NN -> NN pi(+) reaction near threshold in a chiral power counting approach

Power-counting arguments are used to organize the interactions contributing to the NN-->d pi,pn pi reactions near threshold. We estimate the contributions from the three formally leading mechanisms: the Weinberg-Tomozawa (WT) term, the impulse term, and the Delta-excitation mechanism. Subleading but potentially large mechanisms, including S-wave pion rescattering, the Galilean correction to the WT term, and short-ranged contributions are also examined. The WT term is shown to be numerically the largest, and the other contributions are found to approximately cancel. Similarly to the reaction pp-->pp pi(0), the computed cross sections are considerably smaller than the data. We discuss possible origins of this discrepancy.

Counting singularities via fitting ideals

The stable singularities of differential map germs constitute the main source of studying the geometric and topological behavior of these maps. In particular, one interesting problem is to find formulae which allow us to count the isolated stable singularities which appear in the discriminant of a stable deformation of a finitely determined map germ. Mond and Pellikaan showed how the Fitting ideals are related to such singularities and obtain a formula to count the number of ordinary triple points in map germs from C-2 to C-3, in terms of the Fitting ideals associated with the discriminant. In this article we consider map germs from (Cn+m, 0) to (C-m, 0), and obtain results to count the number of isolated singularities by means of the dimension of some associated algebras to the Fitting ideals. First in Corollary 4.5 we provide a way to compute the total sum of these singularities. In Proposition 4.9, for m = 3 we show how to compute the number of ordinary triple points. In Corollary 4.10 and with f of co-rank one, we show a way to compute the number of points formed by the intersection between a germ of a cuspidal edge and a germ of a plane. Furthermore, we show in some examples how to calculate the number of isolated singularities using these results.

Simcluster: clustering enumeration gene expression data on the simplex space

Abstract Background Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space. Results Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster. Conclusion Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression data.

Multi-Sensor people counting

[EN]An accurate estimation of the number of people entering / leaving a controlled area is an interesting capability for automatic surveil- lance systems. Potential applications where this technology can be ap- plied include those related to security, safety, energy saving or fraud control. In this paper we present a novel con guration of a multi-sensor system combining both visual and range data specially suited for trou- blesome scenarios such as public transportation. The approach applies probabilistic estimation lters on raw sensor data to create intermediate level hypothesis that are later fused using a certainty-based integration stage. Promising results have been obtained in several tests performed on a realistic test bed scenario under variable lightning conditions.

People counting with re-identification using depth cameras

[EN]Low cost real-time depth cameras offer new sensors for a wide field of applications apart from the gaming world. Other active research scenarios as for example surveillance, can take ad- vantage of the capabilities offered by this kind of sensors that integrate depth and visual information. In this paper, we present a system that operates in a novel application context for these devices, in troublesome scenarios where illumination conditions can suffer sudden changes. We focus on the people counting problem with re-identification and trajectory analysis.

A Phase Space Box-counting based Method for Arrhythmia Prediction from Electrocardiogram Time Series

Arrhythmia is one kind of cardiovascular diseases that give rise to the number of deaths and potentially yields immedicable danger. Arrhythmia is a life threatening condition originating from disorganized propagation of electrical signals in heart resulting in desynchronization among different chambers of the heart. Fundamentally, the synchronization process means that the phase relationship of electrical activities between the chambers remains coherent, maintaining a constant phase difference over time. If desynchronization occurs due to arrhythmia, the coherent phase relationship breaks down resulting in chaotic rhythm affecting the regular pumping mechanism of heart. This phenomenon was explored by using the phase space reconstruction technique which is a standard analysis technique of time series data generated from nonlinear dynamical system. In this project a novel index is presented for predicting the onset of ventricular arrhythmias. Analysis of continuously captured long-term ECG data recordings was conducted up to the onset of arrhythmia by the phase space reconstruction method, obtaining 2-dimensional images, analysed by the box counting method. The method was tested using the ECG data set of three different kinds including normal (NR), Ventricular Tachycardia (VT), Ventricular Fibrillation (VF), extracted from the Physionet ECG database. Statistical measures like mean (μ), standard deviation (σ) and coefficient of variation (σ/μ) for the box-counting in phase space diagrams are derived for a sliding window of 10 beats of ECG signal. From the results of these statistical analyses, a threshold was derived as an upper bound of Coefficient of Variation (CV) for box-counting of ECG phase portraits which is capable of reliably predicting the impeding arrhythmia long before its actual occurrence. As future work of research, it was planned to validate this prediction tool over a wider population of patients affected by different kind of arrhythmia, like atrial fibrillation, bundle and brunch block, and set different thresholds for them, in order to confirm its clinical applicability.

Focal cystic high-attenuation lesions: characterization in renal phantom by using photon-counting spectral CT--improved differentiation of lesion composition

To evaluate the capability of spectral computed tomography (CT) to improve the characterization of cystic high-attenuation lesions in a renal phantom and to test the hypothesis that spectral CT will improve the differentiation of cystic renal lesions with high protein content and those that have undergone hemorrhage or malignant contrast-enhancing transformation.

Carbohydrate counting of food

Carbohydrate counting is a principal strategy in nutritional management of type 1 diabetes. The Nutri-Learn buffet (NLB) is a new computer-based tool for patient instruction in carbohydrate counting. It is based on food dummies made of plastic equipped with a microchip containing relevant food content data. The tool enables the dietician to assess the patient's food counting abilities and the patient to learn in a hands-on interactive manner to estimate food contents such as carbohydrate content.

The recoil transfer chamber - An interface to connect the physical preseparator TASCA with chemistry and counting setups

Performing experiments with transactinide elements demands highly sensitive detection methods due to the extremely low production rates (one-atom-at-a-time conditions). Preseparation with a physical recoil separator is a powerful method to significantly reduce the background in experiments with sufficiently long-lived isotopes (t1/2≥0.5 s). In the last years, the new gas-filled TransActinide Separator and Chemistry Apparatus (TASCA) was installed and successfully commissioned at GSI. Here, we report on the design and performance of a Recoil Transfer Chamber (RTC) for TASCA—an interface to connect various chemistry and counting setups with the separator. Nuclear reaction products recoiling out of the target are separated according to their magnetic rigidity within TASCA, and the wanted products are guided to the focal plane of TASCA. In the focal plane, they pass a thin Mylar window that separates the ∼1 mbar atmosphere in TASCA from the RTC kept at ∼1 bar. The ions are stopped in the RTC and transported by a continuous gas flow from the RTC to the ancillary setup. In this paper, we report on measurements of the transportation yields under various conditions and on the first chemistry experiments at TASCA—an electrochemistry experiment with osmium and an ion exchange experiment with the transactinide element rutherfordium.

Duration of Greenland Stadial 22 and ice-gas Δage from counting of annual layers in Greenland NGRIP ice core

High-resolution measurements of chemical impurities and methane concentrations in Greenland ice core samples from the early glacial period allow the extension of annual-layer counted chronologies and the improvement of gas age-ice age difference (Δage) essential to the synchronization of ice core records. We report high-resolution measurements of a 50 m section of the NorthGRIP ice core and corresponding annual layer thicknesses in order to constrain the duration of the Greenland Stadial 22 (GS-22) between Greenland Interstadials (GIs) 21 and 22, for which inconsistent durations and ages have been reported from Greenland and Antarctic ice core records as well as European speleothems. Depending on the chronology used, GS-22 occurred between approximately 89 (end of GI-22) and 83 kyr b2k (onset of GI-21). From annual layer counting, we find that GS-22 lasted between 2696 and 3092 years and was followed by a GI-21 pre-cursor event lasting between 331 and 369 yr. Our layer-based counting agrees with the duration of stadial 22 as determined from the NALPS speleothem record (3250 ± 526 yr) but not with that of the GICC05modelext chronology (2620 yr) or an alternative chronology based on gas-marker synchronization to EPICA Dronning Maud Land ice core. These results show that GICC05modelext overestimates accumulation and/or underestimates thinning in this early part of the last glacial period. We also revise the possible ranges of NorthGRIP Δdepth (5.49 to 5.85 m) and Δage (498 to 601 yr) at the warming onset of GI-21 as well as the Δage range at the onset of the GI-21 precursor warming (523 to 654 yr), observing that temperature (represented by the δ15N proxy) increases before CH4 concentration by no more than a few decades.

Analyzing Panel Count Data with Informative Observation Times

In this paper, we study panel count data with informative observation times. We assume nonparametric and semiparametric proportional rate models for the underlying recurrent event process, where the form of the baseline rate function is left unspecified and a subject-specific frailty variable inflates or deflates the rate function multiplicatively. The proposed models allow the recurrent event processes and observation times to be correlated through their connections with the unobserved frailty; moreover, the distributions of both the frailty variable and observation times are considered as nuisance parameters. The baseline rate function and the regression parameters are estimated by maximizing a conditional likelihood function of observed event counts and solving estimation equations. Large sample properties of the proposed estimators are studied. Numerical studies demonstrate that the proposed estimation procedures perform well for moderate sample sizes. An application to a bladder tumor study is presented to illustrate the use of the proposed methods.