Determination of heat transfer coefficient for hot stamping process

© 2015 The Authors.The selection of the heat transfer coefficient is one of the most important factors that determine the reliability of FE simulation results of a hot stamping process, in which the formed component is held within cold dies until fully quenched. The quenching process could take up to 10. seconds. In order to maximise the production rate, the optimised quenching parameters should be identified to achieve the highest possible quenching rate and to reduce the quenching time. For this purpose, a novel-testing rig for the Gleeble 3800 thermo- mechanical simulator was designed and manufactured, with an advanced control system for temperature and contact pressure. The effect of contact pressure on the heat transfer coefficient was studied. The findings of this research will provide useful guidelines for the selection of the heat transfer coefficient in simulations of hot stamping processes and useful information for the design of hot stamping processes

Likelihood inference for exponential-trawl processes

Integer-valued trawl processes are a class of serially correlated, stationary and infinitely divisible processes that Ole E. Barndorff-Nielsen has been working on in recent years. In this Chapter, we provide the first analysis of likelihood inference for trawl processes by focusing on the so-called exponential-trawl process, which is also a continuous time hidden Markov process with countable state space. The core ideas include prediction decomposition, filtering and smoothing, complete-data analysis and EM algorithm. These can be easily scaled up to adapt to more general trawl processes but with increasing computation efforts.Comment: 29 pages, 6 figures, forthcoming in: "A Fascinating Journey through Probability, Statistics and Applications: In Honour of Ole E. Barndorff-Nielsen's 80th Birthday", Springer, New Yor

On the Exploitation of Search History and Accumulative Sampling in Robust Optimisation

This is the author accepted manuscript. The final version is available from ACM via the DOI in this record.Efficient robust optimisation methods exploit the search history when evaluating a new solution by using information from previously visited solutions that fall in the new solution’s uncertainty neighbourhood. We propose a full exploitation of the search history by updating the robust fitness approximations across the entire search history rather than a fixed population. Our proposed method shows promising results on a range of test problems compared with other approaches from the literature.This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/N017846/1]

Optimisation and Landscape Analysis of Computational Biology Models: A Case Study

This is the author accepted manuscript. The final version is available from ACM via the DOI in this record.The parameter explosion problem is a crucial bottleneck in modelling gene regulatory networks (GRNs), limiting the size of models that can be optimised to experimental data. By discretising state, but not time, Boolean delay equations (BDEs) provide a signi ficant reduction in parameter numbers, whilst still providing dynamical complexity comparable to more biochemically detailed models, such as those based on differential equations. Here, we explore several approaches to optimising BDEs to timeseries data, using a simple circadian clock model as a case study. We compare the ffectiveness of two optimisers on our problem: a genetic algorithmf(GA) and an elite accumulative sampling (EAS) algorithm that provides robustness to data discretisation. Our results show that both methods are able to distinguish effectively between alternative architectures, yielding excellent ts to data. We also perform a landscape analysis, providing insights into the properties that determine optimiser performance (e.g. number of local optima and basin sizes). Our results provide a promising platform for the analysis of more complex GRNs, and suggest the possibility of leveraging cost landscapes to devise more effi cient optimisation schemes.This work was financially supported by the Engineering and Physical Sciences Research Council [grant numbers EP/N017846/1, EP/N014391/1], and made use of the Zeus and Isca supercomputing facilities provided by the University of Exeter HPC Strategy

The Input Signal Step Function (ISSF), a Standard Method to Encode Input Signals in SBML Models with Software Support, Applied to Circadian Clock Models

LetterThis is the final version of the article. Available from SAGE Publications via the DOI in this record.Time-dependent light input is an important feature of computational models of the circadian clock. However, publicly available models encoded in standard representations such as the Systems Biology Markup Language (SBML) either do not encode this input or use different mechanisms to do so, which hinders reproducibility of published results as well as model reuse. The authors describe here a numerically continuous function suitable for use in SBML for models of circadian rhythms forced by periodic light-dark cycles. The Input Signal Step Function (ISSF) is broadly applicable to encoding experimental manipulations, such as drug treatments, temperature changes, or inducible transgene expression, which may be transient, periodic, or mixed. It is highly configurable and is able to reproduce a wide range of waveforms. The authors have implemented this function in SBML and demonstrated its ability to modify the behavior of publicly available models to accurately reproduce published results. The implementation of ISSF allows standard simulation software to reproduce specialized circadian protocols, such as the phase-response curve. To facilitate the reuse of this function in public models, the authors have developed software to configure its behavior without any specialist knowledge of SBML. A community-standard approach to represent the inputs that entrain circadian clock models could particularly facilitate research in chronobiology.K.S. was supported by the UK BBSRC grant BB/E015263/1. SynthSys Edinburgh is a Centre for Integrative Systems Biology (CISB) funded by BBSRC and EPSRC, reference BB/D019621/1

Classroom Climate and Students’ Academic Achievement in Social Studies in Cross River, Nigeria

This research project examined “Classroom climate and its relationship with students’ academic achievement in Social Studies”. Ex post facto design was adopted. The population of the study comprised 14,297 JSS III students and the sample was 1,200 JSS III students selected through stratified random technique from the three Educational Zones in State Secondary Education Board, Cross River State. The instrument used was a structured six-point Likert scale questionnaire, the reliability estimate of which ranged from 0.7 to 0.8 and achievement test adapted from Junior Secondary School Certificate Examination, Ministry of Education, Cross River State (2004) were used to collect information used in the study. The data collected were analysed using Pearson Product Moment Correlation and Multiple Regression. The hypothesis was tested at .05 level of significance and 1198 and F (9,1190) degree of freedom. Based on the findings, it was concludedthat all the independent variables mentioned in this study jointly contribute to the variance in students’ academic achievement in Social Studies. It was recommended that Social Studies teachers should be trained to improve their skills on an encouraging classroom climate for students’ confidence and initiative through seminars, conferences and in-service programmes

Comparative antioxidant and hypoglycaemic effects of aqueous, ethanol and n-hexane extracts of leaf of Vitex doniana on streptozotocin-induced diabetes in albino rats

Several herbal preparations are used to treat diabetes, but their reported hypoglycemic effects are complex. This study therefore was designed to evaluate the effect of aqueous extract of Vitex doniana leaves on oxidative stress and lipid peroxidation in streptozotocin-induced diabetic and non-diabetic rats. Diabetes was induced intraperitoneally using 50 mg/kg streptozotocin, while diabetic rats were treated in 12 h cycles for four weeks with 100 mg/kg of the extract and glibenclamide (2.5 mg/kg). Nondiabetic control rats received distilled water. The levels of fasting blood sugar (FBS), thiobarbituric acid reactive substance (TBARS), aspartatate aminotransfrease (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), catalase (CAT) and superoxide dismutase (SOD) activities total, conjugated and unconjugated bilirubin concentration were assayed. The results indicate that the concentrations of TBARS, ALT, AST, ALP and bilirubin were significantly increased while the activities of SOD and CAT were reduced in the diabetic animals (p<0.05). The extract significantly increased CAT and SOD activity and reduced FBS, TBARS, ALT, AST, ALP and bilirubin concentrations significantly (p<0.05) compared to normal. However, glibenclamide treatment showed slight modification in the changes observed compared to the extract. The study concluded that the extract reversed diabetes and diabetes-induced oxidative changes in the hepatocytes, thus suggesting its use for the management of diabetic complications.Keywords: Vitex doniana, lipid peroxidation, streptozotocin-induced diabeticAfrican Journal of Biotechnology Vol. 12(40), pp. 5933-594

BDEtools: A MATLAB package for Boolean delay equation modelling.

This is the final version. Available from Mary Ann Liebert via the DOI in this record. DATA AVAILABILITY: The BDEtools package is under version control with git at GitHub: https://github.com/oeakman/BDEtools. BDEtools is released under the MIT license and requires MATLAB R2017a or later.Boolean Delay Equations (BDEs) can simulate surprisingly complex behavior, despite their relative simplicity. In addition to steady-state dynamics, BDEs can also generate periodic and quasiperiodic oscillations, m:n frequency locking, and even chaos. Further, the enumerability of Boolean update functions and their compact parametrization means that BDEs can be leveraged to generate low-level descriptions of biological networks, from which more detailed formulations (e.g., differential equation models) can be constructed. However, although several studies have demonstrated the utility of BDE modeling in computational biology, a current barrier to the wider adoption of the BDE approach is the absence of freely available simulation software. In this work, we present BDEtools-an open-source MATLAB package for numerically solving BDE models. After giving a brief introduction to BDE modeling, we describe the package's solver algorithms, together with several utility functions that can be used to provide solver inputs and to process solver outputs. We also demonstrate the functionality of BDEtools by illustrating its application to an established model of a gene regulatory network that controls circadian rhythms. BDEtools makes it straightforward for researchers to quickly build reliable BDE models of biological networks. We hope that its ease of use and free availability will encourage more researchers to explore BDE formulations of their systems of interest. Through the continued use of BDEs by the computational biology community, we will, no doubt, discover their potential applicability to a broader class of biological networks.Engineering and Physical Sciences Research CouncilEngineering and Physical Sciences Research Counci