Effects of adding polyclonal antibody preparations on ruminal fermentation patterns and digestibility of cows fed different energy sources

Nine ruminally cannulated cows fed different energy sources were used to evaluate an avian-derived polyclonal antibody preparation (PAP-MV) against the specific ruminal bacteria Streptococcus bovis, Fusobacterium necrophorum, Clostridium aminophilum, Peptostreptococcus anaerobius, and Clostridium stick-landii and monensin (MON) on ruminal fermentation patterns and in vivo digestibility. The experimental design was three 3 x 3 Latin squares distinguished by the main energy source in the diet [dry-ground corn grain (CG), high-moisture corn silage (HMCS), or citrus pulp (CiPu)]. Inside each Latin square, animals received one of the feed additives per period [none (CON), MON, or PAP-MV]. Dry matter intake and ruminal fermentation variables such as pH, total short-chain fatty acids (tSCFA), which included acetate, propionate, and butyrate, as well as lactic acid and NH(3)-N concentration were analyzed in this trial. Total tract DM apparent digestibility and its fractions were estimated using chromic oxide as an external marker. Each experimental period lasted 21 d. Ruminal fluid sampling was carried out on the last day of the period at 0, 2, 4, 6, 8, 10, and 12 h after the morning meal. Ruminal pH was higher (P = 0.006) 4 h postfeeding in MON and PAP-MV groups when compared with CON. Acetate: propionate ratio was greater in PAP-MV compared with MON across sampling times. Polyclonal antibodies did not alter (P > 0.05) tSCFA, molar proportion of acetate and butyrate, or lactic acid and NH(3)-N concentration. Ruminal pH was higher (P = 0.01), 4 h postfeeding in CiPu diets compared with CG and HMCS. There was no interaction between feed additive and energy source (P > 0.05) for any of the digestibility coefficients analyzed. Starch digestibility was less (P = 0.008) in PAP-MV when compared with CON and MON. In relation to energy sources, NDF digestibility was greater (P = 0.007) in CG and CiPu vs. the HMCS diet. The digestibility of ADF was greater (P = 0.002) in CiPu diets followed by CG and HMCS. Feeding PAP-MV or monensin altered ruminal fermentation patterns and digestive function in cows; however, those changes were independent of the main energy source of the diet.

Clear cell odontogenic carcinoma: case report with immunohistochemical findings adding support to the challenging diagnosis

Clear cell odontogenic carcinoma (CCOC) is a rare odontogenic tumor associated with aggressive clinical behavior, metastasis, and low survival. We report a case of CCOC affecting the mandible of a 39-year-old man. The tumor presented a biphasic pattern composed of clear cell nests intermingled with eosinophilic cells and separated by collagenous stroma. Immunoreactivity to cytokeratin (CK), specifically AE1/AE3 and CK 8, 14, 18, and 19 was found, as well as to epithelial membrane antigen (EMA). The tumor cells were negative for S100 protein, CK 13, vimentin, smooth muscle actin, laminin and type IV collagen. Low labeling indices for the proliferation markers Ki-67 and proliferating cell nuclear antigen and to p53 protein might predict a favorable prognosis for the lesion. A surgical resection was performed, followed by adjuvant radiotherapy. A 2-year follow-up has shown no signs of recurrence. The significance of histochemical and immunohistochemical resources in the correct diagnosis of CCOC is analyzed.

The composite Euler method for stiff stochastic differential equations

In this paper we present the composite Euler method for the strong solution of stochastic differential equations driven by d-dimensional Wiener processes. This method is a combination of the semi-implicit Euler method and the implicit Euler method. At each step either the semi-implicit Euler method or the implicit Euler method is used in order to obtain better stability properties. We give criteria for selecting the semi-implicit Euler method or the implicit Euler method. For the linear test equation, the convergence properties of the composite Euler method depend on the criteria for selecting the methods. Numerical results suggest that the convergence properties of the composite Euler method applied to nonlinear SDEs is the same as those applied to linear equations. The stability properties of the composite Euler method are shown to be far superior to those of the Euler methods, and numerical results show that the composite Euler method is a very promising method. (C) 2001 Elsevier Science B.V. All rights reserved.

Implicit Taylor methods for stiff stochastic differential equations

In this paper we discuss implicit Taylor methods for stiff Ito stochastic differential equations. Based on the relationship between Ito stochastic integrals and backward stochastic integrals, we introduce three implicit Taylor methods: the implicit Euler-Taylor method with strong order 0.5, the implicit Milstein-Taylor method with strong order 1.0 and the implicit Taylor method with strong order 1.5. The mean-square stability properties of the implicit Euler-Taylor and Milstein-Taylor methods are much better than those of the corresponding semi-implicit Euler and Milstein methods and these two implicit methods can be used to solve stochastic differential equations which are stiff in both the deterministic and the stochastic components. Numerical results are reported to show the convergence properties and the stability properties of these three implicit Taylor methods. The stability analysis and numerical results show that the implicit Euler-Taylor and Milstein-Taylor methods are very promising methods for stiff stochastic differential equations.

On the decay rates of buffers in continuous flow lines

Consider a tandem system of machines separated by infinitely large buffers. The machines process a continuous flow of products, possibly at different speeds. The life and repair times of the machines are assumed to be exponential. We claim that the overflow probability of each buffer has an exponential decay, and provide an algorithm to determine the exact decay rates in terms of the speeds and the failure and repair rates of the machines. These decay rates provide useful qualitative insight into the behavior of the flow line. In the derivation of the algorithm we use the theory of Large Deviations.

Stiffly accurate Runge-Kutta methods for stiff stochastic differential equations

In this paper we discuss implicit methods based on stiffly accurate Runge-Kutta methods and splitting techniques for solving Stratonovich stochastic differential equations (SDEs). Two splitting techniques: the balanced splitting technique and the deterministic splitting technique, are used in this paper. We construct a two-stage implicit Runge-Kutta method with strong order 1.0 which is corrected twice and no update is needed. The stability properties and numerical results show that this approach is suitable for solving stiff SDEs. (C) 2001 Elsevier Science B.V. All rights reserved.

Stochastic gauges in quantum dynamics for many-body simulations

Quantum dynamics simulations can be improved using novel quasiprobability distributions based on non-orthogonal Hermitian kernel operators. This introduces arbitrary functions (gauges) into the stochastic equations. which can be used to tailor them for improved calculations. A possible application to full quantum dynamic simulations of BEC's is presented. (C) 2001 Elsevier Science B.V. All rights reserved.

Stochastic Schrodinger equation approach to quantum noise in resonant tunneling current

We apply the quantum trajectory method to current noise in resonant tunneling devices. The results from dynamical simulation are compared with those from unconditional master equation approach. We show that the stochastic Schrodinger equation approach is useful in modeling the dynamical processes in mesoscopic electronic systems.

Predictions of quantum mechanics and stochastic electrodynamics in travelling wave second harmonic generation

We show that stochastic electrodynamics and quantum mechanics give quantitatively different predictions for the quantum nondemolition (QND) correlations in travelling wave second harmonic generation. Using phase space methods and stochastic integration, we calculate correlations in both the positive-P and truncated Wigner representations, the latter being equivalent to the semi-classical theory of stochastic electrodynamics. We show that the semiclassical results are different in the regions where the system performs best in relation to the QND criteria, and that they significantly overestimate the performance in these regions. (C) 2001 Published by Elsevier Science B.V.

The stochastic design of force-minimized compact magnets for high-field magnetic resonance imaging applications

New designs for force-minimized compact high-field clinical MRI magnets are described. The design method is a modified simulated annealing (SA) procedure which includes Maxwell forces in the error function to be minimized. This permits an automated force reduction in the magnet designs while controlling the overall dimensions of the system. As SA optimization requires many iterations to achieve a final design, it is important that each iteration in the procedure is rapid. We have therefore developed a rapid force calculation algorithm. Novel designs for short 3- and 4-T clinical MRI systems are presented in which force reduction has been invoked. The final designs provide large homogeneous regions and reduced stray fields in remarkable short magnets. A shielded 4-T design that is approximately 30% shorter than current designs is presented. This novel magnet generates a full 50-cm diameter homogeneous region.

Patchy populations in stochastic environments: Critical number of patches for persistence

We introduce a model for the dynamics of a patchy population in a stochastic environment and derive a criterion for its persistence. This criterion is based on the geometric mean (GM) through time of the spatial-arithmetic mean of growth rates. For the population to persist, the GM has to be greater than or equal to1. The GM increases with the number of patches (because the sampling error is reduced) and decreases with both the variance and the spatial covariance of growth rates. We derive analytical expressions for the minimum number of patches (and the maximum harvesting rate) required for the persistence of the population. As the magnitude of environmental fluctuations increases, the number of patches required for persistence increases, and the fraction of individuals that can be harvested decreases. The novelty of our approach is that we focus on Malthusian local population dynamics with high dispersal and strong environmental variability from year to year. Unlike previous models of patchy populations that assume an infinite number of patches, we focus specifically on the effect that the number of patches has on population persistence. Our work is therefore directly relevant to patchily distributed organisms that are restricted to a small number of habitat patches.

Model specification tests in nonparametric stochastic regression models

In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example. (C) 2002 Elsevier Science (USA).