Reproductive performance of Santa Inês ewes fed protected fat diet

The objective of this work was to evaluate the reproductive performance of Santa Inês ewes fed a diet supplemented with protected fat. Intervals from lambing to first clinical estrus and to conception, conception rate, prolificacy, live weight and body condition were determined. After lambing, 60 ewes and their offsprings were weighted and randomly assigned to three treatments, based on age, body weight and number of born lambs. Treatments consisted of: control diet, or control diet plus 30 g of protected fat, from lambing to day 25 of post-lambing (Sup25), or to day 60 of post-lambing (Sup60). Out of 60 evaluated ewes, 93.3% returned to estrus, and 74.5% got pregnant, with 73.53% lambing rate and 196.5 days lambing interval. The average periods from lambing to first estrus were 32.4, 27.2 and 35.5 days for ewes fed the control diet, Sup25, and Sup60, respectively. The intervals from lambing to conception were 45.2, 46.5 and 45.2 days, and the supplemented diets did not show differences in comparison to the control diet. Supplementation with protected fat to well-nourished Santa Inês ewes does not improve their reproductive performance.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

High-SNR analytical performance of spatial multiplexing MIMO systems with CSI

In this paper, we investigate the average andoutage performance of spatial multiplexing multiple-input multiple-output (MIMO) systems with channel state information at both sides of the link. Such systems result, for example, from exploiting the channel eigenmodes in multiantenna systems. Dueto the complexity of obtaining the exact expression for the average bit error rate (BER) and the outage probability, we deriveapproximations in the high signal-to-noise ratio (SNR) regime assuming an uncorrelated Rayleigh flat-fading channel. Moreexactly, capitalizing on previous work by Wang and Giannakis, the average BER and outage probability versus SNR curves ofspatial multiplexing MIMO systems are characterized in terms of two key parameters: the array gain and the diversity gain. Finally, these results are applied to analyze the performance of a variety of linear MIMO transceiver designs available in the literature.

Average performance analysis of circular and hyperbolic geolocation

A comparative performance analysis of four geolocation methods in terms of their theoretical root mean square positioning errors is provided. Comparison is established in two different ways: strict and average. In the strict type, methods are examined for a particular geometric configuration of base stations(BSs) with respect to mobile position, which determines a givennoise profile affecting the respective time-of-arrival (TOA) or timedifference-of-arrival (TDOA) estimates. In the average type, methodsare evaluated in terms of the expected covariance matrix ofthe position error over an ensemble of random geometries, so thatcomparison is geometry independent. Exact semianalytical equationsand associated lower bounds (depending solely on the noiseprofile) are obtained for the average covariance matrix of the positionerror in terms of the so-called information matrix specific toeach geolocation method. Statistical channel models inferred fromfield trials are used to define realistic prior probabilities for therandom geometries. A final evaluation provides extensive resultsrelating the expected position error to channel model parametersand the number of base stations.

Quantile Estimation in Non-Stationary Streaming Data

We provide an incremental quantile estimator for Non-stationary Streaming Data. We propose a method for simultaneous estimation of multiple quantiles corresponding to the given probability levels from streaming data. Due to the limitations of the memory, it is not feasible to compute the quantiles by storing the data. So estimating the quantiles as the data pass by is the only possibility. This can be effective in network measurement. To provide the minimum of the mean-squared error of the estimation, we use parabolic approximation and for comparison we simulate the results for different number of runs and using both linear and parabolic approximations.

Distance Transforms on Gray-Level Surfaces

This thesis studies gray-level distance transforms, particularly the Distance Transform on Curved Space (DTOCS). The transform is produced by calculating distances on a gray-level surface. The DTOCS is improved by definingmore accurate local distances, and developing a faster transformation algorithm. The Optimal DTOCS enhances the locally Euclidean Weighted DTOCS (WDTOCS) with local distance coefficients, which minimize the maximum error from the Euclideandistance in the image plane, and produce more accurate global distance values.Convergence properties of the traditional mask operation, or sequential localtransformation, and the ordered propagation approach are analyzed, and compared to the new efficient priority pixel queue algorithm. The Route DTOCS algorithmdeveloped in this work can be used to find and visualize shortest routes between two points, or two point sets, along a varying height surface. In a digital image, there can be several paths sharing the same minimal length, and the Route DTOCS visualizes them all. A single optimal path can be extracted from the route set using a simple backtracking algorithm. A new extension of the priority pixel queue algorithm produces the nearest neighbor transform, or Voronoi or Dirichlet tessellation, simultaneously with the distance map. The transformation divides the image into regions so that each pixel belongs to the region surrounding the reference point, which is nearest according to the distance definition used. Applications and application ideas for the DTOCS and its extensions are presented, including obstacle avoidance, image compression and surface roughness evaluation.

Intravoxel incoherent motion diffusion-weighted imaging in the liver: comparison of mono-, bi- and tri-exponential modelling at 3.0-T.

PURPOSE: To determine whether a mono-, bi- or tri-exponential model best fits the intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) signal of normal livers. MATERIALS AND METHODS: The pilot and validation studies were conducted in 38 and 36 patients with normal livers, respectively. The DWI sequence was performed using single-shot echoplanar imaging with 11 (pilot study) and 16 (validation study) b values. In each study, data from all patients were used to model the IVIM signal of normal liver. Diffusion coefficients (Di ± standard deviations) and their fractions (fi ± standard deviations) were determined from each model. The models were compared using the extra sum-of-squares test and information criteria. RESULTS: The tri-exponential model provided a better fit than both the bi- and mono-exponential models. The tri-exponential IVIM model determined three diffusion compartments: a slow (D1 = 1.35 ± 0.03 × 10(-3) mm(2)/s; f1 = 72.7 ± 0.9 %), a fast (D2 = 26.50 ± 2.49 × 10(-3) mm(2)/s; f2 = 13.7 ± 0.6 %) and a very fast (D3 = 404.00 ± 43.7 × 10(-3) mm(2)/s; f3 = 13.5 ± 0.8 %) diffusion compartment [results from the validation study]. The very fast compartment contributed to the IVIM signal only for b values ≤15 s/mm(2) CONCLUSION: The tri-exponential model provided the best fit for IVIM signal decay in the liver over the 0-800 s/mm(2) range. In IVIM analysis of normal liver, a third very fast (pseudo)diffusion component might be relevant. KEY POINTS: ? For normal liver, tri-exponential IVIM model might be superior to bi-exponential ? A very fast compartment (D = 404.00 ± 43.7 × 10 (-3)  mm (2) /s; f = 13.5 ± 0.8 %) is determined from the tri-exponential model ? The compartment contributes to the IVIM signal only for b ≤ 15 s/mm (2.)

An efficient solver for weighted Max-SAT

We present a new branch and bound algorithm for weighted Max-SAT, called Lazy which incorporates original data structures and inference rules, as well as a lower bound of better quality. We provide experimental evidence that our solver is very competitive and outperforms some of the best performing Max-SAT and weighted Max-SAT solvers on a wide range of instances.

Prevalence of iodine inadequacy in Switzerland assessed by the estimated average requirement cut-point method in relation to the impact of iodized salt.

OBJECTIVE: To assess the iodine status of Swiss population groups and to evaluate the influence of iodized salt as a vector for iodine fortification. DESIGN: The relationship between 24 h urinary iodine and Na excretions was assessed in the general population after correcting for confounders. Single-day intakes were estimated assuming that 92 % of dietary iodine was excreted in 24 h urine. Usual intake distributions were derived for male and female population groups after adjustment for within-subject variability. The estimated average requirement (EAR) cut-point method was applied as guidance to assess the inadequacy of the iodine supply. SETTING: Public health strategies to reduce the dietary salt intake in the general population may affect its iodine supply. SUBJECTS: The study population (1481 volunteers, aged ≥15 years) was randomly selected from three different linguistic regions of Switzerland. RESULTS: The 24 h urine samples from 1420 participants were determined to be properly collected. Mean iodine intakes obtained for men (n 705) and women (n 715) were 179 (sd 68.1) µg/d and 138 (sd 57.8) µg/d, respectively. Urinary Na and Ca, and BMI were significantly and positively associated with higher iodine intake, as were men and non-smokers. Fifty-four per cent of the total iodine intake originated from iodized salt. The prevalence of inadequate iodine intake as estimated by the EAR cut-point method was 2 % for men and 14 % for women. CONCLUSIONS: The estimated prevalence of inadequate iodine intake was within the optimal target range of 2-3 % for men, but not for women.

Diffusion-weighted MR imaging in musculoskeletal diseases: Current concepts.

MR imaging is currently regarded as a pivotal technique for the assessment of a variety of musculoskeletal conditions. Diffusion-weighted MR imaging (DWI) is a relatively recent sequence that provides information on the degree of cellularity of lesions. Apparent diffusion coefficient (ADC) value provides information on the movement of water molecules outside the cells. The literature contains many studies that have evaluated the role of DWI in musculoskeletal diseases. However, to date they yielded conflicting results on the use and the diagnostic capabilities of DWI in the area of musculoskeletal diseases. However, many of them have showed that DWI is a useful technique for the evaluation of the extent of the disease in a subset of musculoskeletal cancers. In terms of tissue characterization, DWI may be an adjunct to the more conventional MR imaging techniques but should be interpreted along with the signal of the lesion as observed on conventional sequences, especially in musculoskeletal cancers. Regarding the monitoring of response to therapy in cancer or inflammatory disease, the use of ADC value may represent a more reliable additional tool but must be compared to the initial ADC value of the lesions along with the knowledge of the actual therapy.

Rainfall is a risk factor for sporadic cases of Legionella pneumophila Pneumonia

It is not known whether rainfall increases the risk of sporadic cases of Legionella pneumonia. We sought to test this hypothesis in a prospective observational cohort study of non-immunosuppressed adults hospitalized for community-acquired pneumonia (1995-2011). Cases with Legionella pneumonia were compared with those with non-Legionella pneumonia. Using daily rainfall data obtained from the regional meteorological service we examined patterns of rainfall over the days prior to admission in each study group. Of 4168 patients, 231 (5.5%) had Legionella pneumonia. The diagnosis was based on one or more of the following: sputum (41 cases), antigenuria (206) and serology (98). Daily rainfall average was 0.556 liters/m2 in the Legionella pneumonia group vs. 0.328 liters/m2 for non-Legionella pneumonia cases (p = 0.04). A ROC curve was plotted to compare the incidence of Legionella pneumonia and the weighted median rainfall. The cut-off point was 0.42 (AUC 0.54). Patients who were admitted to hospital with a prior weighted median rainfall higher than 0.42 were more likely to have Legionella pneumonia (OR 1.35; 95% CI 1.02-1.78; p = .03). Spearman Rho correlations revealed a relationship between Legionella pneumonia and rainfall average during each two-week reporting period (0.14; p = 0.003). No relationship was found between rainfall average and non-Legionella pneumonia cases (−0.06; p = 0.24). As a conclusion, rainfall is a significant risk factor for sporadic Legionella pneumonia. Physicians should carefully consider Legionella pneumonia when selecting diagnostic tests and antimicrobial therapy for patients presenting with CAP after periods of rainfall.

Pointwise estimates for the Bergman kernel of the weighted Fock space

We prove upper pointwise estimates for the Bergman kernel of the weighted Fock space of entire functions in $L^{2}(e^{-2\phi}) $ where $\phi$ is a subharmonic function with $\Delta\phi$ a doubling measure. We derive estimates for the canonical solution operator to the inhomogeneous Cauchy-Riemann equation and we characterize the compactness of this operator in terms of $\Delta\phi$.

Glassy magnetic phase driven by short range charge and magnetic ordering in nanocrystalline La1/3Sr2/3FeO3-δ: Magnetization, Mössbauer, and polarized neutron studies

The charge ordered La1/3Sr2/3FeO3−δ (LSFO) in bulk and nanocrystalline forms are investigated using ac and dc magnetization, M¨ossbauer, and polarized neutron studies. A complex scenario of short-range charge and magnetic ordering is realized from the polarized neutron studies in nanocrystalline specimen. This short-range ordering does not involve any change in spin state and modification in the charge disproportion between Fe3+ and Fe5+ compared to bulk counterpart as evident in the M¨ossbauer results. The refinement of magnetic diffraction peaks provides magnetic moments of Fe3+ and Fe5+ are about 3.15 μB and 1.57 μB for bulk, and 2.7 μB and 0.53 μB for nanocrystalline specimen, respectively. The destabilization of charge ordering leads to magnetic phase separation, giving rise to the robust exchange bias (EB) effect. Strikingly, EB field at 5 K attains a value as high as 4.4 kOe for average size ∼70 nm, which is zero for the bulk counterpart. A strong frequency dependence of ac susceptibility reveals cluster-glass-like transition around ∼65 K, below which EB appears. Overall results propose that finite-size effect directs the complex glassy magnetic behavior driven by unconventional short-range charge and magnetic ordering, and magnetic phase separation appears in nanocrystalline LSFO.

Beurling-Landau densities of weighted Fekete sets and correlation kernel estimates

Let $Q$ be a suitable real function on $C$. An $n$-Fekete set corresponding to $Q$ is a subset ${Z_{n1}},\dotsb, Z_{nn}}$ of $C$ which maximizes the expression $\Pi^n_i_{