Some hydrophysical and hydrochemical parameters of the upper part of the hydrogen sulfide zone in the Black Sea, September 11-22, 1994

Features of spatial variability of hydrogen sulfide in the northeastern part of the Black Sea are estimated. Some technical aspects of H2S concentration determination in the anoxic zone are discussed: in its upper part at H2S concentration <30 µmol/l, the photometric method is recommended, while for deeper layers the iodometric method should be used. With linearity of vertical distribution of hydrogen sulfide and ammonium taken into account their vertical gradients are estimated as 0.49+/-0.04 µmol/m and 0.19+/-0.06 µmol/m respectively. It is shown that the upper boundary of the H2S layer corresponds to the isopycnal surface with Sigma_t = 16.19+/-0.05 arbitrary units. Special attention is paid to relationship of hydrogen sulfide distribution with hydrophysical features in the region under study, in particular in the coastal zone. It is shown that hydrodynamic conditions control spatial distribution of hydrogen sulfide. On the basis of isopycnal treatment of the H2S field existence of a coastal convergence zone is proved, and peculiarities are recognized of vertical circulation in the main Black Sea gyre and coastal anticyclonic eddies; here hydrogen sulfide serves as a tracer of hydrophysical mixing processes.

(Table 4) Estimated surface water phosphate concentrations for the past 200 kyr at the location of sediment core GeoB1016-3

We compared ocean atlas values of surface water [PO4]3- and [CO2(aq)] against the carbon isotopic fractionation (ep) of alkenones obtained from surface sediments of the South Atlantic and the central Pacific (Pacific data are from Pagani et al. 2002, doi:10.1029/2002PA000756). We observed a positive correlation between ep and 1/[CO2(aq)], which is opposite of what would be expected if the concentration of CO2(aq) were the major factor controlling the carbon isotopic fractionation of C37:2 alkenones. Instead, we found inverse relationships between ep and [PO4]3- for the two ocean basins (for the Atlantic, ep = -4.6*[PO4]3- + 15.1, R = 0.76; for the Pacific, ep = -4.1*[PO4]3- + 13.7, R = 0.64), suggesting that ep is predominantly controlled by growth rate, which in turn is related to nutrient concentration. The similarity of the slopes implies that a general relationship between both parameters may exist. Using the relationship obtained from the South Atlantic, we estimated surface water nutrient concentrations for the past 200,000 years from a deep-sea sediment core recovered off Angola. Low ep values, indicating high nutrient concentrations, coincide with high contents of total organic carbon and C37 alkenones, low surface water temperatures, and decreased bulk d15N values, suggesting an increased upwelling of nutrient-rich cool subsurface waters as the main cause for the observed ep decrease.

Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images

Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters.

Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images

Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (Λ1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates

Fractal scaling of apparent soil moisture estimated from vertical planesof Vertisol pit images

Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak? digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ?373 ?m of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (?1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates.

Maximum Likelihood Estimation of Modal Parameters in Structures Using the Expectation Maximization Algorithm

This paper presents a time-domain stochastic system identification method based on maximum likelihood estimation (MLE) with the expectation maximization (EM) algorithm. The effectiveness of this structural identification method is evaluated through numerical simulation in the context of the ASCE benchmark problem on structural health monitoring. The benchmark structure is a four-story, two-bay by two-bay steel-frame scale model structure built in the Earthquake Engineering Research Laboratory at the University of British Columbia, Canada. This paper focuses on Phase I of the analytical benchmark studies. A MATLAB-based finite element analysis code obtained from the IASC-ASCE SHM Task Group web site is used to calculate the dynamic response of the prototype structure. A number of 100 simulations have been made using this MATLAB-based finite element analysis code in order to evaluate the proposed identification method. There are several techniques to realize system identification. In this work, stochastic subspace identification (SSI)method has been used for comparison. SSI identification method is a well known method and computes accurate estimates of the modal parameters. The principles of the SSI identification method has been introduced in the paper and next the proposed MLE with EM algorithm has been explained in detail. The advantages of the proposed structural identification method can be summarized as follows: (i) the method is based on maximum likelihood, that implies minimum variance estimates; (ii) EM is a computational simpler estimation procedure than other optimization algorithms; (iii) estimate more parameters than SSI, and these estimates are accurate. On the contrary, the main disadvantages of the method are: (i) EM algorithm is an iterative procedure and it consumes time until convergence is reached; and (ii) this method needs starting values for the parameters. Modal parameters (eigenfrequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using both the SSI method and the proposed MLE + EM method. The numerical results show that the proposed method identifies eigenfrequencies, damping ratios and mode shapes reasonably well even in the presence of 10% measurement noises. These modal parameters are more accurate than the SSI estimated modal parameters.

Estimating the modal parameters from multiple measurement setups using a joint state space model

Computing the modal parameters of structural systems often requires processing data from multiple non-simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors, which are fixed for all measurements, while the other sensors change their position from one setup to the next. One possibility is to process the setups separately resulting in different modal parameter estimates for each setup. Then, the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global mode shapes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a new state space model that processes all setups at once. The result is that the global mode shapes are obtained automatically, and only a value for the natural frequency and damping ratio of each mode is estimated. We also investigate the estimation of this model using maximum likelihood and the Expectation Maximization algorithm, and apply this technique to simulated and measured data corresponding to different structures.

The estimation of statistical parameters for local alignment score distributions

The distribution of optimal local alignment scores of random sequences plays a vital role in evaluating the statistical significance of sequence alignments. These scores can be well described by an extreme-value distribution. The distribution’s parameters depend upon the scoring system employed and the random letter frequencies; in general they cannot be derived analytically, but must be estimated by curve fitting. For obtaining accurate parameter estimates, a form of the recently described ‘island’ method has several advantages. We describe this method in detail, and use it to investigate the functional dependence of these parameters on finite-length edge effects.

Productive parameters of seawater and epipelagic plankton and mesozooplankton biomass at stations of R/V Akademik Mstislav Keldysh during 1994-1998

Calculated and measured estimations of biomass of small (<3 mm), large (3-30 mm), and total zooplankton were verified (compared). These integral parameters of epipelagic communities were estimated by two methods. We used previously obtained regression equations, which correlate these parameters with water transparency. Measured values of aforesaid parameters were compared with their mean values in waters of different productivity estimated from NASA satellite maps. We compared data collected at fifteen stations in September-December in regions of different productivity in the North Atlantic. In warm regions (to the south of 40°N) measured and calculated values coincide well. In boreal regions in autumn bulk of mesozooplankton descends to deep layers due to seasonal migrations; hence correlation between measured and calculated values is disrupted. It is evident that correlation between water transparency and mesozooplankton biomass (integral index of water productivity) obtained before should be corrected for seasonal variations.

Parameters of the Earths orbit for the last 5 Million years in 1 kyr resolution

New values for the astronomical parameters of the Earth's orbit and rotation (eccentricity, obliquity and precession) are proposed for paleoclimatic research related to the Late Miocene, the Pliocene and the Quaternary. They have been obtained from a numerical solution of the Lagrangian system of the planetary point masses and from an analytical solution of the Poisson equations of the Earth-Moon system. The analytical expansion developed in this paper allows the direct determination of the main frequencies with their phase and amplitude. Numerical and analytical comparisons with the former astronomical solution BER78 are performed so that the accuracy and the interval of time over which the new solution is valid can be estimated. The corresponding insolation values have also been computed and compared to the former ones. This analysis leads to the conclusion that the new values are expected to be reliable over the last 5 Ma in the time domain and at least over the last 10 Ma in the frequency domain.

Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel((R))

This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel((R)) spreadsheet was implemented with the use of Solver((R)) and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

Genetic parameters and predicted response to selection for lean growth in an Australian commercial nucleus pig herd

Genetic parameters for performance traits in a pig population were estimated using a multi-trait derivative-free REML algorithm. The 2590 total data included 922 restrictively fed male and 1668 ad libitum fed female records. Estimates of heritability (standard error in parentheses) were 0.25 (0.03), 0.15 (0.03), and 0.30 (0.05) for lifetime daily gain, test daily gain, and P2-fat depth in males, respectively; and 0.27 (0.04) and 0.38 (0.05) for average daily gain and P2-fat depth in females, respectively. The genetic correlation between P2-fat depth and test daily gain in males was -0.17 (0.06) and between P2-fat and lifetime average daily gain in females 0.44 (0.09). Genetic correlations between sexes were 0.71 (0.11) for average daily gain and -0.30 (0.10) for P2-fat depth. Genetic response per standard deviation of selection on an index combining all traits was predicted at $AU120 per sow per year. Responses in daily gain and backfat were expected to be higher when using only male selection than when using only female selection. Selection for growth rate in males will improve growth rate and carcass leanness simultaneously.