Laning and clustering transitions in driven binary active matter systems

It is well known that a binary system of nonactive disks that experience driving in opposite directions exhibits jammed, phase separated, disordered, and laning states. In active matter systems, such as a crowd of pedestrians, driving in opposite directions is common and relevant, especially in conditions which are characterized by high pedestrian density and emergency. In such cases, the transition from laning to disordered states may be associated with the onset of a panic state. We simulate a laning system containing active disks that obey run-and-tumble dynamics, and we measure the drift mobility and structure as a function of run length, disk density, and drift force. The activity of each disk can be quantified based on the correlation timescale of the velocity vector. We find that in some cases, increasing the activity can increase the system mobility by breaking up jammed configurations; however, an activity level that is too high can reduce the mobility by increasing the probability of disk-disk collisions. In the laning state, the increase of activity induces a sharp transition to a disordered strongly fluctuating state with reduced mobility. We identify a novel drive-induced clustered laning state that remains stable even at densities below the activity-induced clustering transition of the undriven system. We map out the dynamic phase diagrams highlighting transitions between the different phases as a function of activity, drive, and density.

Evolution of ELNES spectra as a function of experimental settings for any uniaxial specimen: A fully relativistic study

We perform calculations of the fully relativistic, corrected geometrical weighting of the pi* and sigma* transitions measured from the 1s core loss electron energy loss spectroscopy (EELS) spectrum in any uniaxial specimen. We present a complete calculation of the differential scattering cross-section (DSCS), taking into account the collection angle, the illumination angle and the tilt of the sample over the optical axis. Owing to high electron velocity in an EELS experiment, the relativistic correction has to be considered. We thus, present a relativistic, corrected DSCS by using the theory recently developed by Jouffrey et al. [Ultramicroscopy 102 (2004) 61] and P. Schattschneider et al. [Phys. Rev. B 72 (2005) 045142]. The relativistic correction is first performed in the natural coordinate system of the scattering event. We then point out a straightforward method to introduce this correction in the microscopic coordinate system, where all calculations have to be done to be experimentally useful. Using the fully corrected DSCS, we present an expression predicting the evolution of the R=pi*/(pi*+sigma*) ratio (related to the ratio of sp2 and sp3 bondings) as a function of experimental settings. We show how the R-evolution can be predicted, for any experimental setting, by the knowledge of one unique reference value. We verify on graphite specimens, the validity of the R-calculation by comparing theoretical predictions presented in this work with experimental data published elsewhere [Daniels et al., Ultramicroscopy 96 (2003) 523 and Menon et al., Ultramicroscopy 74 (1998) 83].

Degeneration of dopaminergic neurons triggers an expression of individual enzymes of dopamine synthesis in non-dopaminergic neurons of the arcuate nucleus in adult rats

Non-dopaminergic neurons expressing individual complementary enzymes dopamine (DA) synthesis were shown to produce DA in cooperation [Ugrumov, M., Melnikova, V., Ershov, P., Balan, I., Calas A., 2002. Tyrosine hydroxylase- and/or aromatic L-amino acid decarboxylase-expressing neurons in the rat arcuate nucleus: ontogenesis and functional significance. Psychoneuroendocrinology 27, 533-548; Ugrumov, M.V., Melnikova, V.I., Lavrentyeva, A.V., Kudrin, V.S., Rayevsky, K.S., 2004. Dopamine synthesis by non-dopaminergic neurons expressing individual complementary enzymes of the dopamine synthetic pathway in the arcuate nucleus of fetal rats. Neuroscience 124, 629-635]. This study was aimed at testing our hypothesis that the cooperative synthesis of DA in non-dopaminergic neurons is an adaptive reaction under functional insufficiency of the dopaminergic system. Functional insufficiency of the tuberoinfundibular dopaminergic system was provoked by 6-OHDA-induced degeneration of dopaminergic neurons in the arcuate nucleus in adult rats. Bienzymatic (dopaminergic) neurons and monoenzymatic neurons expressing tyrosine hydroxylase (TH) or aromatic L-amino acid decarboxylase (AADC) were detected with a double-immunofluorescent technique on cryostat sections. The 6-OHDA-induced degeneration of dopaminergic neurons was accompanied by a significant increase of the number of monoenzymatic TH neurons and AADC neurons that appears to support our hypothesis. The reaction of bienzymatic and monoenzymatic neuron populations to the 6-OHDA administration occurred to be region-specific. The former disappeared in the dorsomedial region of the arcuate nucleus while the latter increased in the ventrolateral region. Thus, degeneration of dopaminergic neurons in the arcuate nucleus of adult rats is accompanied by the expression of individual enzymes of DA synthesis in non-dopaminergic neurons that may be an adaptive reaction.

A novel reconstruction algorithm to extend the CT scan field-of-view

For various reasons, a projection dataset acquired on a computed tomography (CT) scanner can be truncated. That is, a portion of the scanned object is positioned outside the scan field-of-view (SFOV) and the line integrals corresponding to those regions are not measured. A projection truncation problem causes imaging artifacts that lead to suboptimal image quality. In this paper, we propose a reconstruction algorithm that enables an adequate estimation of the projection outside the SFOV. We make use of the fact that the total attenuation of each ideal projection in a parallel sampling geometry remains constant over views. We use the magnitudes and slopes of the projection samples at the location of truncation to estimate water cylinders that can best fit to the projection data outside the SFOV. To improve the robustness of the algorithm, continuity constraints are placed on the fitting parameters. Extensive phantom and patient experiments were conducted to test the robustness and accuracy of the proposed algorithm.

Nucleation and growth of single-walled nanotubes: the role of metallic catalysts

We present a review of experimental and theoretical results on the nucleation and growth of single-walled nanotubes, with particular emphasis on the growth of nanotube bundles emerging from catalyst particles obtained from evaporation-based elaboration techniques. General results are first discussed. Experiments strongly suggest a root-growth process in which carbon, dissolved at high temperatures in catalytic particles, segregates at the surface at lower temperatures to form tube embryos and finally nanotubes through a nucleation and growth process. A theoretical analysis of the reasons carbon does not always form graphene sheets to wrap the particles suggests analogies with other surface or interface instabilities, in particular, with those found in epitaxial growth. In the second part, detailed experimental results for nickel-rare earth metal catalysts are presented. By using various electron microscopy techniques, it is shown that carbon and the rare earth metal co-segregate at the surface of the particle and form carbide platelets, providing nucleation sites for nanotubes growing in directions perpendicular to the surface. A simple theoretical model is then presented in which the role of the rare earth metal is just to transfer electrons from metal to carbon. The graphene sheet is shown to become unstable; pentagons and heptagons are favored, which can explain the occurrence of local curvatures and of tube embryos. Finally, a brief discussion of some recent atomistic models is given.

Calculation of the Pitot tube correction factor for Newtonian and non-Newtonian fluids

This paper presents the numerical investigation performed to calculate the correction factor for Pitot tubes. The purely viscous non-Newtonian fluids with the power-law model constitutive equation were considered. It was shown that the power-law index, the Reynolds number, and the distance between the impact and static tubes have a major influence on the Pitot tube correction factor. The problem was solved for a wide range of these parameters. It was shown that employing Bernoulli's equation could lead to large errors, which depend on the magnitude of the kinetic energy and energy friction loss terms. A neural network model was used to correlate the correction factor of a Pitot tube as a function of these three parameters. This correlation is valid for most Newtonian, pseudoplastic, and dilatant fluids at low Reynolds number.

Multicriteria optimization of gluconic acid production using net flow

The biochemical process industry is often confronted with the challenge of making decisions in an atmosphere of multiple and conflicting objectives. Recent innovations in the field of operations research and systems science have yielded rigorous multicriteria optimization techniques that can be successfully applied to the field of biochemical engineering. These techniques incorporate the expert's experience into the optimization routine and provide valuable information about the zone of possible solutions. This paper presents a multicriteria optimization strategy that generates a Pareto domain, given a set of conflicting objective criteria, and determines the optimal operating region for the production of gluconic acid using the net flow method (NFM). The objective criteria include maximizing the productivity and concentration of gluconic acid, while minimizing the residual substrate. Three optimization strategies are considered. The first two strategies identify the optimal operating region for the process inputs. The results yielded an acceptable compromise between productivity, gluconic acid concentration and residual substrate concentration. Fixing the process inputs representing the batch time, initial substrate concentration and initial biomass equal to their optimal values, the remaining simulations were used to study the sensitivity of the optimum operating region to changes in the oxygen mass transfer coefficient, K(L) a, by utilizing a multi-level K(L) a strategy. The results show that controlling K(L) a during the reaction reduced the production of biomass, which in turn resulted in increased productivity and concentration of gluconic acid above that of a fixed K(L) a.

Statistical data validation methods for large cheese plant database

Production data of the cheesemaking process are used to monitor milk fat and protein recoveries in cheese, cheese yield, and composition and eventually to predict these parameters. Due to the large impact of these factors on cheese quality and plant profitability, it is very important to use reliable data for analysis, modeling, and control of the process. This paper tested six methods for detecting erroneous data in industrial cheesemaking databases. The data analyzed came from 4 yr of stirred-curd Cheddar cheese production in an industrial cheesemaking facility, comprising over 10,000 vats. Single vat outliers were detected using a simple statistical criterion of mean +/- 3.6 SD on single variable distributions, Fourier series modeling of seasonal variables (fat, protein, lactose, and total solids in milk, and protein in whey), and the multivariate Mahalanobis outlier analysis. Detection of outlier productions (corresponding to several vats) was done by applying the mean +/- 3.6 SD criterion to variables obtained through calculating the fat mass balance, fat retention coefficient, and yield efficiency. Data treatment enabled the detection of outlier data, but also pinpointed variables with a low reliability (manually registered times). Single variable and multivariable methods proved complementary, and the use of both types of methods is recommended when validating an existing database.