Post-transcriptional regulation in the nucleus and cytoplasm: study of mean time to threshold (MTT) and narrow escape problem

Messenger RNAs (mRNAs) can be repressed and degraded by small non-coding RNA molecules. In this paper, we formulate a coarsegrained Markov-chain description of the post-transcriptional regulation of mRNAs by either small interfering RNAs (siRNAs) or microRNAs (miRNAs). We calculate the probability of an mRNA escaping from its domain before it is repressed by siRNAs/miRNAs via cal- culation of the mean time to threshold: when the number of bound siRNAs/miRNAs exceeds a certain threshold value, the mRNA is irreversibly repressed. In some cases,the analysis can be reduced to counting certain paths in a reduced Markov model. We obtain explicit expressions when the small RNA bind irreversibly to the mRNA and we also discuss the reversible binding case. We apply our models to the study of RNA interference in the nucleus, examining the probability of mRNAs escaping via small nuclear pores before being degraded by siRNAs. Using the same modelling framework, we further investigate the effect of small, decoy RNAs (decoys) on the process of post-transcriptional regulation, by studying regulation of the tumor suppressor gene, PTEN : decoys are able to block binding sites on PTEN mRNAs, thereby educing the number of sites available to siRNAs/miRNAs and helping to protect it from repression. We calculate the probability of a cytoplasmic PTEN mRNA translocating to the endoplasmic reticulum before being repressed by miRNAs. We support our results with stochastic simulations

Estimation of the time of a linear trend in monitoring survival time

Change point estimation is recognized as an essential tool of root cause analyses within quality control programs as it enables clinical experts to search for potential causes of change in hospital outcomes more effectively. In this paper, we consider estimation of the time when a linear trend disturbance has occurred in survival time following an in-control clinical intervention in the presence of variable patient mix. To model the process and change point, a linear trend in the survival time of patients who underwent cardiac surgery is formulated using hierarchical models in a Bayesian framework. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. We use Markov Chain Monte Carlo to obtain posterior distributions of the change point parameters including the location and the slope size of the trend and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time cumulative sum control chart (CUSUM) control charts for different trend scenarios. In comparison with the alternatives, step change point model and built-in CUSUM estimator, more accurate and precise estimates are obtained by the proposed Bayesian estimator over linear trends. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Linear and weakly nonlinear stability analyses of cooperative car-following models

Stability analyses have been widely used to better understand the mechanism of traffic jam formation. In this paper, we consider the impact of cooperative systems (a.k.a. connected vehicles) on traffic dynamics and, more precisely, on flow stability. Cooperative systems are emerging technologies enabling communication between vehicles and/or with the infrastructure. In a distributed communication framework, equipped vehicles are able to send and receive information to/from other equipped vehicles. Here, the effects of cooperative traffic are modeled through a general bilateral multianticipative car-following law that improves cooperative drivers' perception of their surrounding traffic conditions within a given communication range. Linear stability analyses are performed for a broad class of car-following models. They point out different stability conditions in both multianticipative and nonmultianticipative situations. To better understand what happens in unstable conditions, information on the shock wave structure is studied in the weakly nonlinear regime by the mean of the reductive perturbation method. The shock wave equation is obtained for generic car-following models by deriving the Korteweg de Vries equations. We then derive traffic-state-dependent conditions for the sign of the solitary wave (soliton) amplitude. This analytical result is verified through simulations. Simulation results confirm the validity of the speed estimate. The variation of the soliton amplitude as a function of the communication range is provided. The performed linear and weakly nonlinear analyses help justify the potential benefits of vehicle-integrated communication systems and provide new insights supporting the future implementation of cooperative systems.

Convergence of regenerative medicine and synthetic biology to develop standardized and validated models of human diseases with clinical relevance

In order to progress beyond currently available medical devices and implants, the concept of tissue engineering has moved into the centre of biomedical research worldwide. The aim of this approach is not to replace damaged tissue with an implant or device but rather to prompt the patient's own tissue to enact a regenerative response by using a tissue-engineered construct to assemble new functional and healthy tissue. More recently, it has been suggested that the combination of Synthetic Biology and translational tissue-engineering techniques could enhance the field of personalized medicine, not only from a regenerative medicine perspective, but also to provide frontier technologies for building and transforming the research landscape in the field of in vitro and in vivo disease models.

Estimating the parameters of stochastic volatility models using option price data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

A queuing approach for inventory planning with batch ordering in multi-echelon supply chains

This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

Compositional agent-based models for electricity distribution networks

This thesis presents a novel approach to building large-scale agent-based models of networked physical systems using a compositional approach to provide extensibility and flexibility in building the models and simulations. A software framework (MODAM - MODular Agent-based Model) was implemented for this purpose, and validated through simulations. These simulations allow assessment of the impact of technological change on the electricity distribution network looking at the trajectories of electricity consumption at key locations over many years.

Multiphase models for simulating hot and slightly miscible DNAPL (dense non-aqueous phase fluids) in a saturated rock fracture under deformation

In the present study a two dimensional model is first developed to show the behaviour of dense non-aqueous phase liquids (DNAPL) within a rough fracture. To consider the rough fracture, the fracture is imposed with variable apertures along its plane. It is found that DNAPL follows preferential pathways. In next part of the study the above model is further extended for non-isothermal DNAPL flow and DNAPL-water interphase mass transfer phenomenon. These two models are then coupled with joint deformation due to normal stresses. The primary focus of these models is specifically to elucidate the influence of joint alteration due to external stress and fluid pressures on flow driven energy transport and interphase mass transfer. For this, it is assumed that the critical value for joint alteration is associated with external stress and average of water and DNAPL pressures in multiphase system and the temporal and spatial evolution of joint alteration are determined for its further influence on energy transport and miscible phase transfer. The developed model has been studied to show the influence of deformation on DNAPL flow. Further this preliminary study demonstrates the influence of joint deformation on heat transport and phase miscibility via multiphase flow velocities. It is seen that the temperature profile changes and shows higher diffusivity due to deformation and although the interphase miscibility value decreases but the lateral dispersion increases to a considerably higher extent.

Exploring aged care business models : A typological study

Australian providers of aged care are facing a rapidly ageing population and growth in demand for services. Beyond a sheer increase in consumers and major regulatory changes from Federal Government, many customers are becoming progressively discontented with a medically dominated model of care provision. This period of turbulence presents an opportunity for new entrants and forward-thinking organisations to disrupt the market by designing a more compelling value offering. Under this line of inquiry, the researchers conducted a qualitative content analysis study of over 37 Australian aged care organisations, clustering providers into six business model typologies. The study revealed that providers of aged care are becoming increasingly aware of emerging customer needs, and, in addressing these needs, are seeking to establish innovative models of care provision. This paper therefore presents a future model of care, along with implications for practice and policy.

Comparison between computational models of abdominal aortic aneurysm

Objective: To compare the differences in the hemodynamic parameters of abdominal aortic aneurysm (AAA) between fluid-structure interaction model (FSIM) and fluid-only model (FM), so as to discuss their application in the research of AAA. Methods: An idealized AAA model was created based on patient-specific AAA data. In FM, the flow, pressure and wall shear stress (WSS) were computed using finite volume method. In FSIM, an Arbitrary Lagrangian-Eulerian algorithm was used to solve the flow in a continuously deforming geometry. The hemodynamic parameters of both models were obtained for discussion. Results: Under the same inlet velocity, there were only two symmetrical vortexes in the AAA dilation area for FSIM. In contrast, four recirculation areas existed in FM; two were main vortexes and the other two were secondary flow, which were located between the main recirculation area and the arterial wall. Six local pressure concentrations occurred in the distal end of AAA and the recirculation area for FM. However, there were only two local pressure concentrations in FSIM. The vortex center of the recirculation area in FSIM was much more close to the distal end of AAA and the area was much larger because of AAA expansion. Four extreme values of WSS existed at the proximal of AAA, the point of boundary layer separation, the point of flow reattachment and the distal end of AAA, respectively, in both FM and FSIM. The maximum wall stress and the largest wall deformation were both located at the proximal and distal end of AAA. Conclusions: The number and center of the recirculation area for both models are different, while the change of vortex is closely associated with the AAA growth. The largest WSS of FSIM is 36% smaller than that of FM. Both the maximum wall stress and largest wall displacement shall increase with the outlet pressure increasing. FSIM needs to be considered for studying the relationship between AAA growth and shear stress.

Electrochemical phase formation (ECPF): Nucleation growth vis-a-vis adsorption models

The nucleataon growth model of electrochemical phase formation is analysed for the hnear potential sweep input Apart from deducing diagnostic criteria and method~ of estimating model parameters, the predictions of the nucleation growth model are compared and contrasted with those of a sample adsorption model A dastlnCtlOn is made possible between adsorption and phase transition, which seems useful for understanding the nature of ECPF phenomena, especially underpotentlal deposition (UPD).

Comparison of Interproton Distances in DNA Models with Nuclear Overhauser Enhancement Data

The conformational flexibility inherent in the polynucleotide chain plays an important role in deciding its three-dimensonal structure and enables it to undergo structural transitions in order to fulfil all its functions. Following certain stereochemical guidelines, both right and left handed double-helical models have been built in our laboratory and they are in reasonably good agreement with the fibre patterns for various polymorphous forms of DNA. Recently, nuclear magnetic resonance spectroscopy has become an important technique for studying the solution conformation and polymorphism of nucleic acids. Several workers have used 1H nuclear magnetic resonance nuclear Overhauser enhancement measurements to estimate the interproton distances for the various DNA oligomers and compared them with the interproton distances for particular models of A and Β form DNA. In some cases the solution conformation does not seem to fit either of these models. We have been studying various models for DNA with a view to exploring the full conformational space allowed for nucleic acid polymers. In this paper, the interproton distances calculated for the different stereochemically feasible models of DNA are presented and they are compared and correlated against those obtained from 1Η nuclear magnetic resonance nuclear Overhauser enhancement measurements of various nucleic acid oligomers.

Relativistic particle models with separable interactions

We present relativistic, classical particle models that possess Poincaré invariance, invariant world lines, particle interaction, and separability.

Designing innovative business models with a framework that promotes experimentation

Purpose – Business models to date have remained the creation of management, however, it is the belief of the authors that designers should be critically approaching, challenging and creating new business models as part of their practice. This belief portrays a new era where business model constructs become the new design brief of the future and fuel design and innovation to work together at the strategic level of an organisation. Design/methodology/approach – The purpose of this paper is to explore and investigate business model design. The research followed a deductive structured qualitative content analysis approach utilizing a predetermined categorization matrix. The analysis of forty business cases uncovered commonalities of key strategic drivers behind these innovative business models. Findings – Five business model typologies were derived from this content analysis, from which quick prototypes of new business models can be created. Research limitations/implications – Implications from this research suggest there is no “one right” model, but rather through experimentation, the generation of many unique and diverse concepts can result in greater possibilities for future innovation and sustained competitive advantage. Originality/value – This paper builds upon the emerging research and exploration into the importance and relevance of dynamic, design-driven approaches to the creation of innovative business models. These models aim to synthesize knowledge gained from real world examples into a tangible, accessible and provoking framework that provide new prototyping templates to aid the process of business model experimentation.