Experimental evidence for a light and broad scalar resonance in D(+) --> pi(-)pi(+)pi(+) decay

From a sample of 1172 +/- 61 D(+)-->pi(-)pi(+)pi(+) decays, we find gamma(D(+)-->pi(-)pi(+)pi(+))/gamma(D(+)-->K-pi(+)pi(+)) = 0.0311 +/- 0.0018(+0.0016)(-0.0026). Using a coherent amplitude analysis to fit the Dalitz plot of these decays, we find strong evidence that a scalar resonance of mass 478(+24)(-23) +/- 17 MeV/c(2) and width 324(+42)(-40) +/- 21 MeV/c(2) accounts for approximately half of all decays.     

Non-spherical sources of static gravitational fields: Investigating the boundaries of the no-hair theorem

A new, globally regular model describing a static, non spherical gravitating object in General Relativity is presented. The model is composed by a vacuum Weyl–Levi-Civita special field – the so called gamma metric – generated by a regular static distribution of mass-energy. Standard requirements of physical reasonableness such as, energy, matching and regularity conditions are satisfied. The model is used as a toy in investigating various issues related to the directional behavior of naked singularities in static spacetimes and the black hole (Schwarzschild) limit.     

Neurofibrillary tangles and plaques are not accompanied by white matter pathology in aged triple transgenic-Alzheimer disease mice

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is the most common cause of dementia in aging populations. Although senile plaques and neurofibrillary tangles are well-established hallmarks of AD, changes in cerebral white matter correlate with cognitive decline and may increase the risk of the development of dementia. We used the triple transgenic (3xTg)-AD mouse model of AD, previously used to show that white matter changes precede plaque formation, to test the hypothesis that MRI detectable changes occur in the corpus callosum, external capsule and the fornix. T₂-weighted and diffusion tensor magnetic resonance imaging and histological stains were employed to assess white matter in older (11–17 months) 3xTg-AD mice and controls. We found no statistically significant changes in white matter between 3xTg-AD mice and controls, despite well-developed neurofibrillary tangles and beta amyloid immunoreactive plaques. Myelin staining was normal in affected mice. These data suggest that the 3xTg-AD mouse model does not develop MRI detectable white matter changes at the ages we examined.     

Preparation and characterization of poly(lactic acid)/poly(methyl methacrylate) blend tablets for application in quantitative analysis by micro Raman spectroscopy

Poly(lactic acid) (PLA) is a biodegradable polymer that has a variety of applications, one of which is as biomaterial in surgery or as functional layers on implants, due to its compatibility with living tissue. This paper reports the possibilities of quantification of poly(lactic acid) (PLA) in a polymer matrix such as poly(methyl methacrylate) (PMMA) by micro Raman spectroscopy (MRS). Blends of amorphous poly(DL‐lactic acid) with poly(methyl methacrylate) were prepared by the procedure of dissolution/precipitation. Thermal properties of the blends such as the glass transition temperature (Tg) were characterized by differential scanning calorimetry (DSC). The PLA/PMMA blends exhibited only a single glass transition region, indicating that this system is miscible. The PLA/PMMA system obeys the Gordon–Taylor equation (Tg versus PLA content). Various concentration ratios of PLA blends were prepared to use as a basis for quantitative analysis by MRS. Intensities of the characteristic bands at 813 cm⁻¹ (νCOC of PMMA) and 873 cm⁻¹ (νC―COO of PLA) were used for the calculation. The calibration graph showed a good linear correlation with an R² value of 0.9985. On the basis of the calibration curve obtained, the determined content of several PLA/PMMA blends was in good agreement when compared with nominal contents. The limit of detection (LOD) and quantification (LOQ) were calculated by the calibration data set as signal‐to‐noise method. The relative standard deviation of this method was lower than 10% and the accuracy better than 4%. This study demonstrated that Raman spectroscopy provides an alternative non destructive method for quantitative analysis of PLA in a PMMA matrix. Copyright © 2015 John Wiley & Sons, Ltd.     

Identification of cellulose fibres belonging to Spanish cultural heritage using synchrotron high resolution X-ray diffraction

A complete characterisation of fibres used in Spanish artwork is necessary to provide a complete knowledge of these natural fibres and their stage of degradation. Textile samples employed as painting supports on canvas and one sample of unprocessed plant material were chosen for this study. All the samples were investigated by synchrotron radiation X-ray diffraction (SR-XRD). Flax and cotton have the Cellulose I structure. The values of the crystalline index (CI) were calculated for both types of fibres. The structure of Cellulose IV was associated with the unprocessed plant material. The information obtained by SR-XRD was confirmed by laboratory techniques including scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR).     

Sticky model of charged colloids

Summary We use the Sticky Electrolyte Model, which we solved before in PY/MSA, to obtain the equation of state of a charge colloid taking into account both sticky and charge contribution. Paper presented at the I International Conference on Scaling Concepts and Complex Fluids, Copanello, Italy, July 4–8, 1994.     

A Comparative Analysis of Machine Learning Techniques for Muon Count in UHECR Extensive Air-Showers

The main goal of this work is to adapt a Physics problem to the Machine Learning (ML) domain and to compare several techniques to solve it. The problem consists of how to perform muon count from the signal registered by particle detectors which record a mix of electromagnetic and muonic signals. Finding a good solution could be a building block on future experiments. After proposing an approach to solve the problem, the experiments show a performance comparison of some popular ML models using two different hadronic models for the test data. The results show that the problem is suitable to be solved using ML as well as how critical the feature selection stage is regarding precision and model complexity.