Giant heat dissipation at the low temperature reversible-irreversible transition in Gd5Ge4

The heat exchanged at the low-temperature first-order magnetostructural transition is directly measured in Gd5Ge4 . Results show that the origin and the temperature dependence of the heat exchanged varies with the reversible/irreversible character of the first-order transition. In the reversible regime, the heat exchanged by the sample is mostly due to the latent heat at the transition and decreases with decreasing temperature, while in the irreversible regime, the heat is irreversibly dissipated and increases strongly with decreasing temperature, reaching a value of 237 J/kg at 4 K.

Long-range-interactions induced ordered structures in deposition processes

We present a new model of sequential adsorption in which the adsorbing particles experience dipolar interactions. We show that in the presence of these long-range interactions, highly ordered structures in the adsorbed layer may be induced at low temperatures. The new phenomenology is manifest through significant variations of the pair correlation function and the jamming limit, with respect to the case of noninteracting particles. Our study could be relevant in understanding the adsorption of magnetic colloidal particles in the presence of a magnetic field.

Finite-temperature QED effects in atoms

We argue that low-temperature effects in QED can, if anywhere, only be quantitatively interesting for bound electrons. Unluckily the dominant thermal contribution turns out to be level independent, so that it does not affect the frequency of the transition radiation.

Analytic behavior of the QED polarizability function at finite temperature

We revisit the analytical properties of the static quasi-photon polarizability function for an electron gas at finite temperature, in connection with the existence of Friedel oscillations in the potential created by an impurity. In contrast with the zero temperature case, where the polarizability is an analytical function, except for the two branch cuts which are responsible for Friedel oscillations, at finite temperature the corresponding function is non analytical, in spite of becoming continuous everywhere on the complex plane. This effect produces, as a result, the survival of the oscillatory behavior of the potential. We calculate the potential at large distances, and relate the calculation to the non-analytical properties of the polarizability.

Treatment of pregnant rats with oleoyl-estrone slows down pup fat deposition after weaning

BACKGROUND: In rats, oral oleoyl-estrone (OE) decreases food intake and body lipid content. The aim of this study was to determine whether OE treatment affects the energy metabolism of pregnant rats and eventually, of their pups; i.e. changes in normal growth patterns and the onset of obesity after weaning. METHODS: Pregnant Wistar rats were treated with daily intragastric gavages of OE in 0.2 ml sunflower oil from days 11 to 21 of pregnancy (i.e. 10 nmol oleoyl-estrone/g/day). Control animals received only the vehicle. Plasma and hormone metabolites were determined together with variations in cellularity of adipose tissue. RESULTS: Treatment decreased food intake and lowered weight gain during late pregnancy, mainly because of reduced adipose tissue accumulation in different sites. OE-treated pregnant rats' metabolic pattern after delivery was similar to that of controls. Neonates from OE-treated rats weighed the same as those from controls. They also maintained the same growth rate up to weaning, but pups from OE-treated rats slowed their growth rate afterwards, despite only limited differences in metabolite concentrations. CONCLUSION: The OE influences on pup growth can be partially buffered by maternal lipid mobilization during the second half of pregnancy. This maternal metabolic "imprinting" may condition the eventual accumulation of adipose tissue after weaning, and its effects can affect the regulation of body weight up to adulthood.

Morphological changes in convection-diffusion-limited deposition

The effect of hydrodynamic flow upon diffusion-limited deposition on a line is investigated using a Monte Carlo model. The growth process is governed by the convection and diffusion field. The convective diffusion field is simulated by the biased-random walker resulting from a superimposed drift that represents the convective flow. The development of distinct morphologies is found with varying direction and strength of drift. By introducing a horizontal drift parallel to the deposition plate, the diffusion-limited deposit changes into a single needle inclined to the plate. The width of the needle decreases with increasing strength of drift. The angle between the needle and the plate is about 45° at high flow rate. In the presence of an inclined drift to the plate, the convection-diffusion-limited deposit leads to the formation of a characteristic columnar morphology. In the limiting case where the convection dominates, the deposition process is equivalent to ballistic deposition onto an inclined surface.

Comment on: Deuterium nuclear fusion at room temperature: A pertinent inequality on barrier penetration

In a recent letter, Rosen claims to justify ...

High-Temperature magnetic ordering in a new organic magnet

Magnetization, heat capacity, and neutron diffraction experiments on the beta-phase of the dithiadiazolyl radical, p-NC.C6F4.CNSSN., provide conclusive evidence that this system exhibits noncollinear antiferromagnetism at 35.5 K, an unprecedented temperature for an organic radical. On the basis of magnetization and powder neutron diffraction results, coupled with theoretical calculations of the spin distribution within the molecule, a magnetic structure for this compound is proposed in which the interactions propagate through S . . .N contacts.

Deposition and residues of azoxystrobin and imidacloprid on greenhouse lettuce with implications for human consumption

Lettuce greenhouse experiments were carried out from March to June 2011 in order to analyze how pesticides behave from the time of application until their intake via human consumption taking into account the primary distribution of pesticides, field dissipation, and post-harvest processing. In addition, experimental conditions were used to evaluate a new dynamic plant uptake model comparing its results with the experimentally derived residues. One application of imidacloprid and two of azoxystrobin were conducted. For evaluating primary pesticide distribution, two approaches based on leaf area index and vegetation cover were used and results were compared with those obtained from a tracer test. High influence of lettuce density, growth stage and type of sprayer was observed in primary distribution showing that low densities or early growth stages implied high losses of pesticides on soil. Washed and unwashed samples of lettuce were taken and analyzed from application to harvest to evaluate removal of pesticides by food processing. Results show that residues found on the Spanish preharvest interval days were in all cases below officially set maximum residue limits, although it was observed that time between application and harvest is as important for residues as application amounts. An overall reduction of 40–60% of pesticides residues was obtained from washing lettuce. Experimentally derived residues were compared with modeled residues and deviate from 1.2 to 1.4 for imidacloprid and azoxystrobin, respectively, presenting good model predictions. Resulting human intake fractions range from... for imidacloprid to ... for azoxystrobin.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.