Modelling drug coatings: A parallel cellular automata model of ethylcellulose-coated microspheres

Pharmaceutical companies today face a growing demand for more complex drug designs. In the past few decades, a number of probabilistic models have been developed, with the aim of improving insight on microscopic features of these complex designs. Of particular interest are models of controlled release systems, which can provide tools to study targeted dose delivery. Controlled release is achieved by using polymers with different dissolution characteristics. We present here an approach for parallelising a large-scale model of a drug delivery system based on Monte Carlo methods, as a framework for Cellular Automata mobility. The model simulates drug release in the gastro-intestinal tract, from coated ethylcellulose microspheres. The objective is high performance simulation of coated drugs for targeted delivery. The overall aim is to understand the importance of various molecular effects with respect to system evolution over time. Important underlying mechanisms of the process, such as erosion and diffusion, are described

Customer purchase behavior prediction in E-commerce: a conceptual framework and research agenda

Digital retailers are experiencing an increasing number of transactions coming from their consumers online, a consequence of the convenience in buying goods via E-commerce platforms. Such interactions compose complex behavioral patterns which can be analyzed through predictive analytics to enable businesses to understand consumer needs. In this abundance of big data and possible tools to analyze them, a systematic review of the literature is missing. Therefore, this paper presents a systematic literature review of recent research dealing with customer purchase prediction in the E-commerce context. The main contributions are a novel analytical framework and a research agenda in the field. The framework reveals three main tasks in this review, namely, the prediction of customer intents, buying sessions, and purchase decisions. Those are followed by their employed predictive methodologies and are analyzed from three perspectives. Finally, the research agenda provides major existing issues for further research in the field of purchase behavior prediction online

Understanding Urban Mobility and Pedestrian Movement

Urban environments continue to expand and mutate, both in terms of size of urban area and number of people commuting daily as well as the number of options for personal mobility. City layouts and infrastructure also change constantly, subject to both short-term and long-term imperatives. Transportation networks have attracted particular attention in recent years, due to efforts to incorporate “green” options, enabling positive lifestyle choices such as walking or cycling commutes. In this chapter we explore the pedestrian viewpoint, aids to familiarity with and ease of navigation in the urban environment, and the impact of novel modes of individual transport (as options such as smart urban bicycles and electric scooters increasingly become the norm). We discuss principal factors influencing rapid transit to daily and leisure destinations, such as schools, offices, parks, and entertainment venues, but also those which facilitate rapid evacuation and movement of large crowds from these locations, characterized by high occupation density or throughput. The focus of the chapter is on understanding and representing pedestrian behavior through the agent-based modeling paradigm, allowing both large numbers of individual actions with active awareness of the environment to be simulated and pedestrian group movements to be modeled on real urban networks, together with congestion and evacuation pattern visualization

Stochastic computational modelling of complex drug delivery systems

As modern drug formulations become more advanced, pharmaceutical companies face the need for adequate tools to permit them to model complex requirements and to reduce unnecessary adsorption rates while increasing the dosage administered. The aim of the research presented here is the development and application of a general stochastic framework with agent-based elements for building drug dissolution models, with a particular focus on controlled release systems. The utilisation of three dimensional Cellular Automata and Monte Carlo methods, to describe structural compositions and the main physico-chemical mechanisms, is shown to have several key advantages: (i) the bottom up approach simplifies the definition of complex interactions between underlying phenomena such as diffusion,polymer degradation and hydration, and the dissolution media; (ii) permits straightforward extensibility for drug formulation variations in terms of supporting various geometries and exploring effects of polymer composition and layering; (iii) facilitates visualisation, affording insight on system structural evolution over time by capturing successive stages of dissolution. The framework has been used to build models simulating several distinct release scenarios from coated spheres covering single coated erosion and swelling dominated spheres as well as the influence of multiple heterogeneous coatings. High-performance computational optimisation enables precision simulations of the very thin coatings used and allows fast realisation of model state changes. Furthermore, theoretical analysis of the comparative impact of synchronous and asynchronous Cellular Automata and the suitability of their application to pharmaceutical systems is performed. Likely parameter distributions from noisy in vitro data are reconstructed using Inverse Monte Carlo methods and outcomes are reported

Towards Refactoring in Cloud-Centric Internet of Things for Smart Cities

Smart city is an urban development vision to integrate multiple Information and Communication Technology (ICT) and Internet of Things (IoT) solutions in a secure fashion to manage a city’s assets. IoT devices are heterogeneous and collect large amount of data which need to be collected, processed, stored and shared among various devices, services and enterprise entities. Cloud technology has the potential to improve the performance, reliability and elasticity of software applications that drive the smart city vision. Due to the rapid increase in the number of devices, there is a critical need for the architecture of the cloud deployment to change constantly to adapt to the way these heterogeneous devices interact with the cloud services and on premise services are needed to migrate to cloud for the purpose of increasing performance and elasticity. Hence refactoring techniques could help tackling these issues as refactoring is a method of changing the internal design of the system while preserving the external behavior. In this paper we discuss refactoring and Clou-centric IoT in the context of Smart city, problems related to the inter-connectivity of these paradigms

A Requirements Framework for the Design of Smart City Reference Architectures

Reference architectures are generalized models of several end systems that share one or more common domains. They facilitate the design of high-quality concrete architectures and the communication between domain professionals. The reference architecture approach should be applied in the smart city domain because of its complexity where different stakeholders and heterogeneous systems and technologies must coexist and interact. Smart cities reference architectures should offer a cooperative framework for stakeholders and a guide to design concrete architectures. Industry and academia have proposed different requirements for concrete architectures. However, there is a lack of standardization in the requirements for the design of smart city reference architectures. This can produce that concrete architectures do not meet citizens’ requirements. The goal of this paper is to define a set of requirements for the design of smart city reference architectures. We conduct a literature review to find the requirements which should fulfil these reference architectures

Day ahead forecasting of FAANG stocks using ARIMA, LSTM networks and wavelets.

Abstract. Facebook Inc., Apple Inc., Amazon.com Inc., Net ix Inc. and Alphabet Inc., known collectively as FAANG, are a group of the best performing tech stocks in recent years. In this study, we present linear and non-linear methods for predicting the closing price of each stock on the following day. We decompose each time series into component series using wavelet methods and develop an novel ensemble approach to improve forecast accuracy

Students’ Behaviours in using Learning Resources in Higher Education: How do behaviours reflect success in Programming Education?

[EN] Programming education traditionally has been an important part of Information Technology-related degrees but, more recently, it is also becoming essential in many STEM domains as well. Despite this, drop-out rates in programming courses in higher education institutions are considerable and cannot be ignored. At the same time, analysing learning behaviours has been reported to be an effective way to support the improvement of teaching and learning quality. This article aims to deliver an in-depth analysis of students’ learning behaviours when using course material items. We analyse an introductory programming course at a University in Dublin. The dataset is extracted from automatically logged learning data from a bespoke online learning system. The analysis makes use of the power of Principal Component Analysis and Random Matrix Theory to reduce dimensionality in, and to extract information from, the data, verifying the results with rigorous statistical tests. Overall, we found that all the students follow a common learning pattern in accessing all given learning items. However, there is a noticeable difference between higher and lower-performing cohorts of students when using practical and theoretical learning items. The high performing students have been consistently active in practice during the study progress. On the other hand, the students who failed the exam have more recorded activities in reading lecture notes and appear to become discouraged and unmotivated from the practical activities, especially in the later stage of the semester.This research is financially supported by Irish Research Council.Mai, T.; Crane, M.; Bezbradica, M. (2021). Students’ Behaviours in using Learning Resources in Higher Education: How do behaviours reflect success in Programming Education?. En 7th International Conference on Higher Education Advances (HEAd'21). Editorial Universitat Politècnica de València. 47-55. https://doi.org/10.4995/HEAd21.2021.12939OCS475

Comparative analysis of asynchronous cellular automata in stochastic pharmaceutical modelling

In pharmaceutical modelling, cellular automata have been used as an established tool to represent molecular changes through discrete structural interactions. The data quality provided by such modelling is found suitable for the early drug design phase where flexibility is paramount. While both synchronous (CA) and asynchronous (ACA) types of automata have been used, analysis of their nature and comparative influence on model outputs is lacking. In this paper, we outline a representative probabilistic CA for modelling complex controlled drug formulations and investigate its transition from synchronous to asynchronous update algorithms. The key investigation points include quantification of model dynamics through three distinct scenarios, parallelisation performance and the ability to describe different release phenomena, namely erosion, diffusion and swelling. The choice of the appropriate update mechanism impacts the perceived realism of the simulation as well as the applicability of large-scale simulations

Probabilistic models for dissolution of ethylcellulose coated microspheres

In the last few decades, a number of probabilistic models for drug delivery have been developed. Of particular interest are those that model controlled release systems to provide targeted dose delivery. Controlled release is achieved by using polymers with dierent dissolution characteristics. We present here a model based on Monte Carlo and Cellular Automata approaches, for simulating drug release from coated microspheres in the gastro-intestinal tract. Controlled release is obtained using ethylcellulose as the coating polymer. Modelling features, such as the drug and coating dissolution are nontrivial, since material is non-homogenously dispersed and the dissolution exhibits complex behaviour. Important underlying mechanisms of the process, such as erosion, are described here