Structural and electrical properties of Fe-doped TiO2 thin films

The present study discusses the effect of iron doping in TiO2 thin films deposited by rf sputtering. Iron doping induces a structural transformation from anatase to rutile and electrical measurements indicate that iron acts as an acceptor impurity. Thermoelectric power measurement shows a transition between n-type and p-type electrical conduction for an iron concentration around 0.13 at.%. The highest p-type conductivity at room temperature achieved by iron doping was 10(-6) S m(-1).

Evaluation of drug-induced neurotoxicity based on metabolomics, proteomics and electrical activity measurements in complementary CNS in vitro models.

The present study was performed in an attempt to develop an in vitro integrated testing strategy (ITS) to evaluate drug-induced neurotoxicity. A number of endpoints were analyzed using two complementary brain cell culture models and an in vitro blood-brain barrier (BBB) model after single and repeated exposure treatments with selected drugs that covered the major biological, pharmacological and neuro-toxicological responses. Furthermore, four drugs (diazepam, cyclosporine A, chlorpromazine and amiodarone) were tested more in depth as representatives of different classes of neurotoxicants, inducing toxicity through different pathways of toxicity. The developed in vitro BBB model allowed detection of toxic effects at the level of BBB and evaluation of drug transport through the barrier for predicting free brain concentrations of the studied drugs. The measurement of neuronal electrical activity was found to be a sensitive tool to predict the neuroactivity and neurotoxicity of drugs after acute exposure. The histotypic 3D re-aggregating brain cell cultures, containing all brain cell types, were found to be well suited for OMICs analyses after both acute and long term treatment. The obtained data suggest that an in vitro ITS based on the information obtained from BBB studies and combined with metabolomics, proteomics and neuronal electrical activity measurements performed in stable in vitro neuronal cell culture systems, has high potential to improve current in vitro drug-induced neurotoxicity evaluation.

The borehole-fluid effect in electrical resistivity imaging

Fluid that fills boreholes in crosswell electrical resistivity investigations provides the necessary electrical contact between the electrodes and the rock formation but it is also the source of image artifacts in standard inversions that do not account for the effects of the boreholes. The image distortions can be severe for large resistivity contrasts between the rock formation and borehole fluid and for large borehole diameters. We have carried out 3D finite-element modeling using an unstructured-grid approach to quantify the magnitude of borehole effects for different resistivity contrasts, borehole diameters, and electrode configurations. Relatively common resistivity contrasts of 100:1 and borehole diameters of 10 and 20 cm yielded, for a bipole length of 5 m, apparent resistivity underestimates of approximately 12% and 32% when using AB-MN configurations and apparent resistivity overestimates of approximately 24% and 95% when using AM-BN configurations. Effects are generally more severe at shorter bipole spacings. We report the results obtained by either including or ignoring the boreholes in inversions of 3D field data from a test site in Switzerland, where approximately 10,000 crosswell resistivity-tomography measurements were made across six acquisition planes among four boreholes. Inversions of raw data that ignored the boreholes filled with low-resistivity fluid paradoxically produced high-resistivity artifacts around the boreholes. Including correction factors based on the modeling results fora ID model with and without the boreholes did not markedly improve the images. The only satisfactory approach was to use a 3D inversion code that explicitly incorporated the boreholes in the actual inversion. This new approach yielded an electrical resistivity image that was devoid of artifacts around the boreholes and that correlated well with coincident crosswell radar images.

Bio-electrical impedance analysis for estimation of fat-free mass and muscle mass in cystic fibrosis patients.

The nutritional status of cystic fibrosis (CF) patients has to be regularly evaluated and alimentary support instituted when indicated. Bio-electrical impedance analysis (BIA) is a recent method for determining body composition. The present study evaluates its use in CF patients without any clinical sign of malnutrition. Thirty-nine patients with CF and 39 healthy subjects aged 6-24 years were studied. Body density and mid-arm muscle circumference were determined by anthropometry and skinfold measurements. Fat-free mass was calculated taking into account the body density. Muscle mass was obtained from the urinary creatinine excretion rate. The resistance index was calculated by dividing the square of the subject's height by the body impedance. We show that fat-free mass, mid-arm muscle circumference and muscle mass are each linearly correlated to the resistance index and that the regression equations are similar for both CF patients and healthy subjects.

Brain energy consumption induced by electrical stimulation promotes systemic glucose uptake.

BACKGROUND: Controlled transcranial stimulation of the brain is part of clinical treatment strategies in neuropsychiatric diseases such as depression, stroke, or Parkinson's disease. Manipulating brain activity by transcranial stimulation, however, inevitably influences other control centers of various neuronal and neurohormonal feedback loops and therefore may concomitantly affect systemic metabolic regulation. Because hypothalamic adenosine triphosphate-sensitive potassium channels, which function as local energy sensors, are centrally involved in the regulation of glucose homeostasis, we tested whether transcranial direct current stimulation (tDCS) causes an excitation-induced transient neuronal energy depletion and thus influences systemic glucose homeostasis and related neuroendocrine mediators.METHODS: In a crossover design testing 15 healthy male volunteers, we increased neuronal excitation by anodal tDCS versus sham and examined cerebral energy consumption with (31)phosphorus magnetic resonance spectroscopy. Systemic glucose uptake was determined by euglycemic-hyperinsulinemic glucose clamp, and neurohormonal measurements comprised the parameters of the stress systems.RESULTS: We found that anodic tDCS-induced neuronal excitation causes an energetic depletion, as quantified by (31)phosphorus magnetic resonance spectroscopy. Moreover, tDCS-induced cerebral energy consumption promotes systemic glucose tolerance in a standardized euglycemic-hyperinsulinemic glucose clamp procedure and reduces neurohormonal stress axes activity.CONCLUSIONS: Our data demonstrate that transcranial brain stimulation not only evokes alterations in local neuronal processes but also clearly influences downstream metabolic systems regulated by the brain. The beneficial effects of tDCS on metabolic features may thus qualify brain stimulation as a promising nonpharmacologic therapy option for drug-induced or comorbid metabolic disturbances in various neuropsychiatric diseases.

Heated Optical Fiber for Distributed Soil-Moisture Measurements: A Lysimeter Experiment

An Actively Heated Fiber Optics (AHFO) method to estimate soil moisture is tested and the analysis technique improved on. The measurements were performed in a lysimeter uniformly packed with loam soil with variable water content profiles. In the first meter of the soil profi le, 30 m of fiber optic cable were installed in a 12 loops coil. The metal sheath armoring the fiber cable was used as an electrical resistance heater to generate a heat pulse, and the soil response was monitored with a Distributed Temperature Sensing (DTS) system. We study the cooling following three continuous heat pulses of 120 s at 36 W m(-1) by means of long-time approximation of radial heat conduction. The soil volumetric water contents were then inferred from the estimated thermal conductivities through a specifically calibrated model relating thermal conductivity and volumetric water content. To use the pre-asymptotic data we employed a time correction that allowed the volumetric water content to be estimated with a precision of 0.01-0.035 (m(3) m(-3)). A comparison of the AHFO measurements with soil-moisture measurements obtained with calibrated capacitance-based probes gave good agreement for wetter soils [discrepancy between the two methods was less than 0.04 (m(3) m(-3))]. In the shallow drier soils, the AHFO method underestimated the volumetric water content due to the longertime required for the temperature increment to become asymptotic in less thermally conductive media [discrepancy between the two methods was larger than 0.1 (m(3) m(-3))]. The present work suggests that future applications of the AHFO method should include longer heat pulses, that longer heating and cooling events are analyzed, and, temperature increments ideally be measured with higher frequency.

A tutorial review of electrical neuroimaging from group-average to single-trial event-related potentials.

This tutorial review details some of the recent advances in signal analyses applied to event-related potential (ERP) data. These "electrical neuroimaging" analyses provide reference-independent measurements of response strength and response topography that circumvent statistical and interpretational caveats of canonical ERP analysis methods while also taking advantage of the greater information provided by high-density electrode montages. Electrical neuroimaging can be applied across scales ranging from group-averaged ERPs to single-subject and single-trial datasets. We illustrate these methods with a tutorial dataset and place particular emphasis on their suitability for studies of clinical and/or developmental populations.

A non-linear Bayesian approach for upscaling local-scale hydraulic conductivity measurements based on local- and regional-scale geophysical data

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Spectral induced polarization: Laboratory measurements on sandy quartz samples of varied pore characteristics

Understanding the influence of pore space characteristics on the hydraulic conductivity and spectral induced polarization (SIP) response is critical for establishing relationships between the electrical and hydrological properties of surficial sedimentary deposits. Here, we present the results of laboratory SIP measurements on saturated quartz samples with granulometric characteristics ranging from fine sand to fine gravel. We alter the pore characteristics using three principal methods: (i) variation of the grain sizes, (ii) changing the degree of compaction, and (iii) changing the level of sorting. We then examine how these changes affect both the SIP response and the hydraulic conductivity. In general, the results indicate a clear connection between the applied changes in pore characteristics and the SIP response. In particular, we observe a systematic correlation between the hydraulic conductivity and the relaxation time of the Cole-Cole model describing the observed SIP effect for the whole range of considered grain sizes.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities.

Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

Activation of electrical triggers of atrial fibrillation in hyperthyroidism.

CONTEXT: A shortening of the atrial refractory period has been considered as the main mechanism for the increased risk of atrial fibrillation in hyperthyroidism. However, other important factors may be involved. OBJECTIVE: Our objective was to determine the activity of abnormal supraventricular electrical depolarizations in response to elevated thyroid hormones in patients without structural heart disease. PATIENTS AND DESIGN: Twenty-eight patients (25 females, three males, mean age 43+/-11 yr) with newly diagnosed and untreated hyperthyroidism were enrolled in a prospective trial after exclusion of heart disease. Patients were followed up for 16 +/- 6 months and studied at baseline and 6 months after normalization of serum TSH levels. MAIN OUTCOME MEASURES: The incidence of abnormal premature supraventricular depolarizations (SVPD) and the number of episodes of supraventricular tachycardia was defined as primary outcome measurements before the start of the study. In addition, heart rate oscillations (turbulence) after premature depolarizations and heart rate variability were compared at baseline and follow-up. RESULTS: SVPDs decreased from 59 +/- 29 to 21 +/- 8 per 24 h (P = 0.003), very early SVPDs (so called P on T) decreased from 36 +/- 24 to 3 +/- 1 per 24 h (P < 0.0001), respectively, and nonsustained supraventricular tachycardias decreased from 22 +/- 11 to 0.5 +/- 0.2 per 24 h (P = 0.01) after normalization of serum thyrotropin levels. The hyperthyroid phase was characterized by an increased heart rate (93 +/- 14 vs. 79 +/- 8 beats/min, P < 0.0001) and a decreased turbulence slope (3.6 vs. 9.2, P = 0.003), consistent with decreased vagal tone. This was confirmed by a significant decrease of heart rate variability. CONCLUSION: Hyperthyroidism is associated with an increased supraventricular ectopic activity in patients with normal hearts. The activation of these arrhythmogenic foci by elevated thyroid hormones may be an important causal link between hyperthyroidism and atrial fibrillation.

Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

Single acquisition electrical property mapping based on relative coil sensitivities: A proof-of-concept demonstration.

PURPOSE: All methods presented to date to map both conductivity and permittivity rely on multiple acquisitions to compute quantitatively the magnitude of radiofrequency transmit fields, B1+. In this work, we propose a method to compute both conductivity and permittivity based solely on relative receive coil sensitivities ( B1-) that can be obtained in one single measurement without the need to neither explicitly perform transmit/receive phase separation nor make assumptions regarding those phases. THEORY AND METHODS: To demonstrate the validity and the noise sensitivity of our method we used electromagnetic finite differences simulations of a 16-channel transceiver array. To experimentally validate our methodology at 7 Tesla, multi compartment phantom data was acquired using a standard 32-channel receive coil system and two-dimensional (2D) and 3D gradient echo acquisition. The reconstructed electric properties were correlated to those measured using dielectric probes. RESULTS: The method was demonstrated both in simulations and in phantom data with correlations to both the modeled and bench measurements being close to identity. The noise properties were modeled and understood. CONCLUSION: The proposed methodology allows to quantitatively determine the electrical properties of a sample using any MR contrast, with the only constraint being the need to have 4 or more receive coils and high SNR. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Probabilistic electrical resistivity tomography of a CO2 sequestration analog

Electrical resistivity tomography (ERT) is a well-established method for geophysical characterization and has shown potential for monitoring geologic CO2 sequestration, due to its sensitivity to electrical resistivity contrasts generated by liquid/gas saturation variability. In contrast to deterministic inversion approaches, probabilistic inversion provides the full posterior probability density function of the saturation field and accounts for the uncertainties inherent in the petrophysical parameters relating the resistivity to saturation. In this study, the data are from benchtop ERT experiments conducted during gas injection into a quasi-2D brine-saturated sand chamber with a packing that mimics a simple anticlinal geological reservoir. The saturation fields are estimated by Markov chain Monte Carlo inversion of the measured data and compared to independent saturation measurements from light transmission through the chamber. Different model parameterizations are evaluated in terms of the recovered saturation and petrophysical parameter values. The saturation field is parameterized (1) in Cartesian coordinates, (2) by means of its discrete cosine transform coefficients, and (3) by fixed saturation values in structural elements whose shape and location is assumed known or represented by an arbitrary Gaussian Bell structure. Results show that the estimated saturation fields are in overall agreement with saturations measured by light transmission, but differ strongly in terms of parameter estimates, parameter uncertainties and computational intensity. Discretization in the frequency domain (as in the discrete cosine transform parameterization) provides more accurate models at a lower computational cost compared to spatially discretized (Cartesian) models. A priori knowledge about the expected geologic structures allows for non-discretized model descriptions with markedly reduced degrees of freedom. Constraining the solutions to the known injected gas volume improved estimates of saturation and parameter values of the petrophysical relationship. (C) 2014 Elsevier B.V. All rights reserved.

New measurements of energy expenditure and physical activity in chronic kidney disease.

The accurate estimation of total daily energy expenditure (TEE) in chronic kidney patients is essential to allow the provision of nutritional requirements; however, it remains a challenge to collect actual physical activity and resting energy expenditure in maintenance dialysis patients. The direct measurement of TEE by direct calorimetry or doubly labeled water cannot be used easily so that, in clinical practice, TEE is usually estimated from resting energy expenditure and physical activity. Prediction equations may also be used to estimate resting energy expenditure; however, their use has been poorly documented in dialysis patients. Recently, a new system called SenseWear Armband (BodyMedia, Pittsburgh, PA) was developed to assess TEE, but so far no data have been published in chronic kidney disease patients. The aim of this review is to describe new measurements of energy expenditure and physical activity in chronic kidney disease patients.