Thermal signal propagation in soils in Romania: conductive and non-conductive processes

Temperature data recorded in 2002 and 2003 at 10 stations out of the 70 available in the Romanian automatic weather stations network are presented and analyzed in terms of the heat transfer from air to underground. The air temperature at 2 m, the soil temperatures at 0, 5, 10, 20, 50 and 100 cm below the surface as well as rain fall and snow cover thickness have been monitored. The selected locations sample various climate environments in Romania. Preliminary analytical modelling shows that soil temperatures track air temperature variations at certain locations and, consequently, the heat transfer is by conduction, while at other stations processes such as soil freezing and/or solar radiation heating play an important part in the heat flux balance at the air/soil interface. However, the propagation of the annual thermal signal in the uppermost one meter of soil is mainly by conduction; the inferred thermal diffusivity for 8 stations with continuous time series at all depth levels ranges from 3 to 10×10<sup>−7</sup> m<sup>2</sup> s<sup>−1</sup>

Visuomotor learning promotes visually evoked activity in the medial prefrontal cortex

The medial prefrontal cortex (mPFC) is necessary for executing many learned associations between stimuli and movement. It is unclear, however, how activity in the mPFC evolves across learning, and how this activity correlates with sensory stimuli and the learned movements they evoke. To address these questions, we record cortical activity with widefield calcium imaging while mice learned to associate a visual stimulus with a forelimb movement. After learning, the mPFC shows stimulus-evoked activity both during task performance and during passive viewing, when the stimulus evokes no action. This stimulus-evoked activity closely tracks behavioral performance across training, with both exhibiting a marked increase between days when mice first learn the task, followed by a steady increase with further training. Electrophysiological recordings localized this activity to the secondary motor and anterior cingulate cortex. We conclude that learning a visuomotor task promotes a route for visual information to reach the prefrontal cortex

Anodal-tDCS over the human right occipital cortex enhances the perception and memory of both faces and objects

Accurate face processing skills are pivotal for typical social cognition, and impairments in this ability characterise various clinical conditions (e.g., prosopagnosia). No study to date has investigated whether transcranial direct current stimulation (tDCS) can causally enhance face processing. In addition, the category- and the process- specificity of tDCS effects, as well as the role of the timing of neuromodulation with respect to the execution of cognitive tasks are still unknown. In this single-blind, sham-controlled study, we examined whether the administration of anodal-tDCS (a-tDCS) over the right occipital cortex of healthy volunteers (N = 64) enhances performance on perceptual and memory tasks involving both face and object stimuli. Neuromodulation was delivered in two conditions: online (a-tDCS during task execution) and offline (a-tDCS before task execution). The results demonstrate that offline atDCS enhances the perception and memory performance of both faces and objects. There was no effect of online a-tDCS on behaviour. Furthermore, the offline effect was site-specific since a-tDCS over the sensory-motor cortex did not lead to behavioural changes. Our results add relevant information about the breadth of cognitive processes and visual stimuli that can be modulated by tDCS, and about the design of effective neuromodulation protocols, which have implications for advancing theories in cognitive neuroscience and clinical applications

Electromagnetic follow-up of gravitational wave transient signal candidates

Pioneering efforts aiming at the development of multi-messenger gravitational wave and electromagnetic astronomy have been made. An electromagnetic observation follow-up program of candidate gravitational wave events has been performed (Dec 17 2009 to Jan 8 2010 and Sep 4 to Oct 20 2010) during the recent runs of the LIGO and Virgo gravitational wave detectors. It involved ground-based and space electromagnetic facilities observing the sky at optical, X-ray and radio wavelengths. The joint gravitational wave and electromagnetic observation study requires the development of specific image analysis procedures able to discriminate the possible electromagnetic counterpart of gravitational wave triggers from contaminant/background events. The paper presents an overview of the electromagnetic follow-up program and the image analysis procedures.Comment: Proceedings of the 12th International Conference on "Topics in Astroparticle and Underground Physics" (TAUP 2011), Munich, September 2011 (to appear in IoP Journal of Physics: Conference Series

ELECTRO-ACOUSTIC ANALOGIES BETWEEN THERMOELASTIC COMPONENT OF THE PHOTOACOUSTIC SIGNAL AND LOW-PASS RC FILTER

This paper presents a new approach to the thermal characterization of aluminum, based on the electro-acoustic analogy between the thermoelastic component of the photoacoustic signal and the passive RC low-pass filter. The analogies were used to calculate the characteristic thermoelastic cut-off frequencies of the photoacoustic component and obtain their relationship with the thickness of the aluminum samples. Detailed numerical analysis showed that the required relationship is linear in the log-log scale and can serve as a reference curve for the given material. The results of the numerical analysis were also confirmed experimentally

Еvaluation of Thermophysical Properties of Semiconductors by Photoacoustic Phase Neural Network

The idea of this paper is to develop a method for determination thermal diffusivity, linear expansion coefficient and thickness of a semiconductor sample from photoacoustic phase measurement by using neural network. The neural network has been trained on photoacoustic phases obtained from a theoretical model of measured signal for Si n-type in the range of 20Hz to 20kHz. For the analysis of parameter determination from phases, we trained phase neural networks on a large database obtained from numerical experiments in the expected range of parameter changes. An analysis of a theoretical photoacoustic model with a phase neural network is demonstrated. The advantages of using a phase neural network with high accuracy and precision in prediction depending on the number of epochs are presented, as well as analyzes of the application of random Gaussian noise to the network in order to better predict the experimental photoacoustic signal.BPU11 : 11th International Conference of the Balkan Physical Union : Proceedings book; Aug 11 - Sep 1, 2022S07-OP Optics and Photonic

Photoacoustic characterization of TiO2 thin-films deposited on Silicon substrate using neural networks

In this paper, the possibility of determining the thermal, elastic and geometric characteristics of a thin TiO2 film deposited on a silicon substrate, thickness 30 mikrons, in the frequency range of 20 to 20 kHz with neural networks was analyzed. For this purpose, the substrate parameters remained the known and constant in the two-layer model and nano layer thin-film parameters were changed: thickness, expansion and thermal diffusivity. Prediction of these three parameters was analyzed separately with three neural networks and all of these together by fourth neural network. It was shown that neural network, which analyzed all three parameters at the same time, achieved the highest accuracy, so the use of networks that provide predictions for only one parameter is less reliable.Comment: 21 pages, 5 figure

Results of international standardised beekeeper surveys of colony losses for winter 2012-2013 : analysis of winter loss rates and mixed effects modelling of risk factors for winter loss.

This article presents results of an analysis of winter losses of honey bee colonies from 19 mainly European countries, most of which implemented the standardised 2013 COLOSS questionnaire. Generalised linear mixed effects models (GLMMs) were used to investigate the effects of several factors on the risk of colony loss, including different treatments for Varroa destructor, allowing for random effects of beekeeper and region. Both winter and summer treatments were considered, and the most common combinations of treatment and timing were used to define treatment factor levels. Overall and within country colony loss rates are presented. Significant factors in the model were found to be: percentage of young queens in the colonies before winter, extent of queen problems in summer, treatment of the varroa mite, and access by foraging honey bees to oilseed rape and maize. Spatial variation at the beekeeper level is shown across geographical regions using random effects from the fitted models, both before and after allowing for the effect of the significant terms in the model. This spatial variation is considerable