Perceptual Principles and Computer Graphics

Now that technology allows us to present photorealistic animations of scenically lit objects acting in real-time, the problem of computer graphics has changed from making displays recognisable, to ensuring that users notice what they are intended to see, without being distracted by irrelevant information. Worse than that, the use of veridical displays that are intended to be lifelike runs the risk of introducing unpredictable sources of information, that can lead users to infer all sorts of unwanted details. Traditional visual theory, based upon bottom-up models of feature extraction from the retinal image, cannot inform us about these aspects of perception. Broader based cognitive theories are required that integrate visual perception with attention, memory, emotion and inference. Theories such as Barnard's Interacting Cognitive Subsystems enable phenomena such as change blindness and the craft principles of film editing to be interpreted within a common framework, supporting extrapolation to computer graphics.     

Nonlinear state estimation with robust convergence

The problem of designing a dynamic measurement processor for the on-line estimation of the state of a multi-input multi-output nonlinear plant is addressed. The plant can be either observable or detectable, encompassing a broad range of cases in process systems engineering. On the basis of the structure of a suitable property of robust nonlinear estimability, an estimator is built and its convergence studied, yielding sufficient conditions for robust convergence, a systematic construction, and a tractable gain tuning procedure. The estimability property has a verifiable test, and the execution of the tuning procedure, as well as the interpretation of its convergence features can be achieved within a conventional control framework for linear single-input controllers or single-output filters. The estimation of a continuous polymer reactor is considered as an application example.     

Permanent elimination of the yield-point phenomenon in AISI 430 stainless steel by skin-pass rolling

The different yielding behaviour of skin-pass and skin-pass plus annealed samples of AISI 430 stainless steel and its dependence on substructure has been studied. Skin-pass specimens show no yield elongation in tensile testing and do not strain age at room temperature. According to TEM observations, this seems to be due to submicroscopic precipitation of low-carbon carbonitrides — most probably Cr₂ (C,N) — preferably on grain boundaries. The locking of interstitials (N, C) by these precipitates could explain the absence of discontinuous yielding. On the other hand, annealing at 700C of skin-pass samples dissolves the carbonitride precipitates, interstitial solutes are able to segregate on dislocations, and the pinned dislocations give rise to yield-point phenomena.     

Germany’s journey toward 14 Tesla human magnetic resonance

Multiple sites within Germany operate human MRI systems with magnetic fields either at 7 Tesla or 9.4 Tesla. In 2013, these sites formed a network to facilitate and harmonize the research being conducted at the different sites and make this technology available to a larger community of researchers and clinicians not only within Germany, but also worldwide. The German Ultrahigh Field Imaging (GUFI) network has defined a strategic goal to establish a 14 Tesla whole-body human MRI system as a national research resource in Germany as the next progression in magnetic field strength. This paper summarizes the history of this initiative, the current status, the motivation for pursuing MR imaging and spectroscopy at such a high magnetic field strength, and the technical and funding challenges involved. It focuses on the scientific and science policy process from the perspective in Germany, and is not intended to be a comprehensive systematic review of the benefits and technical challenges of higher field strengths.

     

Effect of Processing Conditions on Mechanical Properties of a Ti Interstitial Free Steel

The effect of thermal cycle, cold reduction and temper rolling on texture, microstructure and mechanical properties of a Ti‐added IF steel is presented. Sheets with different cold reductions were annealed using cycles with temperatures, heating rates and soaking times including extreme annealing conditions like continuous and batch regimes. Microstructure is characterized by equiaxed grains of about 17 to 20μm, being independent of the annealing cycle applied. As a function of the processing variables, texture depended mainly on heating rate and cold reduction degree, showing little dependence on soaking time or temperature. Despite the great differences between batch and continuous annealing cycles, yield strength, ultimate tensile strength and hardening coefficient n show little variation between these extreme regimes. This characteristic makes this steel almost insensitive to annealing conditions, strongly differing from other deep drawing materials like Al‐killed steels. The influence of texture on r‐value was studied using a Taylor‐based model which showed good agreement with experimental relationships. Finally, temper rolling of annealed materials was simulated with elongations varying from 0.5 to 7%. This resulted in an important increase of YS and a decrease of n, but had a deleterious effect on stretchability.     

Urine collected from diapers can be used for 2-D PAGE in infants and young children

Urinary proteomic profiling has potential to identify candidate biomarkers of renal injury in infants provided an adequate urine sample can be obtained. Although diapers are used to obtain urine for clinical evaluation, their use for proteomic analysis has not been investigated. We therefore performed feasibility studies on the use of diaper-extracted urine for 2-D PAGE. Pediatric waste urine (2–20 mL) was applied to gel-containing, non-gel and cotton-gauze diapers and then mechanically expressed. Urine volume and total protein were measured pre- and post-extraction. Proteins were separated via 2-D PAGE following application of urine (20–40 mL) to each matrix. 2-D PAGE was also performed on clinical specimens collected using each diaper type. Differences in the adsorption and retention of urine volume and protein were noted between matrices. Non-gel and cotton-gauze diapers provided the best protein/volume recovery and the lowest interference with the Bradford assay. 2-D PAGE was also successfully completed using urine samples from both cotton fiber matrices. Conversely, samples from low-gel diapers demonstrated poor protein separation and reproducibility. Diapers containing cotton–fiber matrices appear adequate for 2-D PAGE. Qualitative and quantitative analyses of resolved proteins using replicate, high-resolution gels will be required, however, before diaper-extracted urine can be applied in proteomic profiling.     

Impacts and Adaptation to Climate Change Using a Reservoir Management Tool to a Northern Watershed: Application to Lièvre River Watershed,Quebec, Canada

The purpose of this study is to evaluate the impact of climate change (CC) on the management of the three reservoirs in the Lièvre River watershed and to investigate adaptation strategies to CC. To accomplish this objective, a reservoir management tool was developed. The tool integrates: hydrological ensemble streamflow predictions; a stochastic optimization model; a neural network model; and a water balance model. Five climate projections from a regional climate model, under current (1961–2000) and future (2041–2070) climate scenarios, were used. Adjustments to the reservoirs operating rules were used as an adaptation strategy to limit flooding in the watershed and also in the Montreal Archipelago located downstream of the watershed. A number of constraints in the reservoirs of the Lièvre watershed are related to summer recreational activities, which would start earlier in future climate. Modifications of these constraints were simulated to take into account socio-economic impacts of climate change on reservoirs operation. Results show that greater quantities of water would have to be stored in the Lièvre River watershed in the future, to decrease the risk of flooding in the Montreal Archipelago. The reservoir located at the downstream end of the watershed would be more vulnerable and its reliability may decrease in the future. Adaptation measures reduced the inter-annual variability of the reservoir level under future climate conditions. The reservoir management tool is an example of a no-regrets strategy, as it will contribute to improve the tools currently available to manage the reservoirs of the Lièvre River watershed.     

Model-free control based on reinforcement learning for a wastewater treatment problem

This article presents a proposal, based on the model-free learning control (MFLC) approach, for the control of the advanced oxidation process in wastewater plants. This is prompted by the fact that many organic pollutants in industrial wastewaters are resistant to conventional biological treatments, and the fact that advanced oxidation processes, controlled with learning controllers measuring the oxidation–reduction potential (ORP), give a cost-effective solution. The proposed automation strategy denoted MFLC-MSA is based on the integration of reinforcement learning with multiple step actions. This enables the most adequate control strategy to be learned directly from the process response to selected control inputs. Thus, the proposed methodology is satisfactory for oxidation processes of wastewater treatment plants, where the development of an adequate model for control design is usually too costly. The algorithm proposed has been tested in a lab pilot plant, where phenolic wastewater is oxidized to carboxylic acids and carbon dioxide. The obtained experimental results show that the proposed MFLC-MSA strategy can achieve good performance to guarantee on-specification discharge at maximum degradation rate using readily available measurements such as pH and ORP, inferential measurements of oxidation kinetics and peroxide consumption, respectively.     

Exploring uncertainty and model predictive performance concepts via a modular snowmelt-runoff modeling framework

Model selection is an extremely important aspect of many hydrologic modeling studies because of the complexity, variability, and uncertainty that surrounds the current understanding of watershed-scale systems. However, development and implementation of a complete precipitation-runoff modeling framework, from model selection to calibration and uncertainty analysis, are rarely confronted. This paper introduces a modular precipitation-runoff modeling framework that has been developed and applied to a research site in Central Montana, USA. The case study focuses on an approach to hydrologic modeling that considers model development, selection, calibration, uncertainty analysis, and overall assessment. The results of this case study suggest that a modular framework is useful in identifying the interactions between and among different process representations and their resultant predictions of stream discharge. Such an approach can strengthen model building and address an oft ignored aspect of predictive uncertainty; namely, model structural uncertainty.     

Estimating farfield organic chemical exposures,intake rates and intake fractions to human age classes

This study describes the development and application of the Farfield Human Exposure (FHX) model. This screening level model brings together information on chemical partitioning, degradation, environmental fate and transport, and food web bioaccumulation for assessing human age class-specific exposures from chemicals released to the environment. The Level III model calculates steady-state concentrations in multimedia compartments such as air, water, and soil, and various food groups including fruits, vegetables, milk, dairy, fish, and meats based on a unit emission rate. Human multimedia intake and ingestion rates determine unit emission based chemical exposures, intake rates and intake fractions for various age classes representing the general population. The FHX model is generally applicable to regional areas and is designed to use readily available chemical input data for screening level and priority setting evaluations. In the present study the model is parameterized for an evaluative regional area using Health Canada exposure factors to determine multimedia intake rates for seven selected age classes. The model outputs, human chemical intake rates and human intake fractions are described for four case study chemicals. Biotransformation and biomagnification processes in food webs are highlighted as key factors influencing human exposure. Future research needs to improve the model are discussed.