Analysis of Degradation Data of Poly(L-lactide-co-L,D-lactic actide) and Poly(L-lactide) Obtained at Elevated and Physiological Temperatures Using Mathematical Models

The degradation of resorbable polymeric devices often takes months to years. Accelerated testing at elevated temperatures is an attractive but controversial technique. The purposes of this paper include: (a) to provide a summary of the mathematical models required to analyse accelerated degradation data and to indicate the pitfalls of using these models; (b) to improve the model previously developed by Han and Pan; (c) to provide a simple version of the model of Han and Pan with an analytical solution that is convenient to use; (d) to demonstrate the application of the improved model in two different poly(lactic acid) systems. It is shown that the simple analytical relations between molecular weight and degradation time widely used in the literature can lead to inadequate conclusions. In more general situations the rate equations are only part of a complete degradation model. Together with previous works in the literature, our study calls for care in using the accelerated testing technique.

Applications of statistical models in proportioning medium strength self-compacting concrete

Self-compacting concrete (SCC) is generally designed with a relatively higher content of finer, which includes cement, and dosage of superplasticizer than the conventional concrete. The design of the current SCC leads to high compressive strength, which is already used in special applications, where the high cost of materials can be tolerated. Using SCC, which eliminates the need for vibration, leads to increased speed of casting and thus reduces labour requirement, energy consumption, construction time, and cost of equipment. In order to obtain and gain maximum benefit from SCC it has to be used for wider applications. The cost of materials will be decreased by reducing the cement content and using a minimum amount of admixtures. This paper reviews statistical models obtained from a factorial design which was carried out to determine the influence of four key parameters on filling ability, passing ability, segregation and compressive strength. These parameters are important for the successful development of medium strength self-compacting concrete (MS-SCC). The parameters considered in the study were the contents of cement and pulverised fuel ash (PFA), water-to-powder ratio (W/P), and dosage of superplasticizer (SP). The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined to Orimet, JRing combined to cone, fresh segregation, and compressive strength at 7, 28 and 90 days. The models are valid for mixes made with 0.38 to 0.72 W/P ratio, 60 to 216 kg/m3 of cement content, 183 to 317 kg/m3 of PFA and 0 to 1% of SP, by mass of powder. The utility of such models to optimize concrete mixes to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mix parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined to Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show trade-offs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixes. The paper establishes the usefulness of the mathematical models as a tool to facilitate the test protocol required to optimise medium strength SCC.

Multivariate Statistical Analysis Applied to an IL6 Signal Transduction Model in Hepatocytes

This paper introduces the application of linear multivariate statistical techniques, including partial least squares (PLS), canonical correlation analysis (CCA) and reduced rank regression (RRR), into the area of Systems Biology. This new approach aims to extract the important proteins embedded in complex signal transduction pathway models.The analysis is performed on a model of intracellular signalling along the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in interleukin-6 (IL6) stimulated hepatocytes, which produce signal transducer and activator of transcription factor 3 (STAT3).A region of redundancy within the MAPK pathway that does not affect the STAT3 transcription was identified using CCA. This is the core finding of this analysis and cannot be obtained by inspecting the model by eye. In addition, RRR was found to isolate terms that do not significantly contribute to changes in protein concentrations, while the application of PLS does not provide such a detailed picture by virtue of its construction.This analysis has a similar objective to conventional model reduction techniques with the advantage of maintaining the meaning of the states prior to and after the reduction process. A significant model reduction is performed, with a marginal loss in accuracy, offering a more concise model while maintaining the main influencing factors on the STAT3 transcription.The findings offer a deeper understanding of the reaction terms involved, confirm the relevance of several proteins to the production of Acute Phase Proteins and complement existing findings regarding cross-talk between the two signalling pathways.

Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

Development of a rapid low cost fluorescent biosensor for the detection of food contaminants

A prototype fluorescent based biosensor has been developed for the antibody based detection of food related contaminants. Its performance was characterised and showed a typical antibody binding signal of 200-2000 mV, a short term noise of 9.1 mV, and baseline slope of -0.016 mV/s over 4 h. Bulk signal detection repeatability (n=23) and reproducibility (n=3) were less than 2.4%CV. The biosensor detection unit was evaluated using two food related model systems proving its ability to monitor both binding using commercial products and inhibition through the development of an assay. This assay development potential was evaluated by observing the biosensor's performance whilst appraising several labelled antibody and glass slide configurations. The molecular interaction between biotin and an anti-biotin antibody was shown to be inhibited by 41% due to the presence of biotin in a sample. A food toxin (domoic acid) calibration curve was produced, with %CVs ranging from 2.7 to 7.8%, and a midpoint of approximately 17 ng/ml with further optimisation possible. The ultimate aim of this study was to demonstrate the working principles of this innovative biosensor as a potential portable tool with the opportunity of interchangeable assays. The biosensor design is applicable for the requirements of routine food contaminant analysis, with respect to performance, functionality and cost. (C) 2012 Elsevier B.V. All rights reserved.

Immunohistochemical study of pig retinal development

PURPOSE: The pig eye is similar to the human eye in terms of anatomy, vasculature, and photoreceptor distribution, and therefore provides an attractive animal model for research into retinal disease. The purpose of this study was to characterize retinal histology in the developing and mature pig retina using antibodies to well established retinal cell markers commonly used in rodents.

METHODS: Eyes were enucleated from fetuses in the 9th week of gestation, 1 week old piglets and 6 months old adult animals. Eyeglobes were fixed and cryosectioned. A panel of antibodies to well established retinal markers was employed for immunohistochemistry. Fluorescently labeled secondary antibodies were used for signal detection, and images were acquired by confocal microscopy. Mouse retina at postnatal day (P) 5 was used as a reference for this study to compare progression of histogenesis. Most of the primary antibodies have previously been used on mouse tissue.

RESULTS: Most of the studied markers were detected in midgestation pig retina, and the majority had a similar distribution in pig as in P5 mouse retina. However, rhodopsin immunolabeling was detected in pig retina at midgestation but not in P5 mouse retina. Contrary to findings in all rodents, horizontal cells were Islet1-positive and cones were calbindin-immunoreactive in pig retina, as has also been shown for the primate retina. Recoverin and rhodopsin immunolabeling revealed an increase in the length of photoreceptor segments in 6 months, compared to 1 week old animals.

CONCLUSIONS: Comparison with the published data on human retina revealed similar marker distribution and histogenesis progression in the pig and human retina, supporting the pig as a valuable animal model for studies on retinal disease and repair. Furthermore, this study provides information about the dynamics of retinal histogenesis in the pig and validates a panel of antibodies that reliably detects developing and mature retinal cell phenotypes in the pig retina.

Compressive Sensing based Detector for Sparse Signal Modulation in Precoded OFDM

In this paper, we propose a sparse signal modulation (SSM) method for precoded orthogonal frequency division multiplexing (OFDM) systems and study the signal detection. Although a receiver is able to exploit a path diversity gain with random precoding in OFDM, the complexity of the receiver is usually high as the orthogonality is not retained due to precoding. However, with SSM, we can derive a low-complexity detector that can provide reasonably good performances with a low sparsity ratio based on the notion of compressive sensing (CS). An important feature of a CS detector is that it can estimate SSM signals with a small fraction of the received signals over sub-carriers. This feature can allow us to build a low cost receiver with a small number of demodulators.

The police officer's terrorist dilemma: Trust resilience following fatal errors

Suicide attacks have raised the stakes for officers deciding whether or not to shoot a suspect ('Police Officer's Terrorist Dilemma'). Despite high-profile errors we know little about how trust in the police is affected by their response to the terrorist threat. Building on a conceptualisation of lay observers as intuitive signal detection theorists, a general population sample (N= 1153) were presented with scenarios manipulated in terms of suspect status (Armed/Unarmed), officer decision (Shoot/Not Shoot) and outcome severity (e.g. suspect armed with Bomb/Knife; police shoot suspect/ suspect plus child bystander). Supporting predictions, people showed higher trust in officers who made correct decisions. reflecting good discrimination ability and who decided to shoot, reflecting an 'appropriate' response bias given the relative costs and benefits. This latter effect was moderated by (a) outcome severity, suggesting it did not simply reflect a preference for a particular type of action, and (b) preferences for a tough stance towards terrorism indexed by Right-Wing Authoritarianism (RWA). Despite loss of civilian life, failure to prevent minor terror attacks resulted in no loss of trust amongst people low in RWA. whereas among people high in RWA trust was positive when police erroneously shot all unarmed suspect. Relations to alternative definitions of trust and procedural justice research are discussed. Copyright (C),. 2007 John Wiley & Sons, Ltd.

Correlation Rotation Linear Precoding for MIMO Broadcast Communications

A simple linear precoding technique is proposed for multiple input multiple output (MIMO) broadcast systems using phase shift keying (PSK) modulation. The proposed technique is based on the fact that, on an instantaneous basis, the interference between spatial links in a MIMO system can be constructive and can contribute to the power of the useful signal to improve the performance of signal detection. In MIMO downlinks this co-channel interference (CCI) can be predicted and characterised prior to transmission. Contrary to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to influence the interference and benefit from it, thus gaining advantage from energy already existing in the communication system that is left unexploited otherwise. The proposed precoding aims at adaptively rotating, rather than zeroing, the correlation between the MIMO substreams depending on the transmitted data, so that the signal of interfering transmissions is aligned to the signal of interest at each receive antenna. By doing so, the CCI is always kept constructive and the received signal to interference-plus-noise ratio (SINR) delivered to the mobile units (MUs) is enhanced without the need to invest additional signal power per transmitted symbol at the MIMO base station (BS). It is shown by means of theoretical analysis and simulations that the proposed MIMO precoding technique offers significant performance and throughput gains compared to its conventional counterparts.

Unsteady Gas Dynamic Engine Simulation

This paper provides an overview of the basic theory underlying 1D unsteady gas dynamics, the computational method developed at Queen’s University Belfast (QUB), the use of CFD as an alternative and some experimental results that demonstrate the techniques used to develop the mathematical models.

Auditory false perceptions are mediated by psychosis risk factors

Introduction. Auditory hallucinations exist in psychotic disorders as well as the general population. Proneness to hallucinations, as measured by positive schizotypy, predicts false perceptions during an auditory signal detection task (Barkus, Stirling, Hopkins, McKie, & Lewis, 2007). Our aim was to replicate this result and extend it by examining effects of age and sex, both important demographic predictors of psychosis.

Method. A sample of 76 healthy volunteers split into 15-17 years (n = 46) and 19 years plus (n = 30) underwent a signal detection task designed to detect propensity towards false perceptions under ambiguous auditory conditions. Scores on the Unusual Experiences subscale (UE) of the O-LIFE schizotypy scale, IQ, and a measure of working memory were also assessed.

Results. We replicated our initial finding (Barkus et al., 2007): High scores on positive schizotypy were associated with false perceptions. Younger participants who scored highly on positive schizotypy reported significantly more false perceptions compared to other groups (p = .04). Older participants who had had an imaginary friend reported more false perceptions during the signal detection task (p <. 01).

Conclusions. Younger participants seem most vulnerable to the effects of positive schizotypal traits in terms of a signal detection deficit that underlies auditory hallucinations. Schizotypy may have greatest impact closer to the risk period for development of psychotic disorders.

Implications of Intercellular Signaling for Radiation Therapy: A Theoretical Dose-Planning Study

Purpose
Recent in vitro results have shown significant contributions to cell killing from signaling effects at doses that are typically used in radiation therapy. This study investigates whether these in vitro observations can be reconciled with in vivo knowledge and how signaling may have an impact on future developments in radiation therapy.
Methods and Materials
Prostate cancer treatment plans were generated for a series of 10 patients using 3-dimensional conformal therapy, intensity modulated radiation therapy (IMRT), and volumetric modulated arc therapy techniques. These plans were evaluated using mathematical models of survival following modulated radiation exposures that were developed from in vitro observations and incorporate the effects of intercellular signaling. The impact on dose-volume histograms and mean doses were evaluated by converting these survival levels into "signaling-adjusted doses" for comparison.
Results
Inclusion of intercellular communication leads to significant differences between the signalling-adjusted and physical doses across a large volume. Organs in low-dose regions near target volumes see the largest increases, with mean signaling-adjusted bladder doses increasing from 23 to 33 Gy in IMRT plans. By contrast, in high-dose regions, there is a small decrease in signaling-adjusted dose due to reduced contributions from neighboring cells, with planning target volume mean doses falling from 74 to 71 Gy in IMRT. Overall, however, the dose distributions remain broadly similar, and comparisons between the treatment modalities are largely unchanged whether physical or signaling-adjusted dose is compared. Conclusions Although incorporating cellular signaling significantly affects cell killing in low-dose regions and suggests a different interpretation for many phenomena, their effect in high-dose regions for typical planning techniques is comparatively small. This indicates that the significant signaling effects observed in vitro are not contradicted by comparison with clinical observations. Future investigations are needed to validate these effects in vivo and to quantify their ranges and potential impact on more advanced radiation therapy techniques.

Parasites that change predator or prey behaviour can have keystone effects on community composition

Parasites play pivotal roles in structuring communities, often via indirect interactions with non-host species. These effects can be density-mediated (through mortality) or trait-mediated (behavioural, physiological and developmental), and may be crucial to population interactions, including biological invasions. For instance, parasitism can alter intraguild predation (IGP) between native and invasive crustaceans, reversing invasion outcomes. Here, we use mathematical models to examine how parasite-induced trait changes influence the population dynamics of hosts that interact via IGP. We show that trait-mediated indirect interactions impart keystone effects, promoting or inhibiting host coexistence. Parasites can thus have strong ecological impacts, even if they have negligible virulence, underscoring the need to consider trait-mediated effects when predicting effects of parasites on community structure in general and biological invasions in particular.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.