Neutralization and homophony avoidance in phonological learning

Previous research has suggested that homophony avoidance plays a role in constraining language change; in particular, phonological contrasts are less likely to be neutralized if doing so would greatly increase the amount of homophony in the language. Most of the research on homophony avoidance has focused on the history of real languages, comparing attested and unattested (hypothetical) phonological changes. In this study, we take a novel approach by focusing on the language learner. Using an artificial language learning paradigm, we show that learners are less likely to acquire neutralizing phonological rules compared to non-neutralizing rules, but only if the neutralizing rules create homophony between lexical items encountered during learning. The results indicate that learners are biased against phonological patterns that create homophony, which could have an influence on language change. The results also suggest that lexical learning and phonological learning are highly integrated

Flight simulation testing of a turbulence model based on a Synthetic Eddy Method

This paper presents initial analysis of an ongoing series of flight simulation trials of a new turbulence model based on a synthetic eddy method (SEM). The model is based on the generation of a random distribution of turbulence generating Eddies within a control model surrounding the aircraft. Eddies are displaced by the flow and regenerated at the inflow as they leave the simulation domain. The model allows adjustment of turbulence intensity by adjusting the value of Reynolds stress tensor and of frequency spectra through adjustment of eddy sizes, allowing for a more realistic representation of broadband turbulence. Compared to other random turbulence models, preserving the location of the Eddies in the control volume ensures automatically that turbulence across different aircraft locations is automatically correlated. Piloted flight simulation tests show that both, levels of turbulence intensity and frequency of the induced turbulence have a strong effect on workload and task performance. Increases in turbulence intensity result in a direct increase in pilot workload and reduced task performance. However changes in frequency of turbulence present a more complex picture dependent on flight condition and aircraft response

Smart Grid, Smart City, Customer Research Report

Prepared by the UTS: Institute for Sustainable Futures as part of the AEFI consortium for Ausgrid and EnergyAustrali

Mathematical and computational models for bone tissue engineering in bioreactor systems

Research into cellular engineered bone grafts offers a promising solution to problems associated with the currently used auto- and allografts. Bioreactor systems can facilitate the development of functional cellular bone grafts by augmenting mass transport through media convection and shear flow-induced mechanical stimulation. Developing successful and reproducible protocols for growing bone tissue in vitro is dependent on tuning the bioreactor operating conditions to the specific cell type and graft design. This process, largely reliant on a trial-and-error approach, is challenging, time-consuming and expensive. Modelling can streamline the process by providing further insight into the effect of the bioreactor environment on the cell culture, and by identifying a beneficial range of operational settings to stimulate tissue production. Models can explore the impact of changing flow speeds, scaffold properties, and nutrient and growth factor concentrations. Aiming to act as an introductory reference for bone tissue engineers looking to direct their experimental work, this article presents a comprehensive framework of mathematical models on various aspects of bioreactor bone cultures and overviews modelling case studies from literature

Using zeta-potential measurements to quantify peptide partition to lipid membranes

© The Author(s) 2011. This article is published with open access at Springerlink.com.Open Access: This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.Many cellular phenomena occur on the biomembranes. There are plenty of molecules (natural or xenobiotics) that interact directly or partially with the cell membrane. Biomolecules, such as several peptides (e.g., antimicrobial peptides) and proteins, exert their effects at the cell membrane level. This feature makes necessary investigating their interactions with lipids to clarify their mechanisms of action and side effects necessary. The determination of molecular lipid/water partition constants (Kp) is frequently used to quantify the extension of the interaction. The determination of this parameter has been achieved by using different methodologies, such as UV-Vis absorption spectrophotometry, fluorescence spectroscopy and ζ-potential measurements. In this work, we derived and tested a mathematical model to determine the Kp from ζ-potential data. The values obtained with this method were compared with those obtained by fluorescence spectroscopy, which is a regular technique used to quantify the interaction of intrinsically fluorescent peptides with selected biomembrane model systems. Two antimicrobial peptides (BP100 and pepR) were evaluated by this new method. The results obtained by this new methodology show that ζ-potential is a powerful technique to quantify peptide/lipid interactions of a wide variety of charged molecules, overcoming some of the limitations inherent to other techniques, such as the need for fluorescent labeling.This work was partially supported by project PTDC/QUI/ 69937/2006 from Fundação para a Ciência e Tecnologia-Ministério da Ciência, Tecnologia e Ensino Superior (FCT-MCTES, Portugal), and by Fundação Calouste Gulbenkian (Portugal). JMF and MMD also thank FCT-MCTES for grants IMM/BT/37-2010 and SFRH/BD/41750/2007, respectively

Study protocol: evaluation of a parenting and stress management programme: a randomised controlled trial of Triple P discussion groups and stress control

<br>Background: Children displaying psychosocial problems are at an increased risk of negative developmental outcomes. Parenting practices are closely linked with child development and behaviour, and parenting programmes have been recommended in the treatment of child psychosocial problems. However, parental mental health also needs to be addressed when delivering parenting programmes as it is linked with parenting practices, child outcomes, and treatment outcomes of parenting programmes. This paper describes the protocol of a study examining the effects of a combined intervention of a parenting programme and a cognitive behavioural intervention for mental health problems.</br> <br>Methods: The effects of a combined intervention of Triple P Discussion Groups and Stress Control will be examined using a randomised controlled trial design. Parents with a child aged 3?8?years will be recruited to take part in the study. After obtaining informed consent and pre-intervention measures, participants will be randomly assigned to either an intervention or a waitlist condition. The two primary outcomes for this study are change in dysfunctional/ineffective parenting practices and change in symptoms of depression, anxiety, and stress. Secondary outcomes are child behaviour problems, parenting experiences, parental self-efficacy, family relationships, and positive parental mental health. Demographic information, participant satisfaction with the intervention, and treatment fidelity data will also be collected. Data will be collected at pre-intervention, mid-intervention, post-intervention, and 3-month follow-up.</br> <br>Discussion: The aim of this paper is to describe the study protocol of a randomised controlled trial evaluating the effects of a combined intervention of Triple P Discussion Groups and Stress Control in comparison to a waitlist condition. This study is important because it will provide evidence about the effects of this combined intervention for parents with 3?8?year old children. The results of the study could be used to inform policy about parenting support and support for parents with mental health problems. Trial registration ClinicalTrial.gov: NCT01777724, UTN: U1111-1137-1053.</br&gt

Athermal colorless C-band optical transmitter system for passive optical networks

This paper reports an uncooled transmitter system using a digital super-mode (DS) distributed Bragg reflector (DBR) tunable laser, which is able to act as an athermal, wavelength agnostic transmitter suitable for wavelength division multiplexed (WDM) passive optical network (PON) applications. An open-loop laser current control algorithm is designed to compensate autonomously for wavelength drift, thus allowing constant operating wavelength to be achieved regardless of ambient temperature. An improved wavelength accuracy of ±3 GHz is achieved when using low bandwidth feedback from the central office using information from a centralized shared wavelength locker. The entire laser start-up, channel selection and subsequent wavelength control is autonomous and has been implemented on micro-controllers and field programmable gate arrays. We demonstrate a three channel WDM-PON system comprising an uncooled packaged DS-DBR laser in the presence of two neighboring interfering channels. Error free transmission over 40 km single mode fiber of 10 Gb/s externally modulated NRZ data, is achieved for each of 48 C-band channels on the 100 GHz ITU grid. Successful athermal operation is demonstrated by sweeping the ambient temperature of the laser from 15 to 70 °C with a maximum wavelength deviation for any channel of no more than 0.1 nm.This work has been supported by the Technology Strategy Board, UK and by the German ministry for education and research, through the EU ERA-NET+ projects PIANO+ IMPACT (BMBF grant: 13N11434) and TUCAN (BMBF grant: 13N11573). We also acknowledge the support of the UK Engineering and Physical Sciences Research Council via the INTERNET project.This is the final version of the article. It first appeared from IEEE via http://dx.doi.org/10.1109/JLT.2014.235405

Structure-based statistical analysis of transmembrane helices

Recent advances in determination of the high-resolution structure of membrane proteins now enable analysis of the main features of amino acids in transmembrane (TM) segments in comparison with amino acids in water-soluble helices. In this work, we conducted a large-scale analysis of the prevalent locations of amino acids by using a data set of 170 structures of integral membrane proteins obtained from the MPtopo database and 930 structures of water-soluble helical proteins obtained from the protein data bank. Large hydrophobic amino acids (Leu, Val, Ile, and Phe) plus Gly were clearly prevalent in TM helices whereas polar amino acids (Glu, Lys, Asp, Arg, and Gln) were less frequent in this type of helix. The distribution of amino acids along TM helices was also examined. As expected, hydrophobic and slightly polar amino acids are commonly found in the hydrophobic core of the membrane whereas aromatic (Trp and Tyr), Pro, and the hydrophilic amino acids (Asn, His, and Gln) occur more frequently in the interface regions. Charged amino acids are also statistically prevalent outside the hydrophobic core of the membrane, and whereas acidic amino acids are frequently found at both cytoplasmic and extra-cytoplasmic interfaces, basic amino acids cluster at the cytoplasmic interface. These results strongly support the experimentally demonstrated biased distribution of positively charged amino acids (that is, the so-called the positive-inside rule) with structural data

Mathematical modeling and comparison of protein size distribution in different plant, animal, fungal and microbial species reveals a negative correlation between protein size and protein number, thus providing insight into the evolution of proteomes

<p>Abstract</p> <p>Background</p> <p>The sizes of proteins are relevant to their biochemical structure and for their biological function. The statistical distribution of protein lengths across a diverse set of taxa can provide hints about the evolution of proteomes.</p> <p>Results</p> <p>Using the full genomic sequences of over 1,302 prokaryotic and 140 eukaryotic species two datasets containing 1.2 and 6.1 million proteins were generated and analyzed statistically. The lengthwise distribution of proteins can be roughly described with a gamma type or log-normal model, depending on the species. However the shape parameter of the gamma model has not a fixed value of 2, as previously suggested, but varies between 1.5 and 3 in different species. A gamma model with unrestricted shape parameter described best the distributions in ~48% of the species, whereas the log-normal distribution described better the observed protein sizes in 42% of the species. The gamma restricted function and the sum of exponentials distribution had a better fitting in only ~5% of the species. Eukaryotic proteins have an average size of 472 aa, whereas bacterial (320 aa) and archaeal (283 aa) proteins are significantly smaller (33-40% on average). Average protein sizes in different phylogenetic groups were: Alveolata (628 aa), Amoebozoa (533 aa), Fornicata (543 aa), Placozoa (453 aa), Eumetazoa (486 aa), Fungi (487 aa), Stramenopila (486 aa), Viridiplantae (392 aa). Amino acid composition is biased according to protein size. Protein length correlated negatively with %C, %M, %K, %F, %R, %W, %Y and positively with %D, %E, %Q, %S and %T. Prokaryotic proteins had a different protein size bias for %E, %G, %K and %M as compared to eukaryotes.</p> <p>Conclusions</p> <p>Mathematical modeling of protein length empirical distributions can be used to asses the quality of small ORFs annotation in genomic releases (detection of too many false positive small ORFs). There is a negative correlation between average protein size and total number of proteins among eukaryotes but not in prokaryotes. The %GC content is positively correlated to total protein number and protein size in prokaryotes but not in eukaryotes. Small proteins have a different amino acid bias than larger proteins. Compared to prokaryotic species, the evolution of eukaryotic proteomes was characterized by increased protein number (massive gene duplication) and substantial changes of protein size (domain addition/subtraction).</p