Tactile perception - Perception of tactile distance changes with body site: a neural network modelling study.

La distorsione della percezione della distanza tra due stimoli puntuali applicati sulla superfice della pelle di diverse regioni corporee �� conosciuta come Illusione di Weber. Questa illusione �� stata osservata, e verificata, in molti esperimenti in cui ai soggetti era chiesto di giudicare la distanza tra due stimoli applicati sulla superficie della pelle di differenti parti corporee. Da tali esperimenti si �� dedotto che una stessa distanza tra gli stimoli �� giudicata differentemente per diverse regioni corporee. Il concetto secondo cui la distanza sulla pelle �� spesso percepita in maniera alterata �� ampiamente condiviso, ma i meccanismi neurali che manovrano questa illusione sono, allo stesso tempo, ancora ampiamente sconosciuti. In particolare, non �� ancora chiaro come sia interpretata la distanza tra due stimoli puntuali simultanei, e quali aree celebrali siano coinvolte in questa elaborazione. L���illusione di Weber pu�� essere spiegata, in parte, considerando la differenza in termini di densit�� meccano-recettoriale delle differenti regioni corporee, e l���immagine distorta del nostro corpo che risiede nella Corteccia Primaria Somato-Sensoriale (homunculus). Tuttavia, questi meccanismi sembrano non sufficienti a spiegare il fenomeno osservato: infatti, secondo i risultati derivanti da 100 anni di sperimentazioni, le distorsioni effettive nel giudizio delle distanze sono molto pi�� piccole rispetto alle distorsioni che la Corteccia Primaria suggerisce. In altre parole, l���illusione osservata negli esperimenti tattili �� molto pi�� piccola rispetto all���effetto prodotto dalla differente densit�� recettoriale che affligge le diverse parti del corpo, o dall���estensione corticale. Ci��, ha portato a ipotizzare che la percezione della distanza tattile richieda la presenza di un���ulteriore area celebrale, e di ulteriori meccanismi che operino allo scopo di ridimensionare ��� almeno parzialmente ��� le informazioni derivanti dalla corteccia primaria, in modo da mantenere una certa costanza nella percezione della distanza tattile lungo la superfice corporea. E��� stata cos�� proposta la presenza di una sorta di ���processo di ridimensionamento���, chiamato ���Rescaling Process��� che opera per ridurre questa illusione verso una percezione pi�� verosimile. Il verificarsi di questo processo �� sostenuto da molti ricercatori in ambito neuro scientifico; in particolare, dal Dr. Matthew Longo, neuro scienziato del Department of Psychological Sciences (Birkbeck University of London), le cui ricerche sulla percezione della distanza tattile e sulla rappresentazione corporea sembrano confermare questa ipotesi. Tuttavia, i meccanismi neurali, e i circuiti che stanno alla base di questo potenziale ���Rescaling Process��� sono ancora ampiamente sconosciuti. Lo scopo di questa tesi �� stato quello di chiarire la possibile organizzazione della rete, e i meccanismi neurali che scatenano l���illusione di Weber e il ���Rescaling Process���, usando un modello di rete neurale. La maggior parte del lavoro �� stata svolta nel Dipartimento di Scienze Psicologiche della Birkbeck University of London, sotto la supervisione del Dott. M. Longo, il quale ha contribuito principalmente all���interpretazione dei risultati del modello, dando suggerimenti sull���elaborazione dei risultati in modo da ottenere un���informazione pi�� chiara; inoltre egli ha fornito utili direttive per la validazione dei risultati durante l���implementazione di test statistici. Per replicare l���illusione di Weber ed il ���Rescaling Proess���, la rete neurale �� stata organizzata con due strati principali di neuroni corrispondenti a due differenti aree funzionali corticali: ��� Primo strato di neuroni (il quale d�� il via ad una prima elaborazione degli stimoli esterni): questo strato pu�� essere pensato come parte della Corteccia Primaria Somato-Sensoriale affetta da Magnificazione Corticale (homunculus). ��� Secondo strato di neuroni (successiva elaborazione delle informazioni provenienti dal primo strato): questo strato pu�� rappresentare un���Area Corticale pi�� elevata coinvolta nell���implementazione del ���Rescaling Process���. Le reti neurali sono state costruite includendo connessioni sinaptiche all���interno di ogni strato (Sinapsi Laterali), e connessioni sinaptiche tra i due strati neurali (Sinapsi Feed-Forward), assumendo inoltre che l���attivit�� di ogni neurone dipenda dal suo input attraverso una relazione sigmoidale statica, cosi come da una dinamica del primo ordine. In particolare, usando la struttura appena descritta, sono state implementate due differenti reti neurali, per due differenti regioni corporee (per esempio, Mano e Braccio), caratterizzate da differente risoluzione tattile e differente Magnificazione Corticale, in modo da replicare l���Illusione di Weber ed il ���Rescaling Process���. Questi modelli possono aiutare a comprendere il meccanismo dell���illusione di Weber e dare cos�� una possibile spiegazione al ���Rescaling Process���. Inoltre, le reti neurali implementate forniscono un valido contributo per la comprensione della strategia adottata dal cervello nell���interpretazione della distanza sulla superficie della pelle. Oltre allo scopo di comprensione, tali modelli potrebbero essere impiegati altres�� per formulare predizioni che potranno poi essere verificate in seguito, in vivo, su soggetti reali attraverso esperimenti di percezione tattile. E��� importante sottolineare che i modelli implementati sono da considerarsi prettamente come modelli funzionali e non intendono replicare dettagli fisiologici ed anatomici. I principali risultati ottenuti tramite questi modelli sono la riproduzione del fenomeno della ���Weber���s Illusion��� per due differenti regioni corporee, Mano e Braccio, come riportato nei tanti articoli riguardanti le illusioni tattili (per esempio ���The perception of distance and location for dual tactile pressures��� di Barry G. Green). L���illusione di Weber �� stata registrata attraverso l���output delle reti neurali, e poi rappresentata graficamente, cercando di spiegare le ragioni di tali risultati.

Tactile Perception - Perception of tactile distance on a single skin surface changes with stimulus orientation: a neuronal network modelling study

L���interazione che abbiamo con l���ambiente che ci circonda dipende sia da diverse tipologie di stimoli esterni che percepiamo (tattili, visivi, acustici, ecc.) sia dalla loro elaborazione per opera del nostro sistema nervoso. A volte per��, l���integrazione e l���elaborazione di tali input possono causare effetti d���illusione. Ci�� si presenta, ad esempio, nella percezione tattile. Infatti, la percezione di distanze tattili varia al variare della regione corporea considerata. Il concetto che distanze sulla cute siano frequentemente erroneamente percepite, �� stato scoperto circa un secolo fa da Weber. In particolare, una determinata distanza fisica, �� percepita maggiore su parti del corpo che presentano una pi�� alta densit�� di meccanocettori rispetto a distanze applicate su parti del corpo con inferiore densit��. Oltre a questa illusione, un importante fenomeno osservato in vivo �� rappresentato dal fatto che la percezione della distanza tattile dipende dall���orientazione degli stimoli applicati sulla cute. In sostanza, la distanza percepita su una regione cutanea varia al variare dell���orientazione degli stimoli applicati. Recentemente, Longo e Haggard (Longo & Haggard, J.Exp.Psychol. Hum Percept Perform 37: 720-726, 2011), allo scopo di investigare come sia rappresentato il nostro corpo all���interno del nostro cervello, hanno messo a confronto distanze tattili a diverse orientazioni sulla mano deducendo che la distanza fra due stimoli puntuali �� percepita maggiore se applicata trasversalmente sulla mano anzich�� longitudinalmente. Tale illusione �� nota con il nome di Illusione Tattile Orientazione-Dipendente e diversi risultati riportati in letteratura dimostrano che tale illusione dipende dalla distanza che intercorre fra i due stimoli puntuali sulla cute. Infatti, Green riporta in un suo articolo (Green, Percpept Pshycophys 31, 315-323, 1982) il fatto che maggiore sia la distanza applicata e maggiore risulter�� l���effetto illusivo che si presenta. L���illusione di Weber e l���illusione tattile orientazione-dipendente sono spiegate in letteratura considerando differenze riguardanti la densit�� di recettori, gli effetti di magnificazione corticale a livello della corteccia primaria somatosensoriale (regioni della corteccia somatosensoriale, di dimensioni differenti, sono adibite a diverse regioni corporee) e differenze nella dimensione e forma dei campi recettivi. Tuttavia tali effetti di illusione risultano molto meno rilevanti rispetto a quelli che ci si aspetta semplicemente considerando i meccanismi fisiologici, elencati in precedenza, che li causano. Ci�� suggerisce che l���informazione tattile elaborata a livello della corteccia primaria somatosensoriale, riceva successivi step di elaborazione in aree corticali di pi�� alto livello. Esse agiscono allo scopo di ridurre il divario fra distanza percepita trasversalmente e distanza percepita longitudinalmente, rendendole pi�� simili tra loro. Tale processo assume il nome di ���Rescaling Process���. I meccanismi neurali che operano nel cervello allo scopo di garantire Rescaling Process restano ancora largamente sconosciuti. Perci��, lo scopo del mio progetto di tesi �� stato quello di realizzare un modello di rete neurale che simulasse gli aspetti riguardanti la percezione tattile, l���illusione orientazione-dipendente e il processo di rescaling avanzando possibili ipotesi circa i meccanismi neurali che concorrono alla loro realizzazione. Il modello computazionale si compone di due diversi layers neurali che processano l���informazione tattile. Uno di questi rappresenta un���area corticale di pi�� basso livello (chiamata Area1) nella quale una prima e distorta rappresentazione tattile �� realizzata. Per questo, tale layer potrebbe rappresentare un���area della corteccia primaria somatosensoriale, dove la rappresentazione della distanza tattile �� significativamente distorta a causa dell���anisotropia dei campi recettivi e della magnificazione corticale. Il secondo layer (chiamato Area2) rappresenta un���area di pi�� alto livello che riceve le informazioni tattili dal primo e ne riduce la loro distorsione mediante Rescaling Process. Questo layer potrebbe rappresentare aree corticali superiori (ad esempio la corteccia parietale o quella temporale) adibite anch���esse alla percezione di distanze tattili ed implicate nel Rescaling Process. Nel modello, i neuroni in Area1 ricevono informazioni dagli stimoli esterni (applicati sulla cute) inviando quindi informazioni ai neuroni in Area2 mediante sinapsi Feed-forward eccitatorie. Di fatto, neuroni appartenenti ad uno stesso layer comunicano fra loro attraverso sinapsi laterali aventi una forma a cappello Messicano. E��� importante affermare che la rete neurale implementata �� principalmente un modello concettuale che non si preme di fornire un���accurata riproduzione delle strutture fisiologiche ed anatomiche. Per questo occorre considerare un livello astratto di implementazione senza specificare un���esatta corrispondenza tra layers nel modello e regioni anatomiche presenti nel cervello. Tuttavia, i meccanismi inclusi nel modello sono biologicamente plausibili. Dunque la rete neurale pu�� essere utile per una migliore comprensione dei molteplici meccanismi agenti nel nostro cervello, allo scopo di elaborare diversi input tattili. Infatti, il modello �� in grado di riprodurre diversi risultati riportati negli articoli di Green e Longo & Haggard.

Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16���165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Neural Network Modelling with Input Uncertainty: Theory and Application

It is generally assumed when using Bayesian inference methods for neural networks that the input data contains no noise. For real-world (errors in variable) problems this is clearly an unsafe assumption. This paper presents a Bayesian neural network framework which accounts for input noise provided that a model of the noise process exists. In the limit where the noise process is small and symmetric it is shown, using the Laplace approximation, that this method adds an extra term to the usual Bayesian error bar which depends on the variance of the input noise process. Further, by treating the true (noiseless) input as a hidden variable, and sampling this jointly with the network���s weights, using a Markov chain Monte Carlo method, it is demonstrated that it is possible to infer the regression over the noiseless input. This leads to the possibility of training an accurate model of a system using less accurate, or more uncertain, data. This is demonstrated on both the, synthetic, noisy sine wave problem and a real problem of inferring the forward model for a satellite radar backscatter system used to predict sea surface wind vectors.

Characterisation of the sewage microbiome in four European cities throughout the COVID-19 pandemic by means of ecological and network modelling

The purpose of this work was to investigate possible patterns occurring in the sewage bacterial content of four cities (Bologna, Budapest, Rome, Rotterdam) over time (March 2020 - November 2021), also considering the possible effects of the lockdown periods due to the COVID-19 pandemic. The sewage metagenomics data were provided within VEO (Versatile Emerging infectious disease Observatory) project. The first analysis was the evaluation of the between samples diversity, looking for (dis)similarities among the cities, as well as among different time periods (seasonality). To this aim, we computed both similarity networks and Principal Coordinate Analysis (PCoA) plots based on the Bray-Curtis metric. Then, the alpha-biodiversity of the samples was estimated by means of different diversity indices. By looking at the temporal behaviour of the biodiversity in the four cities, we noticed an abrupt decrease in both Rome and Budapest in the Summer of 2020, that is related to: the prevalence of some species when the minimum occurred, and the change in correlations among species (studied via correlation networks), which is enriched in the period of minimum biodiversity. Rotterdam samples seem to be very different with respect to those from the other cities, as confirmed by PCoA. Moreover, the Rotterdam time series is proved to be stable and stationary also in terms of biodiversity. The low variability in the Rotterdam samples seems to be related to the species of Pseudomonas genus, which are highly variable and plentiful in the other cities, but are not among the most abundant in Rotterdam. Also, we observed that no seasonality effect emerged from the time series of the four cities. Regarding the impact of lockdown periods due to the COVID-19 pandemic, from the limited data available no effect on the time series considered emerges. More samples will be soon available and these analyses will be performed also on them, so that the possible effects of lockdowns may be studied.

Energy-based modelling and simulation of the interconnection of a back-to-back converter and a doubly-fed induction machine

This paper describes the port interconnection of two subsystems: a power electronics subsystem (a back-to-back AC/CA converter (B2B), coupled to a phase of the power grid), and an electromechanical subsystem (a doubly-fed induction machine (DFIM). The B2B is a variable structure system (VSS), due to presence of control-actuated switches: however, from a modelling simulation, as well as a control-design, point of view, it is sensible to consider modulated transformers (MTF in the bond graph language) instead of the pairs of complementary switches. The port-Hamiltonian models of both subsystems are presented and, using a power-preserving interconnection, the Hamiltonian description of the whole system is obtained; detailed bond graphs of all subsystems and the complete system are also provided. Using passivity-based controllers computed in the Hamiltonian formalism for both subsystems, the whole model is simulated; simulations are run to rest the correctness and efficiency of the Hamiltonian network modelling approach used in this work.

Object-Oriented Modelling of Multilayer Networks

T��m�� diplomity��kuuluu tietoliikenneverkkojen suunnittelun tutkimukseen ja pohjimmiltaan kohdistuu verkon mallintamiseen. Tietoliikenneverkkojen suunnittelu on monimutkainen ja vaativa ongelma, joka sis��lt���� mutkikkaita ja aikaa vievi�� teht��vi��. T��m�� diplomity�� esittelee ���monikerroksisen verkkomallin���, jonka tarkoitus on auttaa verkon suunnittelijoita selviytym����n ongelmien monimutkaisuudesta ja v��hent���� verkkojen suunnitteluun kuluvaa aikaa. Monikerroksinen verkkomalli perustuu yleisille objekteille, jotka ovat yhteisi�� kaikille tietoliikenneverkoille. T��m�� tekee mallista soveltuvan mielivaltaisille verkoille, v��litt��m��tt�� verkkokohtaisista ominaisuuksista tai verkon toteutuksessa k��ytetyist�� teknologioista. Malli m����rittelee tarkan terminologian ja k��ytt���� kolmea k��sitett��: verkon jakaminen tasoihin (plane separation), kerrosten muodostaminen (layering) ja osittaminen (partitioning). N��m�� k��sitteet kuvataan yksityiskohtaisesti t��ss�� ty��ss��. Monikerroksisen verkkomallin sis��inen rakenne ja toiminnallisuus ovat m����ritelty k��ytt��en Unified Modelling Language (UML) -notaatiota. T��m�� ty�� esittelee mallin use case- , paketti- ja luokkakaaviot. Diplomity�� esittelee my��s tulokset, jotka on saatu vertailemalla monikerroksista verkkomallia muihin verkkomalleihin. Tulokset osoittavat, ett�� monikerroksisella verkkomallilla on etuja muihin malleihin verrattuna.

International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes.

A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling.

LVDC power distribution system: computational modelling

In the doctoral dissertation, low-voltage direct current (LVDC) distribution system stability, supply security and power quality are evaluated by computational modelling and measurements on an LVDC research platform. Computational models for the LVDC network analysis are developed. Time-domain simulation models are implemented in the time-domain simulation environment PSCAD/EMTDC. The PSCAD/EMTDC models of the LVDC network are applied to the transient behaviour and power quality studies. The LVDC network power loss model is developed in a MATLAB environment and is capable of fast estimation of the network and component power losses. The model integrates analytical equations that describe the power loss mechanism of the network components with power flow calculations. For an LVDC network research platform, a monitoring and control software solution is developed. The solution is used to deliver measurement data for verification of the developed models and analysis of the modelling results. In the work, the power loss mechanism of the LVDC network components and its main dependencies are described. Energy loss distribution of the LVDC network components is presented. Power quality measurements and current spectra are provided and harmonic pollution on the DC network is analysed. The transient behaviour of the network is verified through time-domain simulations. DC capacitor guidelines for an LVDC power distribution network are introduced. The power loss analysis results show that one of the main optimisation targets for an LVDC power distribution network should be reduction of the no-load losses and efficiency improvement of converters at partial loads. Low-frequency spectra of the network voltages and currents are shown, and harmonic propagation is analysed. Power quality in the LVDC network point of common coupling (PCC) is discussed. Power quality standard requirements are shown to be met by the LVDC network. The network behaviour during transients is analysed by time-domain simulations. The network is shown to be transient stable during large-scale disturbances. Measurement results on the LVDC research platform proving this are presented in the work.

Utilizing analytic modelling process in industrial retail context

Nykyp��iv��n monimutkaisessa ja ep��vakaassa liiketoimintaymp��rist��ss�� yritykset, jotka kykenev��t muuttamaan tuottamansa operatiivisen datan tietovarastoiksi, voivat saavuttaa merkitt��v���� kilpailuetua. Ennustavan analytiikan hy��dynt��minen tulevien trendien ennakointiin mahdollistaa yritysten tunnistavan avaintekij��it��, joiden avulla he pystyv��t erottumaan kilpailijoistaan. Ennustavan analytiikan hy��dynt��minen osana p����t��ksentekoprosessia mahdollistaa ketter��mm��n, reaaliaikaisen p����t��ksenteon. T��m��n diplomity��n tarkoituksena on koota teoreettinen viitekehys analytiikan mallintamisesta liike-el��m��n loppuk��ytt��j��n n��k��kulmasta ja hy��dynt���� t��t�� mallinnusprosessia diplomity��n tapaustutkimuksen yritykseen. Teoreettista mallia hy��dynnettiin asiakkuuksien mallintamisessa sek�� tunnistamalla ennakoivia tekij��it�� myynnin ennustamiseen. Ty�� suoritettiin suomalaiseen teollisten suodattimien tukkukauppaan, jolla on liiketoimintaa Suomessa, Ven��j��ll�� ja Balteissa. T��m�� tutkimus on m����r��llinen tapaustutkimus, jossa t��rkeimp��n�� tiedonkeruumenetelm��n�� k��ytettiin tapausyrityksen transaktiodataa. Data ty��h��n saatiin yrityksen toiminnanohjausj��rjestelm��st��.

Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design

A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious RBF network model with excellent generalisation performance. The D-optimality design criterion enhances the model efficiency and robustness. A further advantage of the combined approach is that the user only needs to specify a weighting for the D-optimality cost in the combined RBF model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Predicting the population impact of chlamydia screening programmes: comparative mathematical modelling study

BACKGROUND: Published individual-based, dynamic sexual network modelling studies reach different conclusions about the population impact of screening for Chlamydia trachomatis. The objective of this study was to conduct a direct comparison of the effect of organised chlamydia screening in different models. METHODS: Three models simulating population-level sexual behaviour, chlamydia transmission, screening and partner notification were used. Parameters describing a hypothetical annual opportunistic screening program in 16-24 year olds were standardised, whereas other parameters from the three original studies were retained. Model predictions of the change in chlamydia prevalence were compared under a range of scenarios. RESULTS: Initial overall chlamydia prevalence rates were similar in women but not men and there were age and sex-specific differences between models. The number of screening tests carried out was comparable in all models but there were large differences in the predicted impact of screening. After 10 years of screening, the predicted reduction in chlamydia prevalence in women aged 16-44 years ranged from 4% to 85%. Screening men and women had a greater impact than screening women alone in all models. There were marked differences between models in assumptions about treatment seeking and sexual behaviour before the start of the screening intervention. CONCLUSIONS: Future models of chlamydia transmission should be fitted to both incidence and prevalence data. This meta-modelling study provides essential information for explaining differences between published studies and increasing the utility of individual-based chlamydia transmission models for policy making.

Modelling tribology of slider and disk in a computer hard drive system

Issues of wear and tribology are increasingly important in computer hard drives as slider flying heights are becoming lower and disk protective coatings thinner to minimise spacing loss and allow higher areal density. Friction, stiction and wear between the slider and disk in a hard drive were studied using Accelerated Friction Test (AFT) apparatus. Contact Start Stop (CSS) and constant speed drag tests were performed using commercial rigid disks and two different air bearing slider types. Friction and stiction were captured during testing by a set of strain gauges. System parameters were varied to investigate their effect on tribology at the head/disk interface. Chosen parameters were disk spinning velocity, slider fly height, temperature, humidity and intercycle pause. The effect of different disk texturing methods was also studied. Models were proposed to explain the influence of these parameters on tribology. Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM) were used to study head and disk topography at various test stages and to provide physical parameters to verify the models. X-ray Photoelectron Spectroscopy (XPS) was employed to identify surface composition and determine if any chemical changes had occurred as a result of testing. The parameters most likely to influence the interface were identified for both CSS and drag testing. Neural Network modelling was used to substantiate results. Topographical AFM scans of disk and slider were exported numerically to file and explored extensively. Techniques were developed which improved line and area analysis. A method for detecting surface contacts was also deduced, results supported and explained observed AFT behaviour. Finally surfaces were computer generated to simulate real disk scans, this allowed contact analysis of many types of surface to be performed. Conclusions were drawn about what disk characteristics most affected contacts and hence friction, stiction and wear.