Reentrant transition induced by multiplictative noise in the Time Dependent Ginzburg-Landau model

An effect of multiplicative noise in the time-dependent Ginzburg-Landau model is reported, namely, that noise at a relatively low intensity induces a phase transition towards an ordered state, whereas strong noise plays a destructive role, driving the system back to its disordered state through a reentrant phase transition. The phase diagram is calculated analytically using a mean-field theory and a more sophisticated approach and is compared with the results from extensive numerical simulations.

Mean first-passage time of continuous non-Markovian processes driven by colored noise

An equation for mean first-passage times of non-Markovian processes driven by colored noise is derived through an appropriate backward integro-differential equation. The equation is solved in a Bourret-like approximation. In a weak-noise bistable situation, non-Markovian effects are taken into account by an effective diffusion coefficient. In this situation, our results compare satisfactorily with other approaches and experimental data.

Projecting the self to past and future in mental time

Introduction: Human experience takes place in the line of mental-time (MT) created through imagination of oneself in different time-points in past or future (self-projection in time). Here we manipulated self-projection in MT not only with respect to one's life-events but also with respect to one's faces from different past and future time-points. Methods: We here compared MTT with respect to one's facial images from different time points in past and future (study 1: MT-faces) as well as with respect to different past and future life events (study 2: MT-events). Participants were asked to make judgments about past and future face images and past and future events from three different time-points: the present (Now), eight years earlier (Past) or eight years later (Future). In addition, as a control task participants were asked to make recognition judgments with respect to faces and memory-related judgments with respect to events without changing their habitual self-location in time. Behavioral measures and functional magnetic resonance imaging (fMRI) activity after subtraction of recognition and memory related activities show both absolute MT and relative MT effects for faces and events, signifying a fundamental brain mechanism of MT, disentangled from episodic memory functions. Results: Behavioural and event-related fMRI activity showed three independent effects characterized by (1) similarity between past recollection and future imagination, (2) facilitation of judgments related to the future as compared to the past, and (3) facilitation of judgments related to time-points distant from the present. These effects were found with respect to faces and events suggesting that the brain mechanisms of MT are independent of whether actual life episodes have to be re-/pre-experienced and recruited a common cerebral network including the medial-temporal, precuneus, inferior-frontal, temporo-parietal, and insular cortices. Conclusions: These behavioural and neural data suggest that self-projection in time is a crucial aspect of MT, relying on neural structures encoding memory, mental imagery, and self. Furthermore our results emphasize the idea that mental temporal processing is more strongly directed to future prediction than to past recollection.

Multi-well fungal co-culture for de novo metabolite-induction in time-series studies based on untargeted metabolomics.

The induction of fungal metabolites by fungal co-cultures grown on solid media was explored using multi-well co-cultures in 2 cm diameter Petri dishes. Fungi were grown in 12-well plates to easily and rapidly obtain the large number of replicates necessary for employing metabolomic approaches. Fungal culture using such a format accelerated the production of metabolites by several weeks compared with using the large-format 9 cm Petri dishes. This strategy was applied to a co-culture of a Fusarium and an Aspergillus strain. The metabolite composition of the cultures was assessed using ultra-high pressure liquid chromatography coupled to electrospray ionisation and time-of-flight mass spectrometry, followed by automated data mining. The de novo production of metabolites was dramatically increased by nutriment reduction. A time-series study of the induction of the fungal metabolites of interest over nine days revealed that they exhibited various induction patterns. The concentrations of most of the de novo induced metabolites increased over time. However, interesting patterns were observed, such as with the presence of some compounds only at certain time points. This result indicates the complexity and dynamic nature of fungal metabolism. The large-scale production of the compounds of interest was verified by co-culture in 15 cm Petri dishes; most of the induced metabolites of interest (16/18) were found to be produced as effectively as on a small scale, although not in the same time frames. Large-scale production is a practical solution for the future production, identification and biological evaluation of these metabolites.

N2O emissions from a cultivated mollisol: optimal time of day for sampling and the role of soil temperature

The correct use of closed field chambers to determine N2O emissions requires defining the time of day that best represents the daily mean N2O flux. A short-term field experiment was carried out on a Mollisol soil, on which annual crops were grown under no-till management in the Pampa Ondulada of Argentina. The N2O emission rates were measured every 3 h for three consecutive days. Fluxes ranged from 62.58 to 145.99 ∝g N-N2O m-2 h-1 (average of five field chambers) and were negatively related (R² = 0.34, p < 0.01) to topsoil temperature (14 - 20 ºC). N2O emission rates measured between 9:00 and 12:00 am presented a high relationship to daily mean N2O flux (R² = 0.87, p < 0.01), showing that, in the study region, sampling in the mornings is preferable for GHG.

On the many-time formulation of classical particle dynamics

Starting from the standard one-time dynamics of n nonrelativistic particles, the n-time equations of motion are inferred, and a variational principle is formulated. A suitable generalization of the classical LieKnig theorem is demonstrated, which allows the determination of all the associated presymplectic structures. The conditions under which the action of an invariance group is canonical are studied, and a corresponding Noether theorem is deduced. A formulation of the theory in terms of n first-class constraints is recovered by means of coisotropic imbeddings. The proposed approach also provides for a better understanding of the relativistic particle dynamics, since it shows that the different roles of the physical positions and the canonical variables is not peculiar to special relativity, but rather to any n-time approach: indeed a nonrelativistic no-interaction theorem is deduced.

Isothermal microcalorimetry: a novel method for real-time determination of antifungal susceptibility of Aspergillus species.

We evaluated microcalorimetry for real-time susceptibility testing of Aspergillus spp. based on growth-related heat production. The minimal heat inhibitory concentration (MHIC) for A. fumigatus ATCC 204305 was 1 mg/L for amphotericin B, 0.25 mg/L for voriconazole, 0.06 mg/L for posaconazole, 0.125 mg/L for caspofungin and 0.03 mg/L for anidulafungin. Agreement within two 2-fold dilutions between MHIC (determined by microcalorimetry) and MIC or MEC (determined by CLSI M38A) was 90% for amphotericin B, 100% for voriconazole, 90% for posaconazole and 70% for caspofungin. This proof-of-concept study demonstrated the potential of isothermal microcalorimetry for growth evaluation of Aspergillus spp. and real-time antifungal susceptibility testing.

Nonlinear relaxation time and the detection of weak signals

Laser systems can be used to detect very weak optical signals. The physical mechanism is the dynamical process of the relaxation of a laser from an unstable state to a steady stable state. We present an analysis of this process based on the study of the nonlinear relaxation time. Our analytical results are compared with numerical integration of the stochastic differential equations that model this process.

Water percolation estimated with time domain reflectometry (TDR) in drainage lysimeters

Due to the difficulty of estimating water percolation in unsaturated soils, the purpose of this study was to estimate water percolation based on time-domain reflectometry (TDR). In two drainage lysimeters with different soil textures TDR probes were installed, forming a water monitoring system consisting of different numbers of probes. The soils were saturated and covered with plastic to prevent evaporation. Tests of internal drainage were carried out using a TDR 100 unit with constant dielectric readings (every 15 min). To test the consistency of TDR-estimated percolation levels in comparison with the observed leachate levels in the drainage lysimeters, the combined null hypothesis was tested at 5 % probability. A higher number of probes in the water monitoring system resulted in an approximation of the percolation levels estimated from TDR - based moisture data to the levels measured by lysimeters. The definition of the number of probes required for water monitoring to estimate water percolation by TDR depends on the soil physical properties. For sandy clay soils, three batteries with four probes installed at depths of 0.20, 0.40, 0.60, and 0.80 m, at a distance of 0.20, 0.40 and 0.6 m from the center of lysimeters were sufficient to estimate percolation levels equivalent to the observed. In the sandy loam soils, the observed and predicted percolation levels were not equivalent even when using four batteries with four probes each, at depths of 0.20, 0.40, 0.60, and 0.80 m.