Dynamics of coupled and uncoupled two-phase flows in a slab mold

Two-phase flows in a mold of a slab caster are studied using water modeling, particle-image velocimetry (PIV), and computational fluid-dynamics techniques. Two-way coupled flows are observed in liquidgas systems, because both phases influence each other’s momentum transfer. In addition to this concept, PIV measurements indicate the existence of structurally coupled flows, where the velocity vectors of both phases observe similar orientations. When the drag forces of the liquid, exerted on the bubbles, exceed a certain value of the inertial forces of the liquid phase, at high mass loads of gas (ratio of mass flow rates of the gas phase and the liquid phase), the flow becomes structurally coupled. These types of flows promote large oscillations of the meniscus level. Two jets, liquid and bubble, were identified; the latter always reported larger angles than the first, independent of the gas load. Thus, a gas-rich jet is located closer to the lower edge of the submerged entry nozzle (SEN) port, and the liquid-rich jet is found above this position. The liquid-jet angle approaches that of the SEN port when the flow becomes structurally coupled. Structurally uncoupled flows report gas jets that follow torrent-type patterns which are well explained using a multiphase fluid-dynamics model. Structurally coupled flows yield gas jets with a continuous pattern.     

Insights into the Pharmacokinetics and In Vitro Cell-Based Studies of the Imidazoline I2 Receptor Ligand B06

The impact of neurodegenerative diseases (ND) is becoming unbearable for humankind due to their vast prevalence and the lack of efficacious treatments. In this scenario, we focused on imidazoline I₂ receptors (I₂-IR) that are widely distributed in the brain and are altered in patients with brain disorders. We took the challenge of modulating I₂-IR by developing structurally new molecules, in particular, a family of bicyclic α-iminophosphonates, endowed with high affinity and selectivity to these receptors. Treatment of two murine models, one for age-related cognitive decline and the other for Alzheimer’s disease (AD), with representative compound B06 ameliorated their cognitive impairment and improved their behavioural condition. Furthermore, B06 revealed beneficial in vitro ADME-Tox properties. The pharmacokinetics (PK) and metabolic profile are reported to de-risk B06 for progressing in the preclinical development. To further characterize the pharmacological properties of B06, we assessed its neuroprotective properties and beneficial effect in an in vitro model of Parkinson’s disease (PD). B06 rescued the human dopaminergic cell line SH-SY5Y from death after treatment with 6-hydroxydopamine (6-OHDA) and showed a crucial anti-inflammatory effect in a cellular model of neuroinflammation. This research reveals B06 as a putative candidate for advancing in the difficult path of drug discovery and supports the modulation of I₂-IR as a fresh approach for the therapy of ND.     

Postischemic Neuroprotection of Aminoethoxydiphenyl Borate Associates Shortening of Peri-Infarct Depolarizations

Brain stroke is a highly prevalent pathology and a main cause of disability among older adults. If not promptly treated with recanalization therapies, primary and secondary mechanisms of injury contribute to an increase in the lesion, enhancing neurological deficits. Targeting excitotoxicity and oxidative stress are very promising approaches, but only a few compounds have reached the clinic with relatively good positive outcomes. The exploration of novel targets might overcome the lack of clinical translation of previous efficient preclinical neuroprotective treatments. In this study, we examined the neuroprotective properties of 2-aminoethoxydiphenyl borate (2-APB), a molecule that interferes with intracellular calcium dynamics by the antagonization of several channels and receptors. In a permanent model of cerebral ischemia, we showed that 2-APB reduces the extent of the damage and preserves the functionality of the cortical territory, as evaluated by somatosensory evoked potentials (SSEPs). While in this permanent ischemia model, the neuroprotective effect exerted by the antioxidant scavenger cholesteronitrone F2 was associated with a reduction in reactive oxygen species (ROS) and better neuronal survival in the penumbra, 2-APB did not modify the inflammatory response or decrease the content of ROS and was mostly associated with a shortening of peri-infarct depolarizations, which translated into better cerebral blood perfusion in the penumbra. Our study highlights the potential of 2-APB to target spreading depolarization events and their associated inverse hemodynamic changes, which mainly contribute to extension of the area of lesion in cerebrovascular pathologies.     

Poroelastic behaviour of a water-saturated limestone

This paper presents the results of an experimental study carried out on a porous, water-saturated limestone. First, a set of poroelastic parameters is obtained from a wide range of experiments (drained, undrained, pore pressure loading and unjacketed tests) conducted on the same sample at the same stress state. A “null” test, inspired from unsaturated soil testing, is added to confirm the previous results, in particular the value of the Biot coefficient. Then, the variation of the measured parameters between samples is investigated. Finally, the influence of the stress state is studied in the framework of semilinear poroelasticity. Several expressions are compared to model the evolution of the drained bulk modulus as a function of Terzaghi's effective stress.     

Modeling and gradient pattern analysis of irregular SFM structures of porous silicon

Technological applications in opto-electronic devices have increased the interest in characterizing porous silicon structure patterns. Due to its physical properties, solutions from KPZ 2D are adopted to simulate the structure of porous material interface whose spatial characteristics are equivalent to those found in porous silicon samples. The analysis of the simulated and real Scanning Force Microscopy (SFM) surfaces was done using the Gradient Pattern Analysis (GPA). We found that the KPZ 2D model presented asymmetry levels compatible with the irregular surfaces observed by means of SFM images of π-Si.     

Optimisation de ľefficacité de couplage entre un guide ďonde confiné et une fibre optique monomode par ľintermédiaire ďune lentille boule

Theoretical coupling efficiency between a channel waveguide and a single-mode optical fibre using a ball lens is optimized by varying the parameters of the optical system such as the relative position of the components, the refractive index and the size of the lens. A specific software has been used for the optimization. Numerical calculations have been done under the Gaussian approximation of the fields distributions. The losses due to waveguides misalignments with respect to their ideal position have been evaluated. All these theoretical results are compared with those obtained from buttcoupling.     

Managing logical channel configurations in complex satellite architectures

As a result of the increased switching complexity of many communications satellites, often transponders are available with a variety of configuration options offering flexibility in power, bandwidth, and coverage. Many of these configurations share resources that prevent them from being simultaneously active, making it a challenge to understand and manage the satellite capacity inventory. In this paper we define the logical channel configuration (LCC) as an unambiguous unit of the inventory and present a novel method of modelling the interdependencies between these LCCs using linear algebra. In particular, a projector matrix is defined which can be used to update the activation state of all LCCs when the state of one or more of these is changed. As a result, a number of valid LCC scenarios can be easily generated and evaluated for optimal use of the satellite resources. Copyright © 2005 John Wiley & Sons, Ltd.     

Molds and Resists Studies for Nanoimprint Lithography of Electrodes in Low-Voltage Polymer Thin-Film Transistors

A low-cost patterning of electrodes was investigated looking forward to replacing conventional photolithography for the processing of low-operating voltage polymeric thin-film transistors. Hard silicon, etched by sulfur hexafluoride and oxygen gas mixture, and flexible polydimethylsiloxane imprinting molds were studied through atomic force microscopy (AFM) and field emission gun scanning electron microscopy. The higher the concentration of oxygen in reactive ion etching, the lower the etch rate, sidewall angle, and surface roughness. A concentration around 30 % at 100 mTorr, 65 W and 70 sccm was demonstrated as adequate for submicrometric channels, presenting a reduced etch rate of 176 nm/min. Imprinting with positive photoresist AZ1518 was compared to negative SU-8 2002 by optical microscopy and AFM. Conformal results were obtained only with the last resist by hot embossing at 120 °C and 1 kgf/cm² for 2 min, followed by a 10 min post-baking at 100 °C. The patterning procedure was applied to define gold source and drain electrodes on oxide-covered substrates to produce bottom-gate bottom-contact transistors. Poly(3-hexylthiophene) (P3HT) devices were processed on high-κ titanium oxynitride (TiO _x N _y ) deposited by radiofrequency magnetron sputtering over indium tin oxide-covered glass to achieve low-voltage operation. Hole mobility on micrometric imprinted channels may approach amorphous silicon (～0.01 cm²/V s) and, since these devices operated at less than 5 V, they are not only suitable for electronic applications but also as sensors in aqueous media.     

Two-dimensional profiles of fumonisin B1 production by Fusarium moniliforme and Fusarium proliferatum in relation to environmental factors and potential for modelling toxin formation in maize grain

This study has examined in detail the effect of temperature (7-37 degrees C) and water availability (water activity, a(w), 0.89-0.97) on fumonisin B1 (FB1) production by an isolate of Fusarium moniliforme and F. proliferatum on irradiated maize grain after incubation for 28 days. The optimum conditions for F. moniliforme and F. proliferatum were 30 degrees C at 0.97 a(w) and 15 degrees C at 0.97 a(w), respectively. The maximum concentrations were 2861 mg kg(-1) and 17,628 mg kg(-1) dry wt. maize grain, respectively. At marginal a(w)/temperature conditions for growth (e.g. 0.89-0.91 a(w)) no FB1 was detected (<0.1 mg kg(-1)). A high variability was found between replicates for F. moniliforme, but not for F. proliferatum. These data were used to construct two-dimensional diagrams of all the a(w) x temperature conditions favourable for FB1 production for the first time. The data were also subjected to a polynomical regression, which demonstrated that there was a very good fit for the 15-30 degrees C range of temperature and at 0.97 a(w). However, at marginal environmental conditions this was not possible. This suggests that it may be possible to predict within a limited environmental range the potential for significant FB1 production.     

Image modeling based on a 2-D stochastic subspace system identification algorithm

Fitting a causal dynamic model to an image is a fundamental problem in image processing, pattern recognition, and computer vision. In image restoration, for instance, the goal is to recover an estimate of the true image, preferably in the form of a parametric model, given an image that has been degraded by a combination of blur and additive white Gaussian noise. In texture analysis, on the other hand, a model of a particular texture image can serve as a tool for simulating texture patterns. Finally, in image enhancement one computes a model of the true image and the residuals between the image and the modeled image can be interpreted as the result of applying a de-noising filter. There are numerous other applications within the field of image processing that require a causal dynamic model. Such is the case in scene analysis, machined parts inspection, and biometric analysis, to name only a few. There are many types of causal dynamic models that have been proposed in the literature, among which the autoregressive moving average and state-space models (i.e., Kalman filter) are the most commonly used. In this paper we introduce a 2-D stochastic state-space system identification algorithm for fitting a quarter plane causal dynamic Roesser model to an image. The algorithm constructs a causal, recursive, and separable-in-denominator 2-D Kalman filter model. The algorithm is tested with three real images and the quality of the estimated images are assessed.