A tuneable software cache coherence protocol for heterogeneous MPSoCs

ABSTRACT In a multiprocessor system-on-chip (MPSoC) private caches introduce the cache coherence problem. Here, we target at heterogeneous MPSoCs with a network-on-chip (NoC). Existing hardware cache coherence protocols are less suitable for MPSoCs because many off-the-shelf processors used in MPSoCs do not support these protocols. Furthermore, these protocols typically rely on global visibility and serialization of writes which does not match well with the parallel pointto-point communication provided by a NoC. Therefore, we propose a software cache coherence protocol, which can be applied in a heterogeneous MPSoC with a NoC. The software cache coherence protocol relies on explicit synchronization in the software. More specifically, caches are guaranteed to be coherent according to the Release Consistency model, on top of which we have implemented the standard Pthreads communication library. Heterogeneous MPSoCs with off-the-shelf processors can easily be supported, because processors are only required to provide cache control operations, e.g., clean and invalidate. All cache coherence operations are interruptible and do not impact the execution of tasks on other processors, therefore this protocol is suitable for predictable MPSoCs. Our software cache coherence protocol is implemented on an ARM926EJ-S MPSoC which is mapped on an FPGA. From experiments we conclude that the protocol overhead is low for the applications taken from the SPLASH-2 benchmark set. For these applications we observed a speedup between 1.89 and 2.01 on the two processor MPSoC

Taguchi approach for performance evaluation of service-oriented software systems.

Service-oriented software systems are becoming increasingly common in the world today as big companies such as Microsoft and IBM advocate approaches focusing on assembly of system from distributed services. Although performance of such systems is a big problem, there is surprisingly an obvious lack of attention for evaluating the performance of enterprise-scale, service-oriented software systems. This thesis investigates the application of statistical tools in performance engineering domain for total quality management. In particular, the Taguchi approach is used as an efficient and systematic way to optimize designs for performance, quality, and cost. The aim is to improve the performance of software systems and to reduce application development cost by assembling services from known vendors or intranet services. The focus of this thesis is on the response time of service-oriented systems. Nevertheless, the developed methodology also applies to other performance issues, such as memory management and caching. The interaction problems of those issues are preserved for future work.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .L585. Source: Masters Abstracts International, Volume: 43-01, page: 0240. Adviser: Xiaobu Yuan. Thesis (M.Sc.)--University of Windsor (Canada), 2004

Characterization of vascular heterogeneity of astrocytomas grade 4 for supporting patient prognosis estimation, and treatment response assessment

[ES] Los tumores cerebrales son una de las enfermedades más devastadoras en la actualidad por el importante deterioro cognitivo que sufren los pacientes, la elevada tasa de mortalidad y el mal pronóstico. Los astrocitomas de grado 4 conllevan una supervivencia de cinco años en aproximadamente el 5% de los pacientes diagnosticados, siendo los tumores más agresivos y letales del Sistema Nervioso Central (SNC). Los astrocitomas de grado 4 siguen siendo un problema médico complejo aún sin resolver. A pesar de representar más del 60% de los tumores cerebrales malignos en adultos, estos tumores tienen una baja prevalencia relativa y se consideran una enfermedad huérfana, lo que dificulta el desarrollo de nuevos fármacos o tratamientos que puedan beneficiar a los pacientes. La agresividad de estos tumores se debe a diferentes características, como la fuerte angiogénesis, la necrosis, la microproliferación vascular, la capacidad de invasión e infiltración de las células tumorales y un microambiente inmunológico particular. Además, debido a la rápida progresión de los astrocitomas de grado 4, en la zona de la lesión coexisten diferentes regiones específicas que cambian con el tiempo. Esta naturaleza compleja, junto con la marcada heterogeneidad interpaciente, intratumoral y longitudinal, complica el éxito de un único tratamiento eficaz para todos los pacientes. La imagen de resonancia magnética (MRI) supone una técnica útil para caracterizar la morfología y la vascularidad del tumor. El uso de métodos avanzados y robustos para analizar las imágenes de MR recogidas en las fases iniciales del tratamiento de los pacientes permite la delimitación de las diferentes regiones de los astrocitomas de grado 4, convirtiéndose en herramientas útiles para investigadores, radiólogos y neurocirujanos. Además, el cálculo de biomarcadores vasculares de imagen, como los propuestos en esta tesis, facilitaría la caracterización del tumor, la estimación del pronóstico y los enfoques de tratamiento más personalizados. Esta tesis propone cuatro pilares fundamentales para avanzar en el manejo de los astrocitomas de grado 4. Estos incluyen I) la caracterización multinivel del tumor para mejorar las clasificaciones de los gliomas de alto grado del SNC; II) la búsqueda y desarrollo de biomarcadores robustos para estimar el pronóstico de los pacientes desde el momento prequirúrgico; III) así como para evaluar la respuesta a los tratamientos y la selección de los pacientes que pueden beneficiarse de terapias específicas; y IV) el diseño e implementación de estudios clínicos y protocolos para la recogida de datos a largo plazo de cohortes de pacientes notables a nivel internacional. Para abordar estos cuatro pilares, se ha utilizado un enfoque interdisciplinario que combina el análisis de imágenes médicas, técnicas avanzadas de inteligencia artificial y variables moleculares, histopatológicas y clínicas. En conclusión, hemos abordado la influencia de la heterogeneidad interpaciente e intratumoral del astrocitoma de grado 4 para la caracterización y clasificación del tumor, la estimación del pronóstico del paciente y la predicción de las respuestas al tratamiento. Además, se han diseñado e implementado diferentes estudios clínicos que permiten la recogida de datos multinivel de cohortes internacionales de pacientes con astrocitoma de grado 4.[CA] Els tumors cerebrals són una de les malalties més devastadores en l'actualitat per la important deterioració cognitiva que pateixen els pacients, l'elevada taxa de mortalitat i el mal pronòstic. Els astrocitomes de grau 4 comporten una supervivència de cinc anys en aproximadament el 5% dels pacients diagnosticats, sent els tumors més agressius i letals del Sistema Nerviós Central (SNC). Els astrocitomes de grau 4 continuen sent un problema mèdic complex encara sense resoldre. Malgrat representar més del 60% dels tumors cerebrals malignes en adults, aquests tumors tenen una baixa prevalença relativa i es consideren una malaltia òrfena, la qual cosa dificulta el desenvolupament de nous fàrmacs o tractaments que puguen beneficiar als pacients. L'agressivitat d'aquests tumors es deu a diferents característiques, com la forta angiogènesis, la necrosi, la microproliferació vascular, la capacitat d'invasió i infiltració de les cèl·lules tumorals i un microambient immunològic particular. A més, a causa de la ràpida progressió dels astrocitomes de grau 4, en la zona de la lesió coexisteixen diferents regions específiques que canvien amb el temps. Aquesta naturalesa complexa, juntament amb la marcada heterogeneïtat interpacient, intratumoral i longitudinal fa que es complique l'èxit d'un únic tractament eficaç per a tots els pacients. L'imatge de ressonància magnètica (MRI) suposa una tècnica útil per a caracteritzar la morfologia i la vascularitat del tumor. L'ús de mètodes avançats i robustos per a analitzar les imatges de MR recollides en les fases inicials del tractament dels pacients permet la delimitació de les diferents regions dels astrocitomes de grau 4, convertint-se en eines útils per a investigadors, radiòlegs i neurocirugians. A més, el càlcul de biomarcadors vasculars d'imatge, com els proposats en aquesta tesi, facilitaria la caracterització del tumor, l'estimació del pronòstic i els enfocaments de tractament més personalitzats. Aquesta tesi proposa quatre pilars fonamentals per a avançar en el maneig dels astrocitomes de grau 4. Aquests inclouen I) la caracterització multinivell del tumor per a millorar les classificacions dels gliomes d'alt grau del SNC; II) la cerca i desenvolupament de biomarcadors robustos per a estimar el pronòstic dels pacients des del moment prequirúrgic; III) així com per a avaluar la resposta als tractaments i la selecció dels pacients que poden beneficiar-se de teràpies específiques; i IV) el disseny i implementació d'estudis clínics i protocols per a la recollida de dades a llarg termini de cohorts de pacients notables a nivell internacional. Per a abordar aquests quatre pilars, s'ha utilitzat un enfocament interdisciplinari que combina l'anàlisi d'imatges mèdiques, tècniques avançades d'intel·ligència artificial i variables moleculars, histopatològiques i clíniques. En conclusió, hem abordat la influència de l'heterogeneïtat interpacient i intratumoral del astrocitoma de grau 4 per a la caracterització i classificació del tumor, l'estimació del pronòstic del pacient i la predicció de les respostes al tractament. A més, s'han dissenyat i implementat diferents estudis clínics que permeten la recollida de dades multinivell de cohorts internacionals de pacients amb astrocitoma de grau 4.[EN] Brain tumors are one of the most devastating diseases today because of the significant cognitive impairment suffered by patients, high mortality rates, and poor prognosis. Astrocytomas grade 4 bring five-year survival in approximately 5% of diagnosed patients, being the most aggressive and lethal tumors of the Central Nervous System (CNS). Astrocytomas grade 4 continue to be an unresolved complex medical problem. Despite accounting for more than 60% of malignant brain tumors in adults, these tumors have a low relative prevalence and are considered an orphan disease, making difficult developing new drugs or treatments that might benefit patients. The aggressiveness of these tumors is due to different characteristics, such as strong angiogenesis, necrosis, vascular microproliferation, the capacity of the tumor cells to invade and infiltrate, and a particular immune microenvironment. In addition, due to the rapid progression of astrocytomas grade 4, different specific regions coexist in the lesion area which change over time. This complex nature, along with the marked interpatient, intratumor, and longitudinal heterogeneity, makes complicate the success of a single efficient treatment for all patients. Magnetic Resonance Imaging (MRI) represents a useful technique to characterize tumor morphology and vascularity. Using advanced and robust methods to analyze MR images collected from initial stages of patient management allows the delineation of different regions of astrocytomas grade 4, becoming useful tools for researchers, radiologists and neurosurgeons. In addition, the calculation of imaging vascular biomarkers, such as those proposed in this thesis, would facilitate tumor characterization, prognosis estimation and more personalized treatment approaches. This thesis proposes four fundamental pillars to advance the management of astrocytomas grade 4. These include I) the multilevel characterization of the tumor to improve classifications of high-grade CNS gliomas; II) the search and development of robust biomarkers for estimating patient prognosis from the presurgical moment; III) as well as for evaluating the response to treatments and the selection of patients who may benefit from specific therapies; and IV) the design and implementation of clinical studies and protocols for long-term collecting data from internationally remarkable cohorts of patients. To address these four pillars, an interdisciplinary approach has been used that combines medical imaging analysis, advanced artificial intelligence techniques, and molecular, histopathological, and clinical variables. Concluding, we have addressed the influence of both interpatient and intratumor heterogeneity of astrocytoma grade 4 for tumor characterization and classification, patient prognosis estimation and predicting treatment responses. In addition, different clinical studies have been designed and implemented allowing the collection of multilevel data from international cohorts of patients with astrocytoma grade 4.Álvarez Torres, MDM. (2022). Characterization of vascular heterogeneity of astrocytomas grade 4 for supporting patient prognosis estimation, and treatment response assessment [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/18895

SoS: self-organizing substrates

Large-scale networked systems often, both by design or chance exhibit self-organizing properties. Understanding self-organization using tools from cybernetics, particularly modeling them as Markov processes is a first step towards a formal framework which can be used in (decentralized) systems research and design.Interesting aspects to look for include the time evolution of a system and to investigate if and when a system converges to some absorbing states or stabilizes into a dynamic (and stable) equilibrium and how it performs under such an equilibrium state. Such a formal framework brings in objectivity in systems research, helping discern facts from artefacts as well as providing tools for quantitative evaluation of such systems. This thesis introduces such formalism in analyzing and evaluating peer-to-peer (P2P) systems in order to better understand the dynamics of such systems which in turn helps in better designs. In particular this thesis develops and studies the fundamental building blocks for a P2P storage system. In the process the design and evaluation methodology we pursue illustrate the typical methodological approaches in studying and designing self-organizing systems, and how the analysis methodology influences the design of the algorithms themselves to meet system design goals (preferably with quantifiable guarantees). These goals include efficiency, availability and durability, load-balance, high fault-tolerance and self-maintenance even in adversarial conditions like arbitrarily skewed and dynamic load and high membership dynamics (churn), apart of-course the specific functionalities that the system is supposed to provide. The functionalities we study here are some of the fundamental building blocks for various P2P applications and systems including P2P storage systems, and hence we call them substrates or base infrastructure. These elemental functionalities include: (i) Reliable and efficient discovery of resources distributed over the network in a decentralized manner; (ii) Communication among participants in an address independent manner, i.e., even when peers change their physical addresses; (iii) Availability and persistence of stored objects in the network, irrespective of availability or departure of individual participants from the system at any time; and (iv) Freshness of the objects/resources' (up-to-date replicas). Internet-scale distributed index structures (often termed as structured overlays) are used for discovery and access of resources in a decentralized setting. We propose a rapid construction from scratch and maintenance of the P-Grid overlay network in a self-organized manner so as to provide efficient search of both individual keys as well as a whole range of keys, doing so providing good load-balancing characteristics for diverse kind of arbitrarily skewed loads - storage and replication, query forwarding and query answering loads. For fast overlay construction we employ recursive partitioning of the key-space so that the resulting partitions are balanced with respect to storage load and replication. The proper algorithmic parameters for such partitioning is derived from a transient analysis of the partitioning process which has Markov property. Preservation of ordering information in P-Grid such that queries other than exact queries, like range queries can be efficiently and rather trivially handled makes P-Grid suitable for data-oriented applications. Fast overlay construction is analogous to building an index on a new set of keys making P-Grid suitable as the underlying indexing mechanism for peer-to-peer information retrieval applications among other potential applications which may require frequent indexing of new attributes apart regular updates to an existing index. In order to deal with membership dynamics, in particular changing physical address of peers across sessions, the overlay itself is used as a (self-referential) directory service for maintaining the participating peers' physical addresses across sessions. Exploiting this self-referential directory, a family of overlay maintenance scheme has been designed with lower communication overhead than other overlay maintenance strategies. The notion of dynamic equilibrium study for overlays under continuous churn and repairs, modeled as a Markov process, was introduced in order to evaluate and compare the overlay maintenance schemes. While the self-referential directory was originally invented to realize overlay maintenance schemes with lower overheads than existing overlay maintenance schemes, the self-referential directory is generic in nature and can be used for various other purposes, e.g., as a decentralized public key infrastructure. Persistence of peer identity across sessions, in spite of changes in physical address, provides a logical independence of the overlay network from the underlying physical network. This has many other potential usages, for example, efficient maintenance mechanisms for P2P storage systems and P2P trust and reputation management. We specifically look into the dynamics of maintaining redundancy for storage systems and design a novel lazy maintenance strategy. This strategy is algorithmically a simple variant of existing maintenance strategies which adapts to the system dynamics. This randomized lazy maintenance strategy thus explores the cost-performance trade-offs of the storage maintenance operations in a self-organizing manner. We model the storage system (redundancy), under churn and maintenance, as a Markov process. We perform an equilibrium study to show that the system operates in a more stable dynamic equilibrium with our strategy than for the existing maintenance scheme for comparable overheads. Particularly, we show that our maintenance scheme provides substantial performance gains in terms of maintenance overhead and system's resilience in presence of churn and correlated failures. Finally, we propose a gossip mechanism which works with lower communication overhead than existing approaches for communication among a relatively large set of unreliable peers without assuming any specific structure for their mutual connectivity. We use such a communication primitive for propagating replica updates in P2P systems, facilitating management of mutable content in P2P systems. The peer population affected by a gossip can be modeled as a Markov process. Studying the transient spread of gossips help in choosing proper algorithm parameters to reduce communication overhead while guaranteeing coverage of online peers. Each of these substrates in themselves were developed to find practical solutions for real problems. Put together, these can be used in other applications, including a P2P storage system with support for efficient lookup and inserts, membership dynamics, content mutation and updates, persistence and availability. Many of the ideas have already been implemented in real systems and several others are in the way to be integrated into the implementations. There are two principal contributions of this dissertation. It provides design of the P2P systems which are useful for end-users as well as other application developers who can build upon these existing systems. Secondly, it adapts and introduces the methodology of analysis of a system's time-evolution (tools typically used in diverse domains including physics and cybernetics) to study the long run behavior of P2P systems, and uses this methodology to (re-)design appropriate algorithms and evaluate them. We observed that studying P2P systems from the perspective of complex systems reveals their inner dynamics and hence ways to exploit such dynamics for suitable or better algorithms. In other words, the analysis methodology in itself strongly influences and inspires the way we design such systems. We believe that such an approach of orchestrating self-organization in internet-scale systems, where the algorithms and the analysis methodology have strong mutual influence will significantly change the way future such systems are developed and evaluated. We envision that such an approach will particularly serve as an important tool for the nascent but fast moving P2P systems research and development community

Modelling adaptive routing in Wide Area Networks

Bibliography: leaves 132-138.This study investigates the modelling of adative routing algorithms with specific reference to the algorithm of an existing Wide Area Network (WAN). Packets in the network are routed at each node on the basis of routing tables which contain internal and external delays for each route from the node. The internal delay on a route represents the time that packets queued for transmission will have to wait before being transmitted, while the external delay on a route represents the delay to other nodes via that route. Several modelling methods are investigated and compared for the purpose of identifying the most appropriate and applicable technique. A model of routing in the WAN using an analytic technique is described. The hypothesis of this study is that dynamic routing can be modelled as a sequence of models exhibiting fixed routing. The modelling rationale is that a series of analytic models is run and solved. The routing algorithm of the WAN studied is such that, if viewed at any time instant, the network is one with static routing and no buffer overflow. This characteristic, together with a real time modelling requirement, influences the modelling technique which is applied. Each model represents a routing update interval and a multiclass open queueing network is used to solve the model during a particular interval. Descriptions of the design and implementation of X wan, an X Window based modelling system, are provided. A feature of the modelling system is that it provides a Graphical User Interface (GUI), allowing interactive network specification and the direct observation of network routing through the medium of this interface. Various applications of the modelling system are presented, and overall network behaviour is examined. Experimentation with the routing algorithm is conducted, and (tentative) recommendations are made on ways in which network performance could be improved. A different routing algorithm is also implemented, for the purpose of comparison and to demonstrate the ease with which this can be affected

Enhancing Public Sector Organization Knowledge Retention with Social Network Analysis, Text Mining and Machine Learning

The technical knowledge and expertise possessed by employees are considered amongst an organization’s greatest assets, but are also most vulnerable and can be easily impacted or lost. The loss of experienced employees and important knowledge can put an organization’s competency in great jeopardy. Thus, it is critical to address the challenge of proper knowledge transfer and retention proactively rather than reactively. Public sector organizations have their unique characteristics and are facing emerging HR challenges due to market changes. Most of the current knowledge retention approaches are either outdated and ineffective or developed without considering the features of public sector organizations. A study that overlaps computational and data science techniques with HR data management in light of these features is considered to be a strategic and systematic development that advances existing methods in knowledge retention and overcomes the emerging HR challenges faced by many large public organizations. In the scope of this work, several data tools are studied for their applications to HR databases, with the objectives of enhancing perception on organization-wide attrition risk distribution, identifying critical knowledge at risk of being lost, and choosing the most suitable provider and recipient for a set of knowledge sharing programs. Moreover, an integrated computational system is developed for Georgia DOT. The system uses an existing HR database and provides modular tools to assist HR personnel strategically plan for a range of activities, aiming for increased level of knowledge transfer and lower employee turnover rate, among other benefits. The system is further evaluated by both user experience feedback, as well as a few “use cases” discussed with the end users. The main contributions of this thesis are: 1) This thesis proposes an unprecedented way to transform the classic organizational chart into a more informative network style chart. Several network metrics are developed to inventively describe knowledge management-related attributes of employees; 2) This work develops an innovative approach for systematically and quantitatively evaluating a range of knowledge retention metrics. An inventive workflow is also designed and implemented for conducting various knowledge transfer activities; and 3) A novel computational system, which integrates both existing data tools and the newly developed approach and framework, is designed, developed and deployed at Georgia DOT to assist human resource data management and to enhance organization knowledge retention.Ph.D

The impact of nature of onset of pain and posttraumatic stress on adjustment to chronic pain and treatment outcome

Despite the demonstrated efficacy of cognitive-behavioural therapy for chronic pain, recent research has attempted to identify predictors of treatment outcome in order to improve the effectiveness of such treatments. This research has indicated that variables such as the nature of the onset of the pain and psychopathology are associated with poor adjustment to chronic pain. Accordingly, these variables might also be predictive of poor response to treatment. Individuals who experience a sudden onset of pain following an injury or accident, particularly when the instigating event is experienced as psychologically traumatic, may present for treatment with high levels of distress, including symptoms consistent with a posttraumatic stress response. The impact of this type of onset of pain and posttraumatic stress symptoms on adjustment to chronic pain and treatment outcome is the focus of this thesis. Three studies were conducted to clarify and extend earlier research findings in this area. Using 536 patients referred for treatment in a tertiary referral pain management centre, the first study examined the psychometric properties of a widely used self-report measure of posttraumatic stress symptoms (the PTSD Checklist, or PCL), modified for use in a chronic pain sample. This study provided preliminary support for the suitability of the PCL as a self-report measure of Posttraumatic Stress Disorder (PTSD) symptoms in chronic pain patients. However, the study also highlighted a number of issues with the use of self-report measures of posttraumatic stress symptoms in chronic pain patient samples. In particular, PCL items enquiring about symptoms which are a common aspect of the chronic pain experience (e.g. irritability, sleep problems) appeared to contribute to high mean scores on the PCL Avoidance and Arousal subscales. Furthermore, application of diagnostic cut-off scores and an algorithm recommended for the PCL in other trauma groups suggested that a much larger proportion of the sample was identified as potentially meeting diagnostic criteria for PTSD than would have been expected from previous research. The second study utilised the modified PCL to investigate the impact of different types of onset of pain (e.g. traumatic onset) and posttraumatic stress symptoms on adjustment to chronic pain in a sample of 196 chronic pain patients referred to the same centre. For patients who experienced the onset of pain related to a specific event, two independent experts in the field of PTSD determined whether these events satisfied the definition of a traumatic event according to DSM-IV diagnostic criteria. Adjustment was assessed through a number of validated measures of mood, disability, pain experience, and pain-related cognitions. Contrary to expectations, comparisons between patients who had experienced different types of onset of pain revealed few significant differences between them. That is, analyses comparing patients presenting with accident-related pain, or pain related to other specific events, to patients who had experienced spontaneous or insidious onset of pain revealed no significant differences between the groups on measures of pain severity, pain-related disability, and symptoms of affective distress after adjustment for age, pain duration, and compensation status. Similarly, comparisons between patients who had experienced a potentially traumatic onset of pain with those who had experienced a non-traumatic or spontaneous or insidious onset of pain also revealed no significant differences on the aforementioned variables. In contrast, compensation status, age, and a number of cognitive variables were significant predictors of pain severity, pain-related disability, and depression. The final study investigated the impact of type of pain onset and posttraumatic stress symptoms on response to a multidisciplinary cognitive-behavioural pain management program. Unlike the previous study, this treatment outcome study revealed a number of differences between onset groups. Most notably, patients who had experienced an insidious or spontaneous onset of pain reported greater improvements in pain severity and maintained these improvements more effectively over a one month period than patients who had experienced pain in the context of an accident or other specific incident. There was also limited evidence that improvements in depression favoured patients who had experienced an insidious or spontaneous and non-traumatic onset of pain. Consistent with this, posttraumatic stress symptoms were a significant predictor of treatment outcome, with higher levels of symptoms being associated with smaller improvements in pain-related disability and distress. Notably, this study also revealed that certain cognitive variables (i.e. catastrophising, self-efficacy, and fear-avoidance beliefs) were also significant predictors of treatment outcome, consistent with previous findings in the pain literature. This provided some perspective on the relative roles of both PTSD symptoms and cognitive variables in adjustment to persisting pain and treatment response. These findings were all consistent with expectations and with previous research. Implications for future research and for the assessment and treatment of chronic pain patients who present with posttraumatic stress symptoms are discussed

The impact of nature of onset of pain and posttraumatic stress on adjustment to chronic pain and treatment outcome

Despite the demonstrated efficacy of cognitive-behavioural therapy for chronic pain, recent research has attempted to identify predictors of treatment outcome in order to improve the effectiveness of such treatments. This research has indicated that variables such as the nature of the onset of the pain and psychopathology are associated with poor adjustment to chronic pain. Accordingly, these variables might also be predictive of poor response to treatment. Individuals who experience a sudden onset of pain following an injury or accident, particularly when the instigating event is experienced as psychologically traumatic, may present for treatment with high levels of distress, including symptoms consistent with a posttraumatic stress response. The impact of this type of onset of pain and posttraumatic stress symptoms on adjustment to chronic pain and treatment outcome is the focus of this thesis. Three studies were conducted to clarify and extend earlier research findings in this area. Using 536 patients referred for treatment in a tertiary referral pain management centre, the first study examined the psychometric properties of a widely used self-report measure of posttraumatic stress symptoms (the PTSD Checklist, or PCL), modified for use in a chronic pain sample. This study provided preliminary support for the suitability of the PCL as a self-report measure of Posttraumatic Stress Disorder (PTSD) symptoms in chronic pain patients. However, the study also highlighted a number of issues with the use of self-report measures of posttraumatic stress symptoms in chronic pain patient samples. In particular, PCL items enquiring about symptoms which are a common aspect of the chronic pain experience (e.g. irritability, sleep problems) appeared to contribute to high mean scores on the PCL Avoidance and Arousal subscales. Furthermore, application of diagnostic cut-off scores and an algorithm recommended for the PCL in other trauma groups suggested that a much larger proportion of the sample was identified as potentially meeting diagnostic criteria for PTSD than would have been expected from previous research. The second study utilised the modified PCL to investigate the impact of different types of onset of pain (e.g. traumatic onset) and posttraumatic stress symptoms on adjustment to chronic pain in a sample of 196 chronic pain patients referred to the same centre. For patients who experienced the onset of pain related to a specific event, two independent experts in the field of PTSD determined whether these events satisfied the definition of a traumatic event according to DSM-IV diagnostic criteria. Adjustment was assessed through a number of validated measures of mood, disability, pain experience, and pain-related cognitions. Contrary to expectations, comparisons between patients who had experienced different types of onset of pain revealed few significant differences between them. That is, analyses comparing patients presenting with accident-related pain, or pain related to other specific events, to patients who had experienced spontaneous or insidious onset of pain revealed no significant differences between the groups on measures of pain severity, pain-related disability, and symptoms of affective distress after adjustment for age, pain duration, and compensation status. Similarly, comparisons between patients who had experienced a potentially traumatic onset of pain with those who had experienced a non-traumatic or spontaneous or insidious onset of pain also revealed no significant differences on the aforementioned variables. In contrast, compensation status, age, and a number of cognitive variables were significant predictors of pain severity, pain-related disability, and depression. The final study investigated the impact of type of pain onset and posttraumatic stress symptoms on response to a multidisciplinary cognitive-behavioural pain management program. Unlike the previous study, this treatment outcome study revealed a number of differences between onset groups. Most notably, patients who had experienced an insidious or spontaneous onset of pain reported greater improvements in pain severity and maintained these improvements more effectively over a one month period than patients who had experienced pain in the context of an accident or other specific incident. There was also limited evidence that improvements in depression favoured patients who had experienced an insidious or spontaneous and non-traumatic onset of pain. Consistent with this, posttraumatic stress symptoms were a significant predictor of treatment outcome, with higher levels of symptoms being associated with smaller improvements in pain-related disability and distress. Notably, this study also revealed that certain cognitive variables (i.e. catastrophising, self-efficacy, and fear-avoidance beliefs) were also significant predictors of treatment outcome, consistent with previous findings in the pain literature. This provided some perspective on the relative roles of both PTSD symptoms and cognitive variables in adjustment to persisting pain and treatment response. These findings were all consistent with expectations and with previous research. Implications for future research and for the assessment and treatment of chronic pain patients who present with posttraumatic stress symptoms are discussed