Simulated hot working,cold working,

An investigation was carried out on the effects of changing the hot-working, cold-working, and annealing parameters on the interaction between A1N precipitation and recrystallization in low- carbon steels containing significant amounts of Al and N. The primary aim was to determine whether laboratory torsion testing can be helpful in analyzing precipitation behavior in these steels. The approach taken was first to establish the baseline annealing behavior of material that was hot- and cold-worked in a mill and then to compare this with the behavior of material in which the hot and cold working were simulated by torsion testing. It was found, first of all, that torsion testing can indeed provide a good simulation of the industrial process of hot and cold working followed by annealing, even to the extent that a process as subtle as the inhibition of recrystallization by A1N precipitation can be accurately reproduced. The results also show that the interaction between precipitation and recrystallization during annealing is significantly influenced by the reheat temperature before hot working, as well as by the cooling rate after hot working.     

A model for studying LCAT reaction: In vitro cholesterol esterification in pig ovarian follicular fluid

Phosphatidylcholine acyltransferase (lecithin:cholesterol acyltransferase or LCAT; EC 2.3.1.43) activity was found to be present in pig ovarian follicular fluid (POFF), in addition to pig serum (PS). The cholesterol esterification rate in both POFF and PS is linear with incubation time up to 2 hr. The mean absolute rate of POFF-cholesterol esterification was 8.1±0.4 nmoles per ml per hr approximately one-fourth of that in PS. However, the fractional rate (percent of labeled cholesterol esterified per hr) of POFF-cholesterol esterification was similar to that observed in PS. There was little variation of absolute rate of cholesterol esterification in the fluid obtained from different sizes of follicles. Fatty acid or triacylglycerol did not participate in the reaction of cholesterol esterification in POFF. No appreciable change in enzymatic activity was found from storing POFF at 4 C for periods of time up to 24 hr or at −70 C up to 2 months, but activity was lost thereafter. On the other hand, PS showed a much longer period of stability (5 days at 4 C and 9 months at −70 C). A discrepancy between the fatty acid composition of cholesteryl esters formed by the LCAT reaction and the fatty acid composition at the C-2 position of phosphatidylcholine led us to propose a two-step mechanism for the LCAT reaction. It is concluded that the LCAT of POFF, as well as that of plasma, is specific for individual fatty acids rather than for the fatty acid composition of phosphatidylcholine. The fatty acid concentration of lysophosphatidylcholine decreased during prolonged incubation times (6 to 21 hr) suggesting that the increased lysophosphatidylcholine formed as a product of the LCAT reaction may be reused as substrate for the LCAT reaction or for hydrolysis by lysophosphatidylcholine hydrolase. Presented at the AOCS Meeting, New York, May 1977.     

A method to determine the local surface profile from reconstructed exit waves

Reconstructed exit waves are useful to quantify unknown structure parameters such as the position and composition of the atom columns at atomic scale. Existing techniques provide a complex wave in a flat plane which is close to the plane where the electrons leave the atom columns. However, due to local deviation in the flatness of the exit surface, there will be an offset between the plane of reconstruction and the actual exit of a specific atom column. Using the channelling theory, it has been shown that this defocus offset can in principle be determined atom column-by-atom column. As such, the surface roughness could be quantified at atomic scale. However, the outcome strongly depends on the initial plane of reconstruction especially in a crystalline structure. If this plane is further away from the true exit, the waves of the atom columns become delocalized and interfere mutually which strongly complicates the interpretation of the exit wave in terms of the local structure. In this paper, we will study the delocalization with defocus using the channelling theory in a more systematic way.     

Optimal randomized RANSAC

A randomized model verification strategy for RANSAC is presented. The proposed method finds, like RANSAC, a solution that is optimal with user-specified probability. The solution is found in time that is (i) close to the shortest possible and (ii) superior to any deterministic verification strategy. A provably fastest model verification strategy is designed for the (theoretical) situation when the contamination of data by outliers is known. In this case, the algorithm is the fastest possible (on average) of all randomized \\RANSAC algorithms guaranteeing a confidence in the solution. The derivation of the optimality property is based on Wald's theory of sequential decision making, in particular a modified sequential probability ratio test (SPRT). Next, the R-RANSAC with SPRT algorithm is introduced. The algorithm removes the requirement for a priori knowledge of the fraction of outliers and estimates the quantity online. We show experimentally that on standard test data the method has performance close to the theoretically optimal and is 2 to 10 times faster than standard RANSAC and is up to 4 times faster than previously published methods.     

A formal model of composing components: the TLA+ approach

In this paper, a method for writing composable TLA⁺ specifications that conform to the formal model called Masaccio is introduced. Specifications are organized in TLA⁺ modules that correspond to Masaccio components by means of a trace-based semantics. Hierarchical TLA⁺ specifications are built from atomic component specifications by parallel and serial composition that can be arbitrary nested. While the rule of parallel composition is a variation of the classical joint-action composition, the authors do not know about a reuse method for the TLA⁺ that systematically employs the presented kind of a serial composition. By combining these two composition rules and assuming only the noninterleaving synchronous mode of an execution, the concurrent, sequential, and timed compositionality is achieved.     

Low-contrast lesion segmentation in advanced MRI experiments by time-domain Ricker-type wavelets and fuzzy 2-means

Automated suspicious region segmentation has become a crucial need for the experts dealing with numerous images containing contrast-based lesions in MRI. Not all solutions, however, are based on mathematical infrastructure or providing adequate flexibility. On the other hand, segmentation of low-contrast lesions is very challenging for researchers; therefore, advanced magnetic resonance imaging (MRI) experiments are not commonly used in researches. Given the need of repeatability and adaptability, we present an automated framework for intelligent segmentation of brain lesions by wavelet imaging and fuzzy 2-means. Besides the general use of the wavelets in image processing, which is edge detection; we employed the second-order Ricker-type wavelets as the core of our novel imaging framework for low-contrast lesion segmentation. We firstly introduced the mathematical basis of several Ricker wavelet functions, which are in symmetrical form satisfying finite-energy and admissibility conditions of mother wavelets. Afterwards, we investigated three types of Ricker wavelets to apply on our clinical dataset containing susceptibility-weighted (SW) and minimum intensity projection SW (mIP-SW) images with barely-visible lesions. Finally, we adjusted the system parameters of the wavelets for optimization and post-segmentation by fuzzy 2-means. According to the preliminary results of the clinical experiments we conducted, our framework provided 93.53% average dice score (DSC) for SWI by Ricker-3 and 92.56% for mIP-SWI by Ricker-2 wavelet, as the main performance criteria of segmentation. Despite the lack of SWI or mIP-SWI experiments in the public datasets, we tested our framework with BraTS 2012 training sets containing real images with visible lesions and achieved an average of 88.13% DSC with 11.66% standard deviation by re-optimized framework for whole lesion segmentation, which is one of the highest among other relevant researches. In detail, 87.52% DSC for LG datasets with 11.32% standard deviation; while 88.34% DSC for HG datasets with 11.77% standard deviation are calculated.

     

Reduced brain serotonin transporter availability in major depression as measured by [123I]-2 beta-carbomethoxy-3 beta-(4-iodophenyl)tropane and single photon emission computed tomography

BACKGROUND: Prior research has suggested reductions in the density of serotonin transporter (SERT) binding sites in blood platelets and post-mortem brain tissue of depressed patients. We sought to determine whether patients with unipolar major depression have diminished SERT availability as assessed by both brainstem [123I] beta-CIT SPECT and platelet [3H]paroxetine binding. METHODS: Drug-free depressed and healthy subjects were injected with 211 +/- 22 MBq [123I] beta-CIT and imaged 24 +/- 2 h later under equilibrium conditions. A ratio of specific to nonspecific brain uptake (V3" = (brainstem-occipital)/occipital), a measure proportional to the binding potential (Bmax/Kd), was used for all comparisons. RESULTS: Results showed a statistically significant reduction in brainstem V3" values in depressed as compared to healthy subjects (3.1 +/- .9 vs. 3.8 +/- .8, p = .02). Platelet [3H]paroxetine binding was not altered (Bmax = 2389 +/- 484 vs. 2415 +/- 538 fmol/mg protein, p = .91) and was not significantly correlated with brainstem [123I] beta-CIT binding (r = -0.14, p = .48). CONCLUSIONS: These data are the first to suggest reductions in the density of brain SERT binding sites in living depressed patients. These findings provide further support for a preeminent role for alterations in serotonergic neurons in the pathophysiology of depression.     

All normalized anti-monotonic overlap graph measures are bounded

In graph mining, a frequency measure for graphs is anti-monotonic if the frequency of a pattern never exceeds the frequency of a subpattern. The efficiency and correctness of most graph pattern miners relies critically on this property. We study the case where frequent subgraphs have to be found in one graph. Vanetik et al. (Data Min Knowl Disc 13(2):243?C260, 2006) already gave sufficient and necessary conditions for anti-monotonicity of graph measures depending only on the edge-overlaps between the instances of the pattern in a labeled graph. We extend these results to homomorphisms, isomorphisms and homeomorphisms on both labeled and unlabeled, directed and undirected graphs, for vertex- and edge-overlap. We show a set of reductions between the different morphisms that preserve overlap. As a secondary contribution, we prove that the popular maximum independent set measure assigns the minimal possible normalized frequency and we introduce a new measure based on the minimum clique partition that assigns the maximum possible normalized frequency. In that way, we obtain that all normalized anti-monotonic overlap graph measures are bounded from above and below. We also introduce a new measure sandwiched between the former two based on the polynomial time computable Lovász ??-function.