Simulation models in farming systems research : potential and challenges

Integrated simulation models can be useful tools in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent-based models. Applications of each approach are presented and strengths and drawbacks discussed. We argue that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models contribute important insights to the analysis of farming systems. They help unravelling the complex and dynamic interactions and feedbacks among bio-physical, socio-economic, and institutional components across scales and levels in farming systems. In addition, they can provide a platform for integrative research, and can support transdisciplinary research by functioning as learning platforms in participatory processes.

Social networks and occupational choice: the endogenous formation of attitudes and beliefs about tax compliance

The paper analyses the emergence of group-specific attitudes and beliefs about tax compliance when individuals interact in a social network. It develops a model in which taxpayers possess a range of individual characteristics – including attitude to risk, potential for success in self-employment, and the weight attached to the social custom for honesty – and make an occupational choice based on these characteristics. Occupations differ in the possibility for evading tax. The social network determines which taxpayers are linked, and information about auditing and compliance is transmitted at meetings between linked taxpayers. Using agent-based simulations, the analysis demonstrates how attitudes and beliefs endogenously emerge that differ across sub-groups of the population. Compliance behaviour is different across occupational groups, and this is reinforced by the development of group-specific attitudes and beliefs. Taxpayers self-select into occupations according to the degree of risk aversion, the subjective probability of audit is sustained above the objective probability, and the weight attached to the social custom differs across occupations. These factors combine to lead to compliance levels that differ across occupations.

Landscape structure mediates the effects of a stressor on field vole populations

Spatio-temporal landscape heterogeneity has rarely been considered in population-level impact assessments. Here we test whether landscape heterogeneity is important by examining the case of a pesticide applied seasonally to orchards which may affect non-target vole populations, using a validated ecologically realistic and spatially explicit agent-based model. Voles thrive in unmanaged grasslands and untreated orchards but are particularly exposed to applied pesticide treatments during dispersal between optimal habitats. We therefore hypothesised that vole populations do better (1) in landscapes containing more grassland and (2) where areas of grassland are closer to orchards, but (3) do worse if larger areas of orchards are treated with pesticide. To test these hyposeses we made appropriate manipulations to a model landscape occupied by field voles. Pesticide application reduced model population sizes in all three experiments, but populations subsequently wholly or partly recovered. Population depressions were, as predicted, lower in landscapes containing more unmanaged grassland, in landscapes with reduced distance between grassland and orchards, and in landscapes with fewer treated orchards. Population recovery followed a similar pattern except for an unexpected improvement in recovery when the area of treated orchards was increased. Outside the period of pesticide application, orchards increase landscape connectivity and facilitate vole dispersal and so speed population recovery. Overall our results show that accurate prediction of population impact cannot be achieved without taking account of landscape structure. The specifics of landscape structure and habitat connectivity are likely always important in mediating the effects of stressors.

Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

Understanding the link between single cell and population scale responses of Escherichia coli in differing ligand gradients

We formulate an agent-based population model of Escherichia coli cells which incorporates a description of the chemotaxis signalling cascade at the single cell scale. The model is used to gain insight into the link between the signalling cascade dynamics and the overall population response to differing chemoattractant gradients. Firstly, we consider how the observed variation in total (phosphorylated and unphosphorylated) signalling protein concentration affects the ability of cells to accumulate in differing chemoattractant gradients. Results reveal that a variation in total cell protein concentration between cells may be a mechanism for the survival of cell colonies across a wide range of differing environments. We then study the response of cells in the presence of two different chemoattractants.In doing so we demonstrate that the population scale response depends not on the absolute concentration of each chemoattractant but on the sensitivity of the chemoreceptors to their respective concentrations. Our results show the clear link between single cell features and the overall environment in which cells reside.

Spatial housing economics: a survey

This introduction to the Virtual Special Issue surveys the development of spatial housing economics from its roots in neo-classical theory, through more recent developments in social interactions modelling, and touching on the role of institutions, path dependence and economic history. The survey also points to some of the more promising future directions for the subject that are beginning to appear in the literature. The survey covers elements hedonic models, spatial econometrics, neighbourhood models, housing market areas, housing supply, models of segregation, migration, housing tenure, sub-national house price modelling including the so-called ripple effect, and agent-based models. Possible future directions are set in the context of a selection of recent papers that have appeared in Urban Studies. Nevertheless, there are still important gaps in the literature that merit further attention, arising at least partly from emerging policy problems. These include more research on housing and biodiversity, the relationship between housing and civil unrest, the effects of changing age distributions - notably housing for the elderly - and the impact of different international institutional structures. Methodologically, developments in Big Data provide an exciting framework for future work.

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.

Measuring Application Availability,Usage and Performance : Implementation of EnView System

The main objective for this degree project is to implement an Application Availability Monitoring (AAM) system named Softek EnView for Fujitsu Services. The aim of implementing the AAM system is to proactively identify end user performance problems, such as application and site performance, before the actual end users experience them. No matter how well applications and sites are designed and nomatter how well they meet business requirements, they are useless to the end users if the performance is slow and/or unreliable. It is important for the customers to find out whether the end user problems are caused by the network or application malfunction. The Softek EnView was comprised of the following EnView components: Robot, Monitor, Reporter, Collector and Repository. The implemented system, however, is designed to use only some of these EnView elements: Robot, Reporter and depository. Robots can be placed at any key user location and are dedicated to customers, which means that when the number of customers increases, at the sametime the amount of Robots will increase. To make the AAM system ideal for the company to use, it was integrated with Fujitsu Services’ centralised monitoring system, BMC PATROL Enterprise Manager (PEM). That was actually the reason for deciding to drop the EnView Monitor element. After the system was fully implemented, the AAM system was ready for production. Transactions were (and are) written and deployed on Robots to simulate typical end user actions. These transactions are configured to run with certain intervals, which are defined collectively with customers. While they are driven against customers’ applicationsautomatically, transactions collect availability data and response time data all the time. In case of a failure in transactions, the robot immediately quits the transactionand writes detailed information to a log file about what went wrong and which element failed while going through an application. Then an alert is generated by a BMC PATROL Agent based on this data and is sent to the BMC PEM. Fujitsu Services’ monitoring room receives the alert, reacts to it according to the incident management process in ITIL and by alerting system specialists on critical incidents to resolve problems. As a result of the data gathered by the Robots, weekly reports, which contain detailed statistics and trend analyses of ongoing quality of IT services, is provided for the Customers.

On the Use of Agents in a Bioinformatics Grid

MyGrid is an e-Science Grid project that aims to help biologists and bioinformaticians to perform workflow-based in silico experiments, and help them to automate the management of such workflows through personalisation, notification of change and publication of experiments. In this paper, we describe the architecture of myGrid and how it will be used by the scientist. We then show how myGrid can benefit from agents technologies. We have identified three key uses of agent technologies in myGrid: user agents, able to customize and personalise data, agent communication languages offering a generic and portable communication medium, and negotiation allowing multiple distributed entities to reach service level agreements.

Leveraging new plans in AgentSpeak(PL)

In order to facilitate the development of agent-based software, several agent programming languages and architectures, have been created. Plans in these architectures are often self-contained procedures with an associated triggering event and a context condition, while any further information about the consequences of executing a plan is absent. However, agents designed using such an approach have limited flexibility at runtime, and rely on the designer’s ability to foresee all relevant situations an agent might have to handle. In order to overcome this limitation, we have created AgentSpeak(PL), an interpreter capable of performing state-space planning to generate new high-level plans. As the planning module creates new plans, the plan library is expanded, improving performance over time. However, for new plans to be useful in the long run, it is critical that the context condition associated with new plans is carefully generated. In this paper we describe a plan reuse technique aimed at improving an agent’s runtime performance by deriving optimal context conditions for new plans, allowing an agent to reuse generated plans as much as possible.

Determining the Trustworthiness of New Electronic Contracts

Expressing contractual agreements electronically potentially allows agents to automatically perform functions surrounding contract use: establishment, fulfilment, renegotiation etc. For such automation to be used for real business concerns, there needs to be a high level of trust in the agent-based system. While there has been much research on simulating trust between agents, there are areas where such trust is harder to establish. In particular, contract proposals may come from parties that an agent has had no prior interaction with and, in competitive business-to-business environments, little reputation information may be available. In human practice, trust in a proposed contract is determined in part from the content of the proposal itself, and the similarity of the content to that of prior contracts, executed to varying degrees of success. In this paper, we argue that such analysis is also appropriate in automated systems, and to provide it we need systems to record salient details of prior contract use and algorithms for assessing proposals on their content. We use provenance technology to provide the former and detail algorithms for measuring contract success and similarity for the latter, applying them to an aerospace case study.

SESAME: Finding Ways Of Promoting SME Adaptation To Flood Risk

Small and medium-sized companies and other enterprises (SMEs) around the world are exposed to flood risk and many of the 4.5 million in the UK are at risk. As SMEs represent almost half of total business turnover in the UK, their protection is a vital part of the drive for greater climate change resilience. However, few have measures in place to ensure the continuity of their activities during a flood and its aftermath. The SESAME project aims to develop tools that encourage businesses to discover ways of becoming more resilient to floods and to appreciate how much better off they will be once they have adapted to the ongoing risk. By taking some of the mystery out of flooding and flood risk, it aims to make it susceptible to the same business acumen that enables the UK’s SMEs to deal with the many other challenges they face. In this paper we will report on the different aspects of the research in the project Understanding behaviour Changing behaviour Modelling impacts Economic impacts Through the above the project will advise government, local authorities and other public bodies on how to improve their responses to floods and will enable them to recommend ways to improve the guidelines provided to SMEs in flood risk areas.

O ente estadual na política de atendimento socioeducativo: desafios na implementação a partir de estudo comparativo em Minas Gerais e Rio Grande do Sul

Neste artigo, discute-se os desafios da implementação da política de atendimento socioeducativo em torno dos entes federados, proposta pela Lei 12.594/ 2012– Sistema Nacional de Atendimento Socioeducativo – SINASE. Para isso, realizou-se análise comparativa das normativas de Minas Gerais e Rio Grande do Sul a partir do olhar sobre a regulamentação do exercício profissional do agente de segurança socioeducativa, tendo por base os instrumentos institucionais: as políticas estaduais e o regimento da função de segurança socioeducativa. Identificou-se a prevalência de aspectos de segurança aos de socioeducação, o que torna a efetiva implementação do novo paradigma ainda um desafio. Apontam-se mudanças institucionais como propostas de aperfeiçoamento da política nos entes estaduais.