Combined effect of heterogeneity, anisotropy and saturation on steady state flow and transport: Structure recognition and numerical simulation

1 Natural soil profiles may be interpreted as an arrangement of parts which are characterized by properties like hydraulic conductivity and water retention function. These parts form a complicated structure. Characterizing the soil structure is fundamental in subsurface hydrology because it has a crucial influence on flow and transport and defines the patterns of many ecological processes. We applied an image analysis method for recognition and classification of visual soil attributes in order to model flow and transport through a man-made soil profile. Modeled and measured saturation-dependent effective parameters were compared. We found that characterizing and describing conductivity patterns in soils with sharp conductivity contrasts is feasible. Differently, solving flow and transport on the basis of these conductivity maps is difficult and, in general, requires special care for representation of small-scale processes.

Do optic nerve head and visual field parameters in patients with obstructive sleep apnea syndrome differ from those in control individuals?

BACKGROUND It has been suggested that sleep apnea syndrome may play a role in normal-tension glaucoma contributing to optic nerve damage. The purpose of this study was to evaluate if optic nerve and visual field parameters in individuals with sleep apnea syndrome differ from those in controls. PATIENTS AND METHODS From the records of the sleep laboratory at the University Hospital in Bern, Switzerland, we recruited consecutive patients with severe sleep apnea syndrome proven by polysomnography, apnea-hypopnea index >20, as well as no sleep apnea controls with apnea-hypopnea index <10. Participants had to be unknown to the ophtalmology department and had to have no recent eye examination in the medical history. All participants underwent a comprehensive eye examination, scanning laser polarimetry (GDx VCC, Carl Zeiss Meditec, Dublin, California), scanning laser ophthalmoscopy (Heidelberg Retina Tomograph II, HRT II), and automated perimetry (Octopus 101 Programm G2, Haag-Streit Diagnostics, Koeniz, Switzerland). Mean values of the parameters of the two groups were compared by t-test. RESULTS The sleep apnea group consisted of 69 eyes of 35 patients; age 52.7 ± 9.7 years, apnea-hypopnea index 46.1 ± 24.8. As controls served 38 eyes of 19 patients; age 45.8 ± 11.2 years, apnea-hypopnea index 4.8 ± 1.9. A difference was found in mean intraocular pressure, although in a fully overlapping range, sleep apnea group: 15.2 ± 3.1, range 8-22 mmHg, controls: 13.6 ± 2.3, range 9-18 mmHg; p<0.01. None of the extended visual field, optic nerve head (HRT) and retinal nerve fiber layer (GDx VCC) parameters showed a significant difference between the groups. CONCLUSION Visual field, optic nerve head, and retinal nerve fiber layer parameters in patients with sleep apnea did not differ from those in the control group. Our results do not support a pathogenic relationship between sleep apnea syndrome and glaucoma.

Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel((R))

This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel((R)) spreadsheet was implemented with the use of Solver((R)) and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

Learning with noise and regularizers in multilayer neural networks

We study the effect of two types of noise, data noise and model noise, in an on-line gradient-descent learning scenario for general two-layer student network with an arbitrary number of hidden units. Training examples are randomly drawn input vectors labeled by a two-layer teacher network with an arbitrary number of hidden units. Data is then corrupted by Gaussian noise affecting either the output or the model itself. We examine the effect of both types of noise on the evolution of order parameters and the generalization error in various phases of the learning process.

Learning with regularizers in multilayer neural networks

We study the effect of regularization in an on-line gradient-descent learning scenario for a general two-layer student network with an arbitrary number of hidden units. Training examples are randomly drawn input vectors labelled by a two-layer teacher network with an arbitrary number of hidden units which may be corrupted by Gaussian output noise. We examine the effect of weight decay regularization on the dynamical evolution of the order parameters and generalization error in various phases of the learning process, in both noiseless and noisy scenarios.

Experimental investigation into amplitude-dependent modal properties of an eleven-span motorway bridge

The authors would like to thank their supporters. New Zealand Earthquake Commission (EQC) Research Foundation provided financial support for experimental work (Grant No. UNI/578). New Zealand Transport Agency (NZTA) provided access to the bridge. Piotr Omenzetter’s work within the LRF Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research. Ge-Wei Chen’s doctoral study is supported by China Scholarship Council (CSC) (Grant No. 2011637065).

Quantum Otto heat engine based on a multiferroic chain working substance

We study a quantum Otto engine operating on the basis of a helical spin-1/2 multiferroic chain with strongly coupled magnetic and ferroelectric order parameters. The presence of a finite spin chirality in the working substance enables steering of the cycle by an external electric field that couples to the electric polarization. We observe a direct connection between the chirality, the entanglement and the efficiency of the engine. An electric-field dependent threshold temperature is identified, above which the pair correlations in the system, as quantified by the thermal entanglement, diminish. In contrast to the pair correlations, the collective many-body thermal entanglement is less sensitive to the electric field, and in the high temperature limit converges to a constant value. We also discuss the correlations between the threshold temperature of the pair entanglement, the spin chirality and the minimum of the fidelities in relation to the electric and magnetic fields. The efficiency of the quantum Otto cycle shows a saturation plateau with increasing electric field amplitude.

Preenchimento de cavidades provenientes de remoção de trinca em turbinas hidráulicas por meio do processo GMAW-P

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2016.

Orbital multicriticality in spin-gapped quasi-one-dimensional antiferromagnets

Motivated by the quasi-one-dimensional antiferromagnet CaV(2)O(4), we explore spin-orbital systems in which the spin modes are gapped but orbitals are near a macroscopically degenerate classical transition. Within a simplified model we show that gapless orbital liquid phases possessing power-law correlations may occur without the strict condition of a continuous orbital symmetry. For the model proposed for CaV(2)O(4), we find that an orbital phase with coexisting order parameters emerges from a multicritical point. The effective orbital model consists of zigzag-coupled transverse field Ising chains. The corresponding global phase diagram is constructed using field theory methods and analyzed near the multicritical point with the aid of an exact solution of a zigzag XXZ model.

NMR studies of the low-density lipoprotein receptor-binding peptide of apolipoprotein E bound to dodecylphosphocholine micelles

Circular dichroism and NMR spectroscopy have been used to determine the structure of the low-density lipoprotein (LDL) receptor-binding peptide, comprising residues 130-152, of the human apolipoprotein E. This peptide has little persistent three-dimensional structure in solution, but when bound to micelles of dodecylphosphocholine (DPC) it adopts a predominantly alpha-helical structure. The three-dimensional structure of the DPC-bound peptide has been determined by using H-1-NMR spectroscopy: the structure derived from NOE-based distance constraints and restrained molecular dynamics is largely helical. The derived phi and psi angle order parameters show that the helical structure is well defined but with some flexibility that causes the structures not to be superimposable over the full peptide length. Deuterium exchange experiments suggest that many peptide amide groups are readily accessible to the solvent, but those associated with hydrophobic residues exchange more slowly, and this helix is thus likely to be positioned on the surface of the DPC micelles. In this conformation the peptide has one hydrophobic face and two that are rich in basic amino acid side chains. The solvent-exposed face of the peptide contains residues previously shown to be involved in binding to the LDL receptor.

An uncertainty and sensitivity analysis applied to the prioritisation of pharmaceuticals as surface water contaminants from wastewater treatment plant direct emissions

In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results.

Performance evaluation of a cooperative reputation system for vehicular delay-tolerant networks

In the last decade, both scientific community and automotive industry enabled communications among vehicles in different kinds of scenarios proposing different vehicular architectures. Vehicular delay-tolerant networks (VDTNs) were proposed as a solution to overcome some of the issues found in other vehicular architectures, namely, in dispersed regions and emergency scenarios. Most of these issues arise from the unique characteristics of vehicular networks. Contrary to delay-tolerant networks (DTNs), VDTNs place the bundle layer under the network layer in order to simplify the layered architecture and enable communications in sparse regions characterized by long propagation delays, high error rates, and short contact durations. However, such characteristics turn contacts very important in order to exchange as much information as possible between nodes at every contact opportunity. One way to accomplish this goal is to enforce cooperation between network nodes. To promote cooperation among nodes, it is important that nodes share their own resources to deliver messages from others. This can be a very difficult task, if selfish nodes affect the performance of cooperative nodes. This paper studies the performance of a cooperative reputation system that detects, identify, and avoid communications with selfish nodes. Two scenarios were considered across all the experiments enforcing three different routing protocols (First Contact, Spray and Wait, and GeoSpray). For both scenarios, it was shown that reputation mechanisms that punish aggressively selfish nodes contribute to increase the overall network performance.

A molecularly imprinted sensor for sensitive detection of 8-hydroxy-2'-deoxyguanosine (8-OHdG) oxidative stress biomarker

6th Graduate Student Symposium on Molecular Imprinting

Characterization of sol-gel matrices with entrapped cutinase

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica

Smart windows with permanent memory effect

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica