POSTERIORI PROBABILITY ESTIMATION AND PATTERN CLASSIFICATION WITH HADAMARD TRANSFORMED NEURAL NETWORKS

Neural networks, trained with the backpropagation algorithm have: been applied to various classification problems. For linearly separable and nonseparahle problems, they have been shown to approximate the a posteriori probability of an input vector X belonging to a specific class C. In order to achieve high accuracy, large training data sets have to be used. For a small number of input dimensions, the accuracy of estimation was inferior to estimates using the Parzen density estimation. In this thesis, we propose two new techniques, lowering the mean square estimation error drastically and achieving better classification. In the past, t:he desired output patterns used for training have been of binary nature, using one for the class C the vector belongs to, and zero for the other classes. This work will show that by training against the columns of a Hadamard matrix, and then taking the inverse Hadamard transform of the network output, we can obtain more accurate estimates. The second change proposed in comparison with standard backpropagation networks will be the use of redundant output nodes. In standard backpropagat:ion the number of output nodes equals the number of different classes. In this thesis, it is shown that adding redundant output nodes enables us to decrease the mean square error at the output further, reaching better classification and lower mean square error rates than the Parzen density estimator. Comparisons between the statistical methods, the Parzen density estimation and histogramming, the conventional neural network and the Hadamard transformed neural network with redundant output nodes are given. Further, the effects of the proposed changes to the backpropagation algorithm on the convergence speed and the risk of getting stuck in a local minimum are: studied

Platelet Counts and Risk of Severe Retinopathy of Prematurity: A Bayesian Model-Averaged Meta-Analysis

Background: We aimed to conduct a systematic review and Bayesian model-averaged meta-analysis (BMA) on the association between platelet counts and severe retinopathy of prematurity (ROP). Methods: We searched for studies reporting on platelet counts (continuous variable) or thrombocytopenia (categorical variable) and severe ROP or aggressive posterior ROP (APROP). The timing of platelet counts was divided into Phase 1 (<2 weeks) and Phase 2 (around ROP treatment). BMA was used to calculate Bayes factors (BFs). The BF10 is the ratio of the probability of the data under the alternative hypothesis (H1) over the probability of the data under the null hypothesis (H0). Results: We included 21 studies. BMA showed an association between low platelet counts and severe ROP. The evidence was strong (BF10 = 13.5, 7 studies) for phase 1 and very strong (BF10 = 51.0, 9 studies) for phase 2. Thrombocytopenia (<100 × 109/L) in phase 2 was associated with severe ROP (BF10 = 28.2, 4 studies). Following adjustment for publication bias, only the association of severe ROP with thrombocytopenia remained with moderate evidence in favor of H1 (BF10 = 4.30). Conclusions: Thrombocytopenia is associated with severe ROP. However, the evidence for this association was tempered when results were adjusted for publication bias

Cyclic nucleotide-dependent relaxation in human umbilical vessels

Umbilical vessels have a low sensitivity to dilate, and this property is speculated to have physiological implications. We aimed to investigate the different relaxing responses of human umbilical arteries (HUAs) and veins (HUVs) to agonists acting through the cAMP and cGMP pathways. Vascular rings were suspended in organ baths for isometric force measurement. Following precontraction with the thromboxane prostanoid (TP) receptor agonist U44069, concentration-response curves to the nitric oxide (NO) donor sodium nitroprusside (SNP), the soluble guanylate cyclase (sGC) stimulator BAY 41-2272, the adenylate cyclase (AC) activator forskolin, the \u3b2-adrenergic receptor agonists isoproterenol (ADRB1), salmeterol (ADRB2), and BRL37344 (ADRB3), and the phosphodiesterase (PDE) inhibitors milrinone (PDE3), rolipram (PDE4), and sildenafil (PDE5) were performed. None of the tested drugs induced a relaxation higher than 30% of the U44069-induced tone. Rings from HUAs and HUVs showed a similar relaxation to forskolin, SNP, PDE inhibitors, and ADRB agonists. BAY 41-2272 was significantly more efficient in relaxing veins than arteries. ADRB agonists evoked weak relaxations (< 20%), which were impaired in endothelium-removed vessels or in the presence of the NO synthase inhibitor L-NAME, sGC inhibitor ODQ. PKA and PKG inhibitors impaired ADBR1-mediated relaxation but did not affect ADRB2-mediated relaxation. ADRB3-mediated relaxation was impaired by PKG inhibition in HUAs and by PKA inhibition in HUVs. Although HUA and HUV rings were relaxed by BRL37344, immunohistochemistry and RT-qPCR analysis showed that, compared to ADRB1 and ADRB2, ADRB3 receptors are weakly or not expressed in umbilical vessels. In conclusion, our study confirmed the low relaxing capacity of HUAs and HUVs from term infants. ADRB-induced relaxation is partially mediated by endothelium-derived NO pathway in human umbilical vessels

Revealing three-dimensional structure of individual colloidal crystal grain by coherent x-ray diffractive imaging

We present results of a coherent x-ray diffractive imaging experiment performed on a single colloidal crystal grain. The full three-dimensional (3D) reciprocal space map measured by an azimuthal rotational scan contained several orders of Bragg reflections together with the coherent interference signal between them. Applying the iterative phase retrieval approach, the 3D structure of the crystal grain was reconstructed and positions of individual colloidal particles were resolved. As a result, an exact stacking sequence of hexagonal close-packed layers including planar and linear defects were identified.Comment: 8 pages, 5 figure

Improving Land-Surface Model Hydrology: Is an Explicit Aquifer Model Better than a Deeper Soil Profile?

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the storage and movement of water (including soil moisture, snow, evaporation, and runoff) after it falls to the ground as precipitation. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy. Hence LSMs have been developed to integrate the available information, including satellite observations, using powerful computers, in order to track water storage and redistribution. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. Recently, the models have begun to simulate groundwater storage. In this paper, we compare several possible approaches, and examine the pitfalls associated with trying to estimate aquifer parameters (such as porosity) that are required by the models. We find that explicit representation of groundwater, as opposed to the addition of deeper soil layers, considerably decreases the sensitivity of modeled terrestrial water storage to aquifer parameter choices. We also show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a harmonious set

Amniotic fluid-derived stem cells for cardiovascular tissue engineering applications

Recent research has demonstrated that a population of stem cells can be isolated from amniotic fluid removed by amniocentesis that are broadly multipotent and non-tumorogenic. These amniotic fluid-derived stem cells (AFSC) could potentially provide an autologous cell source for treatment of congenital defects identified during gestation, particularly cardiovascular defects. In this review, the various methods of isolating, sorting and culturing AFSC are compared, along with techniques for inducing differentiation into cardiac myocytes and endothelial cells. Though research has not demonstrated complete and high yield cardiac differentiation, AFSC have been shown to effectively differentiate into endothelial cells and can effectively support cardiac tissue. Additionally, several tissue engineering and regenerative therapeutic approaches for the use of these cells in heart patches, injection after myocardial infarction, heart valves, vascularized scaffolds and blood vessels are summarized. These applications show great promise in the treatment of congenital cardiovascular defects, and further studies of isolation, culture, and differentiation of AFSC will help to develop their use for tissue engineering, regenerative medicine, and cardiovascular therapies