Modelling of Pyroelectric Response in Inhomogeneous Ferroelectric-Semiconductor Films

We have modified Landau-Khalatnikov approach and shown that the pyroelectric response of inhomogeneous ferroelectric-semiconductor films can be described by using six coupled equations for six order parameters: average displacement, its mean-square fluctuation and correlation with charge defects density fluctuations, average pyroelectric coefficient, its fluctuation and correlation with charge defects density fluctuations. Coupled equations demonstrate the inhomogeneous reversal of pyroelectric response in contrast to the equations of Landau-Khalatnikov type, which describe the homogeneous reversal with the sharp pyroelectric coefficient peak near the thermodynamic coercive field value. Within the framework of our model pyroelectric hysteresis loop becomes much smoother, thinner and lower as well as pyroelectric coefficient peaks near the coercive field completely disappear under the increase of disordering caused by defects. This effect is similar to the well-known "square to slim transition" of the ferroelectric hysteresis loops in relaxor ferroelectrics. Also the increase of defect concentration leads to the drastic decrease of the coercive field typical for disordered ferroelectrics. Usually pyroelectric hysteresis loops of doped and inhomogeneous ferroelectrics have typical smooth shape without any pyroelectric coefficient peaks and coercive field values much lower than the thermodynamic one. Therefore our approach qualitatively explains available experimental results. Rather well quantitative agreement between our modelling and typical Pb(Zr,Ti)O3-film pyroelectric and ferroelectric loops has been obtained.Comment: 14 pages, 5 figure

An investigation of artificial neural network structure and its effects on the estimation of the low-cycle fatigue parameters of various steels

Artificial neural networks (ANNs) are a widely used machine learning approach for estimating low-cycle fatigue parameters. ANN structure has its parameters such as hidden layers, hidden neurons, activation functions, training functions, and so forth, and these parameters have a significant influence over the results. Three hidden layer combinations, the hidden neurons ranging from 1 to 25, and different activation functions like hyperbolic tangent sigmoid (tansig), logistic sigmoid (logsig), and linear (purelin) were used, and their effects on the low-cycle fatigue parameter estimation were investigated to determine optimal ANN structure. Based on the results, suggestions regarding ANN structure for the estimation of the low-cycle fatigue parameters and transition fatigue life were presented. For the output layer and hidden layers, the most suitable activation function was tansig. The optimal hidden neuron range has been found between 4 and 9. The neural network structure with one hidden layer was determined to be most suitable in terms of less knowledge, structural complexity, and computational time and power

Identification of Burgers vectors along <111> in In-doped GaAs, by X-ray transmission topography andimage simulation.

International audienceLong dislocations with Burgers vectors along are unusual in f.c.c. lattices. X-ray topographs have beenobtained of as-grown GaAs crystals doped with 1020 atoms cm -3 of In, where the usual extinction criterion g.b = 0leads to this type of defect. However, for several g satisfying the condition g.b = 0 with b = a [111], the images of thesedislocations were still clearly visible. Comparison between experimental and computer-simulated X-ray topographicsections of these defects confirms the existence of Burgers vectors along

The 'Melanoma-enriched' microRNA miR-4731-5p acts as a tumour suppressor

We previously identified miR-4731-5p (miR-4731) as a melanoma-enriched microRNA following comparison of melanoma with other cell lines from solid malignancies. Additionally, miR-4731 has been found in serum from melanoma patients and expressed less abundantly in metastatic melanoma tissues from stage IV patients relative to stage III patients. As miR-4731 has no known function, we used biotin-labelled miRNA duplex pull-down to identify binding targets of miR-4731 in three melanoma cell lines (HT144, MM96L and MM253). Using the miRanda miRNA binding algorithm, all pulled-down transcripts common to the three cell lines (n=1092) had potential to be targets of miR-4731 and gene-set enrichment analysis of these (via STRING v9.1) highlighted significantly associated genes related to the ‘cell cycle’ pathway and the ‘melanosome’. Following miR-4731 overexpression, a selection (n=81) of pull-down transcripts underwent validation using a custom qRT-PCR array. These data revealed that miR-4731 regulates multiple genes associated with the cell cycle (e.g. CCNA2, ORC5L, and PCNA) and the melanosome (e.g. RAB7A, CTSD, and GNA13). Furthermore, members of the synovial sarcoma X breakpoint family (SSX) (melanoma growth promoters) were also down-regulated (e.g. SSX2, SSX4, and SSX4B) as a result of miR-4731 overexpression. Moreover, this down-regulation of mRNA expression resulted in ablation or reduction of SSX4 protein, which, in keeping with previous studies, resulted in loss of 2D colony formation. We therefore speculate that loss of miR-4731 expression in stage IV patient tumours supports melanoma growth by, in part; reducing its regulatory control of SSX expression levels

Formation and emergent dynamics of spatially organized microbial systems

Spatial organization is the norm rather than the exception in the microbial world. While the study of microbial physiology has been dominated by studies in well-mixed cultures, there is now increasing interest in understanding the role of spatial organization in microbial physiology, coexistence and evolution. Where studied, spatial organization has been shown to influence all three of these aspects. In this mini review and perspective article, we emphasize that the dynamics within spatially organized microbial systems (SOMS) are governed by feedbacks between local physico-chemical conditions, cell physiology and movement, and evolution. These feedbacks can give rise to emergent dynamics, which need to be studied through a combination of spatio-temporal measurements and mathematical models. We highlight the initial formation of SOMS and their emergent dynamics as two open areas of investigation for future studies. These studies will benefit from the development of model systems that can mimic natural ones in terms of species composition and spatial structure

Anisotropic coarse-grained statistical potentials improve the ability to identify native-like protein structures

We present a new method to extract distance and orientation dependent potentials between amino acid side chains using a database of protein structures and the standard Boltzmann device. The importance of orientation dependent interactions is first established by computing orientational order parameters for proteins with alpha-helical and beta-sheet architecture. Extraction of the anisotropic interactions requires defining local reference frames for each amino acid that uniquely determine the coordinates of the neighboring residues. Using the local reference frames and histograms of the radial and angular correlation functions for a standard set of non-homologue protein structures, we construct the anisotropic pair potentials. The performance of the orientation dependent potentials was studied using a large database of decoy proteins. The results demonstrate that the new distance and orientation dependent residue-residue potentials present a significantly improved ability to recognize native folds from a set of native and decoy protein structures.Comment: Submitted to "The Journal of Chemical Physics

Can single cell respiration be measured by scanning electrochemical microscopy (SECM)?

Ultramicroelectrode (UME), or, equivalently, microelectrode, probes are increasingly used for single-cell measurements of cellular properties and processes, including physiological activity, such as metabolic fluxes and respiration rates. Major challenges for the sensitivity of such measurements include: (i) the relative magnitude of cellular and UME fluxes (manifested in the current); and (ii) issues around the stability of the UME response over time. To explore the extent to which these factors impact the precision of electrochemical cellular measurements, we undertake a systematic analysis of measurement conditions and experimental parameters for determining single cell respiration rates via the oxygen consumption rate (OCR) in single HeLa cells. Using scanning electrochemical microscopy (SECM), with a platinum UME as the probe, we employ a self-referencing measurement protocol, rarely employed in SECM, whereby the UME is repeatedly approached from bulk solution to a cell, and a short pulse to oxygen reduction reaction (ORR) potential is performed near the cell and in bulk solution. This approach enables the periodic tracking of the bulk UME response to which the near-cell response is repeatedly compared (referenced) and also ensures that the ORR near the cell is performed only briefly, minimizing the effect of the electrochemical process on the cell. SECM experiments are combined with a finite element method (FEM) modeling framework to simulate oxygen diffusion and the UME response. Taking a realistic range of single cell OCR to be 1 × 10–18 to 1 × 10–16 mol s–1, results from the combination of FEM simulations and self-referencing SECM measurements show that these OCR values are at, or below, the present detection sensitivity of the technique. We provide a set of model-based suggestions for improving these measurements in the future but highlight that extraordinary improvements in the stability and precision of SECM measurements will be required if single cell OCR measurements are to be realized

Artificial reefs: from ecological processes to fishing enhancement tools

info:eu-repo/semantics/publishedVersio

Evolution of Taxis Responses in Virtual Bacteria: Non-Adaptive Dynamics

Bacteria are able to sense and respond to a variety of external stimuli, with responses that vary from stimuli to stimuli and from species to species. The best-understood is chemotaxis in the model organism Escherichia coli, where the dynamics and the structure of the underlying pathway are well characterised. It is not clear, however, how well this detailed knowledge applies to mechanisms mediating responses to other stimuli or to pathways in other species. Furthermore, there is increasing experimental evidence that bacteria integrate responses from different stimuli to generate a coherent taxis response. We currently lack a full understanding of the different pathway structures and dynamics and how this integration is achieved. In order to explore different pathway structures and dynamics that can underlie taxis responses in bacteria, we perform a computational simulation of the evolution of taxis. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better able to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. Dynamics that are adaptive under a wide range of conditions, as seen in the chemotaxis pathway of E. coli, do not evolve in these evolutionary simulations. However, we find that stimulus scarcity and fluctuations during evolution results in complex pathway dynamics that result both in adaptive and non-adaptive dynamics depending on basal stimuli levels. Further analyses of evolved pathway structures show that effective taxis dynamics can be mediated with as few as two components. The non-adaptive dynamics mediating taxis responses provide an explanation for experimental observations made in mutant strains of E. coli and in wild-type Rhodobacter sphaeroides that could not be explained with standard models. We speculate that such dynamics exist in other bacteria as well and play a role linking the metabolic state of the cell and the taxis response. The simplicity of mechanisms mediating such dynamics makes them a candidate precursor of more complex taxis responses involving adaptation. This study suggests a strong link between stimulus conditions during evolution and evolved pathway dynamics. When evolution was simulated under conditions of scarce and fluctuating stimulus conditions, the evolved pathway contained features of both adaptive and non-adaptive dynamics, suggesting that these two types of dynamics can have different advantages under distinct environmental circumstances