Evaluating Machine Learning Regression Algorithms for Operational Retrieval of Biophysical Parameters: Opportunities for Sentinel

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Rivera, J. P.; Alonso, L.; Guanter, L.; Moreno, J.

2012-04-01

ESA’s upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT- 5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high spatial and temporal resolution. S2 and S3 will deliver near real-time operational products with a high accuracy for land monitoring. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods. Machine learning regression algorithms could be powerful candidates for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. By using data from the ESA-led field campaign SPARC (Barrax, Spain), it was recently found [1] that Gaussian processes regression (GPR) outperformed competitive machine learning algorithms such as neural networks, support vector regression) and kernel ridge regression both in terms of accuracy and computational speed. For various Sentinel configurations (S2-10m, S2- 20m, S2-60m and S3-300m) three important biophysical parameters were estimated: leaf chlorophyll content (Chl), leaf area index (LAI) and fractional vegetation cover (FVC). GPR was the only method that reached the 10% precision required by end users in the estimation of Chl. In view of implementing the regressor into operational monitoring applications, here the portability of locally trained GPR models to other images was evaluated. The associated confidence maps proved to be a good indicator for evaluating the robustness of the trained models. Consistent retrievals were obtained across the different images, particularly over agricultural sites. To make the method suitable for operational use, however, the poorer confidences over bare soil areas suggest that the training dataset should be expanded with inputs from various land cover types.

Covariance of biophysical data with digital topograpic and land use maps over the FIFE site

NASA Technical Reports Server (NTRS)

Davis, F. W.; Schimel, D. S.; Friedl, M. A.; Michaelsen, J. C.; Kittel, T. G. F.; Dubayah, R.; Dozier, J.

1992-01-01

This paper discusses the biophysical stratification of the FIFE site, implementation of the stratification utilizing geographic information system methods, and validation of the stratification with respect to field measurements of biomass, Bowen ratio, soil moisture, and the greenness vegetation index (GVI) derived from TM satellite data. Maps of burning and topographic position were significantly associated with variation in GVI, biomass, and Bowen ratio. The stratified design did not significantly alter the estimated site-wide means for surface climate parameters but accounted for between 25 and 45 percent of the sample variance depending on the variable.

Temporal measurement and analysis of high-resolution spectral signatures of plants and relationships to biophysical characteristics

NASA Astrophysics Data System (ADS)

Bostater, Charles R., Jr.; Rebbman, Jan; Hall, Carlton; Provancha, Mark; Vieglais, David

1995-11-01

Measurements of temporal reflectance signatures as a function of growing season for sand live oak (Quercus geminata), myrtle oak (Q. myrtifolia, and saw palmetto (Serenoa repens) were collected during a two year study period. Canopy level spectral reflectance signatures, as a function of 252 channels between 368 and 1115 nm, were collected using near nadir viewing geometry and a consistent sun illumination angle. Leaf level reflectance measurements were made in the laboratory using a halogen light source and an environmental optics chamber with a barium sulfate reflectance coating. Spectral measurements were related to several biophysical measurements utilizing optimal passive ambient correlation spectroscopy (OPACS) technique. Biophysical parameters included percent moisture, water potential (MPa), total chlorophyll, and total Kjeldahl nitrogen. Quantitative data processing techniques were used to determine optimal bands based on the utilization of a second order derivative or inflection estimator. An optical cleanup procedure was then employed that computes the double inflection ratio (DIR) spectra for all possible three band combinations normalized to the previously computed optimal bands. These results demonstrate a unique approach to the analysis of high spectral resolution reflectance signatures for estimation of several biophysical measures of plants at the leaf and canopy level from optimally selected bands or bandwidths.

Improved estimation of anomalous diffusion exponents in single-particle tracking experiments

NASA Astrophysics Data System (ADS)

Kepten, Eldad; Bronshtein, Irena; Garini, Yuval

2013-05-01

The mean square displacement is a central tool in the analysis of single-particle tracking experiments, shedding light on various biophysical phenomena. Frequently, parameters are extracted by performing time averages on single-particle trajectories followed by ensemble averaging. This procedure, however, suffers from two systematic errors when applied to particles that perform anomalous diffusion. The first is significant at short-time lags and is induced by measurement errors. The second arises from the natural heterogeneity in biophysical systems. We show how to estimate and correct these two errors and improve the estimation of the anomalous parameters for the whole particle distribution. As a consequence, we manage to characterize ensembles of heterogeneous particles even for rather short and noisy measurements where regular time-averaged mean square displacement analysis fails. We apply this method to both simulations and in vivo measurements of telomere diffusion in 3T3 mouse embryonic fibroblast cells. The motion of telomeres is found to be subdiffusive with an average exponent constant in time. Individual telomere exponents are normally distributed around the average exponent. The proposed methodology has the potential to improve experimental accuracy while maintaining lower experimental costs and complexity.

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

PubMed

Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

2017-12-01

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

Monitoring of biophysical parameters of cashew plants in Cambodia using ALOS/PALSAR data.

PubMed

Avtar, Ram; Takeuchi, Wataru; Sawada, Haruo

2013-02-01

An accurate estimation of a plant's age is required for the prediction of yield and management practices. This study demonstrates the relationship between backscattering properties (σ°) of Phased Array type L-band Synthetic Aperture Radar (PALSAR) dual polarimetric data with cashew plants' biophysical parameters (height, age, crown diameter, diameter at breast height, basal area, tree density, and biomass) in Cambodia. PALSAR σ° has shown a positive correlation with the biophysical parameters of cashew plants. The value of σ° increases with the age of cashew plants. At a young stage, the cashew plants show a higher rate of an increase in σ° compared to that at the mature stage. The σ° horizontal polarization transmitted and vertical received (HV) shows higher sensitivity to the plant's growth than σ° horizontal polarization transmitted and received (HH). High backscattering and low variations were observed at mature stage (8-12 years) of cashew plantation. Saturation in backscattering has shown from the age of about 13 years. The validation results indicate strong coefficient of determination (R(2) = 0.86 and 0.88) for PALSAR-predicted age and biomass of cashew plants with root mean square error = 1.8 years and 16.3 t/ha for age and biomass, respectively. The correlations of σ° (HH) with biophysical parameters observed in the dry season were better than those of the rainy season because soil moisture interferes with backscattering in the rainy season. Biomass accumulation rate of cashew plants has been predicted that would be useful for selection of plants species to enhance carbon sequestration. This study provides an insight to use PALSAR for the monitoring of growth stages of plants at the regional level.

An information-based approach to change-point analysis with applications to biophysics and cell biology.

PubMed

Wiggins, Paul A

2015-07-21

This article describes the application of a change-point algorithm to the analysis of stochastic signals in biological systems whose underlying state dynamics consist of transitions between discrete states. Applications of this analysis include molecular-motor stepping, fluorophore bleaching, electrophysiology, particle and cell tracking, detection of copy number variation by sequencing, tethered-particle motion, etc. We present a unified approach to the analysis of processes whose noise can be modeled by Gaussian, Wiener, or Ornstein-Uhlenbeck processes. To fit the model, we exploit explicit, closed-form algebraic expressions for maximum-likelihood estimators of model parameters and estimated information loss of the generalized noise model, which can be computed extremely efficiently. We implement change-point detection using the frequentist information criterion (which, to our knowledge, is a new information criterion). The frequentist information criterion specifies a single, information-based statistical test that is free from ad hoc parameters and requires no prior probability distribution. We demonstrate this information-based approach in the analysis of simulated and experimental tethered-particle-motion data. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Energy balance model applied to pasture experimental areas in São Paulo State, Brazil

NASA Astrophysics Data System (ADS)

Bayma-Silva, Gustavo; de Castro Teixeira, Antonio Heriberto; de Castro Victoria, Daniel; Furlan Nogueira, Sandra; Freitas Leivas, Janice; Coaguila, Daniel N.; Rodrigues Herling, Valdo

2016-10-01

The Simple Algorithm for Evapotranspiration Retrieving (SAFER) was used to estimate biophysical parameters and the energy balance components in two different pasture experimental areas, in the São Paulo state, Brazil. The experimental pastures consist in six rotational (RGS) and three continuous grazing systems (CGS) paddocks. Landsat-8 images from 2013 and 2015 dry and rainy seasons were used, as these presented similar hydrological cycle, with 1,600 mm and 1,613 mm of annual precipitation, resulting in 19 cloud-free images. Bands 1 to 7 and thermal bands 10 and 11 were used with weather data from a station located near the experimental area. NDVI, biomass, evapotranspiration and latent heat flux (λE) temporal values statistically differ CGS from RGS areas. Grazing systems influences the energy partition and these results indicate that RGS benefits biomass production, evapotranspiration and the microclimate, due higher LE values. SAFER is a feasible tool to estimate biophysical parameters and energy balance components in pasture and has potential to discriminate continuous and rotation grazing systems in a temporal analysis.

Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series

NASA Astrophysics Data System (ADS)

Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik

2016-06-01

Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model biophysical parameters.

Analytical model of diffuse reflectance spectrum of skin tissue

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.; Firago, V. A.; Sobchuk, A. N.

2014-01-01

We have derived simple analytical expressions that enable highly accurate calculation of diffusely reflected light signals of skin in the spectral range from 450 to 800 nm at a distance from the region of delivery of exciting radiation. The expressions, taking into account the dependence of the detected signals on the refractive index, transport scattering coefficient, absorption coefficient and anisotropy factor of the medium, have been obtained in the approximation of a two-layer medium model (epidermis and dermis) for the same parameters of light scattering but different absorption coefficients of layers. Numerical experiments on the retrieval of the skin biophysical parameters from the diffuse reflectance spectra simulated by the Monte Carlo method show that commercially available fibre-optic spectrophotometers with a fixed distance between the radiation source and detector can reliably determine the concentration of bilirubin, oxy- and deoxyhaemoglobin in the dermis tissues and the tissue structure parameter characterising the size of its effective scatterers. We present the examples of quantitative analysis of the experimental data, confirming the correctness of estimates of biophysical parameters of skin using the obtained analytical expressions.

Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter

PubMed Central

Reddy, Chinthala P.; Rathi, Yogesh

2016-01-01

Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts. PMID:27147956

Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter.

PubMed

Reddy, Chinthala P; Rathi, Yogesh

2016-01-01

Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts.

Changes in biophysical properties of the skin following radiotherapy for breast cancer.

PubMed

Hu, Stephen Chu-Sung; Hou, Ming-Feng; Luo, Kuei-Hau; Chuang, Hung-Yi; Wei, Shu-Yi; Chen, Gwo-Shing; Chiang, Wenchang; Huang, Chih-Jen

2014-12-01

Acute radiation dermatitis is a common adverse effect in patients undergoing radiotherapy for breast cancer. However, the effects of radiotherapy on biophysical properties of the skin have rarely been investigated. In this prospective cohort study, we seek to determine the effects of radiotherapy for breast cancer on skin biophysical parameters. We measured various skin biophysical parameters (skin hydration, pH, sebum level, pigmentation, and blood flow) in 144 breast cancer patients by non-invasive techniques before and after radiotherapy. The measurements were simultaneously performed on the irradiated breast and the corresponding contralateral unirradiated breast for comparison. Following radiotherapy, the irradiated breast showed a significant decrease in skin hydration, increase in skin pH, increase in pigmentation, and increase in cutaneous blood flow. The contralateral unirradiated breast showed a slight increase in pigmentation but no significant changes in any of the other biophysical parameters after radiotherapy. No significant associations were found between patient characteristics (diabetes mellitus, hypertension, type of surgery, chemotherapy, hormone therapy) and changes in skin biophysical parameters following radiotherapy. In conclusion, radiation therapy for breast cancer induces measurable and significant changes in biophysical properties of the skin including hydration, pH, pigmentation, and blood flow. These findings give us a greater understanding of the effects of ionizing radiation on skin physiology, and provide non-invasive and objective methods to assess radiation dermatitis. © 2014 Japanese Dermatological Association.

Hybrid System for Ex Vivo Hemorheological and Hemodynamic Analysis: A Feasibility Study

PubMed Central

Yeom, Eunseop; Jun Kang, Yang; Joon Lee, Sang

2015-01-01

Precise measurement of biophysical properties is important to understand the relation between these properties and the outbreak of cardiovascular diseases (CVDs). However, a systematic measurement for these biophysical parameters under in vivo conditions is nearly impossible because of complex vessel shape and limited practicality. In vitro measurements can provide more biophysical information, but in vitro exposure changes hemorheological properties. In this study, a hybrid system composed of an ultrasound system and microfluidic device is proposed for monitoring hemorheological and hemodynamic properties under more reasonable experimental conditions. Biophysical properties including RBC aggregation, viscosity, velocity, and pressure of blood flows are simultaneously measured under various conditions to demonstrate the feasibility and performance of this measurement system. The proposed technique is applied to a rat extracorporeal loop which connects the aorta and jugular vein directly. As a result, the proposed system is found to measure biophysical parameters reasonably without blood collection from the rat and provided more detailed information. This hybrid system, combining ultrasound imaging and microfluidic techniques to ex vivo animal models, would be useful for monitoring the variations of biophysical properties induced by chemical agents. It can be used to understand the relation between biophysical parameters and CVDs. PMID:26090816

Understanding moisture stress on light use efficiency across terrestrial ecosystems based on global flux and remote-sensing data

Treesearch

Yulong Zhang; Conghe Song; Ge Sun; Lawrence E. Band; Asko Noormets; Quanfa Zhang

2015-01-01

Light use efficiency (LUE) is a key biophysical parameter characterizing the ability of plants to convert absorbed light to carbohydrate. However, the environmental regulations on LUE, especially moisture stress, are poorly understood, leading to large uncertainties in primary productivity estimated by LUE models. The objective of this study is to investigate the...

Estimation of key parameters in adaptive neuron model according to firing patterns based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yuan, Chunhua; Wang, Jiang; Yi, Guosheng

2017-03-01

Estimation of ion channel parameters is crucial to spike initiation of neurons. The biophysical neuron models have numerous ion channel parameters, but only a few of them play key roles in the firing patterns of the models. So we choose three parameters featuring the adaptation in the Ermentrout neuron model to be estimated. However, the traditional particle swarm optimization (PSO) algorithm is still easy to fall into local optimum and has the premature convergence phenomenon in the study of some problems. In this paper, we propose an improved method that uses a concave function and dynamic logistic chaotic mapping mixed to adjust the inertia weights of the fitness value, effectively improve the global convergence ability of the algorithm. The perfect predicting firing trajectories of the rebuilt model using the estimated parameters prove that only estimating a few important ion channel parameters can establish the model well and the proposed algorithm is effective. Estimations using two classic PSO algorithms are also compared to the improved PSO to verify that the algorithm proposed in this paper can avoid local optimum and quickly converge to the optimal value. The results provide important theoretical foundations for building biologically realistic neuron models.

Design and validation of diffusion MRI models of white matter

NASA Astrophysics Data System (ADS)

Jelescu, Ileana O.; Budde, Matthew D.

2017-11-01

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the “biological accuracy” of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus.

A semisupervised support vector regression method to estimate biophysical parameters from remotely sensed images

NASA Astrophysics Data System (ADS)

Castelletti, Davide; Demir, Begüm; Bruzzone, Lorenzo

2014-10-01

This paper presents a novel semisupervised learning (SSL) technique defined in the context of ɛ-insensitive support vector regression (SVR) to estimate biophysical parameters from remotely sensed images. The proposed SSL method aims to mitigate the problems of small-sized biased training sets without collecting any additional samples with reference measures. This is achieved on the basis of two consecutive steps. The first step is devoted to inject additional priors information in the learning phase of the SVR in order to adapt the importance of each training sample according to distribution of the unlabeled samples. To this end, a weight is initially associated to each training sample based on a novel strategy that defines higher weights for the samples located in the high density regions of the feature space while giving reduced weights to those that fall into the low density regions of the feature space. Then, in order to exploit different weights for training samples in the learning phase of the SVR, we introduce a weighted SVR (WSVR) algorithm. The second step is devoted to jointly exploit labeled and informative unlabeled samples for further improving the definition of the WSVR learning function. To this end, the most informative unlabeled samples that have an expected accurate target values are initially selected according to a novel strategy that relies on the distribution of the unlabeled samples in the feature space and on the WSVR function estimated at the first step. Then, we introduce a restructured WSVR algorithm that jointly uses labeled and unlabeled samples in the learning phase of the WSVR algorithm and tunes their importance by different values of regularization parameters. Experimental results obtained for the estimation of single-tree stem volume show the effectiveness of the proposed SSL method.

Design and validation of diffusion MRI models of white matter

PubMed Central

Jelescu, Ileana O.; Budde, Matthew D.

2018-01-01

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the “biological accuracy” of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus. PMID:29755979

Senegalese land surface change analysis and biophysical parameter estimation using NOAA AVHRR spectral data

NASA Technical Reports Server (NTRS)

Vukovich, Fred M.; Toll, David L.; Kennard, Ruth L.

1989-01-01

Surface biophysical estimates were derived from analysis of NOAA Advanced Very High Spectral Resolution (AVHRR) spectral data of the Senegalese area of west Africa. The parameters derived were of solar albedo, spectral visible and near-infrared band reflectance, spectral vegetative index, and ground temperature. Wet and dry linked AVHRR scenes from 1981 through 1985 in Senegal were analyzed for a semi-wet southerly site near Tambacounda and a predominantly dry northerly site near Podor. Related problems were studied to convert satellite derived radiance to biophysical estimates of the land surface. Problems studied were associated with sensor miscalibration, atmospheric and aerosol spatial variability, surface anisotropy of reflected radiation, narrow satellite band reflectance to broad solar band conversion, and ground emissivity correction. The middle-infrared reflectance was approximated with a visible AVHRR reflectance for improving solar albedo estimates. In addition, the spectral composition of solar irradiance (direct and diffuse radiation) between major spectral regions (i.e., ultraviolet, visible, near-infrared, and middle-infrared) was found to be insensitive to changes in the clear sky atmospheric optical depth in the narrow band to solar band conversion procedure. Solar albedo derived estimates for both sites were not found to change markedly with significant antecedent precipitation events or correspondingly from increases in green leaf vegetation density. The bright soil/substrate contributed to a high albedo for the dry related scenes, whereas the high internal leaf reflectance in green vegetation canopies in the near-infrared contributed to high solar albedo for the wet related scenes. The relationship between solar albedo and ground temperature was poor, indicating the solar albedo has little control of the ground temperature. The normalized difference vegetation index (NDVI) and the derived visible reflectance were more sensitive to antecedent rainfall amounts and green vegetation changes than were near-infrared changes. The information in the NDVI related to green leaf density changes primarily was from the visible reflectance. The contribution of the near-infrared reflectance to explaining green vegetation is largely reduced when there is a bright substrate.

Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface.

PubMed

Knodel, Markus M; Nägel, Arne; Reiter, Sebastian; Vogel, Andreas; Targett-Adams, Paul; McLauchlan, John; Herrmann, Eva; Wittum, Gabriel

2018-01-08

Exploring biophysical properties of virus-encoded components and their requirement for virus replication is an exciting new area of interdisciplinary virological research. To date, spatial resolution has only rarely been analyzed in computational/biophysical descriptions of virus replication dynamics. However, it is widely acknowledged that intracellular spatial dependence is a crucial component of virus life cycles. The hepatitis C virus-encoded NS5A protein is an endoplasmatic reticulum (ER)-anchored viral protein and an essential component of the virus replication machinery. Therefore, we simulate NS5A dynamics on realistic reconstructed, curved ER surfaces by means of surface partial differential equations (sPDE) upon unstructured grids. We match the in silico NS5A diffusion constant such that the NS5A sPDE simulation data reproduce experimental NS5A fluorescence recovery after photobleaching (FRAP) time series data. This parameter estimation yields the NS5A diffusion constant. Such parameters are needed for spatial models of HCV dynamics, which we are developing in parallel but remain qualitative at this stage. Thus, our present study likely provides the first quantitative biophysical description of the movement of a viral component. Our spatio-temporal resolved ansatz paves new ways for understanding intricate spatial-defined processes central to specfic aspects of virus life cycles.

Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface

PubMed Central

Nägel, Arne; Reiter, Sebastian; Vogel, Andreas; McLauchlan, John; Herrmann, Eva; Wittum, Gabriel

2018-01-01

Exploring biophysical properties of virus-encoded components and their requirement for virus replication is an exciting new area of interdisciplinary virological research. To date, spatial resolution has only rarely been analyzed in computational/biophysical descriptions of virus replication dynamics. However, it is widely acknowledged that intracellular spatial dependence is a crucial component of virus life cycles. The hepatitis C virus-encoded NS5A protein is an endoplasmatic reticulum (ER)-anchored viral protein and an essential component of the virus replication machinery. Therefore, we simulate NS5A dynamics on realistic reconstructed, curved ER surfaces by means of surface partial differential equations (sPDE) upon unstructured grids. We match the in silico NS5A diffusion constant such that the NS5A sPDE simulation data reproduce experimental NS5A fluorescence recovery after photobleaching (FRAP) time series data. This parameter estimation yields the NS5A diffusion constant. Such parameters are needed for spatial models of HCV dynamics, which we are developing in parallel but remain qualitative at this stage. Thus, our present study likely provides the first quantitative biophysical description of the movement of a viral component. Our spatio-temporal resolved ansatz paves new ways for understanding intricate spatial-defined processes central to specfic aspects of virus life cycles. PMID:29316722

Reconstruction of neuronal input through modeling single-neuron dynamics and computations

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

Qin, Qing; Wang, Jiang; Yu, Haitao

Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-spacemore » method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.« less

Reconstruction of neuronal input through modeling single-neuron dynamics and computations

NASA Astrophysics Data System (ADS)

Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin; Chan, Wai-lok

2016-06-01

Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

Can biophysical properties of submersed macrophytes be determined by remote sensing?

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

Malthus, T.J.; Ciraolo, G.; La Loggia, G.

1997-06-01

This paper details the development of a computationally efficient Monte Carlo simulation program to model photon transport through submersed plant canopies, with emphasis on Seagrass communities. The model incorporates three components: the transmission of photons through a water column of varying depth and turbidity; the interaction of photons within a submersed plant canopy of varying biomass; and interactions with the bottom substrate. The three components of the model are discussed. Simulations were performed based on measured parameters for Posidonia oceanica and compared to measured subsurface reflectance spectra made over comparable seagrass communities in Sicilian coastal waters. It is shown thatmore » the output is realistic. Further simulations are undertaken to investigate the effect of depth and turbidity of the overlying water column. Both sets of results indicate the rapid loss of canopy signal as depth increases and water column phytoplankton concentrations increase. The implications for the development of algorithms for the estimation of submersed canopy biophysical parameters are briefly discussed.« less

A Multi-Sensor Approach to Enhance the Prediction of Mangrove Biophysical Characteristics in Chilika Lagoon and Bhitarkanika Wildlife Sanctuary, Odisha, India

NASA Astrophysics Data System (ADS)

Kumar, A.; Bledsoe, R.; Mishra, D. R.; Cameron, C.; Dahal, S.; Remillard, C.; Stone, A.; Stupp, P.

2017-12-01

Mangroves, one of the most productive ecosystems on Earth, play a major role in coastal ecosystem processes from mitigating erosion to acting as a barrier against tidal and storm surges associated with tropical cyclones. India has about 5 % of the world's mangrove vegetation, and over half of which is found along the east coast of the country. Chilika Lagoon and Bhitarkanika Wildlife Sanctuary are Ramsar sites of international wetland importance, situated in the state of Odisha along the east coast of India. Chilika Lagoon holds three small, but distinct mangrove patches, while Bhitarkanika Wildlife Sanctuary has several large, dense patches of mangroves. There is growing concern for the effective management and conservation of these mangrove forests. This study demonstrated the use of a suite of satellite data (Terra, Landsat, and Sentinel-1) for meeting the following objectives: 1. Derive a long-term spatio-temporal phenological maps of the biophysical parameters (chlorophyll, leaf area index, gross primary productivity, and evapotranspiration); 2. Analyze long-term spatio-temporal variability of physical and meteorological parameters; 3. Document decadal changes in mangroves area estimates starting from 1995 to 2017 using Landsat and radar data. The time series developed in this study revealed a phenological pattern for mangrove biophysical characteristics. Historical analysis of land cover maps indicated decrease in dense mangrove area and increase in open mangrove area and fragmentation. The results of this study will be used as an efficient biophysical mapping and monitoring protocol for mangrove forests in restoration decision-making.

Spaceborne SAR Data for Aboveground-Biomass Retrieval of Indian Tropical Forests

NASA Astrophysics Data System (ADS)

Khati, U.; Singh, G.; Musthafa, M.

2017-12-01

Forests are important and indispensable part of the terrestrial ecosystems, and have a direct impact on the global carbon cycle. Forest biophysical parameters such as forest stand height and forest above-ground biomass (AGB) are forest health indicators. Measuring the forest biomass using traditional ground survey techniques are man-power consuming and have very low spatial coverage. Satellite based remote sensing techniques provide synoptic view of the earth with continuous measurements over large, inaccessible forest regions. Satellite Synthetic Aperture Radar (SAR) data has been shown to be sensitive to these forest bio-physical parameters and have been extensively utilized over boreal and tropical forests. However, there are limited studies over Indian tropical forests due to lack of auxiliary airborne data and difficulties in manual in situ data collection. In this research work we utilize spaceborne data from TerraSAR-X/TanDEM-X and ALOS-2/PALSAR-2 and implement both Polarimetric SAR and PolInSAR techniques for retrieval of AGB of a managed tropical forest in India. The TerraSAR-X/TanDEM-X provide a single-baseline PolInSAR data robust to temporal decorrelation. This would be used to accurately estimate the forest stand height. The retrieved height would be an input parameter for modelling AGB using the L-band ALOS-2/PALSAR-2 data. The IWCM model is extensively utilized to estimate AGB from SAR observations. In this research we utilize the six component scattering power decomposition (6SD) parameters and modify the IWCM based technique for a better retrieval of forest AGB. PolInSAR data shows a high estimation accuracy with r2 of 0.8 and a RMSE of 2 m. With this accurate height provided as input to the modified model along with 6SD parameters shows promising results. The results are validated with extensive field based measurements, and are further analysed in detail.

Characterizing Olive Grove Canopies by Means of Ground-Based Hemispherical Photography and Spaceborne RADAR Data

PubMed Central

Molina, Iñigo; Morillo, Carmen; García-Meléndez, Eduardo; Guadalupe, Rafael; Roman, Maria Isabel

2011-01-01

One of the main strengths of active microwave remote sensing, in relation to frequency, is its capacity to penetrate vegetation canopies and reach the ground surface, so that information can be drawn about the vegetation and hydrological properties of the soil surface. All this information is gathered in the so called backscattering coefficient (σ0). The subject of this research have been olive groves canopies, where which types of canopy biophysical variables can be derived by a specific optical sensor and then integrated into microwave scattering models has been investigated. This has been undertaken by means of hemispherical photographs and gap fraction procedures. Then, variables such as effective and true Leaf Area Indices have been estimated. Then, in order to characterize this kind of vegetation canopy, two models based on Radiative Transfer theory have been applied and analyzed. First, a generalized two layer geometry model made up of homogeneous layers of soil and vegetation has been considered. Then, a modified version of the Xu and Steven Water Cloud Model has been assessed integrating the canopy biophysical variables derived by the suggested optical procedure. The backscattering coefficients at various polarized channels have been acquired from RADARSAT 2 (C-band), with 38.5° incidence angle at the scene center. For the soil simulation, the best results have been reached using a Dubois scattering model and the VV polarized channel (r2 = 0.88). In turn, when effective LAI (LAIeff) has been taken into account, the parameters of the scattering canopy model are better estimated (r2 = 0.89). Additionally, an inversion procedure of the vegetation microwave model with the adjusted parameters has been undertaken, where the biophysical values of the canopy retrieved by this methodology fit properly with field measured values. PMID:22164028

Estimating average tree crown size using spatial information from Ikonos and QuickBird images: Across-sensor and across-site comparisons

Treesearch

Conghe Song; Matthew B. Dickinson; Lihong Su; Su Zhang; Daniel Yaussey

2010-01-01

The forest canopy is the medium for energy, mass, and momentum exchanges between the forest ecosystem and the atmosphere. Tree crown size is a critical aspect of canopy structure that significantly influences these biophysical processes in the canopy. Tree crown size is also strongly related to other canopy structural parameters, such as tree height, diameter at breast...

Fitting the multitemporal curve: a fourier series approach to the missing data problem in remote sensing analysis

Treesearch

Evan Brooks; Valerie Thomas; Wynne Randolph; John Coulston

2012-01-01

With the advent of free Landsat data stretching back decades, there has been a surge of interest in utilizing remotely sensed data in multitemporal analysis for estimation of biophysical parameters. Such analysis is confounded by cloud cover and other image-specific problems, which result in missing data at various aperiodic times of the year. While there is a wealth...

On the distinguishability of HRF models in fMRI.

PubMed

Rosa, Paulo N; Figueiredo, Patricia; Silvestre, Carlos J

2015-01-01

Modeling the Hemodynamic Response Function (HRF) is a critical step in fMRI studies of brain activity, and it is often desirable to estimate HRF parameters with physiological interpretability. A biophysically informed model of the HRF can be described by a non-linear time-invariant dynamic system. However, the identification of this dynamic system may leave much uncertainty on the exact values of the parameters. Moreover, the high noise levels in the data may hinder the model estimation task. In this context, the estimation of the HRF may be seen as a problem of model falsification or invalidation, where we are interested in distinguishing among a set of eligible models of dynamic systems. Here, we propose a systematic tool to determine the distinguishability among a set of physiologically plausible HRF models. The concept of absolutely input-distinguishable systems is introduced and applied to a biophysically informed HRF model, by exploiting the structure of the underlying non-linear dynamic system. A strategy to model uncertainty in the input time-delay and magnitude is developed and its impact on the distinguishability of two physiologically plausible HRF models is assessed, in terms of the maximum noise amplitude above which it is not possible to guarantee the falsification of one model in relation to another. Finally, a methodology is proposed for the choice of the input sequence, or experimental paradigm, that maximizes the distinguishability of the HRF models under investigation. The proposed approach may be used to evaluate the performance of HRF model estimation techniques from fMRI data.

A new tower-based hyperspectral system for the estimation of CO2 fluxes and biophysical parameters in a subalpine grassland ecosystem

NASA Astrophysics Data System (ADS)

Vescovo, L.; Gianelle, D.; Marcolla, B.; Zaldei, A.; Sakowska, K.

2013-12-01

Linking optical remote sensing with carbon fluxes and biophysical parameters is critical to exploit spatial and temporal extensive information useful for validating model simulations at different scales. Proximal sensing is fundamental to quantify and understand the seasonal dynamics of ecosystems and to upscale the observations carried out at the ground level. In this study, we present the results from an ongoing research project at the FLUXNET eddy covariance site of Monte Bondone (Italy). The site is located at 1550 m a.s.l. on a mountain plateau in the Italian Alps (Viote del Monte Bondone). The area is managed as an extensively-managed meadow, cut once a year, and dominated by Nardus stricta and Festuca nigrescens. The climate of this area is sub-continental (warm and wet summer), with precipitation peaks in spring and autumn. A new hyperspectral system (WhiteRef Box, developed by Fondazione Edmund Mach in collaboration with the Institute of Biometeorology, CNR, Italy) based on the ASD FieldSpec spectrometer (spectral range 350-2500 nm, resolution ~3 nm at 700 nm) was designed to acquire continuous radiometric measurements. The system was installed on the eddy covariance tower at a height of 6 m, with a field of view of 25°. To obtain reflectance values, white panel radiance spectra and canopy radiance spectra were collected every 5 minutes between 10:00 a.m. and 1:00 p.m. (solar time) during the growing season of 2013. In addition, measurements of biophysical parameters such as above-ground biomass, fraction of Absorbed Photosynthetically Active Radiation (fAPAR), Plant Area Index, Canopy Chlorophyll Content, Canopy Water Content and Green Herbage Ratio were performed at weekly intervals within the spectrometer footprint (~5 m2). In this work, we present some preliminary results regarding the potential of spectral vegetation indices - based on VNIR and SWIR spectral bands- for capturing seasonal trends of CO2 fluxes as well as vegetation biophysical parameters dynamics. Spectral vegetation indices sensitive to chlorophyll content (such as Meris Terrestrial ChIorophyll Index, Vogelmann Indices) showed a good linear correlation with fAPAR, daily Gross Primary Production and chlorophyll content (R2> 0.8 for all the three variables). The SWIR-based Vegetation Indices (e.g. Normalised Difference Infrared Index, Moisture Stress Index) confirmed their ability to estimate Canopy Water Content. Most of the analyzed indices showed to be linearly related with Green Herbage Ratio (explaining more than 80% of variance). The Near Infrared Difference Index (Vescovo et al., 2012) confirmed his potential in predicting canopy structural parameters such as Plant Area Index and biomass (R2> 0.90).

The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter.

PubMed

Nilsson, Markus; van Westen, Danielle; Ståhlberg, Freddy; Sundgren, Pia C; Lätt, Jimmy

2013-08-01

Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.

Exact solutions of a two parameter flux model and cryobiological applications.

PubMed

Benson, James D; Chicone, Carmen C; Critser, John K

2005-06-01

Solute-solvent transmembrane flux models are used throughout biological sciences with applications in plant biology, cryobiology (transplantation and transfusion medicine), as well as circulatory and kidney physiology. Using a standard two parameter differential equation model of solute and solvent transmembrane flux described by Jacobs [The simultaneous measurement of cell permeability to water and to dissolved substances, J. Cell. Comp. Physiol. 2 (1932) 427-444], we determine the functions that describe the intracellular water volume and moles of intracellular solute for every time t and every set of initial conditions. Here, we provide several novel biophysical applications of this theory to important biological problems. These include using this result to calculate the value of cell volume excursion maxima and minima along with the time at which they occur, a novel result that is of significant relevance to the addition and removal of permeating solutes during cryopreservation. We also present a methodology that produces extremely accurate sum of squares estimates when fitting data for cellular permeability parameter values. Finally, we show that this theory allows a significant increase in both accuracy and speed of finite element methods for multicellular volume simulations, which has critical clinical biophysical applications in cryosurgical approaches to cancer treatment.

The effect of dimethylsulfoxide on the water transport response of rat hepatocytes during freezing.

PubMed

Smith, D J; Schulte, M; Bischof, J C

1998-10-01

Successful improvement of cryopreservation protocols for cells in suspension requires knowledge of how such cells respond to the biophysical stresses of freezing (intracellular ice formation, water transport) while in the presence of a cryoprotective agent (CPA). This work investigates the biophysical water transport response in a clinically important cell type--isolated hepatocytes--during freezing in the presence of dimethylsulfoxide (DMSO). Sprague-Dawley rat liver hepatocytes were frozen in Williams E media supplemented with 0, 1, and 2 M DMSO, at rates of 5, 10, and 50 degrees C/min. The water transport was measured by cell volumetric changes as assessed by cryomicroscopy and image analysis. Assuming that water is the only species transported under these conditions, a water transport model of the form dV/dT = f(Lpg([CPA]), ELp([CPA]), T(t)) was curve-fit to the experimental data to obtain the biophysical parameters of water transport--the reference hydraulic permeability (Lpg) and activation energy of water transport (ELp)--for each DMSO concentration. These parameters were estimated two ways: (1) by curve-fitting the model to the average volume of the pooled cell data, and (2) by curve-fitting individual cell volume data and averaging the resulting parameters. The experimental data showed that less dehydration occurs during freezing at a given rate in the presence of DMSO at temperatures between 0 and -10 degrees C. However, dehydration was able to continue at lower temperatures (< -10 degrees C) in the presence of DMSO. The values of Lpg and ELp obtained using the individual cell volume data both decreased from their non-CPA values--4.33 x 10(-13) m3/N-s (2.69 microns/min-atm) and 317 kJ/mol (75.9 kcal/mol), respectively--to 0.873 x 10(-13) m3/N-s (0.542 micron/min-atm) and 137 kJ/mol (32.8 kcal/mol), respectively, in 1 M DMSO and 0.715 x 10(-13) m3/N-s (0.444 micron/min-atm) and 107 kJ/mol (25.7 kcal/mol), respectively, in 2 M DMSO. The trends in the pooled volume values for Lpg and ELp were very similar, but the overall fit was considered worse than for the individual volume parameters. A unique way of presenting the curve-fitting results supports a clear trend of reduction of both biophysical parameters in the presence of DMSO, and no clear trend in cooling rate dependence of the biophysical parameters. In addition, these results suggest that close proximity of the experimental cell volume data to the equilibrium volume curve may significantly reduce the efficiency of the curve-fitting process.

From Spiking Neuron Models to Linear-Nonlinear Models

PubMed Central

Ostojic, Srdjan; Brunel, Nicolas

2011-01-01

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates. PMID:21283777

From spiking neuron models to linear-nonlinear models.

PubMed

Ostojic, Srdjan; Brunel, Nicolas

2011-01-20

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

Dynamic causal modelling: a critical review of the biophysical and statistical foundations.

PubMed

Daunizeau, J; David, O; Stephan, K E

2011-09-15

The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This requires (i) biophysically plausible and physiologically interpretable models of neuronal network dynamics that can predict distributed brain responses to experimental stimuli and (ii) efficient statistical methods for parameter estimation and model comparison. These two key components of DCM have been the focus of more than thirty methodological articles since the seminal work of Friston and colleagues published in 2003. In this paper, we provide a critical review of the current state-of-the-art of DCM. We inspect the properties of DCM in relation to the most common neuroimaging modalities (fMRI and EEG/MEG) and the specificity of inference on neural systems that can be made from these data. We then discuss both the plausibility of the underlying biophysical models and the robustness of the statistical inversion techniques. Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs. Copyright © 2009 Elsevier Inc. All rights reserved.

Reconstructed historical land cover and biophysical parameters for studies of land-atmosphere interactions within the eastern United States

USGS Publications Warehouse

Steyaert, Louis T.; Knox, R.G.

2008-01-01

Over the past 350 years, the eastern half of the United States experienced extensive land cover changes. These began with land clearing in the 1600s, continued with widespread deforestation, wetland drainage, and intensive land use by 1920, and then evolved to the present-day landscape of forest regrowth, intensive agriculture, urban expansion, and landscape fragmentation. Such changes alter biophysical properties that are key determinants of land-atmosphere interactions (water, energy, and carbon exchanges). To understand the potential implications of these land use transformations, we developed and analyzed 20-km land cover and biophysical parameter data sets for the eastern United States at 1650, 1850, 1920, and 1992 time slices. Our approach combined potential vegetation, county-level census data, soils data, resource statistics, a Landsat-derived land cover classification, and published historical information on land cover and land use. We reconstructed land use intensity maps for each time slice and characterized the land cover condition. We combined these land use data with a mutually consistent set of biophysical parameter classes, to characterize the historical diversity and distribution of land surface properties. Time series maps of land surface albedo, leaf area index, a deciduousness index, canopy height, surface roughness, and potential saturated soils in 1650, 1850, 1920, and 1992 illustrate the profound effects of land use change on biophysical properties of the land surface. Although much of the eastern forest has returned, the average biophysical parameters for recent landscapes remain markedly different from those of earlier periods. Understanding the consequences of these historical changes will require land-atmosphere interactions modeling experiments.

Modeling of the Light Speckle Field Structure Inside a Multilayer Human Skin Tissue

NASA Astrophysics Data System (ADS)

Barun, V. V.; Dik, S. K.; Ivanov, A. P.; Abramovich, N. D.

2013-11-01

We present an analytic method and the results of investigating the characteristics of the interference pattern formed by multiply scattered light in a multilayer biological tissue of the type of human skin at the wavelengths of the visible and neat IR spectral regions under laser irradiation. Calculations were performed with the use of the known solutions of the equations of radiation transfer in the biotissue and the relation between the theory of propagation of light in a scattering medium and the coherence theory. The radial structure of the light field in the depth of the human skin formed by coherent and incoherent radiation depending on its biophysical parameters has been investigated. The characteristic sizes of speckles in each layer of the skin have been estimated. The biophysical factors connected with the volume concentration of blood in the dermis and the degree of its oxygenation influencing the contrast of the speckle pattern in the dermis have been discussed. The possibility of formulating and solving inverse problems of biomedical optics on the restoration of blood parameters from measurements of speckle characteristics has been shown.

Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

NASA Astrophysics Data System (ADS)

García-Haro, Francisco Javier; Campos-Taberner, Manuel; Muñoz-Marí, Jordi; Laparra, Valero; Camacho, Fernando; Sánchez-Zapero, Jorge; Camps-Valls, Gustau

2018-05-01

This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological-Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key parameters for a wide range of land-biosphere applications. The algorithm is based on a hybrid approach that blends the generalization capabilities offered by physical radiative transfer models with the accuracy and computational efficiency of machine learning methods. One major feature is the implementation of multi-output retrieval methods able to jointly and more consistently estimate all the biophysical parameters at the same time. We propose a multi-output Gaussian process regression (GPRmulti), which outperforms other considered methods over PROSAIL (coupling of PROSPECT and SAIL (Scattering by Arbitrary Inclined Leaves) radiative transfer models) EPS simulations. The global EPS products include uncertainty estimates taking into account the uncertainty captured by the retrieval method and input errors propagation. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. The paper discusses initial validation studies and provides details about the characteristics and overall quality of the products, which can be of interest to assist the successful use of the data by a broad user's community. The consistent generation and distribution of the EPS vegetation products will constitute a valuable tool for monitoring of earth surface dynamic processes.

Comparing the Potential of the Sentinel-2 MSI and the Future EnMAP HSI for the Retrieval of Winter Wheat Crop Parameters in Southern Germany

NASA Astrophysics Data System (ADS)

Danner, Martin; Hank, Tobias; Mauser, Wolfram

2016-08-01

This study tests the effect of improved spectral resolution on different approaches for the estimation of crop biophysical variables of winter wheat in Southern Germany by comparing the existing Sentinel-2 MSI with the future EnMAP HSI. The experiment is based on simulated sensor data of both Sentinel-2 and EnMAP, with their individual spectral configurations and radiometric properties taken into account. An advanced multispectral setup, such as provided by Sentinel-2, proved to enable reasonable estimation of biophysical variables by applying machine learning algorithms. The augmented information content inherent in hyperspectral signatures, however, marks an advantage for the creation of novel narrow-band indices (RMSE improvement of 10.0%) and for the inversion of canopy reflectance models like PROSAIL independent from in-situ data (RMSE improvement of 18.7%). With the notable advantages of Sentinel-2 - higher revisit rates and better spectral resolution - new synergies are expected to arise, once both instruments will be operating in parallel configuration.

An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India.

PubMed

Deb, Dibyendu; Singh, J P; Deb, Shovik; Datta, Debajit; Ghosh, Arunava; Chaurasia, R S

2017-10-20

Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, carbon stock and other biophysical parameters of that forest. With advancement of geospatial technology in last few decades, AGB estimation now can be done using space-borne and airborne remotely sensed data. It is a well-established, time saving and cost effective technique with high precision and is frequently applied by the scientific community. It involves development of allometric equations based on correlations of ground-based forest biomass measurements with vegetation indices derived from remotely sensed data. However, selection of the best-fit and explanatory models of biomass estimation often becomes a difficult proposition with respect to the image data resolution (spatial and spectral) as well as the sensor platform position in space. Using Resourcesat-2 satellite data and Normalized Difference Vegetation Index (NDVI), this pilot scale study compared traditional linear and nonlinear models with an artificial intelligence-based non-parametric technique, i.e. artificial neural network (ANN) for formulation of the best-fit model to determine AGB of forest of the Bundelkhand region of India. The results confirmed the superiority of ANN over other models in terms of several statistical significance and reliability assessment measures. Accordingly, this study proposed the use of ANN instead of traditional models for determination of AGB and other bio-physical parameters of any dry deciduous forest of tropical sub-humid or semi-arid area. In addition, large numbers of sampling sites with different quadrant sizes for trees, shrubs, and herbs as well as application of LiDAR data as predictor variable were recommended for very high precision modelling in ANN for a large scale study.

Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models

USDA-ARS?s Scientific Manuscript database

Remote sensing technology can rapidly provide spatial information on crop growth status, which ideally could be used to invert radiative transfer models or ecophysiological models for estimating a variety of crop biophysical properties. However, the outcome of the model inversion procedure will be ...

Biophysical model of ion transport across human respiratory epithelia allows quantification of ion permeabilities.

PubMed

Garcia, Guilherme J M; Boucher, Richard C; Elston, Timothy C

2013-02-05

Lung health and normal mucus clearance depend on adequate hydration of airway surfaces. Because transepithelial osmotic gradients drive water flows, sufficient hydration of the airway surface liquid depends on a balance between ion secretion and absorption by respiratory epithelia. In vitro experiments using cultures of primary human nasal epithelia and human bronchial epithelia have established many of the biophysical processes involved in airway surface liquid homeostasis. Most experimental studies, however, have focused on the apical membrane, despite the fact that ion transport across respiratory epithelia involves both cellular and paracellular pathways. In fact, the ion permeabilities of the basolateral membrane and paracellular pathway remain largely unknown. Here we use a biophysical model for water and ion transport to quantify ion permeabilities of all pathways (apical, basolateral, paracellular) in human nasal epithelia cultures using experimental (Ussing Chamber and microelectrode) data reported in the literature. We derive analytical formulas for the steady-state short-circuit current and membrane potential, which are for polarized epithelia the equivalent of the Goldman-Hodgkin-Katz equation for single isolated cells. These relations allow parameter estimation to be performed efficiently. By providing a method to quantify all the ion permeabilities of respiratory epithelia, the model may aid us in understanding the physiology that regulates normal airway surface hydration. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Vegetation species composition and canopy architecture information expressed in leaf water absorption measured in the 1000 nm and 2200 spectral region by an imaging spectrometer

NASA Technical Reports Server (NTRS)

Green, Robert O.; Roberts, Dar A.

1995-01-01

Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring, and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local to regional and even synoptic scales. Classical approaches rely on vegetation indices such as the normalized difference vegetation index (NDVI) to estimate biophysical parameters such as leaf area index or intercepted photosynthetically active radiation (IPAR). Another approach is to apply a variety of classification schemes to map vegetation and thus extrapolate fine-scale information about specific sites to larger areas of similar composition. Imaging spectrometry provides additional information that is not obtainable through broad-band sensors and that may provide improved inputs both to direct biophysical estimates as well as classification schemes. Some of this capability has been demonstrated through improved discrimination of vegetation, estimates of canopy biochemistry, and liquid water estimates from vegetation. We investigate further the potential of leaf water absorption estimated from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data as a means for discriminating vegetation types and deriving canopy architectural information. We expand our analysis to incorporate liquid water estimates from two spectral regions, the 1000-nm region and the 2200-nm region. The study was conducted in the vicinity of Jasper Ridge, California, which is located on the San Francisco peninsula to the west of the Stanford University campus. AVIRIS data were acquired over Jasper Ridge, CA, on June 2, 1992, at 19:31 UTC. Spectra from three sites in this image were analyzed. These data are from an area of healthy grass, oak woodland, and redwood forest, respectively. For these analyses, the AVIRIS-measured upwelling radiance spectra for the entire Jasper Ridge scene were transformed to apparent surface reflectance using a radiative transfer code-based inversion algorithm.

Validation of Global EO Biophysical Products at JECAM Test Site in Ukraine

NASA Astrophysics Data System (ADS)

Skakun, Sergii; Kussul, Nataliia; Kravchenko, Oleksiy; Basarab, Ruslan; Ostapenko, Vadym; Yailymov, Bohdan; Shelestov, Andrii; Kolotii, Andrii; Mironov, Andrii

Efficient global agriculture monitoring requires appropriate validation of Earth observation (EO) products for different regions and cropping system. This problem is addressed within the Joint Experiment of Crop Assessment and Monitoring (JECAM) initiative which aims to develop monitoring and reporting protocols and best practices for a variety of global agricultural systems. Ukraine is actively involved into JECAM, and a JECAM Ukraine test site was officially established in 2011. The following problems are being solved within JECAM Ukraine: (i) crop identification and crop area estimation [1]; (ii) crop yield forecasting [2]; (iii) EO products validation. The following case study regions were selected for these purposes: (i) the whole Kyiv oblast (28,000 sq. km) indented for crop mapping and acreage estimation; (ii) intensive observation sub-site in Pshenichne which is a research farm from the National University of Life and Environmental Sciences of Ukraine and indented for crop biophysical parameters estimation; (iii) Lviv region for rape-seed identification and crop rotation control; (iv) Crimea region for crop damage assessment due to droughts, and illegial field detection. In 2013, Ukrainian JECAM test site was selected as one of the “Champion User” for the ESA Sentinel-2 for Agriculture project. The test site was observed with SPOT-4 and RapidEye satellites every 5 days. The collected images are then used to simulate Sentinel-2 images for agriculture purposes. JECAM Ukraine is responsible for collecting ground observation data for validation purposes, and is involved in providing user requirements for Sentinel-2 agriculture related products. In particular, three field campaigns to characterize the vegetation biophysical parameters at the Pshenichne test site were carried out: First campaign - 14th to 17th of May 2013; second campaign - 12th to 15th of June 2013; third campaign - 14th to 17th of July 2013. Digital Hemispheric Photographs (DHP) images were acquired with a NIKON D70 camera. The images acquired during the field campaign are processed with the CAN-EYE software to derive LAI, FAPAR and FCOVER. The in situ biophysical values were used for producing LAI, FCOVER and FAPAR maps from optical satellite images, and provide cross-validation, and validation of global remote sensing products. The following satellite data were used: SPOT-4, RapidEye and Landsat-8. Inter-comparison of the derived products is performed. The paper presents an insight on the general methodology used within JECAM test site, the results achieved so far and challenges, and future planned activities. 1. Gallego, F.J., Kussul, N., Skakun, S., Kravchenko, O., Shelestov, A., Kussul, O. “Efficiency assessment of using satellite data for crop area estimation in Ukraine,” International Journal of Applied Earth Observation and Geoinformation, vol. 29, pp. 22-30, 2014. 2. Kogan, F., Kussul, N., Adamenko, T., Skakun, S., Kravchenko, O., Kryvobok, O., Shelestov, A., Kolotii, A., Kussul, O., Lavrenyuk, A., “Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models,” International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013.

Biophysics of NASA radiation quality factors.

PubMed

Cucinotta, Francis A

2015-09-01

NASA has implemented new radiation quality factors (QFs) for projecting cancer risks from space radiation exposures to astronauts. The NASA QFs are based on particle track structure concepts with parameters derived from available radiobiology data, and NASA introduces distinct QFs for solid cancer and leukaemia risk estimates. The NASA model was reviewed by the US National Research Council and approved for use by NASA for risk assessment for International Space Station missions and trade studies of future exploration missions to Mars and other destinations. A key feature of the NASA QFs is to represent the uncertainty in the QF assessments and evaluate the importance of the QF uncertainty to overall uncertainties in cancer risk projections. In this article, the biophysical basis for the probability distribution functions representing QF uncertainties was reviewed, and approaches needed to reduce uncertainties were discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Functional stability of cerebral circulatory system

NASA Technical Reports Server (NTRS)

Moskalenko, Y. Y.

1980-01-01

The functional stability of the cerebral circulation system seems to be based on the active mechanisms and on those stemming from specific of the biophysical structure of the system under study. This latter parameter has some relevant criteria for its quantitative estimation. The data obtained suggest that the essential part of the mechanism for active responses of cerebral vessels which maintains the functional stability of this portion of the vascular system, consists of a neurogenic component involving central nervous structures localized, for instance, in the medulla oblongata.

Follow-on proposal identifying environmental features for land management decisions

NASA Technical Reports Server (NTRS)

Wright, P. M.; Ridd, M. K.

1986-01-01

Urban morphology (an examination of spatial fabric and structure), natural ecosystem (investigations emphasizing biophysical processes and patterns), and human ecosystem (emphasizing socio-economic and engineering parameters) were studied. The most critical variable, transpiration, in the ASPCON model, created by Jaynes (1978), describing the hydrology of aspen to conifer succession was studied to improve the accuracy. Transpiration is determined by a canopy transpiration model which estimates consumptive water use (CWU) for specific species and a plant activity index. Also studied was Pinyon-Juniper woodland erosion.

Method of determining forest production from remotely sensed forest parameters

DOEpatents

Corey, J.C.; Mackey, H.E. Jr.

1987-08-31

A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.

Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices

USGS Publications Warehouse

Ji, Lei; Zhang, Li; Rover, Jennifer R.; Wylie, Bruce K.; Chen, Xuexia

2014-01-01

In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.

Improving land surface parameter retrieval by integrating plant traits priors in the MULTIPLY data assimilation platform

NASA Astrophysics Data System (ADS)

Corbin, A. E.; Timmermans, J.; Hauser, L.; Bodegom, P. V.; Soudzilovskaia, N. A.

2017-12-01

There is a growing demand for accurate land surface parameterization from remote sensing (RS) observations. This demand has not been satisfied, because most estimation schemes apply 1) a single-sensor single-scale approach, and 2) require specific key-variables to be `guessed'. This is because of the relevant observational information required to accurately retrieve parameters of interest. Consequently, many schemes assume specific variables to be constant or not present; subsequently leading to more uncertainty. In this aspect, the MULTIscale SENTINEL land surface information retrieval Platform (MULTIPLY) was created. MULTIPLY couples a variety of RS sources with Radiative Transfer Models (RTM) over varying spectral ranges using data-assimilation to estimate geophysical parameters. In addition, MULTIPLY also uses prior information about the land surface to constrain the retrieval problem. This research aims to improve the retrieval of plant biophysical parameters through the use of priors of biophysical parameters/plant traits. Of particular interest are traits (physical, morphological or chemical trait) affecting individual performance and fitness of species. Plant traits that are able to be retrieved via RS and with RTMs include traits such as leaf-pigments, leaf water, LAI, phenols, C/N, etc. In-situ data for plant traits that are retrievable via RS techniques were collected for a meta-analysis from databases such as TRY, Ecosis, and individual collaborators. Of particular interest are the following traits: chlorophyll, carotenoids, anthocyanins, phenols, leaf water, and LAI. ANOVA statistics were generated for each traits according to species, plant functional groups (such as evergreens, grasses, etc.), and the trait itself. Afterwards, traits were also compared using covariance matrices. Using these as priors, MULTIPLY was is used to retrieve several plant traits in two validation sites in the Netherlands (Speulderbos) and in Finland (Sodankylä). Initial comparisons show significant improved results over non-a priori based retrievals.

Hydrological Relevant Parameters from Remote Sensing - Spatial Modelling Input and Validation Basis

NASA Astrophysics Data System (ADS)

Hochschild, V.

2012-12-01

This keynote paper will demonstrate how multisensoral remote sensing data is used as spatial input for mesoscale hydrological modeling as well as for sophisticated validation purposes. The tasks of Water Resources Management are subject as well as the role of remote sensing in regional catchment modeling. Parameters derived from remote sensing discussed in this presentation will be land cover, topographical information from digital elevation models, biophysical vegetation parameters, surface soil moisture, evapotranspiration estimations, lake level measurements, determination of snow covered area, lake ice cycles, soil erosion type, mass wasting monitoring, sealed area, flash flood estimation. The actual possibilities of recent satellite and airborne systems are discussed, as well as the data integration into GIS and hydrological modeling, scaling issues and quality assessment will be mentioned. The presentation will provide an overview of own research examples from Germany, Tibet and Africa (Ethiopia, South Africa) as well as other international research activities. Finally the paper gives an outlook on upcoming sensors and concludes the possibilities of remote sensing in hydrology.

Neurite density from magnetic resonance diffusion measurements at ultrahigh field: Comparison with light microscopy and electron microscopy

PubMed Central

Jespersen, Sune N.; Bjarkam, Carsten R.; Nyengaard, Jens R.; Chakravarty, M. Mallar; Hansen, Brian; Vosegaard, Thomas; Østergaard, Leif; Yablonskiy, Dmitriy; Nielsen, Niels Chr.; Vestergaard-Poulsen, Peter

2010-01-01

Due to its unique sensitivity to tissue microstructure, diffusion-weighted magnetic resonance imaging (MRI) has found many applications in clinical and fundamental science. With few exceptions, a more precise correspondence between physiological or biophysical properties and the obtained diffusion parameters remain uncertain due to lack of specificity. In this work, we address this problem by comparing diffusion parameters of a recently introduced model for water diffusion in brain matter to light microscopy and quantitative electron microscopy. Specifically, we compare diffusion model predictions of neurite density in rats to optical myelin staining intensity and stereological estimation of neurite volume fraction using electron microscopy. We find that the diffusion model describes data better and that its parameters show stronger correlation with optical and electron microscopy, and thus reflect myelinated neurite density better than the more frequently used diffusion tensor imaging (DTI) and cumulant expansion methods. Furthermore, the estimated neurite orientations capture dendritic architecture more faithfully than DTI diffusion ellipsoids. PMID:19732836

A method for operative quantitative interpretation of multispectral images of biological tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2013-10-01

A method for operative retrieval of spatial distributions of biophysical parameters of a biological tissue by using a multispectral image of it has been developed. The method is based on multiple regressions between linearly independent components of the diffuse reflection spectrum of the tissue and unknown parameters. Possibilities of the method are illustrated by an example of determining biophysical parameters of the skin (concentrations of melanin, hemoglobin and bilirubin, blood oxygenation, and scattering coefficient of the tissue). Examples of quantitative interpretation of the experimental data are presented.

Model- based filtering for artifact and noise suppression with state estimation for electrodermal activity measurements in real time.

PubMed

Tronstad, Christian; Staal, Odd M; Saelid, Steinar; Martinsen, Orjan G

2015-08-01

Measurement of electrodermal activity (EDA) has recently made a transition from the laboratory into daily life with the emergence of wearable devices. Movement and nongelled electrodes make these devices more susceptible to noise and artifacts. In addition, real-time interpretation of the measurement is needed for user feedback. The Kalman filter approach may conveniently deal with both these issues. This paper presents a biophysical model for EDA implemented in an extended Kalman filter. Employing the filter on data from Physionet along with simulated noise and artifacts demonstrates noise and artifact suppression while implicitly providing estimates of model states and parameters such as the sudomotor nerve activation.

Biophysical and spectral modeling for crop identification and assessment

NASA Technical Reports Server (NTRS)

Goel, N. S. (Principal Investigator)

1984-01-01

The development of a technique for estimating all canopy parameters occurring in a canopy reflectance model from the measured canopy reflectance data is summarized. The Suits and the SAIL model for a uniform and homogeneous crop canopy were used to determine if the leaf area index and the leaf angle distribution could be estimated. Optimal solar/view angles for measuring CR were also investigated. The use of CR in many wavelengths or spectral bands and of linear and nonlinear transforms of CRs for various solar/view angles and various spectral bands is discussed as well as the inversion of rediance data inside the canopy, angle transforms for filtering out terrain slope effects, and modification of one dimensional models.

Contactless diagnostics of biophysical parameters of skin and blood on the basis of approximating functions for radiation fluxes scattered by skin

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2014-03-01

Approximating expressions are derived to calculate spectral and spatial characteristics of diffuse reflection of light from a two-layer medium mimicking human skin. The effectiveness of the use of these expressions in the optical diagnosis of skin biophysical parameters (tissue scattering parameters, concentration of melanin in the epidermis, concentration of total haemoglobin and bilirubin in the tissues of the dermis) and content of haemoglobin derivatives in blood (oxy-, deoxy-, met-, carboxy- and sulfhaemoglobin) is analysed numerically. The methods are proposed to determine in realtime these parameters without contact of the measuring instrument with the patient's body.

Classification of high-resolution multi-swath hyperspectral data using Landsat 8 surface reflectance data as a calibration target and a novel histogram based unsupervised classification technique to determine natural classes from biophysically relevant fit parameters

NASA Astrophysics Data System (ADS)

McCann, C.; Repasky, K. S.; Morin, M.; Lawrence, R. L.; Powell, S. L.

2016-12-01

Compact, cost-effective, flight-based hyperspectral imaging systems can provide scientifically relevant data over large areas for a variety of applications such as ecosystem studies, precision agriculture, and land management. To fully realize this capability, unsupervised classification techniques based on radiometrically-calibrated data that cluster based on biophysical similarity rather than simply spectral similarity are needed. An automated technique to produce high-resolution, large-area, radiometrically-calibrated hyperspectral data sets based on the Landsat surface reflectance data product as a calibration target was developed and applied to three subsequent years of data covering approximately 1850 hectares. The radiometrically-calibrated data allows inter-comparison of the temporal series. Advantages of the radiometric calibration technique include the need for minimal site access, no ancillary instrumentation, and automated processing. Fitting the reflectance spectra of each pixel using a set of biophysically relevant basis functions reduces the data from 80 spectral bands to 9 parameters providing noise reduction and data compression. Examination of histograms of these parameters allows for determination of natural splitting into biophysical similar clusters. This method creates clusters that are similar in terms of biophysical parameters, not simply spectral proximity. Furthermore, this method can be applied to other data sets, such as urban scenes, by developing other physically meaningful basis functions. The ability to use hyperspectral imaging for a variety of important applications requires the development of data processing techniques that can be automated. The radiometric-calibration combined with the histogram based unsupervised classification technique presented here provide one potential avenue for managing big-data associated with hyperspectral imaging.

Biophysical Model of Ion Transport across Human Respiratory Epithelia Allows Quantification of Ion Permeabilities

PubMed Central

Garcia, Guilherme J.M.; Boucher, Richard C.; Elston, Timothy C.

2013-01-01

Lung health and normal mucus clearance depend on adequate hydration of airway surfaces. Because transepithelial osmotic gradients drive water flows, sufficient hydration of the airway surface liquid depends on a balance between ion secretion and absorption by respiratory epithelia. In vitro experiments using cultures of primary human nasal epithelia and human bronchial epithelia have established many of the biophysical processes involved in airway surface liquid homeostasis. Most experimental studies, however, have focused on the apical membrane, despite the fact that ion transport across respiratory epithelia involves both cellular and paracellular pathways. In fact, the ion permeabilities of the basolateral membrane and paracellular pathway remain largely unknown. Here we use a biophysical model for water and ion transport to quantify ion permeabilities of all pathways (apical, basolateral, paracellular) in human nasal epithelia cultures using experimental (Ussing Chamber and microelectrode) data reported in the literature. We derive analytical formulas for the steady-state short-circuit current and membrane potential, which are for polarized epithelia the equivalent of the Goldman-Hodgkin-Katz equation for single isolated cells. These relations allow parameter estimation to be performed efficiently. By providing a method to quantify all the ion permeabilities of respiratory epithelia, the model may aid us in understanding the physiology that regulates normal airway surface hydration. PMID:23442922

Semi-empirical modelling for forest above ground biomass estimation using hybrid and fully PolSAR data

NASA Astrophysics Data System (ADS)

Tomar, Kiledar S.; Kumar, Shashi; Tolpekin, Valentyn A.; Joshi, Sushil K.

2016-05-01

Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m-alpha and Yamaguchi decomposition modelling were extracted. The R2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha-1) and 73.424 (t ha-1) respectively. On the basis of RMSE and R2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering element for AGB estimation from forest.

Comparison of biophysical factors influencing on emphysema quantification with low-dose CT

NASA Astrophysics Data System (ADS)

Heo, Chang Yong; Kim, Jong Hyo

2014-03-01

Emphysema Index(EI) measurements in MDCT is known to be influenced by various biophysical factors such as total lung volume, and body size. We investigated the association of the four biophysical factors with emphysema index in low-dose MDCT. In particular, we attempted to identify a potentially stronger biophysical factor than total lung volume. A total of 400 low-dose MDCT volumes taken at 120kVp, 40mAs, 1mm thickness, and B30f reconstruction kernel were used. The lungs, airways, and pulmonary vessels were automatically segmented, and two Emphysema Indices, relative area below -950HU(RA950) and 15th percentile(Perc15), were extracted from the segmented lungs. The biophysical factors such as total lung volume(TLV), mode of lung attenuation(ModLA), effective body diameter(EBD), and the water equivalent body diameter(WBD) were estimated from the segmented lung and body area. The association of biophysical factors with emphysema indices were evaluated by correlation coefficients. The mean emphysema indices were 8.3±5.5(%) in RA950, and -930±18(HU) in Perc15. The estimates of biophysical factors were 4.7±1.0(L) in TLV, -901±21(HU) in ModLA, 26.9±2.2(cm) in EBD, and 25.9±2.6(cm) in WBD. The correlation coefficients of biophysical factors with RA950 were 0.73 in TLV, 0.94 in ModLA, 0.31 in EBD, and 0.18 WBD, the ones with Perc15 were 0.74 in TLV, 0.98 in ModLA, 0.29 in EBD, and 0.15 WBD. Study results revealed that two biophysical factors, TLV and ModLA, mostly affects the emphysema indices. In particular, the ModLA exhibited strongest correlation of 0.98 with Perc15, which indicating the ModLA is the most significant confounding biophysical factor in emphysema indices measurement.

Cellular biophysical markers of hydroxyurea treatment in sickle cell disease

NASA Astrophysics Data System (ADS)

So, Peter T. C.; Hosseini, Poorya; Abidi, Sabia Z.; Du, E.; Papageorgiou, Dimitrios P.; Park, YongKeun; Higgins, John; Kato, Gregory J.; Suresh, Subra; Dao, Ming; Yaqoob, Zahid

2017-04-01

Using a common-path interferometric technique, we measure biomechanical and morphological properties of individual red blood cells in SCD patients as a function of cell density, and investigate the correlation of these biophysical properties with drug intake as well as other clinically measured parameters.

Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.

PubMed

Yu, T; Sejnowski, T J; Cauwenberghs, G

2011-10-01

We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.

Hyperspectral measurements for estimating biophysical parameters and CO2 exchanges in a rice field

NASA Astrophysics Data System (ADS)

Rossini, M.; Migliavacca, M.; Meroni, M.; Manca, G.; Cogliati, S.; Busetto, L.; Picchi, V.; Galvagno, M.; Colombo, R.; Seufert, G.

2009-04-01

The objective of this work was to monitor the main biophysical and structural parameters as well as the CO2 exchanges between atmosphere and a terrestrial ecosystem from remote and high spectral resolution spectroradiometric measurements. Estimation of photosynthetic rate or gross primary productivity from remotely sensed data is based on the light use efficiency model (LUE), which states that carbon exchange is a function of the photosynthetically active radiation absorbed by vegetation (APAR) and the radiation use efficiency (ɛ) which represents the conversion efficiency of energy to fixed carbon. Hyperspectral data were used in this study in order to derived both the APAR of green vegetation and the ɛ term. The experimental site was a rice paddy field in North Italy equipped with an Eddy Covariance (EC) flux measurement tower (Castellaro IES-JRC site). Intensive field campaigns were conducted during summer 2007 and 2008. In each sampling day, canopy optical properties, canopy structure, biophysical and ecophysiological parameters were measured. EC fluxes were calculated with a time step of 30 minutes according to EUROFLUX methodology. Measured half-hourly net ecosystem exchange (NEE) was partitioned to derive half hourly gross ecosystem production (GEP). Canopy reflectance spectra were collected under clear sky conditions using two portable spectrometers (HR4000, OceanOptics, USA) characterised by different spectral resolutions. A spectrometer characterised by a Full Width at Half Maximum (FWHM) of 0.13 nm was used to estimate steady-state fluorescence (F) and a second one with a FWHM of 2.8 nm was used for the computation of traditional vegetation indices (e.g. NVDI, Normalized Difference Vegetation Index and SAVI, Soil Adjusted Vegetation Index) and PRI (Photochemical Reflectance Index, Gamon et al. 1992). F was estimated by exploiting a variation of the Fraunhofer Line Depth (FLD) principle (Plascyk 1975): the spectral fitting method described in Meroni and Colombo (2006) applied at the 760 nm atmospheric oxygen absorption band. An index of F efficiency, the apparent fluorescence yield (NF760) was also computed as the ratio between F760 and the incident radiation. Results show that Leaf Area Index (LAI), the fraction of absorbed photosynthetically active radiation (fAPAR) and plant height values were well correlated with SAVI (R2 from 0.68 to 0.83) while NDVI was poorly or not correlated. The NDVI-fAPAR relationship, as well as the relationships NDVI-LAI and NDVI-plant height, is very different in the vegetative and ripening stages. The lower correlation with NDVI in this analysis could be explained by the dependence of the relationship on phenology. In contrast, other indices adjusting for background effects (like SAVI) showed highly linear relationships with fAPAR, LAI and plant height for the entire growing period. Furthermore, the use of innovative spectral indices related to physiological processes such as the activation of photoprotective mechanisms and excess energy dissipation via sun-induced passive fluorescence allowed the development of semi-empirical models between radiometric measurements and GEP. The average of half-hourly GEP acquired between 11 a.m. and 1 p.m. (solar time) was related with hyperspectral indices and fluorescence parameters acquired at the same time with the spectrometers. Different LUE models were tested. SAVI was selected to estimate fAPAR because it showed higher correlation than NDVI. Results showed very high coefficient of determination (i.e. R2from 0.88 to 0.98) between GEP and F760 and the product (NF760 x PARi x SAVI) for both years. The regression between GEP and the product (PRI x PARi x SAVI) was instead not significant. The semi-empirical models show high correlation between GEP and chlorophyll fluorescence parameters throughout the two years study period. This result opens up new possibilities for the application of semi-empirical model for the spatial estimation of biophysical parameters and carbon GEP based on aerial and satellite images. References Gamon J.A., Penuelas J., Field C.B. 1992. A Narrow-Waveband Spectral Index That Tracks Diurnal Changes in Photosynthetic Efficiency. Remote Sensing of Environment, 41:35-44. Meroni M., Colombo R. 2006. Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer. Remote Sensing of Environment, 103:438-448. Plascyk J.A. 1975. The MK II Fraunhofer line discriminator (FLD-II) for airborne and orbital remote sensing of solar-stimulated luminescence. Optical Engineering, 14:339-346.

BIOPHYSICAL PARAMETERS DURING RADIOFREQUENCY CATHETER ABLATION OF SCAR-MEDIATED VENTRICULAR TACHYCARDIA: EPICARDIAL AND ENDOCARDIAL APPLICATIONS VIA MANUAL AND MAGNETIC NAVIGATION

PubMed Central

Bourke, Tara; Buch, Eric; Mathuria, Nilesh; Michowitz, Yoav; Yu, Ricky; Mandapati, Ravi; Shivkumar, Kalyanam; Tung, Roderick

2014-01-01

Background There is a paucity of data on biophysical parameters during radiofrequency ablation of scar-mediated ventricular tachycardia (VT). Methods and Results Data was collected from consecutive patients undergoing VT ablation with open-irrigation. Complete data was available for 372 lesions in 21 patients. The frequency of biophysical parameter changes were: >10Ω reduction (80%), bipolar EGM reduction (69%), while loss of capture was uncommon (32%). Unipolar injury current was seen in 72% of radiofrequency applications. Both EGM reduction and impedance drop were seen in 57% and a change in all 3 parameters was seen in only 20% of lesions. Late potentials were eliminated in 33%, reduced/modified in 56%, and remained after ablation in 11%. Epicardial lesions exhibited an impedance drop (90% vs 76%, p=0.002) and loss of capture (46% vs 27%, p<0.001) more frequently than endocardial lesions. Lesions delivered manually exhibited a >10Ω impedance drop (83% vs 71%, p=0.02) and an EGM reduction (71% vs 40%, p< 0.001) more frequently than lesions applied using magnetic navigation, although loss of capture, elimination of LPs, and a change in all 3 parameters were similarly observed. Conclusions VT ablation is inefficient as the majority of radiofrequency lesions do not achieve more than one targeted biophysical parameter. Only one-third of RF applications targeted at LPs result in complete elimination. Epicardial ablation within scar may be more effective than endocardial lesions and lesions applied manually may be more effective than lesions applied using magnetic navigation. New technologies directed at identifying and optimizing ablation effectiveness in scar are clinically warranted. PMID:24946895

Biophysical parameters during radiofrequency catheter ablation of scar-mediated ventricular tachycardia: epicardial and endocardial applications via manual and magnetic navigation.

PubMed

Bourke, Tara; Buch, Eric; Mathuria, Nilesh; Michowitz, Yoav; Yu, Ricky; Mandapati, Ravi; Shivkumar, Kalyanam; Tung, Roderick

2014-11-01

There is a paucity of data on biophysical parameters during radiofrequency ablation of scar-mediated ventricular tachycardia (VT). Data were collected from consecutive patients undergoing VT ablation with open-irrigation. Complete data were available for 372 lesions in 21 patients. The frequency of biophysical parameter changes were: >10Ω reduction (80%), bipolar EGM reduction (69%), while loss of capture was uncommon (32%). Unipolar injury current was seen in 72% of radiofrequency applications. Both EGM reduction and impedance drop were seen in 57% and a change in all 3 parameters was seen in only 20% of lesions. Late potentials were eliminated in 33%, reduced/modified in 56%, and remained after ablation in 11%. Epicardial lesions exhibited an impedance drop (90% vs. 76%, P = 0.002) and loss of capture (46% vs. 27%, P < 0.001) more frequently than endocardial lesions. Lesions delivered manually exhibited a >10Ω impedance drop (83% vs. 71%, P = 0.02) and an EGM reduction (71% vs. 40%, P < 0.001) more frequently than lesions applied using magnetic navigation, although loss of capture, elimination of LPs, and a change in all 3 parameters were similarly observed. VT ablation is inefficient as the majority of radiofrequency lesions do not achieve more than one targeted biophysical parameter. Only one-third of RF applications targeted at LPs result in complete elimination. Epicardial ablation within scar may be more effective than endocardial lesions, and lesions applied manually may be more effective than lesions applied using magnetic navigation. New technologies directed at identifying and optimizing ablation effectiveness in scar are clinically warranted. © 2014 Wiley Periodicals, Inc.

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations

PubMed Central

Simon, Aaron B.; Dubowitz, David J.; Blockley, Nicholas P.; Buxton, Richard B.

2016-01-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2′ as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2′, we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2′-based estimate of the metabolic response to CO2 of 1.4%, and R2′- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2′-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. PMID:26790354

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations.

PubMed

Simon, Aaron B; Dubowitz, David J; Blockley, Nicholas P; Buxton, Richard B

2016-04-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2' as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2', we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2'-based estimate of the metabolic response to CO2 of 1.4%, and R2'- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2'-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. Copyright © 2016 Elsevier Inc. All rights reserved.

Farmland Drought Evaluation Based on the Assimilation of Multi-Temporal Multi-Source Remote Sensing Data into AquaCrop Model

NASA Astrophysics Data System (ADS)

Yang, Guijun; Yang, Hao; Jin, Xiuliang; Pignatti, Stefano; Casa, Faffaele; Silverstro, Paolo Cosmo

2016-08-01

Drought is the most costly natural disasters in China and all over the world. It is very important to evaluate the drought-induced crop yield losses and further improve water use efficiency at regional scale. Firstly, crop biomass was estimated by the combined use of Synthetic Aperture Radar (SAR) and optical remote sensing data. Then the estimated biophysical variable was assimilated into crop growth model (FAO AquaCrop) by the Particle Swarm Optimization (PSO) method from farmland scale to regional scale.At farmland scale, the most important crop parameters of AquaCrop model were determined to reduce the used parameters in assimilation procedure. The Extended Fourier Amplitude Sensitivity Test (EFAST) method was used for assessing the contribution of different crop parameters to model output. Moreover, the AquaCrop model was calibrated using the experiment data in Xiaotangshan, Beijing.At regional scale, spatial application of our methods were carried out and validated in the rural area of Yangling, Shaanxi Province, in 2014. This study will provide guideline to make irrigation decision of balancing of water consumption and yield loss.

Estimation of biophysical properties of upland Sitka spruce (Picea sitchensis) plantations

NASA Technical Reports Server (NTRS)

Green, Robert M.

1993-01-01

It is widely accepted that estimates of forest above-ground biomass are required as inputs to forest ecosystem models, and that SAR data have the potential to provide such information. This study describes relationships between polarimetric radar backscatter and key biophysical properties of a coniferous plantation in upland central Wales, U.K. Over the test site, topography was relatively complex and was expected to influence the amount of radar backscatter.

Biophysical mechanism of spike threshold dependence on the rate of rise of the membrane potential by sodium channel inactivation or subthreshold axonal potassium current

PubMed Central

Wester, Jason C.

2013-01-01

Spike threshold filters incoming inputs and thus gates activity flow through neuronal networks. Threshold is variable, and in many types of neurons there is a relationship between the threshold voltage and the rate of rise of the membrane potential (dVm/dt) leading to the spike. In primary sensory cortex this relationship enhances the sensitivity of neurons to a particular stimulus feature. While Na+ channel inactivation may contribute to this relationship, recent evidence indicates that K+ currents located in the spike initiation zone are crucial. Here we used a simple Hodgkin-Huxley biophysical model to systematically investigate the role of K+ and Na+ current parameters (activation voltages and kinetics) in regulating spike threshold as a function of dVm/dt. Threshold was determined empirically and not estimated from the shape of the Vm prior to a spike. This allowed us to investigate intrinsic currents and values of gating variables at the precise voltage threshold. We found that Na+ inactivation is sufficient to produce the relationship provided it occurs at hyperpolarized voltages combined with slow kinetics. Alternatively, hyperpolarization of the K+ current activation voltage, even in the absence of Na+ inactivation, is also sufficient to produce the relationship. This hyperpolarized shift of K+ activation allows an outward current prior to spike initiation to antagonize the Na+ inward current such that it becomes self-sustaining at a more depolarized voltage. Our simulations demonstrate parameter constraints on Na+ inactivation and the biophysical mechanism by which an outward current regulates spike threshold as a function of dVm/dt. PMID:23344915

Numerical investigation of oxygen transport by hemoglobin-based carriers through microvessels.

PubMed

Hyakutake, Toru; Kishimoto, Takumi

2017-12-01

The small size of hemoglobin-based oxygen carriers (HBOCs) may expand the realm of new treatment possibilities for various circulatory diseases. The parametric evaluation of HBOC performance for oxygen transport within tissue is essential for effectively characterizing its performance for each circulatory disease assessed. Thus, the overarching objective of this present study was to numerically investigate the reaction-diffusion phenomenon of oxygenated HBOCs and oxygen on tissues through microvessels. We considered dissociation rate coefficients, oxygen affinity, and diffusion coefficients due to Brownian motion as the biophysical parameters for estimating HBOC performance for oxygen transport. A two-dimensional computational domain, including vessel and tissue regions, was, therefore, accordingly assumed. It was observed that HBOC flows in a microvessel with a diameter of 25 μm and a length of 1 mm, and that the dissociated oxygen diffuses to the tissue region. The results indicated that oxyhemoglobin saturation and partial oxygen tension in a downstream region changed according to each biophysical parameter of HBOC. Moreover, the change in oxygen consumption rate in the tissue region had considerable influence on the oxyhemoglobin saturation level within the vessel. Comparison between simulation results and existing in vitro experimental data of actual HBOCs and RBC showed qualitatively good agreement. These results provide important information for the effective design of robust HBOCs in future.

Biophysical effects on temperature and precipitation due to land cover change

NASA Astrophysics Data System (ADS)

Perugini, Lucia; Caporaso, Luca; Marconi, Sergio; Cescatti, Alessandro; Quesada, Benjamin; de Noblet-Ducoudré, Nathalie; House, Johanna I.; Arneth, Almut

2017-05-01

Anthropogenic land cover changes (LCC) affect regional and global climate through biophysical variations of the surface energy budget mediated by albedo, evapotranspiration, and roughness. This change in surface energy budget may exacerbate or counteract biogeochemical greenhouse gas effects of LCC, with a large body of emerging assessments being produced, sometimes apparently contradictory. We reviewed the existing scientific literature with the objective to provide an overview of the state-of-the-knowledge of the biophysical LCC climate effects, in support of the assessment of mitigation/adaptation land policies. Out of the published studies that were analyzed, 28 papers fulfilled the eligibility criteria, providing surface air temperature and/or precipitation change with respect to LCC regionally and/or globally. We provide a synthesis of the signal, magnitude and uncertainty of temperature and precipitation changes in response to LCC biophysical effects by climate region (boreal/temperate/tropical) and by key land cover transitions. Model results indicate that a modification of biophysical processes at the land surface has a strong regional climate effect, and non-negligible global impact on temperature. Simulations experiments of large-scale (i.e. complete) regional deforestation lead to a mean reduction in precipitation in all regions, while air surface temperature increases in the tropics and decreases in boreal regions. The net global climate effects of regional deforestation are less certain. There is an overall consensus in the model experiments that the average global biophysical climate response to complete global deforestation is atmospheric cooling and drying. Observed estimates of temperature change following deforestation indicate a smaller effect than model-based regional estimates in boreal regions, comparable results in the tropics, and contrasting results in temperate regions. Regional/local biophysical effects following LCC are important for local climate, water cycle, ecosystems, their productivity and biodiversity, and thus important to consider in the formulation of adaptation policy. However before considering the inclusion of biophysical climate effects of LCC under the UNFCCC, science has to provide robust tools and methods for estimation of both country and global level effects.

Comparative effects of a fixed Polypodium leucotomos/Pomegranate combination versus Polypodium leucotomos alone on skin biophysical parameters.

PubMed

Emanuele, Enzo; Bertona, Marco; Biagi, Marco

2017-02-01

Polypodium leucotomos extract is a commonly used systemic photoprotective agent. In an exploratory fashion, the current study aimed to compare the effects of oral supplementation with a fixed Polypodium leucotomos/pomegranate combination (PPmix®) versus Polypodium leucotomos alone (Fernblock®) on skin biophysical parameters of Caucasian adults. Forty healthy adult volunteers (20 males and 20 females; mean age: 37.2±5.5 years) were randomized in a 1:1 fashion to a fixed Polypodium leucotomos/pomegranate combination (480 mg/day; n=20) or Polypodium leucotomos alone (480 mg/day; n=20) for 3 months. Six skin biophysical parameters (skin sebum content, hydration, transepidermal water loss [TEWL], erythema index, melanin index, and elasticity) were measured at baseline and after 3 months by personnel blinded to participant allocation. At the end of the study, hydration and elasticity were significantly improved and TEWL was reduced in both groups, without significant intergroup differences. The erythema index was decreased by both treatments, although the fixed Polypodium leucotomos/pomegranate combination was significantly more effective. Finally, melanin index and skin sebum content were reduced by the fixed Polypodium leucotomos/pomegranate combination, whereas Polypodium leucotomos alone did not affect them. Our results suggest that a fixed Polypodium leucotomos/pomegranate combination provides a greater improvement of skin biophysical parameters compared to Polypodium leucotomos alone in adult Caucasians. Our findings may have implications for optimizing systemic skin photoprotection and beautification strategies.

The Correlation of Arterial Stiffness with Biophysical Parameters and Blood Biochemistry.

PubMed

Khiyami, Anamil M; Dore, Fiona J; Mammadova, Aytan; Amdur, Richard L; Sen, Sabyasachi

2017-05-01

Type 2 diabetes presents with numerous macrovascular and microvascular impairments, which in turn lead to various co-morbidities. Vascular co-morbidities can be seen when examining arterial stiffness (AS), which is a predictor for endothelial health and cardiovascular disease risk. Pulse wave analysis (PWA) and pulse wave velocity (PWV) are two tests that are commonly used to measure AS. Currently, disease states and progression are tracked via blood biochemistry. These gold standards in monitoring diabetes are expensive and need optimization. To investigate which biophysical and biochemical parameters correlated best with AS, which may reduce the number of biochemical tests and biophysical parameter measurements needed to track disease progression. Data from 42 subjects with type 2 diabetes mellitus for ≤10 years, aged 40-70 years, were analyzed at a single time point. We investigated various blood biochemistry, body composition, and AS parameters. A combination of fat mass and fat-free mass was most associated with PWA over any other parameters. Leptin and high-sensitivity C-reactive protein seem to be the next two parameters that correlate with augmentation index. No other parameters had strong correlations to either PWA or PWV values. Body composition methods seemed to be better predictors of type 2 diabetes mellitus patient's vascular disease progression. Our study indicates that body composition measurements may help replace expensive tests. This may have public health and health surveillance implications in countries facing financial challenges.

Boltzmann Energy-based Image Analysis Demonstrates that Extracellular Domain Size Differences Explain Protein Segregation at Immune Synapses

PubMed Central

Burroughs, Nigel J.; Köhler, Karsten; Miloserdov, Vladimir; Dustin, Michael L.; van der Merwe, P. Anton; Davis, Daniel M.

2011-01-01

Immune synapses formed by T and NK cells both show segregation of the integrin ICAM1 from other proteins such as CD2 (T cell) or KIR (NK cell). However, the mechanism by which these proteins segregate remains unclear; one key hypothesis is a redistribution based on protein size. Simulations of this mechanism qualitatively reproduce observed segregation patterns, but only in certain parameter regimes. Verifying that these parameter constraints in fact hold has not been possible to date, this requiring a quantitative coupling of theory to experimental data. Here, we address this challenge, developing a new methodology for analysing and quantifying image data and its integration with biophysical models. Specifically we fit a binding kinetics model to 2 colour fluorescence data for cytoskeleton independent synapses (2 and 3D) and test whether the observed inverse correlation between fluorophores conforms to size dependent exclusion, and further, whether patterned states are predicted when model parameters are estimated on individual synapses. All synapses analysed satisfy these conditions demonstrating that the mechanisms of protein redistribution have identifiable signatures in their spatial patterns. We conclude that energy processes implicit in protein size based segregation can drive the patternation observed in individual synapses, at least for the specific examples tested, such that no additional processes need to be invoked. This implies that biophysical processes within the membrane interface have a crucial impact on cell∶cell communication and cell signalling, governing protein interactions and protein aggregation. PMID:21829338

Monitoring the resilience of rivers as social-ecological systems: a paradigm shift for river assessment in the 21st Century

EPA Science Inventory

First, we briefly describe the development of the major, biophysically-focused river assessment and monitoring approaches over the last 50 years. We then assess the utility of biophysical parameters for assessing rivers as social-ecological systems. We then develop a framework de...

Benefits of detailed models of muscle activation and mechanics

NASA Technical Reports Server (NTRS)

Lehman, S. L.; Stark, L.

1981-01-01

Recent biophysical and physiological studies identified some of the detailed mechanisms involved in excitation-contraction coupling, muscle contraction, and deactivation. Mathematical models incorporating these mechanisms allow independent estimates of key parameters, direct interplay between basic muscle research and the study of motor control, and realistic model behaviors, some of which are not accessible to previous, simpler, models. The existence of previously unmodeled behaviors has important implications for strategies of motor control and identification of neural signals. New developments in the analysis of differential equations make the more detailed models feasible for simulation in realistic experimental situations.

Comparisons of MODIS vegetation index products with biophysical and flux tower measurements

NASA Astrophysics Data System (ADS)

Sirikul, Natthanich

Vegetation indices (VI) play an important role in studies of global climate and biogeochemical cycles, and are also positively related to many biophysical parameters and satellite products, such as leaf area index (LAI), gross primary production (GPP), land surface water index (LSWI) and land surface temperature (LST). In this study we found that VI's had strong relationships with some biophysical products, such as gross primary production, yet were less well correlated with biophysical structural parameters, such as leaf area index. The relationships between MODIS VI's and biophysical field measured LAI showed poor correlation at semi-arid land and broadleaf forest land cover type whereas cropland showed stronger correlations than the other vegetation types. In addition, the relationship between the enhanced vegetation index (EVI)-LAI and normalized difference vegetation index (NDVI)-LAI did not show significant differences. Comparisons of the relationships between the EVI and NDVI with tower-measured GPP from 11 flux towers in North America, showed that MODIS EVI had much stronger relationships with tower-GPP than did NDVI, and EVI was better correlated with the seasonal dynamics of GPP than was NDVI. In addition, there were no significant differences among the 1x1, 3x3 and 7x7 pixel sample sizes. The comparisons of VIs from the 3 MODIS products from which VI's are generated (Standard VI (MOD13)), Nadir Adjusted Surface Reflectance (NBAR (MOD43)), and Surface Reflectance (MOD09)), showed that MODIS NBAR-EVI (MOD43) was best correlated with GPP compared with the other VI products. In addition, the MODIS VI - tower GPP relationships were significantly improved using NBAR-EVI over the more complex canopy structures, such as the broadleaf and needleleaf forests. The relationship of tower-GPP with other MODIS products would be useful in more thorough characterization of some land cover types in which the VI's have encountered problems. The land surface temperature (LST) product were found useful for empirical estimations of GPP in needleleaf forests, but were not useful for the other land cover types, whereas the land surface water index (LSWI) was more sensitive to noise from snowmelt, ground water table levels, and wet soils than to the canopy moisture levels. Also the MODIS EVI was better correlated with LST than was NDVI. Finally, the cross-site comparisons of GPP and multi-products from MODIS showed that the relationships between EVI and GPP were the strongest while LST and GPP was the weakest. EVI may thus be useful in scaling across landscapes, including heterogeneous ones, for regional estimations of GPP, especially if BRDF effects have been taken into account (such as with the NBAR product). Thus, the relationships of EVI-GPP over space and time would potentially provide much useful information for studies of the global carbon cycle.

AN IMPROVED STRATEGY FOR REGRESSION OF BIOPHYSICAL VARIABLES AND LANDSAT ETM+ DATA. (R828309)

EPA Science Inventory

Empirical models are important tools for relating field-measured biophysical variables to remote sensing data. Regression analysis has been a popular empirical method of linking these two types of data to provide continuous estimates for variables such as biomass, percent wood...

Characterization of Sensory-Motor Behavior Under Cognitive Load Using a New Statistical Platform for Studies of Embodied Cognition

PubMed Central

Ryu, Jihye; Torres, Elizabeth B.

2018-01-01

The field of enacted/embodied cognition has emerged as a contemporary attempt to connect the mind and body in the study of cognition. However, there has been a paucity of methods that enable a multi-layered approach tapping into different levels of functionality within the nervous systems (e.g., continuously capturing in tandem multi-modal biophysical signals in naturalistic settings). The present study introduces a new theoretical and statistical framework to characterize the influences of cognitive demands on biophysical rhythmic signals harnessed from deliberate, spontaneous and autonomic activities. In this study, nine participants performed a basic pointing task to communicate a decision while they were exposed to different levels of cognitive load. Within these decision-making contexts, we examined the moment-by-moment fluctuations in the peak amplitude and timing of the biophysical time series data (e.g., continuous waveforms extracted from hand kinematics and heart signals). These spike-trains data offered high statistical power for personalized empirical statistical estimation and were well-characterized by a Gamma process. Our approach enabled the identification of different empirically estimated families of probability distributions to facilitate inference regarding the continuous physiological phenomena underlying cognitively driven decision-making. We found that the same pointing task revealed shifts in the probability distribution functions (PDFs) of the hand kinematic signals under study and were accompanied by shifts in the signatures of the heart inter-beat-interval timings. Within the time scale of an experimental session, marked changes in skewness and dispersion of the distributions were tracked on the Gamma parameter plane with 95% confidence. The results suggest that traditional theoretical assumptions of stationarity and normality in biophysical data from the nervous systems are incongruent with the true statistical nature of empirical data. This work offers a unifying platform for personalized statistical inference that goes far beyond those used in conventional studies, often assuming a “one size fits all model” on data drawn from discrete events such as mouse clicks, and observations that leave out continuously co-occurring spontaneous activity taking place largely beneath awareness. PMID:29681805

Statistical and Biophysical Models for Predicting Total and Outdoor Water Use in Los Angeles

NASA Astrophysics Data System (ADS)

Mini, C.; Hogue, T. S.; Pincetl, S.

2012-04-01

Modeling water demand is a complex exercise in the choice of the functional form, techniques and variables to integrate in the model. The goal of the current research is to identify the determinants that control total and outdoor residential water use in semi-arid cities and to utilize that information in the development of statistical and biophysical models that can forecast spatial and temporal urban water use. The City of Los Angeles is unique in its highly diverse socio-demographic, economic and cultural characteristics across neighborhoods, which introduces significant challenges in modeling water use. Increasing climate variability also contributes to uncertainties in water use predictions in urban areas. Monthly individual water use records were acquired from the Los Angeles Department of Water and Power (LADWP) for the 2000 to 2010 period. Study predictors of residential water use include socio-demographic, economic, climate and landscaping variables at the zip code level collected from US Census database. Climate variables are estimated from ground-based observations and calculated at the centroid of each zip code by inverse-distance weighting method. Remotely-sensed products of vegetation biomass and landscape land cover are also utilized. Two linear regression models were developed based on the panel data and variables described: a pooled-OLS regression model and a linear mixed effects model. Both models show income per capita and the percentage of landscape areas in each zip code as being statistically significant predictors. The pooled-OLS model tends to over-estimate higher water use zip codes and both models provide similar RMSE values.Outdoor water use was estimated at the census tract level as the residual between total water use and indoor use. This residual is being compared with the output from a biophysical model including tree and grass cover areas, climate variables and estimates of evapotranspiration at very high spatial resolution. A genetic algorithm based model (Shuffled Complex Evolution-UA; SCE-UA) is also being developed to provide estimates of the predictions and parameters uncertainties and to compare against the linear regression models. Ultimately, models will be selected to undertake predictions for a range of climate change and landscape scenarios. Finally, project results will contribute to a better understanding of water demand to help predict future water use and implement targeted landscaping conservation programs to maintain sustainable water needs for a growing population under uncertain climate variability.

Biophysical mechanism of differential growth during gravitropism

NASA Technical Reports Server (NTRS)

Cosgrove, D.

1984-01-01

A research project is described the goal of which is to determine the mechanism of gravitropic curvature in plant stems at the biophysical and the cellular level. The reorientation of plant organs under the influence of gravity is due to differential growth of the upper and lower sides of the organ. The rate of plant cell enlargement is governed by four biophysical parameters: (1) the extensibility of the cell wall; (2) the minimum stress in the cell wall required for wall expansion (the "yield threshold'); (3) the osmotic pressure difference between the cell contents and the water source; and (4) the hydraulic conductivity of the pathway for water uptake. Gravitropic response must involve differential alteration of one or more of these four parameters on the two sides of the growing organ. Each of these factors will be examined to assess the role it plays in gravitropism.

Quantum-Sequencing: Biophysics of quantum tunneling through nucleic acids

NASA Astrophysics Data System (ADS)

Casamada Ribot, Josep; Chatterjee, Anushree; Nagpal, Prashant

2014-03-01

Tunneling microscopy and spectroscopy has extensively been used in physical surface sciences to study quantum tunneling to measure electronic local density of states of nanomaterials and to characterize adsorbed species. Quantum-Sequencing (Q-Seq) is a new method based on tunneling microscopy for electronic sequencing of single molecule of nucleic acids. A major goal of third-generation sequencing technologies is to develop a fast, reliable, enzyme-free single-molecule sequencing method. Here, we present the unique ``electronic fingerprints'' for all nucleotides on DNA and RNA using Q-Seq along their intrinsic biophysical parameters. We have analyzed tunneling spectra for the nucleotides at different pH conditions and analyzed the HOMO, LUMO and energy gap for all of them. In addition we show a number of biophysical parameters to further characterize all nucleobases (electron and hole transition voltage and energy barriers). These results highlight the robustness of Q-Seq as a technique for next-generation sequencing.

Inferring neural activity from BOLD signals through nonlinear optimization.

PubMed

Vakorin, Vasily A; Krakovska, Olga O; Borowsky, Ron; Sarty, Gordon E

2007-11-01

The blood oxygen level-dependent (BOLD) fMRI signal does not measure neuronal activity directly. This fact is a key concern for interpreting functional imaging data based on BOLD. Mathematical models describing the path from neural activity to the BOLD response allow us to numerically solve the inverse problem of estimating the timing and amplitude of the neuronal activity underlying the BOLD signal. In fact, these models can be viewed as an advanced substitute for the impulse response function. In this work, the issue of estimating the dynamics of neuronal activity from the observed BOLD signal is considered within the framework of optimization problems. The model is based on the extended "balloon" model and describes the conversion of neuronal signals into the BOLD response through the transitional dynamics of the blood flow-inducing signal, cerebral blood flow, cerebral blood volume and deoxyhemoglobin concentration. Global optimization techniques are applied to find a control input (the neuronal activity and/or the biophysical parameters in the model) that causes the system to follow an admissible solution to minimize discrepancy between model and experimental data. As an alternative to a local linearization (LL) filtering scheme, the optimization method escapes the linearization of the transition system and provides a possibility to search for the global optimum, avoiding spurious local minima. We have found that the dynamics of the neural signals and the physiological variables as well as the biophysical parameters can be robustly reconstructed from the BOLD responses. Furthermore, it is shown that spiking off/on dynamics of the neural activity is the natural mathematical solution of the model. Incorporating, in addition, the expansion of the neural input by smooth basis functions, representing a low-pass filtering, allows us to model local field potential (LFP) solutions instead of spiking solutions.

Biophysical applications of neutron Compton scattering

NASA Astrophysics Data System (ADS)

Wanderlingh, U. N.; Albergamo, F.; Hayward, R. L.; Middendorf, H. D.

Neutron Compton scattering (NCS) can be applied to measuring nuclear momentum distributions and potential parameters in molecules of biophysical interest. We discuss the analysis of NCS spectra from peptide models, focusing on the characterisation of the amide proton dynamics in terms of the width of the H-bond potential well, its Laplacian, and the mean kinetic energy of the proton. The Sears expansion is used to quantify deviations from the high-Q limit (impulse approximation), and line-shape asymmetry parameters are evaluated in terms of Hermite polynomials. Results on NCS from selectively deuterated acetanilide are used to illustrate this approach.

Variation of Biophysical Parameters of the Skin with Age, Gender, and Body Region

PubMed Central

Firooz, Alireza; Sadr, Bardia; Babakoohi, Shahab; Sarraf-Yazdy, Maryam; Fanian, Ferial; Kazerouni-Timsar, Ali; Nassiri-Kashani, Mansour; Naghizadeh, Mohammad Mehdi; Dowlati, Yahya

2012-01-01

Background. Understanding the physiological, chemical, and biophysical characteristics of the skin helps us to arrange a proper approach to the management of skin diseases. Objective. The aim of this study was to measure 6 biophysical characteristics of normal skin (sebum content, hydration, transepidermal water loss (TEWL), erythema index, melanin index, and elasticity) in a normal population and assess the effect of sex, age, and body location on them. Methods. Fifty healthy volunteers in 5 age groups (5 males and females in each) were enrolled in this study. A multifunctional skin physiology monitor (Courage & Khazaka electronic GmbH, Germany) was used to measure skin sebum content, hydration, TEWL, erythema index, melanin index, and elasticity in 8 different locations of the body. Results. There were significant differences between the hydration, melanin index, and elasticity of different age groups. Regarding the locations, forehead had the highest melanin index, where as palm had the lowest value. The mean values of erythema index and melanin index and TEWL were significantly higher in males and anatomic location was a significant independent factor for all of 6 measured parameters. Conclusion. Several biophysical properties of the skin vary among different gender, age groups, and body locations. PMID:22536139

Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots

PubMed Central

Lelong, Camille C. D.; Burger, Philippe; Jubelin, Guillaume; Roux, Bruno; Labbé, Sylvain; Baret, Frédéric

2008-01-01

This paper outlines how light Unmanned Aerial Vehicles (UAV) can be used in remote sensing for precision farming. It focuses on the combination of simple digital photographic cameras with spectral filters, designed to provide multispectral images in the visible and near-infrared domains. In 2005, these instruments were fitted to powered glider and parachute, and flown at six dates staggered over the crop season. We monitored ten varieties of wheat, grown in trial micro-plots in the South-West of France. For each date, we acquired multiple views in four spectral bands corresponding to blue, green, red, and near-infrared. We then performed accurate corrections of image vignetting, geometric distortions, and radiometric bidirectional effects. Afterwards, we derived for each experimental micro-plot several vegetation indexes relevant for vegetation analyses. Finally, we sought relationships between these indexes and field-measured biophysical parameters, both generic and date-specific. Therefore, we established a robust and stable generic relationship between, in one hand, leaf area index and NDVI and, in the other hand, nitrogen uptake and GNDVI. Due to a high amount of noise in the data, it was not possible to obtain a more accurate model for each date independently. A validation protocol showed that we could expect a precision level of 15% in the biophysical parameters estimation while using these relationships. PMID:27879893

Canopy reflectance modelling of semiarid vegetation

NASA Technical Reports Server (NTRS)

Franklin, Janet

1994-01-01

Three different types of remote sensing algorithms for estimating vegetation amount and other land surface biophysical parameters were tested for semiarid environments. These included statistical linear models, the Li-Strahler geometric-optical canopy model, and linear spectral mixture analysis. The two study areas were the National Science Foundation's Jornada Long Term Ecological Research site near Las Cruces, NM, in the northern Chihuahuan desert, and the HAPEX-Sahel site near Niamey, Niger, in West Africa, comprising semiarid rangeland and subtropical crop land. The statistical approach (simple and multiple regression) resulted in high correlations between SPOT satellite spectral reflectance and shrub and grass cover, although these correlations varied with the spatial scale of aggregation of the measurements. The Li-Strahler model produced estimated of shrub size and density for both study sites with large standard errors. In the Jornada, the estimates were accurate enough to be useful for characterizing structural differences among three shrub strata. In Niger, the range of shrub cover and size in short-fallow shrublands is so low that the necessity of spatially distributed estimation of shrub size and density is questionable. Spectral mixture analysis of multiscale, multitemporal, multispectral radiometer data and imagery for Niger showed a positive relationship between fractions of spectral endmembers and surface parameters of interest including soil cover, vegetation cover, and leaf area index.

An extended model of vesicle fusion at the plasma membrane to estimate protein lateral diffusion from TIRF microscopy images.

PubMed

Basset, Antoine; Bouthemy, Patrick; Boulanger, Jérôme; Waharte, François; Salamero, Jean; Kervrann, Charles

2017-07-24

Characterizing membrane dynamics is a key issue to understand cell exchanges with the extra-cellular medium. Total internal reflection fluorescence microscopy (TIRFM) is well suited to focus on the late steps of exocytosis at the plasma membrane. However, it is still a challenging task to quantify (lateral) diffusion and estimate local dynamics of proteins. A new model was introduced to represent the behavior of cargo transmembrane proteins during the vesicle fusion to the plasma membrane at the end of the exocytosis process. Two biophysical parameters, the diffusion coefficient and the release rate parameter, are automatically estimated from TIRFM image sequences, to account for both the lateral diffusion of molecules at the membrane and the continuous release of the proteins from the vesicle to the plasma membrane. Quantitative evaluation on 300 realistic computer-generated image sequences demonstrated the efficiency and accuracy of the method. The application of our method on 16 real TIRFM image sequences additionally revealed differences in the dynamic behavior of Transferrin Receptor (TfR) and Langerin proteins. An automated method has been designed to simultaneously estimate the diffusion coefficient and the release rate for each individual vesicle fusion event at the plasma membrane in TIRFM image sequences. It can be exploited for further deciphering cell membrane dynamics.

A unifying view of synchronization for data assimilation in complex nonlinear networks

NASA Astrophysics Data System (ADS)

Abarbanel, Henry D. I.; Shirman, Sasha; Breen, Daniel; Kadakia, Nirag; Rey, Daniel; Armstrong, Eve; Margoliash, Daniel

2017-12-01

Networks of nonlinear systems contain unknown parameters and dynamical degrees of freedom that may not be observable with existing instruments. From observable state variables, we want to estimate the connectivity of a model of such a network and determine the full state of the model at the termination of a temporal observation window during which measurements transfer information to a model of the network. The model state at the termination of a measurement window acts as an initial condition for predicting the future behavior of the network. This allows the validation (or invalidation) of the model as a representation of the dynamical processes producing the observations. Once the model has been tested against new data, it may be utilized as a predictor of responses to innovative stimuli or forcing. We describe a general framework for the tasks involved in the "inverse" problem of determining properties of a model built to represent measured output from physical, biological, or other processes when the measurements are noisy, the model has errors, and the state of the model is unknown when measurements begin. This framework is called statistical data assimilation and is the best one can do in estimating model properties through the use of the conditional probability distributions of the model state variables, conditioned on observations. There is a very broad arena of applications of the methods described. These include numerical weather prediction, properties of nonlinear electrical circuitry, and determining the biophysical properties of functional networks of neurons. Illustrative examples will be given of (1) estimating the connectivity among neurons with known dynamics in a network of unknown connectivity, and (2) estimating the biophysical properties of individual neurons in vitro taken from a functional network underlying vocalization in songbirds.

Chromosome aberrations and cell death by ionizing radiation: Evolution of a biophysical model

NASA Astrophysics Data System (ADS)

Ballarini, Francesca; Carante, Mario P.

2016-11-01

The manuscript summarizes and discusses the various versions of a radiation damage biophysical model, implemented as a Monte Carlo simulation code, originally developed for chromosome aberrations and subsequently extended to cell death. This extended version has been called BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations). According to the basic assumptions, complex double-strand breaks (called ;Cluster Lesions;, or CLs) produce independent chromosome free-ends, mis-rejoining within a threshold distance d (or un-rejoining) leads to chromosome aberrations, and ;lethal aberrations; (i.e., dicentrics plus rings plus large deletions) lead to clonogenic cell death. The mean number of CLs per Gy and per cell is an adjustable parameter. While in BIANCA the threshold distance d was the second parameter, in a subsequent version, called BIANCA II, d has been fixed as the mean distance between two adjacent interphase chromosome territories, and a new parameter, f, has been introduced to represent the chromosome free-end un-rejoining probability. Simulated dose-response curves for chromosome aberrations and cell survival obtained by the various model versions were compared with literature experimental data. Such comparisons provided indications on some open questions, including the role of energy deposition clustering at the nm and the μm level, the probability for a chromosome free-end to remain un-rejoined, and the relationship between chromosome aberrations and cell death. Although both BIANCA and BIANCA II provided cell survival curves in general agreement with human and hamster fibroblast survival data, BIANCA II allowed for a better reproduction of dicentrics, rings and deletions considered separately. Furthermore, the approach adopted in BIANCA II for d is more consistent with estimates reported in the literature. After testing against aberration and survival data, BIANCA II was applied to investigate the depth-dependence of the radiation effectiveness for a proton SOBP used to treat eye melanoma in Catania, Italy. The survival of AG01522 cells at different depths was reproduced, and the survival of V79 cells was predicted. For both cell lines, the simulations also predicted yields of chromosome aberrations, some of which can be regarded as indicators of the risk to normal tissues.

An improved strategy for regression of biophysical variables and Landsat ETM+ data.

Treesearch

Warren B. Cohen; Thomas K. Maiersperger; Stith T. Gower; David P. Turner

2003-01-01

Empirical models are important tools for relating field-measured biophysical variables to remote sensing data. Regression analysis has been a popular empirical method of linking these two types of data to provide continuous estimates for variables such as biomass, percent woody canopy cover, and leaf area index (LAI). Traditional methods of regression are not...

Improving Access to MODIS Biophysical Science Products for NACP Investigators

NASA Technical Reports Server (NTRS)

Wolfe, Robert E.; Gao, Feng; Morisette, Jeffrey T.; Ederer, Gregory A.; Pedelty, Jeffrey A.

2007-01-01

MODIS 4 NACP is a NASA-funded project supporting the North American Carbon Program (NACP). The purpose of this Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) project is to provide researchers with Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical data products that are custom tailored for use in NACP model studies. Standard MODIS biophysical products provide used to improve our understanding on the climate and ecosystem changes. However, direct uses of the MODIS biophysical parameters are constrained by retrieval quality and cloud contamination. Another challenge that NACP users face is acquiring MODIS data in formats and at spatial-temporal resolutions consistent with other data sets they use. We have been working closely with key NACP users to tailor the MODIS products to fit their needs. First, we provide new temporally smoothed and spatially continuous MODIS biophysical data sets. Second, we are distributing MODIS data at suitable spatial-temporal resolutions and in formats consistent with other data integration into model studies.

How gene order is influenced by the biophysics of transcription regulation

PubMed Central

Kolesov, Grigory; Wunderlich, Zeba; Laikova, Olga N.; Gelfand, Mikhail S.; Mirny, Leonid A.

2007-01-01

What are the forces that shape the structure of prokaryotic genomes: the order of genes, their proximity, and their orientation? Coregulation and coordinated horizontal gene transfer are believed to promote the proximity of functionally related genes and the formation of operons. However, forces that influence the structure of the genome beyond the level of a single operon remain unknown. Here, we show that the biophysical mechanism by which regulatory proteins search for their sites on DNA can impose constraints on genome structure. Using simulations, we demonstrate that rapid and reliable gene regulation requires that the transcription factor (TF) gene be close to the site on DNA the TF has to bind, thus promoting the colocalization of TF genes and their targets on the genome. We use parameters that have been measured in recent experiments to estimate the relevant length and times scales of this process and demonstrate that the search for a cognate site may be prohibitively slow if a TF has a low copy number and is not colocalized. We also analyze TFs and their sites in a number of bacterial genomes, confirm that they are colocalized significantly more often than expected, and show that this observation cannot be attributed to the pressure for coregulation or formation of selfish gene clusters, thus supporting the role of the biophysical constraint in shaping the structure of prokaryotic genomes. Our results demonstrate how spatial organization can influence timing and noise in gene expression. PMID:17709750

Comparison of machine-learning methods for above-ground biomass estimation based on Landsat imagery

NASA Astrophysics Data System (ADS)

Wu, Chaofan; Shen, Huanhuan; Shen, Aihua; Deng, Jinsong; Gan, Muye; Zhu, Jinxia; Xu, Hongwei; Wang, Ke

2016-07-01

Biomass is one significant biophysical parameter of a forest ecosystem, and accurate biomass estimation on the regional scale provides important information for carbon-cycle investigation and sustainable forest management. In this study, Landsat satellite imagery data combined with field-based measurements were integrated through comparisons of five regression approaches [stepwise linear regression, K-nearest neighbor, support vector regression, random forest (RF), and stochastic gradient boosting] with two different candidate variable strategies to implement the optimal spatial above-ground biomass (AGB) estimation. The results suggested that RF algorithm exhibited the best performance by 10-fold cross-validation with respect to R2 (0.63) and root-mean-square error (26.44 ton/ha). Consequently, the map of estimated AGB was generated with a mean value of 89.34 ton/ha in northwestern Zhejiang Province, China, with a similar pattern to the distribution mode of local forest species. This research indicates that machine-learning approaches associated with Landsat imagery provide an economical way for biomass estimation. Moreover, ensemble methods using all candidate variables, especially for Landsat images, provide an alternative for regional biomass simulation.

Developing a generalized allometric equation for aboveground biomass estimation

NASA Astrophysics Data System (ADS)

Xu, Q.; Balamuta, J. J.; Greenberg, J. A.; Li, B.; Man, A.; Xu, Z.

2015-12-01

A key potential uncertainty in estimating carbon stocks across multiple scales stems from the use of empirically calibrated allometric equations, which estimate aboveground biomass (AGB) from plant characteristics such as diameter at breast height (DBH) and/or height (H). The equations themselves contain significant and, at times, poorly characterized errors. Species-specific equations may be missing. Plant responses to their local biophysical environment may lead to spatially varying allometric relationships. The structural predictor may be difficult or impossible to measure accurately, particularly when derived from remote sensing data. All of these issues may lead to significant and spatially varying uncertainties in the estimation of AGB that are unexplored in the literature. We sought to quantify the errors in predicting AGB at the tree and plot level for vegetation plots in California. To accomplish this, we derived a generalized allometric equation (GAE) which we used to model the AGB on a full set of tree information such as DBH, H, taxonomy, and biophysical environment. The GAE was derived using published allometric equations in the GlobAllomeTree database. The equations were sparse in details about the error since authors provide the coefficient of determination (R2) and the sample size. A more realistic simulation of tree AGB should also contain the noise that was not captured by the allometric equation. We derived an empirically corrected variance estimate for the amount of noise to represent the errors in the real biomass. Also, we accounted for the hierarchical relationship between different species by treating each taxonomic level as a covariate nested within a higher taxonomic level (e.g. species < genus). This approach provides estimation under incomplete tree information (e.g. missing species) or blurred information (e.g. conjecture of species), plus the biophysical environment. The GAE allowed us to quantify contribution of each different covariate in estimating the AGB of trees. Lastly, we applied the GAE to an existing vegetation plot database - Forest Inventory and Analysis database - to derive per-tree and per-plot AGB estimations, their errors, and how much the error could be contributed to the original equations, the plant's taxonomy, and their biophysical environment.

Quantify the Biophysical and Socioeconomic Drivers of Changes in Forest and Agricultural Land in South and Southeast Asia

NASA Astrophysics Data System (ADS)

Xu, X.; Jain, A. K.; Calvin, K. V.

2017-12-01

Due to the rapid socioeconomic development and biophysical factors, South and Southeast Asia (SSEA) has become a hotspot region of land use and land cover changes (LULCCs) in past few decades. Uncovering the drivers of LULCC is crucial for improving the understanding of LULCC processes. Due to the differences from spatiotemporal scales, methods and data sources in previous studies, the quantitative relationships between the LULCC activities and biophysical and socioeconomic drivers at the regional scale of SSEA have not been established. Here we present a comprehensive estimation of the biophysical and socioeconomic drivers of the major LULCC activities in SSEA: changes in forest and agricultural land. We used the Climate Change Initiative land cover data developed by European Space Agency to reveal the dynamics of forest and agricultural land from 1992 to 2015. Then we synthesized 200 publications about LULCC drivers at different spatial scales in SSEA to identify the major drivers of these LULCC activities. Corresponding representative variables of the major drivers were collected. The geographically weighted regression was employed to assess the spatiotemporally heterogeneous drivers of LULCC. Moreover, we validated our results with some national level case studies in SSEA. The results showed that both biophysical conditions such as terrain, soil, and climate, and socioeconomic factors such as migration, poverty, and economy played important roles in driving the changes of forest and agricultural land. The major drivers varied in different locations and periods. Our study integrated the bottom-up knowledge from local scale case studies with the top-down estimation of LULCC drivers, therefore generated more accurate and credible results. The identified biophysical and socioeconomic components could be used to improve the LULCC modelling and projection.

Daytime Changes of Skin Biophysical Characteristics: A Study of Hydration, Transepidermal Water Loss, pH, Sebum, Elasticity, Erythema, and Color Index on Middle Eastern Skin.

PubMed

Firooz, Alireza; Zartab, Hamed; Sadr, Bardia; Bagherpour, Leili Naraghi; Masoudi, Aidin; Fanian, Ferial; Dowlati, Yahya; Ehsani, Amir Hooshang; Samadi, Aniseh

2016-01-01

The exposure of skin to ultraviolet radiation and temperature differs significantly during the day. It is reasonable that biophysical parameters of human skin have periodic daily fluctuation. The objective of this study was to study the fluctuations of various biophysical characteristics of Middle Eastern skin in standardized experimental conditions. Seven biophysical parameters of skin including stratum corneum hydration, transepidermal water loss, pH, sebum, elasticity, skin color, and erythema index were measured at three time points (8 a.m., 12 p.m. and 4 p.m.) on the forearm of 12 healthy participants (mean age of 28.4 years) without any ongoing skin disease using the CK MPA 580 device in standard temperature and humidity conditions. A significant difference was observed between means of skin color index at 8 a.m. (175.42 ± 13.92) and 4 p.m. (164.44 ± 13.72, P = 0.025), between the pH at 8 a.m. (5.72 ± 0.48) and 4 p.m. (5.33 ± 0.55, P = 0.001) and pH at 12 p.m. (5.60 ± 0.48) and 4 p.m. (5.33 ± 0.55, P = 0.001). Other comparisons between the means of these parameters at different time points resulted in nonsignificant P values. There are daytime changes in skin color index and pH. Skin color index might be higher and cutaneous pH more basic in the early morning compared to later of the day.

Single Nucleobase Identification Using Biophysical Signatures from Nanoelectronic Quantum Tunneling.

PubMed

Korshoj, Lee E; Afsari, Sepideh; Khan, Sajida; Chatterjee, Anushree; Nagpal, Prashant

2017-03-01

Nanoelectronic DNA sequencing can provide an important alternative to sequencing-by-synthesis by reducing sample preparation time, cost, and complexity as a high-throughput next-generation technique with accurate single-molecule identification. However, sample noise and signature overlap continue to prevent high-resolution and accurate sequencing results. Probing the molecular orbitals of chemically distinct DNA nucleobases offers a path for facile sequence identification, but molecular entropy (from nucleotide conformations) makes such identification difficult when relying only on the energies of lowest-unoccupied and highest-occupied molecular orbitals (LUMO and HOMO). Here, nine biophysical parameters are developed to better characterize molecular orbitals of individual nucleobases, intended for single-molecule DNA sequencing using quantum tunneling of charges. For this analysis, theoretical models for quantum tunneling are combined with transition voltage spectroscopy to obtain measurable parameters unique to the molecule within an electronic junction. Scanning tunneling spectroscopy is then used to measure these nine biophysical parameters for DNA nucleotides, and a modified machine learning algorithm identified nucleobases. The new parameters significantly improve base calling over merely using LUMO and HOMO frontier orbital energies. Furthermore, high accuracies for identifying DNA nucleobases were observed at different pH conditions. These results have significant implications for developing a robust and accurate high-throughput nanoelectronic DNA sequencing technique. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Changes in cytoskeletal dynamics and nonlinear rheology with metastatic ability in cancer cell lines

NASA Astrophysics Data System (ADS)

Coughlin, Mark F.; Fredberg, Jeffrey J.

2013-12-01

Metastatic outcome is impacted by the biophysical state of the primary tumor cell. To determine if changes in cancer cell biophysical properties facilitate metastasis, we quantified cytoskeletal biophysics in well-characterized human skin, bladder, prostate and kidney cell line pairs that differ in metastatic ability. Using magnetic twisting cytometry with optical detection, cytoskeletal dynamics was observed through spontaneous motion of surface bound marker beads and nonlinear rheology was characterized through large amplitude forced oscillations of probe beads. Measurements of cytoskeletal dynamics and nonlinear rheology differed between strongly and weakly metastatic cells. However, no set of biophysical parameters changed systematically with metastatic ability across all cell lines. Compared to their weakly metastatic counterparts, the strongly metastatic kidney cancer cells exhibited both increased cytoskeletal dynamics and stiffness at large deformation which are thought to facilitate the process of vascular invasion.

Detecting cis-regulatory binding sites for cooperatively binding proteins

PubMed Central

van Oeffelen, Liesbeth; Cornelis, Pierre; Van Delm, Wouter; De Ridder, Fedor; De Moor, Bart; Moreau, Yves

2008-01-01

Several methods are available to predict cis-regulatory modules in DNA based on position weight matrices. However, the performance of these methods generally depends on a number of additional parameters that cannot be derived from sequences and are difficult to estimate because they have no physical meaning. As the best way to detect cis-regulatory modules is the way in which the proteins recognize them, we developed a new scoring method that utilizes the underlying physical binding model. This method requires no additional parameter to account for multiple binding sites; and the only necessary parameters to model homotypic cooperative interactions are the distances between adjacent protein binding sites in basepairs, and the corresponding cooperative binding constants. The heterotypic cooperative binding model requires one more parameter per cooperatively binding protein, which is the concentration multiplied by the partition function of this protein. In a case study on the bacterial ferric uptake regulator, we show that our scoring method for homotypic cooperatively binding proteins significantly outperforms other PWM-based methods where biophysical cooperativity is not taken into account. PMID:18400778

Phytoplankton productivity in relation to light intensity: A simple equation

USGS Publications Warehouse

Peterson, D.H.; Perry, M.J.; Bencala, K.E.; Talbot, M.C.

1987-01-01

A simple exponential equation is used to describe photosynthetic rate as a function of light intensity for a variety of unicellular algae and higher plants where photosynthesis is proportional to (1-e-??1). The parameter ?? (=Ik-1) is derived by a simultaneous curve-fitting method, where I is incident quantum-flux density. The exponential equation is tested against a wide range of data and is found to adequately describe P vs. I curves. The errors associated with photosynthetic parameters are calculated. A simplified statistical model (Poisson) of photon capture provides a biophysical basis for the equation and for its ability to fit a range of light intensities. The exponential equation provides a non-subjective simultaneous curve fitting estimate for photosynthetic efficiency (a) which is less ambiguous than subjective methods: subjective methods assume that a linear region of the P vs. I curve is readily identifiable. Photosynthetic parameters ?? and a are used widely in aquatic studies to define photosynthesis at low quantum flux. These parameters are particularly important in estuarine environments where high suspended-material concentrations and high diffuse-light extinction coefficients are commonly encountered. ?? 1987.

Precision Viticulture from Multitemporal, Multispectral Very High Resolution Satellite Data

NASA Astrophysics Data System (ADS)

Kandylakis, Z.; Karantzalos, K.

2016-06-01

In order to exploit efficiently very high resolution satellite multispectral data for precision agriculture applications, validated methodologies should be established which link the observed reflectance spectra with certain crop/plant/fruit biophysical and biochemical quality parameters. To this end, based on concurrent satellite and field campaigns during the veraison period, satellite and in-situ data were collected, along with several grape samples, at specific locations during the harvesting period. These data were collected for a period of three years in two viticultural areas in Northern Greece. After the required data pre-processing, canopy reflectance observations, through the combination of several vegetation indices were correlated with the quantitative results from the grape/must analysis of grape sampling. Results appear quite promising, indicating that certain key quality parameters (like brix levels, total phenolic content, brix to total acidity, anthocyanin levels) which describe the oenological potential, phenolic composition and chromatic characteristics can be efficiently estimated from the satellite data.

Engineered biomaterial and biophysical stimulation as combinatorial strategies to address prosthetic infection by pathogenic bacteria.

PubMed

Boda, Sunil Kumar; Basu, Bikramjit

2017-10-01

A plethora of antimicrobial strategies are being developed to address prosthetic infection. The currently available methods for implant infection treatment include the use of antibiotics and revision surgery. Among the bacterial strains, Staphylococcus species pose significant challenges particularly, with regard to hospital acquired infections. In order to combat such life threatening infectious diseases, researchers have developed implantable biomaterials incorporating nanoparticles, antimicrobial reinforcements, surface coatings, slippery/non-adhesive and contact killing surfaces. This review discusses a few of the biomaterial and biophysical antimicrobial strategies, which are in the developmental stage and actively being pursued by several research groups. The clinical efficacy of biophysical stimulation methods such as ultrasound, electric and magnetic field treatments against prosthetic infection depends critically on the stimulation protocol and parameters of the treatment modality. A common thread among the three biophysical stimulation methods is the mechanism of bactericidal action, which is centered on biophysical rupture of bacterial membranes, the generation of reactive oxygen species (ROS) and bacterial membrane depolarization evoked by the interference of essential ion-transport. Although the extent of antimicrobial effect, normally achieved through biophysical stimulation protocol is insufficient to warrant therapeutic application, a combination of antibiotic/ROS inducing agents and biophysical stimulation methods can elicit a clinically relevant reduction in viable bacterial numbers. In this review, we present a detailed account of both the biomaterial and biophysical approaches for achieving maximum bacterial inactivation. Summarizing, the biophysical stimulation methods in a combinatorial manner with material based strategies can be a more potent solution to control bacterial infections. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 2174-2190, 2017. © 2016 Wiley Periodicals, Inc.

Analytical method for the fast time-domain reconstruction of fluorescent inclusions in vitro and in vivo.

PubMed

Han, Sung-Ho; Farshchi-Heydari, Salman; Hall, David J

2010-01-20

A novel time-domain optical method to reconstruct the relative concentration, lifetime, and depth of a fluorescent inclusion is described. We establish an analytical method for the estimations of these parameters for a localized fluorescent object directly from the simple evaluations of continuous wave intensity, exponential decay, and temporal position of the maximum of the fluorescence temporal point-spread function. Since the more complex full inversion process is not involved, this method permits a robust and fast processing in exploring the properties of a fluorescent inclusion. This method is confirmed by in vitro and in vivo experiments. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Low-Cost Evaluation of EO-1 Hyperion and ALI for Detection and Biophysical Characterization of Forest Logging in Amazonia (NCC5-481)

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Keller, Michael M.; Silva, Jose Natalino; Zweede, Johan C.; Pereira, Rodrigo, Jr.

2002-01-01

Major uncertainties exist regarding the rate and intensity of logging in tropical forests worldwide: these uncertainties severely limit economic, ecological, and biogeochemical analyses of these regions. Recent sawmill surveys in the Amazon region of Brazil show that the area logged is nearly equal to total area deforested annually, but conversion of survey data to forest area, forest structural damage, and biomass estimates requires multiple assumptions about logging practices. Remote sensing could provide an independent means to monitor logging activity and to estimate the biophysical consequences of this land use. Previous studies have demonstrated that the detection of logging in Amazon forests is difficult and no studies have developed either the quantitative physical basis or remote sensing approaches needed to estimate the effects of various logging regimes on forest structure. A major reason for these limitations has been a lack of sufficient, well-calibrated optical satellite data, which in turn, has impeded the development and use of physically-based, quantitative approaches for detection and structural characterization of forest logging regimes. We propose to use data from the EO-1 Hyperion imaging spectrometer to greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin. Our approach is based on four "biogeophysical indicators" not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes. Our quantitative assessment of Hyperion hyperspectral and ALI multi-spectral data for the detection and structural characterization of selective logging in Amazonia will benefit from data collected through an ongoing project run by the Tropical Forest Foundation, within which we have developed a study of the canopy and landscape biophysics of conventional and reduced-impact logging. We will add to our base of forest structural information in concert with an EO-1 overpass. Using a photon transport model inversion technique that accounts for non-linear mixing of the four biogeophysical indicators, we will estimate these parameters across a gradient of selective logging intensity provided by conventional and reduced impact logging sites. We will also compare our physical ly-based approach to both conventional (e.g., NDVI) and novel (e.g., SWIR-channel) vegetation indices as well as to linear mixture modeling methods. We will cross-compare these approaches using Hyperion and ALI imagers to determine the strengths and limitations of these two sensors for applications of forest biophysics. This effort will yield the first physical ly-based, quantitative analysis of the detection and intensity of selective logging in Amazonia, comparing hyperspectral and improved multi-spectral approaches as well as inverse modeling, linear mixture modeling, and vegetation index techniques.

The Effects of Statistical Multiplicity of Infection on Virus Quantification and Infectivity Assays.

PubMed

Mistry, Bhaven A; D'Orsogna, Maria R; Chou, Tom

2018-06-19

Many biological assays are employed in virology to quantify parameters of interest. Two such classes of assays, virus quantification assays (VQAs) and infectivity assays (IAs), aim to estimate the number of viruses present in a solution and the ability of a viral strain to successfully infect a host cell, respectively. VQAs operate at extremely dilute concentrations, and results can be subject to stochastic variability in virus-cell interactions. At the other extreme, high viral-particle concentrations are used in IAs, resulting in large numbers of viruses infecting each cell, enough for measurable change in total transcription activity. Furthermore, host cells can be infected at any concentration regime by multiple particles, resulting in a statistical multiplicity of infection and yielding potentially significant variability in the assay signal and parameter estimates. We develop probabilistic models for statistical multiplicity of infection at low and high viral-particle-concentration limits and apply them to the plaque (VQA), endpoint dilution (VQA), and luciferase reporter (IA) assays. A web-based tool implementing our models and analysis is also developed and presented. We test our proposed new methods for inferring experimental parameters from data using numerical simulations and show improvement on existing procedures in all limits. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Carbon farming economics: What have we learned?

PubMed

Tang, Kai; Kragt, Marit E; Hailu, Atakelty; Ma, Chunbo

2016-05-01

This study reviewed 62 economic analyses published between 1995 and 2014 on the economic impacts of policies that incentivise agricultural greenhouse (GHG) mitigation. Typically, biophysical models are used to evaluate the changes in GHG mitigation that result from landholders changing their farm and land management practices. The estimated results of biophysical models are then integrated with economic models to simulate the costs of different policy scenarios to production systems. The cost estimates vary between $3 and $130/t CO2 equivalent in 2012 US dollars, depending on the mitigation strategies, spatial locations, and policy scenarios considered. Most studies assessed the consequences of a single, rather than multiple, mitigation strategies, and few considered the co-benefits of carbon farming. These omissions could challenge the reality and robustness of the studies' results. One of the biggest challenges facing agricultural economists is to assess the full extent of the trade-offs involved in carbon farming. We need to improve our biophysical knowledge about carbon farming co-benefits, predict the economic impacts of employing multiple strategies and policy incentives, and develop the associated integrated models, to estimate the full costs and benefits of agricultural GHG mitigation to farmers and the rest of society. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimating crop net primary production using inventory data and MODIS-derived parameters

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

Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.

2013-06-03

National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois inmore » years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.« less

Cellular biophysics during freezing of rat and mouse sperm predicts post-thaw motility.

PubMed

Hagiwara, Mie; Choi, Jeung Hwan; Devireddy, Ramachandra V; Roberts, Kenneth P; Wolkers, Willem F; Makhlouf, Antoine; Bischof, John C

2009-10-01

Though cryopreservation of mouse sperm yields good survival and motility after thawing, cryopreservation of rat sperm remains a challenge. This study was designed to evaluate the biophysics (membrane permeability) of rat in comparison to mouse to better understand the cooling rate response that contributes to cryopreservation success or failure in these two sperm types. In order to extract subzero membrane hydraulic permeability in the presence of ice, a differential scanning calorimeter (DSC) method was used. By analyzing rat and mouse sperm frozen at 5 degrees C/min and 20 degrees C/min, heat release signatures characteristic of each sperm type were obtained and correlated to cellular dehydration. The dehydration response was then fit to a model of cellular water transport (dehydration) by adjusting cell-specific biophysical (membrane hydraulic permeability) parameters L(pg) and E(Lp). A "combined fit" (to 5 degrees C/min and 20 degrees C/min data) for rat sperm in Biggers-Whitten-Whittingham media yielded L(pg) = 0.007 microm min(-1) atm(-1) and E(Lp) = 17.8 kcal/mol, and in egg yolk cryopreservation media yielded L(pg) = 0.005 microm min(-1) atm(-1) and E(Lp) = 14.3 kcal/mol. These parameters, especially the activation energy, were found to be lower than previously published parameters for mouse sperm. In addition, the biophysical responses in mouse and rat sperm were shown to depend on the constituents of the cryopreservation media, in particular egg yolk and glycerol. Using these parameters, optimal cooling rates for cryopreservation were predicted for each sperm based on a criteria of 5%-15% normalized cell water at -30 degrees C during freezing in cryopreservation media. These predicted rates range from 53 degrees C/min to 70 degrees C/min and from 28 degrees C/min to 36 degrees C/min in rat and mouse, respectively. These predictions were validated by comparison to experimentally determined cryopreservation outcomes, in this case based on motility. Maximum motility was obtained with freezing rates between 50 degrees C/min and 80 degrees C/min for rat and at 20 degrees C/min with a sharp drop at 50 degrees C/min for mouse. In summary, DSC experiments on mouse and rat sperm yielded a difference in membrane permeability parameters in the two sperm types that, when implemented in a biophysical model of water transport, reasonably predict different optimal cooling rate outcomes for each sperm after cryopreservation.

Daytime Changes of Skin Biophysical Characteristics: A Study of Hydration, Transepidermal Water Loss, pH, Sebum, Elasticity, Erythema, and Color Index on Middle Eastern Skin

PubMed Central

Firooz, Alireza; Zartab, Hamed; Sadr, Bardia; Bagherpour, Leili Naraghi; Masoudi, Aidin; Fanian, Ferial; Dowlati, Yahya; Ehsani, Amir Hooshang; Samadi, Aniseh

2016-01-01

Background: The exposure of skin to ultraviolet radiation and temperature differs significantly during the day. It is reasonable that biophysical parameters of human skin have periodic daily fluctuation. The objective of this study was to study the fluctuations of various biophysical characteristics of Middle Eastern skin in standardized experimental conditions. Materials and Methods: Seven biophysical parameters of skin including stratum corneum hydration, transepidermal water loss, pH, sebum, elasticity, skin color, and erythema index were measured at three time points (8 a.m., 12 p.m. and 4 p.m.) on the forearm of 12 healthy participants (mean age of 28.4 years) without any ongoing skin disease using the CK MPA 580 device in standard temperature and humidity conditions. Results: A significant difference was observed between means of skin color index at 8 a.m. (175.42 ± 13.92) and 4 p.m. (164.44 ± 13.72, P = 0.025), between the pH at 8 a.m. (5.72 ± 0.48) and 4 p.m. (5.33 ± 0.55, P = 0.001) and pH at 12 p.m. (5.60 ± 0.48) and 4 p.m. (5.33 ± 0.55, P = 0.001). Other comparisons between the means of these parameters at different time points resulted in nonsignificant P values. Conclusion: There are daytime changes in skin color index and pH. Skin color index might be higher and cutaneous pH more basic in the early morning compared to later of the day. PMID:27904203

Biophysical aspects of using liposomes as delivery vehicles.

PubMed

Ulrich, Anne S

2002-04-01

Liposomes are used as biocompatible carriers of drugs, peptides, proteins, plasmic DNA, antisense oligonucleotides or ribozymes, for pharmaceutical, cosmetic, and biochemical purposes. The enormous versatility in particle size and in the physical parameters of the lipids affords an attractive potential for constructing tailor-made vehicles for a wide range of applications. Some of the recent literature will be reviewed here and presented from a biophysical point of view, thus providing a background for the more specialized articles in this special issue on liposome technology. Different properties (size, colloidal behavior, phase transitions, and polymorphism) of diverse lipid formulations (liposomes, lipoplexes, cubic phases, emulsions, and solid lipid nanoparticles) for distinct applications (parenteral, transdermal, pulmonary, and oral administration) will be rationalized in terms of common structural, thermodynamic and kinetic parameters of the lipids. This general biophysical basis helps to understand pharmaceutically relevant aspects such as liposome stability during storage and towards serum, the biodistribution and specific targeting of cargo, and how to trigger drug release and membrane fusion. Methods for the preparation and characterization of liposomal formulations in vitro will be outlined, too.

Optimizing spatial and temporal constraints for cropland canopy water content retrieval through coupled radiative transfer model inversion

NASA Astrophysics Data System (ADS)

Boren, E. J.; Boschetti, L.; Johnson, D.

2017-12-01

Water plays a critical role in all plant physiological processes, including transpiration, photosynthesis, nutrient transportation, and maintenance of proper plant cell functions. Deficits in water content cause drought-induced stress conditions, such as constrained plant growth and cellular metabolism, while overabundance of water cause anoxic conditions which limit plant physiological processes and promote disease. Vegetation water content maps can provide agricultural producers key knowledge for improving production capacity and resiliency in agricultural systems while facilitating the ability to pinpoint, monitor, and resolve water scarcity issues. Radiative transfer model (RTM) inversion has been successfully applied to remotely sensed data to retrieve biophysical and canopy parameter estimates, including water content. The successful launch of the Landsat 8 Operational Land Imager (OLI) in 2012, Sentinel 2A Multispectral Instrument (MSI) in 2015, followed by Sentinel 2B in 2017, the systematic acquisition schedule and free data distribution policy provide the opportunity for water content estimation at a spatial and temporal scale that can meet the demands of potential operational users: combined, these polar-orbiting systems provide 10 m to 30 m multi-spectral global coverage up to every 3 days. The goal of the present research is to prototype the generation of a cropland canopy water content product, obtained from the newly developed Landsat 8 and Sentinel 2 atmospherically corrected HLS product, through the inversion of the leaf and canopy model PROSAIL5B. We assess the impact of a novel spatial and temporal stratification, where some parameters of the model are constrained by crop type and phenological phase, based on ancillary biophysical data, collected from various crop species grown in a controlled setting and under different water stress conditions. Canopy-level data, collected coincidently with satellite overpasses during four summer field campaigns in northern Idaho (2014 to 2017), are used to validate the results of the model inversion.

Determining Biophysical Controls on Forest Structure using Hyperspatial Satellite Imagery and Ecological Gradient Modeling

NASA Astrophysics Data System (ADS)

Dobrowski, S. Z.; Greenberg, J. A.; Schladow, G.

2006-12-01

There is evidence from the Sierra Nevada that sub-alpine and alpine environments are currently experiencing landscape-mediated changes in growth and recruitment due to recent climate change. Understanding the biophysical controls of forest structure, growth, and recruitment in these environments is critical for interpreting and predicting the direction and magnitude of biotic responses to climate shift. We examined the abiotic controls of forest biomass within a 305 km2 region of the Carson Range on the eastern shore of Lake Tahoe, CA USA using estimates of forest structure and biophysical drivers developed continuously over the landscape. The study area ranged from 1900 m to 3400 m a.s.l. and encompassed montane, sub-alpine, and alpine environments. From hyperspatial optical imagery (IKONOS), we derived per-tree positions and crown sizes using a template matching approach applied to a pre-classified image of sunlit and shadowed vegetation pixels. From this remote sensing derived stem map, we calculated plot-level estimates of stem density, tree cover and average crown size. Additionally, we developed high resolution (30 m) estimates of climate variables within the study area using meteorological station data, topographic data, and a combination of empirical and mechanistic modeling approaches. From these climate surfaces, digital elevation data, and soil survey data, we derived estimates of direct and indirect biophysical drivers including heat loading, reference evapotranspiration, water deficit, solar radiation, topographic convergence, soil depth, and soil water holding capacity. Using these data sets, we conducted a regression tree analysis with stem density, tree cover, and average tree size as response and biophysical drivers as predictors. Trees were fit using half of the dataset randomly sampled (168,000 samples) and pruned using cost-complexity pruning based on 10-fold cross- validation. Predictions from pruned trees were then assessed against the hold-out data. Preliminary results from this analysis suggest that: 1) the relative importance and dependencies of biophysical drivers on forest structure are contingent upon the position of these forests along gradients of a limiting resource, 2) stem density shows a stronger dependence on water availability than tree size and 3) that the predictive power of abiotic variables are limited with our best models accounting for only 36-40 percent of the variance in the response. These results suggest that the response of forest structure to climate change may be highly idiosyncratic and difficult to predict using abiotic drivers alone.

A method to investigate the diffusion properties of nuclear calcium.

PubMed

Queisser, Gillian; Wittum, Gabriel

2011-10-01

Modeling biophysical processes in general requires knowledge about underlying biological parameters. The quality of simulation results is strongly influenced by the accuracy of these parameters, hence the identification of parameter values that the model includes is a major part of simulating biophysical processes. In many cases, secondary data can be gathered by experimental setups, which are exploitable by mathematical inverse modeling techniques. Here we describe a method for parameter identification of diffusion properties of calcium in the nuclei of rat hippocampal neurons. The method is based on a Gauss-Newton method for solving a least-squares minimization problem and was formulated in such a way that it is ideally implementable in the simulation platform uG. Making use of independently published space- and time-dependent calcium imaging data, generated from laser-assisted calcium uncaging experiments, here we could identify the diffusion properties of nuclear calcium and were able to validate a previously published model that describes nuclear calcium dynamics as a diffusion process.

Urban thermal environment and its biophysical parameters derived from satellite remote sensing imagery

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.

2013-10-01

In frame of global warming, the field of urbanization and urban thermal environment are important issues among scientists all over the world. This paper investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Bucharest metropolitan area of Romania based on satellite remote sensing imagery Landsat TM/ETM+, time series MODIS Terra/Aqua data and IKONOS acquired during 1990 - 2012 period. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also retrieved from thermal infrared band of Landsat TM/ETM+, from MODIS Terra/Aqua datasets. Based on these parameters, the urban growth, urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. Results indicated that the metropolitan area ratio of impervious surface in Bucharest increased significantly during two decades investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

Online determination of biophysical parameters of mucous membranes of a human body

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2013-07-01

We have developed a method for online determination of biophysical parameters of mucous membranes (MMs) of a human body (transport scattering coefficient, scattering anisotropy factor, haemoglobin concentration, degrees of blood oxygenation, average diameter of capillaries with blood) from measurements of spectral and spatial characteristics of diffuse reflection. The method is based on regression relationships between linearly independent components of the measured light signals and the unknown parameters of MMs, obtained by simulation of the radiation transfer in the MM under conditions of its general variability. We have proposed and justified the calibration-free fibre-optic method for determining the concentration of haemoglobin in MMs by measuring the light signals diffusely reflected by the tissue in four spectral regions at two different distances from the illumination spot. We have selected the optimal wavelengths of optical probing for the implementation of the method.

Reconstructed Historical Land Cover and Biophysical Parameters for Studies of Land-Atmosphere Interactions within the Eastern United States

NASA Technical Reports Server (NTRS)

Steyaert, Louis T.; Knox, Robert G.

2007-01-01

The local environment where we live within the Earth's biosphere is often taken for granted. This environment can vary depending on whether the land cover is a forest, grassland, wetland, water body, bare soil, pastureland, agricultural field, village, residential suburb, or an urban complex with concrete, asphalt, and large buildings. In general, the type and characteristics of land cover influence surface temperatures, sunlight exposure and duration, relative humidity, wind speed and direction, soil moisture amount, plant life, birds, and other wildlife in our backyards. The physical and biological properties (biophysical characteristics) of land cover help to determine our surface environment because they directly affect surface radiation, heat, and soil moisture processes, and also feedback to regional weather and climate. Depending on the spatial scale and land use intensity, land cover changes can have profound impacts on our local and regional environment. Over the past 350 years, the eastern half of the United States, an area extending from the grassland prairies of the Great Plains to the Gulf and Atlantic coasts, has experienced extensive land cover and land use changes that began with land clearing in the 1600s, led to extensive deforestation and intensive land use practices by 1920, and then evolved to the present-day landscape. Determining the consequences of such land cover changes on regional and global climate is a major research issue. Such research requires detailed historical land cover data and modeling experiments simulating historical climates. Given the need to understand the effects of historical land cover changes in the eastern United States, some questions include: - What were the most important land cover transformations and how did they alter biophysical characteristics of the land cover at key points in time since the mid-1600s? - How have land cover and land use changes over the past 350 years affected the land surface environment including surface weather, hydrologic, and climatic variability? - How do the potential effects of regional human-induced land cover change on the environment compare to similar changes that are caused by the natural variations of the Earth's climate system? To help answer these questions, we reconstructed a fractional land cover and biophysical parameter dataset for the eastern United States at 1650, 1850, 1920, and 1992 time-slices. Each land cover fraction is associated with a biophysical parameter class, a suite of parameters defining the biophysical characteristics of that kind of land cover. This new dataset is designed for use in computer models of land-atmosphere interactions, to understand and quantify the effects of historical land cover changes on the water, energy, and carbon cycles

Live-cell mass profiling: an emerging approach in quantitative biophysics.

PubMed

Zangle, Thomas A; Teitell, Michael A

2014-12-01

Cell mass, volume and growth rate are tightly controlled biophysical parameters in cellular development and homeostasis, and pathological cell growth defines cancer in metazoans. The first measurements of cell mass were made in the 1950s, but only recently have advances in computer science and microfabrication spurred the rapid development of precision mass-quantifying approaches. Here we discuss available techniques for quantifying the mass of single live cells with an emphasis on relative features, capabilities and drawbacks for different applications.

The application of multiple biophysical cues to engineer functional neocartilage for treatment of osteoarthritis. Part I: cellular response.

PubMed

Brady, Mariea A; Waldman, Stephen D; Ethier, C Ross

2015-02-01

Osteoarthritis (OA) is a complex disease of the joint for which current treatments are unsatisfactory, thus motivating development of tissue engineering (TE)-based therapies. To date, TE strategies have had some success, developing replacement tissue constructs with biochemical properties approaching that of native cartilage. However, poor biomechanical properties and limited postimplantation integration with surrounding tissue are major shortcomings that need to be addressed. Functional tissue engineering strategies that apply physiologically relevant biophysical cues provide a platform to improve TE constructs before implantation. In the previous decade, new experimental and theoretical findings in cartilage biomechanics and electromechanics have emerged, resulting in an increased understanding of the complex interplay of multiple biophysical cues in the extracellular matrix of the tissue. The effect of biophysical stimulation on cartilage, and the resulting chondrocyte-mediated biosynthesis, remodeling, degradation, and repair, has, therefore, been extensively explored by the TE community. This article compares and contrasts the cellular response of chondrocytes to multiple biophysical stimuli, and may be read in conjunction with its companion paper that compares and contrasts the subsequent intracellular signal transduction cascades. Mechanical, magnetic, and electrical stimuli promote proliferation, differentiation, and maturation of chondrocytes within established dose parameters or "biological windows." This knowledge will provide a framework for ongoing studies incorporating multiple biophysical cues in TE functional neocartilage for treatment of OA.

The application of multiple biophysical cues to engineer functional neocartilage for treatment of osteoarthritis. Part II: signal transduction.

PubMed

Brady, Mariea A; Waldman, Stephen D; Ethier, C Ross

2015-02-01

The unique mechanoelectrochemical environment of cartilage has motivated researchers to investigate the effect of multiple biophysical cues, including mechanical, magnetic, and electrical stimulation, on chondrocyte biology. It is well established that biophysical stimuli promote chondrocyte proliferation, differentiation, and maturation within "biological windows" of defined dose parameters, including mode, frequency, magnitude, and duration of stimuli (see companion review Part I: Cellular Response). However, the underlying molecular mechanisms and signal transduction pathways activated in response to multiple biophysical stimuli remain to be elucidated. Understanding the mechanisms of biophysical signal transduction will deepen knowledge of tissue organogenesis, remodeling, and regeneration and aiding in the treatment of pathologies such as osteoarthritis. Further, this knowledge will provide the tissue engineer with a potent toolset to manipulate and control cell fate and subsequently develop functional replacement cartilage. The aim of this article is to review chondrocyte signal transduction pathways in response to mechanical, magnetic, and electrical cues. Signal transduction does not occur along a single pathway; rather a number of parallel pathways appear to be activated, with calcium signaling apparently common to all three types of stimuli, though there are different modes of activation. Current tissue engineering strategies, such as the development of "smart" functionalized biomaterials that enable the delivery of growth factors or integration of conjugated nanoparticles, may further benefit from targeting known signal transduction pathways in combination with external biophysical cues.

On the relationship between ecosystem-scale hyperspectral reflectance and CO2 exchange in European mountain grasslands

NASA Astrophysics Data System (ADS)

Balzarolo, M.; Vescovo, L.; Hammerle, A.; Gianelle, D.; Papale, D.; Tomelleri, E.; Wohlfahrt, G.

2015-05-01

In this paper we explore the skill of hyperspectral reflectance measurements and vegetation indices (VIs) derived from these in estimating carbon dioxide (CO2) fluxes of grasslands. Hyperspectral reflectance data, CO2 fluxes and biophysical parameters were measured at three grassland sites located in European mountain regions using standardized protocols. The relationships between CO2 fluxes, ecophysiological variables, traditional VIs and VIs derived using all two-band combinations of wavelengths available from the whole hyperspectral data space were analysed. We found that VIs derived from hyperspectral data generally explained a large fraction of the variability in the investigated dependent variables but differed in their ability to estimate midday and daily average CO2 fluxes and various derived ecophysiological parameters. Relationships between VIs and CO2 fluxes and ecophysiological parameters were site-specific, likely due to differences in soils, vegetation parameters and environmental conditions. Chlorophyll and water-content-related VIs explained the largest fraction of variability in most of the dependent variables. Band selection based on a combination of a genetic algorithm with random forests (GA-rF) confirmed that it is difficult to select a universal band region suitable across the investigated ecosystems. Our findings have major implications for upscaling terrestrial CO2 fluxes to larger regions and for remote- and proximal-sensing sampling and analysis strategies and call for more cross-site synthesis studies linking ground-based spectral reflectance with ecosystem-scale CO2 fluxes.

GOSAILT: A hybrid of GOMS and SAILT with topography consideration

NASA Astrophysics Data System (ADS)

Wu, S.; Wen, J.

2017-12-01

Heterogeneous terrain significantly complicated the energy, mass and momentum exchange between the atmosphere and terrestrial ecosystem. Understanding of topographic effect on the forest reflectance is critical for biophysical parameters retrieval over rugged area. In this paper, a new hybrid bidirectional reflectance distribution function (BRDF) model of geometric optical mutual shadowing and scattering-from-arbitrarily-inclined-leaves model coupled topography (GOSAILT) for sloping forest was proposed. The effects of slope, aspect, gravity field of tree crown, multiple scattering scheme, and diffuse skylight are considered. The area proportions of scene components estimated by the GOSAILT model were compared with the geometric optical model for sloping terrains (GOST) model. The 3-D discrete anisotropic radiative transfer (DART) simulations were used to evaluate the performance of GOSAILT. The results indicate that the canopy reflectance is distorted by the slopes with a maximum variation of 78.3% in the red band and 17.3% in the NIR band on a steep 60 º slope. Compared with the DART simulations, the proposed GOSAILT model can capture anisotropic reflectance well with a determine coefficient (R2) of 0.9720 and 0.6701, root-mean-square error (RMSE) of 0.0024 and 0.0393, mean absolute percentage error of 2.4% and 4.61% for the red and near-infrared (NIR) band. The comparison results indicate the GOSAIL model can accurately reproducing the angular feature of discrete canopy over rugged terrain conditions. The GOSAILT model is promising for the land surface biophysical parameters retrieval (e.g. albedo, leaf area index) over the heterogeneous terrain.

Ecophysiology of nickel phytoaccumulation: a simplified biophysical approach.

PubMed

Coinchelin, David; Bartoli, François; Robin, Christophe; Echevarria, Guillaume

2012-10-01

Solute active transport or exclusion by plants can be identified by the values of the Transpiration Stream Concentration Factor (TSCF=xylem:solution solute concentration ratio). The aim of this study was to estimate this parameter for Ni uptake by the Ni-hyperaccumulator Leptoplax emarginata or the Ni-excluder Triticum aestivum cultivar 'Fidel'. The Intact Plant TSCF for nickel (IPTSCF(Ni)) was calculated as the ratio between the nickel mass accumulation in the leaves and the nickel concentration in solution per volume of water transpired. Predominantly, Ni active transport occurred for L. emarginata, with IPTSCF(Ni) values of 4.7-7.2 and convective component proportions of the root Ni uptake flow of only 15-20% for a range of Ni concentrations in solutions of 2-16 µmol Ni l(-1), regardless of the growth period and the time of Ni uptake. Hyperaccumulator roots were permeable to both water and nickel (mean reflection coefficient for Ni, σ(Ni), of 0.06), which was mainly attributed to an absence of exodermis. Results provide a new view of the mechanisms of Ni hyperaccumulation. By contrast, the wheat excluder was characterized by an extremely low mean IPTSCF(Ni) value of 0.006, characterizing a predominantly Ni sequestration in roots. From a methodological viewpoint, the 'microscopic' TSCF(Ni), measured directly on excised plants was 2.4 times larger than its recommended 'macroscopic' IPTSCF(Ni) counterpart. Overall, IPTSCF and σ determined on intact transpiring plants appeared to be very useful biophysical parameters in the study of the mechanisms involved in metal uptake and accumulation by plants, and in their modelling.

An In Situ and In Silico Evaluation of Biophysical Effects of 27 MHz Electromagnetic Whole Body Humans Exposure Expressed by the Limb Current

PubMed Central

2017-01-01

Objectives The aim was to evaluate correlations between biophysical effects of 27 MHz electromagnetic field exposure in humans (limb induced current (LIC)) and (1) parameters of affecting heterogeneous electric field and (2) body anthropometric properties, in order to improve the evaluation of electromagnetic environmental hazards. Methods Biophysical effects of exposure were studied in situ by measurements of LIC in 24 volunteers (at the ankle) standing near radio communication rod antenna and in silico in 4 numerical body phantoms exposed near a model of antenna. Results Strong, positive, statistically significant correlations were found in all exposure scenarios between LIC and body volume index (body height multiplied by mass) (r > 0.7; p < 0.001). The most informative exposure parameters, with respect to the evaluation of electromagnetic hazards by measurements (i.e., the ones strongest correlated with LIC), were found to be the value of electric field (unperturbed field, in the absence of body) in front of the chest (50 cm from body axis) or the maximum value in space occupied by human. Such parameters were not analysed in previous studies. Conclusions Exposed person's body volume and electric field strength in front of the chest determine LIC in studied exposure scenarios, but their wider applicability needs further studies. PMID:28758119

Safety Assessment of Tretinoin Loaded Nano Emulsion and Nanostructured Lipid Carriers: A Non-invasive Trial on Human Volunteers.

PubMed

Nasrollahi, Saman Ahmad; Hassanzade, Hurnaz; Moradi, Azadeh; Sabouri, Mahsa; Samadi, Aniseh; Kashani, Mansour Nassiri; Firooz, Alireza

2017-01-01

Topical application of tretinoin (TRE) is followed by a high incidence of side effects. One method to overcome the problem is loading TRE into lipid nanoparticles. The potential safety of the nanoparticle materials has been always considered as a major concern. In this in vivo study, changes in human skin biophysical parameters including hydration, TEWL, erythema, and pH have been used to determine the safety of tretinoin loaded nano emulsion (NE) and nanostructured lipid carriers (NLC). TRE loaded NE and NLC were prepared using a high pressure homogenizer. Skin biophysical parameters were measured on the volar forearms of twenty healthy volunteers, before and after applying TRE-NE and TRE-NLC lotions. All the measurements were done using respective probes of MPA 580Cutometer®. We obtained particles of nanometric size (<130 nm) with narrow distribution and optimal physical stability. None of the formulations made any statistically significant change in any of the measured skin properties. P-values were 0.646, 0.139, 0.386, 0.169 after applying TRE-NE and 0.508, 0.051, 0.139, 0.333 after applying TRE-NLC, respectively. Both formulations are reasonably safe to apply on human skin and topical application of TRE-NE and TRE-NLC had almost similar effects on skin biophysical parameters. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

VitiCanopy: A Free Computer App to Estimate Canopy Vigor and Porosity for Grapevine

PubMed Central

De Bei, Roberta; Fuentes, Sigfredo; Gilliham, Matthew; Tyerman, Steve; Edwards, Everard; Bianchini, Nicolò; Smith, Jason; Collins, Cassandra

2016-01-01

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants. PMID:27120600

VitiCanopy: A Free Computer App to Estimate Canopy Vigor and Porosity for Grapevine.

PubMed

De Bei, Roberta; Fuentes, Sigfredo; Gilliham, Matthew; Tyerman, Steve; Edwards, Everard; Bianchini, Nicolò; Smith, Jason; Collins, Cassandra

2016-04-23

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants.

Generalized Recurrent Neural Network accommodating Dynamic Causal Modeling for functional MRI analysis.

PubMed

Wang, Yuan; Wang, Yao; Lui, Yvonne W

2018-05-18

Dynamic Causal Modeling (DCM) is an advanced biophysical model which explicitly describes the entire process from experimental stimuli to functional magnetic resonance imaging (fMRI) signals via neural activity and cerebral hemodynamics. To conduct a DCM study, one needs to represent the experimental stimuli as a compact vector-valued function of time, which is hard in complex tasks such as book reading and natural movie watching. Deep learning provides the state-of-the-art signal representation solution, encoding complex signals into compact dense vectors while preserving the essence of the original signals. There is growing interest in using Recurrent Neural Networks (RNNs), a major family of deep learning techniques, in fMRI modeling. However, the generic RNNs used in existing studies work as black boxes, making the interpretation of results in a neuroscience context difficult and obscure. In this paper, we propose a new biophysically interpretable RNN built on DCM, DCM-RNN. We generalize the vanilla RNN and show that DCM can be cast faithfully as a special form of the generalized RNN. DCM-RNN uses back propagation for parameter estimation. We believe DCM-RNN is a promising tool for neuroscience. It can fit seamlessly into classical DCM studies. We demonstrate face validity of DCM-RNN in two principal applications of DCM: causal brain architecture hypotheses testing and effective connectivity estimation. We also demonstrate construct validity of DCM-RNN in an attention-visual experiment. Moreover, DCM-RNN enables end-to-end training of DCM and representation learning deep neural networks, extending DCM studies to complex tasks. Copyright © 2018 Elsevier Inc. All rights reserved.

Carbon-Water-Energy Relations for Selected River Basins

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1998-01-01

A biophysical process-based model was run using satellite, assimilated and ancillary data for four years (1987-1990) to calculate components of total evaporation (transpiration, interception, soil and snow evaporation), net radiation, absorbed photosynthetically active radiation and net primary productivity over the global land surface. Satellite observations provided fractional vegetation cover, solar and photosynthetically active radiation incident of the surface, surface albedo, fractional cloud cover, air temperature and vapor pressure. The friction velocity and surface air pressure are obtained from a four dimensional data assimilation results, while precipitation is either only surface observations or a blended product of surface and satellite observations. All surface and satellite data are monthly mean values; precipitation has been disaggregated into daily values. All biophysical parameters of the model are prescribed according to published records. From these global land surface calculations results for river basins are derived using digital templates of basin boundaries. Comparisons with field observations (micrometeorologic, catchment water balance, biomass production) and atmospheric water budget analysis for monthly evaporation from six river basins have been done to assess errors in the calculations. Comparisons are also made with previous estimates of zonal variations of evaporation and net primary productivity. Efficiencies of transpiration, total evaporation and radiation use, and evaporative fraction for selected river basins will be presented.

Characterizing Facial Skin Ageing in Humans: Disentangling Extrinsic from Intrinsic Biological Phenomena

PubMed Central

Trojahn, Carina; Dobos, Gabor; Lichterfeld, Andrea; Blume-Peytavi, Ulrike; Kottner, Jan

2015-01-01

Facial skin ageing is caused by intrinsic and extrinsic mechanisms. Intrinsic ageing is highly related to chronological age. Age related skin changes can be measured using clinical and biophysical methods. The aim of this study was to evaluate whether and how clinical characteristics and biophysical parameters are associated with each other with and without adjustment for chronological age. Twenty-four female subjects of three age groups were enrolled. Clinical assessments (global facial skin ageing, wrinkling, and sagging), and biophysical measurements (roughness, colour, skin elasticity, and barrier function) were conducted at both upper cheeks. Pearson's correlations and linear regression models adjusted for age were calculated. Most of the measured parameters were correlated with chronological age (e.g., association with wrinkle score, r = 0.901) and with each other (e.g., residual skin deformation and wrinkle score, r = 0.606). After statistical adjustment for age, only few associations remained (e.g., mean roughness (R z) and luminance (L *),  β = −0.507, R 2 = 0.377). Chronological age as surrogate marker for intrinsic ageing has the most important influence on most facial skin ageing signs. Changes in skin elasticity, wrinkling, sagging, and yellowness seem to be caused by additional extrinsic ageing. PMID:25767806

Emergent relation between surface vapor conductance and relative humidity profiles yields evaporation rates from weather data

NASA Astrophysics Data System (ADS)

Salvucci, Guido D.; Gentine, Pierre

2013-04-01

The ability to predict terrestrial evapotranspiration (E) is limited by the complexity of rate-limiting pathways as water moves through the soil, vegetation (roots, xylem, stomata), canopy air space, and the atmospheric boundary layer. The impossibility of specifying the numerous parameters required to model this process in full spatial detail has necessitated spatially upscaled models that depend on effective parameters such as the surface vapor conductance (Csurf). Csurf accounts for the biophysical and hydrological effects on diffusion through the soil and vegetation substrate. This approach, however, requires either site-specific calibration of Csurf to measured E, or further parameterization based on metrics such as leaf area, senescence state, stomatal conductance, soil texture, soil moisture, and water table depth. Here, we show that this key, rate-limiting, parameter can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and E. The relation is that the vertical variance of the relative humidity profile is less than would occur for increased or decreased evaporation rates, suggesting that land-atmosphere feedback processes minimize this variance. It is found to hold over a wide range of climate conditions (arid-humid) and limiting factors (soil moisture, leaf area, energy). With this relation, estimates of E and Csurf can be obtained globally from widely available meteorological measurements, many of which have been archived since the early 1900s. In conjunction with precipitation and stream flow, long-term E estimates provide insights and empirical constraints on projected accelerations of the hydrologic cycle.

Emergent relation between surface vapor conductance and relative humidity profiles yields evaporation rates from weather data.

PubMed

Salvucci, Guido D; Gentine, Pierre

2013-04-16

The ability to predict terrestrial evapotranspiration (E) is limited by the complexity of rate-limiting pathways as water moves through the soil, vegetation (roots, xylem, stomata), canopy air space, and the atmospheric boundary layer. The impossibility of specifying the numerous parameters required to model this process in full spatial detail has necessitated spatially upscaled models that depend on effective parameters such as the surface vapor conductance (C(surf)). C(surf) accounts for the biophysical and hydrological effects on diffusion through the soil and vegetation substrate. This approach, however, requires either site-specific calibration of C(surf) to measured E, or further parameterization based on metrics such as leaf area, senescence state, stomatal conductance, soil texture, soil moisture, and water table depth. Here, we show that this key, rate-limiting, parameter can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and E. The relation is that the vertical variance of the relative humidity profile is less than would occur for increased or decreased evaporation rates, suggesting that land-atmosphere feedback processes minimize this variance. It is found to hold over a wide range of climate conditions (arid-humid) and limiting factors (soil moisture, leaf area, energy). With this relation, estimates of E and C(surf) can be obtained globally from widely available meteorological measurements, many of which have been archived since the early 1900s. In conjunction with precipitation and stream flow, long-term E estimates provide insights and empirical constraints on projected accelerations of the hydrologic cycle.

Cell migration through connective tissue in 3-D

NASA Astrophysics Data System (ADS)

Fabry, Ben

2008-03-01

A prerequisite for metastasis formation is the ability of tumor cells to invade and migrate through connective tissue. Four key components endow tumor cells with this ability: secretion of matrix-degrading enzymes, firm but temporary adhesion onto connective tissue fibers, contractile force generation, and rapid remodeling of cytoskeletal structures. Cell adhesion, contraction, and cytoskeletal remodeling are biomechanical parameter that can be measured on single cells using a panel of biophysical methods. We use 2-D and 3-D traction microscopy to measure contractile forces; magnetic tweezer microrheology to estimate adhesion strengths, cytoskeletal stiffness and molecular turn-over rates; and nanoscale particle tracking to measure cytoskeletal remodeling. On a wide range of tumor cell lines we could show that cell invasiveness correlates with increased expression of integrin adhesion receptors, increased contractile force generation, and increased speed of cytoskeletal reorganization. Each of those biomechanical parameters, however, varied considerably between cell lines of similar invasivity, suggesting that tumor cells employ multiple invasion strategies that cannot be unambiguously characterized using a single assay.

A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons

PubMed Central

Tian, Tian; Salis, Howard M.

2015-01-01

Natural and engineered genetic systems require the coordinated expression of proteins. In bacteria, translational coupling provides a genetically encoded mechanism to control expression level ratios within multi-cistronic operons. We have developed a sequence-to-function biophysical model of translational coupling to predict expression level ratios in natural operons and to design synthetic operons with desired expression level ratios. To quantitatively measure ribosome re-initiation rates, we designed and characterized 22 bi-cistronic operon variants with systematically modified intergenic distances and upstream translation rates. We then derived a thermodynamic free energy model to calculate de novo initiation rates as a result of ribosome-assisted unfolding of intergenic RNA structures. The complete biophysical model has only five free parameters, but was able to accurately predict downstream translation rates for 120 synthetic bi-cistronic and tri-cistronic operons with rationally designed intergenic regions and systematically increased upstream translation rates. The biophysical model also accurately predicted the translation rates of the nine protein atp operon, compared to ribosome profiling measurements. Altogether, the biophysical model quantitatively predicts how translational coupling controls protein expression levels in synthetic and natural bacterial operons, providing a deeper understanding of an important post-transcriptional regulatory mechanism and offering the ability to rationally engineer operons with desired behaviors. PMID:26117546

Effect of maternal exercises on biophysical fetal and maternal parameters: a transversal study

PubMed Central

dos Santos, Caroline Mombaque; dos Santos, Wendel Mombaque; Gallarreta, Francisco Maximiliano Pancich; Pigatto, Camila; Portela, Luiz Osório Cruz; de Morais, Edson Nunes

2016-01-01

ABSTRACT Objective To evaluate the acute effects of maternal and fetal hemodynamic responses in pregnant women submitted to fetal Doppler and an aerobic physical exercise test according to the degree of effort during the activity and the impact on the well-being. Methods Transversal study with low risk pregnant women, obtained by convenience sample with gestational age between 26 to 34 weeks. The participants carry out a progressive exercise test. Results After the exercise session, reduced resistance (p=0.02) and pulsatility indices (p=0.01) were identified in the umbilical artery; however, other Doppler parameters analyzed, in addition to cardiotocography and fetal biophysical profile did not achieve significant change. Maternal parameters obtained linear growth with activity, but it was not possible to establish a standard with the Borg scale, and oxygen saturation remained stable. Conclusion A short submaximal exercise had little effect on placental blood flow after exercise in pregnancies without complications, corroborating that healthy fetus maintains homeostasis even in situations that alter maternal hemodynamics. PMID:28076590

[Influence of accessories mixing ratio on sludge biophysical co-drying].

PubMed

Yang, Jin-Long; Du, Qiong; Li, Dong; Han, Rong; Zhao, Yan; Wang, Hong-Tao

2011-08-01

Parameters (temperature, water content and so on) in the process of sludge biophysical co-drying were studied in self-made biophysical co-drying reactor. The sludge: tree bark: recycled sludge was set as 7: 3: 0.5, 9: 3: 0.5, 12: 3: 0.5 respectively. The results suggested that sludge temperature first increased then decreased along with drying time, water content decreased in the first 96 h, then had no obvious variability. While sludge: tree bark: recycled sludge was 9: 3: 0.5, the temperature of sludge spiraling, received to max 67 degrees C at 48 h under three different accessories mixture ratio, and was kept for 72 h above 55 degrees C, then spiraling, the final water content of sludge decreased from 74.1% to 61.8%, received the optimal water content removing rate 43.5%. Accessories mixing ratio had important influence on the process of sludge biophysical co-drying, sludge with proper mixing ratio can modify the structure of sludge, improve sludge permeability, arouse and keep microorganic activity, which will enhance sludge temperature and strengthen water content removal rate.

Predicting the Presence of Scyphozoan Jellyfish in the Gulf of Mexico Using a Biophysical Model

NASA Astrophysics Data System (ADS)

Aleksa, K. T.; Nero, R. W.; Wiggert, J. D.; Graham, W. M.

2016-02-01

The study and quantification of jellyfish (cnidarian medusae and ctenophores) is difficult due to their fragile body plan and a composition similar to their environment. The development of a predictive biophysical jellyfish model would be the first of its kind for the Gulf of Mexico and could provide assistance in ecological research and human interactions. In this study, the collection data of two scyphozoan medusae, Chrysaora quinquecirrha and Aurelia spp., were extracted from SEAMAP trawling surveys and were used to determine biophysical predictors for the presence of large jellyfish medusae in the Gulf of Mexico. Both in situ and remote sensing measurements from 2003 to 2013 were obtained. Logistic regressions were then applied to 27 biophysical parameters derived from these data to explore and determine significant predictors for the presence of medusae. Significant predictors identified by this analysis included water temperature, chlorophyll a, turbidity, distance from shore, and salinity. Future application for this model include foraging assessment of gelatinous predators as well as possible near real time monitoring of the distribution and movement of these medusae in the Gulf of Mexico.

Forest Attributes from Radar Interferometric Structure and its Fusion with Optical Remote Sensing

NASA Technical Reports Server (NTRS)

Treuhaft, Robert N.; Law, Beverly E.; Asner, Gregory P.

2004-01-01

The possibility of global, three-dimensional remote sensing of forest structure with interferometric synthetic aperture radar (InSAR) bears on important forest ecological processes, particularly the carbon cycle. InSAR supplements two-dimensional remote sensing with information in the vertical dimension. Its strengths in potential for global coverage complement those of lidar (light detecting and ranging), which has the potential for high-accuracy vertical profiles over small areas. InSAR derives its sensitivity to forest vertical structure from the differences in signals received by two, spatially separate radar receivers. Estimation of parameters describing vertical structure requires multiple-polarization, multiple-frequency, or multiple-baseline InSAR. Combining InSAR with complementary remote sensing techniques, such as hyperspectral optical imaging and lidar, can enhance vertical-structure estimates and consequent biophysical quantities of importance to ecologists, such as biomass. Future InSAR experiments will supplement recent airborne and spaceborne demonstrations, and together with inputs from ecologists regarding structure, they will suggest designs for future spaceborne strategies for measuring global vegetation structure.

The Role of Parvalbumin, Sarcoplasmatic Reticulum Calcium Pump Rate, Rates of Cross-Bridge Dynamics, and Ryanodine Receptor Calcium Current on Peripheral Muscle Fatigue: A Simulation Study

PubMed Central

Neumann, Verena

2016-01-01

A biophysical model of the excitation-contraction pathway, which has previously been validated for slow-twitch and fast-twitch skeletal muscles, is employed to investigate key biophysical processes leading to peripheral muscle fatigue. Special emphasis hereby is on investigating how the model's original parameter sets can be interpolated such that realistic behaviour with respect to contraction time and fatigue progression can be obtained for a continuous distribution of the model's parameters across the muscle units, as found for the functional properties of muscles. The parameters are divided into 5 groups describing (i) the sarcoplasmatic reticulum calcium pump rate, (ii) the cross-bridge dynamics rates, (iii) the ryanodine receptor calcium current, (iv) the rates of binding of magnesium and calcium ions to parvalbumin and corresponding dissociations, and (v) the remaining processes. The simulations reveal that the first two parameter groups are sensitive to contraction time but not fatigue, the third parameter group affects both considered properties, and the fourth parameter group is only sensitive to fatigue progression. Hence, within the scope of the underlying model, further experimental studies should investigate parvalbumin dynamics and the ryanodine receptor calcium current to enhance the understanding of peripheral muscle fatigue. PMID:27980606

Tree crown structural characterization: A study using terrestrial laser scanning and three-dimensional radiative transfer modeling

NASA Astrophysics Data System (ADS)

Moorthy, Inian

Spectroscopic observational data for vegetated environments, have been coupled with 3D physically-based radiative transfer models for retrievals of biochemical and biophysical indicators of vegetation health and condition. With the recent introduction of Terrestrial Laser Scanning (TLS) units, there now exists a means of rapidly measuring intricate structural details of vegetation canopies, which can also serve as input into 3D radiative transfer models. In this investigation, Intelligent Laser Ranging and Imaging System (ILRIS-3D) data was acquired of individual tree crowns in laboratory, and field-based experiments. The ILRIS-3D uses the Time-Of-Flight (TOF) principle to measure the distances of objects based on the time interval between laser pulse exitance and return, upon reflection from an object. At the laboratory-level, this exploratory study demonstrated and validated innovative approaches for retrieving crown-level estimates of Leaf Area Index (LAI) (r2 = 0.98, rmse = 0.26m2/m2), a critical biophysical parameter for vegetation monitoring and modeling. These methods were implemented and expanded in field experiments conducted in olive (Olea europaea L.) orchards in Cordoba, Spain, where ILRIS-3D observations for 24 structurally-variable trees were made. Robust methodologies were developed to characterize diagnostic architectural parameters, such as tree height (r2 = 0.97, rmse = 0.21m), crown width (r 2 = 0.98, rmse = 0.12m), crown height (r2 = 0.81, rmse = 0.11m), crown volume (r2 = 0.99, rmse = 2.6m3), and LAI (r2 = 0.76, rmse = 0.27m2/ m2). These parameters were subsequently used as direct inputs into the Forest LIGHT (FLIGHT) 3D ray tracing model for characterization of the spectral behavior of the olive crowns. Comparisons between FLIGHT-simulated spectra and measured data showed small differences in the visible (< 3%) and near infrared (< 10%) spectral ranges. These differences between model simulations and measurements were significantly correlated to TLS-derived tree crown complexity metrics. The specific implications of internal crown complexity on estimating leaf chlorophyll concentration, a pertinent physiological health indicator, is highlighted. This research demonstrates that TLS systems can potentially be the new observational tool and benchmark for precise characterization of vegetation architecture for synergy with 3D radiative transfer models for improved operational management of agricultural crops.

The Instrumentation of a Microfluidic Analyzer Enabling the Characterization of the Specific Membrane Capacitance, Cytoplasm Conductivity, and Instantaneous Young's Modulus of Single Cells.

PubMed

Wang, Ke; Zhao, Yang; Chen, Deyong; Huang, Chengjun; Fan, Beiyuan; Long, Rong; Hsieh, Chia-Hsun; Wang, Junbo; Wu, Min-Hsien; Chen, Jian

2017-06-19

This paper presents the instrumentation of a microfluidic analyzer enabling the characterization of single-cell biophysical properties, which includes seven key components: a microfluidic module, a pressure module, an imaging module, an impedance module, two LabVIEW platforms for instrument operation and raw data processing, respectively, and a Python code for data translation. Under the control of the LabVIEW platform for instrument operation, the pressure module flushes single cells into the microfluidic module with raw biophysical parameters sampled by the imaging and impedance modules and processed by the LabVIEW platform for raw data processing, which were further translated into intrinsic cellular biophysical parameters using the code developed in Python. Based on this system, specific membrane capacitance, cytoplasm conductivity, and instantaneous Young's modulus of three cell types were quantified as 2.76 ± 0.57 μF/cm², 1.00 ± 0.14 S/m, and 3.79 ± 1.11 kPa for A549 cells ( n cell = 202); 1.88 ± 0.31 μF/cm², 1.05 ± 0.16 S/m, and 3.74 ± 0.75 kPa for 95D cells ( n cell = 257); 2.11 ± 0.38 μF/cm², 0.87 ± 0.11 S/m, and 5.39 ± 0.89 kPa for H460 cells ( n cell = 246). As a semi-automatic instrument with a throughput of roughly 1 cell per second, this prototype instrument can be potentially used for the characterization of cellular biophysical properties.

The Instrumentation of a Microfluidic Analyzer Enabling the Characterization of the Specific Membrane Capacitance, Cytoplasm Conductivity, and Instantaneous Young’s Modulus of Single Cells

PubMed Central

Wang, Ke; Zhao, Yang; Chen, Deyong; Huang, Chengjun; Fan, Beiyuan; Long, Rong; Hsieh, Chia-Hsun; Wang, Junbo; Wu, Min-Hsien; Chen, Jian

2017-01-01

This paper presents the instrumentation of a microfluidic analyzer enabling the characterization of single-cell biophysical properties, which includes seven key components: a microfluidic module, a pressure module, an imaging module, an impedance module, two LabVIEW platforms for instrument operation and raw data processing, respectively, and a Python code for data translation. Under the control of the LabVIEW platform for instrument operation, the pressure module flushes single cells into the microfluidic module with raw biophysical parameters sampled by the imaging and impedance modules and processed by the LabVIEW platform for raw data processing, which were further translated into intrinsic cellular biophysical parameters using the code developed in Python. Based on this system, specific membrane capacitance, cytoplasm conductivity, and instantaneous Young’s modulus of three cell types were quantified as 2.76 ± 0.57 μF/cm2, 1.00 ± 0.14 S/m, and 3.79 ± 1.11 kPa for A549 cells (ncell = 202); 1.88 ± 0.31 μF/cm2, 1.05 ± 0.16 S/m, and 3.74 ± 0.75 kPa for 95D cells (ncell = 257); 2.11 ± 0.38 μF/cm2, 0.87 ± 0.11 S/m, and 5.39 ± 0.89 kPa for H460 cells (ncell = 246). As a semi-automatic instrument with a throughput of roughly 1 cell per second, this prototype instrument can be potentially used for the characterization of cellular biophysical properties. PMID:28629175

Mathematical model of cycad cones' thermogenic temperature responses: inverse calorimetry to estimate metabolic heating rates.

PubMed

Roemer, R B; Booth, D; Bhavsar, A A; Walter, G H; Terry, L I

2012-12-21

A mathematical model based on conservation of energy has been developed and used to simulate the temperature responses of cones of the Australian cycads Macrozamia lucida and Macrozamia. macleayi during their daily thermogenic cycle. These cones generate diel midday thermogenic temperature increases as large as 12 °C above ambient during their approximately two week pollination period. The cone temperature response model is shown to accurately predict the cones' temperatures over multiple days as based on simulations of experimental results from 28 thermogenic events from 3 different cones, each simulated for either 9 or 10 sequential days. The verified model is then used as the foundation of a new, parameter estimation based technique (termed inverse calorimetry) that estimates the cones' daily metabolic heating rates from temperature measurements alone. The inverse calorimetry technique's predictions of the major features of the cones' thermogenic metabolism compare favorably with the estimates from conventional respirometry (indirect calorimetry). Because the new technique uses only temperature measurements, and does not require measurements of oxygen consumption, it provides a simple, inexpensive and portable complement to conventional respirometry for estimating metabolic heating rates. It thus provides an additional tool to facilitate field and laboratory investigations of the bio-physics of thermogenic plants. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimal Background Estimators in Single-Molecule FRET Microscopy.

PubMed

Preus, Søren; Hildebrandt, Lasse L; Birkedal, Victoria

2016-09-20

Single-molecule total internal reflection fluorescence (TIRF) microscopy constitutes an umbrella of powerful tools that facilitate direct observation of the biophysical properties, population heterogeneities, and interactions of single biomolecules without the need for ensemble synchronization. Due to the low signal/noise ratio in single-molecule TIRF microscopy experiments, it is important to determine the local background intensity, especially when the fluorescence intensity of the molecule is used quantitatively. Here we compare and evaluate the performance of different aperture-based background estimators used particularly in single-molecule Förster resonance energy transfer. We introduce the general concept of multiaperture signatures and use this technique to demonstrate how the choice of background can affect the measured fluorescence signal considerably. A new, to our knowledge, and simple background estimator is proposed, called the local statistical percentile (LSP). We show that the LSP background estimator performs as well as current background estimators at low molecular densities and significantly better in regions of high molecular densities. The LSP background estimator is thus suited for single-particle TIRF microscopy of dense biological samples in which the intensity itself is an observable of the technique. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Mesoscale, Radiometrically Referenced, Multi-Temporal Hyperspectral Data for Co2 Leak Detection by Locating Spatial Variation of Biophysically Relevant Parameters

NASA Astrophysics Data System (ADS)

McCann, Cooper Patrick

Low-cost flight-based hyperspectral imaging systems have the potential to provide valuable information for ecosystem and environmental studies as well as aide in land management and land health monitoring. This thesis describes (1) a bootstrap method of producing mesoscale, radiometrically-referenced hyperspectral data using the Landsat surface reflectance (LaSRC) data product as a reference target, (2) biophysically relevant basis functions to model the reflectance spectra, (3) an unsupervised classification technique based on natural histogram splitting of these biophysically relevant parameters, and (4) local and multi-temporal anomaly detection. The bootstrap method extends standard processing techniques to remove uneven illumination conditions between flight passes, allowing the creation of radiometrically self-consistent data. Through selective spectral and spatial resampling, LaSRC data is used as a radiometric reference target. Advantages of the bootstrap method include the need for minimal site access, no ancillary instrumentation, and automated data processing. Data from a flight on 06/02/2016 is compared with concurrently collected ground based reflectance spectra as a means of validation achieving an average error of 2.74%. Fitting reflectance spectra using basis functions, based on biophysically relevant spectral features, allows both noise and data reductions while shifting information from spectral bands to biophysical features. Histogram splitting is used to determine a clustering based on natural splittings of these fit parameters. The Indian Pines reference data enabled comparisons of the efficacy of this technique to established techniques. The splitting technique is shown to be an improvement over the ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. This improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA. Three hyperspectral flights over the Kevin Dome area, covering 1843 ha, acquired 06/21/2014, 06/24/2015 and 06/26/2016 are examined with different methods of anomaly detection. Detection of anomalies within a single data set is examined to determine, on a local scale, areas that are significantly different from the surrounding area. Additionally, the detection and identification of persistent anomalies and non-persistent anomalies was investigated across multiple data sets.

Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model

NASA Astrophysics Data System (ADS)

di Vittorio, A. V.; Anderson, R. S.; Miller, N. L.; Running, S. W.

2009-12-01

Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.

Climate Regulation Services of Natural and Managed Ecosystems of the Americas

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Snyder, P. K.; Twine, T. E.; Costa, M. H.; Cuadra, S.; DeLucia, E. H.

2011-12-01

Terrestrial ecosystems regulate climate through both biogeochemical mechanisms (greenhouse gas regulation) and biophysical mechanisms (regulation of water and energy). Land management therefore provides some of the most effective strategies for climate change mitigation. However, most policies aimed at climate protection through land management, including UNFCCC mechanisms and bioenergy sustainability standards, account only for biogeochemical climate services. By ignoring biophysical climate regulation services that in some cases offset the biogeochemical regulation services, these policies run the risk of failing to advance the best climate solutions. Quantifying the combined value of biogeochemical and biophysical climate regulation services remains an important challenge. Here, we use a combination of data synthesis and modeling to quantify how biogeochemical and biophysical effects combine to shape the climate regulation value (CRV) of 18 natural and managed ecosystem types across the Western Hemisphere. Natural ecosystems generally had higher CRVs than agroecosystems, largely driven by differences in biogeochemical services. Biophysical contributions ranged from minimal to dominant. They were highly variable in space and across ecosystem types, and their relative importance varied strongly with the spatio-temporal scale of analysis. Our findings pertain to current efforts to protect climate through land management. Specifically, they reinforce the importance of protecting tropical forests and recent findings that the climatic effects of bioenergy production may be somewhat more positive than previously estimated. Given that biophysical effects in some cases dominate, ensuring effective climate protection through land management requires consideration of combined biogeochemical and biophysical climate regulation services. While quantification of ecosystem climate services is necessarily complex, our CRV index serves as one potential approach to measure the full climate services of terrestrial ecosystems.

On the complexity of Engh and Huber refinement restraints: the angle τ as example

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

Touw, Wouter G.; Vriend, Gert, E-mail: vriend@cmbi.ru.nl

2010-12-01

The angle τ (backbone N—C{sup α}—C) is the most contested Engh and Huber refinement target parameter. It is shown that this parameter is ‘correct’ as a PDB-wide average, but can be improved by taking into account residue types, secondary structures and many other aspects of our knowledge of the biophysical relations between residue type and protein structure. The Engh and Huber parameters for bond lengths and bond angles have been used uncontested in macromolecular structure refinement from 1991 until very recently, despite critical discussion of their ubiquitous validity by many authors. An extensive analysis of the backbone angle τ (N—C{supmore » α}—C) illustrates that the Engh and Huber parameters can indeed be improved and a recent study [Tronrud et al. (2010 ▶), Acta Cryst. D66, 834–842] confirms these ideas. However, the present study of τ shows that improving the Engh and Huber parameters will be considerably more complex than simply making the parameters a function of the backbone ϕ, ψ angles. Many other aspects, such as the cooperativity of hydrogen bonds, the bending of secondary-structure elements and a series of biophysical aspects of the 20 amino-acid types, will also need to be taken into account. Different sets of Engh and Huber parameters will be needed for conceptually different refinement programs.« less

Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest

NASA Astrophysics Data System (ADS)

Ali, Abebe Mohammed; Darvishzadeh, Roshanak; Skidmore, Andrew K.; Duren, Iris van; Heiden, Uta; Heurich, Marco

2016-03-01

Assessments of ecosystem functioning rely heavily on quantification of vegetation properties. The search is on for methods that produce reliable and accurate baseline information on plant functional traits. In this study, the inversion of the PROSPECT radiative transfer model was used to estimate two functional leaf traits: leaf dry matter content (LDMC) and specific leaf area (SLA). Inversion of PROSPECT usually aims at quantifying its direct input parameters. This is the first time the technique has been used to indirectly model LDMC and SLA. Biophysical parameters of 137 leaf samples were measured in July 2013 in the Bavarian Forest National Park, Germany. Spectra of the leaf samples were measured using an ASD FieldSpec3 equipped with an integrating sphere. PROSPECT was inverted using a look-up table (LUT) approach. The LUTs were generated with and without using prior information. The effect of incorporating prior information on the retrieval accuracy was studied before and after stratifying the samples into broadleaf and conifer categories. The estimated values were evaluated using R2 and normalized root mean square error (nRMSE). Among the retrieved variables the lowest nRMSE (0.0899) was observed for LDMC. For both traits higher R2 values (0.83 for LDMC and 0.89 for SLA) were discovered in the pooled samples. The use of prior information improved accuracy of the retrieved traits. The strong correlation between the estimated traits and the NIR/SWIR region of the electromagnetic spectrum suggests that these leaf traits could be assessed at canopy level by using remotely sensed data.

Functional identification of spike-processing neural circuits.

PubMed

Lazar, Aurel A; Slutskiy, Yevgeniy B

2014-02-01

We introduce a novel approach for a complete functional identification of biophysical spike-processing neural circuits. The circuits considered accept multidimensional spike trains as their input and comprise a multitude of temporal receptive fields and conductance-based models of action potential generation. Each temporal receptive field describes the spatiotemporal contribution of all synapses between any two neurons and incorporates the (passive) processing carried out by the dendritic tree. The aggregate dendritic current produced by a multitude of temporal receptive fields is encoded into a sequence of action potentials by a spike generator modeled as a nonlinear dynamical system. Our approach builds on the observation that during any experiment, an entire neural circuit, including its receptive fields and biophysical spike generators, is projected onto the space of stimuli used to identify the circuit. Employing the reproducing kernel Hilbert space (RKHS) of trigonometric polynomials to describe input stimuli, we quantitatively describe the relationship between underlying circuit parameters and their projections. We also derive experimental conditions under which these projections converge to the true parameters. In doing so, we achieve the mathematical tractability needed to characterize the biophysical spike generator and identify the multitude of receptive fields. The algorithms obviate the need to repeat experiments in order to compute the neurons' rate of response, rendering our methodology of interest to both experimental and theoretical neuroscientists.

PRince: a web server for structural and physicochemical analysis of protein-RNA interface.

PubMed

Barik, Amita; Mishra, Abhishek; Bahadur, Ranjit Prasad

2012-07-01

We have developed a web server, PRince, which analyzes the structural features and physicochemical properties of the protein-RNA interface. Users need to submit a PDB file containing the atomic coordinates of both the protein and the RNA molecules in complex form (in '.pdb' format). They should also mention the chain identifiers of interacting protein and RNA molecules. The size of the protein-RNA interface is estimated by measuring the solvent accessible surface area buried in contact. For a given protein-RNA complex, PRince calculates structural, physicochemical and hydration properties of the interacting surfaces. All these parameters generated by the server are presented in a tabular format. The interacting surfaces can also be visualized with software plug-in like Jmol. In addition, the output files containing the list of the atomic coordinates of the interacting protein, RNA and interface water molecules can be downloaded. The parameters generated by PRince are novel, and users can correlate them with the experimentally determined biophysical and biochemical parameters for better understanding the specificity of the protein-RNA recognition process. This server will be continuously upgraded to include more parameters. PRince is publicly accessible and free for use. Available at http://www.facweb.iitkgp.ernet.in/~rbahadur/prince/home.html.

Dynamics of a modified Hindmarsh-Rose neural model with random perturbations: Moment analysis and firing activities

NASA Astrophysics Data System (ADS)

Mondal, Argha; Upadhyay, Ranjit Kumar

2017-11-01

In this paper, an attempt has been made to understand the activity of mean membrane voltage and subsidiary system variables with moment equations (i.e., mean, variance and covariance's) under noisy environment. We consider a biophysically plausible modified Hindmarsh-Rose (H-R) neural system injected by an applied current exhibiting spiking-bursting phenomenon. The effects of predominant parameters on the dynamical behavior of a modified H-R system are investigated. Numerically, it exhibits period-doubling, period halving bifurcation and chaos phenomena. Further, a nonlinear system has been analyzed for the first and second order moments with additive stochastic perturbations. It has been solved using fourth order Runge-Kutta method and noisy systems by Euler's scheme. It has been demonstrated that the firing properties of neurons to evoke an action potential in a certain parameter space of the large exact systems can be estimated using an approximated model. Strong stimulation can cause a change in increase or decrease of the firing patterns. Corresponding to a fixed set of parameter values, the firing behavior and dynamical differences of the collective variables of a large, exact and approximated systems are investigated.

Modeling carbon dynamics and social drivers of bioenergy agroecosystems

NASA Astrophysics Data System (ADS)

Hunt, Natalie D.

Meeting society's energy needs through bioenergy feedstock production presents a significant and urgent challenge, as it can aid in achieving energy independence goals and mitigating climate change. With federal biofuel production standards to be met within the next decade, and with no commercial scale production or markets currently in place, many questions regarding the sustainability and social feasibility of bioenergy still persist. Clarifying these uncertainties requires the incorporation of biogeochemical, biophysical, and socioeconomic modeling tools. Chapter 2 validated the biogeochemical cycling model AGRO-BGC by comparing model estimates with empirical observations from corn and perennial C4 grass systems across Wisconsin and Illinois. AGRO-BGC, in its first application to an annual cropping system, was found to be a robust model for simulating carbon dynamics of an annual cropping system. Chapter 3 investigated the long-term implications of bioenergy feedstock harvest on soil productivity and erosion in annual corn and perennial switchgrass agroecosystems using AGRO-BGC and the soil erosion model RUSLE2. Modeling environments included biophysical landscape characteristics and management practices of bioenergy feedstock production systems. This study found that intensifying aboveground residue harvest reduces soil productivity over time, and the magnitude of these losses is greater in corn than in switchgrass systems. Results of this study will aid in the design of sustainable bioenergy feedstock management practices. Chapter 4 provided evidence that combining biophysical crop canopy characteristics with satellite-derived vegetation indices offers suitable estimates of crop canopy phenology for corn and soybeans in Southwest Wisconsin farms. LANDSAT based vegetation indices, when combined with a light use efficiency model, provide yield estimates in agreement with farmer reports, providing an efficient and accurate means of estimating crop yields from satellite data. The most important stakeholder in bioenergy sustainability and feasibility research is the farmer. Chapter 5 identified and measured the influence of bioenergy feedstock choice drivers using logistic regression choice models constructed from survey and geospatial data. The strongest choice drivers among farmers willing to participate in a proposed bioenergy feedstock production program included socioeconomic, biophysical, and environmental attitudes. Outcomes of this research will be useful in designing further bioenergy policy and economic incentives.

Elucidating Inherent Uncertainties in Data Assimilation for Predictions Incorporating Non-stationary Processes - Focus on Predictive Phenology

NASA Astrophysics Data System (ADS)

Lowman, L.; Barros, A. P.

2017-12-01

Data assimilation (DA) is the widely accepted procedure for estimating parameters within predictive models because of the adaptability and uncertainty quantification offered by Bayesian methods. DA applications in phenology modeling offer critical insights into how extreme weather or changes in climate impact the vegetation life cycle. Changes in leaf onset and senescence, root phenology, and intermittent leaf shedding imply large changes in the surface radiative, water, and carbon budgets at multiple scales. Models of leaf phenology require concurrent atmospheric and soil conditions to determine how biophysical plant properties respond to changes in temperature, light and water demand. Presently, climatological records for fraction of photosynthetically active radiation (FPAR) and leaf area index (LAI), the modelled states indicative of plant phenology, are not available. Further, DA models are typically trained on short periods of record (e.g. less than 10 years). Using limited records with a DA framework imposes non-stationarity on estimated parameters and the resulting predicted model states. This talk discusses how uncertainty introduced by the inherent non-stationarity of the modeled processes propagates through a land-surface hydrology model coupled to a predictive phenology model. How water demand is accounted for in the upscaling of DA model inputs and analysis period serves as a key source of uncertainty in the FPAR and LAI predictions. Parameters estimated from different DA effectively calibrate a plant water-use strategy within the land-surface hydrology model. For example, when extreme droughts are included in the DA period, the plants are trained to uptake water, transpire, and assimilate carbon under favorable conditions and quickly shut down at the onset of water stress.

Fresh Biomass Estimation in Heterogeneous Grassland Using Hyperspectral Measurements and Multivariate Statistical Analysis

NASA Astrophysics Data System (ADS)

Darvishzadeh, R.; Skidmore, A. K.; Mirzaie, M.; Atzberger, C.; Schlerf, M.

2014-12-01

Accurate estimation of grassland biomass at their peak productivity can provide crucial information regarding the functioning and productivity of the rangelands. Hyperspectral remote sensing has proved to be valuable for estimation of vegetation biophysical parameters such as biomass using different statistical techniques. However, in statistical analysis of hyperspectral data, multicollinearity is a common problem due to large amount of correlated hyper-spectral reflectance measurements. The aim of this study was to examine the prospect of above ground biomass estimation in a heterogeneous Mediterranean rangeland employing multivariate calibration methods. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of above ground biomass for 170 sample plots. Multivariate calibrations including partial least squares regression (PLSR), principal component regression (PCR), and Least-Squared Support Vector Machine (LS-SVM) were used to estimate the above ground biomass. The prediction accuracy of the multivariate calibration methods were assessed using cross validated R2 and RMSE. The best model performance was obtained using LS_SVM and then PLSR both calibrated with first derivative reflectance dataset with R2cv = 0.88 & 0.86 and RMSEcv= 1.15 & 1.07 respectively. The weakest prediction accuracy was appeared when PCR were used (R2cv = 0.31 and RMSEcv= 2.48). The obtained results highlight the importance of multivariate calibration methods for biomass estimation when hyperspectral data are used.

Comparison Between the Use of SAR and Optical Data for Wheat Yield Estimations Using Crop Model Assimilation

NASA Astrophysics Data System (ADS)

Silvestro, Paolo Cosmo; Yang, Hao; Jin, X. L.; Yang, Guijun; Casa, Raffaele; Pignatti, Stefano

2016-08-01

The ultimate aim of this work is to develop methods for the assimilation of the biophysical variables estimated by remote sensing in a suitable crop growth model. Two strategies were followed, one based on the use of Leaf Area Index (LAI) estimated by optical data, and the other based on the use of biomass estimated by SAR. The first one estimates LAI from the reflectance measured by the optical sensors on board of HJ1A, HJ1B and Landsat, using a method based on the training of artificial neural networks (ANN) with PROSAIL model simulations. The retrieved LAI is used to improve wheat yield estimation, using assimilation methods based on the Ensemble Kalman Filter, which assimilate the biophysical variables into growth crop model. The second strategy estimates biomass from SAR imagery. Polarimetric decomposition methods were used based on multi-temporal fully polarimetric Radarsat-2 data during the entire growing season. The estimated biomass was assimilating to FAO Aqua crop model for improving the winter wheat yield estimation, with the Particle Swarm Optimization (PSO) method. These procedures were used in a spatial application with data collected in the rural area of Yangling (Shaanxi Province) in 2014 and were validated for a number of wheat fields for which ground yield data had been recorded and according to statistical yield data for the area.

Retrieval of biophysical parameters with AVIRIS and ISM: The Landes Forest, south west France

NASA Technical Reports Server (NTRS)

Zagolski, F.; Gastellu-Etchegorry, J. P.; Mougin, E.; Giordano, G.; Marty, G.; Letoan, T.; Beaudoin, A.

1992-01-01

The first steps of an experiment for investigating the capability of airborne spectrometer data for retrieval of biophysical parameters of vegetation, especially water conditions are presented. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and ISM data were acquired in the frame of the 1991 NASA/JPL and CNES campaigns on the Landes, South west France, a large and flat forest area with mainly maritime pines. In-situ measurements were completed at that time; i.e. reflectance spectra, atmospheric profiles, sampling for further laboratory analyses of elements concentrations (lignin, water, cellulose, nitrogen,...). All information was integrated in an already existing data base (age, LAI, DBH, understory cover,...). A methodology was designed for (1) obtaining geometrically and atmospherically corrected reflectance data, (2) registering all available information, and (3) analyzing these multi-source informations. Our objective is to conduct comparative studies with simulation reflectance models, and to improve these models, especially in the MIR.

Development of an analytical solution for the Budyko watershed parameter in terms of catchment physical features

NASA Astrophysics Data System (ADS)

Reaver, N.; Kaplan, D. A.; Jawitz, J. W.

2017-12-01

The Budyko hypothesis states that a catchment's long-term water and energy balances are dependent on two relatively easy to measure quantities: rainfall depth and potential evaporation. This hypothesis is expressed as a simple function, the Budyko equation, which allows for the prediction of a catchment's actual evapotranspiration and discharge from measured rainfall depth and potential evaporation, data which are widely available. However, the two main analytically derived forms of the Budyko equation contain a single unknown watershed parameter, whose value varies across catchments; variation in this parameter has been used to explain the hydrological behavior of different catchments. The watershed parameter is generally thought of as a lumped quantity that represents the influence of all catchment biophysical features (e.g. soil type and depth, vegetation type, timing of rainfall, etc). Previous work has shown that the parameter is statistically correlated with catchment properties, but an explicit expression has been elusive. While the watershed parameter can be determined empirically by fitting the Budyko equation to measured data in gauged catchments where actual evapotranspiration can be estimated, this limits the utility of the framework for predicting impacts to catchment hydrology due to changing climate and land use. In this study, we developed an analytical solution for the lumped catchment parameter for both forms of the Budyko equation. We combined these solutions with a statistical soil moisture model to obtain analytical solutions for the Budyko equation parameter as a function of measurable catchment physical features, including rooting depth, soil porosity, and soil wilting point. We tested the predictive power of these solutions using the U.S. catchments in the MOPEX database. We also compared the Budyko equation parameter estimates generated from our analytical solutions (i.e. predicted parameters) with those obtained through the calibration of the Budyko equation to discharge data (i.e. empirical parameters), and found good agreement. These results suggest that it is possible to predict the Budyko equation watershed parameter directly from physical features, even for ungauged catchments.

Estimation of biogeochemical climate regulation services in Chinese forest ecosystems

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, S.

2016-12-01

As the global climate is changing, the climate regulation service of terrestrial ecosystem has been widely studied. Forests, as one of the most important terrestrial ecosystem types, is the biggest carbon pool or sink on land and can regulate climate through both biophysical and biogeochemical means. China is a country with vast forested areas and a variety of forest ecosystems types. Although current studies have related the climate regulation service of forest in China with biophysical or biogeochemical mechanism, there is still a lack of quantitative estimation of climate regulation services, especially for the biogeochemical climate regulation service. The GHGV (greenhouse gas value) is an indicator that can quantify the biochemical climate regulation service using ecosystems' stored organic matter, annual greenhouse gas flux, and potential greenhouse gas exchange rates during disturbances over a multiple year time frame. Therefore, we used GHGV to estimate the contribution of China's ten main forest types to biogeochemical climate regulation and generate the pattern of biochemical climate regulation service in Chinese forest ecosystems.

Parameterization and sensitivity analyses of a radiative transfer model for remote sensing plant canopies

NASA Astrophysics Data System (ADS)

Hall, Carlton Raden

A major objective of remote sensing is determination of biochemical and biophysical characteristics of plant canopies utilizing high spectral resolution sensors. Canopy reflectance signatures are dependent on absorption and scattering processes of the leaf, canopy properties, and the ground beneath the canopy. This research investigates, through field and laboratory data collection, and computer model parameterization and simulations, the relationships between leaf optical properties, canopy biophysical features, and the nadir viewed above-canopy reflectance signature. Emphasis is placed on parameterization and application of an existing irradiance radiative transfer model developed for aquatic systems. Data and model analyses provide knowledge on the relative importance of leaves and canopy biophysical features in estimating the diffuse absorption a(lambda,m-1), diffuse backscatter b(lambda,m-1), beam attenuation alpha(lambda,m-1), and beam to diffuse conversion c(lambda,m-1 ) coefficients of the two-flow irradiance model. Data sets include field and laboratory measurements from three plant species, live oak (Quercus virginiana), Brazilian pepper (Schinus terebinthifolius) and grapefruit (Citrus paradisi) sampled on Cape Canaveral Air Force Station and Kennedy Space Center Florida in March and April of 1997. Features measured were depth h (m), projected foliage coverage PFC, leaf area index LAI, and zenith leaf angle. Optical measurements, collected with a Spectron SE 590 high sensitivity narrow bandwidth spectrograph, included above canopy reflectance, internal canopy transmittance and reflectance and bottom reflectance. Leaf samples were returned to laboratory where optical and physical and chemical measurements of leaf thickness, leaf area, leaf moisture and pigment content were made. A new term, the leaf volume correction index LVCI was developed and demonstrated in support of model coefficient parameterization. The LVCI is based on angle adjusted leaf thickness Ltadj, LAI, and h (m). Its function is to translate leaf level estimates of diffuse absorption and backscatter to the canopy scale allowing the leaf optical properties to directly influence above canopy estimates of reflectance. The model was successfully modified and parameterized to operate in a canopy scale and a leaf scale mode. Canopy scale model simulations produced the best results. Simulations based on leaf derived coefficients produced calculated above canopy reflectance errors of 15% to 18%. A comprehensive sensitivity analyses indicated the most important parameters were beam to diffuse conversion c(lambda, m-1), diffuse absorption a(lambda, m-1), diffuse backscatter b(lambda, m-1), h (m), Q, and direct and diffuse irradiance. Sources of error include the estimation procedure for the direct beam to diffuse conversion and attenuation coefficients and other field and laboratory measurement and analysis errors. Applications of the model include creation of synthetic reflectance data sets for remote sensing algorithm development, simulations of stress and drought on vegetation reflectance signatures, and the potential to estimate leaf moisture and chemical status.

On the distribution of protein refractive index increments.

PubMed

Zhao, Huaying; Brown, Patrick H; Schuck, Peter

2011-05-04

The protein refractive index increment, dn/dc, is an important parameter underlying the concentration determination and the biophysical characterization of proteins and protein complexes in many techniques. In this study, we examine the widely used assumption that most proteins have dn/dc values in a very narrow range, and reappraise the prediction of dn/dc of unmodified proteins based on their amino acid composition. Applying this approach in large scale to the entire set of known and predicted human proteins, we obtain, for the first time, to our knowledge, an estimate of the full distribution of protein dn/dc values. The distribution is close to Gaussian with a mean of 0.190 ml/g (for unmodified proteins at 589 nm) and a standard deviation of 0.003 ml/g. However, small proteins <10 kDa exhibit a larger spread, and almost 3000 proteins have values deviating by more than two standard deviations from the mean. Due to the widespread availability of protein sequences and the potential for outliers, the compositional prediction should be convenient and provide greater accuracy than an average consensus value for all proteins. We discuss how this approach should be particularly valuable for certain protein classes where a high dn/dc is coincidental to structural features, or may be functionally relevant such as in proteins of the eye. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Bayesian Statistical Inference in Ion-Channel Models with Exact Missed Event Correction.

PubMed

Epstein, Michael; Calderhead, Ben; Girolami, Mark A; Sivilotti, Lucia G

2016-07-26

The stochastic behavior of single ion channels is most often described as an aggregated continuous-time Markov process with discrete states. For ligand-gated channels each state can represent a different conformation of the channel protein or a different number of bound ligands. Single-channel recordings show only whether the channel is open or shut: states of equal conductance are aggregated, so transitions between them have to be inferred indirectly. The requirement to filter noise from the raw signal further complicates the modeling process, as it limits the time resolution of the data. The consequence of the reduced bandwidth is that openings or shuttings that are shorter than the resolution cannot be observed; these are known as missed events. Postulated models fitted using filtered data must therefore explicitly account for missed events to avoid bias in the estimation of rate parameters and therefore assess parameter identifiability accurately. In this article, we present the first, to our knowledge, Bayesian modeling of ion-channels with exact missed events correction. Bayesian analysis represents uncertain knowledge of the true value of model parameters by considering these parameters as random variables. This allows us to gain a full appreciation of parameter identifiability and uncertainty when estimating values for model parameters. However, Bayesian inference is particularly challenging in this context as the correction for missed events increases the computational complexity of the model likelihood. Nonetheless, we successfully implemented a two-step Markov chain Monte Carlo method that we called "BICME", which performs Bayesian inference in models of realistic complexity. The method is demonstrated on synthetic and real single-channel data from muscle nicotinic acetylcholine channels. We show that parameter uncertainty can be characterized more accurately than with maximum-likelihood methods. Our code for performing inference in these ion channel models is publicly available. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Canopy reflectance, photosynthesis, and transpiration. II - The role of biophysics in the linearity of their interdependence

NASA Technical Reports Server (NTRS)

Sellers, P. J.

1987-01-01

The ability of satellite sensor systems to estimate area-averaged canopy photosynthetic and transpirative properties is evaluated. The near linear relationship between the simple ratio (SR) and normalized difference (ND) and the surface biophysical properties of canopy photosynthetically active radiation (PAR) absorption, photosynthesis, and bulk stomatal resistance is studied. The models utilized to illustrate the processes of canopy reflectance, photosynthesis, and resistance are described. The dependence of SR, the absorbed fraction of PAR, and canopy photosynthesis and resistance on total leaf area index is analyzed. It is noted that the SR and ND vegetation indices and vegetation-dependent qualities are near-linearly related due to the proportion of leaf scattering coefficient in visible and near IR wavelength regions. The data reveal that satellite sensor systems are useful for the estimation of photosynthesis and transpirative properties.

Assessment of economic and water quality impacts of land use change using a simple bioeconomic model.

PubMed

Bhattarai, Gandhi; Srivastava, Puneet; Marzen, Luke; Hite, Diane; Hatch, Upton

2008-07-01

The objective of this study is to assess the economic and water quality impact of land use change in a small watershed in the Wiregrass region of Alabama. The study compares changes in water quality and revenue from agricultural and timber production due to changes in land use between years 1992 and 2001. The study was completed in two stages. In the first stage, a biophysical model was used to estimate the effect of land use change on nitrogen and phosphorus runoff and sediment deposition in the main channel; in the second stage, farm enterprise budgeting tools were used to estimate the economic returns for the changes in land use condition. Both biophysical and economic results are discussed, and a case for complex optimization to develop a decision support system is presented.

A revised surface resistance parameterisation for estimating latent heat flux from remotely sensed data

NASA Astrophysics Data System (ADS)

Song, Yi; Wang, Jiemin; Yang, Kun; Ma, Mingguo; Li, Xin; Zhang, Zhihui; Wang, Xufeng

2012-07-01

Estimating evapotranspiration (ET) is required for many environmental studies. Remote sensing provides the ability to spatially map latent heat flux. Many studies have developed approaches to derive spatially distributed surface energy fluxes from various satellite sensors with the help of field observations. In this study, remote-sensing-based λE mapping was conducted using a Landsat Thematic Mapper (TM) image and an Enhanced Thematic Mapper Plus (ETM+) image. The remotely sensed data and field observations employed in this study were obtained from Watershed Allied Telemetry Experimental Research (WATER). A biophysics-based surface resistance model was revised to account for water stress and temperature constraints. The precision of the results was validated using 'ground truth' data obtained by eddy covariance (EC) system. Scale effects play an important role, especially for parameter optimisation and validation of the latent heat flux (λE). After considering the footprint of EC, the λE derived from the remote sensing data was comparable to the EC measured value during the satellite's passage. The results showed that the revised surface resistance parameterisation scheme was useful for estimating the latent heat flux over cropland in arid regions.

Microfluidics for simultaneous quantification of platelet adhesion and blood viscosity

PubMed Central

Yeom, Eunseop; Park, Jun Hong; Kang, Yang Jun; Lee, Sang Joon

2016-01-01

Platelet functions, including adhesion, activation, and aggregation have an influence on thrombosis and the progression of atherosclerosis. In the present study, a new microfluidic-based method is proposed to estimate platelet adhesion and blood viscosity simultaneously. Blood sample flows into an H-shaped microfluidic device with a peristaltic pump. Since platelet aggregation may be initiated by the compression of rotors inside the peristaltic pump, platelet aggregates may adhere to the H-shaped channel. Through correlation mapping, which visualizes decorrelation of the streaming blood flow, the area of adhered platelets (APlatelet) can be estimated without labeling platelets. The platelet function is estimated by determining the representative index IA·T based on APlatelet and contact time. Blood viscosity is measured by monitoring the flow conditions in the one side channel of the H-shaped device. Based on the relation between interfacial width (W) and pressure ratio of sample flows to the reference, blood sample viscosity (μ) can be estimated by measuring W. Biophysical parameters (IA·T, μ) are compared for normal and diabetic rats using an ex vivo extracorporeal model. This microfluidic-based method can be used for evaluating variations in the platelet adhesion and blood viscosity of animal models with cardiovascular diseases under ex vivo conditions. PMID:27118101

Determining the K coefficient to leaf area index estimations in a tropical dry forest

NASA Astrophysics Data System (ADS)

Magalhães, Sarah Freitas; Calvo-Rodriguez, Sofia; do Espírito Santo, Mário Marcos; Sánchez Azofeifa, Gerardo Arturo

2018-03-01

Vegetation indices are useful tools to remotely estimate several important parameters related to ecosystem functioning. However, improving and validating estimations for a wide range of vegetation types are necessary. In this study, we provide a methodology for the estimation of the leaf area index (LAI) in a tropical dry forest (TDF) using the light diffusion through the canopy as a function of the successional stage. For this purpose, we estimated the K coefficient, a parameter that relates the normalized difference vegetation index (NDVI) to LAI, based on photosynthetically active radiation (PAR) and solar radiation. The study was conducted in the Mata Seca State Park, in southeastern Brazil, from 2012 to 2013. We defined four successional stages (very early, early, intermediate, and late) and established one optical phenology tower at one plot of 20 × 20 m per stage. Towers measured the incoming and reflected solar radiation and PAR for NDVI calculation. For each plot, we established 24 points for LAI sampling through hemispherical photographs. Because leaf cover is highly seasonal in TDFs, we determined ΔK (leaf growth phase) and K max (leaf maturity phase). We detected a strong correlation between NDVI and LAI, which is necessary for a reliable determination of the K coefficient. Both NDVI and LAI varied significantly between successional stages, indicating sensitivity to structural changes in forest regeneration. Furthermore, the K values differed between successional stages and correlated significantly with other environmental variables such as air temperature and humidity, fraction of absorbed PAR, and soil moisture. Thus, we established a model based on spectral properties of the vegetation coupled with biophysical characteristics in a TDF that makes possible to estimate LAI from NDVI values. The application of the K coefficient can improve remote estimations of forest primary productivity and gases and energy exchanges between vegetation and atmosphere. This model can be applied to distinguish different successional stages of TDFs, supporting environmental monitoring and conservation policies towards this biome.

GPP/RE Partitioning of Long-term Network Flux Data as a Tool for Estimating Ecosystem-scale Ecophysiological Parameters of Grasslands and Croplands

NASA Astrophysics Data System (ADS)

Gilmanov, T. G.; Wylie, B. K.; Gu, Y.; Howard, D. M.; Zhang, L.

2013-12-01

The physiologically based model of canopy CO2 exchange by Thornly and Johnson (2000) modified to incorporate vapor pressure deficit (VPD) limitation of photosynthesis is a robust tool for partitioning tower network net CO2 exchange data into gross photosynthesis (GPP) and ecosystem respiration (RE) (Gilmanov et al. 2013a, b). In addition to 30-min and daily photosynthesis and respiration values, the procedure generates daily estimates and uncertainties of essential ecosystem-scale parameters such as apparent quantum yield ALPHA, photosynthetic capacity AMAX, convexity of light response THETA, gross ecological light-use efficiency LUE, daytime ecosystem respiration rate RDAY, and nighttime ecosystem respiration rate RNIGHT. These ecosystem-scale parameters are highly demanded by the modeling community and open opportunities for comparison with the rich data of leaf-level estimates of corresponding parameters available from physiological studies of previous decades. Based on the data for 70+ site-years of flux tower measurements at the non-forest sites of the Ameriflux network and the non-affiliated sites, we present results of the comparative analysis and multi-site synthesis of the magnitudes, uncertainties, patterns of seasonal and yearly dynamics, and spatiotemporal distribution of these parameters for grasslands and croplands of the conterminous United States (CONUS). Combining this site-level parameter data set with the rich spatiotemporal data sets of a remotely sensed vegetation index, weather and climate conditions, and site biophysical and geophysical features (phenology, photosynthetically active radiation, and soil water holding capacity) using methods of multivariate analysis (e.g., Cubist regression tree) offers new opportunities for predictive modeling and scaling-up of ecosystem-scale parameters of carbon cycling in grassland and agricultural ecosystems of CONUS (Zhang et al. 2011; Gu et al. 2012). REFERENCES Gilmanov TG, Baker JM, Bernacchi CJ, Billesbach DP, Burba GG, et al. (2013a). Productivity and CO2 exchange of the leguminous crops: Estimates from flux tower measurements. Agronomy J (submitted). Gilmanov TG, Wylie BK, Tieszen LL, Meyers TP, Baron VS, et al. (2013b). CO2 uptake and ecophysiological parameters of the grain crops of midcontinent North America: Estimates from flux tower measurements. Agric Ecosyst Environm 164: 162-175 Gu Y, Howard DM, Wylie BK, and Zhang L (2012). Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains: Landscape Ecology, 27: 319-326. Thornley JHM., Johnson IR (2000). Plant and crop modelling. A mathematical approach to plant and crop physiology. The Blackburn Press, Caldwell, New Jersey. Zhang L, Wylie BK, Ji L, Gilmanov TG, Tieszen LL, Howard DM (2011). Upscaling carbon fluxes over the Great Plains grasslands: Sinks and sources. J Geophys Res G: Biogeosciences 116: G00J3

Using biophysical models to manage nitrogen pollution from agricultural sources: Utopic or realistic approach for non-scientist users? Case study of a drinking water catchment area in Lorraine, France.

PubMed

Bernard, Pierre-Yves; Benoît, Marc; Roger-Estrade, Jean; Plantureux, Sylvain

2016-12-01

The objectives of this comparison of two biophysical models of nitrogen losses were to evaluate first whether results were similar and second whether both were equally practical for use by non-scientist users. Results were obtained with the crop model STICS and the environmental model AGRIFLUX based on nitrogen loss simulations across a small groundwater catchment area (<1 km(2)) located in the Lorraine region in France. Both models simulate the influences of leaching and cropping systems on nitrogen losses in a relevant manner. The authors conclude that limiting the simulations to areas where soils with a greater risk of leaching cover a significant spatial extent would likely yield acceptable results because those soils have more predictable leaching of nitrogen. In addition, the choice of an environmental model such as AGRIFLUX which requires fewer parameters and input variables seems more user-friendly for agro-environmental assessment. The authors then discuss additional challenges for non-scientists such as lack of parameter optimization, which is essential to accurately assessing nitrogen fluxes and indirectly not to limit the diversity of uses of simulated results. Despite current restrictions, with some improvement, biophysical models could become useful environmental assessment tools for non-scientists. Copyright © 2016 Elsevier Ltd. All rights reserved.

Irrigation Requirement Estimation Using Vegetation Indices and Inverse Biophysical Modeling

NASA Technical Reports Server (NTRS)

Bounoua, Lahouari; Imhoff, Marc L.; Franks, Shannon

2010-01-01

We explore an inverse biophysical modeling process forced by satellite and climatological data to quantify irrigation requirements in semi-arid agricultural areas. We constrain the carbon and water cycles modeled under both equilibrium, balance between vegetation and climate, and non-equilibrium, water added through irrigation. We postulate that the degree to which irrigated dry lands vary from equilibrium climate conditions is related to the amount of irrigation. The amount of water required over and above precipitation is considered as an irrigation requirement. For July, results show that spray irrigation resulted in an additional amount of water of 1.3 mm per occurrence with a frequency of 24.6 hours. In contrast, the drip irrigation required only 0.6 mm every 45.6 hours or 46% of that simulated by the spray irrigation. The modeled estimates account for 87% of the total reported irrigation water use, when soil salinity is not important and 66% in saline lands.

Accurate, robust and reliable calculations of Poisson-Boltzmann binding energies

PubMed Central

Nguyen, Duc D.; Wang, Bao

2017-01-01

Poisson-Boltzmann (PB) model is one of the most popular implicit solvent models in biophysical modeling and computation. The ability of providing accurate and reliable PB estimation of electrostatic solvation free energy, ΔGel, and binding free energy, ΔΔGel, is important to computational biophysics and biochemistry. In this work, we investigate the grid dependence of our PB solver (MIBPB) with SESs for estimating both electrostatic solvation free energies and electrostatic binding free energies. It is found that the relative absolute error of ΔGel obtained at the grid spacing of 1.0 Å compared to ΔGel at 0.2 Å averaged over 153 molecules is less than 0.2%. Our results indicate that the use of grid spacing 0.6 Å ensures accuracy and reliability in ΔΔGel calculation. In fact, the grid spacing of 1.1 Å appears to deliver adequate accuracy for high throughput screening. PMID:28211071

A Review on the Role of Vibrational Spectroscopy as An Analytical Method to Measure Starch Biochemical and Biophysical Properties in Cereals and Starchy Foods

PubMed Central

Cozzolino, D.; Degner, S.; Eglinton, J.

2014-01-01

Starch is the major component of cereal grains and starchy foods, and changes in its biophysical and biochemical properties (e.g., amylose, amylopectin, pasting, gelatinization, viscosity) will have a direct effect on its end use properties (e.g., bread, malt, polymers). The use of rapid and non-destructive methods to study and monitor starch properties, such as gelatinization, retrogradation, water absorption in cereals and starchy foods, is of great interest in order to improve and assess their quality. In recent years, near infrared reflectance (NIR) and mid infrared (MIR) spectroscopy have been explored to predict several quality parameters, such as those generated by instrumental methods commonly used in routine analysis like the rapid visco analyser (RVA) or viscometers. In this review, applications of both NIR and MIR spectroscopy to measure and monitor starch biochemical (amylose, amylopectin, starch) and biophysical properties (e.g., pasting properties) will be presented and discussed. PMID:28234340

Estimation of Some Bio-Physical Indicators for Sustainable Crop Production in the Eastern Nile Basin of Sudan Using Landsat-8 Imagery and SEBAL Model

NASA Astrophysics Data System (ADS)

Guma Biro Turk, Khalid

2016-07-01

Crop production under modern irrigation systems require unique management at field level and hence better utilization of agricultural inputs and water resources. This study aims to make use of remote sensing (RS) data and the surface energy balance algorithm for land (SEBAL) to improve the on-farm management. The study area is located in the Eastern part of the Blue Nile River about 60 km south of Khartoum, Sudan. Landsat-8 data were used to estimate a number of bio-physical indicators during the growing season of the year 2014/2015. Accordingly, in-situ weather data and SEBAL model were applied to calculate: the reference (ET0), actual (ETa) and potential (ETp) evapotranspiration, soil moisture (SM), crop factor (kc), nitrogen (N), biomass production (BP) and crop water productivity (CWP). Results revealed that ET0 showed steady variation throughout the year, varying from 5 to 7 mm/day. However, ETa and ETp showed clear temporal variation attributed to frequent cutting of the alfalfa, almost monthly. The BP of the alfalfa was observed to be high when there is no cutting activates were made before the image acquisition date. Nevertheless the CWP trends are following the biomass production ones, low when there is no biomass and high when the biomass is high. The application of SEBAL model within the study area using the Landsat-8 imagery indicates that it's possible to produce field-based bio-physical indicators, which can be useful in monitoring and managing the field during the growing season. However, a cross-calibration with the in-situ data should be considered in order to maintain the spatial variability within the field. Keywords: Bio-physical Indicators; Remote Sensing; SEBAL; Landsat-8; Eastern Nile Basin

Non-invasive diagnostics of several structural and biophysical parameters of skin cover by spectral light reflectance

NASA Astrophysics Data System (ADS)

Ivanov, Arkady P.; Barun, Vladimir V.

2007-05-01

A calculation scheme and an algorithm to simultaneously diagnose several structural and biophysical parameters of skin by reflected light are constructed in the paper. The procedure is based the fact that, after absorption and scattering, light reflected by tissue contains information on its optically active chromophores and structure. The problem on isolating the desired parameters is a spectroscopic one under multiple scattering conditions. The latter considerably complicates the solution of the problem and requires the elaboration of an approach that is specific to the object studied. The procedure presented in the paper is based on spectral tissue model properties proposed earlier and engineering methods for solving the radiative transfer equation. The desired parameters are melanin and blood volume fractions, f and c, epidermis thickness d, mean diameter D of capillaries, and blood oxygenation degree S. Spectral diffuse reflectance R(λ) of skin over the range of 400 to 850 nm was calculated as a first stage. Then the sensitivity of R(λ) to the above parameters was studied to optimize the algorithm by wavelengths and to propose an experimental scheme for diagnostics. It is shown that blood volume fraction and f*d product can be rather surely determined by the reflected green -- red light. One can find f and d separately as well as D by the blue reflectance. The last stage is the derivation of S at about 600 nm.

The role of bio-physical cohesive substrates on sediment winnowing and bedform development

NASA Astrophysics Data System (ADS)

Ye, Leiping; Parsons, Daniel; Manning, Andrew

2017-04-01

Existing sediment transport and bedform size predictions for natural open-channel flows in many environments are seriously impeded by a lack of process-based knowledge concerning the dynamics of complex bed sediment mixtures comprising cohesionless sand and biologically-active cohesive muds. A series of flume experiments (14 experimental runs) with different substrate mixtures of sand-clay-EPS (Extracellular Polymeric Substance) are combined with a detailed estuarine field survey (Dee estuary, NW England) to investigate the development of bedform morphologies and characteristics of suspended sediment over bio-physical cohesive substrates. The experimental results indicate that winnowing and sediment sorting can occur pervasively in bio-physical cohesive sediment - flow systems. Importantly however, the evolution of the bed and bedform dynamics, and hence turbulence production, is significantly reduced as bed substrate cohesivity increases. The estuarine subtidal zone survey also revealed that the bio-physical cohesion provided by both the clay and microorganism fractions in the bed plays a significant role in controlling the interactions between bed substrate and sediment suspension, deposition and bedform generation. The work will be presented here concludes by outlining the need to extend and revisit the effects of cohesivity in morphodynamic systems and the sets of parameters presently used in numerical modelling, particularly in the context of the impact of climate change on estuarine and coastal systems.

The seasonal variation in skin hydration, sebum, scaliness, brightness and elasticity in Korean females.

PubMed

Nam, G W; Baek, J H; Koh, J S; Hwang, J-K

2015-02-01

Age, gender, regional, and ethnic differences influence skin conditions. The purpose of this study was to observe the effects of environments, especially the air temperature, relative humidity, air pressure, duration of sunshine, and precipitation on skin, and the seasonal variation in skin hydration, sebum, scales, brightness, and elasticity in Korean females. The study included 89 Korean subjects, aged 29.7 ± 6.2 years. The five skin biophysical parameters (skin hydration, sebum, scales, brightness, and elasticity) were measured at six sites: forehead, under the eye, frontal cheek, crow's foot, lateral cheek, and inner forearm. Skin hydration was measured using the Corneometer® CM 825. Skin sebum was measured with Sebumeter® SM 815. Skin scaliness was measured with Visioscan® VC 98. Skin brightness (L* value) was measured by using Spectrophotometer. A suction chamber device, Cutometer® MPA 580, was used to measure the skin elasticity. The measurements were performed every month for 13 months, from April 2007 to April 2008. There were significantly seasonal variations in environmental factors. The air temperature was the lowest in January (-1.7°C), and the highest in August (26.5°C). The relative humidity was the lowest in February (46%), and the highest in July and August (75%). There was a negative correlation between skin scaliness and three environmental factors such as air temperature, relative humidity, and highest precipitation. There was a positive correlation between skin scaliness and two environmental factors such as air pressure and duration of sunshine. Elasticity was correlated with air temperature positively and with air pressure negatively. The correlations shown between the skin biophysical parameters and environmental factors demonstrate that the skin biophysical parameters are affected by environmental factors. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Quantifying the thermal heat requirement of Brassica in assessing biophysical parameters under semi-arid microenvironments

NASA Astrophysics Data System (ADS)

Adak, Tarun; Chakravarty, N. V. K.

2010-07-01

Evaluation of the thermal heat requirement of Brassica spp. across agro-ecological regions is required in order to understand the further effects of climate change. Spatio-temporal changes in hydrothermal regimes are likely to affect the physiological growth pattern of the crop, which in turn will affect economic yields and crop quality. Such information is helpful in developing crop simulation models to describe the differential thermal regimes that prevail at different phenophases of the crop. Thus, the current lack of quantitative information on the thermal heat requirement of Brassica crops under debranched microenvironments prompted the present study, which set out to examine the response of biophysical parameters [leaf area index (LAI), dry biomass production, seed yield and oil content] to modified microenvironments. Following 2 years of field experiments on Typic Ustocrepts soils under semi-arid climatic conditions, it was concluded that the Brassica crop is significantly responsive to microenvironment modification. A highly significant and curvilinear relationship was observed between LAI and dry biomass production with accumulated heat units, with thermal accumulation explaining ≥80% of the variation in LAI and dry biomass production. It was further observed that the economic seed yield and oil content, which are a function of the prevailing weather conditions, were significantly responsive to the heat units accumulated from sowing to 50% physiological maturity. Linear regression analysis showed that growing degree days (GDD) could indicate 60-70% variation in seed yield and oil content, probably because of the significant response to differential thermal microenvironments. The present study illustrates the statistically strong and significant response of biophysical parameters of Brassica spp. to microenvironment modification in semi-arid regions of northern India.

Unified Bayesian Estimator of EEG Reference at Infinity: rREST (Regularized Reference Electrode Standardization Technique).

PubMed

Hu, Shiang; Yao, Dezhong; Valdes-Sosa, Pedro A

2018-01-01

The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs-with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the "oracle" choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance.

Lidar Remote Sensing for Characterizing Forest Vegetation - Special Issue. Foreword

NASA Technical Reports Server (NTRS)

Popescu, Sorin C.; Nelson, Ross F.

2011-01-01

The Silvilaser 2009 conference held in College Station, Texas, USA, was the ninth conference in the Silvilaser series, which started in 2002 with the international workshop on using lidar (Light Detection and Ranging) for analyzing forest structure, held in Victoria, British Columbia, Canada. Following the Canadian workshop, subsequent forestry-lidar conferences took place in Australia, Sweden, Germany, USA, Japan, Finland, and the United Kingdom (UK). By the time this Silvilaser 2009 special issue of PE&RS is published, the 10th international conference will have been held in Freiburg, Germany, and planning will be ongoing for the 11th meeting to take place in Tasmania, Australia, in October 2011. Papers presented at the 2005 conference held in Blacksburg, Virginia, USA, were assembled in a special issue of PE&RS published in December 2006. Other special issues resulting from previous conferences were published in journals such as the Canadian Journal of Remote Sensing (2003), the Scandinavian Journal of Forest Research (2004), and Japan s Journal of Forest Planning (2008). Given the conference history and the much longer record of publications on lidar applications for estimating forest biophysical parameters, which dates back to the early 1980s, we may consider lidar an established remote sensing technology for characterizing forest canopy structure and estimating forest biophysical parameters. Randy Wynne, a professor at Virginia Tech and the final keynote speaker at Silvilaser 2009, made the case that it was time to push 30 years of research into operations, along the lines of what has already been done to good effect in the Scandinavian countries. In Randy s words, it s time to "Just do it!" This special issue includes a selection of papers presented during the 2009 Silvilaser conference, which consisted of eight sections as follows: (1) biomass and carbon stock estimates, (2) tree species and forest type classification, (3) data fusion and integration, (4, 5, and 6) forest inventory, (7) silvicultural and ecological applications, and (8) terrestrial lidar applications. Within the constraint limiting the number of papers that could be fitted into the special issue we attempted to select those papers that best represented these conference topics and sections, giving special consideration to studies using forestry lidar data collected from each of the three platforms -- terrestrial, airborne, and spaceborne. Reflecting the international participation and reach of the conference, the studies presented here took place in the USA, Canada, Taiwan, the UK, and China.

Estimating biophysical properties of coffee (Coffea canephora) plants with above-canopy field measurements, using CropSpec®

NASA Astrophysics Data System (ADS)

Putra, Bayu T. Widjaja; Soni, Peeyush; Morimoto, Eiji; Pujiyanto, Pujiyanto

2018-04-01

Remote sensing technologies have been applied to many crops, but tree crops like Robusta coffee (Coffea canephora) under shade conditions require additional attention while making above-canopy measurements. The objective of this study was to determine how well chlorophyll and nitrogen status of Robusta coffee plants can be estimated with the laser-based (CropSpec®) active sensor. This study also identified appropriate vegetation indices for estimating Nitrogen content by above-canopy measurement, using near-infra red and red-edge bands. Varying light intensity and different background of the plants were considered in developing the indices. Field experiments were conducted involving different non-destructive tools (CropSpec® and SPAD-502 chlorophyll meter). Subsequently, Kjeldahl laboratory analyses were performed to determine the actual Nitrogen content of the plants with different ages and field conditions used in the non-destructive previous stage. Measurements were undertaken for assessing the biophysical properties of tree plant. The usefulness of near-infrared and red-edge bands from these sensors in measuring critical nitrogen levels of coffee plants by above-canopy measurement are investigated in this study.

Correlative live and super-resolution imaging reveals the dynamic structure of replication domains.

PubMed

Xiang, Wanqing; Roberti, M Julia; Hériché, Jean-Karim; Huet, Sébastien; Alexander, Stephanie; Ellenberg, Jan

2018-06-04

Chromosome organization in higher eukaryotes controls gene expression, DNA replication, and DNA repair. Genome mapping has revealed the functional units of chromatin at the submegabase scale as self-interacting regions called topologically associating domains (TADs) and showed they correspond to replication domains (RDs). A quantitative structural and dynamic description of RD behavior in the nucleus is, however, missing because visualization of dynamic subdiffraction-sized RDs remains challenging. Using fluorescence labeling of RDs combined with correlative live and super-resolution microscopy in situ, we determined biophysical parameters to characterize the internal organization, spacing, and mechanical coupling of RDs. We found that RDs are typically 150 nm in size and contain four co-replicating regions spaced 60 nm apart. Spatially neighboring RDs are spaced 300 nm apart and connected by highly flexible linker regions that couple their motion only <550 nm. Our pipeline allows a robust quantitative characterization of chromosome structure in situ and provides important biophysical parameters to understand general principles of chromatin organization. © 2018 Xiang et al.

Analysis of Video-Based Microscopic Particle Trajectories Using Kalman Filtering

PubMed Central

Wu, Pei-Hsun; Agarwal, Ashutosh; Hess, Henry; Khargonekar, Pramod P.; Tseng, Yiider

2010-01-01

Abstract The fidelity of the trajectories obtained from video-based particle tracking determines the success of a variety of biophysical techniques, including in situ single cell particle tracking and in vitro motility assays. However, the image acquisition process is complicated by system noise, which causes positioning error in the trajectories derived from image analysis. Here, we explore the possibility of reducing the positioning error by the application of a Kalman filter, a powerful algorithm to estimate the state of a linear dynamic system from noisy measurements. We show that the optimal Kalman filter parameters can be determined in an appropriate experimental setting, and that the Kalman filter can markedly reduce the positioning error while retaining the intrinsic fluctuations of the dynamic process. We believe the Kalman filter can potentially serve as a powerful tool to infer a trajectory of ultra-high fidelity from noisy images, revealing the details of dynamic cellular processes. PMID:20550894

Plasma membrane--cortical cytoskeleton interactions: a cell biology approach with biophysical considerations.

PubMed

Kapus, András; Janmey, Paul

2013-07-01

From a biophysical standpoint, the interface between the cell membrane and the cytoskeleton is an intriguing site where a "two-dimensional fluid" interacts with an exceedingly complex three-dimensional protein meshwork. The membrane is a key regulator of the cytoskeleton, which not only provides docking sites for cytoskeletal elements through transmembrane proteins, lipid binding-based, and electrostatic interactions, but also serves as the source of the signaling events and molecules that control cytoskeletal organization and remolding. Conversely, the cytoskeleton is a key determinant of the biophysical and biochemical properties of the membrane, including its shape, tension, movement, composition, as well as the mobility, partitioning, and recycling of its constituents. From a cell biological standpoint, the membrane-cytoskeleton interplay underlies--as a central executor and/or regulator--a multitude of complex processes including chemical and mechanical signal transduction, motility/migration, endo-/exo-/phagocytosis, and other forms of membrane traffic, cell-cell, and cell-matrix adhesion. The aim of this article is to provide an overview of the tight structural and functional coupling between the membrane and the cytoskeleton. As biophysical approaches, both theoretical and experimental, proved to be instrumental for our understanding of the membrane/cytoskeleton interplay, this review will "oscillate" between the cell biological phenomena and the corresponding biophysical principles and considerations. After describing the types of connections between the membrane and the cytoskeleton, we will focus on a few key physical parameters and processes (force generation, curvature, tension, and surface charge) and will discuss how these contribute to a variety of fundamental cell biological functions. © 2013 American Physiological Society.

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley

2015-01-01

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

Agriculture land suitability analysis evaluation based multi criteria and GIS approach

NASA Astrophysics Data System (ADS)

Bedawi Ahmed, Goma; Shariff, Abdul Rashid M.; Balasundram, Siva Kumar; Abdullah, Ahmad Fikri bin

2016-06-01

Land suitability evaluation (LSE) is a valuable tool for land use planning in major countries of the world as well as in Malaysia. However, previous LSE studies have been conducted with the use of biophysical and ecological datasets for the design of equally important socio-economic variables. Therefore, this research has been conducted at the sub national level to estimate suitable agricultural land for rubber crops in Seremban, Malaysia by application of physical variables in combination with widely employed biophysical and ecological variables. The objective of this study has been to provide an up-to date GIS-based agricultural land suitability evaluation (ALSE) for determining suitable agricultural land for Rubber crops in Malaysia. Biophysical and ecological factors were assumed to influence agricultural land use were assembled and the weights of their respective contributions to land suitability for agricultural uses were assessed using an analytic hierarchical process. The result of this study found Senawang, Mambau, Sandakan and Rantau as the most suitable areas for cultivating Rubber; whereas, Nilai and Labu are moderately suitable for growing rubber. Lenggeng, Mantin and Pantai are not suitable for growing rubber as the study foresaw potential environmental degradation of these locations from agricultural intensification. While this study could be useful in assessing the potential agricultural yields and potential environmental degradation in the study area, it could also help to estimate the potential conversion of agricultural land to non-agricultural uses.

Estimation of effective connectivity via data-driven neural modeling

PubMed Central

Freestone, Dean R.; Karoly, Philippa J.; Nešić, Dragan; Aram, Parham; Cook, Mark J.; Grayden, David B.

2014-01-01

This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination. PMID:25506315

Estimating aboveground biomass in interior Alaska with Landsat data and field measurements

USGS Publications Warehouse

Ji, Lei; Wylie, Bruce K.; Nossov, Dana R.; Peterson, Birgit E.; Waldrop, Mark P.; McFarland, Jack W.; Rover, Jennifer R.; Hollingsworth, Teresa N.

2012-01-01

Terrestrial plant biomass is a key biophysical parameter required for understanding ecological systems in Alaska. An accurate estimation of biomass at a regional scale provides an important data input for ecological modeling in this region. In this study, we created an aboveground biomass (AGB) map at 30-m resolution for the Yukon Flats ecoregion of interior Alaska using Landsat data and field measurements. Tree, shrub, and herbaceous AGB data in both live and dead forms were collected in summers and autumns of 2009 and 2010. Using the Landsat-derived spectral variables and the field AGB data, we generated a regression model and applied this model to map AGB for the ecoregion. A 3-fold cross-validation indicated that the AGB estimates had a mean absolute error of 21.8 Mg/ha and a mean bias error of 5.2 Mg/ha. Additionally, we validated the mapping results using an airborne lidar dataset acquired for a portion of the ecoregion. We found a significant relationship between the lidar-derived canopy height and the Landsat-derived AGB (R2 = 0.40). The AGB map showed that 90% of the ecoregion had AGB values ranging from 10 Mg/ha to 134 Mg/ha. Vegetation types and fires were the primary factors controlling the spatial AGB patterns in this ecoregion.

Bio-physical modeling of time-resolved forward scattering by Listeria colonies

NASA Astrophysics Data System (ADS)

Bae, Euiwon; Banada, Padmapriya P.; Bhunia, Arun K.; Hirleman, E. Daniel

2006-10-01

We have developed a detection system and associated protocol based on optical forward scattering where the bacterial colonies of various species and strains growing on solid nutrient surfaces produced unique scatter signatures. The aim of the present investigation was to develop a bio-physical model for the relevant phenomena. In particular, we considered time-varying macroscopic morphological properties of the growing colonies and modeled the scattering using scalar diffraction theory. For the present work we performed detailed studies with three species of Listeria; L. innocua, L. monocytogenes, and L. ivanovii. The baseline experiments involved cultures grown on brain heart infusion (BHI) agar and the scatter images were captured every six hours for an incubation period of 42 hours. The morphologies of the colonies were studied by phase contrast microscopy, including measurement of the diameter of the colony. Growth curves, represented by colony diameter as a function of time, were compared with the time-evolution of scattering signatures. Similar studies were carried out with L. monocytogenes grown on different substrates. Non-dimensionalizing incubation time in terms of the time to reach stationary phase was effective in reducing the dimensionality of the model. Bio-physical properties of the colony such as diameter, bacteria density variation, surface curvature/profile, and transmission coefficient are important parameters in predicting the features of the forward scattering signatures. These parameters are included in a baseline model that treats the colony as a concentric structure with radial variations in phase modulation. In some cases azimuthal variations and random phase inclusions were included as well. The end result is a protocol (growth media, incubation time and conditions) that produces reproducible and distinguishable scatter patterns for a variety of harmful food borne pathogens in a short period of time. Further, the bio-physical model we developed is very effective in predicting the dominant features of the scattering signatures required by the identification process and will be effective for informing further improvements in the instrumentation.

Allometric Scaling and Resource Limitations Model of Total Aboveground Biomass in Forest Stands: Site-scale Test of Model

NASA Astrophysics Data System (ADS)

CHOI, S.; Shi, Y.; Ni, X.; Simard, M.; Myneni, R. B.

2013-12-01

Sparseness in in-situ observations has precluded the spatially explicit and accurate mapping of forest biomass. The need for large-scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e.g., machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U.S. Forest Service (USFS) were produced to evaluate the model. This research focuses on a site-scale test of the biomass model to explore the robustness of predictors, and to potentially improve models using additional geospatial predictors such as climatic variables, vegetation indices, soil properties, and lidar-/radar-derived altimetry products (or existing forest canopy height maps). As results, the optimized ASRL estimates satisfactorily resemble the FIA aboveground biomass in terms of data distribution, overall agreement, and spatial similarity across scales. Uncertainties are quantified (ranged from 0.2 to 0.4) by taking into account the spatial mismatch (FIA plot vs. PRISM grid), heterogeneity (species composition), and an example bias scenario (= 0.2) in the root system extents.

Importance of biophysical effects on climate warming mitigation potential of biofuel crops over the conterminous United States

DOE PAGES

Zhu, Peng; Zhuang, Qianlai; Eva, Joo; ...

2016-06-21

Current quantification of climate warming mitigation potential (CWMP) of biomass-derived energy has focused primarily on its biogeochemical effects. This study used site-level observations of carbon, water, and energy fluxes of biofuel crops to parameterize and evaluate the community land model (CLM) and estimate CO 2 fluxes, surface energy balance, soil carbon dynamics of corn (Zea mays), switchgrass (Panicum virgatum), and miscanthus (Miscanthus × giganteus) ecosystems across the conterminous United States considering different agricultural management practices and land-use scenarios. Here, we find that neglecting biophysical effects underestimates the CWMP of transitioning from croplands and marginal lands to energy crops. Biogeochemical effectsmore » alone result in changes in carbon storage of -1.9, 49.1, and 69.3 g C m -2 y -1 compared to 20.5, 78.5, and 96.2 g C m -2 y -1 when considering both biophysical and biogeochemical effects for corn, switchgrass, and miscanthus, respectively. The biophysical contribution to CWMP is dominated by changes in latent heat fluxes. Using the model to optimize growth conditions through fertilization and irrigation increases the CWMP further to 79.6, 98.3, and 118.8 g C m -2 y -1, respectively, representing the upper threshold for CWMP. Results also show that the CWMP over marginal lands is lower than that over croplands. Our study highlights that neglecting the biophysical effects of altered surface energy and water balance underestimates the CWMP of transitioning to bioenergy crops at regional scales.« less

Satellite-guided hydro-economic analysis for integrated management and prediction of the impact of droughts on agricultural regions

NASA Astrophysics Data System (ADS)

Maneta, M. P.; Howitt, R.; Kimball, J. S.

2013-12-01

Agricultural activity can exacerbate or buffer the impact of climate variability, especially droughts, on the hydrologic and socioeconomic conditions of rural areas. Potential negative regional impacts of droughts include impoverishment of agricultural regions, deterioration or overuse of water resources, risk of monoculture, and regional dependence on external food markets. Policies that encourage adequate management practices in the face of adverse climatic events are critical to preserve rural livelihoods and to ensure a sustainable future for agriculture. Diagnosing and managing drought effects on agricultural production, on the social and natural environment, and on limited water resources, is highly complex and interdisciplinary. The challenges that decision-makers face to mitigate the impact of water shortage are social, agronomic, economic and environmental in nature and therefore must be approached from an integrated multidisciplinary point of view. Existing observation technologies, in conjunction with models and assimilation methods open the opportunity for novel interdisciplinary analysis tools to support policy and decision making. We present an integrated modeling and observation framework driven by satellite remote sensing and other ancillary information from regional monitoring networks to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, management decisions and socioeconomic policy. The core of this framework is a hydroeconomic model of agricultural production that assimilates remote sensing inputs to quantify the amount of land, water, fertilizer and labor farmers allocate for each crop they choose to grow on a seasonal basis in response to changing climatic conditions, including drought. A regional hydroclimatologic model provides biophysical constraints to an economic model of agricultural production based on a class of models referred to as positive mathematical programming (PMP). A recursive Bayesian update method is used to adjust the model parameters by assimilating information on crop acreage, production, and crop evapotranspiration estimated from high-spatial resolution satellite remote sensing. We are developing new land parameter records adapted for agricultural application by merging relatively fine scale, calibrated spectral reflectance time series with similar spectral information from coarser scale and more temporally continuous global satellite data records. These new products will be used to generate field scale estimates of LAI and FPAR, which will be used with regional surface meteorology and biophysical data to estimate crop production including C4 crop types. This integrated framework provides an operational means to monitor and forecast what crops will be grown and how farmers will allocate land, water and other agricultural resources under expected adverse conditions, and the resulting consequences for other water users. It will also permit evaluation of impacts of water policy and changes in food prices on rural community livelihoods. The Bayesian update framework constitutes an efficient method for the identification of the production function parameters and provides valuable information on the associated uncertainty of the forecasts.

Method for Estimating Evaporative Potential (IM/CLO) from ASTM Standard Single Wind Velocity Measures

DTIC Science & Technology

2016-08-10

IM/CLO) FROM ASTM STANDARD SINGLE WIND VELOCITY MEASURES DISCLAIMER The opinions or assertions contained herein are the private views of the...USARIEM TECHNICAL REPORT T16-14 METHOD FOR ESTIMATING EVAPORATIVE POTENTIAL (IM/CLO) FROM ASTM STANDARD SINGLE WIND VELOCITY...ASTM STANDARD SINGLE WIND VELOCITY MEASURES Adam W. Potter Biophysics and Biomedical Modeling Division U.S. Army Research Institute of Environmental

Verification of satellite radar remote sensing based estimates of boreal and subalpine growing seasons using an ecosystem process model and surface biophysical measurement network information

NASA Technical Reports Server (NTRS)

McDonald, K. C.; Kimball, J. S.; Zimmerman, R.

2002-01-01

We employ daily surface Radar backscatter data from the SeaWinds Ku-band Scatterometer onboard Quikscat to estimate landscape freeze-thaw state and associated length of the seasonal non-frozen period as a surrogate for determining the annual growing season across boreal and subalpine regions of North America for 2000 and 2001.

Modeled differences of coral life-history traits influence the refugium potential of a remote Caribbean reef

NASA Astrophysics Data System (ADS)

Davies, Sarah W.; Strader, Marie E.; Kool, Johnathan T.; Kenkel, Carly D.; Matz, Mikhail V.

2017-09-01

Remote populations can influence connectivity and may serve as refugia from climate change. We investigated two reef-building corals ( Pseudodiploria strigosa and Orbicella franksi) from the Flower Garden Banks (FGB), the most isolated, high-latitude Caribbean reef system, which, until recently, retained high coral cover. We characterized coral size-frequency distributions, quantified larval mortality rates and onset of competence ex situ, estimated larval production, and created detailed biophysical models incorporating these parameters to evaluate the source-sink dynamics at the FGB from 2009 to 2012. Estimated mortality rates were similar between species, but pre-competency differed dramatically; P. strigosa was capable of metamorphosis within 2.5 d post-fertilization (dpf) and was competent at least until 8 dpf, while O. franksi was not competent until >20 dpf and remained competent up to 120 dpf. To explore the effect of such contrasting life histories on connectivity, we modeled larval dispersal from the FGB assuming pelagic larval durations (PLD) of either 3-20 d, approximating laboratory-measured pre-competency of P. strigosa, or 20-120 d, approximating pre-competency observed in O. franksi. Surprisingly, both models predicted similar probabilities of local retention at the FGB, either by direct rapid reseeding or via long-term persistence in the Loop Current with larvae returning to the FGB within a month. However, our models predicted that short PLDs would result in complete isolation from the rest of the Caribbean, while long PLDs allowed for larval export to more distant northern Caribbean reefs, highlighting the importance of quantifying larval pre-competency dynamics when parameterizing biophysical models to predict larval connectivity. These simulations suggest that FGB coral populations are likely to be largely self-sustaining and highlight the potential of long-PLD corals, such as endangered Orbicella, to act as larval sources for other degraded Caribbean reefs.

Effective connectivity: Influence, causality and biophysical modeling

PubMed Central

Valdes-Sosa, Pedro A.; Roebroeck, Alard; Daunizeau, Jean; Friston, Karl

2011-01-01

This is the final paper in a Comments and Controversies series dedicated to “The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution”. We argue that discovering effective connectivity depends critically on state-space models with biophysically informed observation and state equations. These models have to be endowed with priors on unknown parameters and afford checks for model Identifiability. We consider the similarities and differences among Dynamic Causal Modeling, Granger Causal Modeling and other approaches. We establish links between past and current statistical causal modeling, in terms of Bayesian dependency graphs and Wiener–Akaike–Granger–Schweder influence measures. We show that some of the challenges faced in this field have promising solutions and speculate on future developments. PMID:21477655

A New Paradigm for Habitability in Planetary Systems: the Extremophilic Zone

NASA Astrophysics Data System (ADS)

Janot-Pacheco, E., Bernardes, L., Lage, C. A. S.

2014-03-01

More than a thousand exoplanets have been discovered so far. Planetary surface temperature may strongly depends on its albedo and geodynamic conditions. We have fed exoplanets from the Encyclopedia database with a comprehensive model of Earth's atmosphere and plate tectonics. As CO2 is the main agent responsible for the greenhouse effect, its partial pressure has been taken as a free parameter to estimate the surface temperature of some known planets. We also investigated the possible presence of "exomoons" belonging to giant planets in the Habitable Zone capable of harbour dynamic stability, to retain an atmosphere and to keep geodynamic activity for long time spans. Biological data on earthly micro-organisms classified as "extremophiles" indicate that such kind of microbial species could dwell on the surface of many exoplanets and exomoons. We thus propose an extension of the mainly astronomically defined "Habitable Zone" concept into the more astrobiologically one, the "Extremophililic Zone", that takes into account other parameters allowing survival of more robust life forms. This contribution comes from an ongoing project developed by a French-Brazilian colaboration in Astrophysics and Biophysics to search for living fingerprints in astrobiologically promising exoplanets.

A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton

PubMed Central

Das, Raibatak; Cairo, Christopher W.; Coombs, Daniel

2009-01-01

The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation. PMID:19893741

Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

NASA Technical Reports Server (NTRS)

Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah

2007-01-01

An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

Integrated Water and Sanitation Risk Assessment and Modeling in the Upper Sonora River basin (Northwest, Mexico)

NASA Astrophysics Data System (ADS)

Mayer, A. S.; Robles-Morua, A.; Halvorsen, K. E.; Vivoni, E. R.; Auer, M. T.

2011-12-01

Studies that integrate human dimensions and the biophysical characteristics of watersheds are necessary to meet the challenge of sustainable water resources development. In this project, we integrated perspectives from sociology, hydrology, and environmental engineering to examine and suggest solutions for managing waterborne disease risks associated with wastewater contamination in the Sonora River basin (SRB), a semiarid rural basin in northwest Mexico. This research consisted of four sub-projects. First, we assessed the perceptions of risks associated with wastewater contamination of water resources in rural communities in the SRB through a series of semi-structured interviews Results from this study indicate that there are major differences in risk perceptions among health professionals, government officials, and lay citizens. Government officials and lay citizens tend to underestimate the severity of the problems related to water related risks. Second, a fully distributed hydrologic model was used to make streamflow predictions in the un-gauged SRB. Synthetic flows generated from the hydrologic model were used to evaluate pollutant transport processes associated with wastewater loadings to the Sonora River. The hydrologic model revealed that the high degree of spatio-temporal variability of runoff in the SRB is associated with links between runoff generation mechanisms and land-atmosphere interactions. Third, a surface water quality model was used to assess the impact of wastewater discharges and develop pathogen contamination indicators in two sites along the Sonora River. To parameterize the water quality model, pathogenic indicator loadings and removal rates were estimated, along with their uncertainty. Results from the water quality modeling show regions in the watershed that may be exceeding pathogenic standards, but also that uncertainty in model parameters requires a probabilistic approach for estimating risks. Finally, a workshop was conducted to explore the use of participatory modeling frameworks in less developed regions. Results indicate that respondents agreed strongly with the hydrologic and water quality modeling methodologies presented and considered the modeling results useful. Our results also show that participatory modeling approaches can have short term impacts as seen in the changes in water-related risk perceptions. In total, these projects revealed that water resources management solutions need to take into account variations across the human landscape (i.e. risk perceptions) and variations in the biophysical response of watersheds to natural phenomena (i.e. streamflow generation) and to anthropogenic activities (i.e. contaminant fate and transport). In addition, this work underscores the notion that sustainable water resources solutions need to contend with uncertainty in our understanding and predictions of human perceptions and biophysical systems.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

PubMed

Daducci, Alessandro; Canales-Rodríguez, Erick J; Zhang, Hui; Dyrby, Tim B; Alexander, Daniel C; Thiran, Jean-Philippe

2015-01-15

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

A diffusion model-free framework with echo time dependence for free-water elimination and brain tissue microstructure characterization.

PubMed

Molina-Romero, Miguel; Gómez, Pedro A; Sperl, Jonathan I; Czisch, Michael; Sämann, Philipp G; Jones, Derek K; Menzel, Marion I; Menze, Bjoern H

2018-03-23

The compartmental nature of brain tissue microstructure is typically studied by diffusion MRI, MR relaxometry or their correlation. Diffusion MRI relies on signal representations or biophysical models, while MR relaxometry and correlation studies are based on regularized inverse Laplace transforms (ILTs). Here we introduce a general framework for characterizing microstructure that does not depend on diffusion modeling and replaces ill-posed ILTs with blind source separation (BSS). This framework yields proton density, relaxation times, volume fractions, and signal disentanglement, allowing for separation of the free-water component. Diffusion experiments repeated for several different echo times, contain entangled diffusion and relaxation compartmental information. These can be disentangled by BSS using a physically constrained nonnegative matrix factorization. Computer simulations, phantom studies, together with repeatability and reproducibility experiments demonstrated that BSS is capable of estimating proton density, compartmental volume fractions and transversal relaxations. In vivo results proved its potential to correct for free-water contamination and to estimate tissue parameters. Formulation of the diffusion-relaxation dependence as a BSS problem introduces a new framework for studying microstructure compartmentalization, and a novel tool for free-water elimination. © 2018 International Society for Magnetic Resonance in Medicine.

Comparison of two integration methods for dynamic causal modeling of electrophysiological data.

PubMed

Lemaréchal, Jean-Didier; George, Nathalie; David, Olivier

2018-06-01

Dynamic causal modeling (DCM) is a methodological approach to study effective connectivity among brain regions. Based on a set of observations and a biophysical model of brain interactions, DCM uses a Bayesian framework to estimate the posterior distribution of the free parameters of the model (e.g. modulation of connectivity) and infer architectural properties of the most plausible model (i.e. model selection). When modeling electrophysiological event-related responses, the estimation of the model relies on the integration of the system of delay differential equations (DDEs) that describe the dynamics of the system. In this technical note, we compared two numerical schemes for the integration of DDEs. The first, and standard, scheme approximates the DDEs (more precisely, the state of the system, with respect to conduction delays among brain regions) using ordinary differential equations (ODEs) and solves it with a fixed step size. The second scheme uses a dedicated DDEs solver with adaptive step sizes to control error, making it theoretically more accurate. To highlight the effects of the approximation used by the first integration scheme in regard to parameter estimation and Bayesian model selection, we performed simulations of local field potentials using first, a simple model comprising 2 regions and second, a more complex model comprising 6 regions. In these simulations, the second integration scheme served as the standard to which the first one was compared. Then, the performances of the two integration schemes were directly compared by fitting a public mismatch negativity EEG dataset with different models. The simulations revealed that the use of the standard DCM integration scheme was acceptable for Bayesian model selection but underestimated the connectivity parameters and did not allow an accurate estimation of conduction delays. Fitting to empirical data showed that the models systematically obtained an increased accuracy when using the second integration scheme. We conclude that inference on connectivity strength and delay based on DCM for EEG/MEG requires an accurate integration scheme. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Detection and isolation of cell-derived microparticles are compromised by protein complexes resulting from shared biophysical parameters.

PubMed

György, Bence; Módos, Károly; Pállinger, Eva; Pálóczi, Krisztina; Pásztói, Mária; Misják, Petra; Deli, Mária A; Sipos, Aron; Szalai, Anikó; Voszka, István; Polgár, Anna; Tóth, Kálmán; Csete, Mária; Nagy, György; Gay, Steffen; Falus, András; Kittel, Agnes; Buzás, Edit I

2011-01-27

Numerous diseases, recently reported to associate with elevated microvesicle/microparticle (MP) counts, have also long been known to be characterized by accelerated immune complex (IC) formation. The goal of this study was to investigate the potential overlap between parameters of protein complexes (eg, ICs or avidin-biotin complexes) and MPs, which might perturb detection and/or isolation of MPs. In this work, after comprehensive characterization of MPs by electron microscopy, atomic force microscopy, dynamic light-scattering analysis, and flow cytometry, for the first time, we drive attention to the fact that protein complexes, especially insoluble ICs, overlap in biophysical properties (size, light scattering, and sedimentation) with MPs. This, in turn, affects MP quantification by flow cytometry and purification by differential centrifugation, especially in diseases in which IC formation is common, including not only autoimmune diseases, but also hematologic disorders, infections, and cancer. These data may necessitate reevaluation of certain published data on patient-derived MPs and contribute to correct the clinical laboratory assessment of the presence and biologic functions of MPs in health and disease.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

2018-06-01

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

Lidar remote sensing of savanna biophysical attributes

NASA Astrophysics Data System (ADS)

Gwenzi, David

Although savanna ecosystems cover approximately 20 % of the terrestrial land surface and can have productivity equal to some closed forests, their role in the global carbon cycle is poorly understood. This study explored the applicability of a past spaceborne Lidar mission and the potential of future missions to estimate canopy height and carbon storage in these biomes. The research used data from two Oak savannas in California, USA: the Tejon Ranch Conservancy in Kern County and the Tonzi Ranch in Santa Clara County. In the first paper we used non-parametric regression techniques to estimate canopy height from waveform parameters derived from the Ice Cloud and land Elevation Satellite's Geoscience Laser Altimeter System (ICESat-GLAS) data. Merely adopting the methods derived for forests did not produce adequate results but the modeling was significantly improved by incorporating canopy cover information and interaction terms to address the high structural heterogeneity inherent to savannas. Paper 2 explored the relationship between canopy height and aboveground biomass. To accomplish this we developed generalized models using the classical least squares regression modeling approach to relate canopy height to above ground woody biomass and then employed Hierarchical Bayesian Analysis (HBA) to explore the implications of using generalized instead of species composition-specific models. Models that incorporated canopy cover proxies performed better than those that did not. Although the model parameters indicated interspecific variability, the distribution of the posterior densities of the differences between composition level and global level parameter values showed a high support for the use of global parameters, suggesting that these canopy height-biomass models are universally (large scale) applicable. As the spatial coverage of spaceborne lidar will remain limited for the immediate future, our objective in paper 3 was to explore the best means of extrapolating plot level biomass into wall-to-wall maps that provide more ecological information. We evaluated the utility of three spatial modeling approaches to address this problem: deterministic methods, geostatistical methods and an image segmentation approach. Overall, the mean pixel biomass estimated by the 3 approaches did not differ significantly but the output maps showed marked differences in the estimation precision and ability of each model to mimic the primary variable's trend across the landscape. The results emphasized the need for future satellite lidar missions to consider increasing the sampling intensity across track so that biomass observations are made and characterized at the scale at which they vary. We used data from the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne photon counting lidar sensor developed by NASA Goddard to simulate ICESat-2 data. We segmented each transect into different block sizes and calculated canopy top and mean ground elevation based on the structure of the histogram of the block's aggregated photons. Our algorithm was able to compute canopy height and generate visually meaningful vegetation profiles at MABEL's signal and noise levels but a simulation of the expected performance of ICESat-2 by adjusting MABEL data's detected number of signal and noise photons to that predicted using ATLAS instrument model design cases indicated that signal photons will be substantially lower. The lower data resolution reduces canopy height estimation precision especially in areas of low density vegetation cover. Given the clear difficulties in processing simulated ATLAS data, it appears unlikely that it will provide the kind of data required for mapping of the biophysical properties of savanna vegetation. Rather, resources are better concentrated on preparing for the Global Ecosystem Dynamics Investigation (GEDI) mission, a waveform lidar mission scheduled to launch by the end of this decade. In addition to the full waveform technique, GEDI will collect data from 25 m diameter contiguous footprints with a high across track density, a requirement that we identified as critically necessary in paper 3. (Abstract shortened by UMI.).

Biophysical and biological contributions of polyamine-coated carbon nanotubes and bidimensional buckypapers in the delivery of miRNAs to human cells.

PubMed

Celluzzi, Antonella; Paolini, Alessandro; D'Oria, Valentina; Risoluti, Roberta; Materazzi, Stefano; Pezzullo, Marco; Casciardi, Stefano; Sennato, Simona; Bordi, Federico; Masotti, Andrea

2018-01-01

Recent findings in nanomedicine have revealed that carbon nanotubes (CNTs) can be used as potential drug carriers, therapeutic agents and diagnostics tools. Moreover, due to their ability to cross cellular membranes, their nanosize dimension, high surface area and relatively good biocompatibility, CNTs have also been employed as a novel gene delivery vector system. In our previous work, we functionalized CNTs with two polyamine polymers, polyethyleneimine (PEI) and polyamidoamine dendrimer (PAMAM). These compounds have low cytotoxicity, ability to conjugate microRNAs (such as miR-503) and, at the same time, transfect efficiently endothelial cells. The parameters contributing to the good efficiency of transfection that we observed were not investigated in detail. In fact, the diameter and length of CNTs are important parameters to be taken into account when evaluating the effects on drug delivery efficiency. In order to investigate the biophysical and biological contributions of polymer-coated CNTs in delivery of miRNAs to human cells, we decided to investigate three different preparations, characterized by different dimensions and aspect ratios. In particular, we took into account very small CNTs, a suspension of CNTs starting from the commercial product and a 2D material based on CNTs (ie, buckypapers [BPs]) to examine the transfection efficiency of a rigid scaffold. In conclusion, we extensively investigated the biophysical and biological contributions of polyamine-coated CNTs and bidimensional BPs in the delivery of miRNAs to human cells, in order to optimize the transfection efficiency of these compounds to be employed as efficient drug delivery vectors in biomedical applications.

Comparison of surface energy budgets and feedbacks to microclimate among different land use types in an agro-pastoral ecotone of northern China.

PubMed

Zhao, Wei; Hu, Zhongmin; Li, Shenggong; Guo, Qun; Liu, Zhengjia; Zhang, Leiming

2017-12-01

The biophysical effect of land use conversion plays a significant role in regulating climate change. Owing to albedo and evapotranspiration (ET) change, the effect of energy budget difference on land surface temperature (LST) is important but unclear among contrasting land use types, especially in temperate semi-arid regions. Based on moderate-resolution imaging spectroradiometer (MODIS) data, we compared the differences in albedo, ET, and LST between cropland and grassland (CR-GR), and between planted forest and grassland (PF-GR) in the Horqin Sandy Land of Inner Mongolia, an agro-pastoral ecotone of northern China. Our main objective was to explore the magnitude and direction of albedo and ET change during the growing season and, subsequently, to estimate the biophysical effects on LST as a result of land use and land cover change. Our results indicate no significant difference in mean monthly albedo for CR-GR and PF-GR. Cropland lost more water through ET and significantly decreased daytime LST compared with grassland from July to September, but no significant differences in ET and LST were observed for PF-GR in any month. The biophysical climate effects were more pronounced for CR-GR compared with PF-GR. The response of LST to the changes in energy budget confirmed that ET was the critical driving factor relative to albedo. Compared with grassland, cropland and planted forest tended to cool the land surface by 5.15°C and 1.51°C during the growing season, respectively, because of the biophysical effects. Our findings suggest the significance of local-scale biophysical effect on climate variation after land use conversion in semi-arid regions. Copyright © 2017 Elsevier B.V. All rights reserved.

An Analytical Model for Determining Two-Dimensional Receptor-Ligand Kinetics

PubMed Central

Cheung, Luthur Siu-Lun; Konstantopoulos, Konstantinos

2011-01-01

Cell-cell adhesive interactions play a pivotal role in major pathophysiological vascular processes, such as inflammation, infection, thrombosis, and cancer metastasis, and are regulated by hemodynamic forces generated by blood flow. Cell adhesion is mediated by the binding of receptors to ligands, which are both anchored on two-dimensional (2-D) membranes of apposing cells. Biophysical assays have been developed to determine the unstressed (no-force) 2-D affinity but fail to disclose its dependence on force. Here we develop an analytical model to estimate the 2-D kinetics of diverse receptor-ligand pairs as a function of force, including antibody-antigen, vascular selectin-ligand, and bacterial adhesin-ligand interactions. The model can account for multiple bond interactions necessary to mediate adhesion and resist detachment amid high hemodynamic forces. Using this model, we provide a generalized biophysical interpretation of the counterintuitive force-induced stabilization of cell rolling observed by a select subset of receptor-ligand pairs with specific intrinsic kinetic properties. This study enables us to understand how single-molecule and multibond biophysics modulate the macroscopic cell behavior in diverse pathophysiological processes. PMID:21575567

Estimation of the number of biophotons involved in the visual perception of a single-object image: biophoton intensity can be considerably higher inside cells than outside.

PubMed

Bókkon, I; Salari, V; Tuszynski, J A; Antal, I

2010-09-02

Recently, we have proposed a redox molecular hypothesis about the natural biophysical substrate of visual perception and imagery [1,6]. Namely, the retina transforms external photon signals into electrical signals that are carried to the V1 (striatecortex). Then, V1 retinotopic electrical signals (spike-related electrical signals along classical axonal-dendritic pathways) can be converted into regulated ultraweak bioluminescent photons (biophotons) through redox processes within retinotopic visual neurons that make it possible to create intrinsic biophysical pictures during visual perception and imagery. However, the consensus opinion is to consider biophotons as by-products of cellular metabolism. This paper argues that biophotons are not by-products, other than originating from regulated cellular radical/redox processes. It also shows that the biophoton intensity can be considerably higher inside cells than outside. Our simple calculations, within a level of accuracy, suggest that the real biophoton intensity in retinotopic neurons may be sufficient for creating intrinsic biophysical picture representation of a single-object image during visual perception. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Modeling the dispersion effects of contractile fibers in smooth muscles

NASA Astrophysics Data System (ADS)

Murtada, Sae-Il; Kroon, Martin; Holzapfel, Gerhard A.

2010-12-01

Micro-structurally based models for smooth muscle contraction are crucial for a better understanding of pathological conditions such as atherosclerosis, incontinence and asthma. It is meaningful that models consider the underlying mechanical structure and the biochemical activation. Hence, a simple mechanochemical model is proposed that includes the dispersion of the orientation of smooth muscle myofilaments and that is capable to capture available experimental data on smooth muscle contraction. This allows a refined study of the effects of myofilament dispersion on the smooth muscle contraction. A classical biochemical model is used to describe the cross-bridge interactions with the thin filament in smooth muscles in which calcium-dependent myosin phosphorylation is the only regulatory mechanism. A novel mechanical model considers the dispersion of the contractile fiber orientations in smooth muscle cells by means of a strain-energy function in terms of one dispersion parameter. All model parameters have a biophysical meaning and may be estimated through comparisons with experimental data. The contraction of the middle layer of a carotid artery is studied numerically. Using a tube the relationships between the internal pressure and the stretches are investigated as functions of the dispersion parameter, which implies a strong influence of the orientation of smooth muscle myofilaments on the contraction response. It is straightforward to implement this model in a finite element code to better analyze more complex boundary-value problems.

Universal algorithm for identification of fractional Brownian motion. A case of telomere subdiffusion.

PubMed

Burnecki, Krzysztof; Kepten, Eldad; Janczura, Joanna; Bronshtein, Irena; Garini, Yuval; Weron, Aleksander

2012-11-07

We present a systematic statistical analysis of the recently measured individual trajectories of fluorescently labeled telomeres in the nucleus of living human cells. The experiments were performed in the U2OS cancer cell line. We propose an algorithm for identification of the telomere motion. By expanding the previously published data set, we are able to explore the dynamics in six time orders, a task not possible earlier. As a result, we establish a rigorous mathematical characterization of the stochastic process and identify the basic mathematical mechanisms behind the telomere motion. We find that the increments of the motion are stationary, Gaussian, ergodic, and even more chaotic--mixing. Moreover, the obtained memory parameter estimates, as well as the ensemble average mean square displacement reveal subdiffusive behavior at all time spans. All these findings statistically prove a fractional Brownian motion for the telomere trajectories, which is confirmed by a generalized p-variation test. Taking into account the biophysical nature of telomeres as monomers in the chromatin chain, we suggest polymer dynamics as a sufficient framework for their motion with no influence of other models. In addition, these results shed light on other studies of telomere motion and the alternative telomere lengthening mechanism. We hope that identification of these mechanisms will allow the development of a proper physical and biological model for telomere subdynamics. This array of tests can be easily implemented to other data sets to enable quick and accurate analysis of their statistical characteristics. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

The role of cavitation in liposome formation.

PubMed

Richardson, Eric S; Pitt, William G; Woodbury, Dixon J

2007-12-15

Liposome size is a vital parameter of many quantitative biophysical studies. Sonication, or exposure to ultrasound, is used widely to manufacture artificial liposomes, yet little is known about the mechanism by which liposomes are affected by ultrasound. Cavitation, or the oscillation of small gas bubbles in a pressure-varying field, has been shown to be responsible for many biophysical effects of ultrasound on cells. In this study, we correlate the presence and type of cavitation with a decrease in liposome size. Aqueous lipid suspensions surrounding a hydrophone were exposed to various intensities of ultrasound and hydrostatic pressures before measuring their size distribution with dynamic light scattering. As expected, increasing ultrasound intensity at atmospheric pressure decreased the average liposome diameter. The presence of collapse cavitation was manifested in the acoustic spectrum at high ultrasonic intensities. Increasing hydrostatic pressure was shown to inhibit the presence of collapse cavitation. Collapse cavitation, however, did not correlate with decreases in liposome size, as changes in size still occurred when collapse cavitation was inhibited either by lowering ultrasound intensity or by increasing static pressure. We propose a mechanism whereby stable cavitation, another type of cavitation present in sound fields, causes fluid shearing of liposomes and reduction of liposome size. A mathematical model was developed based on the Rayleigh-Plesset equation of bubble dynamics and principles of acoustic microstreaming to estimate the shear field magnitude around an oscillating bubble. This model predicts the ultrasound intensities and pressures needed to create shear fields sufficient to cause liposome size change, and correlates well with our experimental data.

Determining Crop Soil Water Deficit with an UAS

USDA-ARS?s Scientific Manuscript database

Remote sensing (RS) techniques have been used to identify crops grown during different seasons and to estimate crop bio-physical characteristics and water use. Images from satellites such as Landsat 5, 7, and 8 have been used extensively to map crop evapotranspiration rates (ET) using a suite of alg...

Defining conservation priorities using fragmentation forecasts

Treesearch

David Wear; John Pye; Kurt H. Riitters

2004-01-01

Methods are developed for forecasting the effects of population and economic growth on the distribution of interior forest habitat. An application to the southeastern United States shows that models provide significant explanatory power with regard to the observed distribution of interior forest. Estimates for economic and biophysical variables are significant and...

A remote-sensing driven tool for estimating crop stress and yields

USDA-ARS?s Scientific Manuscript database

Biophysical crop simulation models are normally forced with precipitation data recorded with either gages or ground-based radar. However, ground based recording networks are not available at spatial and temporal scales needed to drive the models at many critical places on earth. An alternative would...

Perceived impacts of disturbance in central hardwood ecosystems

Treesearch

John Hetherington; John Burde

1997-01-01

The intent of this research was to empirically identify and estimate the relationship between perceived scenic beauty and biophysical resources of hardwood stands in southeast Missouri under various disturbance regimes. The scenic effects of different harvest methods, wind, and fire were systematically investigated using a psychophysical approach. Ratings of scenic...

Long-term Hydroclimate and Pacific Salmon Population Linkages Across a Headwater-to-Coast Continuum in Northern British Columbia, Canada: A Perspective From Multiple Tree-Ring Proxy Records

NASA Astrophysics Data System (ADS)

Welsh, C.; Smith, D. J.; Edwards, T.; Prowse, T.

2016-12-01

Ongoing climate change is expected to have lasting impacts on the runoff behaviour of rivers in northern British Columbia, Canada. Of particular concern is the loss of mountain snowpack and greater rainfall totals altering hydrograph characteristics. Sustained deviations in seasonal streamflow will pose significant challenges for effective watershed management. These ongoing changes highlight the importance of improving our understanding of the long-term biophysical linkages between the storage and release of water and downstream freshwater ecosystems. Such integrated research is particularly relevant to fisheries management as fluctuations in populations of Pacific salmon represent a complex and management-relevant biophysical issue in northern Canada. Unfortunately, hydroclimate and salmon productivity records in this region are sparse and of short duration, constraining our understanding of the impact of climate-induced hydrologic changes and biological responses to the last century. Proxy records derived from tree-rings provide annually or seasonally resolved data and have played a prominent role in attempts to establish how hydroclimate has varied in the past. The objective of my doctoral research is to reconstruct the prehistoric hydroclimate and salmon population trends in the Skeena, Nass and Stikine Watersheds using multiple tree-ring proxies to investigate the long-term biophysical linkages extending across a headwater-to-coast continuum in northern British Columbia, Canada. Ring-width, wood density and stable isotope chronologies using a number of mid-to high-elevation tree species will be constructed across each basin and sub-basin area for the purposes of reconstrucing the predominent temperature and precipiation signature that influence streamflow. Preliminary tree-ring δ18O and δ13C-isotope results indicate a strong negative association with mean monthly relative humidity values, suggesting a physiological control by moisture loss. The results of this study highlight the importance of combining several tree-ring parameters and species in order to strengthen streamflow reconstructions. This study is ongoing and has an estimated completion timeframe of spring 2018.

The γ parameter of the stretched-exponential model is influenced by internal gradients: validation in phantoms.

PubMed

Palombo, Marco; Gabrielli, Andrea; De Santis, Silvia; Capuani, Silvia

2012-03-01

In this paper, we investigate the image contrast that characterizes anomalous and non-gaussian diffusion images obtained using the stretched exponential model. This model is based on the introduction of the γ stretched parameter, which quantifies deviation from the mono-exponential decay of diffusion signal as a function of the b-value. To date, the biophysical substrate underpinning the contrast observed in γ maps, in other words, the biophysical interpretation of the γ parameter (or the fractional order derivative in space, β parameter) is still not fully understood, although it has already been applied to investigate both animal models and human brain. Due to the ability of γ maps to reflect additional microstructural information which cannot be obtained using diffusion procedures based on gaussian diffusion, some authors propose this parameter as a measure of diffusion heterogeneity or water compartmentalization in biological tissues. Based on our recent work we suggest here that the coupling between internal and diffusion gradients provide pseudo-superdiffusion effects which are quantified by the stretching exponential parameter γ. This means that the image contrast of Mγ maps reflects local magnetic susceptibility differences (Δχ(m)), thus highlighting better than T(2)(∗) contrast the interface between compartments characterized by Δχ(m). Thanks to this characteristic, Mγ imaging may represent an interesting tool to develop contrast-enhanced MRI for molecular imaging. The spectroscopic and imaging experiments (performed in controlled micro-beads dispersion) that are reported here, strongly suggest internal gradients, and as a consequence Δχ(m), to be an important factor in fully understanding the source of contrast in anomalous diffusion methods that are based on a stretched exponential model analysis of diffusion data obtained at varying gradient strengths g. Copyright © 2012 Elsevier Inc. All rights reserved.

Biophysical influence of coumarin 35 on bovine serum albumin: Spectroscopic study

NASA Astrophysics Data System (ADS)

Bayraktutan, Tuğba; Onganer, Yavuz

2017-01-01

The binding mechanism and protein-fluorescence probe interactions between bovine serum albumin (BSA) and coumarin 35 (C35) was investigated by using UV-Vis absorption and fluorescence spectroscopies since they remain major research topics in biophysics. The spectroscopic data indicated that a fluorescence quenching process for BSA-C35 system was occurred. The fluorescence quenching processes were analyzed using Stern-Volmer method. In this regard, Stern-Volmer quenching constants (KSV) and binding constants were calculated at different temperatures. The distance r between BSA (donor) and C35 (acceptor) was determined by exploiting fluorescence resonance energy transfer (FRET) method. Synchronous fluorescence spectra were also studied to observe information about conformational changes. Moreover, thermodynamics parameters were calculated for better understanding of interactions and conformational changes of the system.

The value of mechanistic biophysical information for systems-level understanding of complex biological processes such as cytokinesis.

PubMed

Pollard, Thomas D

2014-12-02

This review illustrates the value of quantitative information including concentrations, kinetic constants and equilibrium constants in modeling and simulating complex biological processes. Although much has been learned about some biological systems without these parameter values, they greatly strengthen mechanistic accounts of dynamical systems. The analysis of muscle contraction is a classic example of the value of combining an inventory of the molecules, atomic structures of the molecules, kinetic constants for the reactions, reconstitutions with purified proteins and theoretical modeling to account for the contraction of whole muscles. A similar strategy is now being used to understand the mechanism of cytokinesis using fission yeast as a favorable model system. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Biophysical, morphological, canopy optical property, and productivity data from the Superior National Forest

NASA Technical Reports Server (NTRS)

Hall, F. G.; Huemmrich, K. F.; Strebel, D. E.; Goetz, S. J.; Nickeson, J. E.; Woods, K. D.

1992-01-01

Described here are the results of a NASA field experiment conducted in the Superior National Forest near Ely, Minnesota, during the summers of 1983 and 1984. The purpose of the experiment was to examine the use of remote sensing to provide measurements of biophysical parameters in the boreal forests. Leaf area index, biomass, net primary productivity, canopy coverage, overstory and understory species composition data are reported for about 60 sites, representing a range of stand density and age for aspen and spruce. Leaf, needle, and bark high-resolution spectral reflectance and transmittance data are reported for the major boreal forest species. Canopy bidirectional reflectance measurements are provided from a helicopter-mounted Barnes Multiband Modular Radiometer (MMR) and the Thematic Mapper Simulator (TMS) on the NASA C-130 aircraft.

Natural Forest Biomass Estimation Based on Plantation Information Using PALSAR Data

PubMed Central

Avtar, Ram; Suzuki, Rikie; Sawada, Haruo

2014-01-01

Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (σ0) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR σ0 showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR σ0 were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R2 = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE  = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal. PMID:24465908

Information-geometric measures as robust estimators of connection strengths and external inputs.

PubMed

Tatsuno, Masami; Fellous, Jean-Marc; Amari, Shun-Ichi

2009-08-01

Information geometry has been suggested to provide a powerful tool for analyzing multineuronal spike trains. Among several advantages of this approach, a significant property is the close link between information-geometric measures and neural network architectures. Previous modeling studies established that the first- and second-order information-geometric measures corresponded to the number of external inputs and the connection strengths of the network, respectively. This relationship was, however, limited to a symmetrically connected network, and the number of neurons used in the parameter estimation of the log-linear model needed to be known. Recently, simulation studies of biophysical model neurons have suggested that information geometry can estimate the relative change of connection strengths and external inputs even with asymmetric connections. Inspired by these studies, we analytically investigated the link between the information-geometric measures and the neural network structure with asymmetrically connected networks of N neurons. We focused on the information-geometric measures of orders one and two, which can be derived from the two-neuron log-linear model, because unlike higher-order measures, they can be easily estimated experimentally. Considering the equilibrium state of a network of binary model neurons that obey stochastic dynamics, we analytically showed that the corrected first- and second-order information-geometric measures provided robust and consistent approximation of the external inputs and connection strengths, respectively. These results suggest that information-geometric measures provide useful insights into the neural network architecture and that they will contribute to the study of system-level neuroscience.

Unified Bayesian Estimator of EEG Reference at Infinity: rREST (Regularized Reference Electrode Standardization Technique)

PubMed Central

Hu, Shiang; Yao, Dezhong; Valdes-Sosa, Pedro A.

2018-01-01

The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs—with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the “oracle” choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance. PMID:29780302

Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion-EO-1 Data

NASA Technical Reports Server (NTRS)

Thenkabail, Prasad S.; Mariotto, Isabella; Gumma, Murali Krishna; Middleton, Elizabeth M.; Landis, David R.; Huemmrich, K. Fred

2013-01-01

The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy approx. 70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using approx. 20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was approx. 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or "the curse of high dimensionality") in hyperspectral data for a particular application (e.g., biophysical characterization of crops). The findings of this study will make a significant contribution to future hyperspectral missions such as NASA's HyspIRI. Index Terms-Hyperion, field reflectance, imaging spectroscopy, HyspIRI, biophysical parameters, hyperspectral vegetation indices, hyperspectral narrowbands, broadbands.

Use of passive UAS imaging to measure biophysical parameters in a southern Rocky Mountain subalpine forest

NASA Astrophysics Data System (ADS)

Caldwell, M. K.; Sloan, J.; Mladinich, C. S.; Wessman, C. A.

2013-12-01

Unmanned Aerial Systems (UAS) can provide detailed, fine spatial resolution imagery for ecological uses not otherwise obtainable through standard methods. The use of UAS imagery for ecology is a rapidly -evolving field, where the study of forest landscape ecology can be augmented using UAS imagery to scale and validate biophysical data from field measurements to spaceborne observations. High resolution imagery provided by UAS (30 cm2 pixels) offers detailed canopy cover and forest structure data in a time efficient and inexpensive manner. Using a GoPro Hero2 (2 mm focal length) camera mounted in the nose cone of a Raven unmanned system, we collected aerial and thermal data monthly during the summer 2013, over two subalpine forests in the Southern Rocky Mountains in Colorado. These forests are dominated by lodgepole pine (Pinus ponderosae) and have experienced insect-driven (primarily mountain pine beetle; MPB, Dendroctonus ponderosae) mortality. Objectives of this study include observations of forest health variables such as canopy water content (CWC) from thermal imagery and leaf area index (LAI), biomass and forest productivity from the Normalized Difference Vegetation Index (NDVI) from UAS imagery. Observations were, validated with ground measurements. Images were processed using a combination of AgiSoft Photoscan professional software and ENVI remote imaging software. We utilized the software Leaf Area Index Calculator (LAIC) developed by Córcoles et al. (2013) for calculating LAI from digital images and modified to conform to leaf area of needle-leaf trees as in Chen and Cihlar (1996) . LAIC uses a K-means cluster analysis to decipher the RGB levels for each pixel and distinguish between green aboveground vegetation and other materials, and project leaf area per unit of ground surface area (i.e. half total needle surface area per unit area). Preliminary LAIC UAS data shows summer average LAI was 3.8 in the most dense forest stands and 2.95 in less dense stands. These data correspond to 4.8 and 2.2 respectively from in situ Licor LAI 2200 measurements (Wilcoxon signed rank p value of 0.25, indicating there is no significant difference between LAIC and field measurements). Imagery over plots indicates about 12% canopy cover from standing dead vegetation within plots, which corresponds to about a 10% estimate of standing dead measured in the field. The next steps for analysis include calculating NDVI and CWC for plot-level vegetation, and scaling to the surrounding forested landscape. These high resolution estimates from UAS imagery will provide forest stand-to- landscape level biophysical data for forest health assessments, management, drought and disturbance monitoring and climate change modeling. Chen, J. M., and J. Cihlar. 1996. Retrieving LAI of boreal conifer forests using Landsat TM images. RSE 55:153-162. Córcoles, J., J. Ortega, D. Hernández, and M. Moreno. 2013. Use of digital photography from unmanned aerial vehicles for estimation of LAI in onion. EJoA. 45:96-104.

Reducing uncertainties in energy dissipation measurements in atomic force spectroscopy of molecular networks and cell-adhesion studies.

PubMed

Biswas, Soma; Leitao, Samuel; Theillaud, Quentin; Erickson, Blake W; Fantner, Georg E

2018-06-20

Atomic force microscope (AFM) based single molecule force spectroscopy (SMFS) is a valuable tool in biophysics to investigate the ligand-receptor interactions, cell adhesion and cell mechanics. However, the force spectroscopy data analysis needs to be done carefully to extract the required quantitative parameters correctly. Especially the large number of molecules, commonly involved in complex networks formation; leads to very complicated force spectroscopy curves. One therefore, generally characterizes the total dissipated energy over a whole pulling cycle, as it is difficult to decompose the complex force curves into individual single molecule events. However, calculating the energy dissipation directly from the transformed force spectroscopy curves can lead to a significant over-estimation of the dissipated energy during a pulling experiment. The over-estimation of dissipated energy arises from the finite stiffness of the cantilever used for AFM based SMFS. Although this error can be significant, it is generally not compensated for. This can lead to significant misinterpretation of the energy dissipation (up to the order of 30%). In this paper, we show how in complex SMFS the excess dissipated energy caused by the stiffness of the cantilever can be identified and corrected using a high throughput algorithm. This algorithm is then applied to experimental results from molecular networks and cell-adhesion measurements to quantify the improvement in the estimation of the total energy dissipation.

Retrieval of Winter Wheat Leaf Area Index from Chinese GF-1 Satellite Data Using the PROSAIL Model.

PubMed

Li, He; Liu, Gaohuan; Liu, Qingsheng; Chen, Zhongxin; Huang, Chong

2018-04-06

Leaf area index (LAI) is one of the key biophysical parameters in crop structure. The accurate quantitative estimation of crop LAI is essential to verify crop growth and health. The PROSAIL radiative transfer model (RTM) is one of the most established methods for estimating crop LAI. In this study, a look-up table (LUT) based on the PROSAIL RTM was first used to estimate winter wheat LAI from GF-1 data, which accounted for some available prior knowledge relating to the distribution of winter wheat characteristics. Next, the effects of 15 LAI-LUT strategies with reflectance bands and 10 LAI-LUT strategies with vegetation indexes on the accuracy of the winter wheat LAI retrieval with different phenological stages were evaluated against in situ LAI measurements. The results showed that the LUT strategies of LAI-GNDVI were optimal and had the highest accuracy with a root mean squared error (RMSE) value of 0.34, and a coefficient of determination (R²) of 0.61 during the elongation stages, and the LUT strategies of LAI-Green were optimal with a RMSE of 0.74, and R² of 0.20 during the grain-filling stages. The results demonstrated that the PROSAIL RTM had great potential in winter wheat LAI inversion with GF-1 satellite data and the performance could be improved by selecting the appropriate LUT inversion strategies in different growth periods.

High Tensile Strength of Engineered β-Solenoid Fibrils via Sonication and Pulling.

PubMed

Peng, Zeyu; Parker, Amanda S; Peralta, Maria D R; Ravikumar, Krishnakumar M; Cox, Daniel L; Toney, Michael D

2017-11-07

We present estimates of ultimate tensile strength (UTS) for two engineered β-solenoid protein mutant fibril structures (spruce budworm and Rhagium inquisitor antifreeze proteins) derived from sonication-based measurements and from force pulling molecular dynamics simulations, both in water. Sonication experiments generate limiting scissioned fibrils with a well-defined length-to-width correlation for the mutant spruce budworm protein and the resultant UTS estimate is 0.66 ± 0.08 GPa. For fibrils formed from engineered R. inquisitor antifreeze protein, depending upon geometry, we estimate UTSs of 3.5 ± 3.2-5.5 ± 5.1 GPa for proteins with interfacial disulfide bonds, and 1.6 ± 1.5-2.5 ± 2.3 GPa for the reduced form. The large error bars for the R. inquisitor structures are intrinsic to the broad distribution of limiting scission lengths. Simulations provide pulling velocity-dependent UTSs increasing from 0.2 to 1 GPa in the available speed range, and 1.5 GPa extrapolated to the speeds expected in the sonication experiments. Simulations yield low-velocity values for the Young's modulus of 6.0 GPa. Without protein optimization, these mechanical parameters are similar to those of spider silk and Kevlar, but in contrast to spider silk, these proteins have a precisely known sequence-structure relationship. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Biophysical controls on surface fuel litterfall and decomposition in the northern Rocky Mountains, USA

Treesearch

Robert E. Keane

2008-01-01

Litterfall and decomposition rates of the organic matter that comprise forest fuels are important to fire management, because they define fuel treatment longevity and provide parameters to design, test, and validate ecosystem models. This study explores the environmental factors that control litterfall and decomposition in the context of fuel management for several...

Laboratory Model of the Cardiovascular System for Experimental Demonstration of Pulse Wave Propagation

ERIC Educational Resources Information Center

Stojadinovic, Bojana; Nestorovic, Zorica; Djuric, Biljana; Tenne, Tamar; Zikich, Dragoslav; Žikic, Dejan

2017-01-01

The velocity by which a disturbance moves through the medium is the wave velocity. Pulse wave velocity is among the key parameters in hemodynamics. Investigation of wave propagation through the fluid-filled elastic tube has a great importance for the proper biophysical understanding of the nature of blood flow through the cardiovascular system.…

XXIst century magnetotherapy.

PubMed

Markov, M

2015-09-01

This paper discusses the state of the art therapeutic application of magnetic and electromagnetic fields (EMF) in treatment of various medical problems - from pain relief to musculoskeletal trauma, to vascular and endocrine disorders. The paper describes problems related to physical parameters of used fields, biophysical dosimetry, clinical protocols, and safety of the device operators. Clinical benefits and mechanisms of action are also discussed.

A fully synthetic human Fab antibody library based on fixed VH/VL framework pairings with favorable biophysical properties

PubMed Central

Tiller, Thomas; Schuster, Ingrid; Deppe, Dorothée; Siegers, Katja; Strohner, Ralf; Herrmann, Tanja; Berenguer, Marion; Poujol, Dominique; Stehle, Jennifer; Stark, Yvonne; Heßling, Martin; Daubert, Daniela; Felderer, Karin; Kaden, Stefan; Kölln, Johanna; Enzelberger, Markus; Urlinger, Stefanie

2013-01-01

This report describes the design, generation and testing of Ylanthia, a fully synthetic human Fab antibody library with 1.3E+11 clones. Ylanthia comprises 36 fixed immunoglobulin (Ig) variable heavy (VH)/variable light (VL) chain pairs, which cover a broad range of canonical complementarity-determining region (CDR) structures. The variable Ig heavy and Ig light (VH/VL) chain pairs were selected for biophysical characteristics favorable to manufacturing and development. The selection process included multiple parameters, e.g., assessment of protein expression yield, thermal stability and aggregation propensity in fragment antigen binding (Fab) and IgG1 formats, and relative Fab display rate on phage. The framework regions are fixed and the diversified CDRs were designed based on a systematic analysis of a large set of rearranged human antibody sequences. Care was taken to minimize the occurrence of potential posttranslational modification sites within the CDRs. Phage selection was performed against various antigens and unique antibodies with excellent biophysical properties were isolated. Our results confirm that quality can be built into an antibody library by prudent selection of unmodified, fully human VH/VL pairs as scaffolds. PMID:23571156

A reverse engineering algorithm for neural networks, applied to the subthalamopallidal network of basal ganglia.

PubMed

Floares, Alexandru George

2008-01-01

Modeling neural networks with ordinary differential equations systems is a sensible approach, but also very difficult. This paper describes a new algorithm based on linear genetic programming which can be used to reverse engineer neural networks. The RODES algorithm automatically discovers the structure of the network, including neural connections, their signs and strengths, estimates its parameters, and can even be used to identify the biophysical mechanisms involved. The algorithm is tested on simulated time series data, generated using a realistic model of the subthalamopallidal network of basal ganglia. The resulting ODE system is highly accurate, and results are obtained in a matter of minutes. This is because the problem of reverse engineering a system of coupled differential equations is reduced to one of reverse engineering individual algebraic equations. The algorithm allows the incorporation of common domain knowledge to restrict the solution space. To our knowledge, this is the first time a realistic reverse engineering algorithm based on linear genetic programming has been applied to neural networks.

Psychophysics of time perception and intertemporal choice models

NASA Astrophysics Data System (ADS)

Takahashi, Taiki; Oono, Hidemi; Radford, Mark H. B.

2008-03-01

Intertemporal choice and psychophysics of time perception have been attracting attention in econophysics and neuroeconomics. Several models have been proposed for intertemporal choice: exponential discounting, general hyperbolic discounting (exponential discounting with logarithmic time perception of the Weber-Fechner law, a q-exponential discount model based on Tsallis's statistics), simple hyperbolic discounting, and Stevens' power law-exponential discounting (exponential discounting with Stevens' power time perception). In order to examine the fitness of the models for behavioral data, we estimated the parameters and AICc (Akaike Information Criterion with small sample correction) of the intertemporal choice models by assessing the points of subjective equality (indifference points) at seven delays. Our results have shown that the orders of the goodness-of-fit for both group and individual data were [Weber-Fechner discounting (general hyperbola) > Stevens' power law discounting > Simple hyperbolic discounting > Exponential discounting], indicating that human time perception in intertemporal choice may follow the Weber-Fechner law. Indications of the results for neuropsychopharmacological treatments of addiction and biophysical processing underlying temporal discounting and time perception are discussed.

The Spectrum of a Dissociation Intermediate of Cysteine. A Biophysical Chemistry Experiment.

ERIC Educational Resources Information Center

Splittgerber, A. G.; Chinander, L. L.

1988-01-01

Outlines a laboratory exercise that makes use of Beer's Law plots of cysteine constructed at several pH values over a broad range of wavelengths to estimate the tautomeric ratio (R) of two singly charged ionic forms, calculate the microscopic constants, and construct ultraviolet spectra for both light absorbing species. (CW)

Biophysical controls on carbon and water vapor fluxes across a grassland climatic gradient in the United States

USDA-ARS?s Scientific Manuscript database

Understanding of the underlying causes of spatial variation in exchange of carbon and water vapor fluxes between grasslands and the atmosphere is crucial for accurate estimates of regional and global carbon and water budgets, and for predicting the impact of climate change on biosphere–atmosphere fe...

Scale as the common language for soil variations revealed with geophysics, biophysics, and remote sensing

USDA-ARS?s Scientific Manuscript database

Quantification and estimation of crop response to management are important for efficient use of resources. Because the spatial distribution of crop response is related to the distribution of soil properties, crop response to management practices will also have a strong spatial component. Most plot r...

A biophysical approach using water deficit factor for daily estimations of evapotranspiration and CO2 uptake in Mediterranean environments

NASA Astrophysics Data System (ADS)

Helman, David; Lensky, Itamar M.; Osem, Yagil; Rohatyn, Shani; Rotenberg, Eyal; Yakir, Dan

2017-09-01

Estimations of ecosystem-level evapotranspiration (ET) and CO2 uptake in water-limited environments are scarce and scaling up ground-level measurements is not straightforward. A biophysical approach using remote sensing (RS) and meteorological data (RS-Met) is adjusted to extreme high-energy water-limited Mediterranean ecosystems that suffer from continuous stress conditions to provide daily estimations of ET and CO2 uptake (measured as gross primary production, GPP) at a spatial resolution of 250 m. The RS-Met was adjusted using a seasonal water deficit factor (fWD) based on daily rainfall, temperature and radiation data. We validated our adjusted RS-Met with eddy covariance flux measurements using a newly developed mobile lab system and the single active FLUXNET station operating in this region (Yatir pine forest station) at a total of seven forest and non-forest sites across a climatic transect in Israel (280-770 mm yr-1). RS-Met was also compared to the satellite-borne MODIS-based ET and GPP products (MOD16 and MOD17, respectively) at these sites.Results show that the inclusion of the fWD significantly improved the model, with R = 0.64-0.91 for the ET-adjusted model (compared to 0.05-0.80 for the unadjusted model) and R = 0.72-0.92 for the adjusted GPP model (compared to R = 0.56-0.90 of the non-adjusted model). The RS-Met (with the fWD) successfully tracked observed changes in ET and GPP between dry and wet seasons across the sites. ET and GPP estimates from the adjusted RS-Met also agreed well with eddy covariance estimates on an annual timescale at the FLUXNET station of Yatir (266 ± 61 vs. 257 ± 58 mm yr-1 and 765 ± 112 vs. 748 ± 124 gC m-2 yr-1 for ET and GPP, respectively). Comparison with MODIS products showed consistently lower estimates from the MODIS-based models, particularly at the forest sites. Using the adjusted RS-Met, we show that afforestation significantly increased the water use efficiency (the ratio of carbon uptake to ET) in this region, with the positive effect decreasing when moving from dry to more humid environments, strengthening the importance of drylands afforestation. This simple yet robust biophysical approach shows promise for reliable ecosystem-level estimations of ET and CO2 uptake in extreme high-energy water-limited environments.

Distilling allometric and environmental information from time series of conduit size: the standardization issue and its relationship to tree hydraulic architecture.

PubMed

Carrer, Marco; von Arx, Georg; Castagneri, Daniele; Petit, Giai

2015-01-01

Trees are among the best natural archives of past environmental information. Xylem anatomy preserves information related to tree allometry and ecophysiological performance, which is not available from the more customary ring-width or wood-density proxy parameters. Recent technological advances make tree-ring anatomy very attractive because time frames of many centuries can now be covered. This calls for the proper treatment of time series of xylem anatomical attributes. In this article, we synthesize current knowledge on the biophysical and physiological mechanisms influencing the short- to long-term variation in the most widely used wood-anatomical feature, namely conduit size. We also clarify the strong mechanistic link between conduit-lumen size, tree hydraulic architecture and height growth. Among the key consequences of these biophysical constraints is the pervasive, increasing trend of conduit size during ontogeny. Such knowledge is required to process time series of anatomical parameters correctly in order to obtain the information of interest. An appropriate standardization procedure is fundamental when analysing long tree-ring-related chronologies. When dealing with wood-anatomical parameters, this is even more critical. Only an interdisciplinary approach involving ecophysiology, wood anatomy and dendrochronology will help to distill the valuable information about tree height growth and past environmental variability correctly. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A generic implementation of replica exchange with solute tempering (REST2) algorithm in NAMD for complex biophysical simulations

NASA Astrophysics Data System (ADS)

Jo, Sunhwan; Jiang, Wei

2015-12-01

Replica Exchange with Solute Tempering (REST2) is a powerful sampling enhancement algorithm of molecular dynamics (MD) in that it needs significantly smaller number of replicas but achieves higher sampling efficiency relative to standard temperature exchange algorithm. In this paper, we extend the applicability of REST2 for quantitative biophysical simulations through a robust and generic implementation in greatly scalable MD software NAMD. The rescaling procedure of force field parameters controlling REST2 "hot region" is implemented into NAMD at the source code level. A user can conveniently select hot region through VMD and write the selection information into a PDB file. The rescaling keyword/parameter is written in NAMD Tcl script interface that enables an on-the-fly simulation parameter change. Our implementation of REST2 is within communication-enabled Tcl script built on top of Charm++, thus communication overhead of an exchange attempt is vanishingly small. Such a generic implementation facilitates seamless cooperation between REST2 and other modules of NAMD to provide enhanced sampling for complex biomolecular simulations. Three challenging applications including native REST2 simulation for peptide folding-unfolding transition, free energy perturbation/REST2 for absolute binding affinity of protein-ligand complex and umbrella sampling/REST2 Hamiltonian exchange for free energy landscape calculation were carried out on IBM Blue Gene/Q supercomputer to demonstrate efficacy of REST2 based on the present implementation.

Aboveground Biomass and Dynamics of Forest Attributes using LiDAR Data and Vegetation Model

NASA Astrophysics Data System (ADS)

V V L, P. A.

2015-12-01

In recent years, biomass estimation for tropical forests has received much attention because of the fact that regional biomass is considered to be a critical input to climate change. Biomass almost determines the potential carbon emission that could be released to the atmosphere due to deforestation or conservation to non-forest land use. Thus, accurate biomass estimation is necessary for better understating of deforestation impacts on global warming and environmental degradation. In this context, forest stand height inclusion in biomass estimation plays a major role in reducing the uncertainty in the estimation of biomass. The improvement in the accuracy in biomass shall also help in meeting the MRV objectives of REDD+. Along with the precise estimate of biomass, it is also important to emphasize the role of vegetation models that will most likely become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. Remote sensing is an efficient way to estimate forest parameters in large area, especially at regional scale where field data is limited. LIDAR (Light Detection And Ranging) provides accurate information on the vertical structure of forests. We estimated average tree canopy heights and AGB from GLAS waveform parameters by using a multi-regression linear model in forested area of Madhya Pradesh (area-3,08,245 km2), India. The derived heights from ICESat-GLAS were correlated with field measured tree canopy heights for 60 plots. Results have shown a significant correlation of R2= 74% for top canopy heights and R2= 57% for stand biomass. The total biomass estimation 320.17 Mt and canopy heights are generated by using random forest algorithm. These canopy heights and biomass maps were used in vegetation models to predict the changes biophysical/physiological characteristics of forest according to the changing climate. In our study we have used Dynamic Global Vegetation Model to understand the possible vegetation dynamics in the event of climate change. The vegetation represents a biogeographic regime. Simulations were carried out for 70 years time period. The model produced leaf area index and biomass for each plant functional type and biome for each grid in that region.

Properties of human brain sodium channel α-subunits expressed in HEK293 cells and their modulation by carbamazepine, phenytoin and lamotrigine

PubMed Central

Qiao, Xin; Sun, Guangchun; Clare, Jeffrey J; Werkman, Taco R; Wadman, Wytse J

2014-01-01

Background and purpose Voltage-activated Na+ channels contain one distinct α-subunit. In the brain NaV1.1, NaV1.2, NaV1.3 and NaV1.6 are the four most abundantly expressed α-subunits. The antiepileptic drugs (AEDs) carbamazepine, phenytoin and lamotrigine have voltage-gated Na+ channels as their primary therapeutic targets. This study provides a systematic comparison of the biophysical properties of these four α-subunits and characterizes their interaction with carbamazepine, phenytoin and lamotrigine. Experimental approach Na+ currents were recorded in voltage-clamp mode in HEK293 cells stably expressing one of the four α-subunits. Key results NaV1.2 and NaV1.3 subunits have a relatively slow recovery from inactivation, compared with the other subunits and NaV1.1 subunits generate the largest window current. Lamotrigine evokes a larger maximal shift of the steady-state inactivation relationship than carbamazepine or phenytoin. Carbamazepine shows the highest binding rate to the α-subunits. Lamotrigine binding to NaV1.1 subunits is faster than to the other α-subunits. Lamotrigine unbinding from the α-subunits is slower than that of carbamazepine and phenytoin. Conclusions and implications The four Na+ channel α-subunits show subtle differences in their biophysical properties, which, in combination with their (sub)cellular expression patterns in the brain, could contribute to differences in neuronal excitability. We also observed differences in the parameters that characterize AED binding to the Na+ channel subunits. Particularly, lamotrigine binding to the four α-subunits suggests a subunit-specific response. Such differences will have consequences for the clinical efficacy of AEDs. Knowledge of the biophysical and binding parameters could be employed to optimize therapeutic strategies and drug development. PMID:24283699

Analyzing Single-Molecule Time Series via Nonparametric Bayesian Inference

PubMed Central

Hines, Keegan E.; Bankston, John R.; Aldrich, Richard W.

2015-01-01

The ability to measure the properties of proteins at the single-molecule level offers an unparalleled glimpse into biological systems at the molecular scale. The interpretation of single-molecule time series has often been rooted in statistical mechanics and the theory of Markov processes. While existing analysis methods have been useful, they are not without significant limitations including problems of model selection and parameter nonidentifiability. To address these challenges, we introduce the use of nonparametric Bayesian inference for the analysis of single-molecule time series. These methods provide a flexible way to extract structure from data instead of assuming models beforehand. We demonstrate these methods with applications to several diverse settings in single-molecule biophysics. This approach provides a well-constrained and rigorously grounded method for determining the number of biophysical states underlying single-molecule data. PMID:25650922

The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke

PubMed Central

Falcon, Maria Inez; Riley, Jeffrey D.; Jirsa, Viktor; McIntosh, Anthony R.; Shereen, Ahmed D.; Chen, E. Elinor; Solodkin, Ana

2015-01-01

There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual’s brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions. PMID:26579071

Fundamental remote sensing science research program. Part 1: Scene radiation and atmospheric effects characterization project

NASA Technical Reports Server (NTRS)

Murphy, R. E.; Deering, D. W.

1984-01-01

Brief articles summarizing the status of research in the scene radiation and atmospheric effect characterization (SRAEC) project are presented. Research conducted within the SRAEC program is focused on the development of empirical characterizations and mathematical process models which relate the electromagnetic energy reflected or emitted from a scene to the biophysical parameters of interest.

BOREAS Level-0 NS001 TMS Imagery: Digital Counts in BIL Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Newcomer, Jeffrey A.; Dominguez, Roseanne

2000-01-01

For BOREAS, the NS001 TMS imagery, along with the other remotely sensed images, was collected in order to provide spatially extensive information over the primary study areas. This information includes detailed land cover and biophysical parameter maps such as fPAR and LAI. Data collections occurred over the study areas during the 1994 field campaigns.

Synergy between optical and microwave remote sensing to derive soil and vegetation parameters from MAC Europe 1991 Experiment

NASA Technical Reports Server (NTRS)

Taconet, O.; Benallegue, M.; Vidal, A.; Vidal-Madjar, D.; Prevot, L.; Normand, M.

1993-01-01

The ability of remote sensing for monitoring vegetation density and soil moisture for agricultural applications is extensively studied. In optical bands, vegetation indices (NDVI, WDVI) in visible and near infrared reflectances are related to biophysical quantities as the leaf area index, the biomass. In active microwave bands, the quantitative assessment of crop parameters and soil moisture over agricultural areas by radar multiconfiguration algorithms remains prospective. Furthermore the main results are mostly validated on small test sites, but have still to be demonstrated in an operational way at a regional scale. In this study, a large data set of radar backscattering has been achieved at a regional scale on a French pilot watershed, the Orgeval, along two growing seasons in 1988 and 1989 (mainly wheat and corn). The radar backscattering was provided by the airborne scatterometer ERASME, designed at CRPE, (C and X bands and HH and VV polarizations). Empirical relationships to estimate water crop and soil moisture over wheat in CHH band under actual field conditions and at a watershed scale are investigated. Therefore, the algorithms developed in CHH band are applied for mapping the surface conditions over wheat fields using the AIRSAR and TMS images collected during the MAC EUROPE 1991 experiment. The synergy between optical and microwave bands is analyzed.

Brain metabolite alterations in infants born preterm with intrauterine growth restriction: association with structural changes and neurodevelopmental outcome.

PubMed

Simões, Rui V; Muñoz-Moreno, Emma; Cruz-Lemini, Mónica; Eixarch, Elisenda; Bargalló, Núria; Sanz-Cortés, Magdalena; Gratacós, Eduard

2017-01-01

Intrauterine growth restriction and premature birth represent 2 independent problems that may occur simultaneously and contribute to impaired neurodevelopment. The objective of the study was to assess changes in the frontal lobe metabolic profiles of 1 year old intrauterine growth restriction infants born prematurely and adequate-for-gestational-age controls, both premature and term adequate for gestational age and their association with brain structural and biophysical parameters and neurodevelopmental outcome at 2 years. A total of 26 prematurely born intrauterine growth restriction infants (birthweight <10th centile for gestational age), 22 prematurely born but adequate for gestational age controls, and 26 term adequate-for-gestational-age infants underwent brain magnetic resonance imaging and magnetic resonance spectroscopy at 1 year of age during natural sleep, on a 3 Tesla scanner. All brain T1-weighted and diffusion-weighted images were acquired along with short echo time single-voxel proton spectra from the frontal lobe. Magnetic resonance imaging/magnetic resonance spectroscopy data were processed to derive structural, biophysical, and metabolic information, respectively. Neurodevelopment was evaluated at 2 years of age using the Bayley Scales 3rd edition, assessing cognitive, language, motor, socioemotional, and adaptive behavior. Prematurely born intrauterine growth restriction infants had slightly smaller brain volumes and increased frontal lobe white matter mean diffusivity compared with both prematurely born but adequate for gestational age and term adequate for gestational age controls. Frontal lobe N-acetylaspartate levels were significantly lower in prematurely born intrauterine growth restriction than in prematurely born but adequate for gestational age infants but increased in prematurely born but adequate for gestational age compared with term adequate-for-gestational-age infants. The prematurely born intrauterine growth restriction group also showed slightly lower choline compounds, borderline decrements of estimated glutathione levels, and increased myoinositol to choline ratios, compared with prematurely born but adequate for gestational age controls. These specific metabolite changes were locally correlated to lower gray matter content and increased mean diffusivity and reduced white matter fraction and fractional anisotropy. Prematurely born intrauterine growth restriction infants also showed a tendency for poorer neurodevelopmental outcome at 2 years, associated with lower levels of frontal lobe N-acetylaspartate at 1 year within the preterm subset. Preterm intrauterine growth restriction infants showed altered brain metabolite profiles during a critical stage of brain maturation, which correlate with brain structural and biophysical parameters and neurodevelopmental outcome. Our results suggest altered neurodevelopmental trajectories in preterm intrauterine growth restriction and adequate-for-gestational-age infants, compared with term adequate-for-gestational-age infants, which require further characterization. Copyright © 2016 Elsevier Inc. All rights reserved.

Estimating cropland NPP using national crop inventory and MODIS derived crop specific parameters

NASA Astrophysics Data System (ADS)

Bandaru, V.; West, T. O.; Ricciuto, D. M.

2011-12-01

Estimates of cropland net primary production (NPP) are needed as input for estimates of carbon flux and carbon stock changes. Cropland NPP is currently estimated using terrestrial ecosystem models, satellite remote sensing, or inventory data. All three of these methods have benefits and problems. Terrestrial ecosystem models are often better suited for prognostic estimates rather than diagnostic estimates. Satellite-based NPP estimates often underestimate productivity on intensely managed croplands and are also limited to a few broad crop categories. Inventory-based estimates are consistent with nationally collected data on crop yields, but they lack sub-county spatial resolution. Integrating these methods will allow for spatial resolution consistent with current land cover and land use, while also maintaining total biomass quantities recorded in national inventory data. The main objective of this study was to improve cropland NPP estimates by using a modification of the CASA NPP model with individual crop biophysical parameters partly derived from inventory data and MODIS 8day 250m EVI product. The study was conducted for corn and soybean crops in Iowa and Illinois for years 2006 and 2007. We used EVI as a linear function for fPAR, and used crop land cover data (56m spatial resolution) to extract individual crop EVI pixels. First, we separated mixed pixels of both corn and soybean that occur when MODIS 250m pixel contains more than one crop. Second, we substituted mixed EVI pixels with nearest pure pixel values of the same crop within 1km radius. To get more accurate photosynthetic active radiation (PAR), we applied the Mountain Climate Simulator (MTCLIM) algorithm with the use of temperature and precipitation data from the North American Land Data Assimilation System (NLDAS-2) to generate shortwave radiation data. Finally, county specific light use efficiency (LUE) values of each crop for years 2006 to 2007 were determined by application of mean county inventory NPP and EVI-derived APAR into the Monteith equation. Results indicate spatial variability in LUE values across Iowa and Illinois. Northern regions of both Iowa and Illinois have higher LUE values than southern regions. This trend is reflected in NPP estimates. Results also show that corn has higher LUE values than soybean, resulting in higher NPP for corn than for soybean. Current NPP estimates were compared with NPP estimates from MOD17A3 product and with county inventory-based NPP estimates. Results indicate that current NPP estimates closely agree with inventory-based estimates, and that current NPP estimates are higher than those of the MOD17A3 product. It was also found that when mixed pixels were substituted with nearest pure pixels, revised NPP estimates were improved showing better agreement with inventory-based estimates.

The beginning of Space Life Science in China exploration rockets for biological experiment during 1960's

NASA Astrophysics Data System (ADS)

Jiang, Peidong; Zhang, Jingxue

The first step of space biological experiment in China was a set of five exploration rockets launched during 1964 to 1966, by Shanghai Institute of Machine and Electricity, and Institute of Biophysics of The Chinese Academy of Sciences. Three T-7AS1rockets for rats, mice and other samples in a biological cabin were launched and recovered safely in July of 1964 and June of 1965. Two T-7AS2rockets for dog, rats, mice and other samples in a biological cabin were launched and recovered safely in July of 1966. Institute of Biophysics in charged of the general design of biological experiments, telemetry of physiological parameters, and selection and training of experiment animals. The samples on-board were: rats, mice, dogs, and test tubes with fruit fly, enzyme, bacteria, E. Coli., lysozyme, bacteriaphage, RNAase, DNAase, crystals of enzyme, etc. Physiological, biochemical, bacte-riological, immunological, genetic, histochemical studies had been conducted, in cellular and sub cellular level. The postures of rat and dog were monitored during flight and under weight-lessness. Physiological parameters of ECG, blood pressure, respiration rate, body temperature were recorded. A dog named"Xiao Bao"was flight in 1966 with video monitor, life support system and conditioned reflex equipment. It flighted for more than 20 minutes and about 70km high. After 40 years, the experimental data recorded of its four physiological parameters during the flight process was reviewed. The change of 4 parameters during various phase of total flight process were compared, analyzed and discussed.

Urban Growth Detection Using Filtered Landsat Dense Time Trajectory in an Arid City

NASA Astrophysics Data System (ADS)

Ye, Z.; Schneider, A.

2014-12-01

Among all remote sensing environment monitoring techniques, time series analysis of biophysical index is drawing increasing attention. Although many of them studied forest disturbance and land cover change detection, few focused on urban growth mapping at medium spatial resolution. As Landsat archive becomes open accessible, methods using Landsat time-series imagery to detect urban growth is possible. It is found that a time trajectory from a newly developed urban area shows a dramatic drop of vegetation index. This enable the utilization of time trajectory analysis to distinguish impervious surface and crop land that has a different temporal biophysical pattern. Also, the time of change can be estimated, yet many challenges remain. Landsat data has lower temporal resolution, which may be worse when cloud-contaminated pixels and SLC-off effect exist. It is difficult to tease apart intra-annual, inter-annual, and land cover difference in a time series. Here, several methods of time trajectory analysis are utilized and compared to find a computationally efficient and accurate way on urban growth detection. A case study city, Ankara, Turkey is chosen for its arid climate and various landscape distributions. For preliminary research, Landsat TM and ETM+ scenes from 1998 to 2002 are chosen. NDVI, EVI, and SAVI are selected as research biophysical indices. The procedure starts with a seasonality filtering. Only areas with seasonality need to be filtered so as to decompose seasonality and extract overall trend. Harmonic transform, wavelet transform, and a pre-defined bell shape filter are used to estimate the overall trend in the time trajectory for each pixel. The point with significant drop in the trajectory is tagged as change point. After an urban change is detected, forward and backward checking is undertaken to make sure it is really new urban expansion other than short time crop fallow or forest disturbance. The method proposed here can capture most of the urban growth during research time period, although the accuracy of time point determination is a bit lower than this. Results from several biophysical indices and filtering methods are similar. Some fallows and bare lands in arid area are easily confused with urban impervious surface.

Stochastic time series analysis of fetal heart-rate variability

NASA Astrophysics Data System (ADS)

Shariati, M. A.; Dripps, J. H.

1990-06-01

Fetal Heart Rate(FHR) is one of the important features of fetal biophysical activity and its long term monitoring is used for the antepartum(period of pregnancy before labour) assessment of fetal well being. But as yet no successful method has been proposed to quantitatively represent variety of random non-white patterns seen in FHR. Objective of this paper is to address this issue. In this study the Box-Jenkins method of model identification and diagnostic checking was used on phonocardiographic derived FHR(averaged) time series. Models remained exclusively autoregressive(AR). Kalman filtering in conjunction with maximum likelihood estimation technique forms the parametric estimator. Diagnosrics perfonned on the residuals indicated that a second order model may be adequate in capturing type of variability observed in 1 up to 2 mm data windows of FHR. The scheme may be viewed as a means of data reduction of a highly redundant information source. This allows a much more efficient transmission of FHR information from remote locations to places with facilities and expertise for doser analysis. The extracted parameters is aimed to reflect numerically the important FHR features. These are normally picked up visually by experts for their assessments. As a result long term FHR recorded during antepartum period could then be screened quantitatively for detection of patterns considered normal or abnonnal. 1.

An overview of surface radiance and biology studies in FIFE

NASA Astrophysics Data System (ADS)

Blad, B. L.; Schimel, D. S.

1992-11-01

The use of satellite data to study and to understand energy and mass exchanges between the land surface and the atmosphere requires information about various biological processes and how various reflected or emitted spectral radiances are influenced by or manifested in these processes. To obtain such information, studies were conducted by the First ISLSCP Field Experiment (FIFE) surface radiances and biology (SRB) group using surface, near-surface, helicopter, and aircraft measurements. The two primary objectives of this group were to relate radiative fluxes to biophysical parameters and physiological processes and to assess how various management treatments affect important biological processes. This overview paper summarizes the results obtained by various SRB teams working in nine different areas: (1) measurement of bidirectional reflectance and estimation of hemispherical albedo; (2) evaluation of spatial and seasonal variability of spectral reflectance and vegetation indices; (3) determination of surface and radiational factors and their effects on vegetation indices and PAR relationships; (4) use of surface temperatures to estimate sensible heat flux; (5) controls over photosynthesis and respiration at small scales; (6) soil surface CO2 fluxes and grassland carbon budget; (7) landscape variations in controls over gas exchange and energy partitioning; (8) radiometric response of prairie to management and topography; and (9) determination of nitrogen gas exchanges in a tallgrass prairie.

Retrospective dose assessment for the population living in areas of local fallout from the Semipalatinsk Nuclear Test Site Part II: Internal exposure to thyroid.

PubMed

Gordeev, Konstantin; Shinkarev, Sergey; Ilyin, Leonid; Bouville, André; Hoshi, Masaharu; Luckyanov, Nickolas; Simon, Steven L

2006-02-01

A methodology to assess internal exposure to thyroid from radioiodines for the residents living in settlements located in the vicinity of the Semipalatinsk Nuclear Test Site is described that is the result of many years of research, primarily at the Moscow Institute of Biophysics. This methodology introduces two important concepts. First, the biologically active fraction, is defined as the fraction of the total activity on fallout particles with diameter less than 50 microns. That fraction is retained by vegetation and will ultimately result in contamination of dairy products. Second, the relative distance is derived as a dimensionless quantity from information on test yield, maximum height of cloud, and average wind velocity and describes how the biologically active fraction is distributed with distance from the site of the explosion. The parameter is derived in such a way that at locations with equal values of relative distance, the biologically active fraction will be the same for any test. The estimates of internal exposure to thyroid for the residents of Dolon and Kanonerka villages, for which the external exposure were assessed and given in a companion paper (Gordeev et al. 2006) in this conference, are presented. The main sources of uncertainty in the estimates are identified.

Biophysical modeling of in vitro and in vivo processes underlying regulated photoprotective mechanism in cyanobacteria.

PubMed

Shirshin, Evgeny A; Nikonova, Elena E; Kuzminov, Fedor I; Sluchanko, Nikolai N; Elanskaya, Irina V; Gorbunov, Maxim Y; Fadeev, Victor V; Friedrich, Thomas; Maksimov, Eugene G

2017-09-01

Non-photochemical quenching (NPQ) is a mechanism responsible for high light tolerance in photosynthetic organisms. In cyanobacteria, NPQ is realized by the interplay between light-harvesting complexes, phycobilisomes (PBs), a light sensor and effector of NPQ, the photoactive orange carotenoid protein (OCP), and the fluorescence recovery protein (FRP). Here, we introduced a biophysical model, which takes into account the whole spectrum of interactions between PBs, OCP, and FRP and describes the experimental PBs fluorescence kinetics, unraveling interaction rate constants between the components involved and their relative concentrations in the cell. We took benefit from the possibility to reconstruct the photoprotection mechanism and its parts in vitro, where most of the parameters could be varied, to develop the model and then applied it to describe the NPQ kinetics in the Synechocystis sp. PCC 6803 mutant lacking photosystems. Our analyses revealed  that while an excess of the OCP over PBs is required to obtain substantial PBs fluorescence quenching in vitro, in vivo the OCP/PBs ratio is less than unity, due to higher local concentration of PBs, which was estimated as ~10 -5 M, compared to in vitro experiments. The analysis of PBs fluorescence recovery on the basis of the generalized model of enzymatic catalysis resulted in determination of the FRP concentration in vivo close to 10% of the OCP concentration. Finally, the possible role of the FRP oligomeric state alteration in the kinetics of PBs fluorescence was shown. This paper provides the most comprehensive model of the OCP-induced PBs fluorescence quenching to date and the results are important for better understanding of the regulatory molecular mechanisms underlying NPQ in cyanobacteria.

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

NASA Astrophysics Data System (ADS)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

The feasibility of remotely sensed data to estimate urban tree dimensions and biomass

Treesearch

Jun-Hak Lee; Yekang Ko; E. Gregory McPherson

2016-01-01

Accurately measuring the biophysical dimensions of urban trees, such as crown diameter, stem diameter, height, and biomass, is essential for quantifying their collective benefits as an urban forest. However, the cost of directly measuring thousands or millions of individual trees through field surveys can be prohibitive. Supplementing field surveys with remotely sensed...

Spatial heterogeneity and air pollution removal by an urban forest

Treesearch

Francisco J. Escobedo; David J. Nowak

2009-01-01

Estimates of air pollution removal by the urban forest have mostly been based on mean values of forest structure variables for an entire city. However, the urban forest is not uniformly distributed across a city because of biophysical and social factors. Consequently, air pollution removal function by urban vegetation should vary because of this spatial heterogeneity....

microclim: Global estimates of hourly microclimate based on long-term monthly climate averages

PubMed Central

Kearney, Michael R; Isaac, Andrew P; Porter, Warren P

2014-01-01

The mechanistic links between climate and the environmental sensitivities of organisms occur through the microclimatic conditions that organisms experience. Here we present a dataset of gridded hourly estimates of typical microclimatic conditions (air temperature, wind speed, relative humidity, solar radiation, sky radiation and substrate temperatures from the surface to 1 m depth) at high resolution (~15 km) for the globe. The estimates are for the middle day of each month, based on long-term average macroclimates, and include six shade levels and three generic substrates (soil, rock and sand) per pixel. These data are suitable for deriving biophysical estimates of the heat, water and activity budgets of terrestrial organisms. PMID:25977764

Microclim: Global estimates of hourly microclimate based on long-term monthly climate averages.

PubMed

Kearney, Michael R; Isaac, Andrew P; Porter, Warren P

2014-01-01

The mechanistic links between climate and the environmental sensitivities of organisms occur through the microclimatic conditions that organisms experience. Here we present a dataset of gridded hourly estimates of typical microclimatic conditions (air temperature, wind speed, relative humidity, solar radiation, sky radiation and substrate temperatures from the surface to 1 m depth) at high resolution (~15 km) for the globe. The estimates are for the middle day of each month, based on long-term average macroclimates, and include six shade levels and three generic substrates (soil, rock and sand) per pixel. These data are suitable for deriving biophysical estimates of the heat, water and activity budgets of terrestrial organisms.

Watershed-Scale Heterogeneity of the Biophysical Controls on Soil Respiration

NASA Astrophysics Data System (ADS)

Riveros, D. A.; Pacific, V. J.; McGlynn, B. L.; Welsch, D. L.; Epstein, H. E.; Muth, D. J.; Marshall, L.; Wraith, J.

2006-12-01

Large gaps exist in our understanding of the variability of soil respiration response to changing hydrologic conditions across spatial and temporal scales. Determining the linkages between the hydrologic cycle and the biophysical controls of soil respiration from the local point, to the plot, to the watershed scale is critical to understanding the dynamics of net ecosystem CO2 exchange (NEE). To study the biophysical controls of soil respiration, we measured soil CO2 concentration, soil CO2 flux, dissolved CO2 in stream water, soil moisture, soil temperature, groundwater dynamics, and precipitation at 20-minute intervals throughout the growing season at 4 sites and at weekly intervals at 62 sites covering the range of topographic position, slope, aspect, land cover, and upslope accumulated area conditions in a 555-ha subalpine watershed in central Montana. Our goal was to quantify watershed-scale heterogeneity in soil CO2 concentrations and surface efflux and gain understanding of the biophysical controls on soil respiration. We seek to improve our ability to evaluate and predict soil respiration responses to a dynamic hydrologic cycle across multiple temporal and spatial scales. We found that time lags between biophysical controls and soil respiration can occur from hourly to daily scales. The sensitivity of soil respiration to changes in environmental conditions is controlled by the antecedent soil moisture and by topographic position. At the watershed scale, significant differences in soil respiration exist between upland (dry) and lowland (wet) sites. However, differences in the magnitude and timing of soil respiration also exist within upland settings due to heterogeneity in soil temperature, soil moisture, and soil organic matter. Finally, we used a process-based model to simulate respiration at different times of the year across spatial locations. Our simulations highlight the importance of autotrophic and heterotrophic respiration (production) over diffusivity and soil physical properties (transport). Our work begins to address the disconnect between point, footprint, watershed scale estimates of ecosystem respiration and the role of a dynamic hydrologic cycle.

Dependence of soil respiration on soil temperature and soil moisture in successional forests in Southern China

USGS Publications Warehouse

Tang, X.-L.; Zhou, G.-Y.; Liu, S.-G.; Zhang, D.-Q.; Liu, S.-Z.; Li, Ji; Zhou, C.-Y.

2006-01-01

The spatial and temporal variations in soil respiration and its relationship with biophysical factors in forests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three successional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared in successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season (April-September) and with low rates in the cool dry season (October-March). Soil respiration measured at these forests showed a clear increasing trend with the progressive succession. Annual mean (±SD) soil respiration rate in the DNR forests was (9.0 ± 4.6) Mg CO2-C/hm2per year, ranging from (6.1 ± 3.2) Mg CO2-C/hm2per year in early successional forests to (10.7 ± 4.9) Mg CO2-C/hm2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation in DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture increased with progressive succession processes. This increase is caused, in part, by abundant respirators in advanced-successional forest, where more soil moisture is needed to maintain their activities.

Tissue microstructure estimation using a deep network inspired by a dictionary-based framework.

PubMed

Ye, Chuyang

2017-12-01

Diffusion magnetic resonance imaging (dMRI) captures the anisotropic pattern of water displacement in the neuronal tissue and allows noninvasive investigation of the complex tissue microstructure. A number of biophysical models have been proposed to relate the tissue organization with the observed diffusion signals, so that the tissue microstructure can be inferred. The Neurite Orientation Dispersion and Density Imaging (NODDI) model has been a popular choice and has been widely used for many neuroscientific studies. It models the diffusion signal with three compartments that are characterized by distinct diffusion properties, and the parameters in the model describe tissue microstructure. In NODDI, these parameters are estimated in a maximum likelihood framework, where the nonlinear model fitting is computationally intensive. Therefore, efforts have been made to develop efficient and accurate algorithms for NODDI microstructure estimation, which is still an open problem. In this work, we propose a deep network based approach that performs end-to-end estimation of NODDI microstructure, which is named Microstructure Estimation using a Deep Network (MEDN). MEDN comprises two cascaded stages and is motivated by the AMICO algorithm, where the NODDI microstructure estimation is formulated in a dictionary-based framework. The first stage computes the coefficients of the dictionary. It resembles the solution to a sparse reconstruction problem, where the iterative process in conventional estimation approaches is unfolded and truncated, and the weights are learned instead of predetermined by the dictionary. In the second stage, microstructure properties are computed from the output of the first stage, which resembles the weighted sum of normalized dictionary coefficients in AMICO, and the weights are also learned. Because spatial consistency of diffusion signals can be used to reduce the effect of noise, we also propose MEDN+, which is an extended version of MEDN. MEDN+ allows incorporation of neighborhood information by inserting a stage with learned weights before the MEDN structure, where the diffusion signals in the neighborhood of a voxel are processed. The weights in MEDN or MEDN+ are jointly learned from training samples that are acquired with diffusion gradients densely sampling the q-space. We performed MEDN and MEDN+ on brain dMRI scans, where two shells each with 30 gradient directions were used, and measured their accuracy with respect to the gold standard. Results demonstrate that the proposed networks outperform the competing methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Measuring grassland structure for recovery of grassland species at risk

NASA Astrophysics Data System (ADS)

Guo, Xulin; Gao, Wei; Wilmshurst, John

2005-09-01

An action plan for recovering species at risk (SAR) depends on an understanding of the plant community distribution, vegetation structure, quality of the food source and the impact of environmental factors such as climate change at large scale and disturbance at small scale, as these are fundamental factors for SAR habitat. Therefore, it is essential to advance our knowledge of understanding the SAR habitat distribution, habitat quality and dynamics, as well as developing an effective tool for measuring and monitoring SAR habitat changes. Using the advantages of non-destructive, low cost, and high efficient land surface vegetation biophysical parameter characterization, remote sensing is a potential tool for helping SAR recovery action. The main objective of this paper is to assess the most suitable techniques for using hyperspectral remote sensing to quantify grassland biophysical characteristics. The challenge of applying remote sensing in semi-arid and arid regions exists simply due to the lower biomass vegetation and high soil exposure. In conservation grasslands, this problem is enhanced because of the presence of senescent vegetation. Results from this study demonstrated that hyperspectral remote sensing could be the solution for semi-arid grassland remote sensing applications. Narrow band raw data and derived spectral vegetation indices showed stronger relationships with biophysical variables compared to the simulated broad band vegetation indices.

Biophysical Characterization of Supported Lipid Bilayers Using Parallel Dual-Wavelength Surface Plasmon Resonance and Quartz Crystal Microbalance Measurements.

PubMed

Parkkila, Petteri; Elderdfi, Mohamed; Bunker, Alex; Viitala, Tapani

2018-06-25

Supported lipid bilayers (SLBs) have been used extensively as an effective model of biological membranes, in the context of in vitro biophysics research, and the membranes of liposomes, in the context of the development of nanoscale drug delivery devices. Despite numerous surface-sensitive techniques having been applied to their study, the comprehensive optical characterization of SLBs using surface plasmon resonance (SPR) has not been conducted. In this study, Fresnel multilayer analysis is utilized to effectively calculate layer parameters (thickness and refractive indices) with the aid of dual-wavelength and dispersion coefficient analysis, in which the linear change in the refractive index as a function of wavelength is assumed. Using complementary information from impedance-based quartz crystal microbalance experiments, biophysical properties, for example, area-per-lipid-molecule and the quantity of lipid-associated water molecules, are calculated for different lipid types and mixtures, one of which is representative of a raft-forming lipid mixture. It is proposed that the hydration layer beneath the bilayer is, in fact, an integral part of the measured optical signal. Also, the traditional Jung model analysis and the ratio of SPR responses are investigated in terms of assessing the structure of the lipid layer that is formed.

The molecular determinants of CD8 co-receptor function.

PubMed

Cole, David K; Laugel, Bruno; Clement, Mathew; Price, David A; Wooldridge, Linda; Sewell, Andrew K

2012-10-01

CD8(+) T cells respond to signals mediated through a specific interaction between the T-cell receptor (TCR) and a composite antigen in the form of an epitopic peptide bound between the polymorphic α1 and α2 helices of an MHC class I (MHCI) molecule. The CD8 glycoprotein 'co-receives' antigen by binding to an invariant region of the MHCI molecule and can enhance ligand recognition by up to 1 million-fold. In recent years, a number of structural and biophysical investigations have shed light on the role of the CD8 co-receptor during T-cell antigen recognition. Here, we provide a collated resource for these data, and discuss how the structural and biophysical parameters governing CD8 co-receptor function further our understanding of T-cell cross-reactivity and the productive engagement of low-affinity antigenic ligands. © 2012 The Authors. Immunology © 2012 Blackwell Publishing Ltd.

Biophysical synaptic dynamics in an analog VLSI network of Hodgkin-Huxley neurons.

PubMed

Yu, Theodore; Cauwenberghs, Gert

2009-01-01

We study synaptic dynamics in a biophysical network of four coupled spiking neurons implemented in an analog VLSI silicon microchip. The four neurons implement a generalized Hodgkin-Huxley model with individually configurable rate-based kinetics of opening and closing of Na+ and K+ ion channels. The twelve synapses implement a rate-based first-order kinetic model of neurotransmitter and receptor dynamics, accounting for NMDA and non-NMDA type chemical synapses. The implemented models on the chip are fully configurable by 384 parameters accounting for conductances, reversal potentials, and pre/post-synaptic voltage-dependence of the channel kinetics. We describe the models and present experimental results from the chip characterizing single neuron dynamics, single synapse dynamics, and multi-neuron network dynamics showing phase-locking behavior as a function of synaptic coupling strength. The 3mm x 3mm microchip consumes 1.29 mW power making it promising for applications including neuromorphic modeling and neural prostheses.

A remote sensing based vegetation classification logic for global land cover analysis

USGS Publications Warehouse

Running, Steven W.; Loveland, Thomas R.; Pierce, Lars L.; Nemani, R.R.; Hunt, E. Raymond

1995-01-01

This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested.

Retrieval of Winter Wheat Leaf Area Index from Chinese GF-1 Satellite Data Using the PROSAIL Model

PubMed Central

Li, He; Liu, Gaohuan; Liu, Qingsheng; Chen, Zhongxin; Huang, Chong

2018-01-01

Leaf area index (LAI) is one of the key biophysical parameters in crop structure. The accurate quantitative estimation of crop LAI is essential to verify crop growth and health. The PROSAIL radiative transfer model (RTM) is one of the most established methods for estimating crop LAI. In this study, a look-up table (LUT) based on the PROSAIL RTM was first used to estimate winter wheat LAI from GF-1 data, which accounted for some available prior knowledge relating to the distribution of winter wheat characteristics. Next, the effects of 15 LAI-LUT strategies with reflectance bands and 10 LAI-LUT strategies with vegetation indexes on the accuracy of the winter wheat LAI retrieval with different phenological stages were evaluated against in situ LAI measurements. The results showed that the LUT strategies of LAI-GNDVI were optimal and had the highest accuracy with a root mean squared error (RMSE) value of 0.34, and a coefficient of determination (R2) of 0.61 during the elongation stages, and the LUT strategies of LAI-Green were optimal with a RMSE of 0.74, and R2 of 0.20 during the grain-filling stages. The results demonstrated that the PROSAIL RTM had great potential in winter wheat LAI inversion with GF-1 satellite data and the performance could be improved by selecting the appropriate LUT inversion strategies in different growth periods. PMID:29642395

Spectrometry of Pasture Condition and Biogeochemistry in the Central Amazon

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Townsend, Alan R.; Bustamante, Mercedes M. C.

1999-01-01

Regional analyses of Amazon cattle pasture biogeochemistry are difficult due to the complexity of human, edaphic, biotic and climatic factors and persistent cloud cover in satellite observations. We developed a method to estimate key biophysical properties of Amazon pastures using hyperspectral reflectance data and photon transport inverse modeling. Remote estimates of live and senescent biomass were strongly correlated with plant-available forms of soil phosphorus and calcium. These results provide a basis for monitoring pasture condition and biogeochemistry in the Amazon Basin using spaceborne hyperspectral sensors.

Integrated remote sensing for multi-temporal analysis of urban land cover-climate interactions

NASA Astrophysics Data System (ADS)

Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.

2016-08-01

Climate change is considered to be the biggest environmental threat in the future in the South- Eastern part of Europe. In frame of predicted global warming, urban climate is an important issue in scientific research. Surface energy processes have an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. This paper investigated the influences of urban growth on thermal environment in relationship with other biophysical variables in Bucharest metropolitan area of Romania. Remote sensing data from Landsat TM/ETM+ and time series MODIS Terra/Aqua sensors have been used to assess urban land cover- climate interactions over period between 2000 and 2015 years. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Based on these parameters, the urban growth, and urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

Investigation of Polarization Phase Difference Related to Forest Fields Characterizations

NASA Astrophysics Data System (ADS)

Majidi, M.; Maghsoudi, Y.

2013-09-01

The information content of Synthetic Aperture Radar (SAR) data significantly included in the radiometric polarization channels, hence polarimetric SAR data should be analyzed in relation with target structure. The importance of the phase difference between two co-polarized scattered signals due to the possible association between the biophysical parameters and the measured Polarization Phase Difference (PPD) statistics of the backscattered signal recorded components has been recognized in geophysical remote sensing. This paper examines two Radarsat-2 images statistics of the phase difference to describe the feasibility of relationship with the physical properties of scattering targets and tries to understand relevance of PPD statistics with various types of forest fields. As well as variation of incidence angle due to affecting on PPD statistics is investigated. The experimental forest pieces that are used in this research are characterized white pine (Pinus strobus L.), red pine (Pinus resinosa Ait.), jack pine (Pinus banksiana Lamb.), white spruce (Picea glauca (Moench Voss), black spruce (Picea mariana (Mill) B.S.P.), poplar (Populus L.), red oak (Quercus rubra L.) , aspen and ground vegetation. The experimental results show that despite of biophysical parameters have a wide diversity, PPD statistics are almost the same. Forest fields distributions as distributed targets have close to zero means regardless of the incidence angle. Also, The PPD distribution are function of both target and sensor parameters, but for more appropriate examination related to PPD statistics the observations should made in the leaf-off season or in bands with lower frequencies.

A multivariate analysis of biophysical parameters of tallgrass prairie among land management practices and years

USGS Publications Warehouse

Griffith, J.A.; Price, K.P.; Martinko, E.A.

2001-01-01

Six treatments of eastern Kansas tallgrass prairie - native prairie, hayed, mowed, grazed, burned and untreated - were studied to examine the biophysical effects of land management practices on grasslands. On each treatment, measurements of plant biomass, leaf area index, plant cover, leaf moisture and soil moisture were collected. In addition, measurements were taken of the Normalized Difference Vegetation Index (NDVI), which is derived from spectral reflectance measurements. Measurements were taken in mid-June, mid-July and late summer of 1990 and 1991. Multivariate analysis of variance was used to determine whether there were differences in the set of variables among treatments and years. Follow-up tests included univariate t-tests to determine which variables were contributing to any significant difference. Results showed a significant difference (p < 0.0005) among treatments in the composite of parameters during each of the months sampled. In most treatment types, there was a significant difference between years within each month. The univariate tests showed, however, that only some variables, primarily soil moisture, were contributing to this difference. We conclude that biomass and % plant cover show the best potential to serve as long-term indicators of grassland condition as they generally were sensitive to effects of different land management practices but not to yearly change in weather conditions. NDVI was insensitive to precipitation differences between years in July for most treatments, but was not in the native prairie. Choice of sampling time is important for these parameters to serve effectively as indicators.

Unravel biophysical factors on river water quality response in Chilean Central-Southern watersheds.

PubMed

Yevenes, Mariela A; Arumí, José L; Farías, Laura

2016-05-01

Identifying the key anthropogenic (land uses) and natural (topography and climate) biophysical drivers affecting river water quality is essential for efficient management of water resources. We tested the hypothesis that water quality can be predicted by different biophysical factors. Multivariate statistics based on a geographical information system (GIS) were used to explore the influence of factors (i.e., precipitation, topography, and land uses) on water quality (i.e., nitrate (NO 3 (-)), phosphate (PO 4 (3-)), silicate (Si(OH)4), dissolved oxygen (DO), suspended solids (TSS), biological oxygen demand (DO), temperature (T), conductivity (EC), and pH) for two consecutive years in the Itata and Biobío river watersheds, Central Chile (36° 00' and 38° 30'). The results showed that (NO 3 (-)), (PO 4 (3-)), Si(OH)4, TSS, EC, and DO were higher during rainy season (austral fall, winter, and spring), whereas BOD and temperature were higher during dry season. The spatial variation of these parameters in both watersheds was related to land use, topography (e.g., soil moisture, soil hydrological group, and erodability), and precipitation. Soil hydrological group and soil moisture were the strongest explanatory predictors for PO 4 (3-) , Si(OH)4 and EC in the river, followed by land use such as agriculture for NO 3 (-) and DO and silviculture for TSS and Si(OH)4. High-resolution water leaching and runoff maps allowed us to identify agriculture areas with major probability of water leaching and higher probability of runoff in silviculture areas. Moreover, redundancy analysis (RDA) revealed that land uses (agriculture and silviculture) explained in 60 % the river water quality variation. Our finding highlights the vulnerability of Chilean river waters to different biophysical drivers, rather than climate conditions alone, which is amplified by human-induced degradation.

Strengths and Limitations of Operational Use of 1 Km EO Biophysical Products for Regional Prediction of Grain Yelds in Europe (wheat, barley and maize)

NASA Astrophysics Data System (ADS)

Meroni, M.; LEO, O.; Lopez-Lozano, R.; Baruth, B.; Duveiller, G.; Garcia-Condado, S.; Hooker, J.; Seguini, L.

2014-12-01

The site-specific relationship between EO indicators and actual crop yields has been explored in many different studies, describing semi-empirical regression models between spatially aggregated biophysical parameters or vegetation indices and observed yields (from field measurements or official statistics). However, when considering larger extensions -from countries to continents- agro-climatic conditions and crop management may differ substantially among regions, and these differences may greatly influence the relationship between biophysical indicators and the observed yields, which may be also driven by limiting factors other than green biomass formation. The present study aims to better assess the contribution of EO indicators within an operational crop yield forecasting system in Europe and neighbouring countries, by evaluating how these above mentioned geographic differences influence the relationship between biophysical indicators and crop yield. We therefore explore, as a first step, the correspondence between fAPAR time-series (1999-2013) and the inter-annual yield variability of wheat, barley and grain maize, at sub-national level across Europe (270-450 Administrative Units, depending on crop). In a second step, we map the agro-climatic contexts in which EO indicators better explain the observed yield inter-annual variability, identify the influence of some meteorological events on the fAPAR -yield relationship and provide some recommendations for further investigation. The results indicate that in water-limited environments (e.g. Mediterranean and Black Sea areas), fAPAR is highly correlated with yields whereas in northern Europe, crop yield appears much less limited by leaf area expansion along the season, and the relationship between yield and EO products becomes more difficult to interpret.

Identifiability, reducibility, and adaptability in allosteric macromolecules.

PubMed

Bohner, Gergő; Venkataraman, Gaurav

2017-05-01

The ability of macromolecules to transduce stimulus information at one site into conformational changes at a distant site, termed "allostery," is vital for cellular signaling. Here, we propose a link between the sensitivity of allosteric macromolecules to their underlying biophysical parameters, the interrelationships between these parameters, and macromolecular adaptability. We demonstrate that the parameters of a canonical model of the mSlo large-conductance Ca 2+ -activated K + (BK) ion channel are non-identifiable with respect to the equilibrium open probability-voltage relationship, a common functional assay. We construct a reduced model with emergent parameters that are identifiable and expressed as combinations of the original mechanistic parameters. These emergent parameters indicate which coordinated changes in mechanistic parameters can leave assay output unchanged. We predict that these coordinated changes are used by allosteric macromolecules to adapt, and we demonstrate how this prediction can be tested experimentally. We show that these predicted parameter compensations are used in the first reported allosteric phenomena: the Bohr effect, by which hemoglobin adapts to varying pH. © 2017 Bohner and Venkataraman.

Identifiability, reducibility, and adaptability in allosteric macromolecules

PubMed Central

Bohner, Gergő

2017-01-01

The ability of macromolecules to transduce stimulus information at one site into conformational changes at a distant site, termed “allostery,” is vital for cellular signaling. Here, we propose a link between the sensitivity of allosteric macromolecules to their underlying biophysical parameters, the interrelationships between these parameters, and macromolecular adaptability. We demonstrate that the parameters of a canonical model of the mSlo large-conductance Ca2+-activated K+ (BK) ion channel are non-identifiable with respect to the equilibrium open probability-voltage relationship, a common functional assay. We construct a reduced model with emergent parameters that are identifiable and expressed as combinations of the original mechanistic parameters. These emergent parameters indicate which coordinated changes in mechanistic parameters can leave assay output unchanged. We predict that these coordinated changes are used by allosteric macromolecules to adapt, and we demonstrate how this prediction can be tested experimentally. We show that these predicted parameter compensations are used in the first reported allosteric phenomena: the Bohr effect, by which hemoglobin adapts to varying pH. PMID:28416647

A Study on PolInSAR Coherence Based Regression Analysis of Forest Biomass (BARKOT Reserve Forest India), Using RADARSAT-2 Datasets

NASA Astrophysics Data System (ADS)

Singh, J.; Kumar, S.; Kushwaha, S. P. S.

2015-04-01

Forests cover 30% of the world's land surface, and are home to around 90% of the world's flora and fauna. They serve as one of the world's largest carbon sinks, absorbing 2.4 million tons of CO2 each year and storing billions more in form of biomass. Around 6 million hectares of forest is lost or changed each year and as much as a fifth of global emissions are estimated to come from deforestation. Hence accurate estimation of forest biophysical variables is necessary as it is a key parameter in determination of forest inventories, vegetation modeling and global carbon cycle. SAR Remote sensing technique is capable of providing accurate and reliable information about forest parameters. The present work aims to explore the potential of C-band Radarsat-2 Polarimetric Interferometric Synthetic Aperture Radar (PolinSAR) technique for developing a relationship between complex coherence and forest aboveground biomass (t/ha). In order to attain our objective Radarsat-2 satellite interferometric pair of 4th March 2013(master image) and 28th March 2013(slave image) were acquired for Barkot Reserve Forest, Dehradun, India. Field inventory was done for 30 plots (31.62m x 31.62m) and tree height and stem diameter were procured for each plot which were later utilized in calculation of aboveground biomass(AGB).Work emphasizes on the application of PolinSAR coherence instead of using SAR backscatter which saturates after a certain value of biomass content. Complex coherence values for different polarization channels were computed with the help of polarimetric interferometric coherence matrix. Retrieved complex coherences were investigated individually and then regression analysis was carried with the field estimated aboveground biomass. R2 value of HV+VH complex coherence component was found to be relatively higher than other polarization channel components

Italian biophysics and SIBPA speed-up the pace towards the long and winding road of the interdisciplinary science.

PubMed

Giacomazza, Daniela; Musio, Carlo

2016-01-01

This Special Issue of Biophysical Chemistry presents a selection of the contributions presented at the XXII National Congress of the Italian Society of Pure and Applied Biophysics (i.e., SIBPA, Società Italiana di Biofisica Pura ed Applicata) held on September 2014 in Palermo, Italy. Topics cover all biophysical disciplines, from molecular to cellular, to integrative biophysics giving a comprehensive view of the inter- and multi-disciplinary approach of modern biophysics. SIBPA, which turned 40 in 2013, continues to grow and attract interest.

In vivo oxygen, temperature and pH dynamics in the female reproductive tract and their importance in human conception: a systematic review.

PubMed

Ng, Ka Ying Bonnie; Mingels, Roel; Morgan, Hywel; Macklon, Nick; Cheong, Ying

2018-01-01

Despite advances in ART, implantation and pregnancy rates per embryo transfer still remain low. IVF laboratories strive to ensure that the process of handling gametes in vitro closely mimics the in vivo environment. However, there remains a lack of knowledge regarding the in vivo regulation and dynamic variation in biophysical parameters such as oxygen concentration, pH and temperature within the reproductive tract. To undertake a systematic review of the current understanding of the physico-chemical parameters of oxygen tension (pO2), pH and temperature within the female reproductive tract, and their potential implications in clinical and pathological processes related to fertility and those pertaining to limited reproductive capacity. A comprehensive literature search was performed using electronic databases including Medline, Embase, Cochrane Library and Pubmed to identify original and review articles addressing the biophysical parameters (pO2, pH and temperature) in the female reproductive tract of any species. The search included all studies published between 1946 and November 2015. Search terms included 'oxygen', 'pH', 'hydrogen ion concentration', 'acid base' and others terms. We also used special features and truncations to identify synonyms and broaden the search. Studies were excluded if they only assessed embryo culture conditions, fetal acid-base status, oxidative stress, outcomes of pregnancy and measurements of these parameters in non-reproductive organs. Our search generated 18 685 records and 60 articles were included. pO2 within the female reproductive tract shows cyclical variation and minute-to-minute oscillations, which may be influenced by uterine contractility, hormones, the autonomic system, cardiac pulsatility, and myometrial and smooth muscle integrity. Fine balanced control of pO2 and avoidance of overwhelming oxidative stress is crucial for embryogenesis and implantation. The pH in the female reproductive tract is graduated, with lowest pH in the vagina (~pH 4.42) increasing toward the Fallopian tubes (FTs) (~pH 7.94), reflecting variation in the site-specific microbiome and acid-base buffering at the tissue/cellular level. The temperature variation in humans is cyclical by day and month. In humans, it is biphasic, increasing in the luteal phase; with the caudal region of the oviduct 1-2 degrees cooler than the cranial portion. Temperature variation is influenced by hormones, density of pelvic/uterine vascular beds and effectiveness of heat exchange locally, crucial for sperm motility and embryo development. We have identified significant deficiencies and inconsistencies in the methods used to assess these biophysical factors within the reproductive tract. We have suggested that the technological solutions including the development of methods and models for real time, in vivo recordings of biophysical parameters. The notion of 'back to nature' in assisted conception suggested 20 years ago has yet to be translated into clinical practice. While the findings from this systematic review do not provide evidence to change current in vitro protocols, it highlights our current inability to assess the in vivo reproductive tract environment in real time. Data made available through future development of sensing technology in utero may help to provide new insights into how best to optimize the in vitro embryo environment and allow for more precise and personalized fertility treatment. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Desert plains classification based on Geomorphometrical parameters (Case study: Aghda, Yazd)

NASA Astrophysics Data System (ADS)

Tazeh, mahdi; Kalantari, Saeideh

2013-04-01

This research focuses on plains. There are several tremendous methods and classification which presented for plain classification. One of The natural resource based classification which is mostly using in Iran, classified plains into three types, Erosional Pediment, Denudation Pediment Aggradational Piedmont. The qualitative and quantitative factors to differentiate them from each other are also used appropriately. In this study effective Geomorphometrical parameters in differentiate landforms were applied for plain. Geomorphometrical parameters are calculable and can be extracted using mathematical equations and the corresponding relations on digital elevation model. Geomorphometrical parameters used in this study included Percent of Slope, Plan Curvature, Profile Curvature, Minimum Curvature, the Maximum Curvature, Cross sectional Curvature, Longitudinal Curvature and Gaussian Curvature. The results indicated that the most important affecting Geomorphometrical parameters for plain and desert classifications includes: Percent of Slope, Minimum Curvature, Profile Curvature, and Longitudinal Curvature. Key Words: Plain, Geomorphometry, Classification, Biophysical, Yazd Khezarabad.

Optical vortices as potential indicators of biophysical dynamics

NASA Astrophysics Data System (ADS)

Majumdar, Anindya; Kirkpatrick, Sean J.

2017-03-01

Laser speckle patterns are granular patterns produced as a result of random interference of light waves. Optical vortices (OVs) are phase singularities in such speckle fields, characterized by zero intensity and an undefined phase. Decorrelation of the speckle fields causes these OVs to move in both time and space. In this work, a variety of parameters of these OVs have been studied. The speckle fields were simulated to undergo three distinct decorrelation behaviors- Gaussian, Lorentzian and constant decorrelations. Different decorrelation behaviors represent different dynamics. For example, Lorentzian and Gaussian decorrelations represent Brownian and ordered motions, respectively. Typical dynamical systems in biophysics are generally argued to be a combination of these. For each of the decorrelation behaviors under study, the vortex trails were tracked while varying the rate of decorrelation. Parameters such as the decorrelation length, average trail length and the deviation of the vortices as they traversed in the speckle field, were studied. Empirical studies were also performed to define the distinction between trails arising from different speckle decorrelation behaviors. The initial studies under stationary speckle fields were followed up by similar studies on shifting fields. A new idea to employ Poincaŕe plots in speckle analysis has also been introduced. Our studies indicate that tracking OVs can be a potential method to study cell and tissue dynamics.

Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells.

PubMed

Masoli, Stefano; Rizza, Martina F; Sgritta, Martina; Van Geit, Werner; Schürmann, Felix; D'Angelo, Egidio

2017-01-01

In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (G i-max ) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of G i-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of G i-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental G i-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.

Teaching and learning the Hodgkin-Huxley model based on software developed in NEURON's programming language hoc.

PubMed

Hernández, Oscar E; Zurek, Eduardo E

2013-05-15

We present a software tool called SENB, which allows the geometric and biophysical neuronal properties in a simple computational model of a Hodgkin-Huxley (HH) axon to be changed. The aim of this work is to develop a didactic and easy-to-use computational tool in the NEURON simulation environment, which allows graphical visualization of both the passive and active conduction parameters and the geometric characteristics of a cylindrical axon with HH properties. The SENB software offers several advantages for teaching and learning electrophysiology. First, SENB offers ease and flexibility in determining the number of stimuli. Second, SENB allows immediate and simultaneous visualization, in the same window and time frame, of the evolution of the electrophysiological variables. Third, SENB calculates parameters such as time and space constants, stimuli frequency, cellular area and volume, sodium and potassium equilibrium potentials, and propagation velocity of the action potentials. Furthermore, it allows the user to see all this information immediately in the main window. Finally, with just one click SENB can save an image of the main window as evidence. The SENB software is didactic and versatile, and can be used to improve and facilitate the teaching and learning of the underlying mechanisms in the electrical activity of an axon using the biophysical properties of the squid giant axon.

Biophysics of olfaction

NASA Astrophysics Data System (ADS)

Marques Simoes de Souza, Fabio; Antunes, Gabriela

2007-03-01

The majority of the biophysical models of olfaction have been focused on the electrical properties of the system, which is justified by the relative facility of recording the electrical activity of the olfactory cells. However, depending on the level of detail utilized, a biophysical model can explore molecular, cellular and network phenomena. This review presents the state of the art of the biophysical approach to understanding olfaction. The reader is introduced to the principal problems involving the study of olfaction and guided gradually to comprehend why it is important to develop biophysical models to investigate olfaction. A large number of representative biophysical efforts in olfaction, their main contributions, the trends for the next generations of biophysical models and the improvements that may be explored by future biophysicists of olfaction have been reviewed.

Phenemenological vs. biophysical models of thermal stress in aquatic eggs

NASA Astrophysics Data System (ADS)

Martin, B.

2016-12-01

Predicting species responses to climate change is a central challenge in ecology, with most efforts relying on lab derived phenomenological relationships between temperature and fitness metrics. We tested one of these models using the embryonic stage of a Chinook salmon population. We parameterized the model with laboratory data, applied it to predict survival in the field, and found that it significantly underestimated field-derived estimates of thermal mortality. We used a biophysical model based on mass-transfer theory to show that the discrepancy was due to the differences in water flow velocities between the lab and the field. This mechanistic approach provides testable predictions for how the thermal tolerance of embryos depends on egg size and flow velocity of the surrounding water. We found support for these predictions across more than 180 fish species, suggesting that flow and temperature mediated oxygen limitation is a general mechanism underlying the thermal tolerance of embryos.

The transfer function of neuron spike.

PubMed

Palmieri, Igor; Monteiro, Luiz H A; Miranda, Maria D

2015-08-01

The mathematical modeling of neuronal signals is a relevant problem in neuroscience. The complexity of the neuron behavior, however, makes this problem a particularly difficult task. Here, we propose a discrete-time linear time-invariant (LTI) model with a rational function in order to represent the neuronal spike detected by an electrode located in the surroundings of the nerve cell. The model is presented as a cascade association of two subsystems: one that generates an action potential from an input stimulus, and one that represents the medium between the cell and the electrode. The suggested approach employs system identification and signal processing concepts, and is dissociated from any considerations about the biophysical processes of the neuronal cell, providing a low-complexity alternative to model the neuronal spike. The model is validated by using in vivo experimental readings of intracellular and extracellular signals. A computational simulation of the model is presented in order to assess its proximity to the neuronal signal and to observe the variability of the estimated parameters. The implications of the results are discussed in the context of spike sorting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

NASA Astrophysics Data System (ADS)

Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei

2008-10-01

Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.

Modelling insights on the partition of evapotranspiration components across biomes

NASA Astrophysics Data System (ADS)

Fatichi, Simone; Pappas, Christoforos

2017-04-01

Recent studies using various methodologies have found a large variability (from 35 to 90%) in the ratio of transpiration to total evapotranspiration (denoted as T:ET) across biomes or even at the global scale. Concurrently, previous results suggest that T:ET is independent of mean precipitation and has a positive correlation with Leaf Area Index (LAI). We used the mechanistic ecohydrological model, T&C, with a refined process-based description of soil resistance and a detailed treatment of canopy biophysics and ecophysiology, to investigate T:ET across multiple biomes. Contrary to observation-based estimates, simulation results highlight a well-constrained range of mean T:ET across biomes that is also robust to perturbations of the most sensitive parameters. Simulated T:ET was confirmed to be independent of average precipitation, while it was found to be uncorrelated with LAI across biomes. Higher values of LAI increase evaporation from interception but suppress ground evaporation with the two effects largely cancelling each other in many sites. These results offer mechanistic, model-based, evidence to the ongoing research about the range of T:ET and the factors affecting its magnitude across biomes.

The Physics of Decision Making:. Stochastic Differential Equations as Models for Neural Dynamics and Evidence Accumulation in Cortical Circuits

NASA Astrophysics Data System (ADS)

Holmes, Philip; Eckhoff, Philip; Wong-Lin, K. F.; Bogacz, Rafal; Zacksenhouse, Miriam; Cohen, Jonathan D.

2010-03-01

We describe how drift-diffusion (DD) processes - systems familiar in physics - can be used to model evidence accumulation and decision-making in two-alternative, forced choice tasks. We sketch the derivation of these stochastic differential equations from biophysically-detailed models of spiking neurons. DD processes are also continuum limits of the sequential probability ratio test and are therefore optimal in the sense that they deliver decisions of specified accuracy in the shortest possible time. This leaves open the critical balance of accuracy and speed. Using the DD model, we derive a speed-accuracy tradeoff that optimizes reward rate for a simple perceptual decision task, compare human performance with this benchmark, and discuss possible reasons for prevalent sub-optimality, focussing on the question of uncertain estimates of key parameters. We present an alternative theory of robust decisions that allows for uncertainty, and show that its predictions provide better fits to experimental data than a more prevalent account that emphasises a commitment to accuracy. The article illustrates how mathematical models can illuminate the neural basis of cognitive processes.

Commentary on “Biophysical Economics” and Evolving Areas

NASA Astrophysics Data System (ADS)

Flomenbom, Ophir; Coban, Gul Unal; Adigüzel, Yekbun

2016-07-01

In this Issue, papers in the area of socio-econo-physics and biophysical economics are presented. We have recently introduced socio-econo-physics and biophysical economics in Biophysical Reviews and Letters (BRL), yet saw 3 to 4 relevant papers just in these most recent three quarters. In this commentary, we therefore would like to elaborate on the topics of socio-econo-physics and biophysical economics and to introduce these concepts to the readers of BRL and the biophysical community of science, with the purpose of supporting many more publications here in BRL, in this evolving area.

[Parameters of cardiac muscle repolarization on the electrocardiogram when changing anatomical and electric position of the heart].

PubMed

Chaĭkovskiĭ, I A; Baum, O V; Popov, L A; Voloshin, V I; Budnik, N N; Frolov, Iu A; Kovalenko, A S

2014-01-01

While discussing the diagnostic value of the single channel electrocardiogram a set of theoretical considerations emerges inevitably, one of the most important among them is the question about dependence of the electrocardiogram parameters from the direction of electrical axis of heart. In other words, changes in what of electrocardiogram parameters are in fact liable to reflect pathological processes in myocardium, and what ones are determined by extracardiac factors, primarily by anatomic characteristics of patients. It is arguable that while analyzing electrocardiogram it is necessary to orient to such physiologically based informative indexes as ST segment displacement. Also, symmetry of the T wave shape is an important parameter which is independent of patients anatomic features. The results obtained are of interest for theoretical and applied aspects of the biophysics of the cardiac electric field.

A tool to evaluate local biophysical effects on temperature due to land cover change transitions

NASA Astrophysics Data System (ADS)

Perugini, Lucia; Caporaso, Luca; Duveiller, Gregory; Cescatti, Alessandro; Abad-Viñas, Raul; Grassi, Giacomo; Quesada, Benjamin

2017-04-01

Land Cover Changes (LCC) affect local, regional and global climate through biophysical variations of the surface energy budget mediated by albedo, evapotranspiration, and roughness. Assessment of the full climate impacts of anthropogenic LCC are incomplete without considering biophysical effects, but the high level of uncertainties in quantifying their impacts to date have made it impractical to offer clear advice on which policy makers could act. To overcome this barrier, we provide a tool to evaluate the biophysical impact of a matrix of land cover transitions, following a tiered methodological approach similar to the one provided by the IPCC to estimate the biogeochemical effects, i.e. through three levels of methodological complexity, from Tier 1 (i.e. default method and factors) to Tier 3 (i.e. specific methods and factors). In particular, the tool provides guidance for quantitative assessment of changes in temperature following a land cover transition. The tool focuses on temperature for two main reasons (i) it is the main variable of interest for policy makers at local and regional level, and (ii) temperature is able to summarize the impact of radiative and non-radiative processes following LULCC. The potential changes in annual air temperature that can be expected from various land cover transitions are derived from a dedicated dataset constructed by the JRC in the framework of the LUC4C FP7 project. The inputs for the dataset are air temperature values derived from satellite Earth Observation data (MODIS) and land cover characterization from the ESA Climate Change Initiative product reclassified into their IPCC land use category equivalent. This data, originally at 0.05 degree of spatial resolution, is aggregated and analysed at regional level to provide guidance on the expected temperature impact following specific LCC transitions.

Private and public incomes in dehesas and coniferous forests in Andalusia, Spain

Treesearch

Paola Ovando; Pablo Campos; Jose L. Oviedo; Alejandro Caparrós

2015-01-01

We apply an ecosystem accounting system to estimate the total social income accrued from private and public products in a group of agroforestry farms in Andalusia (Spain). We provide bio-physical and economic indicators for two contrasting farm types, a sub-group of 15 publicly owned coniferous forests and a sub-group of 24 privately owned dehesa farms. Total social...

Ecosystem carbon storage and flux in upland/peatland watersheds in northern Minnesota. Chapter 9.

Treesearch

David F. Grigal; Peter C. Bates; Randall K. Kolka

2011-01-01

Carbon (C) storage and fluxes (inputs and outputs of C per unit time) are central issues in global change. Spatial patterns of C storage on the landscape, both that in soil and in biomass, are important from an inventory perspective and for understanding the biophysical processes that affect C fluxes. Regional and national estimates of C storage are uncertain because...

Modeling Endoplasmic Reticulum Network Maintenance in a Plant Cell.

PubMed

Lin, Congping; White, Rhiannon R; Sparkes, Imogen; Ashwin, Peter

2017-07-11

The endoplasmic reticulum (ER) in plant cells forms a highly dynamic network of complex geometry. ER network morphology and dynamics are influenced by a number of biophysical processes, including filament/tubule tension, viscous forces, Brownian diffusion, and interactions with many other organelles and cytoskeletal elements. Previous studies have indicated that ER networks can be thought of as constrained minimal-length networks acted on by a variety of forces that perturb and/or remodel the network. Here, we study two specific biophysical processes involved in remodeling. One is the dynamic relaxation process involving a combination of tubule tension and viscous forces. The other is the rapid creation of cross-connection tubules by direct or indirect interactions with cytoskeletal elements. These processes are able to remodel the ER network: the first reduces network length and complexity whereas the second increases both. Using live cell imaging of ER network dynamics in tobacco leaf epidermal cells, we examine these processes on ER network dynamics. Away from regions of cytoplasmic streaming, we suggest that the dynamic network structure is a balance between the two processes, and we build an integrative model of the two processes for network remodeling. This model produces quantitatively similar ER networks to those observed in experiments. We use the model to explore the effect of parameter variation on statistical properties of the ER network. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Ionizable Nitroxides for Studying Local Electrostatic Properties of Lipid Bilayers and Protein Systems by EPR

PubMed Central

Voinov, Maxim A.; Smirnov, Alex I.

2016-01-01

Electrostatic interactions are known to play one of the major roles in the myriad of biochemical and biophysical processes. In this Chapter we describe biophysical methods to probe local electrostatic potentials of proteins and lipid bilayer systems that is based on an observation of reversible protonation of nitroxides by EPR. Two types of the electrostatic probes are discussed. The first one includes methanethiosulfonate derivatives of protonatable nitroxides that could be used for highly specific covalent modification of the cysteine’s sulfhydryl groups. Such spin labels are very similar in magnetic parameters and chemical properties to conventional MTSL making them suitable for studying local electrostatic properties of protein-lipid interfaces. The second type of EPR probes is designed as spin-labeled phospholipids having a protonatable nitroxide tethered to the polar head group. The probes of both types report on their ionization state through changes in magnetic parameters and a degree of rotational averaging, thus, allowing one to determine the electrostatic contribution to the interfacial pKa of the nitroxide, and, therefore, determining the local electrostatic potential. Due to their small molecular volume these probes cause a minimal perturbation to the protein or lipid system while covalent attachment secure the position of the reporter nitroxides. Experimental procedures to characterize and calibrate these probes by EPR and also the methods to analyze the EPR spectra by least-squares simulations are also outlined. The ionizable nitroxide labels and the nitroxide-labeled phospholipids described so far cover an exceptionally wide pH range from ca. 2.5 to 7.0 pH units making them suitable to study a broad range of biophysical phenomena especially at the negatively charged lipid bilayer surfaces. The rationale for selecting proper electrostatically neutral interface for calibrating such probes and example of studying surface potential of lipid bilayer is also described. PMID:26477252

Relationships between gastric slow wave frequency, velocity, and extracellular amplitude studied by a joint experimental-theoretical approach.

PubMed

Wang, T H-H; Du, P; Angeli, T R; Paskaranandavadivel, N; Erickson, J C; Abell, T L; Cheng, L K; O'Grady, G

2018-01-01

Gastric slow wave dysrhythmias are accompanied by deviations in frequency, velocity, and extracellular amplitude, but the inherent association between these parameters in normal activity still requires clarification. This study quantified these associations using a joint experimental-theoretical approach. Gastric pacing was conducted in pigs with simultaneous high-resolution slow wave mapping (32-256 electrodes; 4-7.6 mm spacing). Relationships between period, velocity, and amplitude were quantified and correlated for each wavefront. Human data from two existing mapping control cohorts were analyzed to extract and correlate these same parameters. A validated biophysically based ICC model was also applied in silico to quantify velocity-period relationships during entrainment simulations and velocity-amplitude relationships from membrane potential equations. Porcine pacing studies identified positive correlations for velocity-period (0.13 mm s -1 per 1 s, r 2 =.63, P<.001) and amplitude-velocity (74 μV per 1 mm s -1 , r 2 =.21, P=.002). In humans, positive correlations were also quantified for velocity-period (corpus: 0.11 mm s -1 per 1 s, r 2 =.16, P<.001; antrum: 0.23 mm s -1 per 1 s, r 2 =.55; P<.001), and amplitude-velocity (94 μV per 1 mm s -1 , r 2 =.56; P<.001). Entrainment simulations matched the experimental velocity-period relationships and demonstrated dependence on the slow wave recovery phase. Simulated membrane potential relationships were close to these experimental results (100 μV per 1 mm s -1 ). These data quantify the relationships between slow wave frequency, velocity, and extracellular amplitude. The results from both human and porcine studies were in keeping with biophysical models, demonstrating concordance with ICC biophysics. These relationships are important in the regulation of gastric motility and will help to guide interpretations of dysrhythmias. © 2017 John Wiley & Sons Ltd.

Bio-physical vs. Economic Uncertainty in the Analysis of Climate Change Impacts on World Agriculture

NASA Astrophysics Data System (ADS)

Hertel, T. W.; Lobell, D. B.

2010-12-01

Accumulating evidence suggests that agricultural production could be greatly affected by climate change, but there remains little quantitative understanding of how these agricultural impacts would affect economic livelihoods in poor countries. The recent paper by Hertel, Burke and Lobell (GEC, 2010) considers three scenarios of agricultural impacts of climate change, corresponding to the fifth, fiftieth, and ninety fifth percentiles of projected yield distributions for the world’s crops in 2030. They evaluate the resulting changes in global commodity prices, national economic welfare, and the incidence of poverty in a set of 15 developing countries. Although the small price changes under the medium scenario are consistent with previous findings, their low productivity scenario reveals the potential for much larger food price changes than reported in recent studies which have hitherto focused on the most likely outcomes. The poverty impacts of price changes under the extremely adverse scenario are quite heterogeneous and very significant in some population strata. They conclude that it is critical to look beyond central case climate shocks and beyond a simple focus on yields and highly aggregated poverty impacts. In this paper, we conduct a more formal, systematic sensitivity analysis (SSA) with respect to uncertainty in the biophysical impacts of climate change on agriculture, by explicitly specifying joint distributions for global yield changes - this time focusing on 2050. This permits us to place confidence intervals on the resulting price impacts and poverty results which reflect the uncertainty inherited from the biophysical side of the analysis. We contrast this with the economic uncertainty inherited from the global general equilibrium model (GTAP), by undertaking SSA with respect to the behavioral parameters in that model. This permits us to assess which type of uncertainty is more important for regional price and poverty outcomes. Finally, we undertake a combined SSA, wherein climate change-induced productivity shocks are permitted to interact with the uncertain economic parameters. This permits us to examine potential interactions between the two sources of uncertainty.

Effect of ambient light on the time needed to complete a fetal biophysical profile: A randomized controlled trial.

PubMed

Said, Heather M; Gupta, Shweta; Vricella, Laura K; Wand, Katy; Nguyen, Thinh; Gross, Gilad

2017-10-01

The objective of this study is to determine whether ambient light serves as a fetal stimulus to decrease the amount of time needed to complete a biophysical profile. This is a randomized controlled trial of singleton gestations undergoing a biophysical profile. Patients were randomized to either ambient light or a darkened room. The primary outcome was the time needed to complete the biophysical profile. Secondary outcomes included total and individual component biophysical profile scores and scores less than 8. A subgroup analysis of different maternal body mass indices was also performed. 357 biophysical profile studies were analyzed. 182 studies were performed with ambient light and 175 were performed in a darkened room. There was no difference in the median time needed to complete the biophysical profile based on exposure to ambient light (6.1min in darkened room versus 6.6min with ambient light; P=0.73). No difference was found in total or individual component biophysical profile scores. Subgroup analysis by maternal body mass index did not demonstrate shorter study times with ambient light exposure in women who were normal weight, overweight or obese. Ambient light exposure did not decrease the time needed to complete the biophysical profile. There was no evidence that ambient light altered fetal behavior observed during the biophysical profile. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimation of reactogenicity of preparations produced on the basis of photoinactivated live vaccines against brucellosis and tularaemia on the organismic level. 2. Using the method of speckle-microscopy with high spatial resolution

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

Ulianova, O V; Uianov, S S; Li Pengcheng

2011-04-30

The method of speckle microscopy was adapted to estimate the reactogenicity of the prototypes of vaccine preparations against extremely dangerous infections. The theory is proposed to describe the mechanism of formation of the output signal from the super-high spatial resolution speckle microscope. The experimental studies show that bacterial suspensions, irradiated in different regimes of inactivation, do not exert negative influence on the blood microcirculations in laboratory animals. (optical technologies in biophysics and medicine)

Utilizing NASA Earth Observations to Assess Impacts of Hurricanes Andrew and Irma on Mangrove Forests in Biscayne Bay National Park, FL

NASA Astrophysics Data System (ADS)

Kumar, A.; Weber, S.; Remillard, C.; Escobar Pardo, M. L.; Hashemi Tonekaboni, N.; Cameron, C.; Linton, S.; Rickless, D.; Rivero, R.; Madden, M.

2017-12-01

Extreme weather events, such as hurricanes, pose major threats to coastal communities around the globe. However, mangrove forests along coastlines act as barriers and subdue the impacts associated with these catastrophic events. The Biscayne Bay National Park mangrove forest located near the city of Miami Beach was recently affected by the category four hurricane Irma in September of 2017. This study analyzed the impact of Hurricane Irma on Biscayne Bay National Park mangroves. Several remote sensing datasets including Landsat 8 Operational Land Imager (OLI), Sentinel 2-Multi Spectral Imager (MSI), PlanetScope, and aerial imagery were utilized to assess pre-and post-hurricane conditions. The high-resolution aerial imagery and PlanetScope data were used to map damaged areas within the national park. Additionally, Landsat 8 OLI and Sentinel-2 MSI data were utilized to estimate changes in biophysical parameters, including gross primary productivity (GPP), before and after Hurricane Irma. This project also examined damages associated with Hurricane Andrew (1992) using historical Landsat 5 Thematic Mapper (TM) data. These results were compared to GPP estimates following Hurricane Irma and suggested that Hurricane Andrew's impact was greater than that of Irma in Biscayne Bay National Park. The results of this study will help to enhance the mangrove health monitoring and shoreline management programs led by officials at the City of Miami Beach Public Works Department.

Alternating Current Delivered into the Scala Media Alters Sound Pressure at the Eardrum

NASA Astrophysics Data System (ADS)

Hubbard, Allyn E.; Mountain, David C.

1983-11-01

Alternating current delivered into the scala media of the gerbil cochlea modulates the amplitude of a test tone measured near the eardrum. Variations in the electromechanical effect with acoustic stimulus parameters and observed physiological vulnerability suggest that cochlear hair cells are the biophysical origin of the process. Cochlear hair cells have traditionally been thought of as passive receptor cells, but they may play an active role in cochlear micromechanics.

[Biocybernetic approach to the thermometric methods of blood supply measurements of periodontal tissues].

PubMed

Pastusiak, J; Zakrzewski, J

1988-11-01

Specific biocybernetic approach to the problem of the blood supply determination of paradontium tissues by means of thermometric methods has been presented in the paper. The compartment models of the measuring procedure have been given. Dilutodynamic methology and classification has been applied. Such an approach enables to select appropriate biophysical parameters describing the state of blood supply of paradontium tissues and optimal design of transducers and measuring methods.

Effects of an invasive polychaete on benthic phosphorus cycling at sea basin scale: An ecosystem disservice.

PubMed

Sandman, Antonia Nyström; Näslund, Johan; Gren, Ing-Marie; Norling, Karl

2018-05-05

Macrofaunal activities in sediments modify nutrient fluxes in different ways including the expression of species-specific functional traits and density-dependent population processes. The invasive polychaete genus Marenzelleria was first observed in the Baltic Sea in the 1980s. It has caused changes in benthic processes and affected the functioning of ecosystem services such as nutrient regulation. The large-scale effects of these changes are not known. We estimated the current Marenzelleria spp. wet weight biomass in the Baltic Sea to be 60-87 kton (95% confidence interval). We assessed the potential impact of Marenzelleria spp. on phosphorus cycling using a spatially explicit model, comparing estimates of expected sediment to water phosphorus fluxes from a biophysical model to ecologically relevant experimental measurements of benthic phosphorus flux. The estimated yearly net increases (95% CI) in phosphorous flux due to Marenzelleria spp. were 4.2-6.1 kton based on the biophysical model and 6.3-9.1 kton based on experimental data. The current biomass densities of Marenzelleria spp. in the Baltic Sea enhance the phosphorus fluxes from sediment to water on a sea basin scale. Although high densities of Marenzelleria spp. can increase phosphorus retention locally, such biomass densities are uncommon. Thus, the major effect of Marenzelleria seems to be a large-scale net decrease in the self-cleaning capacity of the Baltic Sea that counteracts human efforts to mitigate eutrophication in the region.

Vegetation Coverage and Impervious Surface Area Estimated Based on the Estarfm Model and Remote Sensing Monitoring

NASA Astrophysics Data System (ADS)

Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun

2018-04-01

Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

Overview of the Graphical User Interface for the GERM Code (GCR Event-Based Risk Model

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee; Cucinotta, Francis A.

2010-01-01

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERM code calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERM code also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERM code accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERM code for application to thick target experiments. The GERM code provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERM code GUI, as well as providing training applications.

Overview of the Graphical User Interface for the GERMcode (GCR Event-Based Risk Model)

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; Cucinotta, Francis A.

2010-01-01

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERMcode calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERMcode also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERMcode for application to thick target experiments. The GERMcode provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERMcode GUI, as well as providing training applications.

Computational modeling of the human auditory periphery: Auditory-nerve responses, evoked potentials and hearing loss.

PubMed

Verhulst, Sarah; Altoè, Alessandro; Vasilkov, Viacheslav

2018-03-01

Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descriptions of cellular components into human auditory models because single-cell data stems from invasive animal recordings while human reference data only exists in the form of population responses (e.g., otoacoustic emissions, auditory evoked potentials). To embed physiological models within a comprehensive human auditory periphery framework, it is important to capitalize on the success of basic functional models of hearing and render their descriptions more biophysical where possible. At the same time, comprehensive models should capture a variety of key auditory features, rather than fitting their parameters to a single reference dataset. In this study, we review and improve existing models of the IHC-AN complex by updating their equations and expressing their fitting parameters into biophysical quantities. The quality of the model framework for human auditory processing is evaluated using recorded auditory brainstem response (ABR) and envelope-following response (EFR) reference data from normal and hearing-impaired listeners. We present a model with 12 fitting parameters from the cochlea to the brainstem that can be rendered hearing impaired to simulate how cochlear gain loss and synaptopathy affect human population responses. The model description forms a compromise between capturing well-described single-unit IHC and AN properties and human population response features. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Full-waveform and discrete-return lidar in salt marsh environments: An assessment of biophysical parameters, vertical uncertatinty, and nonparametric dem correction

NASA Astrophysics Data System (ADS)

Rogers, Jeffrey N.

High-resolution and high-accuracy elevation data sets of coastal salt marsh environments are necessary to support restoration and other management initiatives, such as adaptation to sea level rise. Lidar (light detection and ranging) data may serve this need by enabling efficient acquisition of detailed elevation data from an airborne platform. However, previous research has revealed that lidar data tend to have lower vertical accuracy (i.e., greater uncertainty) in salt marshes than in other environments. The increase in vertical uncertainty in lidar data of salt marshes can be attributed primarily to low, dense-growing salt marsh vegetation. Unfortunately, this increased vertical uncertainty often renders lidar-derived digital elevation models (DEM) ineffective for analysis of topographic features controlling tidal inundation frequency and ecology. This study aims to address these challenges by providing a detailed assessment of the factors influencing lidar-derived elevation uncertainty in marshes. The information gained from this assessment is then used to: 1) test the ability to predict marsh vegetation biophysical parameters from lidar-derived metrics, and 2) develop a method for improving salt marsh DEM accuracy. Discrete-return and full-waveform lidar, along with RTK GNSS (Real-time Kinematic Global Navigation Satellite System) reference data, were acquired for four salt marsh systems characterized by four major taxa (Spartina alterniflora, Spartina patens, Distichlis spicata, and Salicornia spp.) on Cape Cod, Massachusetts. These data were used to: 1) develop an innovative combination of full-waveform lidar and field methods to assess the vertical distribution of aboveground biomass as well as its light blocking properties; 2) investigate lidar elevation bias and standard deviation using varying interpolation and filtering methods; 3) evaluate the effects of seasonality (temporal differences between peak growth and senescent conditions) using lidar data flown in summer and spring; 4) create new products, called Relative Uncertainty Surfaces (RUS), from lidar waveform-derived metrics and determine their utility; and 5) develop and test five nonparametric regression model algorithms (MARS -- Multivariate Adaptive Regression, CART -- Classification and Regression Trees, TreeNet, Random Forests, and GPSM -- Generalized Path Seeker) with 13 predictor variables derived from both discrete and full waveform lidar sources in order to develop a method of improving lidar DEM quality. Results of this study indicate strong correlations for Spartina alterniflora (r > 0.9) between vertical biomass (VB), the distribution of vegetation biomass by height, and vertical obscuration (VO), the measure of the vertical distribution of the ratio of vegetation to airspace. It was determined that simple, feature-based lidar waveform metrics, such as waveform width, can provide new information to estimate salt marsh vegetation biophysical parameters such as vegetation height. The results also clearly illustrate the importance of seasonality, species, and lidar interpolation and filtering methods on elevation uncertainty in salt marshes. Relative uncertainty surfaces generated from lidar waveform features were determined useful in qualitative/visual assessment of lidar elevation uncertainty and correlate well with vegetation height and presence of Spartina alterniflora. Finally, DEMs generated using full-waveform predictor models produced corrections (compared to ground based RTK GNSS elevations) with R2 values of up to 0.98 and slopes within 4% of a perfect 1:1 correlation. The findings from this research have strong potential to advance tidal marsh mapping, research and management initiatives.

Dealing with the Challenges of Teaching Molecular Biophysics to Biochemistry Majors through an Heuristics-Based Approach

ERIC Educational Resources Information Center

Castanho, Miguel A. R. B.

2002-01-01

The main distinction between the overlapping fields of molecular biophysics and biochemistry resides in their different approaches to the same problems. Molecular biophysics makes more use of physical techniques and focuses on quantitative data. This difference encounters two difficult pedagogical challenges when teaching molecular biophysics to…

[Physiological basis of a possible increase in the efficacy of the photo- and magnetotherapy of the visual nerve upon partial atrophy and ischemia].

PubMed

Shlygin, V V; Tiuliaev, A P; Ioĭleva, E E; Maksimov, G V

2004-01-01

An approach to the choice of the parameters of physiotherapeutic and biophysical influence on the visual nerve was proposed. The approach is based on parallel photo- and magnetostimulation of excitable fibers in which the morphological and electrophysiological properties of fibers and some parameters of the pathological processes associated with partial artophy and ischemia are taken into account. A method for correlating the photostimulation by light flashes (intensity 65 mWt at emission wavelength 660 nm) of a portion of the retina with the choice of the parameters of magnetic influence (amplitude 73 mT, duration of the wave front of 40 ms, and frequency of pulse sequence of about 1 Hz) on the visual nerve was developed.

Photophysical Study of Novel Perylene Analogues for Biophysical Applications

NASA Astrophysics Data System (ADS)

Palos-Chávez, Jorge; Penick, Mark; Negrete, George; Brancaleon, Lorenzo

2011-03-01

Perylene and perylene derivatives have been shown to be useful in a variety of photoinitiated applications, such as molecular dyes, organic solar cells, etc. Recently we started the characterization of novel 3,9-perylene analogues which could potentially lead to the synthesis of novel molecules with improved ability to separate charges. We have characterized the basic photophysical properties of these molecules, and we are currently investigating the photochemistry that leads to photoproducts in chlorinated compounds. Spectroscopic measurements show the substantial changes in photophysical parameters consistent with the conversion of the original compounds into photoproducts. SEM and AFM imaging show that these photoproducts form ordered particles. Mass spectrometry studies have confirmed the presence of these photoproducts as well. Additional studies are underway concerning the use of these novel perylene analogues in binding to biological structures such as proteins. It is hoped that these compounds will prove useful for biophysical applications, specifically in studying the manipulation of protein conformation via physical methods. Supported by NIH/NIGMS MBRS RISE GM-60655.

Biophysical characterization of V3-lipopeptide liposomes influencing HIV-1 infectivity

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

Rizos, Apostolos K.; Baritaki, Stavroula; Department of Virology, Medical School, University of Crete, Heraklion, Crete

2007-04-20

The V3-loop of the HIV-1 gp120 alters host cell immune function and modulates infectivity. We investigated biophysical parameters of liposome constructs with embedded lipopeptides from the principle neutralizing domain of the V3-loop and their influence on viral infectivity. Dynamic light scattering measurements showed liposome supramolecular structures with hydrodynamic radius of the order of 900 and 1300 nm for plain and V3-lipopeptide liposomes. Electron paramagnetic resonance measurements showed almost identical local microenvironment. The difference in liposome hydrodynamic radius was attributed to the fluctuating ionic environment of the V3-lipopeptide liposomes. In vitro HIV-1 infectivity assays showed that plain liposomes reduced virus productionmore » in all cell cultures, probably due to the hydrophobic nature of the aggregates. Liposomes carrying V3-lipopeptides with different cationic potentials restored and even enhanced infectivity (p < 0.05). These results highlight the need for elucidation of the involvement of lipid bilayers as dynamic components in supramolecular structures and in HIV-1 fusion mechanisms.« less

In vivo measurement of age-related stiffening in the crystalline lens by Brillouin optical microscopy.

PubMed

Scarcelli, Giuliano; Kim, Pilhan; Yun, Seok Hyun

2011-09-21

The biophysical and biomechanical properties of the crystalline lens (e.g., viscoelasticity) have long been implicated in accommodation and vision problems, such as presbyopia and cataracts. However, it has been difficult to measure such parameters noninvasively. Here, we used in vivo Brillouin optical microscopy to characterize material acoustic properties at GHz frequency and measure the longitudinal elastic moduli of lenses. We obtained three-dimensional elasticity maps of the lenses in live mice, which showed biomechanical heterogeneity in the cortex and nucleus of the lens with high spatial resolution. An in vivo longitudinal study of mice over a period of 2 months revealed a marked age-related stiffening of the lens nucleus. We found remarkably good correlation (log-log linear) between the Brillouin elastic modulus and the Young's modulus measured by conventional mechanical techniques at low frequencies (~1 Hz). Our results suggest that Brillouin microscopy is potentially useful for basic and animal research and clinical ophthalmology. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Elucidating the molecular mechanisms underlying cellular response to biophysical cues using synthetic biology approaches

PubMed Central

Denning, Denise; Roos, Wouter H.

2016-01-01

ABSTRACT The use of synthetic surfaces and materials to influence and study cell behavior has vastly progressed our understanding of the underlying molecular mechanisms involved in cellular response to physicochemical and biophysical cues. Reconstituting cytoskeletal proteins and interfacing them with a defined microenvironment has also garnered deep insight into the engineering mechanisms existing within the cell. This review presents recent experimental findings on the influence of several parameters of the extracellular environment on cell behavior and fate, such as substrate topography, stiffness, chemistry and charge. In addition, the use of synthetic environments to measure physical properties of the reconstituted cytoskeleton and their interaction with intracellular proteins such as molecular motors is discussed, which is relevant for understanding cell migration, division and structural integrity, as well as intracellular transport. Insight is provided regarding the next steps to be taken in this interdisciplinary field, in order to achieve the global aim of artificially directing cellular response. PMID:27266767

Protein–ligand interactions investigated by thermal shift assays (TSA) and dual polarization interferometry (DPI)

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

Grøftehauge, Morten K., E-mail: m.k.groftehauge@durham.ac.uk; Hajizadeh, Nelly R.; Swann, Marcus J.

2015-01-01

The biophysical characterization of protein–ligand interactions in solution using techniques such as thermal shift assay, or on surfaces using, for example, dual polarization interferometry, plays an increasingly important role in complementing crystal structure determinations. Over the last decades, a wide range of biophysical techniques investigating protein–ligand interactions have become indispensable tools to complement high-resolution crystal structure determinations. Current approaches in solution range from high-throughput-capable methods such as thermal shift assays (TSA) to highly accurate techniques including microscale thermophoresis (MST) and isothermal titration calorimetry (ITC) that can provide a full thermodynamic description of binding events. Surface-based methods such as surface plasmonmore » resonance (SPR) and dual polarization interferometry (DPI) allow real-time measurements and can provide kinetic parameters as well as binding constants. DPI provides additional spatial information about the binding event. Here, an account is presented of new developments and recent applications of TSA and DPI connected to crystallography.« less

Morphogengineering roots: comparing mechanisms of morphogen gradient formation

PubMed Central

2012-01-01

Background In developmental biology, there has been a recent focus on the robustness of morphogen gradients as possible providers of positional information. It was shown that functional morphogen gradients present strong biophysical constraints and lack of robustness to noise. Here we explore how the details of the mechanism which underlies the generation of a morphogen gradient can influence those properties. Results We contrast three gradient-generating mechanisms, (i) a source-decay mechanism; and (ii) a unidirectional transport mechanism; and (iii) a so-called reflux-loop mechanism. Focusing on the dynamics of the phytohormone auxin in the root, we show that only the reflux-loop mechanism can generate a gradient that would be adequate to supply functional positional information for the Arabidopsis root, for biophysically reasonable kinetic parameters. Conclusions We argue that traits that differ in spatial and temporal time-scales can impose complex selective pressures on the mechanism of morphogen gradient formation used for the development of the particular organism. PMID:22583698

Lipid phase behavior studied with a quartz crystal microbalance: A technique for biophysical studies with applications in screening

NASA Astrophysics Data System (ADS)

Peschel, Astrid; Langhoff, Arne; Uhl, Eva; Dathathreyan, Aruna; Haindl, Susanne; Johannsmann, Diethelm; Reviakine, Ilya

2016-11-01

Quartz crystal microbalance (QCM) is emerging as a versatile tool for studying lipid phase behavior. The technique is attractive for fundamental biophysical studies as well applications because of its simplicity, flexibility, and ability to work with very small amounts of material crucial for biomedical studies. Further progress hinges on the understanding of the mechanism, by which a surface-acoustic technique such as QCM, senses lipid phase changes. Here, we use a custom-built instrument with improved sensitivity to investigate phase behavior in solid-supported lipid systems of different geometries (adsorbed liposomes and bilayers). We show that we can detect a model anesthetic (ethanol) through its effect on the lipid phase behavior. Further, through the analysis of the overtone dependence of the phase transition parameters, we show that hydrodynamic effects are important in the case of adsorbed liposomes, and viscoelasticity is significant in supported bilayers, while layer thickness changes make up the strongest contribution in both systems.

Intercomparison of a 'Bottom-up' and 'Top-down' Modeling Paradigm for estimating carbon and latent heat fluxes over a variety of vegetative regimes across the U.S., Agricultural and Forest Meteorology

USDA-ARS?s Scientific Manuscript database

Biophysical models intended for routine applications at a range of scales should attempt to balance the competing demands of generality and simplicity and be capable of realistically simulating the response of CO2 and energy fluxes to environmental and physiological forcings. At the same time they m...

Linking ecosystem characteristics to final ecosystem services for public policy.

PubMed

Wong, Christina P; Jiang, Bo; Kinzig, Ann P; Lee, Kai N; Ouyang, Zhiyun

2015-01-01

Governments worldwide are recognising ecosystem services as an approach to address sustainability challenges. Decision-makers need credible and legitimate measurements of ecosystem services to evaluate decisions for trade-offs to make wise choices. Managers lack these measurements because of a data gap linking ecosystem characteristics to final ecosystem services. The dominant method to address the data gap is benefit transfer using ecological data from one location to estimate ecosystem services at other locations with similar land cover. However, benefit transfer is only valid once the data gap is adequately resolved. Disciplinary frames separating ecology from economics and policy have resulted in confusion on concepts and methods preventing progress on the data gap. In this study, we present a 10-step approach to unify concepts, methods and data from the disparate disciplines to offer guidance on overcoming the data gap. We suggest: (1) estimate ecosystem characteristics using biophysical models, (2) identify final ecosystem services using endpoints and (3) connect them using ecological production functions to quantify biophysical trade-offs. The guidance is strategic for public policy because analysts need to be: (1) realistic when setting priorities, (2) attentive to timelines to acquire relevant data, given resources and (3) responsive to the needs of decision-makers. © 2014 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

The Influence of Life History Variability on Population Connectivity: Development and Application of a Trait-Based Biophysical Model of Individuals

NASA Astrophysics Data System (ADS)

Wong-Ala, J.; Neuheimer, A. B.; Hixon, M.; Powell, B.

2016-02-01

Connectivity estimates, which measure the exchange of individuals among populations, are necessary to create effective reserves for marine life. Connectivity can be influenced by a combination of biology (e.g. spawning time) and physics (e.g. currents). In the past a dispersal model was created in an effort to explain connectivity for the highly sought after reef fish Lau`ipala (Yellow Tang, Zebrasoma flavescens) around Hawai`i Island using physics alone, but this was shown to be insufficient. Here we created an individual based model (IBM) to describe Lau`ipala life history and behavior forced with ocean currents and temperature (via coupling to a physical model) to examine biophysical interactions. The IBM allows for tracking of individual fish from spawning to settlement, and individual variability in modeled processes. We first examined the influence of different reproductive (e.g. batch vs. constant spawners), developmental (e.g. pelagic larval duration), and behavioral (e.g. active vs. passive buoyancy control) traits on modeled connectivity estimates for larval reef fish around Hawai`i Island and compared results to genetic observations of parent-offspring pair distribution. Our model is trait-based which allows individuals to vary in life history strategies enabling mechanistic links between predictions and underlying traits and straightforward applications to other species and sites.

Implications of heterogeneous impacts of protected areas on deforestation and poverty

PubMed Central

Hanauer, Merlin M.; Canavire-Bacarreza, Gustavo

2015-01-01

Protected areas are a popular policy instrument in the global fight against loss of biodiversity and ecosystem services. However, the effectiveness of protected areas in preventing deforestation, and their impacts on poverty, are not well understood. Recent studies have found that Bolivia's protected-area system, on average, reduced deforestation and poverty. We implement several non-parametric and semi-parametric econometric estimators to characterize the heterogeneity in Bolivia's protected-area impacts on joint deforestation and poverty outcomes across a number of socioeconomic and biophysical moderators. Like previous studies from Costa Rica and Thailand, we find that Bolivia's protected areas are not associated with poverty traps. Our results also indicate that protection did not have a differential impact on indigenous populations. However, results from new multidimensional non-parametric estimators provide evidence that the biophysical characteristics associated with the greatest avoided deforestation are the characteristics associated with the potential for poverty exacerbation from protection. We demonstrate that these results would not be identified using the methods implemented in previous studies. Thus, this study provides valuable practical information on the impacts of Bolivia's protected areas for conservation practitioners and demonstrates methods that are likely to be valuable to researchers interested in better understanding the heterogeneity in conservation impacts. PMID:26460125

Implications of heterogeneous impacts of protected areas on deforestation and poverty.

PubMed

Hanauer, Merlin M; Canavire-Bacarreza, Gustavo

2015-11-05

Protected areas are a popular policy instrument in the global fight against loss of biodiversity and ecosystem services. However, the effectiveness of protected areas in preventing deforestation, and their impacts on poverty, are not well understood. Recent studies have found that Bolivia's protected-area system, on average, reduced deforestation and poverty. We implement several non-parametric and semi-parametric econometric estimators to characterize the heterogeneity in Bolivia's protected-area impacts on joint deforestation and poverty outcomes across a number of socioeconomic and biophysical moderators. Like previous studies from Costa Rica and Thailand, we find that Bolivia's protected areas are not associated with poverty traps. Our results also indicate that protection did not have a differential impact on indigenous populations. However, results from new multidimensional non-parametric estimators provide evidence that the biophysical characteristics associated with the greatest avoided deforestation are the characteristics associated with the potential for poverty exacerbation from protection. We demonstrate that these results would not be identified using the methods implemented in previous studies. Thus, this study provides valuable practical information on the impacts of Bolivia's protected areas for conservation practitioners and demonstrates methods that are likely to be valuable to researchers interested in better understanding the heterogeneity in conservation impacts. © 2015 The Author(s).

The Shape of the Urine Stream — From Biophysics to Diagnostics

PubMed Central

Wheeler, Andrew P. S.; Morad, Samir; Buchholz, Noor; Knight, Martin M.

2012-01-01

We develop a new computational model of capillary-waves in free-jet flows, and apply this to the problem of urological diagnosis in this first ever study of the biophysics behind the characteristic shape of the urine stream as it exits the urethral meatus. The computational fluid dynamics model is used to determine the shape of a liquid jet issuing from a non-axisymmetric orifice as it deforms under the action of surface tension. The computational results are verified with experimental modelling of the urine stream. We find that the shape of the stream can be used as an indicator of both the flow rate and orifice geometry. We performed volunteer trials which showed these fundamental correlations are also observed in vivo for male healthy volunteers and patients undergoing treatment for low flow rate. For healthy volunteers, self estimation of the flow shape provided an accurate estimation of peak flow rate (). However for the patients, the relationship between shape and flow rate suggested poor meatal opening during voiding. The results show that self measurement of the shape of the urine stream can be a useful diagnostic tool for medical practitioners since it provides a non-invasive method of measuring urine flow rate and urethral dilation. PMID:23091609

Linking ecosystem characteristics to final ecosystem services for public policy

PubMed Central

Wong, Christina P; Jiang, Bo; Kinzig, Ann P; Lee, Kai N; Ouyang, Zhiyun

2015-01-01

Governments worldwide are recognising ecosystem services as an approach to address sustainability challenges. Decision-makers need credible and legitimate measurements of ecosystem services to evaluate decisions for trade-offs to make wise choices. Managers lack these measurements because of a data gap linking ecosystem characteristics to final ecosystem services. The dominant method to address the data gap is benefit transfer using ecological data from one location to estimate ecosystem services at other locations with similar land cover. However, benefit transfer is only valid once the data gap is adequately resolved. Disciplinary frames separating ecology from economics and policy have resulted in confusion on concepts and methods preventing progress on the data gap. In this study, we present a 10-step approach to unify concepts, methods and data from the disparate disciplines to offer guidance on overcoming the data gap. We suggest: (1) estimate ecosystem characteristics using biophysical models, (2) identify final ecosystem services using endpoints and (3) connect them using ecological production functions to quantify biophysical trade-offs. The guidance is strategic for public policy because analysts need to be: (1) realistic when setting priorities, (2) attentive to timelines to acquire relevant data, given resources and (3) responsive to the needs of decision-makers. PMID:25394857

ACR Appropriateness Criteria® growth disturbances - risk of intrauterine growth restriction.

PubMed

Zelop, Carolyn M; Javitt, Marcia C; Glanc, Phyllis; Dubinsky, Theodore; Harisinghani, Mukesh G; Harris, Robert D; Khati, Nadia J; Mitchell, Donald G; Pandharipande, Pari V; Pannu, Harpreet K; Podrasky, Ann E; Shipp, Thomas D; Siegel, Cary Lynn; Simpson, Lynn; Wall, Darci J; Wong-You-Cheong, Jade J

2013-09-01

Fetal growth disturbances include fetuses at risk for intrauterine growth restriction. These fetuses may have an estimated fetal weight at less than the 10% or demonstrate a plateau of fetal growth with an estimated fetal growth greater than the 10%. Uteroplacental insufficiency may play a major role in the etiology of intrauterine growth restriction. Fetuses at risk for intrauterine fetal growth restriction are susceptible to the potential hostility of the intrauterine environment leading to fetal hypoxia and fetal acidosis. Fetal well-being can be assessed using biophysical profile, Doppler velocimetry, fetal heart rate monitoring, and fetal movement counting.Fetal growth disturbances include fetuses at risk for intrauterine growth restriction. These fetuses may have an estimated fetal weight at less than the 10% or demonstrate a plateau of fetal growth with an estimated fetal growth greater than the 10%. Uteroplacental insufficiency may play a major role in the etiology of intrauterine growth restriction. Fetuses at risk for intrauterine fetal growth restriction are susceptible to the potential hostility of the intrauterine environment leading to fetal hypoxia and fetal acidosis. Fetal well-being can be assessed using biophysical profile, Doppler velocimetry, fetal heart rate monitoring, and fetal movement counting.The ACR Appropriateness Criteria® are evidence-based guidelines for specific clinical conditions that are reviewed every two years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

Coastal Zone Ecosystem Services: from science to values and decision making; a case study.

PubMed

Luisetti, T; Turner, R K; Jickells, T; Andrews, J; Elliott, M; Schaafsma, M; Beaumont, N; Malcolm, S; Burdon, D; Adams, C; Watts, W

2014-09-15

This research is concerned with the following environmental research questions: socio-ecological system complexity, especially when valuing ecosystem services; ecosystems stock and services flow sustainability and valuation; the incorporation of scale issues when valuing ecosystem services; and the integration of knowledge from diverse disciplines for governance and decision making. In this case study, we focused on ecosystem services that can be jointly supplied but independently valued in economic terms: healthy climate (via carbon sequestration and storage), food (via fisheries production in nursery grounds), and nature recreation (nature watching and enjoyment). We also explored the issue of ecosystem stock and services flow, and we provide recommendations on how to value stock and flows of ecosystem services via accounting and economic values respectively. We considered broadly comparable estuarine systems located on the English North Sea coast: the Blackwater estuary and the Humber estuary. In the past, these two estuaries have undergone major land-claim. Managed realignment is a policy through which previously claimed intertidal habitats are recreated allowing the enhancement of the ecosystem services provided by saltmarshes. In this context, we investigated ecosystem service values, through biophysical estimates and welfare value estimates. Using an optimistic (extended conservation of coastal ecosystems) and a pessimistic (loss of coastal ecosystems because of, for example, European policy reversal) scenario, we find that context dependency, and hence value transfer possibilities, vary among ecosystem services and benefits. As a result, careful consideration in the use and application of value transfer, both in biophysical estimates and welfare value estimates, is advocated to supply reliable information for policy making. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

Potential Influences of Climate and Nest Structure on Spotted Owl Reproductive Success: A Biophysical Approach

PubMed Central

Rockweit, Jeremy T.; Franklin, Alan B.; Bakken, George S.; Gutiérrez, R. J.

2012-01-01

Many bird species do not make their own nests; therefore, selection of existing sites that provide adequate microclimates is critical. This is particularly true for owls in north temperate climates that often nest early in the year when inclement weather is common. Spotted owls use three main types of nest structures, each of which are structurally distinct and may provide varying levels of protection to the eggs or young. We tested the hypothesis that spotted owl nest configuration influences nest microclimate using both experimental and observational data. We used a wind tunnel to estimate the convective heat transfer coefficient (hc) of eggs in 25 potential nest configurations that mimicked 2 nest types (top-cavity and platform nests), at 3 different wind speeds. We then used the estimates of hc in a biophysical heat transfer model to estimate how long it would take unattended eggs to cool from incubation temperature (∼36°C) to physiological zero temperature (PZT; ∼26°C) under natural environmental conditions. Our results indicated that the structural configuration of nests influences the cooling time of the eggs inside those nests, and hence, influences the nest microclimate. Estimates of time to PZT ranged from 10.6 minutes to 33.3 minutes. Nest configurations that were most similar to platform nests always had the fastest egg cooling times, suggesting that platform nests were the least protective of those nests we tested. Our field data coupled with our experimental results suggested that nest choice is important for the reproductive success of owls during years of inclement weather or in regions characterized by inclement weather during the nesting season. PMID:22859993

Trends in Biophysical Research and Their Implications for Medical Libraries

PubMed Central

Chen, Ching-chih

1973-01-01

This is a statistical survey of the trends in biophysical research as reflected by papers presented at four Biophysical Society (BPS) annual meetings between 1958 and 1972 and by the funding sources of the reported projects. The study reveals that biophysical research has grown quite substantially, particularly since 1968. Although biophysics is truly interdisciplinary, since 1968 there has been more pronounced emphasis on biomedically oriented problems and a tendency toward more specific and more highly specialized problems. Between 1958 and 1972, most biophysicists were academic researchers, 50% of whom were biomedical scientists. Over three quarters of the ongoing biophysical research projects during this period were supported by governmental agencies, and among them, the National Institutes of Health was the largest single funding source. PMID:4573970

Applications of the BIOPHYS Algorithm for Physically-Based Retrieval of Biophysical, Structural and Forest Disturbance Information

NASA Technical Reports Server (NTRS)

Peddle, Derek R.; Huemmrich, K. Fred; Hall, Forrest G.; Masek, Jeffrey G.; Soenen, Scott A.; Jackson, Chris D.

2011-01-01

Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.

Biophysical characterization and management effects on semiarid rangeland observed from Landsat ETM+ data

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

Fang, Hongliang; Liang, Shunlin; McClaran, Mitchell P.

2005-01-20

Semi-arid rangelands are very sensitive to global climatic change; studies of their biophysical attributes are crucial to understanding the dynamics of rangeland ecosystems under human disturbance. In the Santa Rita Experimental Range (SRER), Arizona, the vegetation has changed considerably and there have been many management activities applied. This study calculates seven surface variables: the enhanced vegetation index (EVI), the normalized difference vegetation index (NDVI), surface albedos (total shortwave, visible and near-infrared), leaf area index (LAI) and the fraction of photosynthetically active radiation absorbed by green vegetation (FPAR) from the Enhanced Thematic Mapper (ETM+) data. Comparison with the MODIS (Moderate Resolutionmore » Imaging Spectroradiometer) vegetation index and albedo products indicate they agree well with our estimates from ETM+ while their LAI and FPAR are larger than ETM+. Human disturbance has significantly changed the cover types and biophysical conditions. Statistical tests indicate that surface albedos increased and FPAR decreased at all sites. The recovery will require more than 67 years, and is about 50% complete within 40 years at the higher elevation. Grass cover, vegetation indices, albedos and LAI recovered from cutting faster at the higher elevation. Woody plants, vegetation indices and LAI have recovered to their original characteristics after 65 years at the lower elevation. More studies are needed to examine the spectral characteristics of different ground components.« less

An Analysis of Potential Predictive Parameters of Motion Sickness Using a Computerized Biophysical Data Acquisition System.

DTIC Science & Technology

1985-12-01

Despite the problems, drug therapy was seen as the easiest and most effective treatment. Some wartime research, primarily Canadian and Australian ...sickness was further supported by the Australians when they found that small head motions greatly contributed to the onset of motion sickness (46:20). It is...particularly noteworthy that one Australian , McIntyre, laid the groundwork for modern sensory conflict theory when he stated in 1941, "In most cases

Biophysics of Cold Adaptation and Acclimatization: Microbial Decomposition.

DTIC Science & Technology

1984-03-01

plant communities. Parameters such as temperature, precipitation and relative humidity, as they are related to winds and sea ice, interact to produce the...predictable pattern, 9 the occurrence of clouds, precipitation and heavy fogs build to a maximum as the number of daily sunshine hours increases. At 12...August 2, the sun finally sets for 1 hour and 25 minutes. Climatic records kept since 1934 show low precipitation levels with a 40 year mean of 11.5 cm/yr

Biophysical model for assessment of risk of acute exposures in combination with low level chronic irradiation

NASA Astrophysics Data System (ADS)

Smirnova, O. A.

A biophysical model is developed which describes the mortality dynamics in mammalian populations unexposed and exposed to radiation The model relates statistical biometric functions mortality rate life span probability density and life span probability with statistical characteristics and dynamics of a critical body system in individuals composing the population The model describing the dynamics of thrombocytopoiesis in nonirradiated and irradiated mammals is also developed this hematopoietic line being considered as the critical body system under exposures in question The mortality model constructed in the framework of the proposed approach was identified to reproduce the irradiation effects on populations of mice The most parameters of the thrombocytopoiesis model were determined from the data available in the literature on hematology and radiobiology the rest parameters were evaluated by fitting some experimental data on the dynamics of this system in acutely irradiated mice The successful verification of the thrombocytopoiesis model was fulfilled by the quantitative juxtaposition of the modeling predictions and experimental data on the dynamics of this system in mice exposed to either acute or chronic irradiation at wide ranges of doses and dose rates It is important that only experimental data on the mortality rate in nonirradiated population and the relevant statistical characteristics of the thrombocytopoiesis system in mice which are also available in the literature on radiobiology are needed for the final identification of

Label-free high-throughput imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mahjoubfar, A.; Chen, C.; Niazi, K. R.; Rabizadeh, S.; Jalali, B.

2014-03-01

Flow cytometry is an optical method for studying cells based on their individual physical and chemical characteristics. It is widely used in clinical diagnosis, medical research, and biotechnology for analysis of blood cells and other cells in suspension. Conventional flow cytometers aim a laser beam at a stream of cells and measure the elastic scattering of light at forward and side angles. They also perform single-point measurements of fluorescent emissions from labeled cells. However, many reagents used in cell labeling reduce cellular viability or change the behavior of the target cells through the activation of undesired cellular processes or inhibition of normal cellular activity. Therefore, labeled cells are not completely representative of their unaltered form nor are they fully reliable for downstream studies. To remove the requirement of cell labeling in flow cytometry, while still meeting the classification sensitivity and specificity goals, measurement of additional biophysical parameters is essential. Here, we introduce an interferometric imaging flow cytometer based on the world's fastest continuous-time camera. Our system simultaneously measures cellular size, scattering, and protein concentration as supplementary biophysical parameters for label-free cell classification. It exploits the wide bandwidth of ultrafast laser pulses to perform blur-free quantitative phase and intensity imaging at flow speeds as high as 10 meters per second and achieves nanometer-scale optical path length resolution for precise measurements of cellular protein concentration.

Teaching and learning the Hodgkin-Huxley model based on software developed in NEURON’s programming language hoc

PubMed Central

2013-01-01

Background We present a software tool called SENB, which allows the geometric and biophysical neuronal properties in a simple computational model of a Hodgkin-Huxley (HH) axon to be changed. The aim of this work is to develop a didactic and easy-to-use computational tool in the NEURON simulation environment, which allows graphical visualization of both the passive and active conduction parameters and the geometric characteristics of a cylindrical axon with HH properties. Results The SENB software offers several advantages for teaching and learning electrophysiology. First, SENB offers ease and flexibility in determining the number of stimuli. Second, SENB allows immediate and simultaneous visualization, in the same window and time frame, of the evolution of the electrophysiological variables. Third, SENB calculates parameters such as time and space constants, stimuli frequency, cellular area and volume, sodium and potassium equilibrium potentials, and propagation velocity of the action potentials. Furthermore, it allows the user to see all this information immediately in the main window. Finally, with just one click SENB can save an image of the main window as evidence. Conclusions The SENB software is didactic and versatile, and can be used to improve and facilitate the teaching and learning of the underlying mechanisms in the electrical activity of an axon using the biophysical properties of the squid giant axon. PMID:23675833

Hyperpolarization-Activated Current Induces Period-Doubling Cascades and Chaos in a Cold Thermoreceptor Model

PubMed Central

Xu, Kesheng; Maidana, Jean P.; Caviedes, Mauricio; Quero, Daniel; Aguirre, Pablo; Orio, Patricio

2017-01-01

In this article, we describe and analyze the chaotic behavior of a conductance-based neuronal bursting model. This is a model with a reduced number of variables, yet it retains biophysical plausibility. Inspired by the activity of cold thermoreceptors, the model contains a persistent Sodium current, a Calcium-activated Potassium current and a hyperpolarization-activated current (Ih) that drive a slow subthreshold oscillation. Driven by this oscillation, a fast subsystem (fast Sodium and Potassium currents) fires action potentials in a periodic fashion. Depending on the parameters, this model can generate a variety of firing patterns that includes bursting, regular tonic and polymodal firing. Here we show that the transitions between different firing patterns are often accompanied by a range of chaotic firing, as suggested by an irregular, non-periodic firing pattern. To confirm this, we measure the maximum Lyapunov exponent of the voltage trajectories, and the Lyapunov exponent and Lempel-Ziv's complexity of the ISI time series. The four-variable slow system (without spiking) also generates chaotic behavior, and bifurcation analysis shows that this is often originated by period doubling cascades. Either with or without spikes, chaos is no longer generated when the Ih is removed from the system. As the model is biologically plausible with biophysically meaningful parameters, we propose it as a useful tool to understand chaotic dynamics in neurons. PMID:28344550

Investigating the Relationship Between Liquid Water and Leaf Area in Clonal Populus

NASA Technical Reports Server (NTRS)

Roberts, Dar; Brown, K.; Green, R.; Ustin, S.; Hinckley, T.

1998-01-01

Leaf Area Index (LAI) is one of the most commonly employed biophysical parameters used to characterize vegetation canopies and scale leaf physiological processes to larger scales. For example, LAI is a critical parameter used in regional scale estimates of evapotranspiration, photosynthesis, primary productivity, and carbon cycling (Running et al., 1989; Dorman and Sellers, 1989; Potter et al., 1993). LAI is typically estimated using ratio-based techniques, such as the Normalized Difference Vegetation Index (NDVI: e.g. Tucker 1979; Asrar et al., 1989; Sellers 1985, 1987). The physical basis behind this relationship depends on the high spectral contrast between scattered near-infrared (NIR) and absorbed red radiation in canopies. As the number of leaves present in a canopy increases over a unit area, NIR reflectance increases, while red reflectance decreases, resulting in an increase in the ratio. Through time series and image compositing, NDVI provides an additional temporal measure of how these parameters change, providing a means to monitor fluxes and productivity (Tucker et al., 1983). NDVI, while highly successful for agriculture and grassland ecosystems has been found to be less successful in evergreen chaparral and forested ecosystems (Badhwar et al., 1986; Gamon et al., 1993; Hall et al., 1995). Typically, the relationship between NDVI and LAI becomes progressively more asymptotic at LAI values above three (Sellers, 1985), although linear relationships have been observed in conifers at LAis as high as 13 (Spanner et al., 1990). In this paper, we explore an alternative approach for estimating LAI for remotely sensed data from AVIRIS based on estimates of canopy liquid water. Our primary objective is to test the hypothesis that the depth of the liquid water bands expressed in canopy reflectance spectra at 960, 1200, 1400 and 1900 nm increases with increasing LAI in canopies. This study builds from work by Roberts et al. (1997), in which liquid water was shown to increase following a gradient of increasing LAI ranging from grasslands to coniferous forests. In that study, it was observed that forests, which showed little variation in NDVI, showed significant variation in liquid water. In order to test this hypothesis, we analyzed field spectra measured over Populus resprouts of known LAI and monitored changes in liquid water in young Populus stands as they aged over a 4-year time span. The study was conducted in south-central Washington, in a clonal Populus fiber farm owned and operated by Boise-Cascade near the town of Wallula.

Biophysics: for HTS hit validation, chemical lead optimization, and beyond.

PubMed

Genick, Christine C; Wright, S Kirk

2017-09-01

There are many challenges to the drug discovery process, including the complexity of the target, its interactions, and how these factors play a role in causing the disease. Traditionally, biophysics has been used for hit validation and chemical lead optimization. With its increased throughput and sensitivity, biophysics is now being applied earlier in this process to empower target characterization and hit finding. Areas covered: In this article, the authors provide an overview of how biophysics can be utilized to assess the quality of the reagents used in screening assays, to validate potential tool compounds, to test the integrity of screening assays, and to create follow-up strategies for compound characterization. They also briefly discuss the utilization of different biophysical methods in hit validation to help avoid the resource consuming pitfalls caused by the lack of hit overlap between biophysical methods. Expert opinion: The use of biophysics early on in the drug discovery process has proven crucial to identifying and characterizing targets of complex nature. It also has enabled the identification and classification of small molecules which interact in an allosteric or covalent manner with the target. By applying biophysics in this manner and at the early stages of this process, the chances of finding chemical leads with novel mechanisms of action are increased. In the future, focused screens with biophysics as a primary readout will become increasingly common.

New horizons in Biophysics

PubMed Central

2011-01-01

This editorial celebrates the re-launch of PMC Biophysics previously published by PhysMath Central, in its new format as BMC Biophysics published by BioMed Central with an expanded scope and Editorial Board. BMC Biophysics will fill its own niche in the BMC series alongside complementary companion journals including BMC Bioinformatics, BMC Medical Physics, BMC Structural Biology and BMC Systems Biology. PMID:21595996

Biophysics of protein evolution and evolutionary protein biophysics

PubMed Central

Sikosek, Tobias; Chan, Hue Sun

2014-01-01

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution. PMID:25165599

Regional comparison of tundra carbon budget response over the Alaska North Slope to varying environmental conditions as informed by in situ and flux tower measurements, remote sensing and biophysical modeling

NASA Astrophysics Data System (ADS)

Shirley, S.; Watts, J. D.; Kimball, J. S.; Zhang, Z.; Poulter, B.; Klene, A. E.; Jones, L. A.; Kim, Y.; Oechel, W. C.; Zona, D.; Euskirchen, E. S.

2017-12-01

A warming Arctic climate is contributing to shifts in landscape moisture and temperature regimes, a shortening of the non-frozen season, and increases in the depth of annual active layer. The changing environmental conditions make it difficult to determine whether tundra ecosystems are a carbon sink or source. At present, eddy covariance flux towers and biophysical measurements within the tower footprint provide the most direct assessment of change to the tundra carbon balance. However, these measurements have a limited spatial footprint and exist over relatively short timescales. Thus, terrestrial ecosystem models are needed to provide an improved understanding of how changes in landscape environmental conditions impact regional carbon fluxes. This study examines the primary drivers thought to affect the magnitude and variability of tundra-atmosphere CO2 and CH4 fluxes over the Alaska North Slope. Also investigated is the ability of biophysical models to capture seasonal flux characteristics over the 9 tundra tower sites examined. First, we apply a regression tree approach to ascertain which remotely sensed environmental variables best explain observed variability in the tower fluxes. Next, we compare flux estimates obtained from multiple process models including Terrestrial Carbon Flux (TCF) and the Lund-Potsdam-Jena Wald Schnee und Landschaft (LPJ-wsl), and Soil Moisture Active Passive Level 4 Carbon (SMAP L4_C) products. Our results indicate that out of 7 variables examined vegetation greenness, temperature, and moisture are more significant predictors of carbon flux magnitude over the tundra tower sites. This study found that satellite data-driven models, due to the ability of remote sensing instruments to capture the physical principles and processes driving tundra carbon flux, are more effective at estimating the magnitude and spatiotemporal variability of CO2 and CH4 fluxes in northern high latitude ecosystems.

Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations.

PubMed

Costa, Caroline Mendonca; Hoetzl, Elena; Rocha, Bernardo Martins; Prassl, Anton J; Plank, Gernot

2013-10-01

Driven by recent advances in medical imaging, image segmentation and numerical techniques, computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parameterization poses a major challenge. A minimum requirement in combined experimental and modeling studies is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study, we propose basic techniques which aid in determining bidomain parameters to match activation sequences. An iterative parameterization algorithm is implemented which determines appropriate bulk conductivities which yield prescribed velocities. In addition, a method is proposed for splitting the computed bulk conductivities into individual bidomain conductivities by prescribing anisotropy ratios.

Combined Screening for Early Detection of Pre-Eclampsia

PubMed Central

Park, Hee Jin; Shim, Sung Shin; Cha, Dong Hyun

2015-01-01

Although the precise pathophysiology of pre-eclampsia remains unknown, this condition continues to be a major cause of maternal and fetal mortality. Early prediction of pre-eclampsia would allow for timely initiation of preventive therapy. A combination of biophysical and biochemical markers are superior to other tests for early prediction of the development of pre-eclampsia. Apart from the use of parameters in first-trimester aneuploidy screening, cell-free fetal DNA quantification is emerging as a promising marker for prediction of pre-eclampsia. This article reviews the current research of the most important strategies for prediction of pre-eclampsia, including the use of maternal risk factors, mean maternal arterial pressure, ultrasound parameters, and biomarkers. PMID:26247944

Potential and limits for rapid genetic adaptation to warming in a Great Barrier Reef coral.

PubMed

Matz, Mikhail V; Treml, Eric A; Aglyamova, Galina V; Bay, Line K

2018-04-01

Can genetic adaptation in reef-building corals keep pace with the current rate of sea surface warming? Here we combine population genomics, biophysical modeling, and evolutionary simulations to predict future adaptation of the common coral Acropora millepora on the Great Barrier Reef (GBR). Genomics-derived migration rates were high (0.1-1% of immigrants per generation across half the latitudinal range of the GBR) and closely matched the biophysical model of larval dispersal. Both genetic and biophysical models indicated the prevalence of southward migration along the GBR that would facilitate the spread of heat-tolerant alleles to higher latitudes as the climate warms. We developed an individual-based metapopulation model of polygenic adaptation and parameterized it with population sizes and migration rates derived from the genomic analysis. We find that high migration rates do not disrupt local thermal adaptation, and that the resulting standing genetic variation should be sufficient to fuel rapid region-wide adaptation of A. millepora populations to gradual warming over the next 20-50 coral generations (100-250 years). Further adaptation based on novel mutations might also be possible, but this depends on the currently unknown genetic parameters underlying coral thermal tolerance and the rate of warming realized. Despite this capacity for adaptation, our model predicts that coral populations would become increasingly sensitive to random thermal fluctuations such as ENSO cycles or heat waves, which corresponds well with the recent increase in frequency of catastrophic coral bleaching events.

Biophysical and physicochemical methods differentiate highly ligand-efficient human D-amino acid oxidase inhibitors.

PubMed

Lange, Jos H M; Venhorst, Jennifer; van Dongen, Maria J P; Frankena, Jurjen; Bassissi, Firas; de Bruin, Natasja M W J; den Besten, Cathaline; de Beer, Stephanie B A; Oostenbrink, Chris; Markova, Natalia; Kruse, Chris G

2011-10-01

Many early drug research efforts are too reductionist thereby not delivering key parameters such as kinetics and thermodynamics of target-ligand binding. A set of human D-Amino Acid Oxidase (DAAO) inhibitors 1-6 was applied to demonstrate the impact of key biophysical techniques and physicochemical methods in the differentiation of chemical entities that cannot be adequately distinguished on the basis of their normalized potency (ligand efficiency) values. The resulting biophysical and physicochemical data were related to relevant pharmacodynamic and pharmacokinetic properties. Surface Plasmon Resonance data indicated prolonged target-ligand residence times for 5 and 6 as compared to 1-4, based on the observed k(off) values. The Isothermal Titration Calorimetry-derived thermodynamic binding profiles of 1-6 to the DAAO enzyme revealed favorable contributions of both ΔH and ΔS to their ΔG values. Surprisingly, the thermodynamic binding profile of 3 elicited a substantially higher favorable contribution of ΔH to ΔG in comparison with the structurally closely related fused bicyclic acid 4. Molecular dynamics simulations and free energy calculations of 1, 3, and 4 led to novel insights into the thermodynamic properties of the binding process at an atomic level and in the different thermodynamic signatures of 3 and 4. The presented holistic approach is anticipated to facilitate the identification of compounds with best-in-class properties at an early research stage. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Melatonin reverses the enhanced oxidative damage to membrane lipids and improves skin biophysical characteristics in former-smokers - A study in postmenopausal women.

PubMed

Sagan, Dorota; Stepniak, Jan; Gesing, Adam; Lewinski, Andrzej; Karbownik-Lewinska, Malgorzata

2017-12-23

Protective antioxidative effects of melatonin have been repeatedly documented in experimental and clinical studies. One of the most spectacular exogenous prooxidative agents is cigarette smoking. The aim of the study was to evaluate the level of oxidative damage to membrane lipids (lipid peroxidation; LPO) in blood serum, and in epidermis exfoliated during microdermabrasion collected from former-smokers who were treated with melatonin. The study was performed in postmenopausal women. Ninety (90) female volunteers, aged 46-67 years, were enrolled. Two major groups, i.e. never-smokers (n=44) and former-smokers (n=46), were divided into: Control, melatonin topical skin application, Restructurer (containing antioxidants) topical skin application, and melatonin oral treatment. Microdermabrasion was performed at point '0', after 2 weeks, and after 4 weeks of treatment. The following parameters were measured: LPO in blood serum, LPO in epidermis exfoliated during microdermabrasion, and skin biophysical characteristics, such as sebum, moisture, elasticity, and pigmentation. Malondialdehyde+4-hydroxyalkenals level (LPO index) was measured spectrophotometrically. Melatonin oral treatment significantly reversed the increased serum LPO level in former-smokers already after 2 weeks of treatment. In a univariate regression model, LPO blood level constituted the only independent factor negatively associated with melatonin oral treatment. After 4 weeks of treatment, melatonin given orally increased skin sebum, moisture and elasticity levels, and melatonin applied topically increased sebum level. Exogenous melatonin reverses the enhanced oxidative damage to membrane lipids and improves skin biophysical characteristics in former-smokers.

Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data.

PubMed

Luo, Laiping; Zhai, Qiuping; Su, Yanjun; Ma, Qin; Kelly, Maggi; Guo, Qinghua

2018-05-14

Crown base height (CBH) is an essential tree biophysical parameter for many applications in forest management, forest fuel treatment, wildfire modeling, ecosystem modeling and global climate change studies. Accurate and automatic estimation of CBH for individual trees is still a challenging task. Airborne light detection and ranging (LiDAR) provides reliable and promising data for estimating CBH. Various methods have been developed to calculate CBH indirectly using regression-based means from airborne LiDAR data and field measurements. However, little attention has been paid to directly calculate CBH at the individual tree scale in mixed-species forests without field measurements. In this study, we propose a new method for directly estimating individual-tree CBH from airborne LiDAR data. Our method involves two main strategies: 1) removing noise and understory vegetation for each tree; and 2) estimating CBH by generating percentile ranking profile for each tree and using a spline curve to identify its inflection points. These two strategies lend our method the advantages of no requirement of field measurements and being efficient and effective in mixed-species forests. The proposed method was applied to a mixed conifer forest in the Sierra Nevada, California and was validated by field measurements. The results showed that our method can directly estimate CBH at individual tree level with a root-mean-squared error of 1.62 m, a coefficient of determination of 0.88 and a relative bias of 3.36%. Furthermore, we systematically analyzed the accuracies among different height groups and tree species by comparing with field measurements. Our results implied that taller trees had relatively higher uncertainties than shorter trees. Our findings also show that the accuracy for CBH estimation was the highest for black oak trees, with an RMSE of 0.52 m. The conifer species results were also good with uniformly high R 2 ranging from 0.82 to 0.93. In general, our method has demonstrated high accuracy for individual tree CBH estimation and strong potential for applications in mixed species over large areas.

A comparison of surface biophysical properties and remotely sensed variables from FIFE

NASA Technical Reports Server (NTRS)

Sellers, Piers; Heiser, Mark; Walthall, C. W.; Huemmrich, F.; Strebel, D. E.; Hall, F. G.

1990-01-01

A method for calculating surface energy balances is investigated which incorporates the vegetation index and/or other indicators of surface conductance at visible and near-IR channels. Data from the Konza Prairie are employed to confirm the hypothesized relationship between maximum canopy conductance and the observed simple-ratio vegetation index. The relationship is established, but more data regarding soil-surface contributions are required to estimate the total surface conductance to evapotranspiration.

Differentiating aquatic plant communities in a eutrophic river using hyperspectral and multispectral remote sensing

USGS Publications Warehouse

Tian, Y.Q.; Yu, Q.; Zimmerman, M.J.; Flint, S.; Waldron, M.C.

2010-01-01

This study evaluates the efficacy of remote sensing technology to monitor species composition, areal extent and density of aquatic plants (macrophytes and filamentous algae) in impoundments where their presence may violate water-quality standards. Multispectral satellite (IKONOS) images and more than 500 in situ hyperspectral samples were acquired to map aquatic plant distributions. By analyzing field measurements, we created a library of hyperspectral signatures for a variety of aquatic plant species, associations and densities. We also used three vegetation indices. Normalized Difference Vegetation Index (NDVI), near-infrared (NIR)-Green Angle Index (NGAI) and normalized water absorption depth (DH), at wavelengths 554, 680, 820 and 977 nm to differentiate among aquatic plant species composition, areal density and thickness in cases where hyperspectral analysis yielded potentially ambiguous interpretations. We compared the NDVI derived from IKONOS imagery with the in situ, hyperspectral-derived NDVI. The IKONOS-based images were also compared to data obtained through routine visual observations. Our results confirmed that aquatic species composition alters spectral signatures and affects the accuracy of remote sensing of aquatic plant density. The results also demonstrated that the NGAI has apparent advantages in estimating density over the NDVI and the DH. In the feature space of the three indices, 3D scatter plot analysis revealed that hyperspectral data can differentiate several aquatic plant associations. High-resolution multispectral imagery provided useful information to distinguish among biophysical aquatic plant characteristics. Classification analysis indicated that using satellite imagery to assess Lemna coverage yielded an overall agreement of 79% with visual observations and >90% agreement for the densest aquatic plant coverages. Interpretation of biophysical parameters derived from high-resolution satellite or airborne imagery should prove to be a valuable approach for assessing the effectiveness of management practices for controlling aquatic plant growth in inland waters, as well as for routine monitoring of aquatic plants in lakes and suitable lentic environments. ?? 2010 Blackwell Publishing Ltd.

Visualizing the ill-posedness of the inversion of a canopy radiative transfer model: A case study for Sentinel-2

NASA Astrophysics Data System (ADS)

Zurita-Milla, R.; Laurent, V. C. E.; van Gijsel, J. A. E.

2015-12-01

Monitoring biophysical and biochemical vegetation variables in space and time is key to understand the earth system. Operational approaches using remote sensing imagery rely on the inversion of radiative transfer models, which describe the interactions between light and vegetation canopies. The inversion required to estimate vegetation variables is, however, an ill-posed problem because of variable compensation effects that can cause different combinations of soil and canopy variables to yield extremely similar spectral responses. In this contribution, we present a novel approach to visualise the ill-posed problem using self-organizing maps (SOM), which are a type of unsupervised neural network. The approach is demonstrated with simulations for Sentinel-2 data (13 bands) made with the Soil-Leaf-Canopy (SLC) radiative transfer model. A look-up table of 100,000 entries was built by randomly sampling 14 SLC model input variables between their minimum and maximum allowed values while using both a dark and a bright soil. The Sentinel-2 spectral simulations were used to train a SOM of 200 × 125 neurons. The training projected similar spectral signatures onto either the same, or contiguous, neuron(s). Tracing back the inputs that generated each spectral signature, we created a 200 × 125 map for each of the SLC variables. The lack of spatial patterns and the variability in these maps indicate ill-posed situations, where similar spectral signatures correspond to different canopy variables. For Sentinel-2, our results showed that leaf area index, crown cover and leaf chlorophyll, water and brown pigment content are less confused in the inversion than variables with noisier maps like fraction of brown canopy area, leaf dry matter content and the PROSPECT mesophyll parameter. This study supports both educational and on-going research activities on inversion algorithms and might be useful to evaluate the uncertainties of retrieved canopy biophysical and biochemical state variables.

Modeling Coniferous Canopy Structure over Extensive Areas for Ray Tracing Simulations: Scaling from the Leaf to the Stand Level

NASA Astrophysics Data System (ADS)

van Aardt, J. A.; van Leeuwen, M.; Kelbe, D.; Kampe, T.; Krause, K.

2015-12-01

Remote sensing is widely accepted as a useful technology for characterizing the Earth surface in an objective, reproducible, and economically feasible manner. To date, the calibration and validation of remote sensing data sets and biophysical parameter estimates remain challenging due to the requirements to sample large areas for ground-truth data collection, and restrictions to sample these data within narrow temporal windows centered around flight campaigns or satellite overpasses. The computer graphics community have taken significant steps to ameliorate some of these challenges by providing an ability to generate synthetic images based on geometrically and optically realistic representations of complex targets and imaging instruments. These synthetic data can be used for conceptual and diagnostic tests of instrumentation prior to sensor deployment or to examine linkages between biophysical characteristics of the Earth surface and at-sensor radiance. In the last two decades, the use of image generation techniques for remote sensing of the vegetated environment has evolved from the simulation of simple homogeneous, hypothetical vegetation canopies, to advanced scenes and renderings with a high degree of photo-realism. Reported virtual scenes comprise up to 100M surface facets; however, due to the tighter coupling between hardware and software development, the full potential of image generation techniques for forestry applications yet remains to be fully explored. In this presentation, we examine the potential computer graphics techniques have for the analysis of forest structure-function relationships and demonstrate techniques that provide for the modeling of extremely high-faceted virtual forest canopies, comprising billions of scene elements. We demonstrate the use of ray tracing simulations for the analysis of gap size distributions and characterization of foliage clumping within spatial footprints that allow for a tight matching between characteristics derived from these virtual scenes and typical pixel resolutions of remote sensing imagery.

Thermal Transients Excite Neurons through Universal Intramembrane Mechanoelectrical Effects

NASA Astrophysics Data System (ADS)

Plaksin, Michael; Shapira, Einat; Kimmel, Eitan; Shoham, Shy

2018-01-01

Modern advances in neurotechnology rely on effectively harnessing physical tools and insights towards remote neural control, thereby creating major new scientific and therapeutic opportunities. Specifically, rapid temperature pulses were shown to increase membrane capacitance, causing capacitive currents that explain neural excitation, but the underlying biophysics is not well understood. Here, we show that an intramembrane thermal-mechanical effect wherein the phospholipid bilayer undergoes axial narrowing and lateral expansion accurately predicts a potentially universal thermal capacitance increase rate of ˜0.3 % /°C . This capacitance increase and concurrent changes in the surface charge related fields lead to predictable exciting ionic displacement currents. The new MechanoElectrical Thermal Activation theory's predictions provide an excellent agreement with multiple experimental results and indirect estimates of latent biophysical quantities. Our results further highlight the role of electro-mechanics in neural excitation; they may also help illuminate subthreshold and novel physical cellular effects, and could potentially lead to advanced new methods for neural control.

Bidirectional Reflectance Modeling of Non-homogeneous Plant Canopies

NASA Technical Reports Server (NTRS)

Norman, J. M. (Principal Investigator)

1985-01-01

The objective of this research is to develop a 3-dimensional radiative transfer model for predicting the bidirectional reflectance distribution function (BRDF) for heterogeneous vegetation canopies. The model (named BIGAR) considers the angular distribution of leaves, leaf area index, the location and size of individual subcanopies such as widely spaced rows or trees, spectral and directional properties of leaves, multiple scattering, solar position and sky condition, and characteristics of the soil. The model relates canopy biophysical attributes to down-looking radiation measurements for nadir and off-nadir viewing angles. Therefore, inversion of this model, which is difficult but practical should provide surface biophysical pattern; a fundamental goal of remote sensing. Such a model also will help to evaluate atmospheric limitations to satellite remote sensing by providing a good surface boundary condition for many different kinds of canopies. Furthermore, this model can relate estimates of nadir reflectance, which is approximated by most satellites, to hemispherical reflectance, which is necessary in the energy budget of vegetated surfaces.

The role of emissivity during the cooling of a body: an experimental design for a laboratory classroom

NASA Astrophysics Data System (ADS)

Jiménez-Muñoz, J. C.; Sobrino, J. A.; Sòria, G.; Delegido, J.; Bañauls, S.

2017-01-01

Mechanisms of heat transfer and Newton’s law of cooling are introduced in the first physics and biophysics courses for a number of university science majors. Several papers have commented on the derivation of the exponential decay and validity of this law. However, the description of the phenomena is traditionally described without consideration of basic factors that contribute to the cooling rate of a body. One of these key factors is the emissivity of the body, which requires specific instrumentation to be measured. In particular, we present in this paper an experiment to record the cooling temperatures of an avian egg by means of a thermal camera. The objective is to comment on the dependence of the cooling process on emissivity, and then propose a methodology for estimating the emissivity of the cooling object. The method can be applied a priori to other bodies and is suitable for a biophysics laboratory classroom in higher education.

Building biophysics in mid-century China: the University of Science and Technology of China.

PubMed

Luk, Yi Lai Christine

2015-01-01

Biophysics has been either an independent discipline or an element of another discipline in the United States, but it has always been recognized as a stand-alone discipline in the People's Republic of China (PRC) since 1949. To inquire into this apparent divergence, this paper investigates the formational history of biophysics in China by examining the early institutional history of one of the best-known and prestigious science and technology universities in the PRC, the University of Science and Technology of China (USTC). By showing how the university and its biophysics program co-evolved with national priorities from the school's founding in 1958 to the eve of the Cultural Revolution in 1966, the purpose of this paper is to assess the development of a scientific discipline in the context of national demands and institutional politics. Specific materials for analysis include the school's admission policies, curricula, students' dissertations, and research program. To further contextualize the institutional setting of Chinese biophysics, this paper begins with a general history of proto-biophysical institutions in China during the Nationalist-Communist transitional years. This paper could be of interest to historians wanting to know more about the origin of the biophysics profession in China, and in particular how research areas that constitute biophysics changed in tandem with socio-political contingencies.

Historical and Critical Review on Biophysical Economics

NASA Astrophysics Data System (ADS)

Adigüzel, Yekbun

2016-07-01

Biophysical economics is initiated with the long history of the relation of economics with ecological basis and biophysical perspectives of the physiocrats. It inherently has social, economic, biological, environmental, natural, physical, and scientific grounds. Biological entities in economy like the resources, consumers, populations, and parts of production systems, etc. could all be dealt by biophysical economics. Considering this wide scope, current work is a “biophysical economics at a glance” rather than a comprehensive review of the full range of topics that may just be adequately covered in a book-length work. However, the sense of its wide range of applications is aimed to be provided to the reader in this work. Here, modern approaches and biophysical growth theory are presented after the long history and an overview of the concepts in biophysical economics. Examples of the recent studies are provided at the end with discussions. This review is also related to the work by Cleveland, “Biophysical Economics: From Physiocracy to Ecological Economics and Industrial Ecology” [C. J. Cleveland, in Advances in Bioeconomics and Sustainability: Essay in Honor of Nicholas Gerogescu-Roegen, eds. J. Gowdy and K. Mayumi (Edward Elgar Publishing, Cheltenham, England, 1999), pp. 125-154.]. Relevant parts include critics and comments on the presented concepts in a parallelized fashion with the Cleveland’s work.

A simple method for characterizing passive and active neuronal properties: application to striatal neurons.

PubMed

Lepora, Nathan F; Blomeley, Craig P; Hoyland, Darren; Bracci, Enrico; Overton, Paul G; Gurney, Kevin

2011-11-01

The study of active and passive neuronal dynamics usually relies on a sophisticated array of electrophysiological, staining and pharmacological techniques. We describe here a simple complementary method that recovers many findings of these more complex methods but relies only on a basic patch-clamp recording approach. Somatic short and long current pulses were applied in vitro to striatal medium spiny (MS) and fast spiking (FS) neurons from juvenile rats. The passive dynamics were quantified by fitting two-compartment models to the short current pulse data. Lumped conductances for the active dynamics were then found by compensating this fitted passive dynamics within the current-voltage relationship from the long current pulse data. These estimated passive and active properties were consistent with previous more complex estimations of the neuron properties, supporting the approach. Relationships within the MS and FS neuron types were also evident, including a graduation of MS neuron properties consistent with recent findings about D1 and D2 dopamine receptor expression. Application of the method to simulated neuron data supported the hypothesis that it gives reasonable estimates of membrane properties and gross morphology. Therefore detailed information about the biophysics can be gained from this simple approach, which is useful for both classification of neuron type and biophysical modelling. Furthermore, because these methods rely upon no manipulations to the cell other than patch clamping, they are ideally suited to in vivo electrophysiology. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

In vivo evaluation of some biophysical parameters of the facial skin of Indian subjects living in Mumbai. Part II: Variability with age and gender.

PubMed

Colomb, L; Flament, F; Wagle, A; Idelcaid, Y; Agrawal, D

2018-04-01

A previously published work explored the diversity of some biophysical parameters (colour, elasticity, sebum production, skin microrelief, etc.) of the skin of 1204 Indian women, differently aged, living in four Indian cities (Chennai, Delhi, Kolkata and Mumbai). The present work aimed at completing such research by focusing on possible gender-related differences in the same skin parameters, between Indian men and women living in the same Indian city (Mumbai). A total of 297 Indian men, differently aged (18-70y), were recruited in Mumbai, completing the panel of 303 women who were previously recruited in this same city. The same instrumental measurements of facial skin colour and its homogeneity, its mechanical properties, the sebum production, skin pores size, skin relief, etc. as in the previous work, were conducted. Overall, the facial skin colour shows a darker complexion in men as compared to women, on forehead, ocular region, lips, chin and cheek. The skin colour unevenness, which increases with age, was found higher in men, as compared to women. At comparable age, women and men present a same density of skin pores, whereas those of men appear larger, up to 55y. The deepness of Crow's feet wrinkles does not significantly differ between genders. A lesser extensibility was found on the cheeks of men. In men, the sebum production was found significantly higher than that of women at ages above 40y. This work indicates some commonly shared age-related skin features between women and men from Mumbai, despite slight different characteristics such as skin pigmentation, forehead/cheek colour contrast, mechanical properties and sebum production. © 2018 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Molecular and Cellular Biophysics

NASA Astrophysics Data System (ADS)

Jackson, Meyer B.

2006-01-01

Molecular and Cellular Biophysics provides advanced undergraduate and graduate students with a foundation in the basic concepts of biophysics. Students who have taken physical chemistry and calculus courses will find this book an accessible and valuable aid in learning how these concepts can be used in biological research. The text provides a rigorous treatment of the fundamental theories in biophysics and illustrates their application with examples. Conformational transitions of proteins are studied first using thermodynamics, and subsequently with kinetics. Allosteric theory is developed as the synthesis of conformational transitions and association reactions. Basic ideas of thermodynamics and kinetics are applied to topics such as protein folding, enzyme catalysis and ion channel permeation. These concepts are then used as the building blocks in a treatment of membrane excitability. Through these examples, students will gain an understanding of the general importance and broad applicability of biophysical principles to biological problems. Offers a unique synthesis of concepts across a wide range of biophysical topics Provides a rigorous theoretical treatment, alongside applications in biological systems Author has been teaching biophysics for nearly 25 years

Interaction of silicon nanoparticles with the molecules of bovine serum albumin in aqueous solutions

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

Anenkova, K A; Sergeeva, I A; Petrova, G P

2011-05-31

Using the method of photon-correlation spectroscopy, the coefficient of translational diffusion D{sub t} and the hydrodynamic radius R of the particles in aqueous solutions of the bovine serum albumin, containing silicon nanoparticles, are determined. The character of the dependence of these parameters on the concentration of the protein indicates the absence of interaction between the studied particles in the chosen range of albumin concentrations 0.2 - 1.0 mg mL{sup -1}. (optical technologies in biophysics and medicine)

Digital holographic microscopy for toxicity testing and cell culture quality control

NASA Astrophysics Data System (ADS)

Kemper, Björn

2018-02-01

For the example of digital holographic microscopy (DHM), it is illustrated how label-free biophysical parameter sets can be extracted from quantitative phase images of adherent and suspended cells, and how the retrieved data can be applied for in-vitro toxicity testing and cell culture quality assessment. This includes results from the quantification of the reactions of cells to toxic substances as well as data from sophisticated monitoring of cell alterations that are related to changes of cell culture conditions.

BOREAS Level-0 ER-2 Daedalus TMS Imagery Digital Counts in BIL Format

NASA Technical Reports Server (NTRS)

Newcomer, Jeffrey A.; Dominguez, Roseanne; Hall, Forrest G. (Editor)

2000-01-01

The level-0 Daedalus Thematic Mapper Simulator (TMS) imagery, along with the other remotely sensed images, was collected to provide spatially extensive information about radiant energy over the primary BOReal Ecosystem-Atmosphere Study (BOREAS) study areas. This information includes detailed land cover and biophysical parameter maps such as fraction of Photosynthetically Active Radiation (fPAR) and Leaf Area Index (LAI). Two flights of the Daedalus TMS instrument were made onboard the ER-2 aircraft on 16-Sep-1994 and 17-Sep-1994.

Vegetation Monitoring with Gaussian Processes and Latent Force Models

NASA Astrophysics Data System (ADS)

Camps-Valls, Gustau; Svendsen, Daniel; Martino, Luca; Campos, Manuel; Luengo, David

2017-04-01

Monitoring vegetation by biophysical parameter retrieval from Earth observation data is a challenging problem, where machine learning is currently a key player. Neural networks, kernel methods, and Gaussian Process (GP) regression have excelled in parameter retrieval tasks at both local and global scales. GP regression is based on solid Bayesian statistics, yield efficient and accurate parameter estimates, and provides interesting advantages over competing machine learning approaches such as confidence intervals. However, GP models are hampered by lack of interpretability, that prevented the widespread adoption by a larger community. In this presentation we will summarize some of our latest developments to address this issue. We will review the main characteristics of GPs and their advantages in vegetation monitoring standard applications. Then, three advanced GP models will be introduced. First, we will derive sensitivity maps for the GP predictive function that allows us to obtain feature ranking from the model and to assess the influence of examples in the solution. Second, we will introduce a Joint GP (JGP) model that combines in situ measurements and simulated radiative transfer data in a single GP model. The JGP regression provides more sensible confidence intervals for the predictions, respects the physics of the underlying processes, and allows for transferability across time and space. Finally, a latent force model (LFM) for GP modeling that encodes ordinary differential equations to blend data-driven modeling and physical models of the system is presented. The LFM performs multi-output regression, adapts to the signal characteristics, is able to cope with missing data in the time series, and provides explicit latent functions that allow system analysis and evaluation. Empirical evidence of the performance of these models will be presented through illustrative examples.

Using the ARTMO toolbox for automated retrieval of biophysical parameters through radiative transfer model inversion: Optimizing LUT-based inversion

NASA Astrophysics Data System (ADS)

Verrelst, J.; Rivera, J. P.; Leonenko, G.; Alonso, L.; Moreno, J.

2012-04-01

Radiative transfer (RT) modeling plays a key role for earth observation (EO) because it is needed to design EO instruments and to develop and test inversion algorithms. The inversion of a RT model is considered as a successful approach for the retrieval of biophysical parameters because of being physically-based and generally applicable. However, to the broader community this approach is considered as laborious because of its many processing steps and expert knowledge is required to realize precise model parameterization. We have recently developed a radiative transfer toolbox ARTMO (Automated Radiative Transfer Models Operator) with the purpose of providing in a graphical user interface (GUI) essential models and tools required for terrestrial EO applications such as model inversion. In short, the toolbox allows the user: i) to choose between various plant leaf and canopy RT models (e.g. models from the PROSPECT and SAIL family, FLIGHT), ii) to choose between spectral band settings of various air- and space-borne sensors or defining own sensor settings, iii) to simulate a massive amount of spectra based on a look up table (LUT) approach and storing it in a relational database, iv) to plot spectra of multiple models and compare them with measured spectra, and finally, v) to run model inversion against optical imagery given several cost options and accuracy estimates. In this work ARTMO was used to tackle some well-known problems related to model inversion. According to Hadamard conditions, mathematical models of physical phenomena are mathematically invertible if the solution of the inverse problem to be solved exists, is unique and depends continuously on data. This assumption is not always met because of the large number of unknowns and different strategies have been proposed to overcome this problem. Several of these strategies have been implemented in ARTMO and were here analyzed to optimize the inversion performance. Data came from the SPARC-2003 dataset, which was acquired on the agricultural test site Barrax, Spain. LUTs were created using the 4SAIL and FLIGHT models and were inverted against CHRIS data in order to retrieve maps of chlorophyll content (chl) and leaf area index (LAI). The following inversion steps have been optimized: 1. Cost function. The performances of about 50 different cost functions (i.e. minimum distance functions) were compared. Remarkably, in none of the studied cases the widely used root mean square error (RMSE) led to most accurate results. Depending on the retrieved parameter, more successful functions were: 'Sharma and Mittal', 'Shannońs entropy', 'Hellinger distance', 'Pearsońs chi-square'. 2. Gaussian noise. Earth observation data typically encompass a certain degree of noise due to errors related to radiometric and geometric processing. In all cases, adding 5% Gaussian noise to the simulated spectra led to more accurate retrievals as compared to without noise. 3. Average of multiple best solutions. Because multiple parameter combinations may lead to the same spectra, a way to overcome this problem is not searching for the top best match but for a percentage of best matches. Optimized retrievals were encountered when including an average of 7% (Chl) to 10% (LAI) top best matches. 4. Integration of estimates. The option is provided to integrate estimates of biochemical contents at the canopy level (e.g., total chlorophyll: Chl × LAI, or water: Cw × LAI), which can lead to increased robustness and accuracy. 5. Class-based inversion. This option is probably ARTMÓs most powerful feature as it allows model parameterization depending on the imagés land cover classes (e.g. different soil or vegetation types). Class-based inversion can lead to considerably improved accuracies compared to one generic class. Results suggest that 4SAIL and FLIGHT performed alike for Chl but not for LAI. While both models rely on the leaf model PROSPECT for Chl retrieval, their different nature (e.g. numerical vs. ray tracing) may cause that retrieval of structural parameters such as LAI differ. Finally, it should be noted that the whole analysis can be intuitively performed by the toolbox. ARTMO is freely available to the EO community for further development. Expressions of interest are welcome and should be directed to the corresponding author.

Data bank of optical properties of biological tissue and blood in the visible and near infrared spectral region

NASA Astrophysics Data System (ADS)

Khairullina, Alphiya Y.; Bui, Lilia; Oleinik, Tatiana V.; Artishevsky, Nelli; Prigoun, Natalia; Sevkovsky, Jakov; Mokhort, Tatiana

1996-12-01

The data bank contains optical, ordinary biochemical and biophysical information on 120 venous blood samples of donors, healthy persons, patients with high pathology, 60 tissue samples. The optical parameters include diffuse reflection R((lambda) ) and transmission T((lambda) ) coefficients for optically thick layers, the absorption K((lambda) ) and extinction (epsilon) ((lambda) ) spectra, oxygenation degree CO2, parameter p determined by sizes and shapes of cells and their aggregates, refractive index of a disperse phase relative to surrounding media, and cooperative effects at high relative concentration. The peculiarities in absorption K((lambda) spectra are connected with different pathologies. It is shown from K((lambda) ) that the grade of pathology connected with the concentration of hemoglobin and mithohondrion together with oxygenation degree of blood and tissues, with the pathological hemoglobin's forms and its decomposition products of different levels. Parameter p is an important diagnostic parameter. We consider that it is necessary to include the oxygenation degree and erythrocyte's aggregation parameter to extend the range of common diagnostic parameters of blood by the first rota.

Landscape Variation in Tree Species Richness in Northern Iran Forests

PubMed Central

Bourque, Charles P.-A.; Bayat, Mahmoud

2015-01-01

Mapping landscape variation in tree species richness (SR) is essential to the long term management and conservation of forest ecosystems. The current study examines the prospect of mapping field assessments of SR in a high-elevation, deciduous forest in northern Iran as a function of 16 biophysical variables representative of the area’s unique physiography, including topography and coastal placement, biophysical environment, and forests. Basic to this study is the development of moderate-resolution biophysical surfaces and associated plot-estimates for 202 permanent sampling plots. The biophysical variables include: (i) three topographic variables generated directly from the area’s digital terrain model; (ii) four ecophysiologically-relevant variables derived from process models or from first principles; and (iii) seven variables of Landsat-8-acquired surface reflectance and two, of surface radiance. With symbolic regression, it was shown that only four of the 16 variables were needed to explain 85% of observed plot-level variation in SR (i.e., wind velocity, surface reflectance of blue light, and topographic wetness indices representative of soil water content), yielding mean-absolute and root-mean-squared error of 0.50 and 0.78, respectively. Overall, localised calculations of wind velocity and surface reflectance of blue light explained about 63% of observed variation in SR, with wind velocity accounting for 51% of that variation. The remaining 22% was explained by linear combinations of soil-water-related topographic indices and associated thresholds. In general, SR and diversity tended to be greatest for plots dominated by Carpinus betulus (involving ≥ 33% of all trees in a plot), than by Fagus orientalis (median difference of one species). This study provides a significant step towards describing landscape variation in SR as a function of modelled and satellite-based information and symbolic regression. Methods in this study are sufficiently general to be applicable to the characterisation of SR in other forested regions of the world, providing plot-scale data are available for model generation. PMID:25849029

Landscape variation in tree species richness in northern Iran forests.

PubMed

Bourque, Charles P-A; Bayat, Mahmoud

2015-01-01

Mapping landscape variation in tree species richness (SR) is essential to the long term management and conservation of forest ecosystems. The current study examines the prospect of mapping field assessments of SR in a high-elevation, deciduous forest in northern Iran as a function of 16 biophysical variables representative of the area's unique physiography, including topography and coastal placement, biophysical environment, and forests. Basic to this study is the development of moderate-resolution biophysical surfaces and associated plot-estimates for 202 permanent sampling plots. The biophysical variables include: (i) three topographic variables generated directly from the area's digital terrain model; (ii) four ecophysiologically-relevant variables derived from process models or from first principles; and (iii) seven variables of Landsat-8-acquired surface reflectance and two, of surface radiance. With symbolic regression, it was shown that only four of the 16 variables were needed to explain 85% of observed plot-level variation in SR (i.e., wind velocity, surface reflectance of blue light, and topographic wetness indices representative of soil water content), yielding mean-absolute and root-mean-squared error of 0.50 and 0.78, respectively. Overall, localised calculations of wind velocity and surface reflectance of blue light explained about 63% of observed variation in SR, with wind velocity accounting for 51% of that variation. The remaining 22% was explained by linear combinations of soil-water-related topographic indices and associated thresholds. In general, SR and diversity tended to be greatest for plots dominated by Carpinus betulus (involving ≥ 33% of all trees in a plot), than by Fagus orientalis (median difference of one species). This study provides a significant step towards describing landscape variation in SR as a function of modelled and satellite-based information and symbolic regression. Methods in this study are sufficiently general to be applicable to the characterisation of SR in other forested regions of the world, providing plot-scale data are available for model generation.

Raman spectroscopy of human skin: looking for a quantitative algorithm to reliably estimate human age

NASA Astrophysics Data System (ADS)

Pezzotti, Giuseppe; Boffelli, Marco; Miyamori, Daisuke; Uemura, Takeshi; Marunaka, Yoshinori; Zhu, Wenliang; Ikegaya, Hiroshi

2015-06-01

The possibility of examining soft tissues by Raman spectroscopy is challenged in an attempt to probe human age for the changes in biochemical composition of skin that accompany aging. We present a proof-of-concept report for explicating the biophysical links between vibrational characteristics and the specific compositional and chemical changes associated with aging. The actual existence of such links is then phenomenologically proved. In an attempt to foster the basics for a quantitative use of Raman spectroscopy in assessing aging from human skin samples, a precise spectral deconvolution is performed as a function of donors' ages on five cadaveric samples, which emphasizes the physical significance and the morphological modifications of the Raman bands. The outputs suggest the presence of spectral markers for age identification from skin samples. Some of them appeared as authentic "biological clocks" for the apparent exactness with which they are related to age. Our spectroscopic approach yields clear compositional information of protein folding and crystallization of lipid structures, which can lead to a precise identification of age from infants to adults. Once statistically validated, these parameters might be used to link vibrational aspects at the molecular scale for practical forensic purposes.

Spectrophotometric Method for Differentiation of Human Skin Melanoma. I. Optical Diffuse Reflection Coefficient

NASA Astrophysics Data System (ADS)

Petruk, V. G.; Ivanov, A. P.; Kvaternyuk, S. M.; Barun, V. V.

2016-03-01

We have designed an experimental setup, based on two integrating spheres, that lets us measure the optical diffuse reflectance spectra (diffuse reflection coefficient vs. wavelength) of human skin quickly under clinical conditions in vivo. For the wavelength interval 520-1100 nm, we give the values of the diffuse reflection coefficient for healthy tissue, skin with a benign nevus, and skin with a malignant melanoma for a large group of test subjects. We experimentally established a number of wavelengths in the red-near IR region of the spectrum which can be used for early differential diagnosis of nevi and melanoma in patient cancer screening. According to the Kramer-Welch test, the probability of the diffuse reflection coefficient for skin with melanoma and a nevus having different distributions is >0.94, and at many wavelengths it is >0.999. By solving the inverse problem, we estimated the changes in a number of structural and biophysical parameters of the tissue on going from healthy skin to nevus and melanoma. The results obtained can provide a basis for developing a clinical approach to identifying the risk of malignant transformation of the skin before surgery and histological analysis of the tissue.

An Experimental Determination of Static Magnetic Fields Induced Noise in Living Systems

NASA Astrophysics Data System (ADS)

Brady, Megan; Laramee, Craig

2013-03-01

Living systems are constantly exposed to static magnetic fields (SMFs) from both natural and man-made sources. Exposures vary in dose and duration ranging from geomagnetic (~50 μT) to residential and industrial (~10s of mT) fields. Efforts to characterize responses to SMFs have yielded conflicting results, showing a dependence on experimental variables used. Here we argue that low to moderate SMF exposure is a sub-threshold perturbation operating below thermal noise, and assays that evaluate statistical characteristics of a single cell may identify responses not consistently found by population averaging approaches. Recent studies of gene expression show that it is a stochastic process capable of producing bursting dynamics. Moreover, theoretical and experimental methods have also been developed to allow quantitative estimates of the associated biophysical parameters. These developments provide a new way to assess responses of living systems to SMFs. In this work, we report on our efforts to use single molecule fluorescence in situ hybridization to assess responses of NIH-3T3 cells to SMF exposure at flux densities ranging from 1 to 440 mT for 48 hours. Results will contribute to determining mechanisms by which SMF exposure influences gene expression.

Fluorescence correlation spectroscopy experiments to quantify free diffusion coefficients in reaction-diffusion systems: The case of Ca2 + and its dyes

NASA Astrophysics Data System (ADS)

Sigaut, Lorena; Villarruel, Cecilia; Ponce, María Laura; Ponce Dawson, Silvina

2017-06-01

Many cell signaling pathways involve the diffusion of messengers that bind and unbind to and from intracellular components. Quantifying their net transport rate under different conditions then requires having separate estimates of their free diffusion coefficient and binding or unbinding rates. In this paper, we show how performing sets of fluorescence correlation spectroscopy (FCS) experiments under different conditions, it is possible to quantify free diffusion coefficients and on and off rates of reaction-diffusion systems. We develop the theory and present a practical implementation for the case of the universal second messenger, calcium (Ca2 +) and single-wavelength dyes that increase their fluorescence upon Ca2 + binding. We validate the approach with experiments performed in aqueous solutions containing Ca2 + and Fluo4 dextran (both in its high and low affinity versions). Performing FCS experiments with tetramethylrhodamine-dextran in Xenopus laevis oocytes, we infer the corresponding free diffusion coefficients in the cytosol of these cells. Our approach can be extended to other physiologically relevant reaction-diffusion systems to quantify biophysical parameters that determine the dynamics of various variables of interest.

Estimating Indirect Emissions from Land Use Change Due to Biofuels (Invited)

NASA Astrophysics Data System (ADS)

Reilly, J. M.

2010-12-01

Interest in biofuels as an alternative fuel has led to the realization that they may not be a viable low greenhouse gas alternative, even if process emissions are low, because expansions of land area in biomass crops may lead to forest destruction and hence carbon emissions.(1,2)If the concern was only direct land use effects—changes in carbon stocks on land directly used for biomass—direct measurement would be an option. However, agricultural economists recognize that if biofuels are produced from crops grown on existing cropland the crops previously grown there will likely be replaced by production elsewhere. Given international markets in agricultural products a diversion of land or part of the corn crop in the US for biofuels would result in higher market prices for corn and other crops, and thus spur land conversion almost anywhere around the world. There have now been a number of estimates of the potential land use emissions, and those estimates vary widely and are sensitive to key parameters of both the economic models used in the analysis and the representation of biophysical processes.(3,4,5)Among the important parameters are those that describe the willingness to convert unmanaged land, the ability to intensify production on existing land, the productivity of new land coming to production compared to existing cropland, demand elasticities for agricultural products, and the representation of carbon and nitrogen cycles and storage.(6,7) 1. J. Fargione, J. et al., Science 319, 1235 (2008). 2. T. Searchinger, T et al., Science 319, 1238 (2008) 3. J.M. Melillo, Science, 326: 1397-1399 (2009) 4. M. Wise et al., Science 324, 1183 (2009). 5. W. E. Tyner, et al., Land Use Changes and Consequent CO2 Emissions due to US Corn Ethanol Production: A Comprehensive Analysis, Department of Agricultural Economics, Purdue University (July 2010). 6. T. W. Hertel, The Global Supply and Demand for Agricultural Land in 2050: A Perfect Storm in the Making? AAEA Presidential Address , Purdue University 7. Melillo, et al., op cit

Estimation of evapotranspiration for different land covers in a Brazilian semi-arid region: A case study of the Brígida River basin, Brazil

NASA Astrophysics Data System (ADS)

Santos, Celso Augusto Guimarães; Silva, Richarde Marques da; Silva, Alexandro Medeiros; Brasil Neto, Reginaldo Moura

2017-03-01

In this study, the Surface Energy Balance Algorithm for Land (SEBAL) was used to compute the surface albedo, vegetation indices (NDVI, SAVI and LAI), surface temperature, soil heat flux and evapotranspiration (ET) over two contrasting years (dry and wet) in the Brígida River basin, a semi-arid region of north-eastern Brazil. The actual ET was computed during satellite overpass and was integrated for 24 h on a pixel-by-pixel basis for the daily ET distribution. Due to the topographic effects, an attempt was also made to incorporate DEM information to estimate the net radiation. The land cover types identified in the watershed are cropland, bare land, dense canopy, grassland, and caatinga vegetation. In order to study the variation among the biophysical parameters and ET, two-way analysis of variance (ANOVA) was used. The ET calculated by SEBAL ranged between 2.46 and 6.87 mm/day for the dry year (1990) and 1.31 and 6.84 mm/day for the wet year (2009) for the river basin. The results showed that a reduction in vegetation cover is evident in the temporal and spatial analysis over the studied periods in the region and that these facts influence the values of the energy balance and ET. The results showed significant differences in the variables of land cover type and year at the probability level of 0.05 for all land cover types.

Climate Change Effects on Agriculture: Economic Responses to Biophysical Shocks

NASA Technical Reports Server (NTRS)

Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlik, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina

2014-01-01

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(sup 2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Climate change effects on agriculture: Economic responses to biophysical shocks

PubMed Central

Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d’Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-01-01

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. PMID:24344285

Climate change effects on agriculture: economic responses to biophysical shocks.

PubMed

Nelson, Gerald C; Valin, Hugo; Sands, Ronald D; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d'Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-03-04

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

A regression approach to the mapping of bio-physical characteristics of surface sediment using in situ and airborne hyperspectral acquisitions

NASA Astrophysics Data System (ADS)

Ibrahim, Elsy; Kim, Wonkook; Crawford, Melba; Monbaliu, Jaak

2017-02-01

Remote sensing has been successfully utilized to distinguish and quantify sediment properties in the intertidal environment. Classification approaches of imagery are popular and powerful yet can lead to site- and case-specific results. Such specificity creates challenges for temporal studies. Thus, this paper investigates the use of regression models to quantify sediment properties instead of classifying them. Two regression approaches, namely multiple regression (MR) and support vector regression (SVR), are used in this study for the retrieval of bio-physical variables of intertidal surface sediment of the IJzermonding, a Belgian nature reserve. In the regression analysis, mud content, chlorophyll a concentration, organic matter content, and soil moisture are estimated using radiometric variables of two airborne sensors, namely airborne hyperspectral sensor (AHS) and airborne prism experiment (APEX) and and using field hyperspectral acquisitions by analytical spectral device (ASD). The performance of the two regression approaches is best for the estimation of moisture content. SVR attains the highest accuracy without feature reduction while MR achieves good results when feature reduction is carried out. Sediment property maps are successfully obtained using the models and hyperspectral imagery where SVR used with all bands achieves the best performance. The study also involves the extraction of weights identifying the contribution of each band of the images in the quantification of each sediment property when MR and principal component analysis are used.

Biophysical characterization and surface radiation balance

NASA Technical Reports Server (NTRS)

Walter-Shea, Elizabeth A.; Blad, Blaine L.; Mesarch, Mark A.; Hays, Cynthia J.; Starks, Patrick J.

1993-01-01

The Kursk 1991 Experiment (KUREX-91) was conducted as one of a suite of international studies to develop capabilities to monitor global change. The studies were designed specifically to understand the earth's land-surface vegetation and atmospheric boundary layer interaction. An intensive field campaign was conducted at a site near Kursk, Russia during the month of July in 1991 by a team of international scientists to aid in the understanding of land-surface-atmosphere interactions in an agricultural/grassland setting. We were one of several teams of scientists participating at KUREX-91 at the Streletskaya Steppe Researve near Kursk, Russia. The main goals of our research were to: (1) characterize biophysical properties of the prairie vegetation; and (2) to characterize radiation regime through measurements and from estimates derived from canopy bidirectional reflectance data. Four objectives were defined to achieve these goals: (1) determine dependence of leaf optical properties on leaf water potential of some dominant species in discrete wavebands in the visible, near-infrared, and mid-infrared (spanning 0.4-2.3 microns range); (2) characterize the effective leaf area index (LAI) and leaf angle distribution of prairie vegetation; (3) characterize the radiation regime of the prairie vegetation through measures of the radiation balance components; and (4) examine, develop, and test methods for estimating albedo, APAR, and LAI from canopy bidirectional reflectance data. Papers which were the result of the research efforts are included.

Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations

PubMed Central

Costa, Caroline Mendonca; Hoetzl, Elena; Rocha, Bernardo Martins; Prassl, Anton J; Plank, Gernot

2014-01-01

Driven by recent advances in medical imaging, image segmentation and numerical techniques, computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parameterization poses a major challenge. A minimum requirement in combined experimental and modeling studies is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study, we propose basic techniques which aid in determining bidomain parameters to match activation sequences. An iterative parameterization algorithm is implemented which determines appropriate bulk conductivities which yield prescribed velocities. In addition, a method is proposed for splitting the computed bulk conductivities into individual bidomain conductivities by prescribing anisotropy ratios. PMID:24729986

Brownian Motion and the Temperament of Living Cells

NASA Astrophysics Data System (ADS)

Tsekov, Roumen; Lensen, Marga C.

2013-07-01

The migration of living cells usually obeys the laws of Brownian motion. While the latter is due to the thermal motion of the surrounding matter, the locomotion of cells is generally associated with their vitality. We study what drives cell migration and how to model memory effects in the Brownian motion of cells. The concept of temperament is introduced as an effective biophysical parameter driving the motion of living biological entities in analogy with the physical parameter of temperature, which dictates the movement of lifeless physical objects. The locomemory of cells is also studied via the generalized Langevin equation. We explore the possibility of describing cell locomemory via the Brownian self-similarity concept. An heuristic expression for the diffusion coefficient of cells on structured surfaces is derived.

Biophysical properties of dermal building-blocks affects extra cellular matrix assembly in 3D endogenous macrotissue.

PubMed

Urciuolo, F; Garziano, A; Imparato, G; Panzetta, V; Fusco, S; Casale, C; Netti, P A

2016-01-29

The fabrication of functional tissue units is one of the major challenges in tissue engineering due to their in vitro use in tissue-on-chip systems, as well as in modular tissue engineering for the construction of macrotissue analogs. In this work, we aim to engineer dermal tissue micromodules obtained by culturing human dermal fibroblasts into porous gelatine microscaffold. We proved that such stromal cells coupled with gelatine microscaffolds are able to synthesize and to assemble an endogenous extracellular matrix (ECM) resulting in tissue micromodules, which evolve their biophysical features over the time. In particular, we found a time-dependent variation of oxygen consumption kinetic parameters, of newly formed ECM stiffness and of micromodules self-aggregation properties. As consequence when used as building blocks to fabricate larger tissues, the initial tissue micromodules state strongly affects the ECM organization and maturation in the final macrotissue. Such results highlight the role of the micromodules properties in controlling the formation of three-dimensional macrotissue in vitro, defining an innovative design criterion for selecting tissue-building blocks for modular tissue engineering.

Characterization of new DOPC/DHPC platform for dermal applications.

PubMed

Rodríguez, Gelen; Rubio, Laia; Barba, Clara; López-Iglesias, Carmen; de la Maza, Alfons; López, Olga; Cócera, Mercedes

2013-05-01

Systems formed by mixtures of the phospholipids dioleoylphosphatidylcholine (DOPC) and dihexanoylphosphatidylcholine (DHPC) were characterized by use of differential scanning calorimetry, small angle X-ray scattering and two electron-microscopy techniques, freeze fracture electron microscopy and cryogenic transmission electron microscopy. These techniques allowed for the determination of the size, morphology, structural topology, self-assembly and thermotropic behavior of the nanostructures present in the mixtures. The interaction between the two phospholipids provides curvatures, irregularities and the increase of thickness and flexibility in the membrane. These effects led to the formation of different aggregates with a differential distribution of both phospholipids. The effect of these systems on the skin in vivo was evaluated by measurement of the biophysical skin parameters. Our results show that the DOPC/DHPC application induces a decrease in the permeability and in the hydration of the tissue. These effects in vivo are related to different microstructural changes promoted by these systems in the skin in vitro, published in a recent work. The fundamental biophysical analyses of DOPC/DHPC systems contribute to our understanding of the mechanisms that govern their interaction with the skin.

Effect of viscosity on the wave propagation: Experimental determination of compression and expansion pulse wave velocity in fluid-fill elastic tube.

PubMed

Stojadinović, Bojana; Tenne, Tamar; Zikich, Dragoslav; Rajković, Nemanja; Milošević, Nebojša; Lazović, Biljana; Žikić, Dejan

2015-11-26

The velocity by which the disturbance travels through the medium is the wave velocity. Pulse wave velocity is one of the main parameters in hemodynamics. The study of wave propagation through the fluid-fill elastic tube is of great importance for the proper biophysical understanding of the nature of blood flow through of cardiovascular system. The effect of viscosity on the pulse wave velocity is generally ignored. In this paper we present the results of experimental measurements of pulse wave velocity (PWV) of compression and expansion waves in elastic tube. The solutions with different density and viscosity were used in the experiment. Biophysical model of the circulatory flow is designed to perform measurements. Experimental results show that the PWV of the expansion waves is higher than the compression waves during the same experimental conditions. It was found that the change in viscosity causes a change of PWV for both waves. We found a relationship between PWV, fluid density and viscosity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Tracking diurnal changes of photosynthesis and evapotranspiration using fluorescence, gas exchange and hyperspectral remote sensing measurements

NASA Astrophysics Data System (ADS)

Wang, S.; Zhang, L.; Guanter, L.; Huang, C.

2017-12-01

Photosynthesis and evapotranspiration (ET) are the two most important activities of vegetation and make a great contribution to carbon, water and energy exchanges. Remote sensing provides opportunities for monitoring these processes across time and space. This study focuses on tracking diurnal changes of photosynthesis and evapotranspiration over soybean using multiple measurement techniques. Diurnal changes of both remote sensing-based indicators, including active and passive chlorophyll fluorescence and biophysical-related parameters, including photosynthesis rate (photo) and leaf stomatal conductance (cond), were observed. Results showed that both leaf-level steady-state fluorescence (Fs) and canopy-level solar-induced chlorophyll fluorescence were linearly correlated to photosynthetically active radiation (PAR) during the daytime. A double-peak diurnal change curve was observed for leaf-level photo and cond but not for Fs or SIF. Photo and cond showed a strong nonlinear (second-order) correlation, indicating that photosynthesis, which might be remotely sensed by SIF, has the opportunity to track short-term changes of ET. Results presented in this report will be helpful for better understanding the relationship between remote-sensing-based indices and vegetation's biophysical processes.

Personalized Instruction with Bootstrap Tutors in an Introductory Biophysics Course

ERIC Educational Resources Information Center

Roper, L. David

1974-01-01

Discusses the conduct of an introductory biophysics course with a personalized instruction by using tutors selected from the students themselves. Included are three tables of text contents, a sample of a terminal questionnaire, and a list of biophysics references. (CC)

Foreword for Special Issue on Environmental Biophysics

USDA-ARS?s Scientific Manuscript database

This special issue on Environmental Biophysics is presented in honor of Dr. John Norman. Over the past four decades, Dr. Norman has dedicated himself to building bridges between disparate scientific disciplines for a better understanding and prediction of biophysical interactions. The consummate i...

Biophysics of the Senses

NASA Astrophysics Data System (ADS)

Presley, Tennille D.

2016-12-01

Biophysics of the Senses connects fundamental properties of physics to biological systems, relating them directly to the human body. It includes discussions of the role of charges and free radicals in disease and homeostasis, how aspects of mechanics impact normal body functions, human bioelectricity and circuitry, forces within the body, and biophysical sensory mechanisms. This is an exciting view of how sensory aspects of biophysics are utilized in everyday life for students who are curious but struggle with the connection between biology and physics.

Reconstruction of Cell Surface Densities of Ion Pumps, Exchangers, and Channels from mRNA Expression, Conductance Kinetics, Whole-Cell Calcium, and Current-Clamp Voltage Recordings, with an Application to Human Uterine Smooth Muscle Cells

PubMed Central

Atia, Jolene; McCloskey, Conor; Shmygol, Anatoly S.; Rand, David A.; van den Berg, Hugo A.; Blanks, Andrew M.

2016-01-01

Uterine smooth muscle cells remain quiescent throughout most of gestation, only generating spontaneous action potentials immediately prior to, and during, labor. This study presents a method that combines transcriptomics with biophysical recordings to characterise the conductance repertoire of these cells, the ‘conductance repertoire’ being the total complement of ion channels and transporters expressed by an electrically active cell. Transcriptomic analysis provides a set of potential electrogenic entities, of which the conductance repertoire is a subset. Each entity within the conductance repertoire was modeled independently and its gating parameter values were fixed using the available biophysical data. The only remaining free parameters were the surface densities for each entity. We characterise the space of combinations of surface densities (density vectors) consistent with experimentally observed membrane potential and calcium waveforms. This yields insights on the functional redundancy of the system as well as its behavioral versatility. Our approach couples high-throughput transcriptomic data with physiological behaviors in health and disease, and provides a formal method to link genotype to phenotype in excitable systems. We accurately predict current densities and chart functional redundancy. For example, we find that to evoke the observed voltage waveform, the BK channel is functionally redundant whereas hERG is essential. Furthermore, our analysis suggests that activation of calcium-activated chloride conductances by intracellular calcium release is the key factor underlying spontaneous depolarisations. PMID:27105427

Predictors of cerebral microembolization during phased radiofrequency ablation of atrial fibrillation: analysis of biophysical parameters from the ablation generator.

PubMed

Nagy-Balo, Edina; Kiss, Alexandra; Condie, Catherine; Stewart, Mark; Edes, Istvan; Csanadi, Zoltan

2014-06-01

Pulmonary vein isolation with phased radiofrequency current and use of a pulmonary vein ablation catheter (PVAC) has recently been associated with a high incidence of clinically silent brain infarcts on diffusion-weighted magnetic resonance imaging and a high microembolic signal (MES) count detected by transcranial Doppler. The purpose of this study was to investigate the potential correlation between different biophysical parameters of energy delivery (ED) and MES generation during PVAC ablation. MES counts during consecutive PVAC ablations were recorded for each ED and time stamped for correlation with temperature, power, and impedance data from the GENius 14.4 generator. Additionally, catheter-tissue contact was characterized by the template deviation score, calculated by comparing the temperature curve with an ideal template representing good contact, and by the respiratory contact failure score, to quantify temperature variations indicative of intermittent contact due to respiration. A total of 834 EDs during 48 PVAC ablations were analyzed. A significant increase in MES count was associated with a lower average temperature, a temperature integral over 62°C, a higher average power, the total energy delivered, higher respiration and template deviation scores (P <.0001), and simultaneous ED to the most proximal and distal poles of the PVAC (P <.0001). MES generation during ablation is related to different indicators of poor electrode-tissue contact, the total power delivered, and the interaction between the most distal and the most proximal electrodes. Copyright © 2014. Published by Elsevier Inc.

Human Visual System as a Double-Slit Single Photon Interference Sensor: A Comparison between Modellistic and Biophysical Tests

PubMed Central

Pizzi, Rita; Wang, Rui; Rossetti, Danilo

2016-01-01

This paper describes a computational approach to the theoretical problems involved in the Young's single-photon double-slit experiment, focusing on a simulation of this experiment in the absence of measuring devices. Specifically, the human visual system is used in place of a photomultiplier or similar apparatus. Beginning with the assumption that the human eye perceives light in the presence of very few photons, we measure human eye performance as a sensor in a double-slit one-photon-at-a-time experimental setup. To interpret the results, we implement a simulation algorithm and compare its results with those of human subjects under identical experimental conditions. In order to evaluate the perceptive parameters exactly, which vary depending on the light conditions and on the subject’s sensitivity, we first review the existing literature on the biophysics of the human eye in the presence of a dim light source, and then use the known values of the experimental variables to set the parameters of the computational simulation. The results of the simulation and their comparison with the experiment involving human subjects are reported and discussed. It is found that, while the computer simulation indicates that the human eye has the capacity to detect the corpuscular nature of photons under these conditions, this was not observed in practice. The possible reasons for the difference between theoretical prediction and experimental results are discussed. PMID:26816029

The influence of larval migration and dispersal depth on potential larval trajectories of a deep-sea bivalve

NASA Astrophysics Data System (ADS)

McVeigh, Doreen M.; Eggleston, David B.; Todd, Austin C.; Young, Craig M.; He, Ruoying

2017-09-01

Many fundamental questions in marine ecology require an understanding of larval dispersal and connectivity, yet direct observations of larval trajectories are difficult or impossible to obtain. Although biophysical models provide an alternative approach, in the deep sea, essential biological parameters for these models have seldom been measured empirically. In this study, we used a biophysical model to explore the role of behaviorally mediated migration from two methane seep sites in the Gulf of Mexico on potential larval dispersal patterns and population connectivity of the deep-sea mussel ;Bathymodiolus; childressi, a species for which some biological information is available. Three possible larval dispersal strategies were evaluated for larvae with a Planktonic Larval Duration (PLD) of 395 days: (1) demersal drift, (2) dispersal near the surface early in larval life followed by an extended demersal period before settlement, and (3) dispersal near the surface until just before settlement. Upward swimming speeds varied in the model based on the best data available. Average dispersal distances for simulated larvae varied between 16 km and 1488 km. Dispersal in the upper water column resulted in the greatest dispersal distance (1173 km ± 2.00), followed by mixed dispersal depth (921 km ± 2.00). Larvae originating in the Gulf of Mexico can potentially seed most known seep metapopulations on the Atlantic continental margin, whereas larvae drifting demersally cannot (237 km ± 1.43). Depth of dispersal is therefore shown to be a critical parameter for models of deep-sea connectivity.

Large scale in vivo recordings to study neuronal biophysics.

PubMed

Giocomo, Lisa M

2015-06-01

Over the last several years, technological advances have enabled researchers to more readily observe single-cell membrane biophysics in awake, behaving animals. Studies utilizing these technologies have provided important insights into the mechanisms generating functional neural codes in both sensory and non-sensory cortical circuits. Crucial for a deeper understanding of how membrane biophysics control circuit dynamics however, is a continued effort to move toward large scale studies of membrane biophysics, in terms of the numbers of neurons and ion channels examined. Future work faces a number of theoretical and technical challenges on this front but recent technological developments hold great promise for a larger scale understanding of how membrane biophysics contribute to circuit coding and computation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Seasonal soybean crop reflectance

NASA Technical Reports Server (NTRS)

Lemaster, E. W. (Principal Investigator); Chance, J. E.

1983-01-01

Data are presented from field measurements of 1980 including 5 acquisitions of handheld radiometer reflectance measurements, 7 complete sets of parameters for implementing the Suits mode, and other biophysical parameters to characterize the soybean canopy. LANDSAT calculations on the simulated Brazilian soybean reflectance are included along with data collected during the summer and fall on 1981 on soybean single leaf optical parameters for three irrigation treatments. Tests of the Suits vegetative canopy reflectance model for the full hemisphere of observer directions as well as the nadir direction show moderate agreement for the visible channels of the MSS and poor agreement in the near infrared channel. Temporal changes in the spectral characteristics of the single leaves were seen to occur as a function of maturity which demonstrates that the absorptance of a soybean single leaf is more a function of thetransmittancee characteristics than the seasonally consistent single leaf reflectance.

Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China.

PubMed

Shi, Benyun; Tan, Qi; Zhou, Xiao-Nong; Liu, Jiming

2015-05-27

Geographic variations of an infectious disease characterize the spatial differentiation of disease incidences caused by various impact factors, such as environmental, demographic, and socioeconomic factors. Some factors may directly determine the force of infection of the disease (namely, explicit factors), while many other factors may indirectly affect the number of disease incidences via certain unmeasurable processes (namely, implicit factors). In this study, the impact of heterogeneous factors on geographic variations of Plasmodium vivax incidences is systematically investigate in Tengchong, Yunnan province, China. A space-time model that resembles a P. vivax transmission model and a hidden time-dependent process, is presented by taking into consideration both explicit and implicit factors. Specifically, the transmission model is built upon relevant demographic, environmental, and biophysical factors to describe the local infections of P. vivax. While the hidden time-dependent process is assessed by several socioeconomic factors to account for the imported cases of P. vivax. To quantitatively assess the impact of heterogeneous factors on geographic variations of P. vivax infections, a Markov chain Monte Carlo (MCMC) simulation method is developed to estimate the model parameters by fitting the space-time model to the reported spatial-temporal disease incidences. Since there is no ground-truth information available, the performance of the MCMC method is first evaluated against a synthetic dataset. The results show that the model parameters can be well estimated using the proposed MCMC method. Then, the proposed model is applied to investigate the geographic variations of P. vivax incidences among all 18 towns in Tengchong, Yunnan province, China. Based on the geographic variations, the 18 towns can be further classify into five groups with similar socioeconomic causality for P. vivax incidences. Although this study focuses mainly on the transmission of P. vivax, the proposed space-time model is general and can readily be extended to investigate geographic variations of other diseases. Practically, such a computational model will offer new insights into active surveillance and strategic planning for disease surveillance and control.

Biophysics and Thermodynamics: The Scientific Building Blocks of Bio-inspired Drug Delivery Nano Systems.

PubMed

Demetzos, Costas

2015-06-01

Biophysics and thermodynamics are considered as the scientific milestones for investigating the properties of materials. The relationship between the changes of temperature with the biophysical variables of biomaterials is important in the process of the development of drug delivery systems. Biophysics is a challenge sector of physics and should be used complementary with the biochemistry in order to discover new and promising technological platforms (i.e., drug delivery systems) and to disclose the 'silence functionality' of bio-inspired biological and artificial membranes. Thermal analysis and biophysical approaches in pharmaceuticals present reliable and versatile tools for their characterization and for the successful development of pharmaceutical products. The metastable phases of self-assembled nanostructures such as liposomes should be taken into consideration because they represent the thermal events can affect the functionality of advanced drug delivery nano systems. In conclusion, biophysics and thermodynamics are characterized as the building blocks for design and development of bio-inspired drug delivery systems.

Ionizable Nitroxides for Studying Local Electrostatic Properties of Lipid Bilayers and Protein Systems by EPR.

PubMed

Voinov, Maxim A; Smirnov, Alex I

2015-01-01

Electrostatic interactions are known to play a major role in the myriad of biochemical and biophysical processes. Here, we describe biophysical methods to probe local electrostatic potentials of proteins and lipid bilayer systems that are based on an observation of reversible protonation of nitroxides by electron paramagnetic resonance (EPR). Two types of probes are described: (1) methanethiosulfonate derivatives of protonatable nitroxides for highly specific covalent modification of the cysteine's sulfhydryl groups and (2) spin-labeled phospholipids with a protonatable nitroxide tethered to the polar head group. The probes of both types report on their ionization state through changes in magnetic parameters and degree of rotational averaging, thus, allowing the electrostatic contribution to the interfacial pKa of the nitroxide, and, therefore, the local electrostatic potential to be determined. Due to their small molecular volume, these probes cause a minimal perturbation to the protein or lipid system. Covalent attachment secures the position of the reporter nitroxides. Experimental procedures to characterize and calibrate these probes by EPR, and also the methods to analyze the EPR spectra by simulations are outlined. The ionizable nitroxide labels and the nitroxide-labeled phospholipids described so far cover an exceptionally wide range of ca. 2.5-7.0 pH units, making them suitable to study a broad range of biophysical phenomena, especially at the negatively charged lipid bilayer surfaces. The rationale for selecting proper electrostatically neutral interface for probe calibration, and examples of lipid bilayer surface potential studies, are also described. © 2015 Elsevier Inc. All rights reserved.

Change in the Beaufort Sea ecosystem: Diverging trends in body condition and/or production in five marine vertebrate species

NASA Astrophysics Data System (ADS)

Harwood, L. A.; Smith, T. G.; George, J. C.; Sandstrom, S. J.; Walkusz, W.; Divoky, G. J.

2015-08-01

Studies of the body condition of five marine vertebrate predators in the Beaufort Sea, conducted independently during the past 2-4 decades, suggest each has been affected by biophysical changes in the marine ecosystem. We summarize a temporal trend of increasing body condition in two species (bowhead whale subadults, Arctic char), in both cases influenced by the extent and persistence of annual sea ice. Three other species (ringed seal, beluga, black guillemot chicks), consumers with a dietary preference for Arctic cod, experienced declines in condition, growth and/or production during the same time period. The proximate causes of these observed changes remain unknown, but may reflect an upward trend in secondary productivity, and a concurrent downward trend in the availability of forage fishes, such as the preferred Arctic cod. To further our understanding of these apparent ecosystem shifts, we urge the use of multiple marine vertebrate species in the design of biophysical sampling studies to identify causes of these changes. Continued long-term, standardized monitoring of vertebrate body condition should be paired with concurrent direct (stomach contents) or indirect (isotopes, fatty acids) monitoring of diet, detailed study of movements and seasonal ranges to establish and refine baselines, and identification of critical habitats of the marine vertebrates being monitored. This would be coordinated with biophysical and oceanographic sampling, at spatial and temporal scales, and geographic locations, that are relevant to the home range, critical habitats and prey of the vertebrate indicator species showing changes in condition and related parameters.

Extended ecosystem signatures with application to Eos synergism requirements

NASA Technical Reports Server (NTRS)

Ulaby, Fawwaz T.; Dobson, M. Craig; Sarabandi, Kamal

1993-01-01

The primary objective is to define the advantages of synergistically combining optical and microwave remote sensing measurements for the determination of biophysical properties important in ecosystem modeling. This objective was approached in a stepwise fashion starting with ground-based observations of controlled agricultural and orchard canopies and progressing to airborne observations of more natural forest ecosystems. This observational program is complemented by a parallel effort to model the visible reflectance and microwave scattering properties of composite vegetation canopies. The goals of the modeling studies are to verify our basic understanding of the sensor-scene interaction physics and to provide the basis for development of inverse models optimized for retrieval of key biophysical properties. These retrieval algorithms can then be used to simulate the expected performance of various aspects of Eos including the need for simultaneous SAR and HIRIS observations or justification for other (non-synchronous) relative timing constraints and the frequency, polarization, and angle of incidence requirements for accurate biophysical parameter extractions. This program completed a very successful series of truck-mounted experiments, made remarkable progress in development and validation of optical reflectance and microwave scattering models for vegetation, extended the scattering models to accommodate discontinuous and periodic canopies, developed inversion approaches for surface and canopy properties, and disseminated these results widely through symposia and journal publications. In addition, the third generation of the computer code for the microwave scattering models was provided to a number of other US, Canadian, Australian, and European investigators who are currently presenting and publishing results using the MIMICS research code.

Synergistic estimation of surface parameters from jointly using optical and microwave observations in EOLDAS

NASA Astrophysics Data System (ADS)

Timmermans, Joris; Gomez-Dans, Jose; Lewis, Philip; Loew, Alexander; Schlenz, Florian

2017-04-01

The large amount of remote sensing data nowadays available provides a huge potential for monitoring crop development, drought conditions and water efficiency. This potential however not been realized yet because algorithms for land surface parameter retrieval mostly use data from only a single sensor. Consequently products that combine different low-level observations from different sensors are hard to find. The lack of synergistic retrieval is caused because it is easier to focus on single sensor types/footprints and temporal observation times, than to find a way to compensate for differences. Different sensor types (microwave/optical) require different radiative transfer (RT) models and also require consistency between the models to have any impact on the retrieval of soil moisture by a microwave instrument. Varying spatial footprints require first proper collocation of the data before one can scale between different resolutions. Considering these problems, merging optical and microwave observations have not been performed yet. The goal of this research was to investigate the potential of integrating optical and microwave RT models within the Earth Observation Land Data Assimilation System (EOLDAS) synergistically to derive biophysical parameters. This system uses a Bayesian data assimilation approach together with observation operators such as the PROSAIL model to estimate land surface parameters. For the purpose of enabling the system to integrate passive microwave radiation (from an ELBARRA II passive microwave radiometer), the Community Microwave Emission Model (CMEM) RT-model, was integrated within the EOLDAS system. In order to quantify the potential, a variety of land surface parameters was chosen to be retrieved from the system, in particular variables that a) impact only optical RT (such as leaf water content and leaf dry matter), b) only impact the microwave RT (such as soil moisture and soil temperature), and c) Leaf Area Index (LAI) that impacts both optical and microwave RT. The results show a high potential when both optical and microwave are used independently. Using only RapidEye only with SAIL RT model, LAI was estimated with R=0.68 with p=0.09, although estimating leaf water content and dry matter showed lower correlations |R|<0.4. The results for retrieving soil temperature and leaf area index retrievals using only (passive microwave) Elbarra-II observations were good with respectively R=[0.85, 0.79], P=[0.0, 0.0], when focusing on dry-spells (of at least 9 days) only the results respectively [R=0.73, and P=0.0], and R=0.89 and R=0.77 for respectively the trend and anomalies. Synergistically using optical and microwave shows also a good potential. This scenario shows that absolute errors improved (with RMSE=1.22 and S=0.89), but with degrading correlations (R=0.59 and P=0.04); the sparse optical observations only improved part of the temporal domain. However in general the synergistic retrieval showed good potential; microwave data provides better information concerning the overall trend of the retrieved LAI due to the regular acquisitions, while optical data provides better information concerning the absolute values of the LAI.

Land-use change and costs to rural households: a case study in groundwater nitrate contamination

NASA Astrophysics Data System (ADS)

Keeler, Bonnie L.; Polasky, Stephen

2014-07-01

Loss of grassland from conversion to agriculture threatens water quality and other valuable ecosystem services. Here we estimate how land-use change affects the probability of groundwater contamination by nitrate in private drinking water wells. We find that conversion of grassland to agriculture from 2007 to 2012 in Southeastern Minnesota is expected to increase the future number of wells exceeding 10 ppm nitrate-nitrogen by 45% (from 888 to 1292 wells). We link outputs of the groundwater well contamination model to cost estimates for well remediation, well replacement, and avoidance behaviors to estimate the potential economic value lost due to nitrate contamination from observed land-use change. We estimate 0.7-12 million in costs (present values over a 20 year horizon) to address the increased risk of nitrate contamination of private wells. Our study demonstrates how biophysical models and economic valuation can be integrated to estimate the welfare consequences of land-use change.

PEBL: A Code for Penetrating and Blunt Trauma, Based on the H-ICDA index

DTIC Science & Technology

1978-10-01

separation 0 no separation g =I sacroiliac joint separation 0 no separation The injury is encoded as follows 808,1230000110. The root code 808. of the PEBL...acetabulum c = I lschium 0 not ischlum d w I ilium 0 not ilium e - I sacrum 0 not sacrum f I pubic separation 0 no separation g = I sacroiliac Joint ...numbers of combat casualties. Development of methodologies for making these estimates was requested of the Biophysics Branch by the Joint Technical

[Estimation of efficacy of the ozone-quant therapy in prophylaxis and treatment of the purulent-necrotic complications of pancreatic pseudocysts].

PubMed

Hazdiuk, P V

2009-01-01

There were analyzed the tactics and the results of 132 patients complex surgical treatment , suffering pancreatic gland pseudocysts (PGP). The original method of the ozone-quant therapy (OQTH), using biophysical factors, such as the ozonized solution of sodium chloride and low-intensity laser irradiation, was applied for prophylaxis and treatment of PGP purulent-necrotic complications (PNC). The data obtained, witness about efficacy of the proposed OQTH method in prophylaxis and treatment of PGP PNC.

Factors controlling plasticity of leaf morphology in Robinia pseudoacacia: III. biophysical constraints on leaf expansion under long-term water stress

Treesearch

Yanxiang ​Zhang; Maria Alejandra Equiza; Quanshui Zheng; Melvin T. Tyree

2011-01-01

In this article, we measured the relative growth rate (RGR) of leaves of Robinia pseudoacacia seedlings under well-watered and water-stressed conditions (mid-day Ψw = leaf water potential estimated with a pressure bomb of −0.48 and −0.98 MPa, respectively). Pressure–volume (PV) curves were done on growing leaves at 25, 50 and 95% of the mature size...

Estimation of reactogenicity of preparations produced on the basis of photoinactivated live vaccines against brucellosis and tularaemia on the organismic level. 1. Using the LASCA method

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

Ulianova, O V; Uianov, S S; Li Pengcheng

2011-04-30

A new method of photoinactivation of bacteria aimed at producing prototypes of vaccine preparations against extremely dangerous infections is described. The reactogenicity of the new prophylactic preparations was studied using the laser speckle contrast analysis (LASCA). The performed experimental studies show that bacterial suspensions, irradiated using different regimes of photoinactivation, do not cause detrimental effect on the blood microcirculation in laboratory animals. (optical technologies in biophysics and medicine)

Chapter 5 - Development of biophysical gradient layers for the LANDFIRE Prototype Project

Treesearch

Lisa Holsinger; Robert E. Keane; Russell Parsons; Eva Karau

2006-01-01

Distributions of plant species are generally continuous, gradually changing across landscapes and blending into each other due to the influence of, and interactions between, a complex array of biophysical gradients (Whittaker 1967; 1975). Key biophysical gradients for understanding vegetation distributions include moisture, temperature, evaporative demand, nutrient...

Single Particle Orientation and Rotational Tracking (SPORT) in biophysical studies

NASA Astrophysics Data System (ADS)

Gu, Yan; Ha, Ji Won; Augspurger, Ashley E.; Chen, Kuangcai; Zhu, Shaobin; Fang, Ning

2013-10-01

The single particle orientation and rotational tracking (SPORT) techniques have seen rapid development in the past 5 years. Recent technical advances have greatly expanded the applicability of SPORT in biophysical studies. In this feature article, we survey the current development of SPORT and discuss its potential applications in biophysics, including cellular membrane processes and intracellular transport.The single particle orientation and rotational tracking (SPORT) techniques have seen rapid development in the past 5 years. Recent technical advances have greatly expanded the applicability of SPORT in biophysical studies. In this feature article, we survey the current development of SPORT and discuss its potential applications in biophysics, including cellular membrane processes and intracellular transport. Electronic supplementary information (ESI) available: Three supplementary movies and an experimental section. See DOI: 10.1039/c3nr02254d

Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

NASA Astrophysics Data System (ADS)

Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

2017-09-01

Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Biophysical impacts of climate-smart agriculture in the Midwest United States.

PubMed

Bagley, Justin E; Miller, Jesse; Bernacchi, Carl J

2015-09-01

The potential impacts of climate change in the Midwest United States present unprecedented challenges to regional agriculture. In response to these challenges, a variety of climate-smart agricultural methodologies have been proposed to retain or improve crop yields, reduce agricultural greenhouse gas emissions, retain soil quality and increase climate resilience of agricultural systems. One component that is commonly neglected when assessing the environmental impacts of climate-smart agriculture is the biophysical impacts, where changes in ecosystem fluxes and storage of moisture and energy lead to perturbations in local climate and water availability. Using a combination of observational data and an agroecosystem model, a series of climate-smart agricultural scenarios were assessed to determine the biophysical impacts these techniques have in the Midwest United States. The first scenario extended the growing season for existing crops using future temperature and CO2 concentrations. The second scenario examined the biophysical impacts of no-till agriculture and the impacts of annually retaining crop debris. Finally, the third scenario evaluated the potential impacts that the adoption of perennial cultivars had on biophysical quantities. Each of these scenarios was found to have significant biophysical impacts. However, the timing and magnitude of the biophysical impacts differed between scenarios. © 2014 John Wiley & Sons Ltd.

Anti-pulmonary fibrotic activity of salvianolic acid B was screened by a novel method based on the cyto-biophysical properties

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

Liu, Miao; Zheng, Mingjing; Xu, Hanying

Various methods have been used to evaluate anti-fibrotic activity of drugs. However, most of them are complicated, labor-intensive and lack of efficiency. This study was intended to develop a rapid method for anti-fibrotic drugs screening based on biophysical properties. A549 cells in vitro were stimulated with transforming growth factor-β1 (TGF-β1), and fibrogenesis was confirmed by conventional immunological assays. Meanwhile, the alterations of cyto-biophysical properties including morphology, roughness and stiffness were measured utilizing atomic force microscopy (AFM). It was found that fibrogenesis was accompanied with changes of cellular biophysical properties. TGF-β1-stimulated A549 cells became remarkably longer, rougher and stiffer than the control.more » Then, the effect of N-acetyl-L-cysteine (NAC) as a positive drug on ameliorating fibrogenesis in TGF-β1-stimulated A549 cells was verified respectively by immunological and biophysical markers. The result of Principal Component Analysis showed that stiffness was a leading index among all biophysical markers during fibrogenesis. Salvianolic acid B (SalB), a natural anti-oxidant, was detected by AFM to protect TGF-β1-stimulated A549 cells against stiffening. Then, SalB treatment was provided in preventive mode on a rat model of bleomycin (BLM) -induced pulmonary fibrosis. The results showed that SalB treatment significantly ameliorated BLM-induced histological alterations, blocked collagen accumulations and reduced α-SMA expression in lung tissues. All these results revealed the anti-pulmonary fibrotic activity of SalB. Detection of cyto-biophysical properties were therefore recommended as a rapid method for anti-pulmonary fibrotic drugs screening. - Highlights: • Fibrogenesis was accompanied with the changes of cyto-biophysical properties. • Cyto-biophysical properties could be markers for anti-fibrotic drugs screening. • Stiffness is a leading index among all biophysical markers. • SalB was detected to protect TGF-β1-stimulated A549 cells against stiffening. • SalB treatment ameliorated pulmonary fibrosis induced by BLM in rats.« less

Impacts of Different Assimilation Methodologies on Crop Yield Estimates Using Active and Passive Microwave Dataset at L-Band

NASA Astrophysics Data System (ADS)

Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.

2013-12-01

Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield estimates. An Ensemble Kalman Filter-based methodology is implemented to incorporate σ0 and TB from Aquarius and SMOS in the DSSAT-A-P model to improve crop yield for two growing seasons of soybean -a normal and a drought affected season- in the rain-fed region of the Brazilian La Plata Basin, South America. Different scenarios of assimilation, including active only, passive only, and combined AP observations were considered. The elements of the state vector included both model states and parameters related to soil and vegetation. The number of elements included in the state vector changed depending upon different scenarios of assimilation and also upon the growth stages. Crop yield estimates were compared for different scenarios during the two seasons. A synthetic experiment conducted previously showed an improvement of crop estimates in the RMSD by 90 kg/ha using combined AP compared to the openloop and active only assimilation over the region.

Laboratory techniques and rhythmometry

NASA Technical Reports Server (NTRS)

Halberg, F.

1973-01-01

Some of the procedures used for the analysis of rhythms are illustrated, notably as these apply to current medical and biological practice. For a quantitative approach to medical and broader socio-ecologic goals, the chronobiologist gathers numerical objective reference standards for rhythmic biophysical, biochemical, and behavioral variables. These biological reference standards can be derived by specialized computer analyses of largely self-measured (until eventually automatically recorded) time series (autorhythmometry). Objective numerical values for individual and population parameters of reproductive cycles can be obtained concomitantly with characteristics of about-yearly (circannual), about-daily (circadian) and other rhythms.

To what extent does urbanisation affect fragmented grassland functioning?

PubMed

van der Walt, L; Cilliers, S S; Kellner, K; Du Toit, M J; Tongway, D

2015-03-15

Urbanisation creates altered environments characterised by increased human habitation, impermeable surfaces, artificial structures, landscape fragmentation, habitat loss, resulting in different resource loss pathways. The vulnerable Rand Highveld Grassland vegetation unit in the Tlokwe Municipal area, South Africa, has been extensively affected and transformed by urbanisation, agriculture, and mining. Grassland fragments in urban areas are often considered to be less species rich and less functional than in the more untransformed or "natural" exurban environments, and are therefore seldom a priority for conservation. Furthermore, urban grassland fragments are often being more intensely managed than exurban areas, such as consistent mowing in open urban areas. Four urbanisation measures acting as indicators for patterns and processes associated with urban areas were calculated for matrix areas surrounding each selected grassland fragment to quantify the position of each grassland remnant along an urbanisation gradient. The grassland fragments were objectively classified into two classes of urbanisation, namely "exurban" and "urban" based on the urbanisation measure values. Grazing was recorded in some exurban grasslands and mowing in some urban grassland fragments. Unmanaged grassland fragments were present in both urban and exurban areas. Fine-scale biophysical landscape function was determined by executing the Landscape Function Analysis (LFA) method. LFA assesses fine-scale landscape patchiness (entailing resource conserving potential and erosion resistance) and 11 soil surface indicators to produce three main LFA parameters (stability, infiltration, and nutrient cycling), which indicates how well a system is functioning in terms of fine-scale biophysical soil processes and characteristics. The aim of this study was to determine the effects of urbanisation and associated management practices on fine-scale biophysical landscape function of urban and exurban grassland fragments, as well as to determine the potential for the use of LFA in decision-making involving the conservation of grassland fragments. The results indicated that the occurrence, size and characteristics of vegetated patches, and especially the presence of litter abundances, were the main factors determining differences in the LFA indices. Furthermore, mowing resulted in the overall fine-scale biophysical indices being higher for some of the urban grassland fragments. This implied that it is not necessarily the influence of urbanisation entailing high or low resource conserving patchiness and patch quality, but rather the management practices associated with urban and exurban areas. Therefore, from a conservation point of view, the grassland fragments in the City of Potchefstroom are just as conservable (on a biophysical function level involving soil processes) than the more "natural" exurban grassland fragments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identifying potential recommendation domains for conservation agriculture in Ethiopia, Kenya, and Malawi.

PubMed

Tesfaye, Kindie; Jaleta, Moti; Jena, Pradyot; Mutenje, Munyaradzi

2015-02-01

Conservation agriculture (CA) is being promoted as an option for reducing soil degradation, conserving water, enhancing crop productivity, and maintaining yield stability. However, CA is a knowledge- and technology-intensive practice, and may not be feasible or may not perform better than conventional agriculture under all conditions and farming systems. Using high resolution (≈1 km(2)) biophysical and socioeconomic geospatial data, this study identified potential recommendation domains (RDs) for CA in Ethiopia, Kenya, and Malawi. The biophysical variables used were soil texture, surface slope, and rainfall while the socioeconomic variables were market access and human and livestock population densities. Based on feasibility and comparative performance of CA over conventional agriculture, the biophysical and socioeconomic factors were first used to classify cultivated areas into three biophysical and three socioeconomic potential domains, respectively. Combinations of biophysical and socioeconomic domains were then used to develop potential RDs for CA based on adoption potential within the cultivated areas. About 39, 12, and 5% of the cultivated areas showed high biophysical and socioeconomic potential while 50, 39, and 21% of the cultivated areas showed high biophysical and medium socioeconomic potential for CA in Malawi, Kenya, and Ethiopia, respectively. The results indicate considerable acreages of land with high CA adoption potential in the mixed crop-livestock systems of the studied countries. However, there are large differences among countries depending on biophysical and socio-economic conditions. The information generated in this study could be used for targeting CA and prioritizing CA-related agricultural research and investment priorities in the three countries.

Identifying Potential Recommendation Domains for Conservation Agriculture in Ethiopia, Kenya, and Malawi

NASA Astrophysics Data System (ADS)

Tesfaye, Kindie; Jaleta, Moti; Jena, Pradyot; Mutenje, Munyaradzi

2015-02-01

Conservation agriculture (CA) is being promoted as an option for reducing soil degradation, conserving water, enhancing crop productivity, and maintaining yield stability. However, CA is a knowledge- and technology-intensive practice, and may not be feasible or may not perform better than conventional agriculture under all conditions and farming systems. Using high resolution (≈1 km2) biophysical and socioeconomic geospatial data, this study identified potential recommendation domains (RDs) for CA in Ethiopia, Kenya, and Malawi. The biophysical variables used were soil texture, surface slope, and rainfall while the socioeconomic variables were market access and human and livestock population densities. Based on feasibility and comparative performance of CA over conventional agriculture, the biophysical and socioeconomic factors were first used to classify cultivated areas into three biophysical and three socioeconomic potential domains, respectively. Combinations of biophysical and socioeconomic domains were then used to develop potential RDs for CA based on adoption potential within the cultivated areas. About 39, 12, and 5 % of the cultivated areas showed high biophysical and socioeconomic potential while 50, 39, and 21 % of the cultivated areas showed high biophysical and medium socioeconomic potential for CA in Malawi, Kenya, and Ethiopia, respectively. The results indicate considerable acreages of land with high CA adoption potential in the mixed crop-livestock systems of the studied countries. However, there are large differences among countries depending on biophysical and socio-economic conditions. The information generated in this study could be used for targeting CA and prioritizing CA-related agricultural research and investment priorities in the three countries.

BIOPHYSICAL EVALUATION OF INDIVIDUAL COMPONENT LEVELS AND SELECTED CONFIGURATIONS OF THE UNITED STATES MARINE CORPS COLD-WEATHER CLOTHING ENSEMBLE

DTIC Science & Technology

2018-01-02

TECHNICAL REPORT NO. T18-01 DATE January 2018 BIOPHYSICAL EVALUATION OF INDIVIDUAL COMPONENT...USARIEM TECHNICAL REPORT T18-01 BIOPHYSICAL EVALUATION OF INDIVIDUAL COMPONENT LEVELS AND...OF TABLES Table Page Table 1. Clothing and individual equipment descriptions ................................................. 3 Table 2. Surface

The Biophysics of Infection.

PubMed

Leake, Mark C

2016-01-01

Our understanding of the processes involved in infection has grown enormously in the past decade due in part to emerging methods of biophysics. This new insight has been enabled through advances in interdisciplinary experimental technologies and theoretical methods at the cutting-edge interface of the life and physical sciences. For example, this has involved several state-of-the-art biophysical tools used in conjunction with molecular and cell biology approaches, which enable investigation of infection in living cells. There are also new, emerging interfacial science tools which enable significant improvements to the resolution of quantitative measurements both in space and time. These include single-molecule biophysics methods and super-resolution microscopy approaches. These new technological tools in particular have underpinned much new understanding of dynamic processes of infection at a molecular length scale. Also, there are many valuable advances made recently in theoretical approaches of biophysics which enable advances in predictive modelling to generate new understanding of infection. Here, I discuss these advances, and take stock on our knowledge of the biophysics of infection and discuss where future advances may lead.

Biophysical Regulation of Cell Behavior—Cross Talk between Substrate Stiffness and Nanotopography

PubMed Central

Yang, Yong; Wang, Kai; Gu, Xiaosong; Leong, Kam W.

2017-01-01

The stiffness and nanotopographical characteristics of the extracellular matrix (ECM) influence numerous developmental, physiological, and pathological processes in vivo. These biophysical cues have therefore been applied to modulate almost all aspects of cell behavior, from cell adhesion and spreading to proliferation and differentiation. Delineation of the biophysical modulation of cell behavior is critical to the rational design of new biomaterials, implants, and medical devices. The effects of stiffness and topographical cues on cell behavior have previously been reviewed, respectively; however, the interwoven effects of stiffness and nanotopographical cues on cell behavior have not been well described, despite similarities in phenotypic manifestations. Herein, we first review the effects of substrate stiffness and nanotopography on cell behavior, and then focus on intracellular transmission of the biophysical signals from integrins to nucleus. Attempts are made to connect extracellular regulation of cell behavior with the biophysical cues. We then discuss the challenges in dissecting the biophysical regulation of cell behavior and in translating the mechanistic understanding of these cues to tissue engineering and regenerative medicine. PMID:29071164

Biotic games and cloud experimentation as novel media for biophysics education

NASA Astrophysics Data System (ADS)

Riedel-Kruse, Ingmar; Blikstein, Paulo

2014-03-01

First-hand, open-ended experimentation is key for effective formal and informal biophysics education. We developed, tested and assessed multiple new platforms that enable students and children to directly interact with and learn about microscopic biophysical processes: (1) Biotic games that enable local and online play using galvano- and photo-tactic stimulation of micro-swimmers, illustrating concepts such as biased random walks, Low Reynolds number hydrodynamics, and Brownian motion; (2) an undergraduate course where students learn optics, electronics, micro-fluidics, real time image analysis, and instrument control by building biotic games; and (3) a graduate class on the biophysics of multi-cellular systems that contains a cloud experimentation lab enabling students to execute open-ended chemotaxis experiments on slimemolds online, analyze their data, and build biophysical models. Our work aims to generate the equivalent excitement and educational impact for biophysics as robotics and video games have had for mechatronics and computer science, respectively. We also discuss how scaled-up cloud experimentation systems can support MOOCs with true lab components and life-science research in general.

Predicting the limits to tree height using statistical regressions of leaf traits.

PubMed

Burgess, Stephen S O; Dawson, Todd E

2007-01-01

Leaf morphology and physiological functioning demonstrate considerable plasticity within tree crowns, with various leaf traits often exhibiting pronounced vertical gradients in very tall trees. It has been proposed that the trajectory of these gradients, as determined by regression methods, could be used in conjunction with theoretical biophysical limits to estimate the maximum height to which trees can grow. Here, we examined this approach using published and new experimental data from tall conifer and angiosperm species. We showed that height predictions were sensitive to tree-to-tree variation in the shape of the regression and to the biophysical endpoints selected. We examined the suitability of proposed end-points and their theoretical validity. We also noted that site and environment influenced height predictions considerably. Use of leaf mass per unit area or leaf water potential coupled with vulnerability of twigs to cavitation poses a number of difficulties for predicting tree height. Photosynthetic rate and carbon isotope discrimination show more promise, but in the second case, the complex relationship between light, water availability, photosynthetic capacity and internal conductance to CO(2) must first be characterized.

Optimization of a novel biophysical model using large scale in vivo antisense hybridization data displays improved prediction capabilities of structurally accessible RNA regions

PubMed Central

Vazquez-Anderson, Jorge; Mihailovic, Mia K.; Baldridge, Kevin C.; Reyes, Kristofer G.; Haning, Katie; Cho, Seung Hee; Amador, Paul; Powell, Warren B.

2017-01-01

Abstract Current approaches to design efficient antisense RNAs (asRNAs) rely primarily on a thermodynamic understanding of RNA–RNA interactions. However, these approaches depend on structure predictions and have limited accuracy, arguably due to overlooking important cellular environment factors. In this work, we develop a biophysical model to describe asRNA–RNA hybridization that incorporates in vivo factors using large-scale experimental hybridization data for three model RNAs: a group I intron, CsrB and a tRNA. A unique element of our model is the estimation of the availability of the target region to interact with a given asRNA using a differential entropic consideration of suboptimal structures. We showcase the utility of this model by evaluating its prediction capabilities in four additional RNAs: a group II intron, Spinach II, 2-MS2 binding domain and glgC 5΄ UTR. Additionally, we demonstrate the applicability of this approach to other bacterial species by predicting sRNA–mRNA binding regions in two newly discovered, though uncharacterized, regulatory RNAs. PMID:28334800

Climate change effects on agriculture: Economic responses to biophysical shocks

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

Nelson, Gerald; Valin, Hugo; Sands, Ronald

Agricultural production is sensitive to weather and will thus be directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments inmore » yields, area, consumption, and international trade. We apply biophysical shocks derived from the IPCC’s Representative Concentration Pathway that result in end-of-century radiative forcing of 8.5 watts per square meter. The mean biophysical impact on crop yield with no incremental CO2 fertilization is a 17 percent reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11 percent, increase area of major crops by 12 percent, and reduce consumption by 2 percent. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences includes model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.« less

Molecular mechanism of direct proflavine-DNA intercalation: evidence for drug-induced minimum base-stacking penalty pathway.

PubMed

Sasikala, Wilbee D; Mukherjee, Arnab

2012-10-11

DNA intercalation, a biophysical process of enormous clinical significance, has surprisingly eluded molecular understanding for several decades. With appropriate configurational restraint (to prevent dissociation) in all-atom metadynamics simulations, we capture the free energy surface of direct intercalation from minor groove-bound state for the first time using an anticancer agent proflavine. Mechanism along the minimum free energy path reveals that intercalation happens through a minimum base stacking penalty pathway where nonstacking parameters (Twist→Slide/Shift) change first, followed by base stacking parameters (Buckle/Roll→Rise). This mechanism defies the natural fluctuation hypothesis and provides molecular evidence for the drug-induced cavity formation hypothesis. The thermodynamic origin of the barrier is found to be a combination of entropy and desolvation energy.

Estimating forest structural characteristics using the airborne LiDAR scanning system and a near-real time profiling laser system

NASA Astrophysics Data System (ADS)

Zhao, Kaiguang

LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatially-explicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for real-time remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real-time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real-time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for real-time forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of airborne scanning or profiling laser systems for remotely measuring various forest structural attributes at a range of scales, i.e., from individual tree, plot, stand and up to regional levels. The system not only provides a regional assessment tool, one that can be used to repeatedly, remotely measure hundreds or thousands of square kilometers with little/no analyst interaction or interpretation, but also serves as a paradigm for future efforts in building more advanced airborne laser systems such as real-time laser scanners.

NASA Space Radiation Program Integrative Risk Model Toolkit

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; Hu, Shaowen; Plante, Ianik; Ponomarev, Artem L.; Sandridge, Chris

2015-01-01

NASA Space Radiation Program Element scientists have been actively involved in development of an integrative risk models toolkit that includes models for acute radiation risk and organ dose projection (ARRBOD), NASA space radiation cancer risk projection (NSCR), hemocyte dose estimation (HemoDose), GCR event-based risk model code (GERMcode), and relativistic ion tracks (RITRACKS), NASA radiation track image (NASARTI), and the On-Line Tool for the Assessment of Radiation in Space (OLTARIS). This session will introduce the components of the risk toolkit with opportunity for hands on demonstrations. The brief descriptions of each tools are: ARRBOD for Organ dose projection and acute radiation risk calculation from exposure to solar particle event; NSCR for Projection of cancer risk from exposure to space radiation; HemoDose for retrospective dose estimation by using multi-type blood cell counts; GERMcode for basic physical and biophysical properties for an ion beam, and biophysical and radiobiological properties for a beam transport to the target in the NASA Space Radiation Laboratory beam line; RITRACKS for simulation of heavy ion and delta-ray track structure, radiation chemistry, DNA structure and DNA damage at the molecular scale; NASARTI for modeling of the effects of space radiation on human cells and tissue by incorporating a physical model of tracks, cell nucleus, and DNA damage foci with image segmentation for the automated count; and OLTARIS, an integrated tool set utilizing HZETRN (High Charge and Energy Transport) intended to help scientists and engineers study the effects of space radiation on shielding materials, electronics, and biological systems.

Extensive investigation of the sap flow of maize plants in an oasis farmland in the middle reach of the Heihe River, Northwest China.

PubMed

Zhao, Liwen; He, Zhibin; Zhao, Wenzhi; Yang, Qiyue

2016-09-01

A better understanding of the sap flow characteristics of maize plants is critical for improving irrigation water-use efficiency, especially for regions facing water resource shortages. In this study, sap flow rates, related soil-physics and plant-growth parameters, and meteorological factors, were simultaneously monitored in a maize field in two consecutive years, 2011 and 2012, and the sap flow rates of the maize plants were extensively analyzed based on the monitored data. Seasonal and daily variational characteristics were identified at different growth stages and under different weather conditions, respectively. The analyses on the relationships between sap flow rate and reference evapotranspiration (ET0), as well as several plant-growth parameters, indicate that the irrigation schedule can exert an influence on sap flow, and can consequently affect crop yield. The ranking of the main meteorological factors affecting the sap flow rate was: net radiation > air temperature > vapor pressure deficit > wind speed. For a quick estimation of sap flow rates, an empirical formula based on the two top influencing factors was put forward and verified to be reliable. The sap flow rate appeared to show little response to irrigation when the water content was relatively high, implying that some of the irrigation in recent years may have been wasted. These results may help to reveal the bio-physical processes of maize plants related to plant transpiration, which could be beneficial for establishing an efficient irrigation management system in this region and also for providing a reference for other maize-planting regions.

Social versus biophysical availability of wood in the northern United States

Treesearch

Brett J. Butler; Ma Zhao; David B. Kittredge; Paul Catanzaro

2010-01-01

The availability of wood, be it harvested for sawlogs, pulpwood, biomass, or other products, is constrained by social and biophysical factors. Knowing the difference between social and biophysical availability is important for understanding what can realistically be extracted. This study focuses on the wood located in family forests across the northern United States....

Single Particle Orientation and Rotational Tracking (SPORT) in biophysical studies

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

Gu, Yan; Ha, Ji Won; Augspurger, Ashley E.

The single particle orientation and rotational tracking (SPORT) techniques have seen rapid development in the past 5 years. Recent technical advances have greatly expanded the applicability of SPORT in biophysical studies. In this feature article, we survey the current development of SPORT and discuss its potential applications in biophysics, including cellular membrane processes and intracellular transport.

Human and biophysical factors influencing modern fire disturbance in northern Wisconsin

Treesearch

Brian R. Sturtevant; David T. Cleland

2007-01-01

Humans cause most wildfires in northern Wisconsin, but interactions between human and biophysical variables affecting fire starts and size are not well understood. We applied classification tree analyses to a 16-year fire database from northern Wisconsin to evaluate the relative importance of human v. biophysical variables affecting fire occurrence within (1) all cover...

Linking biophysical models and public preferences for ecosystem service assessments: a case study for the Southern Rocky Mountains

USGS Publications Warehouse

Bagstad, Kenneth J.; Reed, James; Semmens, Darius J.; Sherrouse, Ben C.; Troy, Austin

2016-01-01

Through extensive research, ecosystem services have been mapped using both survey-based and biophysical approaches, but comparative mapping of public values and those quantified using models has been lacking. In this paper, we mapped hot and cold spots for perceived and modeled ecosystem services by synthesizing results from a social-values mapping study of residents living near the Pike–San Isabel National Forest (PSI), located in the Southern Rocky Mountains, with corresponding biophysically modeled ecosystem services. Social-value maps for the PSI were developed using the Social Values for Ecosystem Services tool, providing statistically modeled continuous value surfaces for 12 value types, including aesthetic, biodiversity, and life-sustaining values. Biophysically modeled maps of carbon sequestration and storage, scenic viewsheds, sediment regulation, and water yield were generated using the Artificial Intelligence for Ecosystem Services tool. Hotspots for both perceived and modeled services were disproportionately located within the PSI’s wilderness areas. Additionally, we used regression analysis to evaluate spatial relationships between perceived biodiversity and cultural ecosystem services and corresponding biophysical model outputs. Our goal was to determine whether publicly valued locations for aesthetic, biodiversity, and life-sustaining values relate meaningfully to results from corresponding biophysical ecosystem service models. We found weak relationships between perceived and biophysically modeled services, indicating that public perception of ecosystem service provisioning regions is limited. We believe that biophysical and social approaches to ecosystem service mapping can serve as methodological complements that can advance ecosystem services-based resource management, benefitting resource managers by showing potential locations of synergy or conflict between areas supplying ecosystem services and those valued by the public.

The zipper mechanism in phagocytosis: energetic requirements and variability in phagocytic cup shape

PubMed Central

2010-01-01

Background Phagocytosis is the fundamental cellular process by which eukaryotic cells bind and engulf particles by their cell membrane. Particle engulfment involves particle recognition by cell-surface receptors, signaling and remodeling of the actin cytoskeleton to guide the membrane around the particle in a zipper-like fashion. Despite the signaling complexity, phagocytosis also depends strongly on biophysical parameters, such as particle shape, and the need for actin-driven force generation remains poorly understood. Results Here, we propose a novel, three-dimensional and stochastic biophysical model of phagocytosis, and study the engulfment of particles of various sizes and shapes, including spiral and rod-shaped particles reminiscent of bacteria. Highly curved shapes are not taken up, in line with recent experimental results. Furthermore, we surprisingly find that even without actin-driven force generation, engulfment proceeds in a large regime of parameter values, albeit more slowly and with highly variable phagocytic cups. We experimentally confirm these predictions using fibroblasts, transfected with immunoreceptor FcγRIIa for engulfment of immunoglobulin G-opsonized particles. Specifically, we compare the wild-type receptor with a mutant receptor, unable to signal to the actin cytoskeleton. Based on the reconstruction of phagocytic cups from imaging data, we indeed show that cells are able to engulf small particles even without support from biological actin-driven processes. Conclusions This suggests that biochemical pathways render the evolutionary ancient process of phagocytic highly robust, allowing cells to engulf even very large particles. The particle-shape dependence of phagocytosis makes a systematic investigation of host-pathogen interactions and an efficient design of a vehicle for drug delivery possible. PMID:21059234

The gastro-esophageal reflux barrier: biophysical analysis on 3D models of anatomy from magnetic resonance imaging.

PubMed

Roy, S; Fox, M R; Curcic, J; Schwizer, W; Pal, A

2012-07-01

The function and structure of the gastro-esophageal junction (GEJ) determine its efficacy as a reflux barrier. This study presents a novel methodology for the quantitative assessment of GEJ and proximal gastric morphology from magnetic resonance (MR) imaging. Based on this data we propose a new conceptualization of the hypothesis that a flap valve mechanism contributes to reflux protection. 3D models of the GEJ and proximal stomach were reconstructed from MR images in 12 healthy volunteers during respiration and on eating a test meal to maximum satiation. A rotating plane analysis measured the gastro-esophageal insertion angle and span of contact. An ellipsoid fit provided quantitative assessment of gastric shape and orientation relative to a fixed anatomical reference point. Position of the esophageal insertion on the 'gastric ellipse' was noted. An ellipsoid-cylinder model was designed to analyze the relationships among parameters describing the GEJ morphology. The insertion angle became more acute on expiration, but did not change with meal ingestion. In contrast the span of contact did not vary with respiration, but increased with gastric filling. Changes in gastric morphology with distension further augmented the span of gastro-esophageal contact in almost 70% of the studies. Novel MR imaging and biophysical analysis of the GEJ and proximal stomach provide a quantitative description of structures contributing to the reflux barrier. Changes in these parameters during respiration and on eating support the hypothesis that structural components of a functional 'flap valve' like mechanism contribute to reflux protection. © 2012 Blackwell Publishing Ltd.

Accurate Depth of Radiofrequency-Induced Lesions in Renal Sympathetic Denervation Based on a Fine Histological Sectioning Approach in a Porcine Model

PubMed Central

Terao, Hisako; Nakamura, Shintaro; Hagiwara, Hitomi; Furukawa, Toshihito; Matsumura, Kiyoshi; Sakakura, Kenichi

2018-01-01

Background— Ablation lesion depth caused by radiofrequency-based renal denervation (RDN) was limited to <4 mm in previous animal studies, suggesting that radiofrequency-RDN cannot ablate a substantial percentage of renal sympathetic nerves. We aimed to define the true lesion depth achieved with radiofrequency-RDN using a fine sectioning method and to investigate biophysical parameters that could predict lesion depth. Methods and Results— Radiofrequency was delivered to 87 sites in 14 renal arteries from 9 farm pigs at various ablation settings: 2, 4, 6, and 9 W for 60 seconds and 6 W for 120 seconds. Electric impedance and electrode temperature were recorded during ablation. At 7 days, 2470 histological sections were obtained from the treated arteries. Maximum lesion depth increased at 2 to 6 W, peaking at 6.53 (95% confidence interval, 4.27–8.78) mm under the 6 W/60 s condition. It was not augmented by greater power (9 W) or longer duration (120 seconds). There were statistically significant tendencies at 6 and 9 W, with higher injury scores in the media, nerves, arterioles, and fat. Maximum lesion depth was positively correlated with impedance reduction and peak electrode temperature (Pearson correlation coefficients were 0.59 and 0.53, respectively). Conclusions— Lesion depth was 6.5 mm for radiofrequency-RDN at 6 W/60 s. The impedance reduction and peak electrode temperature during ablation were closely associated with lesion depth. Hence, these biophysical parameters could provide prompt feedback during radiofrequency-RDN procedures in the clinical setting. PMID:29440276

Accurate Depth of Radiofrequency-Induced Lesions in Renal Sympathetic Denervation Based on a Fine Histological Sectioning Approach in a Porcine Model.

PubMed

Sakaoka, Atsushi; Terao, Hisako; Nakamura, Shintaro; Hagiwara, Hitomi; Furukawa, Toshihito; Matsumura, Kiyoshi; Sakakura, Kenichi

2018-02-01

Ablation lesion depth caused by radiofrequency-based renal denervation (RDN) was limited to <4 mm in previous animal studies, suggesting that radiofrequency-RDN cannot ablate a substantial percentage of renal sympathetic nerves. We aimed to define the true lesion depth achieved with radiofrequency-RDN using a fine sectioning method and to investigate biophysical parameters that could predict lesion depth. Radiofrequency was delivered to 87 sites in 14 renal arteries from 9 farm pigs at various ablation settings: 2, 4, 6, and 9 W for 60 seconds and 6 W for 120 seconds. Electric impedance and electrode temperature were recorded during ablation. At 7 days, 2470 histological sections were obtained from the treated arteries. Maximum lesion depth increased at 2 to 6 W, peaking at 6.53 (95% confidence interval, 4.27-8.78) mm under the 6 W/60 s condition. It was not augmented by greater power (9 W) or longer duration (120 seconds). There were statistically significant tendencies at 6 and 9 W, with higher injury scores in the media, nerves, arterioles, and fat. Maximum lesion depth was positively correlated with impedance reduction and peak electrode temperature (Pearson correlation coefficients were 0.59 and 0.53, respectively). Lesion depth was 6.5 mm for radiofrequency-RDN at 6 W/60 s. The impedance reduction and peak electrode temperature during ablation were closely associated with lesion depth. Hence, these biophysical parameters could provide prompt feedback during radiofrequency-RDN procedures in the clinical setting. © 2018 The Authors.

Characterization of oily mature skin by biophysical and skin imaging techniques.

PubMed

de Melo, M O; Maia Campos, P M B G

2018-02-13

The skin is a complex biological system and may suffer change according to the environmental factors, as higher temperatures can increase sebum excretion, presenting oiliness and acne. These alterations can persist during the aging and provoke more changes in aged skin. In this study we evaluated the mature oily skin characteristics using biophysical and skin imaging techniques. Sixty healthy female subjects, aged between 39 and 55 years old were recruited and separated into 2 groups according to their skin type: normal/dry and oily skin. The skin was evaluated in terms of stratum corneum water content, transepidermal water loss (TEWL) sebum content, dermis thickness and echogenicity, skin microrelief, and pores content. The mature oily skin presented no significant differences when compared to the normal/dry skin on the stratum corneum water content and TEWL parameters. The sebum content was significantly higher on the oily skin group. The microrelief analysis showed an increase of skin roughness values in the oily skin and increase of scaliness in the normal/dry skin. The oily skin showed lower dermis echogenicity mainly in the frontal region and higher dermis thickness when compared to normal/dry skin. The mature oily skin showed different characteristics from normal/dry skin in terms of sebum content, microrelief parameters, and dermis thickness. This way, the characterization of mature oily skin in an objective way is very important to development of dermocosmetic products for more effective treatments focused specially on this type of skin. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Ensemble-Based Parameter Estimation in a Coupled General Circulation Model

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-09-10

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data

NASA Astrophysics Data System (ADS)

Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin

2013-04-01

The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the assimilation of the remotely sensed GAI time series. The calibration process led to accurate spatial estimates of GAI, ETR as well as of biomass and yield over the study area (24 km x 24 km window). The results highlight the interest of using a combined approach (crop model coupled with high spatial and temporal resolution remote sensing data) for the estimation of agronomical variables. At local scale, the model reproduced correctly the biomass production and ETR for summer crops (with relative RMSE of 29% and 35%, respectively). At regional scale, estimated yield and water requirement for irrigation were compared to regional statistics of yield and irrigation inventories provided by the local water agency. Results showed good agreements for inter-annual dynamics of yield estimates. Differences between water requirement for irrigation and actual supply were lower than 10% and inter-annual variability was well represented as well. The work, initially focused on summer crops, is being adapted to winter crops.

Beyond the classic thermoneutral zone

PubMed Central

Kingma, Boris RM; Frijns, Arjan JH; Schellen, Lisje; van Marken Lichtenbelt, Wouter D

2014-01-01

The thermoneutral zone is defined as the range of ambient temperatures where the body can maintain its core temperature solely through regulating dry heat loss, i.e., skin blood flow. A living body can only maintain its core temperature when heat production and heat loss are balanced. That means that heat transport from body core to skin must equal heat transport from skin to the environment. This study focuses on what combinations of core and skin temperature satisfy the biophysical requirements of being in the thermoneutral zone for humans. Moreover, consequences are considered of changes in insulation and adding restrictions such as thermal comfort (i.e. driver for thermal behavior). A biophysical model was developed that calculates heat transport within a body, taking into account metabolic heat production, tissue insulation, and heat distribution by blood flow and equates that to heat loss to the environment, considering skin temperature, ambient temperature and other physical parameters. The biophysical analysis shows that the steady-state ambient temperature range associated with the thermoneutral zone does not guarantee that the body is in thermal balance at basal metabolic rate per se. Instead, depending on the combination of core temperature, mean skin temperature and ambient temperature, the body may require significant increases in heat production or heat loss to maintain stable core temperature. Therefore, the definition of the thermoneutral zone might need to be reformulated. Furthermore, after adding restrictions on skin temperature for thermal comfort, the ambient temperature range associated with thermal comfort is smaller than the thermoneutral zone. This, assuming animals seek thermal comfort, suggests that thermal behavior may be initiated already before the boundaries of the thermoneutral zone are reached. PMID:27583296

Surface electrostatics of lipid bilayers by EPR of a pH-sensitive spin-labeled lipid.

PubMed

Voinov, Maxim A; Rivera-Rivera, Izarys; Smirnov, Alex I

2013-01-08

Many biophysical processes such as insertion of proteins into membranes and membrane fusion are governed by bilayer electrostatic potential. At the time of this writing, the arsenal of biophysical methods for such measurements is limited to a few techniques. Here we describe a, to our knowledge, new spin-probe electron paramagnetic resonance (EPR) approach for assessing the electrostatic surface potential of lipid bilayers that is based on a recently synthesized EPR probe (IMTSL-PTE) containing a reversibly ionizable nitroxide tag attached to the lipids' polar headgroup. EPR spectra of the probe directly report on its ionization state and, therefore, on electrostatic potential through changes in nitroxide magnetic parameters and the degree of rotational averaging. Further, the lipid nature of the probe provides its full integration into lipid bilayers. Tethering the nitroxide moiety directly to the lipid polar headgroup defines the location of the measured potential with respect to the lipid bilayer interface. Electrostatic surface potentials measured by EPR of IMTSL-PTE show a remarkable (within ±2%) agreement with the Gouy-Chapman theory for anionic DMPG bilayers in fluid (48°C) phase at low electrolyte concentration (50 mM) and in gel (17°C) phase at 150-mM electrolyte concentration. This agreement begins to diminish for DMPG vesicles in gel phase (17°C) upon varying electrolyte concentration and fluid phase bilayers formed from DMPG/DMPC and POPG/POPC mixtures. Possible reasons for such deviations, as well as the proper choice of an electrostatically neutral reference interface, have been discussed. Described EPR method is expected to be fully applicable to more-complex models of cellular membranes. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Beyond the classic thermoneutral zone: Including thermal comfort.

PubMed

Kingma, Boris Rm; Frijns, Arjan Jh; Schellen, Lisje; van Marken Lichtenbelt, Wouter D

2014-01-01

The thermoneutral zone is defined as the range of ambient temperatures where the body can maintain its core temperature solely through regulating dry heat loss, i.e., skin blood flow. A living body can only maintain its core temperature when heat production and heat loss are balanced. That means that heat transport from body core to skin must equal heat transport from skin to the environment. This study focuses on what combinations of core and skin temperature satisfy the biophysical requirements of being in the thermoneutral zone for humans. Moreover, consequences are considered of changes in insulation and adding restrictions such as thermal comfort (i.e. driver for thermal behavior). A biophysical model was developed that calculates heat transport within a body, taking into account metabolic heat production, tissue insulation, and heat distribution by blood flow and equates that to heat loss to the environment, considering skin temperature, ambient temperature and other physical parameters. The biophysical analysis shows that the steady-state ambient temperature range associated with the thermoneutral zone does not guarantee that the body is in thermal balance at basal metabolic rate per se. Instead, depending on the combination of core temperature, mean skin temperature and ambient temperature, the body may require significant increases in heat production or heat loss to maintain stable core temperature. Therefore, the definition of the thermoneutral zone might need to be reformulated. Furthermore, after adding restrictions on skin temperature for thermal comfort, the ambient temperature range associated with thermal comfort is smaller than the thermoneutral zone. This, assuming animals seek thermal comfort, suggests that thermal behavior may be initiated already before the boundaries of the thermoneutral zone are reached.

Integrating socio-economic and biophysical data to enhance watershed management and planning

NASA Astrophysics Data System (ADS)

Pirani, Farshad Jalili; Mousavi, Seyed Alireza

2016-09-01

Sustainability has always been considered as one of the main aspects of watershed management plans. In many developing countries, watershed management practices and planning are usually performed by integrating biophysical layers, and other existing layers which cannot be identified as geographic layers are ignored. We introduce an approach to consider some socioeconomic parameters which are important for watershed management decisions. Ganj basin in Chaharmahal-Bakhtiari Province was selected as the case study area, which includes three traditional sanctums: Ganj, Shiremard and Gerdabe Olya. Socioeconomic data including net agricultural income, net ranching income, population and household number, literacy rate, unemployment rate, population growth rate and active population were mapped within traditional sanctums and then were integrated into other biophysical layers. After overlaying and processing these data to determine management units, different quantitative and qualitative approaches were adopted to achieve a practical framework for watershed management planning and relevant plans for homogeneous units were afterwards proposed. Comparing the results with current plans, the area of allocated lands to different proposed operations considering both qualitative and quantitative approaches were the same in many cases and there was a meaningful difference with current plans; e.g., 3820 ha of lands are currently managed under an enclosure plan, while qualitative and quantitative approaches in this study suggest 1388 and 1428 ha to be allocated to this operation type, respectively. Findings show that despite the ambiguities and complexities, different techniques could be adopted to incorporate socioeconomic conditions in watershed management plans. This introductory approach will help to enhance watershed management decisions with more attention to societal background and economic conditions, which will presumably motivate local communities to participate in watershed management plans.

The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

NASA Astrophysics Data System (ADS)

Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

2012-10-01

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

Acupuncture-Based Biophysical Frontiers of Complementary Medicine

DTIC Science & Technology

2001-10-28

cf. Fig. 1, an evolutionary older type of intercell communications , transporting ionic electrical signals between excitable cells, whose conductivity...traditional psychology: Biophysical bases of psychosomatic disorders and transpersonal stress reprogramming", in Basic and Clinical Aspects of the Theory...biophysical basis of transpersonal transcendental phenomena", Int. J. Appl. Sci. & Computat, vol. 7, pp. 174-187, 2000 [also presented at Int. Conf

Program review. Challenges and opportunities for training the next generation of biophysicists: perspectives of the directors of the Molecular Biophysics Training Program at Northwestern University.

PubMed

Neuhaus, Francis; Widom, Jonathan; MacDonald, Robert; Jardetzky, Theodore; Radhakrishnan, Ishwar

2008-04-01

Molecular biophysics is a broad, diverse, and dynamic field that has presented a variety of unique challenges and opportunities for training future generations of investigators. Having been or currently being intimately associated with the Molecular Biophysics Training Program at Northwestern, we present our perspectives on various issues that we have encountered over the years. We propose no cookie-cutter solutions, as there is no consensus on what constitutes the "ideal" program. However, there is uniformity in opinion on some key issues that might be useful to those interested in establishing a biophysics training program.

Application of a multicompartment dynamical model to multimodal optical imaging for investigating individual cerebrovascular properties

NASA Astrophysics Data System (ADS)

Desjardins, Michèle; Gagnon, Louis; Gauthier, Claudine; Hoge, Rick D.; Dehaes, Mathieu; Desjardins-Crépeau, Laurence; Bherer, Louis; Lesage, Frédéric

2009-02-01

Biophysical models of hemodynamics provide a tool for quantitative multimodal brain imaging by allowing a deeper understanding of the interplay between neural activity and blood oxygenation, volume and flow responses to stimuli. Multicompartment dynamical models that describe the dynamics and interactions of the vascular and metabolic components of evoked hemodynamic responses have been developed in the literature. In this work, multimodal data using near-infrared spectroscopy (NIRS) and diffuse correlation flowmetry (DCF) is used to estimate total baseline hemoglobin concentration (HBT0) in 7 adult subjects. A validation of the model estimate and investigation of the partial volume effect is done by comparing with time-resolved spectroscopy (TRS) measures of absolute HBT0. Simultaneous NIRS and DCF measurements during hypercapnia are then performed, but are found to be hardly reproducible. The results raise questions about the feasibility of an all-optical model-based estimation of individual vascular properties.

Effects of radiobiological uncertainty on vehicle and habitat shield design for missions to the moon and Mars

NASA Technical Reports Server (NTRS)

Wilson, John W.; Nealy, John E.; Schimmerling, Walter; Cucinotta, Francis A.; Wood, James S.

1993-01-01

Some consequences of uncertainties in radiobiological risk due to galactic cosmic ray (GCR) exposure are analyzed for their effect on engineering designs for the first lunar outpost and a mission to explore Mars. This report presents the plausible effect of biological uncertainties, the design changes necessary to reduce the uncertainties to acceptable levels for a safe mission, and an evaluation of the mission redesign cost. Estimates of the amount of shield mass required to compensate for radiobiological uncertainty are given for a simplified vehicle and habitat. The additional amount of shield mass required to provide a safety factor for uncertainty compensation is calculated from the expected response to GCR exposure. The amount of shield mass greatly increases in the estimated range of biological uncertainty, thus, escalating the estimated cost of the mission. The estimates are used as a quantitative example for the cost-effectiveness of research in radiation biophysics and radiation physics.

Chromosome Aberrations in Astronauts

NASA Technical Reports Server (NTRS)

George, Kerry A.; Durante, M.; Cucinotta, Francis A.

2007-01-01

A review of currently available data on in vivo induced chromosome damage in the blood lymphocytes of astronauts proves that, after protracted exposure of a few months or more to space radiation, cytogenetic biodosimetry analyses of blood collected within a week or two of return from space provides a reliable estimate of equivalent radiation dose and risk. Recent studies indicate that biodosimetry estimates from single spaceflights lie within the range expected from physical dosimetry and biophysical models, but very large uncertainties are associated with single individual measurements and the total sample population remains low. Retrospective doses may be more difficult to estimate because of the fairly rapid time-dependent loss of "stable" aberrations in blood lymphocytes. Also, biodosimetry estimates from individuals who participate in multiple missions, or very long (interplanetary) missions, may be complicated by an adaptive response to space radiation and/or changes in lymphocyte survival and repopulation. A discussion of published data is presented and specific issues related to space radiation biodosimetry protocols are discussed.

Assessing sustainable biophysical human-nature connectedness at regional scales

NASA Astrophysics Data System (ADS)

Dorninger, Christian; Abson, David J.; Fischer, Joern; von Wehrden, Henrik

2017-05-01

Humans are biophysically connected to the biosphere through the flows of materials and energy appropriated from ecosystems. While this connection is fundamental for human well-being, many modern societies have—for better or worse—disconnected themselves from the natural productivity of their immediate regional environment. In this paper, we conceptualize the biophysical human-nature connectedness of land use systems at regional scales. We distinguish two mechanisms by which primordial connectedness of people to regional ecosystems has been circumvented via the use of external inputs. First, ‘biospheric disconnection’ refers to people drawing on non-renewable minerals from outside the biosphere (e.g. fossils, metals and other minerals). Second, ‘spatial disconnection’ arises from the imports and exports of biomass products and imported mineral resources used to extract and process ecological goods. Both mechanisms allow for greater regional resource use than would be possible otherwise, but both pose challenges for sustainability, for example, through waste generation, depletion of non-renewable resources and environmental burden shifting to distant regions. In contrast, biophysically reconnected land use systems may provide renewed opportunities for inhabitants to develop an awareness of their impacts and fundamental reliance on ecosystems. To better understand the causes, consequences, and possible remedies related to biophysical disconnectedness, new quantitative methods to assess the extent of regional biophysical human-nature connectedness are needed. To this end, we propose a new methodological framework that can be applied to assess biophysical human-nature connectedness in any region of the world.

Vegetation and soils field research data base: Experiment summaries

NASA Technical Reports Server (NTRS)

Biehl, L. L.; Daughtry, C. S. T.; Bauer, M. E.

1984-01-01

Understanding of the relationships between the optical, spectral characteristics and important biological-physical parameters of earth-surface features can best be obtained by carefully controlled studies over fields and plots where complete data describing the condition of targets are attainable and where frequent, timely spectral measurement can be obtained. Development of a vegetation and soils field research data base was initiated in 1972 at Purdue University's Laboratory for Applications of Remote Sensing and expanded in the fall of 1974 by NASA as part of LACIE. Since then, over 250,000 truck-mounted and helicopter-borne spectrometer/multiband radiometer observations have been obtained of more than 50 soil series and 20 species of crops, grasses, and trees. These data are supplemented by an extensive set of biophysical and meteorological data acquired during each mission. The field research data form one of the most complete and best-documented data sets acquired for agricultural remote sensing research. Thus, they are well-suited to serve as a data base for research to: (1) quantiatively determine the relationships of spectral and biophysical characteristics of vegetation, (2) define future sensor systems, and (3) develop advanced data analysis techniques.

Cell refractive index for cell biology and disease diagnosis: past, present and future.

PubMed

Liu, P Y; Chin, L K; Ser, W; Chen, H F; Hsieh, C-M; Lee, C-H; Sung, K-B; Ayi, T C; Yap, P H; Liedberg, B; Wang, K; Bourouina, T; Leprince-Wang, Y

2016-02-21

Cell refractive index is a key biophysical parameter, which has been extensively studied. It is correlated with other cell biophysical properties including mechanical, electrical and optical properties, and not only represents the intracellular mass and concentration of a cell, but also provides important insight for various biological models. Measurement techniques developed earlier only measure the effective refractive index of a cell or a cell suspension, providing only limited information on cell refractive index and hence hindering its in-depth analysis and correlation. Recently, the emergence of microfluidic, photonic and imaging technologies has enabled the manipulation of a single cell and the 3D refractive index of a single cell down to sub-micron resolution, providing powerful tools to study cells based on refractive index. In this review, we provide an overview of cell refractive index models and measurement techniques including microfluidic chip-based techniques for the last 50 years, present the applications and significance of cell refractive index in cell biology, hematology, and pathology, and discuss future research trends in the field, including 3D imaging methods, integration with microfluidics and potential applications in new and breakthrough research areas.

Crystallization, Preliminary X-ray Analysis and Biophysical Characterization of HPr Kinase/Phosphatase of Mycoplasma pneumoniae

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

Steinhauer, K.

2002-01-01

The Mycoplasma pneumoniae HPr kinase/phosphatase (HPrK/P) is a member of a large family of enzymes which are central to carbon regulation in Gram-positive bacteria. The full-length M. pneumonia HPrK/P was crystallized from solutions of polyethylene glycol 8000 and KCl or NaCl which also contained the non-hydrolysable ATP analog adenosine 5'-[{beta},{gamma}-methylene]triphosphate (AMPPCP). The crystals belong to the orthorhombic space group P2{sub 1}2{sub 1}2{sub 1}, with unit-cell parameters a = 117.1, b = 127.7, c = 170.7 {angstrom}. A complete X-ray intensity data set has been collected and processed to 2.50 {angstrom} resolution. The slow self-rotation function revealed the presence of amore » sixfold axis. Dynamic light-scattering (DLS) experiments indicated a molecular weight of 197 kDa for HPrK/P in the absence of AMPPCP and of 217 kDa in the presence of the ATP analog. Thus, the biophysical and crystallographic data suggest that HPrK/P is a functional hexamer that undergoes an ATP-binding-induced conformational change.« less

Autocrine signal transmission with extracellular ligand degradation

NASA Astrophysics Data System (ADS)

Muratov, C B; Posta, F; Shvartsman, S Y

2009-03-01

Traveling waves of cell signaling in epithelial layers orchestrate a number of important processes in developing and adult tissues. These waves can be mediated by positive feedback autocrine loops, a mode of cell signaling where binding of a diffusible extracellular ligand to a cell surface receptor can lead to further ligand release. We formulate and analyze a biophysical model that accounts for ligand-induced ligand release, extracellular ligand diffusion and ligand-receptor interaction. We focus on the case when the main mode for ligand degradation is extracellular and analyze the problem with the sharp threshold positive feedback nonlinearity. We derive expressions that link the speed of propagation and other characteristics of traveling waves to the parameters of the biophysical processes, such as diffusion rates, receptor expression level, etc. Analyzing the derived expressions we found that traveling waves in such systems can exhibit a number of unusual properties, e.g. non-monotonic dependence of the speed of propagation on ligand diffusivity. Our results for the fully developed traveling fronts can be used to analyze wave initiation from localized perturbations, a scenario that frequently arises in the in vitro models of epithelial wound healing, and guide future modeling studies of cell communication in epithelial layers.

A Fuzzy Cognitive Model of aeolian instability across the South Texas Sandsheet

NASA Astrophysics Data System (ADS)

Houser, C.; Bishop, M. P.; Barrineau, C. P.

2014-12-01

Characterization of aeolian systems is complicated by rapidly changing surface-process regimes, spatio-temporal scale dependencies, and subjective interpretation of imagery and spatial data. This paper describes the development and application of analytical reasoning to quantify instability of an aeolian environment using scale-dependent information coupled with conceptual knowledge of process and feedback mechanisms. Specifically, a simple Fuzzy Cognitive Model (FCM) for aeolian landscape instability was developed that represents conceptual knowledge of key biophysical processes and feedbacks. Model inputs include satellite-derived surface biophysical and geomorphometric parameters. FCMs are a knowledge-based Artificial Intelligence (AI) technique that merges fuzzy logic and neural computing in which knowledge or concepts are structured as a web of relationships that is similar to both human reasoning and the human decision-making process. Given simple process-form relationships, the analytical reasoning model is able to map the influence of land management practices and the geomorphology of the inherited surface on aeolian instability within the South Texas Sandsheet. Results suggest that FCMs can be used to formalize process-form relationships and information integration analogous to human cognition with future iterations accounting for the spatial interactions and temporal lags across the sand sheets.

Maturation State and Matrix Microstructure Regulate Interstitial Cell Migration in Dense Connective Tissues.

PubMed

Qu, Feini; Li, Qing; Wang, Xiao; Cao, Xuan; Zgonis, Miltiadis H; Esterhai, John L; Shenoy, Vivek B; Han, Lin; Mauck, Robert L

2018-02-19

Few regenerative approaches exist for the treatment of injuries to adult dense connective tissues. Compared to fetal tissues, adult connective tissues are hypocellular and show limited healing after injury. We hypothesized that robust repair can occur in fetal tissues with an immature extracellular matrix (ECM) that is conducive to cell migration, and that this process fails in adults due to the biophysical barriers imposed by the mature ECM. Using the knee meniscus as a platform, we evaluated the evolving micromechanics and microstructure of fetal and adult tissues, and interrogated the interstitial migratory capacity of adult meniscal cells through fetal and adult tissue microenvironments with or without partial enzymatic digestion. To integrate our findings, a computational model was implemented to determine how changing biophysical parameters impact cell migration through these dense networks. Our results show that the micromechanics and microstructure of the adult meniscus ECM sterically hinder cell mobility, and that modulation of these ECM attributes via an exogenous matrix-degrading enzyme permits migration through this otherwise impenetrable network. By addressing the inherent limitations to repair imposed by the mature ECM, these studies may define new clinical strategies to promote repair of damaged dense connective tissues in adults.

Dynamic analysis of modified transcutaneous lower blepharoplasty based on biochemical and biophysical principles.

PubMed

Liao, Chuh-Kai; Tsai, Feng-Chou; Fong, Tsorng-Harn; Huang, Chin-Ju; Shen, Yi-Chin; Ku, Yuan-Hao; Su, Ching-Hua

2013-12-01

In this study, we analyzed the key parameters of modified transcutaneous lower blepharoplasty based on multidisciplinary principles (biochemical findings and biophysical wrinkling theory). A total of 408 female patients received our subciliary lower blepharoplasty between March 2002 and January 2010. The severity of the eyebags (dynamic wrinkle numbers and prolapse) was evaluated through preoperative and postoperative photography, whereas the excised lower eyelid skin specimens from 56 patients were investigated with hematoxylin and eosin staining. The modified techniques produced significant improvements in the severity of eyebags in all age groups (P < 0.001). Poor surgical outcome was found to correlate significantly with preoperative dynamic wrinkle numbers (P < 0.001). Age, dynamic wrinkle numbers, and prolapse correlated significantly with dermal fiber density (P = 0.004, 0.000, and 0.000, respectively) but not epidermal, rete ridge, and dermal thickness or the number of rete ridges. In conclusion, modified transcutaneous lower blepharoplasty provides significant improvement to dynamic wrinkles and prolapse in the eyebags. Periorbital aging progressively disturbs the dermal compactness (fiber density) until the structure can no longer hold its integrity at the critical age (around the age of 40).

The systemic theory of living systems and relevance to CAM: the theory (Part III).

PubMed

Olalde Rangel, José A

2005-09-01

Western medical science lacks a solid philosophical and theoretical approach to disease cognition and therapeutics. My first two articles provided a framework for a humane medicine based on Modern Biophysics. Its precepts encompass modern therapeutics and CAM. Modern Biophysics and its concepts are presently missing in medicine, whether orthodox or CAM, albeit they probably provide the long sought explanation that bridges the abyss between East and West. Key points that differentiate Systemic from other systems' approaches are 'Intelligence', 'Energy' and the objective 'to survive'. The General System Theory (GST) took a forward step by proposing a departure from the mechanistic biological concept-of analyzing parts and processes in isolation-and brought us towards an organismic model. GST examines the system's components and results of their interaction. However, GST still does not go far enough. GST assumes 'Self-Organization' as a spontaneous phenomenon, ignoring a causative entity or central controller to all systems: Intelligence. It also neglects 'Survive' as the directional motivation common to any living system, and scarcely assigns 'Energy' its true inherent value. These three parameters, Intelligence, Energy and Survive, are vital variables to be considered, in our human quest, if we are to achieve a unified theory of life.

Is ET often oversimplified in hydrologic models? Using long records to elucidate unaccounted for controls on ET

NASA Astrophysics Data System (ADS)

Kelleher, Christa A.; Shaw, Stephen B.

2018-02-01

Recent research has found that hydrologic modeling over decadal time periods often requires time variant model parameters. Most prior work has focused on assessing time variance in model parameters conceptualizing watershed features and functions. In this paper, we assess whether adding a time variant scalar to potential evapotranspiration (PET) can be used in place of time variant parameters. Using the HBV hydrologic model and four different simple but common PET methods (Hamon, Priestly-Taylor, Oudin, and Hargreaves), we simulated 60+ years of daily discharge on four rivers in New York state. Allowing all ten model parameters to vary in time achieved good model fits in terms of daily NSE and long-term water balance. However, allowing single model parameters to vary in time - including a scalar on PET - achieved nearly equivalent model fits across PET methods. Overall, varying a PET scalar in time is likely more physically consistent with known biophysical controls on PET as compared to varying parameters conceptualizing innate watershed properties related to soil properties such as wilting point and field capacity. This work suggests that the seeming need for time variance in innate watershed parameters may be due to overly simple evapotranspiration formulations that do not account for all factors controlling evapotranspiration over long time periods.

Oregon transect: Comparison of leaf-level reflectance with canopy-level and modelled reflectance

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Baret, Frederic; Peterson, David L.

1992-01-01

The Oregon Transect Ecosystem Research (OTTER) project involves the collection of a variety of remotely-sensed and in situ measurements for characterization of forest biophysical and biochemical parameters. The project includes nine study plots located along an environmental gradient in west-central Oregon, extending from the Pacific coast inland approximately 300km. These plots represent a broad range in ecosystem structure and function. Within the OTTER project, the sensitivity of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) signal to absorption by foliar biochemicals is being examined. AVIRIS data were acquired over all plots in conjunction with the four OTTER Multi-sensor Aircraft Campaigns spanning the growing season. Foilage samples were gathered during each campaign for biochemical determination (at Ames Research Center), to estimate stand-level constituency at each plot. Directional-hemispheric leaf reflectance throughout the 400-2400nm region was measured in the laboratory as an aid to interpreting concurrent AVIRIS data. Obtaining leaf spectra in this manner reduces or eliminates the confounding influences of atmosphere, canopy architecture, and reflectance by woody components, understory, and exposed soils which are present in airborne observations. These laboratory spectra were compared to simulated spectra derived by inverting the PROSPECT leaf-level canopy reflectance derived from AVIRIS data by use of the LOWTRAN-7 atmospheric radiative-transfer model.

Metastability Gap in the Phase Diagram of Monoclonal IgG Antibody.

PubMed

Rowe, Jacob B; Cancel, Rachel A; Evangelous, Tyler D; Flynn, Rhiannon P; Pechenov, Sergei; Subramony, J Anand; Zhang, Jifeng; Wang, Ying

2017-10-17

Crystallization of IgG antibodies has important applications in the fields of structural biology, biotechnology, and biopharmaceutics. However, a rational approach to crystallize antibodies is still lacking. In this work, we report a method to estimate the solubility of antibodies at various temperatures. We experimentally determined the full phase diagram of an IgG antibody. Using the full diagram, we examined the metastability gaps, i.e., the distance between the crystal solubility line and the liquid-liquid coexistence curve, of IgG antibodies. By comparing our results to the partial phase diagrams of other IgGs reported in literature, we found that IgG antibodies have similar metastability gaps. Thereby, we present an equation with two phenomenological parameters to predict the approximate location of the solubility line of IgG antibodies with respect to their liquid-liquid coexistence curves. We have previously shown that the coexistence curve of an antibody solution can be readily determined by the polyethylene glycol-induced liquid-liquid phase separation method. Combining the polyethylene glycol-induced liquid-liquid phase separation measurements and the phenomenological equation in this article, we provide a general and practical means to predict the thermodynamic conditions for crystallizing IgG antibodies in the solution environments of interest. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Mammalian phospholipid homeostasis: evidence that membrane curvature elastic stress drives homeoviscous adaptation in vivo

PubMed Central

2016-01-01

Several theories of phospholipid homeostasis have postulated that cells regulate the molecular composition of their bilayer membranes, such that a common biophysical membrane parameter is under homeostatic control. Two commonly cited theories are the intrinsic curvature hypothesis, which states that cells control membrane curvature elastic stress, and the theory of homeoviscous adaptation, which postulates cells control acyl chain packing order (membrane order). In this paper, we present evidence from data-driven modelling studies that these two theories correlate in vivo. We estimate the curvature elastic stress of mammalian cells to be 4–7 × 10−12 N, a value high enough to suggest that in mammalian cells the preservation of membrane order arises through a mechanism where membrane curvature elastic stress is controlled. These results emerge from analysing the molecular contribution of individual phospholipids to both membrane order and curvature elastic stress in nearly 500 cellular compositionally diverse lipidomes. Our model suggests that the de novo synthesis of lipids is the dominant mechanism by which cells control curvature elastic stress and hence membrane order in vivo. These results also suggest that cells can increase membrane curvature elastic stress disproportionately to membrane order by incorporating polyunsaturated fatty acids into lipids. PMID:27534697

Proteomic identification of erythrocyte membrane protein deficiency in hereditary spherocytosis.

PubMed

Peker, Selen; Akar, Nejat; Demiralp, Duygu Ozel

2012-03-01

Hereditary spherocytosis (HS) is the most common congenital hemolytic anemia in Caucasians, with an estimated prevalence ranging from 1:2000 to 1:5000. The molecular defect in one of the erythrocytes (RBC) membrane proteins underlying HS like; spectrin-α, spectrin-β, ankyrin, band 3 and protein 4.2 that lead to membrane destabilization and vesiculation, may change the RBCs into denser and more rigid cells (spherocytes), which are removed by the spleen, leading to the development of hemolytic anemia. It is classified as mild, moderate and severe, according to the degree of the hemolytic anemia and the associated symptoms. Two-dimensional gel electrophoresis (2-DE) is potentially valuable method for studying heritable disorders as HS that involve membrane proteins. This separation technique of proteins based upon two biophysically unrelated parameters; molecular weight and charge, is a good option in clinical proteomics in terms of ability to separate complex mixtures, display post-translational modifications and changes after phosphorylation. In this study, we have used contemporary methods with some modifications for the solubilisation, separation and identification of erythrocyte membrane proteins in normal and in HS RBCs. Spectrin alpha and beta chain, ankyrin and band 3 proteins expression differences were found with PDQuest software 8.0.1. and peptide mass fingerprinting (PMF) analysis performed for identification of proteins in this study.

Mammalian phospholipid homeostasis: evidence that membrane curvature elastic stress drives homeoviscous adaptation in vivo.

PubMed

Dymond, Marcus K

2016-08-01

Several theories of phospholipid homeostasis have postulated that cells regulate the molecular composition of their bilayer membranes, such that a common biophysical membrane parameter is under homeostatic control. Two commonly cited theories are the intrinsic curvature hypothesis, which states that cells control membrane curvature elastic stress, and the theory of homeoviscous adaptation, which postulates cells control acyl chain packing order (membrane order). In this paper, we present evidence from data-driven modelling studies that these two theories correlate in vivo. We estimate the curvature elastic stress of mammalian cells to be 4-7 × 10(-12) N, a value high enough to suggest that in mammalian cells the preservation of membrane order arises through a mechanism where membrane curvature elastic stress is controlled. These results emerge from analysing the molecular contribution of individual phospholipids to both membrane order and curvature elastic stress in nearly 500 cellular compositionally diverse lipidomes. Our model suggests that the de novo synthesis of lipids is the dominant mechanism by which cells control curvature elastic stress and hence membrane order in vivo These results also suggest that cells can increase membrane curvature elastic stress disproportionately to membrane order by incorporating polyunsaturated fatty acids into lipids. © 2016 The Author(s).

Tympanal mechanics and neural responses in the ears of a noctuid moth

NASA Astrophysics Data System (ADS)

Ter Hofstede, Hannah M.; Goerlitz, Holger R.; Montealegre-Z, Fernando; Robert, Daniel; Holderied, Marc W.

2011-12-01

Ears evolved in many groups of moths to detect the echolocation calls of predatory bats. Although the neurophysiology of bat detection has been intensively studied in moths for decades, the relationship between sound-induced movement of the noctuid tympanic membrane and action potentials in the auditory sensory cells (A1 and A2) has received little attention. Using laser Doppler vibrometry, we measured the velocity and displacement of the tympanum in response to pure tone pulses for moths that were intact or prepared for neural recording. When recording from the auditory nerve, the displacement of the tympanum at the neural threshold remained constant across frequencies, whereas velocity varied with frequency. This suggests that the key biophysical parameter for triggering action potentials in the sensory cells of noctuid moths is tympanum displacement, not velocity. The validity of studies on the neurophysiology of moth hearing rests on the assumption that the dissection and recording procedures do not affect the biomechanics of the ear. There were no consistent differences in tympanal velocity or displacement when moths were intact or prepared for neural recordings for sound levels close to neural threshold, indicating that this and other neurophysiological studies provide good estimates of what intact moths hear at threshold.

Robust decoding of selective auditory attention from MEG in a competing-speaker environment via state-space modeling✩

PubMed Central

Akram, Sahar; Presacco, Alessandro; Simon, Jonathan Z.; Shamma, Shihab A.; Babadi, Behtash

2015-01-01

The underlying mechanism of how the human brain solves the cocktail party problem is largely unknown. Recent neuroimaging studies, however, suggest salient temporal correlations between the auditory neural response and the attended auditory object. Using magnetoencephalography (MEG) recordings of the neural responses of human subjects, we propose a decoding approach for tracking the attentional state while subjects are selectively listening to one of the two speech streams embedded in a competing-speaker environment. We develop a biophysically-inspired state-space model to account for the modulation of the neural response with respect to the attentional state of the listener. The constructed decoder is based on a maximum a posteriori (MAP) estimate of the state parameters via the Expectation Maximization (EM) algorithm. Using only the envelope of the two speech streams as covariates, the proposed decoder enables us to track the attentional state of the listener with a temporal resolution of the order of seconds, together with statistical confidence intervals. We evaluate the performance of the proposed model using numerical simulations and experimentally measured evoked MEG responses from the human brain. Our analysis reveals considerable performance gains provided by the state-space model in terms of temporal resolution, computational complexity and decoding accuracy. PMID:26436490

Replica exchange and expanded ensemble simulations as Gibbs sampling: simple improvements for enhanced mixing.

PubMed

Chodera, John D; Shirts, Michael R

2011-11-21

The widespread popularity of replica exchange and expanded ensemble algorithms for simulating complex molecular systems in chemistry and biophysics has generated much interest in discovering new ways to enhance the phase space mixing of these protocols in order to improve sampling of uncorrelated configurations. Here, we demonstrate how both of these classes of algorithms can be considered as special cases of Gibbs sampling within a Markov chain Monte Carlo framework. Gibbs sampling is a well-studied scheme in the field of statistical inference in which different random variables are alternately updated from conditional distributions. While the update of the conformational degrees of freedom by Metropolis Monte Carlo or molecular dynamics unavoidably generates correlated samples, we show how judicious updating of the thermodynamic state indices--corresponding to thermodynamic parameters such as temperature or alchemical coupling variables--can substantially increase mixing while still sampling from the desired distributions. We show how state update methods in common use can lead to suboptimal mixing, and present some simple, inexpensive alternatives that can increase mixing of the overall Markov chain, reducing simulation times necessary to obtain estimates of the desired precision. These improved schemes are demonstrated for several common applications, including an alchemical expanded ensemble simulation, parallel tempering, and multidimensional replica exchange umbrella sampling.

Stalk-length-dependence of the contractility of Vorticella convallaria

NASA Astrophysics Data System (ADS)

Gul Chung, Eun; Ryu, Sangjin

2017-12-01

Vorticella convallaria is a sessile protozoan of which the spasmoneme contracts on a millisecond timescale. Because this contraction is induced and powered by the binding of calcium ions (Ca2+), the spasmoneme showcases Ca2+-powered cellular motility. Because the isometric tension of V. convallaria increases linearly with its stalk length, it is hypothesized that the contractility of V. convallaria during unhindered contraction depends on the stalk length. In this study, the contractile force and energetics of V. convallaria cells of different stalk lengths were evaluated using a fluid dynamic drag model which accounts for the unsteadiness and finite Reynolds number of the water flow caused by contracting V. convallaria and the wall effect of the no-slip substrate. It was found that the contraction displacement, peak contraction speed, peak contractile force, total mechanical work, and peak power depended on the stalk length. The observed stalk-length-dependencies were simulated using a damped spring model, and the model estimated that the average spring constant of the contracting stalk was 1.34 nN µm-1. These observed length-dependencies of Vorticella’s key contractility parameters reflect the biophysical mechanism of the spasmonemal contraction, and thus they should be considered in developing a theoretical model of the Vorticella spasmoneme.

Exploring the energy landscapes of protein folding simulations with Bayesian computation.

PubMed

Burkoff, Nikolas S; Várnai, Csilla; Wells, Stephen A; Wild, David L

2012-02-22

Nested sampling is a Bayesian sampling technique developed to explore probability distributions localized in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence (marginal likelihood) of the model. The nested sampling algorithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering. In this article, we describe a parallel implementation of the nested sampling algorithm and its application to the problem of protein folding in a Gō-like force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations. We demonstrate the method by conducting folding simulations on a number of small proteins that are commonly used for testing protein-folding procedures. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high-level description of the potential energy surface for the protein folding simulations. These charts provide qualitative insights into both the folding process and the nature of the model and force field used. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Capability of Hyperspectral data in Spatial Variability Distribution of Chlorophyll and Water Stress in Rice Agriculture System

NASA Astrophysics Data System (ADS)

Moharana, S.; Dutta, S.

2016-12-01

Abstract : The mapping and analysis of spatial variability within the field is a challenging task. However, field variability of a single vegetation cover does not give satisfactory results mainly due to low spectral resolution and non-availability of remote sensing data. From the NASA Earth Observing-1 (EO-1) satellite data, spatial distribution of biophysical parameters like chlorophyll and relative water content in a rice agriculture system is carried out in the present study. Hyperion L1R product composed of 242 spectral bands with 30m spatial resolution was acquired for Assam, India. This high dimensional data is allowed for pre-processing to get an atmospherically corrected imagery. Moreover, ground based hyperspectral measurements are collected from experimental rice fields from the study site using hand held ASD spectroradiometer (350-1050 nm). Published indices specifically designed for chlorophyll (OASVI, mSR, and MTCI indices) and water content (WI and WBI indices) are selected based on stastical performance of the in-situ hyperspectral data. Index models are established for the respective biophysical parameters and observed that the aforementioned indices followed different linear and nonlinear relationships which are completely different from the published indices. By employing the presently developed relationships, spatial variation of total chlorophyll and water stress are mapped for a rice agriculture system from Hyperion imagery. The findings showed that, the variation of chlorophyll and water content ranged from 1.77-10.61mg/g and 40-90% respectively for the studied rice agriculture system. The spatial distribution of these parameters resulted from presently developed index models are well captured from Hyperion imagery and they have good agreement with observed field based chlorophyll (1.14-7.26 mg/g) and water content (60-95%) of paddy crop. This study can be useful in providing essential information to assess the paddy field heterogeneity in an agriculture system. Keywords: Paddy crop, vegetation index, hyperspectral data, chlorophyll, water content

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

Not Available

Summaries of research projects conducted during 1978 and 1979 are presented. Subject areas include research medicine, cancer research, environmental physiology, radiation biophysics, and structural biophysics. (ACR)

Role of perisynaptic parameters in neurotransmitter homeostasis - computational study of a general synapse

PubMed Central

Pendyam, Sandeep; Mohan, Ashwin; Kalivas, Peter W.; Nair, Satish S.

2015-01-01

Extracellular neurotransmitter concentrations vary over a wide range depending on the type of neurotransmitter and location in the brain. Neurotransmitter homeostasis near a synapse is achieved by a balance of several mechanisms including vesicular release from the presynapse, diffusion, uptake by transporters, non-synaptic production, and regulation of release by autoreceptors. These mechanisms are also affected by the glia surrounding the synapse. However, the role of these mechanisms in achieving neurotransmitter homeostasis is not well understood. A biophysical modeling framework was proposed to reverse engineer glial configurations and parameters related to homeostasis for synapses that support a range of neurotransmitter gradients. Model experiments reveal that synapses with extracellular neurotransmitter concentrations in the micromolar range require non-synaptic neurotransmitter sources and tight synaptic isolation by extracellular glial formations. The model was used to identify the role of perisynaptic parameters on neurotransmitter homeostasis, and to propose glial configurations that could support different levels of extracellular neurotransmitter concentrations. Ranking the parameters based on their effect on neurotransmitter homeostasis, non-synaptic sources were found to be the most important followed by transporter concentration and diffusion coefficient. PMID:22460547

Modelling of Molecular Structures and Properties in Physical Chemistry and Biophysics, Forty-Fourth International Meeting (Modelisation des Structures et Proprietes Moleculaires en Chimie Physique et en Biophysique, Quarante- Quatrieme Reunion Internationale)

DTIC Science & Technology

1989-09-01

pyridone).Previous work on, py/ridimum, pyrazinjumn or pyrimidi im salts Koon 2 -pyrimloone and 2 - pyrimidone salts [43j have shown that some...forces. Acct . r ~[U... •K;.i. LJ , ’ 0, ’’ .t_I ..- .It . ( :.. 2 A VIBRATIONAL MOLECULAR FORCE FIELD FOR .ACROMOLECULA-R MODELLI= Gerard VERGOTENi...microscopic point of view are (1) understanding, ( 2 ) interpretation of experimental results, (3) semiquantitative estimates of experimental results and (4

LAI, FAPAR and FCOVER products derived from AVHRR long time series: principles and evaluation

NASA Astrophysics Data System (ADS)

Verger, A.; Baret, F.; Weiss, M.; Lacaze, R.; Makhmara, H.; Pacholczyk, P.; Smets, B.; Kandasamy, S.; Vermote, E.

2012-04-01

Continuous and long term global monitoring of the terrestrial biosphere has draught an intense interest in the recent years in the context of climate and global change. Developing methodologies for generating historical data records from data collected with different satellite sensors over the past three decades by taking benefits from the improvements identified in the processing of the new generation sensors is a new central issue in remote sensing community. In this context, the Bio-geophysical Parameters (BioPar) service within Geoland2 project (http://www.geoland2.eu) aims at developing pre-operational infrastructures for providing global land products both in near real time and off-line mode with long time series. In this contribution, we describe the principles of the GEOLAND algorithm for generating long term datasets of three key biophysical variables, leaf area index (LAI), Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) and cover fraction (FCOVER), that play a key role in several processes, including photosynthesis, respiration and transpiration. LAI, FAPAR and FCOVER are produced globally from AVHRR Long Term Data Record (LTDR) for the 1981-2000 period at 0.05° spatial resolution and 10 days temporal sampling frequency. The proposed algorithm aims to ensure robustness of the derived long time series and consistency with the ones developed in the recent years, and particularly with GEOLAND products derived from VEGETATION sensor. The approach is based on the capacity of neural networks to learn a particular biophysical product (GEOLAND) from reflectances from another sensor (AVHRR normalized reflectances in the red and near infrared bands). Outliers due to possible cloud contamination or residual atmospheric correction are iteratively eliminated. Prior information based on the climatology is used to get more robust estimates. A specific gap filing and smoothing procedure was applied to generate continuous and smooth time series of decadal products. Finally, quality assessment information as well as tentative quantitative uncertainties were proposed. The comparison of the resulting AVHRR LTDR products with actual GEOLAND series derived from VEGETATION demonstrates that they are very consistent, providing continuous time series of global observations of LAI, FAPAR and FCOVER for the last 30-year period, with continuation after 2011.

A multi-sensor method for in-situ quantification of multiple biodiversity and ecosystem service indicators in wetland vegetation

NASA Astrophysics Data System (ADS)

Zlinszky, András; Prager, Katharina; Koma, Zsófia

2017-04-01

Biodiversity and ecosystem services are in the focus of biogeosciences research and conservation management worldwide. However, their quantification is notoriously difficult. Since full coverage of biodiversity and/or ecosystem services is unfeasible due to their complexity, indicators are recommended: biophysical quantities that are measureable and are expected to be closely related to biodiversity or to ecosystem processes. Nevertheless, many biodiversity and ecosystem service assessments are based on upscaling very few (if any) in-situ measurements using models driven by basic land cover data. Also, many assessments select only a single or very few indicators, which then does not enable analysis of trade-offs and interconnections. Here we propose a system of simple yet reliable field measurements, based on basic sensors, measurements, imaging and sampling technology, suitable for quantitatively representing many components of biodiversity and ecosystem services in emergent wetland vegetation. Along a transect from open water to the shore, sampling stations are laid out that include water temperature, air temperature and humidity sensors, zenith facing photographs and pole contact counts of vegetation in height intervals. Additionally, for some of these stations, small quadrats of vegetation are harvested, separated to individual species and weighed in height intervals above ground/water. Underwater surface of vegetation is estimated by counting stalks and registering average diameter. Finally, decomposition is quantified by leaving a standard amount of biomass in a plastic net bag and re-weighing it a year later. This system allows measuring alpha and beta diversity together with vertical structural diversity, leaf area (as a proxy of shading and pollution absorbtion), biomass (as a proxy of carbon sequestration), underwater surface (as a proxy of fish population sustaining), microclimate influence and soil provision. The necessary tools are temperature and humidity sensors, field scales, pruning shears, plastic net bags, measuring poles (for water depth), a digital camera and a GPS; all small and lightweight enough to be carried and operated by one person under wetland field conditions. Additionally, such measurements are suitable for remote sensing-based direct upscaling of biophysical parameters to create area-covering maps of biodiversity and ecosystem service indicators.

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

Liu, Y.; Liu, Z.; Zhang, S.

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less