine the predicted results from the trained SVM. For all the performance measures of our method, Q 3 reaches 79.52, SOV94 reaches 86.10, and SOV99 reaches 74.60; all the measures are higher than those of the SVMpsi method and the SVMfreq method. This validates that considering these physicochemical features in predicting protein secondary structure would exhibit better performances.

Extracting Physicochemical Features to Predict Protein Secondary Structure

PubMed Central

Chen, Shu-Ying

2013-01-01

We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we train the SVM using the PSSM profiles generated from PSI-BLAST and the physicochemical features extracted from the CB513 data set. Finally, we use the filter to refine the predicted results from the trained SVM. For all the performance measures of our method, Q 3 reaches 79.52, SOV94 reaches 86.10, and SOV99 reaches 74.60; all the measures are higher than those of the SVMpsi method and the SVMfreq method. This validates that considering these physicochemical features in predicting protein secondary structure would exhibit better performances. PMID:23766688

Small Scale Features at Vesta South Pole

NASA Image and Video Library

2011-10-01

This image from NASA Dawn spacecraft shows a raised mound material overlying the brighter material that makes up the floor of the south polar depression of asteroid Vesta. Many small scale craters are clear in this image.

Mechanistic modeling of pesticide exposure: The missing keystone of honey bee toxicology.

PubMed

Sponsler, Douglas B; Johnson, Reed M

2017-04-01

The role of pesticides in recent honey bee losses is controversial, partly because field studies often fail to detect effects predicted by laboratory studies. This dissonance highlights a critical gap in the field of honey bee toxicology: there exists little mechanistic understanding of the patterns and processes of exposure that link honey bees to pesticides in their environment. The authors submit that 2 key processes underlie honey bee pesticide exposure: 1) the acquisition of pesticide by foraging bees, and 2) the in-hive distribution of pesticide returned by foragers. The acquisition of pesticide by foraging bees must be understood as the spatiotemporal intersection between environmental contamination and honey bee foraging activity. This implies that exposure is distributional, not discrete, and that a subset of foragers may acquire harmful doses of pesticide while the mean colony exposure would appear safe. The in-hive distribution of pesticide is a complex process driven principally by food transfer interactions between colony members, and this process differs importantly between pollen and nectar. High priority should be placed on applying the extensive literature on honey bee biology to the development of more rigorously mechanistic models of honey bee pesticide exposure. In combination with mechanistic effects modeling, mechanistic exposure modeling has the potential to integrate the field of honey bee toxicology, advancing both risk assessment and basic research. Environ Toxicol Chem 2017;36:871-881. © 2016 SETAC. © 2016 SETAC.

Mechanistic, Mathematical Model to Predict the Dynamics of Tissue Genesis in Bone Defects via Mechanical Feedback and Mediation of Biochemical Factors

PubMed Central

Moore, Shannon R.; Saidel, Gerald M.; Knothe, Ulf; Knothe Tate, Melissa L.

2014-01-01

The link between mechanics and biology in the generation and the adaptation of bone has been well studied in context of skeletal development and fracture healing. Yet, the prediction of tissue genesis within - and the spatiotemporal healing of - postnatal defects, necessitates a quantitative evaluation of mechano-biological interactions using experimental and clinical parameters. To address this current gap in knowledge, this study aims to develop a mechanistic mathematical model of tissue genesis using bone morphogenetic protein (BMP) to represent of a class of factors that may coordinate bone healing. Specifically, we developed a mechanistic, mathematical model to predict the dynamics of tissue genesis by periosteal progenitor cells within a long bone defect surrounded by periosteum and stabilized via an intramedullary nail. The emergent material properties and mechanical environment associated with nascent tissue genesis influence the strain stimulus sensed by progenitor cells within the periosteum. Using a mechanical finite element model, periosteal surface strains are predicted as a function of emergent, nascent tissue properties. Strains are then input to a mechanistic mathematical model, where mechanical regulation of BMP-2 production mediates rates of cellular proliferation, differentiation and tissue production, to predict healing outcomes. A parametric approach enables the spatial and temporal prediction of endochondral tissue regeneration, assessed as areas of cartilage and mineralized bone, as functions of radial distance from the periosteum and time. Comparing model results to histological outcomes from two previous studies of periosteum-mediated bone regeneration in a common ovine model, it was shown that mechanistic models incorporating mechanical feedback successfully predict patterns (spatial) and trends (temporal) of bone tissue regeneration. The novel model framework presented here integrates a mechanistic feedback system based on the

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

DEVELOPMENT AND VALIDATION OF A MECHANISTIC GROUND SPRAYER MODEL

EPA Science Inventory

In the last ten years the Spray Drift Task Force (SDTF), U.S. Environmental Protection Agency (EPA), USDA Agricultural Research Service, and USDA Forest Service cooperated in the refinement and evaluation of a mechanistically-based aerial spray model (contained within AGDISP and ...

Fidelity in Animal Modeling: Prerequisite for a Mechanistic Research Front Relevant to the Inflammatory Incompetence of Acute Pediatric Malnutrition.

PubMed

Woodward, Bill

2016-04-11

Inflammatory incompetence is characteristic of acute pediatric protein-energy malnutrition, but its underlying mechanisms remain obscure. Perhaps substantially because the research front lacks the driving force of a scholarly unifying hypothesis, it is adrift and research activity is declining. A body of animal-based research points to a unifying paradigm, the Tolerance Model, with some potential to offer coherence and a mechanistic impetus to the field. However, reasonable skepticism prevails regarding the relevance of animal models of acute pediatric malnutrition; consequently, the fundamental contributions of the animal-based component of this research front are largely overlooked. Design-related modifications to improve the relevance of animal modeling in this research front include, most notably, prioritizing essential features of pediatric malnutrition pathology rather than dietary minutiae specific to infants and children, selecting windows of experimental animal development that correspond to targeted stages of pediatric immunological ontogeny, and controlling for ontogeny-related confounders. In addition, important opportunities are presented by newer tools including the immunologically humanized mouse and outbred stocks exhibiting a magnitude of genetic heterogeneity comparable to that of human populations. Sound animal modeling is within our grasp to stimulate and support a mechanistic research front relevant to the immunological problems that accompany acute pediatric malnutrition.

Mechanistic basis of infertility of mouse intersubspecific hybrids

PubMed Central

Bhattacharyya, Tanmoy; Gregorova, Sona; Mihola, Ondrej; Anger, Martin; Sebestova, Jaroslava; Denny, Paul; Simecek, Petr; Forejt, Jiri

2013-01-01

According to the Dobzhansky–Muller model, hybrid sterility is a consequence of the independent evolution of related taxa resulting in incompatible genomic interactions of their hybrids. The model implies that the incompatibilities evolve randomly, unless a particular gene or nongenic sequence diverges much faster than the rest of the genome. Here we propose that asynapsis of heterospecific chromosomes in meiotic prophase provides a recurrently evolving trigger for the meiotic arrest of interspecific F1 hybrids. We observed extensive asynapsis of chromosomes and disturbance of the sex body in >95% of pachynemas of Mus m. musculus × Mus m. domesticus sterile F1 males. Asynapsis was not preceded by a failure of double-strand break induction, and the rate of meiotic crossing over was not affected in synapsed chromosomes. DNA double-strand break repair was delayed or failed in unsynapsed autosomes, and misexpression of chromosome X and chromosome Y genes was detected in single pachynemas and by genome-wide expression profiling. Oocytes of F1 hybrid females showed the same kind of synaptic problems but with the incidence reduced to half. Most of the oocytes with pachytene asynapsis were eliminated before birth. We propose the heterospecific pairing of homologous chromosomes as a preexisting condition of asynapsis in interspecific hybrids. The asynapsis may represent a universal mechanistic basis of F1 hybrid sterility manifested by pachytene arrest. It is tempting to speculate that a fast-evolving subset of the noncoding genomic sequence important for chromosome pairing and synapsis may be the culprit. PMID:23329330

Mechanistic basis of infertility of mouse intersubspecific hybrids.

PubMed

Bhattacharyya, Tanmoy; Gregorova, Sona; Mihola, Ondrej; Anger, Martin; Sebestova, Jaroslava; Denny, Paul; Simecek, Petr; Forejt, Jiri

2013-02-05

According to the Dobzhansky-Muller model, hybrid sterility is a consequence of the independent evolution of related taxa resulting in incompatible genomic interactions of their hybrids. The model implies that the incompatibilities evolve randomly, unless a particular gene or nongenic sequence diverges much faster than the rest of the genome. Here we propose that asynapsis of heterospecific chromosomes in meiotic prophase provides a recurrently evolving trigger for the meiotic arrest of interspecific F1 hybrids. We observed extensive asynapsis of chromosomes and disturbance of the sex body in >95% of pachynemas of Mus m. musculus × Mus m. domesticus sterile F1 males. Asynapsis was not preceded by a failure of double-strand break induction, and the rate of meiotic crossing over was not affected in synapsed chromosomes. DNA double-strand break repair was delayed or failed in unsynapsed autosomes, and misexpression of chromosome X and chromosome Y genes was detected in single pachynemas and by genome-wide expression profiling. Oocytes of F1 hybrid females showed the same kind of synaptic problems but with the incidence reduced to half. Most of the oocytes with pachytene asynapsis were eliminated before birth. We propose the heterospecific pairing of homologous chromosomes as a preexisting condition of asynapsis in interspecific hybrids. The asynapsis may represent a universal mechanistic basis of F1 hybrid sterility manifested by pachytene arrest. It is tempting to speculate that a fast-evolving subset of the noncoding genomic sequence important for chromosome pairing and synapsis may be the culprit.

On Features of the Generation of Artificial Ionospheric Irregularities with Transverse Scales of 50-200 m

NASA Astrophysics Data System (ADS)

Bolotin, I. A.; Frolov, V. L.; Akchurin, A. D.; Zykov, E. Yu.

2017-05-01

We consider the features of generation of artificial ionospheric irregularities with transverse (to the geomagnetic field) scales l⊥ ≈ 50-200 m in the ionosphere modified by high-power HF radio waves. It was found that there are at least two mechanisms for generation of these irregularities in the ionospheric F region. The first mechanism is related to the resonant interaction between radio waves and the ionospheric plasma, while the second one takes place even in the absence of the resonant interaction. Different polarization of the high-power radiation was used to separate the mechanisms in the measurements.

Tear gas: an epidemiological and mechanistic reassessment

PubMed Central

Rothenberg, Craig; Achanta, Satyanarayana; Svendsen, Erik R.

2016-01-01

Deployments of tear gas and pepper spray have rapidly increased worldwide. Large amounts of tear gas have been used in densely populated cities, including Cairo, Istanbul, Rio de Janeiro, Manama (Bahrain), and Hong Kong. In the United States, tear gas was used extensively during recent riots in Ferguson, Missouri. Whereas tear gas deployment systems have rapidly improved—with aerial drone systems tested and requested by law enforcement—epidemiological and mechanistic research have lagged behind and have received little attention. Case studies and recent epidemiological studies revealed that tear gas agents can cause lung, cutaneous, and ocular injuries, with individuals affected by chronic morbidities at high risk for complications. Mechanistic studies identified the ion channels TRPV1 and TRPA1 as targets of capsaicin in pepper spray, and of the tear gas agents chloroacetophenone, CS, and CR. TRPV1 and TRPA1 localize to pain‐sensing peripheral sensory neurons and have been linked to acute and chronic pain, cough, asthma, lung injury, dermatitis, itch, and neurodegeneration. In animal models, transient receptor potential inhibitors show promising effects as potential countermeasures against tear gas injuries. On the basis of the available data, a reassessment of the health risks of tear gas exposures in the civilian population is advised, and development of new countermeasures is proposed. PMID:27391380

Total magnitudes of Virgo galaxies - III. Scale errors in the Reference Catalogue of Bright Galaxies T system and light-profile distortion by resolution-degrading and differential-distance effects

NASA Astrophysics Data System (ADS)

Young, Christopher Ke-shih

2004-11-01

We investigate the BT magnitude scales of the Second and Third Reference Catalogues of Bright Galaxies, finding both scales to be reasonably reliable for 11.5 <~Bt<~ 14.0. However, large-scale errors of 0.26 and 0.24mag per unit mag interval respectively are uncovered for early-type galaxies at the bright ends, whilst even larger ones of 0.74 and 0.36mag per unit mag interval are found for galaxies of all morphological types at the faint ends. We attribute this situation to several effects already discussed by Young et al. and Young (Paper I), including the application of relatively inflexible growth-curve models that are only in a few specific cases appropriate to the galaxies concerned. Of particular interest to this study though, we find that the apparent profile shapes of giant galaxies in the Virgo direction of cz < 15000 km s-1 tend to be less centrally concentrated the greater their distance. This demonstrates that even for relatively nearby galaxies, the distortion of the overall shapes of light profiles by resolution-degrading effects such as seeing and data smoothing, as originally predicted and modelled by Young & Currie and Young et al., is a significant effect. It is, therefore, not good practice simply to extrapolate the profiles of galaxies of identical intrinsic size and intrinsic profile shape (i.e. identical morphology) by means of the same growth-curve model, unless the galaxies are known a priori to be at the same distance and unless their photometry is of the same angular resolution. We also investigate the total-magnitude scale of the catalogue of photometric types of Prugniel & Héraudeau, finding it to be much more reliable than the BT one. However, we argue that photometric type is really a measure of apparent profile shape (i.e. intrinsic profile shape after scale reduction on account of distance followed by convolution with a seeing disc and often a smoothing function as well). Strictly, it should therefore only be applicable to

Mental Imagery Scale: a new measurement tool to assess structural features of mental representations

NASA Astrophysics Data System (ADS)

D'Ercole, Martina; Castelli, Paolo; Giannini, Anna Maria; Sbrilli, Antonella

2010-05-01

Mental imagery is a quasi-perceptual experience which resembles perceptual experience, but occurring without (appropriate) external stimuli. It is a form of mental representation and is often considered centrally involved in visuo-spatial reasoning and inventive and creative thought. Although imagery ability is assumed to be functionally independent of verbal systems, it is still considered to interact with verbal representations, enabling objects to be named and names to evoke images. In literature, most measurement tools for evaluating imagery capacity are self-report instruments focusing on differences in individuals. In the present work, we applied a Mental Imagery Scale (MIS) to mental images derived from verbal descriptions in order to assess the structural features of such mental representations. This is a key theme for those disciplines which need to turn objects and representations into words and vice versa, such as art or architectural didactics. To this aim, an MIS questionnaire was administered to 262 participants. The questionnaire, originally consisting of a 33-item 5-step Likert scale, was reduced to 28 items covering six areas: (1) Image Formation Speed, (2) Permanence/Stability, (3) Dimensions, (4) Level of Detail/Grain, (5) Distance and (6) Depth of Field or Perspective. Factor analysis confirmed our six-factor hypothesis underlying the 28 items.

Using USArray Data to Explore Large-Scale Features in the Seismic Wavefield (Invited)

NASA Astrophysics Data System (ADS)

Woodward, R.; Simpson, D. W.; Busby, R. W.

2009-12-01

characteristics associated with seismic noise and earthquake signals. However, there are also unexpected features such as large-scale, geographically-coherent bands of high-noise which, though transient, exist for many hours. These features may be related to very weak observations of the aforementioned Rayleigh wave amplitude anomalies that are associated with elevated and sustained seismicity in particular source regions. We present examples of these observations and test hypotheses for their origin.

Orbital and millennial-scale features of atmospheric CH4 over the past 800,000 years.

PubMed

Loulergue, Laetitia; Schilt, Adrian; Spahni, Renato; Masson-Delmotte, Valérie; Blunier, Thomas; Lemieux, Bénédicte; Barnola, Jean-Marc; Raynaud, Dominique; Stocker, Thomas F; Chappellaz, Jérôme

2008-05-15

Atmospheric methane is an important greenhouse gas and a sensitive indicator of climate change and millennial-scale temperature variability. Its concentrations over the past 650,000 years have varied between approximately 350 and approximately 800 parts per 10(9) by volume (p.p.b.v.) during glacial and interglacial periods, respectively. In comparison, present-day methane levels of approximately 1,770 p.p.b.v. have been reported. Insights into the external forcing factors and internal feedbacks controlling atmospheric methane are essential for predicting the methane budget in a warmer world. Here we present a detailed atmospheric methane record from the EPICA Dome C ice core that extends the history of this greenhouse gas to 800,000 yr before present. The average time resolution of the new data is approximately 380 yr and permits the identification of orbital and millennial-scale features. Spectral analyses indicate that the long-term variability in atmospheric methane levels is dominated by approximately 100,000 yr glacial-interglacial cycles up to approximately 400,000 yr ago with an increasing contribution of the precessional component during the four more recent climatic cycles. We suggest that changes in the strength of tropical methane sources and sinks (wetlands, atmospheric oxidation), possibly influenced by changes in monsoon systems and the position of the intertropical convergence zone, controlled the atmospheric methane budget, with an additional source input during major terminations as the retreat of the northern ice sheet allowed higher methane emissions from extending periglacial wetlands. Millennial-scale changes in methane levels identified in our record as being associated with Antarctic isotope maxima events are indicative of ubiquitous millennial-scale temperature variability during the past eight glacial cycles.

Representing high throughput expression profiles via perturbation barcodes reveals compound targets.

PubMed

Filzen, Tracey M; Kutchukian, Peter S; Hermes, Jeffrey D; Li, Jing; Tudor, Matthew

2017-02-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

Gene expression profiling identifies inflammation and angiogenesis as distinguishing features of canine hemangiosarcoma.

PubMed

Tamburini, Beth A; Phang, Tzu L; Fosmire, Susan P; Scott, Milcah C; Trapp, Susan C; Duckett, Megan M; Robinson, Sally R; Slansky, Jill E; Sharkey, Leslie C; Cutter, Gary R; Wojcieszyn, John W; Bellgrau, Donald; Gemmill, Robert M; Hunter, Lawrence E; Modiano, Jaime F

2010-11-09

The etiology of hemangiosarcoma remains incompletely understood. Its common occurrence in dogs suggests predisposing factors favor its development in this species. These factors could represent a constellation of heritable characteristics that promote transformation events and/or facilitate the establishment of a microenvironment that is conducive for survival of malignant blood vessel-forming cells. The hypothesis for this study was that characteristic molecular features distinguish hemangiosarcoma from non-malignant endothelial cells, and that such features are informative for the etiology of this disease. We first investigated mutations of VHL and Ras family genes that might drive hemangiosarcoma by sequencing tumor DNA and mRNA (cDNA). Protein expression was examined using immunostaining. Next, we evaluated genome-wide gene expression profiling using the Affymetrix Canine 2.0 platform as a global approach to test the hypothesis. Data were evaluated using routine bioinformatics and validation was done using quantitative real time RT-PCR. Each of 10 tumor and four non-tumor samples analyzed had wild type sequences for these genes. At the genome wide level, hemangiosarcoma cells clustered separately from non-malignant endothelial cells based on a robust signature that included genes involved in inflammation, angiogenesis, adhesion, invasion, metabolism, cell cycle, signaling, and patterning. This signature did not simply reflect a cancer-associated angiogenic phenotype, as it also distinguished hemangiosarcoma from non-endothelial, moderately to highly angiogenic bone marrow-derived tumors (lymphoma, leukemia, osteosarcoma). The data show that inflammation and angiogenesis are important processes in the pathogenesis of vascular tumors, but a definitive ontogeny of the cells that give rise to these tumors remains to be established. The data do not yet distinguish whether functional or ontogenetic plasticity creates this phenotype, although they suggest that cells

Gene expression profiling identifies inflammation and angiogenesis as distinguishing features of canine hemangiosarcoma

PubMed Central

2010-01-01

Background The etiology of hemangiosarcoma remains incompletely understood. Its common occurrence in dogs suggests predisposing factors favor its development in this species. These factors could represent a constellation of heritable characteristics that promote transformation events and/or facilitate the establishment of a microenvironment that is conducive for survival of malignant blood vessel-forming cells. The hypothesis for this study was that characteristic molecular features distinguish hemangiosarcoma from non-malignant endothelial cells, and that such features are informative for the etiology of this disease. Methods We first investigated mutations of VHL and Ras family genes that might drive hemangiosarcoma by sequencing tumor DNA and mRNA (cDNA). Protein expression was examined using immunostaining. Next, we evaluated genome-wide gene expression profiling using the Affymetrix Canine 2.0 platform as a global approach to test the hypothesis. Data were evaluated using routine bioinformatics and validation was done using quantitative real time RT-PCR. Results Each of 10 tumor and four non-tumor samples analyzed had wild type sequences for these genes. At the genome wide level, hemangiosarcoma cells clustered separately from non-malignant endothelial cells based on a robust signature that included genes involved in inflammation, angiogenesis, adhesion, invasion, metabolism, cell cycle, signaling, and patterning. This signature did not simply reflect a cancer-associated angiogenic phenotype, as it also distinguished hemangiosarcoma from non-endothelial, moderately to highly angiogenic bone marrow-derived tumors (lymphoma, leukemia, osteosarcoma). Conclusions The data show that inflammation and angiogenesis are important processes in the pathogenesis of vascular tumors, but a definitive ontogeny of the cells that give rise to these tumors remains to be established. The data do not yet distinguish whether functional or ontogenetic plasticity creates this

Modal Profiles for the WISC-III.

ERIC Educational Resources Information Center

Pritchard, David A.; Livingston, Ronald B.; Reynolds, Cecil R.; Moses, James A., Jr.

2000-01-01

Presents a normative typology for classifying the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) factor index profiles according to profile shape. Current analyses indicate that overall profile level accounted for a majority of the variance in WISC-III index scores, but a considerable proportion of the variance was because of…

Investigation of mechanistic deterioration modeling for bridge design and management.

DOT National Transportation Integrated Search

2017-04-01

The ongoing deterioration of highway bridges in Colorado dictates that an effective method for allocating limited management resources be developed. In order to predict bridge deterioration in advance, mechanistic models that analyze the physical pro...

Automated real-time search and analysis algorithms for a non-contact 3D profiling system

NASA Astrophysics Data System (ADS)

Haynes, Mark; Wu, Chih-Hang John; Beck, B. Terry; Peterman, Robert J.

2013-04-01

The purpose of this research is to develop a new means of identifying and extracting geometrical feature statistics from a non-contact precision-measurement 3D profilometer. Autonomous algorithms have been developed to search through large-scale Cartesian point clouds to identify and extract geometrical features. These algorithms are developed with the intent of providing real-time production quality control of cold-rolled steel wires. The steel wires in question are prestressing steel reinforcement wires for concrete members. The geometry of the wire is critical in the performance of the overall concrete structure. For this research a custom 3D non-contact profilometry system has been developed that utilizes laser displacement sensors for submicron resolution surface profiling. Optimizations in the control and sensory system allow for data points to be collected at up to an approximate 400,000 points per second. In order to achieve geometrical feature extraction and tolerancing with this large volume of data, the algorithms employed are optimized for parsing large data quantities. The methods used provide a unique means of maintaining high resolution data of the surface profiles while keeping algorithm running times within practical bounds for industrial application. By a combination of regional sampling, iterative search, spatial filtering, frequency filtering, spatial clustering, and template matching a robust feature identification method has been developed. These algorithms provide an autonomous means of verifying tolerances in geometrical features. The key method of identifying the features is through a combination of downhill simplex and geometrical feature templates. By performing downhill simplex through several procedural programming layers of different search and filtering techniques, very specific geometrical features can be identified within the point cloud and analyzed for proper tolerancing. Being able to perform this quality control in real time

Spatial scale-dependent habitat heterogeneity influences submarine canyon macrofaunal abundance and diversity off the Main and Northwest Hawaiian Islands

NASA Astrophysics Data System (ADS)

De Leo, Fabio C.; Vetter, Eric W.; Smith, Craig R.; Rowden, Ashley A.; McGranaghan, Matthew

2014-06-01

The mapping of biodiversity on continental margins on landscape scales is highly relevant to marine spatial planning and conservation. Submarine canyons are widespread topographic features on continental and island margins that enhance benthic biomass across a range of oceanic provinces and productivity regimes. However, it remains unclear whether canyons enhance faunal biodiversity on landscape scales relevant to marine protected area (MPA) design. Furthermore, it is not known which physical attributes and heterogeneity metrics can provide good surrogates for large-scale mapping of canyon benthic biodiversity. To test mechanistic hypotheses evaluating the role of different canyon-landscape attributes in enhancing benthic biodiversity at different spatial scales we conducted 34 submersible dives in six submarine canyons and nearby slopes in the Hawaiian archipelago, sampling infaunal macrobenthos in a depth-stratified sampling design. We employed multivariate multiple regression models to evaluate sediment and topographic heterogeneity, canyon transverse profiles, and overall water mass variability as potential drivers of macrobenthic community structure and species richness. We find that variables related to habitat heterogeneity at medium (0.13 km2) and large (15-33 km2) spatial scales such as slope, backscatter reflectivity and canyon transverse profiles are often good predictors of macrobenthic biodiversity, explaining 16-30% of the variance. Particulate organic carbon (POC) flux and distance from shore are also important variables, implicating food supply as a major predictor of canyon biodiversity. Canyons off the high Main Hawaiian Islands (Oahu and Moloka'i) are significantly affected by organic enrichment, showing enhanced infaunal macrobenthos abundance, whereas this effect is imperceptible around the low Northwest Hawaiian Islands (Nihoa and Maro Reef). Variable canyon alpha-diversity and high rates of species turnover (beta-diversity), particularly for

Evaluation of the Impact of AIRS Radiance and Profile Data Assimilation in Partly Cloudy Regions

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi; Jedlovec, Gary

2013-01-01

Improvements to global and regional numerical weather prediction have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) are run to examine the impact AIRS radiances and retrieved profiles. Statistical evaluation of a long-term series of forecast runs will be compared along with preliminary results of in-depth investigations for select case comparing the analysis increments in partly cloudy regions and short-term forecast impacts.

Metabolic Profile and Inflammatory Responses in Dairy Cows with Left Displaced Abomasum Kept under Small-Scaled Farm Conditions

PubMed Central

Klevenhusen, Fenja; Humer, Elke; Metzler-Zebeli, Barbara; Podstatzky-Lichtenstein, Leopold; Wittek, Thomas; Zebeli, Qendrim

2015-01-01

Simple Summary This research established an association between lactation number and milk production and metabolic and inflammatory responses in high-producing dairy cows affected by left abomasal displacement in small-scaled dairy farms. The study showed metabolic alterations, liver damage, and inflammation in the sick cows, which were further exacerbated with increasing lactation number and milk yield of the cows. Abstract Left displaced abomasum (LDA) is a severe metabolic disease of cattle with a strong negative impact on production efficiency of dairy farms. Metabolic and inflammatory alterations associated with this disease have been reported in earlier studies, conducted mostly in large dairy farms. This research aimed to: (1) evaluate metabolic and inflammatory responses in dairy cows affected by LDA in small-scaled dairy farms; and (2) establish an association between lactation number and milk production with the outcome of metabolic variables. The cows with LDA had lower serum calcium (Ca), but greater concentrations of non-esterified fatty acids (NEFA) and beta-hydroxy-butyrate (BHBA), in particular when lactation number was >2. Cows with LDA showed elevated levels of aspartate aminotransferase, glutamate dehydrogenase, and serum amyloid A (SAA), regardless of lactation number. In addition, this study revealed strong associations between milk yield and the alteration of metabolic profile but not with inflammation in the sick cows. Results indicate metabolic alterations, liver damage, and inflammation in LDA cows kept under small-scale farm conditions. Furthermore, the data suggest exacerbation of metabolic profile and Ca metabolism but not of inflammation and liver health with increasing lactation number and milk yield in cows affected by LDA. PMID:26479481

A comprehensive mechanistic model for upward two-phase flow in wellbores

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

Sylvester, N.D.; Sarica, C.; Shoham, O.

1994-05-01

A comprehensive model is formulated to predict the flow behavior for upward two-phase flow. This model is composed of a model for flow-pattern prediction and a set of independent mechanistic models for predicting such flow characteristics as holdup and pressure drop in bubble, slug, and annular flow. The comprehensive model is evaluated by using a well data bank made up of 1,712 well cases covering a wide variety of field data. Model performance is also compared with six commonly used empirical correlations and the Hasan-Kabir mechanistic model. Overall model performance is in good agreement with the data. In comparison withmore » other methods, the comprehensive model performed the best.« less

MECHANISTIC DOSIMETRY MODELS OF NANOMATERIAL DEPOSITION IN THE RESPIRATORY TRACT

EPA Science Inventory

Accurate health risk assessments of inhalation exposure to nanomaterials will require dosimetry models that account for interspecies differences in dose delivered to the respiratory tract. Mechanistic models offer the advantage to interspecies extrapolation that physicochemica...

First Comparison of Remote Vertical Profiles of Refractory Black Carbon between the Atlantic and Pacific Basins on Global Scales

NASA Astrophysics Data System (ADS)

Katich, J. M.; Schwarz, J. P.

2016-12-01

The NASA Atmospheric Tomography Mission (ATom) provides a first opportunity to obtain vertical profiles of refractory black carbon (rBC) mass mixing ratios over global scale ( 65S - 85 N latitude) in the remote atmosphere over both the Pacific and Atlantic basins. A NOAA single-particle soot photometer (SP2) will fly on the NASA DC-8 research aircraft over July/August of 2016, obtaining near- continuous vertical profiling ( 0.3 to 12 km) over most of the Earth's latitude range, akin to the NSF HIPPO campaign that occurred only over the Pacific basin during 2009-2011. HIPPO analysis suggested both that high altitude rBC mass mixing ratios (MMRs) were likely zonally well mixed, and that global model estimates of remote rBC MMR throughout the upper troposphere globally, and not just over the Pacific, were likely biased high. Here we will present an initial analysis of the new, more complete data set in which Atlantic rBC profiles will be used to assess these prior suppositions.

Multiscale mechanistic modeling in pharmaceutical research and development.

PubMed

Kuepfer, Lars; Lippert, Jörg; Eissing, Thomas

2012-01-01

Discontinuation of drug development projects due to lack of efficacy or adverse events is one of the main cost drivers in pharmaceutical research and development (R&D). Investments have to be written-off and contribute to the total costs of a successful drug candidate receiving marketing authorization and allowing return on invest. A vital risk for pharmaceutical innovator companies is late stage clinical failure since costs for individual clinical trials may exceed the one billion Euro threshold. To guide investment decisions and to safeguard maximum medical benefit and safety for patients recruited in clinical trials, it is therefore essential to understand the clinical consequences of all information and data generated. The complexity of the physiological and pathophysiological processes and the sheer amount of information available overcharge the mental capacity of any human being and prevent a prediction of the success in clinical development. A rigorous integration of knowledge, assumption, and experimental data into computational models promises a significant improvement of the rationalization of decision making in pharmaceutical industry. We here give an overview of the current status of modeling and simulation in pharmaceutical R&D and outline the perspectives of more recent developments in mechanistic modeling. Specific modeling approaches for different biological scales ranging from intracellular processes to whole organism physiology are introduced and an example for integrative multiscale modeling of therapeutic efficiency in clinical oncology trials is showcased.

Identification of key characteristics of male reproductive toxicants as an approach for screening and sorting mechanistic evidence.

EPA Science Inventory

The application of systematic review practices in human health assessment includes integration of multi-disciplinary evidence from epidemiological, experimental, and mechanistic studies. Although mode of action analysis relies on the evaluation of mechanistic and toxicological ou...

Atomic scale simulations for improved CRUD and fuel performance modeling

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

Andersson, Anders David Ragnar; Cooper, Michael William Donald

2017-01-06

A more mechanistic description of fuel performance codes can be achieved by deriving models and parameters from atomistic scale simulations rather than fitting models empirically to experimental data. The same argument applies to modeling deposition of corrosion products on fuel rods (CRUD). Here are some results from publications in 2016 carried out using the CASL allocation at LANL.

iPcc: a novel feature extraction method for accurate disease class discovery and prediction

PubMed Central

Ren, Xianwen; Wang, Yong; Zhang, Xiang-Sun; Jin, Qi

2013-01-01

Gene expression profiling has gradually become a routine procedure for disease diagnosis and classification. In the past decade, many computational methods have been proposed, resulting in great improvements on various levels, including feature selection and algorithms for classification and clustering. In this study, we present iPcc, a novel method from the feature extraction perspective to further propel gene expression profiling technologies from bench to bedside. We define ‘correlation feature space’ for samples based on the gene expression profiles by iterative employment of Pearson’s correlation coefficient. Numerical experiments on both simulated and real gene expression data sets demonstrate that iPcc can greatly highlight the latent patterns underlying noisy gene expression data and thus greatly improve the robustness and accuracy of the algorithms currently available for disease diagnosis and classification based on gene expression profiles. PMID:23761440

A Physics-Inspired Mechanistic Model of Migratory Movement Patterns in Birds.

PubMed

Revell, Christopher; Somveille, Marius

2017-08-29

In this paper, we introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Previous studies have shed light on the factors influencing bird migration but have mainly relied on statistical correlative analysis of tracking data. Our novel method offers a bottom up explanation of population-level migratory movement patterns. It differs from previous mechanistic models of animal migration and enables predictions of pathways and destinations from a given starting location. We define an environmental potential landscape from environmental data and simulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics. We explore the capacity of the model by qualitatively comparing simulation results to the non-breeding migration patterns of a seabird species, the Black-browed Albatross (Thalassarche melanophris). This minimal, two-parameter model was able to capture remarkably well the previously documented migration patterns of the Black-browed Albatross, with the best combination of parameter values conserved across multiple geographically separate populations. Our physics-inspired mechanistic model could be applied to other bird and highly-mobile species, improving our understanding of the relative importance of various factors driving migration and making predictions that could be useful for conservation.

Electrochemical processes and mechanistic aspects of field-effect sensors for biomolecules

PubMed Central

Huang, Weiguo; Diallo, Abdou Karim; Dailey, Jennifer L.; Besar, Kalpana

2017-01-01

Electronic biosensing is a leading technology for determining concentrations of biomolecules. In some cases, the presence of an analyte molecule induces a measured change in current flow, while in other cases, a new potential difference is established. In the particular case of a field effect biosensor, the potential difference is monitored as a change in conductance elsewhere in the device, such as across a film of an underlying semiconductor. Often, the mechanisms that lead to these responses are not specifically determined. Because improved understanding of these mechanisms will lead to improved performance, it is important to highlight those studies where various mechanistic possibilities are investigated. This review explores a range of possible mechanistic contributions to field-effect biosensor signals. First, we define the field-effect biosensor and the chemical interactions that lead to the field effect, followed by a section on theoretical and mechanistic background. We then discuss materials used in field-effect biosensors and approaches to improving signals from field-effect biosensors. We specifically cover the biomolecule interactions that produce local electric fields, structures and processes at interfaces between bioanalyte solutions and electronic materials, semiconductors used in biochemical sensors, dielectric layers used in top-gated sensors, and mechanisms for converting the surface voltage change to higher signal/noise outputs in circuits. PMID:29238595

Mechanistic applicability domain classification of a local lymph node assay dataset for skin sensitization.

PubMed

Roberts, David W; Patlewicz, Grace; Kern, Petra S; Gerberick, Frank; Kimber, Ian; Dearman, Rebecca J; Ryan, Cindy A; Basketter, David A; Aptula, Aynur O

2007-07-01

The goal of eliminating animal testing in the predictive identification of chemicals with the intrinsic ability to cause skin sensitization is an important target, the attainment of which has recently been brought into even sharper relief by the EU Cosmetics Directive and the requirements of the REACH legislation. Development of alternative methods requires that the chemicals used to evaluate and validate novel approaches comprise not only confirmed skin sensitizers and non-sensitizers but also substances that span the full chemical mechanistic spectrum associated with skin sensitization. To this end, a recently published database of more than 200 chemicals tested in the mouse local lymph node assay (LLNA) has been examined in relation to various chemical reaction mechanistic domains known to be associated with sensitization. It is demonstrated here that the dataset does cover the main reaction mechanistic domains. In addition, it is shown that assignment to a reaction mechanistic domain is a critical first step in a strategic approach to understanding, ultimately on a quantitative basis, how chemical properties influence the potency of skin sensitizing chemicals. This understanding is necessary if reliable non-animal approaches, including (quantitative) structure-activity relationships (Q)SARs, read-across, and experimental chemistry based models, are to be developed.

Physiologic, demographic and mechanistic factors predicting New Injury Severity Score (NISS) in motor vehicle accident victims.

PubMed

Staff, T; Eken, T; Wik, L; Røislien, J; Søvik, S

2014-01-01

Current literature on motor vehicle accidents (MVAs) has few reports regarding field factors that predict the degree of injury. Also, studies of mechanistic factors rarely consider concurrent predictive effects of on-scene patient physiology. The New Injury Severity Score (NISS) has previously been found to correlate with mortality, need for ICU admission, length of hospital stay, and functional recovery after trauma. To potentially increase future precision of trauma triage, we assessed how the NISS is associated with physiologic, demographic and mechanistic variables from the accident site. Using mixed-model linear regression analyses, we explored the association between NISS and pre-hospital Glasgow Coma Scale (GCS) score, Revised Trauma Score (RTS) categories of respiratory rate (RR) and systolic blood pressure (SBP), gender, age, subject position in the vehicle, seatbelt use, airbag deployment, and the estimated squared change in vehicle velocity on impact ((Δv)(2)). Missing values were handled with multiple imputation. We included 190 accidents with 353 dead or injured subjects (mean NISS 17, median NISS 8, IQR 1-27). For the 307 subjects in front-impact MVAs, the mean increase in NISS was -2.58 per GCS point, -2.52 per RR category level, -2.77 per SBP category level, -1.08 for male gender, 0.18 per year of age, 4.98 for driver vs. rear passengers, 4.83 for no seatbelt use, 13.52 for indeterminable seatbelt use, 5.07 for no airbag deployment, and 0.0003 per (km/h)(2) velocity change (all p<0.002). This study in victims of MVAs demonstrated that injury severity (NISS) was concurrently and independently predicted by poor pre-hospital physiologic status, increasing age and female gender, and several mechanistic measures of localised and generalised trauma energy. Our findings underscore the need for precise information from the site of trauma, to reduce undertriage, target diagnostic efforts, and anticipate need for high-level care and rehabilitative resources

Temporal analysis of intratumoral metabolic heterogeneity characterized by textural features in cervical cancer.

PubMed

Yang, Fei; Thomas, Maria A; Dehdashti, Farrokh; Grigsby, Perry W

2013-05-01

The aim of this pilot study was to explore heterogeneity in the temporal behavior of intratumoral [(18)F]fluorodeoxyglucose (FDG) accumulation at a regional scale in patients with cervical cancer undergoing chemoradiotherapy. Included in the study were 20 patients with FIGO stages IB1 to IVA cervical cancer treated with combined chemoradiotherapy. Patients underwent FDG PET/CT before treatment, during weeks 2 and 4 of treatment, and 12 weeks after completion of therapy. Patients were classified based on response to therapy as showing a complete metabolic response (CMR), a partial metabolic response (PMR), or residual disease and the development of new disease (NEW). Based on the presence of residual primary tumor following therapy, patients were divided into two groups, CMR and PMR/NEW. Temporal profiles of intratumoral FDG heterogeneity as characterized by textural features at a regional scale were assessed and compared with those of the standardized uptake value (SUV) indices (SUVmax and SUVmean) within the context of differentiating response groups. Textural features at a regional scale with emphasis on characterizing contiguous regions of high uptake in tumors decreased significantly with time (P < 0.001) in the CMR group, while features describing contiguous regions of low uptake along with those measuring the nonuniformity of contiguous isointense regions in tumors exhibited significant temporal changes in the PMR/NEW group (P < 0.03) but showed no persistent trends with time. Both SUV indices showed significant changes during the course of the disease in both patient groups (P < 0.001 for SUVmax and SUVmean in the CMR group; P = 0.0109 and 0.0136, respectively, for SUVmax and SUVmean in the PMR/NEW group), and also decreased at a constant rate in the CMR group and decreased up to the 4th week of treatment and then increased in the PMR/NEW group. The temporal changes in the heterogeneity of intratumoral FDG distribution characterized at a regional scale using

High throughput profile-profile based fold recognition for the entire human proteome.

PubMed

McGuffin, Liam J; Smith, Richard T; Bryson, Kevin; Sørensen, Søren-Aksel; Jones, David T

2006-06-07

In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power. In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

Rearrangements of Allylic Sulfinates to Sulfones: A Mechanistic Study

ERIC Educational Resources Information Center

Ball, David B.; Mollard, Paul; Voigtritter, Karl R.; Ball, Jenelle L.

2010-01-01

Most current organic chemistry textbooks are organized by functional groups and those of us who teach organic chemistry use functional-group organization in our courses but ask students to learn organic chemistry from a mechanistic approach. To enrich and extend the chemical understanding and knowledge of pericyclic-type reactions for chemistry…

Feature-oriented regional modeling and simulations in the Gulf of Maine and Georges Bank

NASA Astrophysics Data System (ADS)

Gangopadhyay, Avijit; Robinson, Allan R.; Haley, Patrick J.; Leslie, Wayne G.; Lozano, Carlos J.; Bisagni, James J.; Yu, Zhitao

2003-03-01

The multiscale synoptic circulation system in the Gulf of Maine and Georges Bank (GOMGB) region is presented using a feature-oriented approach. Prevalent synoptic circulation structures, or 'features', are identified from previous observational studies. These features include the buoyancy-driven Maine Coastal Current, the Georges Bank anticyclonic frontal circulation system, the basin-scale cyclonic gyres (Jordan, Georges and Wilkinson), the deep inflow through the Northeast Channel (NEC), the shallow outflow via the Great South Channel (GSC), and the shelf-slope front (SSF). Their synoptic water-mass ( T- S) structures are characterized and parameterized in a generalized formulation to develop temperature-salinity feature models. A synoptic initialization scheme for feature-oriented regional modeling and simulation (FORMS) of the circulation in the coastal-to-deep region of the GOMGB system is then developed. First, the temperature and salinity feature-model profiles are placed on a regional circulation template and then objectively analyzed with appropriate background climatology in the coastal region. Furthermore, these fields are melded with adjacent deep-ocean regional circulation (Gulf Stream Meander and Ring region) along and across the SSF. These initialization fields are then used for dynamical simulations via the primitive equation model. Simulation results are analyzed to calibrate the multiparameter feature-oriented modeling system. Experimental short-term synoptic simulations are presented for multiple resolutions in different regions with and without atmospheric forcing. The presented 'generic and portable' methodology demonstrates the potential of applying similar FORMS in many other regions of the Global Coastal Ocean.

Understanding Hydraulic Fracturing: A Multi-Scale Problem

DOE PAGES

Hyman, Jeffrey De'Haven; Gimenez Martinez, Joaquin; Viswanathan, Hari S.; ...

2016-09-05

Despite the impact that hydraulic fracturing has had on the energy sector, the physical mechanisms that control its efficiency and environmental impacts remain poorly understood in part because the length scales involved range from nano-meters to kilo-meters. We characterize flow and transport in shale formations across and between these scales using integrated computational, theoretical, and experimental efforts. At the field scale, we use discrete fracture network modeling to simulate production at a well site whose fracture network is based on a site characterization of a shale formation. At the core scale, we use triaxial fracture experiments and a finite-element discrete-elementmore » fracture propagation model with a coupled fluid solver to study dynamic crack propagation in low permeability shale. We use lattice Boltzmann pore-scale simulations and microfluidic experiments in both synthetic and real micromodels to study pore-scale flow phenomenon such as multiphase flow and mixing. A mechanistic description and integration of these multiple scales is required for accurate predictions of production and the eventual optimization of hydrocarbon extraction from unconventional reservoirs.« less

A priori study of subgrid-scale features in turbulent Rayleigh-Bénard convection

NASA Astrophysics Data System (ADS)

Dabbagh, F.; Trias, F. X.; Gorobets, A.; Oliva, A.

2017-10-01

At the crossroad between flow topology analysis and turbulence modeling, a priori studies are a reliable tool to understand the underlying physics of the subgrid-scale (SGS) motions in turbulent flows. In this paper, properties of the SGS features in the framework of a large-eddy simulation are studied for a turbulent Rayleigh-Bénard convection (RBC). To do so, data from direct numerical simulation (DNS) of a turbulent air-filled RBC in a rectangular cavity of aspect ratio unity and π spanwise open-ended distance are used at two Rayleigh numbers R a ∈{1 08,1 010 } [Dabbagh et al., "On the evolution of flow topology in turbulent Rayleigh-Bénard convection," Phys. Fluids 28, 115105 (2016)]. First, DNS at Ra = 108 is used to assess the performance of eddy-viscosity models such as QR, Wall-Adapting Local Eddy-viscosity (WALE), and the recent S3PQR-models proposed by Trias et al. ["Building proper invariants for eddy-viscosity subgrid-scale models," Phys. Fluids 27, 065103 (2015)]. The outcomes imply that the eddy-viscosity modeling smoothes the coarse-grained viscous straining and retrieves fairly well the effect of the kinetic unfiltered scales in order to reproduce the coherent large scales. However, these models fail to approach the exact evolution of the SGS heat flux and are incapable to reproduce well the further dominant rotational enstrophy pertaining to the buoyant production. Afterwards, the key ingredients of eddy-viscosity, νt, and eddy-diffusivity, κt, are calculated a priori and revealed positive prevalent values to maintain a turbulent wind essentially driven by the mean buoyant force at the sidewalls. The topological analysis suggests that the effective turbulent diffusion paradigm and the hypothesis of a constant turbulent Prandtl number are only applicable in the large-scale strain-dominated areas in the bulk. It is shown that the bulk-dominated rotational structures of vortex-stretching (and its synchronous viscous dissipative structures) hold

Metabolic Profile as a Potential Modifier of Long-Term Radiation Effects on Peripheral Lymphocyte Subsets in Atomic Bomb Survivors.

PubMed

Yoshida, Kengo; Nakashima, Eiji; Kyoizumi, Seishi; Hakoda, Masayuki; Hayashi, Tomonori; Hida, Ayumi; Ohishi, Waka; Kusunoki, Yoichiro

2016-09-01

Immune system impairments reflected by the composition and function of circulating lymphocytes are still observed in atomic bomb survivors, and metabolic abnormalities including altered blood triglyceride and cholesterol levels have also been detected in such survivors. Based on closely related features of immune and metabolic profiles of individuals, we investigated the hypothesis that long-term effects of radiation exposure on lymphocyte subsets might be modified by metabolic profiles in 3,113 atomic bomb survivors who participated in health examinations at the Radiation Effect Research Foundation, Hiroshima and Nagasaki, in 2000-2002. The lymphocyte subsets analyzed involved T-, B- and NK-cell subsets, and their percentages in the lymphocyte fraction were assessed using flow cytometry. Health examinations included metabolic indicators, body mass index, serum levels of total cholesterol, high-density lipoprotein cholesterol, C-reactive protein and hemoglobin A1c, as well as diabetes and fatty liver diagnoses. Standard regression analyses indicated that several metabolic indicators of obesity/related disease, particularly high-density lipoprotein cholesterol levels, were positively associated with type-1 helper T- and B-cell percentages but were inversely associated with naïve CD4 T and NK cells. A regression analysis adjusted for high-density lipoprotein cholesterol revealed a radiation dose relationship with increasing NK-cell percentage. Additionally, an interaction effect was suggested between radiation dose and C-reactive protein on B-cell percentage with a negative coefficient of the interaction term. Collectively, these findings suggest that radiation exposure and subsequent metabolic profile changes, potentially in relationship to obesity-related inflammation, lead to such long-term alterations in lymphocyte subset composition. Because this study is based on cross-sectional and exploratory analyses, the implications regarding radiation exposure, metabolic

Depth-time interpolation of feature trends extracted from mobile microelectrode data with kernel functions.

PubMed

Wong, Stephen; Hargreaves, Eric L; Baltuch, Gordon H; Jaggi, Jurg L; Danish, Shabbar F

2012-01-01

Microelectrode recording (MER) is necessary for precision localization of target structures such as the subthalamic nucleus during deep brain stimulation (DBS) surgery. Attempts to automate this process have produced quantitative temporal trends (feature activity vs. time) extracted from mobile MER data. Our goal was to evaluate computational methods of generating spatial profiles (feature activity vs. depth) from temporal trends that would decouple automated MER localization from the clinical procedure and enhance functional localization in DBS surgery. We evaluated two methods of interpolation (standard vs. kernel) that generated spatial profiles from temporal trends. We compared interpolated spatial profiles to true spatial profiles that were calculated with depth windows, using correlation coefficient analysis. Excellent approximation of true spatial profiles is achieved by interpolation. Kernel-interpolated spatial profiles produced superior correlation coefficient values at optimal kernel widths (r = 0.932-0.940) compared to standard interpolation (r = 0.891). The choice of kernel function and kernel width resulted in trade-offs in smoothing and resolution. Interpolation of feature activity to create spatial profiles from temporal trends is accurate and can standardize and facilitate MER functional localization of subcortical structures. The methods are computationally efficient, enhancing localization without imposing additional constraints on the MER clinical procedure during DBS surgery. Copyright © 2012 S. Karger AG, Basel.

Composite Nanomechanics: A Mechanistic Properties Prediction

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Handler, Louis M.; Manderscheid, Jane M.

2007-01-01

A unique mechanistic theory is described to predict the properties of nanocomposites. The theory is based on composite micromechanics with progressive substructuring down to a nanoscale slice of a nanofiber where all the governing equations are formulated. These equations hav e been programmed in a computer code. That computer code is used to predict 25 properties of a mononanofiber laminate. The results are pr esented graphically and discussed with respect to their practical sig nificance. Most of the results show smooth distributions. Results for matrix-dependent properties show bimodal through-the-thickness distr ibution with discontinuous changes from mode to mode.

Profiler - A Fast and Versatile New Program for Decomposing Galaxy Light Profiles

NASA Astrophysics Data System (ADS)

Ciambur, Bogdan C.

2016-12-01

I introduce Profiler, a user-friendly program designed to analyse the radial surface brightness profiles of galaxies. With an intuitive graphical user interface, Profiler can accurately model galaxies of a broad range of morphological types, with various parametric functions routinely employed in the field (Sérsic, core-Sérsic, exponential, Gaussian, Moffat, and Ferrers). In addition to these, Profiler can employ the broken exponential model for disc truncations or anti-truncations, and two special cases of the edge-on disc model: along the disc's major or minor axis. The convolution of (circular or elliptical) models with the point spread function is performed in 2D, and offers a choice between Gaussian, Moffat or a user-provided profile for the point spread function. Profiler is optimised to work with galaxy light profiles obtained from isophotal measurements, which allow for radial gradients in the geometric parameters of the isophotes, and are thus often better at capturing the total light than 2D image-fitting programs. Additionally, the 1D approach is generally less computationally expensive and more stable. I demonstrate Profiler's features by decomposing three case-study galaxies: the cored elliptical galaxy NGC 3348, the nucleated dwarf Seyfert I galaxy Pox 52, and NGC 2549, a double-barred galaxy with an edge-on, truncated disc.

Mechanistic modelling of the inhibitory effect of pH on microbial growth.

PubMed

Akkermans, Simen; Van Impe, Jan F

2018-06-01

Modelling and simulation of microbial dynamics as a function of processing, transportation and storage conditions is a useful tool to improve microbial food safety and quality. The goal of this research is to improve an existing methodology for building mechanistic predictive models based on the environmental conditions. The effect of environmental conditions on microbial dynamics is often described by combining the separate effects in a multiplicative way (gamma concept). This idea was extended further in this work by including the effects of the lag and stationary growth phases on microbial growth rate as independent gamma factors. A mechanistic description of the stationary phase as a function of pH was included, based on a novel class of models that consider product inhibition. Experimental results on Escherichia coli growth dynamics indicated that also the parameters of the product inhibition equations can be modelled with the gamma approach. This work has extended a modelling methodology, resulting in predictive models that are (i) mechanistically inspired, (ii) easily identifiable with a limited work load and (iii) easily extended to additional environmental conditions. Copyright © 2017. Published by Elsevier Ltd.

Spatial modeling of agricultural land use change at global scale

NASA Astrophysics Data System (ADS)

Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

2014-11-01

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling

REDUCING UNCERTAINTY IN RISK ASSESSMENT USING MECHANISTIC DATA: ENHANCING THE U.S. EPA DEVELOPMENTAL NEUROTOXICITY TESTING GUIDELINES

EPA Science Inventory

SUMMARY: Mechanistic data should provide the Agency with a more accurate basis to estimate risk than do the Agency’s default assumptions (10x uncertainty factors, etc.), thereby improving risk assessment decisions. NTD is providing mechanistic data for toxicant effects on two maj...

iFeature: a python package and web server for features extraction and selection from protein and peptide sequences.

PubMed

Chen, Zhen; Zhao, Pei; Li, Fuyi; Leier, André; Marquez-Lago, Tatiana T; Wang, Yanan; Webb, Geoffrey I; Smith, A Ian; Daly, Roger J; Chou, Kuo-Chen; Song, Jiangning

2018-03-08

Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural, functional, expression and interaction profiles of proteins and peptides as well as DNAs/RNAs. Here, we present iFeature, a versatile Python-based toolkit for generating various numerical feature representation schemes for both protein and peptide sequences. iFeature is capable of calculating and extracting a comprehensive spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. It also allows users to extract specific amino acid properties from the AAindex database. Furthermore, iFeature integrates 12 different types of commonly used feature clustering, selection, and dimensionality reduction algorithms, greatly facilitating training, analysis, and benchmarking of machine-learning models. The functionality of iFeature is made freely available via an online web server and a stand-alone toolkit. http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/. jiangning.song@monash.edu; kcchou@gordonlifescience.org; roger.daly@monash.edu. Supplementary data are available at Bioinformatics online.

Does Mechanistic Thinking Improve Student Success in Organic Chemistry?

ERIC Educational Resources Information Center

Grove, Nathaniel P.; Cooper, Melanie M.; Cox, Elizabeth L.

2012-01-01

The use of the curved-arrow notation to depict electron flow during mechanistic processes is one of the most important representational conventions in the organic chemistry curriculum. Our previous research documented a disturbing trend: when asked to predict the products of a series of reactions, many students do not spontaneously engage in…

Non-Esterified Fatty Acids Profiling in Rheumatoid Arthritis: Associations with Clinical Features and Th1 Response.

PubMed

Rodríguez-Carrio, Javier; Alperi-López, Mercedes; López, Patricia; Ballina-García, Francisco Javier; Suárez, Ana

2016-01-01

Since lipid compounds are known to modulate the function of CD4+ T-cells and macrophages, we hypothesize that altered levels of serum non-esterified fatty acids (NEFA) may underlie rheumatoid arthritis (RA) pathogenesis. Serum levels of NEFA (palmitic, stearic, palmitoleic, oleic, linoleic, γ-linoleic, arachidonic -AA-, linolenic, eicosapentaenoic -EPA- and docosahexaenoic -DHA-) were quantified by LC-MS/MS after methyl-tert-butylether (MTBE)-extraction in 124 RA patients and 56 healthy controls (HC). CD4+ phenotype was studied by flow cytometry. TNFα, IL-8, VEGF, GM-CSF, IFNγ, IL-17, CCL2, CXCL10, leptin and resistin serum levels were quantified by immunoassays. The effect of FA on IFNγ production by PBMC was evaluated in vitro. Lower levels of palmitic (p<0.0001), palmitoleic (p = 0.002), oleic (p = 0.010), arachidonic (p = 0.027), EPA (p<0.0001) and DHA (p<0.0001) were found in RA patients, some NEFA being altered at onset. Cluster analysis identified a NEFA profile (hallmarked by increased stearic and decreased EPA and DHA) overrepresented in RA patients compared to HC (p = 0.002), being associated with clinical features (RF, shared epitope and erosions), increased IFNγ expression in CD4+ T-cells (p = 0.002) and a Th1-enriched serum milieu (IFNγ, CCL2 and CXCL10, all p<0.005). In vitro assays demonstrated that imbalanced FA could underlie IFNγ production by CD4+ T-cells. Finally, changes on NEFA levels were associated with clinical response upon TNFα-blockade. An altered NEFA profile can be found in RA patients associated with clinical characteristics of aggressive disease and enhanced Th1 response. These results support the relevance of lipidomic studies in RA and provide a rationale for new therapeutic targets.

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features

PubMed Central

2011-01-01

Background Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Methods Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Results Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. Conclusion This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features.

PubMed

Haakensen, Vilde D; Lingjaerde, Ole Christian; Lüders, Torben; Riis, Margit; Prat, Aleix; Troester, Melissa A; Holmen, Marit M; Frantzen, Jan Ole; Romundstad, Linda; Navjord, Dina; Bukholm, Ida K; Johannesen, Tom B; Perou, Charles M; Ursin, Giske; Kristensen, Vessela N; Børresen-Dale, Anne-Lise; Helland, Aslaug

2011-11-01

Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.

Distributions of Gas and Galaxies from Galaxy Clusters to Larger Scales

NASA Astrophysics Data System (ADS)

Patej, Anna

2017-01-01

We address the distributions of gas and galaxies on three scales: the outskirts of galaxy clusters, the clustering of galaxies on large scales, and the extremes of the galaxy distribution. In the outskirts of galaxy clusters, long-standing analytical models of structure formation and recent simulations predict the existence of density jumps in the gas and dark matter profiles. We use these features to derive models for the gas density profile, obtaining a simple fiducial model that is in agreement with both observations of cluster interiors and simulations of the outskirts. We next consider the galaxy density profiles of clusters; under the assumption that the galaxies in cluster outskirts follow similar collisionless dynamics as the dark matter, their distribution should show a steep jump as well. We examine the profiles of a low-redshift sample of clusters and groups, finding evidence for the jump in some of these clusters. Moving to larger scales where massive galaxies of different types are expected to trace the same large-scale structure, we present a test of this prediction by measuring the clustering of red and blue galaxies at z 0.6, finding low stochasticity between the two populations. These results address a key source of systematic uncertainty - understanding how target populations of galaxies trace large-scale structure - in galaxy redshift surveys. Such surveys use baryon acoustic oscillations (BAO) as a cosmological probe, but are limited by the expense of obtaining sufficiently dense spectroscopy. With the intention of leveraging upcoming deep imaging data, we develop a new method of detecting the BAO in sparse spectroscopic samples via cross-correlation with a dense photometric catalog. This method will permit the extension of BAO measurements to higher redshifts than possible with the existing spectroscopy alone. Lastly, we connect galaxies near and far: the Local Group dwarfs and the high redshift galaxies observed by Hubble and Spitzer. We

Does the scale of our observational window affect our conclusions about correlations between endangered salmon populations and their habitat?

Treesearch

Blake E. Feist; E. Ashley Steel; David W. Jensen; Damon N.D. Sather

2010-01-01

Differences in the strength of species-habitat relationships across scales provide insights into the mechanisms that drive these relationships and guidance for designing in situ monitoring programs, conservation efforts and mechanistic studies. The scale of our observation can also impact the strength of perceived relationships between animals and habitat conditions....

Scale-free gravitational collapse as the origin of ρ ˜ r-2 density profile - a possible role of turbulence in regulating gravitational collapse

NASA Astrophysics Data System (ADS)

Li, Guang-Xing

2018-03-01

Astrophysical systems, such as clumps that form star clusters share a density profile that is close to ρ ˜ r-2. We prove analytically this density profile is the result of the scale-free nature of the gravitational collapse. Therefore, it should emerge in many different situations as long as gravity is dominating the evolution for a period that is comparable or longer than the free-fall time, and this does not necessarily imply an isothermal model, as many have previously believed. To describe the collapse process, we construct a model called the turbulence-regulated gravitational collapse model, where turbulence is sustained by accretion and dissipates in roughly a crossing time. We demonstrate that a ρ ˜ r-2 profile emerges due to the scale-free nature the system. In this particular case, the rate of gravitational collapse is regulated by the rate at which turbulence dissipates the kinetic energy such that the infall speed can be 20-50% of the free-fall speed(which also depends on the interpretation of the crossing time based on simulations of driven turbulence). These predictions are consistent with existing observations, which suggests that these clumps are in the stage of turbulence-regulated gravitational collapse. Our analysis provides a unified description of gravitational collapse in different environments.

Mechanistic Investigation on Grinding-Induced Subvisible Particle Formation during Mixing and Filling of Monoclonal Antibody Formulations.

PubMed

Gikanga, Benson; Hui, Ada; Maa, Yuh-Fun

2018-01-01

the absence of significant high-molecular-weight species and low-molecular-weight species, in spray-dried monoclonal antibody powders. This investigation provides a mechanistic understanding of the underlying stress mechanism leading to monoclonal antibody subvisible particle formation as the result of drug product processing involving grinding of solid surfaces. LAY ABSTRACT: Subvisible particles present in therapeutic protein formulations could adversely affect drug product safety and efficacy. We previously illustrated that grinding action of the solid surfaces in some bottom-mounted mixers and piston pump is responsible for subvisible particle formation of monoclonal antibody formulations. In this study, we delved into mechanistic understanding of the stress types associated with solid surface grinding. The approach was to employ several scale-down stress models with known stress types. Protein formulations stressed in these models were analytically characterized for subvisible particles and other degradants. Some commonly known stress types-such as air-liquid interface, mechanical stress, cavitation, nucleation, and thermal effect-were assessed in this study. The stress model yielding a degradation profile matching that of bottom-mounted mixers and piston pump warranted further assessment. Localized, thermal stress proved to be the most feasible mechanism. This study, along with previously published results, may further advance our understanding of these particular drug product manufacturing processes and benefit scientists and engineers in overcoming these development challenges. © PDA, Inc. 2018.

Mechanistic-empirical design concepts for continuously reinforced concrete pavements in Illinois.

DOT National Transportation Integrated Search

2009-04-01

The Illinois Department of Transportation (IDOT) currently has an existing jointed plain concrete pavement : (JPCP) design based on mechanistic-empirical (M-E) principles. However, their continuously reinforced concrete : pavement (CRCP) design proce...

Predicting agricultural impacts of large-scale drought: 2012 and the case for better modeling

USDA-ARS?s Scientific Manuscript database

We present an example of a simulation-based forecast for the 2012 U.S. maize growing season produced as part of a high-resolution, multi-scale, predictive mechanistic modeling study designed for decision support, risk management, and counterfactual analysis. The simulations undertaken for this analy...

Association of high proliferation marker Ki-67 expression with DCEMR imaging features of breast: a large scale evaluation

NASA Astrophysics Data System (ADS)

Saha, Ashirbani; Harowicz, Michael R.; Grimm, Lars J.; Kim, Connie E.; Ghate, Sujata V.; Walsh, Ruth; Mazurowski, Maciej A.

2018-02-01

One of the methods widely used to measure the proliferative activity of cells in breast cancer patients is the immunohistochemical (IHC) measurement of the percentage of cells stained for nuclear antigen Ki-67. Use of Ki-67 expression as a prognostic marker is still under investigation. However, numerous clinical studies have reported an association between a high Ki-67 and overall survival (OS) and disease free survival (DFS). On the other hand, to offer non-invasive alternative in determining Ki-67 expression, researchers have made recent attempts to study the association of Ki-67 expression with magnetic resonance (MR) imaging features of breast cancer in small cohorts (<30). Here, we present a large scale evaluation of the relationship between imaging features and Ki-67 score as: (a) we used a set of 450 invasive breast cancer patients, (b) we extracted a set of 529 imaging features of shape and enhancement from breast, tumor and fibroglandular tissue of the patients, (c) used a subset of patients as the training set to select features and trained a multivariate logistic regression model to predict high versus low Ki-67 values, and (d) we validated the performance of the trained model in an independent test set using the area-under the receiver operating characteristics (ROC) curve (AUC) of the values predicted. Our model was able to predict high versus low Ki-67 in the test set with an AUC of 0.67 (95% CI: 0.58-0.75, p<1.1e-04). Thus, a moderate strength of association of Ki-67 values and MRextracted imaging features was demonstrated in our experiments.

Karolinska Psychodynamic Profile for Sexual Disorders: KAPP-SD. A proposal for a psychodynamic rating scale for sexual disorders.

PubMed

Soldati, Lorenzo; Köhl, John; Abraham, Georges; Bianchi Demicheli, Francesco; Wilczek, Alexander

2015-01-01

Our first objective in this paper was to review the literature on psychodynamic rating scales of sexual disorders. Our second objective, based on the findings from our review, was to develop a psychodynamic rating scale for people with sexual disorders: the KAPP-SD. We developed the KAPP-SD by modifying an existing psychodynamic rating scale, which assesses stable modes of mental functioning and character traits, the Karolinska Psychodynamic Profile (KAPP). We removed items 13 and 14 of the KAPP and replaced them with three other items-sexual fantasies, conceptions and role of gender identity, and conceptions and role of sexual orientation. These items are part of the assessment of an individual's sexuality and are used to evaluate a person with a sexual disorder psychodynamically. The KAPP-SD, a modified version of the KAPP, can be found in the Appendix. We developed the KAPP-SD in order to help sex therapists make a rigorous psychodynamic evaluation of persons with sexual disorders, which would give information on the prognosis and on the type of treatment to offer.

Scaling laws for coastal overwash morphology

NASA Astrophysics Data System (ADS)

Lazarus, Eli D.

2016-12-01

Overwash is a physical process of coastal sediment transport driven by storm events and is essential to landscape resilience in low-lying barrier environments. This work establishes a comprehensive set of scaling laws for overwash morphology: unifying quantitative descriptions with which to compare overwash features by their morphological attributes across case examples. Such scaling laws also help relate overwash features to other morphodynamic phenomena. Here morphometric data from a physical experiment are compared with data from natural examples of overwash features. The resulting scaling relationships indicate scale invariance spanning several orders of magnitude. Furthermore, these new relationships for overwash morphology align with classic scaling laws for fluvial drainages and alluvial fans.

Existing pavement input information for the mechanistic-empirical pavement design guide.

DOT National Transportation Integrated Search

2009-02-01

The objective of this study is to systematically evaluate the Iowa Department of Transportations (DOTs) existing Pavement Management Information System (PMIS) with respect to the input information required for Mechanistic-Empirical Pavement Des...

Calibrating the mechanistic-empirical pavement design guide for Kansas : [technical summary].

DOT National Transportation Integrated Search

2015-04-01

The Kansas Department of Transportation (KDOT) is moving toward the implementation : of the new American Association of State Highway and Transportation Officials : (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) for pavement : design. T...

The scaling features of the 3D organization of chromosomes are highlighted by a transformation à la Kadanoff of Hi-C data

NASA Astrophysics Data System (ADS)

Chiariello, Andrea M.; Bianco, Simona; Annunziatella, Carlo; Esposito, Andrea; Nicodemi, Mario

2017-11-01

Technologies such as Hi-C and GAM have revealed that chromosomes are not randomly folded into the nucleus of cells, but are composed by a sequence of contact domains (TADs), each typically 0.5 Mb long. However, the larger scale organization of the genome remains still not well understood. To investigate the scaling behaviour of chromosome folding, here we apply an approach à la Kadanoff, inspired by the Renormalization Group theory, to Hi-C interaction data, across different cell types and chromosomes. We find that the genome is characterized by complex scaling features, where the average size of contact domains exhibits a power-law behaviour with the rescaling level. That is compatible with the existence of contact domains extending across length scales up to chromosomal sizes. The scaling exponent is statistically indistinguishable among the different murine cell types analysed. These results point toward a scenario of a universal higher-order spatial architecture of the genome, which could reflect fundamental, organizational principles.