Homogeneous and inhomogeneous contributions to the luminescence linewidth of point defects in amorphous solids: Quantitative assessment based on time-resolved emission spectroscopy

The article describes an experimental method that allows to estimate the inhomogeneous and homogeneous linewidths of the photoluminescence band of a point defect in an amorphous solid. We performed low temperature time-resolved luminescence measurements on two defects chosen as model systems for our analysis: extrinsic Oxygen Deficient Centers (ODC(II)) in amorphous silica and F+ 3 centers in crystalline Lithium Fluoride. Measurements evidence that only defects embedded in the amorphous matrix feature a dependence of the radiative decay lifetime on the emission energy and a time dependence of the first moment of the emission band. A theoretical model is developed to link these properties to the structural disorder typical of amorphous solids. Specifically, the observations on ODC(II) are interpreted by introducing a gaussian statistical distribution of the zero phonon line energy position. Comparison with the results obtained on F+ 3 crystalline defects strongly confirms the validity of the model. By analyzing experimental data within this frame, we obtain separate estimations of the homogenous and inhomogeneous contributions to the measured total linewidth of ODC(II), which results to be mostly inhomogeneous.Comment: 8 pages, 4 figure

Long term ordering kinetics of the two dimensional q-state Potts model

We studied the non-equilibrium dynamics of the q-state Potts model in the square lattice, after a quench to sub-critical temperatures. By means of a continuous time Monte Carlo algorithm (non-conserved order parameter dynamics) we analyzed the long term behavior of the energy and relaxation time for a wide range of quench temperatures and system sizes. For q>4 we found the existence of different dynamical regimes, according to quench temperature range. At low (but finite) temperatures and very long times the Lifshitz-Allen-Cahn domain growth behavior is interrupted with finite probability when the system stuck in highly symmetric non-equilibrium metastable states, which induce activation in the domain growth, in agreement with early predictions of Lifshitz [JETP 42, 1354 (1962)]. Moreover, if the temperature is very low, the system always gets stuck at short times in a highly disordered metastable states with finite life time, which have been recently identified as glassy states. The finite size scaling properties of the different relaxation times involved, as well as their temperature dependency are analyzed in detail.Comment: 10 pages, 17 figure

Homologous self-organising scale-invariant properties characterise long range species spread and cancer invasion

The invariance of some system properties over a range of temporal and/or spatial scales is an attribute of many processes in nature1, often characterised by power law functions and fractal geometry2. In particular, there is growing consensus in that fat-tailed functions like the power law adequately describe long-distance dispersal (LDD) spread of organisms 3,4. Here we show that the spatial spread of individuals governed by a power law dispersal function is represented by a clear and unique signature, characterised by two properties: A fractal geometry of the boundaries of patches generated by dispersal with a fractal dimension D displaying universal features, and a disrupted patch size distribution characterised by two different power laws. Analysing patterns obtained by simulations and real patterns from species dispersal and cell spread in cancer invasion we show that both pattern properties are a direct result of LDD and localised dispersal and recruitment, reflecting population self-organisation

A nutrition mathematical model to account for dietary supply and requirements of energy and nutrients for domesticated small ruminants: the development and evaluation of the Small Ruminant Nutrition System

A mechanistic model that predicts nutrient requirements and biological values of feeds for sheep (Cornell Net Carbohydrate and Protein System; CNCPS-S) was expanded to include goats and the name was changed to the Small Ruminant Nutrition System (SRNS). The SRNS uses animal and environmental factors to predict metabolizable energy (ME) and protein, and Ca and P requirements. Requirements for goats in the SRNS are predicted based on the equations developed for CNCPS-S, modified to account for specific requirements of goats, including maintenance, lactation, and pregnancy requirements, and body reserves. Feed biological values are predicted based on carbohydrate and protein fractions and their ruminal fermentation rates, forage, concentrate and liquid passage rates, and microbial growth. The evaluation of the SRNS for sheep using published papers (19 treatment means) indicated no mean bias (MB; 1.1 g/100 g) and low root mean square prediction error (RMSPE; 3.6 g/100g) when predicting dietary organic matter digestibility for diets not deficient in ruminal nitrogen. The SRNS accurately predicted gains and losses of shrunk body weight (SBW) of adult sheep (15 treatment means; MB = 5.8 g/d and RMSPE = 30 g/d) when diets were not deficient in ruminal nitrogen. The SRNS for sheep had MB varying from -34 to 1 g/d and RSME varying from 37 to 56 g/d when predicting average daily gain (ADG) of growing lambs (42 treatment means). The evaluation of the SRNS for goats based on literature data showed accurate predictions for ADG of kids (31 treatment means; RMSEP = 32.5 g/d; r2= 0.85; concordance correlation coefficient, CCC, = 0.91), daily ME intake (21 treatment means; RMSEP = 0.24 Mcal/d g/d; r2 = 0.99; CCC = 0.99), and energy balance (21 treatment means; RMSEP = 0.20 Mcal/d g/d; r2 = 0.87; CCC = 0.90) of goats. In conclusion, the SRNS for sheep can accurately predict dietary organic matter digestibility, ADG of growing lambs and changes in SBW of mature sheep. The SRNS for goats is suitable for predicting ME intake and the energy balance of lactating and non-lactating adult goats and the ADG of kids of dairy, meat, and indigenous breeds. The SRNS model is available at http://nutritionmodels.tamu.edu

Video analysis of dogs with separation-related behaviors

Separation-related behaviors are described as problematic behaviors that occur exclusively in the owner's absence or virtual absence. Diagnosis is generally based on indirect evidence such as elimination or destruction that occurs during owner absence. Questionnaire studies are based on owner perception and might therefore underestimate the actual proportion of dogs with separation problems. The aim of this study was to film dogs with separation-related problems when left home alone and compile objective information on behaviors exhibited. Twenty-three dogs, ranging in age from 5 months to 13 years (2.9 \ub1 22.7 years), were filmed home alone for 20-60 min (49.87 \ub1 12.9 min) after owner departure. Analysis of behaviors on tape showed that dogs spent most of their time vocalizing (22.95 \ub1 12.3% of total observed time) and being oriented to the environment (21 \ub1 20%). Dogs also exhibited panting (14 \ub1 18%), were passive (12 \ub1 27%) and were destroying (6 \ub1 6%) during owner absence. Most dogs displayed signs within less than 10 min after owner departure, such as vocalizing (mean latency 3.25 min) and/or destroying (mean latency 7.13 min). Barking and oriented to the environment tended to decrease (respectively p = 0.08 and p = 0.07) and conversely panting tended to increase over time (p = 0.07). Diagnosis of separation-related problems is traditionally dependant on owner reports. Although owner observation may be informative, direct observation and standardized behavioral measurement of dogs with separation-related problems, before and after treatment, would be the best way to diagnose and to measure behavioral improvement

Selection of features based on electric power quantities for non-intrusive load monitoring

Non-intrusive load monitoring (NILM) is a process of determining the operating states and the energy consumption of single electric devices using a single energy meter providing aggregate load measurements. Due to the large spread of power electronic-based and nonlinear devices connected to the network, the time signals of both voltage and current are typically non-sinusoidal. The effectiveness of a NILM algorithm strongly depends on determining a set of discriminative features. In this paper, voltage and current signals were combined to define, according to the definitions provided in Standard IEEE 1459, different power quantities, that can be used to distinguish different types of appliance. Multi-layer perceptron (MLP) classifiers were trained to solve the appliance detection problem as a multi-class event classification problem, varying the electric features in input. This allowed to select an optimal set of features guarantying good classification performance in identifying typical electric loads

A Mechanistic model for predicting the nutrient requirements and feed biological values for sheep

The Cornell Net Carbohydrate and Protein System (CNCPS), a mechanistic model that predicts nutrient requirements and biological values of feeds for cattle, was modified for use with sheep. Published equations were added for predicting the energy and protein requirements of sheep, with a special emphasis on dairy sheep, whose specific needs are not considered by most sheep-feeding systems. The CNCPS for cattle equations that are used to predict the supply of nutrients from each feed were modified to include new solid and liquid ruminal passage rates for sheep, and revised equations were inserted to predict metabolic fecal N. Equations were added to predict fluxes in body energy and protein reserves from BW and condition score. When evaluated with data from seven published studies (19 treatments), for which the CNCPS for sheep predicted positive ruminal N balance, the CNCPS for sheep predicted OM digestibility, which is used to predict feed ME values, with no mean bias (1.1 g/100 g of OM; P > 0.10) and a low root mean squared prediction error (RMSPE; 3.6 g/100 g of OM). Crude protein digestibility, which is used to predict N excretion, was evaluated with eight published studies (23 treatments). The model predicted CP digestibility with no mean bias (-1.9 g/100 g of CP; P > 0.10) but with a large RMSPE (7.2 g/100 g of CP). Evaluation with a data set of published studies in which the CNCPS for sheep predicted negative ruminal N balance indicated that the model tended to underpredict OM digestibility (mean bias of -3.3 g/100 g of OM, P > 0.10; RMSPE = 6.5 g/100 g of OM; n = 12) and to overpredict CP digestibility (mean bias of 2.7 g/100 g of CP, P > 0.10; RMSPE = 12.8 g/100 g of CP; n = 7). The ability of the CNCPS for sheep to predict gains and losses in shrunk BW was evaluated using data from six studies with adult sheep (13 treatments with lactating ewes and 16 with dry ewes). It accurately predicted variations in shrunk BW when diets had positive N balance (mean bias of 5.8 g/d; P > 0.10; RMSPE of 30.0 g/d; n = 15), whereas it markedly overpredicted the variations in shrunk BW when ruminal balance was negative (mean bias of 53.4 g/d, P < 0.05; RMSPE = 84.1 g/d; n = 14). These evaluations indicated that the Cornell Net Carbohydrate and Protein System for Sheep can be used to predict energy and protein requirements, feed biological values, and BW gains and losses in adult sheep

The Small Ruminant Nutrition System: development and evaluation of a goat submodel

The Small Ruminant Nutrition System (SRNS) is a computer model based on the structure of the Cornell Net Carbohydrate and Protein System for Sheep.A version of the SRNS for goats is under development and evaluation. In the SRNS for goats, energy and protein requirements are predicted based on the equations developed for the SRNS for sheep, modified to account for specific requirements of goats. Feed biological values are predicted based on carbohydrate and protein fractions and their ruminal degradation rates, on forage, concentrate and liquid passage rates, on microbial growth, and on physically effective fiber. The evaluation of the SRNS for goats based on literature data showed that the SRNS accurately predicted the ADG of kids (RMSEP = 32.5 g/d; r2 = 0.85; CCC = 0.91), and the daily MEI (RMSEP = 0.24 Mcal/d g/d; r2 = 0.99; CCC = 0.99) and the energy balance (RMSEP = 0.20 Mcal/d g/d; r2 = 0.87; CCC = 0.90) of goats

Evolution of the Magnetic and Structural Properties with the Chemical Composition in Oleate-Capped MnxCo1- xFe2O4Nanoparticles

Understanding the complex link among composition, microstructure, and magnetic properties paves the way to the rational design of well-defined magnetic materials. In this context, the evolution of the magnetic and structural properties in a series of oleate-capped manganese-substituted cobalt ferrites (MnxCo1-xFe2O4) with variable Co/Mn molar ratios is deeply discussed. Single-phase ferrites with similar crystallite and particle sizes (about 10 nm), size dispersity (14%), and weight percentage of capping oleate molecules (17%) were obtained by an oleate-based solvothermal approach. The similarities among the samples permitted the interpretation of the results exclusively on the basis of the actual composition, beyond the other parameters. The temperature and magnetic field dependences of the magnetization were studied together with the interparticle interactions by DC magnetometry. Characteristic temperatures (Tmax, Tdiff, and Tb), coercivity, anisotropy field, and reduced remanence were found to be affected by the Co/Mn ratio, mainly due to the magnetic anisotropy, interparticle interactions, and particle volume distribution. In addition, the cobalt and manganese distributions were hypothesized on the basis of the chemical composition, the inversion degree obtained by 57Fe Mössbauer spectroscopy, the anisotropy constant, and the saturation magnetization

On the thermal and hydrothermal stability of spinel iron oxide nanoparticles as single and core-shell hard-soft phases

The thermal and hydrothermal stability of oleate-capped nanosized spinel iron oxides is of primary importance for the plethora of applications and environments for which they are employed. An in-situ XRD and ex-situ autoclave treatments have been set up for monitoring the thermal and hydrothermal stability in different samples. In detail, spinel iron oxide nanoparticles (NPs) were studied as (i) single-phase alone at three different sizes (about 6, 10, and 15 nm); (ii) as core in a core-shell architecture having cobalt ferrite as shell, at different core sizes (about 6 and 10 nm); (iii) as shell in a core-shell architecture with cobalt ferrite as core, at different shell thicknesses (about 3 and 4 nm). The Rietveld refinement of the diffraction patterns and 57Fe Mössbauer spectroscopy have been exploited to monitor the evolution of the structural parameters and the hematite fraction. Moreover, transmission electron microscopy has permitted to deepen the morphological details on the phases. The spinel iron oxide-hematite transition has been found size- and time-dependent for the single-phase iron oxide NPs (360–455 °C). The transition temperature has increased significantly when iron oxide is incorporated in a core-shell architecture, both as core (630 °C) and shell (520 °C), suggesting a stabilizing effect of cobalt ferrite. The hydrothermal stability of iron oxide and core-shell NPs has been found dependent on water content, time, and temperature, with a reducing effect of pentanol toward the formation of magnetite from maghemite, highlighted by 57Fe Mössbauer spectroscopy. The synergic effects of cobalt ferrite and pentanol have limited the formation of hematite, leading to the obtainment of magnetite-covered cobalt ferrite NPs upon the hydrothermal treatment