A computational method for determining segmental and overall geothermal gradients and geothermal heat flow values

A new computational method is presented which calculates geothermal heat flow values and geothermal gradients with more precision than permitted by previously published techniques. The data required are: geothermal temperature at a known depth, mean surface temperature, the rock types in the stratigraphic column and the thermal resistivity values for the different types of rocks. This method is valuable in areas that have no measured gradient values. Basic equation used was the Fourier heat transfer equation where is heat flux in μcal/(cm² s), ρ_i is thermal resistivity (°C s cm/μcal) and ∂T/∂x is the x component of the temperature gradient (°C/cm). The thermal resistivity was allowed to vary linearly with temperature ρ_i = ρ_i^o [1 + K_i (T − 30)] where ρ_i is thermal resistivity of the lithographic segment «iå at a temperature T, ρ_i^o is thermal resistivity at 30°C and K_i is the temperature coefficient of thermal resistivity. The procedure consisted of integrating the combined equation for heat flux in terms of temperature dependent resistivity.Two iterative solutions were used to simplify the calculations: exact and approximate. The heat flux for each well was assumed to be 1.0 HFU and segmental temperatures were calculated from the bottom (arbitrarily) up, until a surface temperature was obtained. The calculated surface temperature could then be compared with the mean surface temperature (MST). Correction in the heat flux value was made until the calculated surface temperature and MST agreed. An analysis of three deep Appalachian test wells was made and the results showed the critical importance of lithographic ordering and the temperature dependence of thermal resistivity upon calculated geothermal quantities.     

High-power CW operation of AlGaInP laser-diode array at 640 nm

Visible-emitting high-power laser bars are investigated at an emission wavelength of 640 nm. AlGaInP/GaInP, single tensile-strained quantum well, separate confinement heterostructures are fabricated into one cm long laser bars using a 0.7 fill factor. The low threshold current of the diode, combined with the aggressive heatsinking of a silicon microchannel cooler has resulted in more than 12 W of continuous wave output power     

A sub-micron metallic electrothermal gripper

We report the design, fabrication, and characterization of a multiple bent beam, sub-micron metallic electrothermal gripper. A bottom electroplating mold for electrodes was patterned using electron beam lithography in an SU-8, followed by nickel electroplating. A top electroplating mold for a sub-micron metallic gripper with high aspect ratio bent beams (thickness of 1 μm, width of 350 nm) was prepared using electron beam lithography in a polymethyl methacrylate (PMMA), followed by nickel electroplating and dry release of the top and bottom molds. The sub-micron gripper was characterized using a nanomanipulator system installed in a dual column scanning electron microscopy/focused ion beam system. The ability of the jaw to close up to 1.39 μm displacement with high precision and reliability has been reproducibly observed at an applied current of 28 mA, corresponding to the maximum power consumption of 11.2 mW. Finite element modeling displacement results performed using ANSYS for effective bent beam widths of 370 nm showed a good agreement with the measured displacement results. The sub-micron gripper demonstrated herein will enable the reproducible manipulations with nano-scale resolution displacement and could provide an effective means of interface between nano-scale objects and the micro/macro scale robotic systems.     

Towards red‐edge positions less sensitive to canopy biophysical parameters for leaf chlorophyll estimation using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) simulated data

Several methods for extracting the chlorophyll sensitive red‐edge position (REP) from hyperspectral data are reported in literature. This study is a continuation of a recent paper published as ‘A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method’. The method was validated experimentally for estimation of foliar nitrogen concentrations of rye, maize and mixed grass/herb. The objective of this study was to test the utility of the linear extrapolation method under different conditions including variable canopy biophysical parameters, solar zenith angle, sensor noise and spectral bandwidth. REPs were extracted from synthetic canopy spectra that were simulated using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) radiative transfer models. REPs extracted by the linear extrapolation method involving wavebands at 680, 694, 724 and 760 nm produced the highest correlation (R ² = 0.75) with leaf chlorophyll content with minimal effects of leaf and canopy biophysical confounders (leaf area index, leaf inclination distribution and leaf dry matter content) compared to traditional techniques including the linear interpolation, inverted Gaussian modelling and polynomial fitting techniques. In addition, the new technique is insensitive to changes in solar zenith angle. However, the advantage of using the linear extrapolation method compared to the various alternative methods diminishes with increasing sensor noise and decreasing spectral resolution. In summary, the linear extrapolation technique confirms its high potential for leaf chlorophyll estimation. The efficacy of the technique under field conditions needs to be established.     

Estimating tropical forest biomass more accurately by integrating ALOS PALSAR and Landsat-7 ETM+ data

Integration of multisensor data provides the opportunity to explore benefits emanating from different data sources. A fusion between fraction images derived from spectral mixture analysis of Landsat-7 ETM+ and phased array L-band synthetic aperture radar (PALSAR) is introduced. The aim of this fusion is to improve the estimation accuracy of above-ground biomass (AGB) in lowland mixed dipterocarp forest. Spectral mixture analysis was applied to decompose a mixture of spectral components of Landsat-7 ETM+ into vegetation, soil, and shade fractions. These fraction images were integrated with PALSAR data using the discrete wavelet transform (DWT) and Brovey transform. As a comparison, spectral reflectance of Landsat-7 ETM+ was fused directly with PALSAR data. Backscatter of horizontal–horizontal and horizontal–vertical polarizations was also used to estimate AGB. Forest inventory was carried out in 77 randomly distributed plots, the data being used for either model development or validation. A local allometric equation was applied to calculate AGB per plot. Regression models were developed by integrating field measurements of 50 sample plots with remotely sensed data, e.g. fraction images, reflectance of Landsat-7 ETM+, and PALSAR data. The models developed were validated using 27 independent sample plots. The results showed that not all fused images significantly improved the accuracy of AGB estimation. The model based on Brovey transform using the reflectance of Landsat-7ETM+ and PALSAR produced an R² of only 0.03–0.10. By contrast, fusion between PALSAR data and fraction images using Brovey transform improved the accuracy of R² to 0.33–0.46. Further improvement in the accuracy of estimating AGB was observed when DWT was applied to integrate PALSAR with the reflectance of Landsat-7ETM+ (R² = 0.69–0.72) and PALSAR with fraction images (R² = 0.70–0.75).     

Comparing direct image and wavelet transform-based approaches to analysing remote sensing imagery for predicting wildlife distribution

In this study we tested the ability to predict the probability of elephant (Loxodonta africana) presence in an agricultural landscape of Zimbabwe based on three methods of measuring the spatial heterogeneity in vegetation cover, where vegetation cover was measured using the Landsat Thematic Mapper (TM)-derived normalized difference vegetation index (NDVI). The three methods of measuring spatial heterogeneity were: one wavelet-derived spatial heterogeneity measure; and two direct image measures. The wavelet-derived spatial heterogeneity measure consists of the intensity, which measures the maximum contrast in the vegetation cover, and the dominant scale, which determines the scale at which this intensity occurs. The two direct image measures use the NDVI average and the NDVI coefficient of variation (NDVIcv). The results show that the wavelet-derived spatial heterogeneity significantly explains 80% of the variance in elephant presence compared with 60% and 48% variance explained by the NDVI average and NDVIcv, respectively. We conclude that the wavelet transform-based approach predicts elephant distribution better than the direct image measures of spatial heterogeneity.     

Displaying remotely sensed vegetation dynamics along natural gradients for ecological studies

Normalized difference vegetation index (NDVI) datasets are growing in popularity to represent vegetation dynamics in ecological studies. Because of its multidimensional nature, it is difficult to visualise the spatial and temporal components of NDVI datasets simultaneously. This letter presents a method to display vegetation dynamics as captured by the NDVI along natural gradients and to visualise and test correlations between vegetation phenology and animal movement.     

Electrothermal properties and modeling of polysilicon microthermal actuators

This work addresses a range of issues on modeling electrothermal microactuators, including the physics of temperature dependent material properties and Finite Element Analysis (FEA) modeling techniques. Electrical and thermal conductivity are a nonlinear function of temperature that can be explained with electron and phonon transport models, respectively. Parametric forms of these equations are developed for polysilicon and a technique to extract these parameters from experimental data is given. A modeling technique to capture the convective and conductive cooling effects on a thermal actuator in air is then presented. Using this modeling technique and the established polysilicon material properties, simulation results are compared with measured actuator responses. Both static and transient analyzes have been performed on two styles of actuators and the results compare well with measured data.     

Saccharomyces cerevisiae boulardii CNCM I-1079 affects health,growth, and fecal microbiota in milk-fed veal calves

The objective of this study was to investigate the effect of one specific strain of yeast, Saccharomyces cerevisiae boulardii CNCM I-1079 (SCB), on the growth performance, health, and fecal bacterial profile of veal calves. A total of 84 animals were enrolled in an experiment at a commercial veal farm for a total of 7 wk. Calves were fed twice a day with a milk replacer meal during the entire experiment and were randomly assigned to receive daily either SCB supplementation (10 × 10⁹ cfu/d) or a placebo (CON). Individual feed intake and body weight were monitored on a daily and weekly basis, respectively. Fecal samples were collected at arrival to the veal facility (wk 0) and additional samples were taken on d 14 (wk 2) and d 49 (wk 7). These samples were subjected to 16S rRNA gene amplicon sequencing using Illumina MiSeq (Illumina Inc., San Diego, CA) to examine the bacterial profiles and real-time quantitative PCR to quantify Saccharomyces cerevisiae and specific bacterial groups. The significant increase of S. cerevisiae in the feces of SCB calves at wk 2 and 7 compared with wk 0 (respectively 1.7 × 10⁷, 1.2 × 10⁷, and 2.2 × 10⁵ copy number of S. cerevisiae/g of feces) indicates a good survival of that yeast strain along the gastrointestinal tract. Supplementation of SCB did not improve overall growth performance with regard to average daily gain (ADG), final body weight, and feed intake. Nevertheless, a total of 69.1% of nonsupplemented calves had diarrhea and 28.6% experienced severe diarrhea, whereas 50.0% of the calves supplemented with SCB had diarrhea and 9.5% experienced severe diarrhea. With respect to antibiotic use, 89.7% of the diarrheic calves recorded in the CON group were treated, whereas only 66.7% of the SCB diarrheic calves received an antibiotic. In addition, diarrheic calves supplemented with SCB maintained an ADG similar to nondiarrheic animals, whereas the CON diarrheic calves had a significantly lower ADG in comparison with nondiarrheic CON calves. Fecalibacterium was the most predominant bacterial genus in fecal samples of nondiarrheic and diarrheic calves supplemented with SCB, whereas fecal microbiota was predominated by Collinsella in diarrheic calves from the CON group. Live yeast supplementation in milk replacer led to a decrease of diarrhea in milk-fed veal calves and the fecal microbiota of diarrheic calves maintained a healthy community similar to nondiarrheic animals, with Fecalibacterium being the predominant genus.