Statistic Rate Monotonic Scheduling

In this paper we present Statistical Rate Monotonic Scheduling (SRMS), a generalization of the classical RMS results of Liu and Layland that allows scheduling periodic tasks with highly variable execution times and statistical QoS requirements. Similar to RMS, SRMS has two components: a feasibility test and a scheduling algorithm. The feasibility test for SRMS ensures that using SRMS' scheduling algorithms, it is possible for a given periodic task set to share a given resource (e.g. a processor, communication medium, switching device, etc.) in such a way that such sharing does not result in the violation of any of the periodic tasks QoS constraints. The SRMS scheduling algorithm incorporates a number of unique features. First, it allows for fixed priority scheduling that keeps the tasks' value (or importance) independent of their periods. Second, it allows for job admission control, which allows the rejection of jobs that are not guaranteed to finish by their deadlines as soon as they are released, thus enabling the system to take necessary compensating actions. Also, admission control allows the preservation of resources since no time is spent on jobs that will miss their deadlines anyway. Third, SRMS integrates reservation-based and best-effort resource scheduling seamlessly. Reservation-based scheduling ensures the delivery of the minimal requested QoS; best-effort scheduling ensures that unused, reserved bandwidth is not wasted, but rather used to improve QoS further. Fourth, SRMS allows a system to deal gracefully with overload conditions by ensuring a fair deterioration in QoS across all tasks---as opposed to penalizing tasks with longer periods, for example. Finally, SRMS has the added advantage that its schedulability test is simple and its scheduling algorithm has a constant overhead in the sense that the complexity of the scheduler is not dependent on the number of the tasks in the system. We have evaluated SRMS against a number of alternative scheduling algorithms suggested in the literature (e.g. RMS and slack stealing), as well as refinements thereof, which we describe in this paper. Consistently throughout our experiments, SRMS provided the best performance. In addition, to evaluate the optimality of SRMS, we have compared it to an inefficient, yet optimal scheduler for task sets with harmonic periods.

From Synapse to Self: Spikes, Synchrony, and Attentive Learning by Laminar Thalamocortical Circuits

How do our brains transform the "blooming buzzing confusion" of daily experience into a coherent sense of self that can learn and selectively attend to important information? How do local signals at multiple processing stages, none of which has a global view of brain dynamics or behavioral outcomes, trigger learning at multiple synaptic sites when appropriate, and prevent learning when inappropriate, to achieve useful behavioral goals in a continually changing world? How does the brain allow synaptic plasticity at a remarkably rapid rate, as anyone who has gone to an exciting movie is readily aware, yet also protect useful memories from catastrophic forgetting? A neural model provides a unified answer by explaining and quantitatively simulating data about single cell biophysics and neurophysiology, laminar neuroanatomy, aggregate cell recordings (current-source densities, local field potentials), large-scale oscillations (beta, gamma), and spike-timing dependent plasticity, and functionally linking them all to cognitive information processing requirements.

Store Working Memory Networks for Storage and Recall of Arbitrary Temporal Sequences

Neural network models of working memory, called Sustained Temporal Order REcurrent (STORE) models, are described. They encode the invariant temporal order of sequential events in short term memory (STM) in a way that mimics cognitive data about working memory, including primacy, recency, and bowed order and error gradients. As new items are presented, the pattern of previously stored items is invariant in the sense that, relative activations remain constant through time. This invariant temporal order code enables all possible groupings of sequential events to be stably learned and remembered in real time, even as new events perturb the system. Such a competence is needed to design self-organizing temporal recognition and planning systems in which any subsequence of events may need to be categorized in order to to control and predict future behavior or external events. STORE models show how arbitrary event sequences may be invariantly stored, including repeated events. A preprocessor interacts with the working memory to represent event repeats in spatially separate locations. It is shown why at least two processing levels are needed to invariantly store events presented with variable durations and interstimulus intervals. It is also shown how network parameters control the type and shape of primacy, recency, or bowed temporal order gradients that will be stored.

Trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms: a model-based framework

Evaluation of temperature distribution in cold rooms is an important consideration in the design of food storage solutions. Two common approaches used in both industry and academia to address this question are the deployment of wireless sensors, and modelling with Computational Fluid Dynamics (CFD). However, for a realworld evaluation of temperature distribution in a cold room, both approaches have their limitations. For wireless sensors, it is economically unfeasible to carry out large-scale deployment (to obtain a high resolution of temperature distribution); while with CFD modelling, it is usually not accurate enough to get a reliable result. In this paper, we propose a model-based framework which combines the wireless sensors technique with CFD modelling technique together to achieve a satisfactory trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms. A case study is presented to demonstrate the usability of the framework.

Understanding student stress: a qualitative study of the stress experienced by third level students

Stress can be understood in terms of the meaning of stressful experiences for individuals. The meaning of stressful experiences involves threats to self-adequacy, where self-adequacy is considered a basic human need. Appropriate research methods are required to explore this aspect of stress. The present study is a qualitative exploration of the stress experienced by a group of 27 students at the National Institute of Higher Education, Limerick (since renamed the University of Limerick). The study was carried out by the resident student counsellor at the college. A model of student stress was explored, based on student developmental needs. The data consist of a series of interviews recorded with each of the 27 students over a 3 month period. These interviews were transcribed and the resulting transcripts are the subject of detailed analysis. The analysis of the data is an account of the sense-making process by the student counsellor of the students' reported experiences. The aim of the analysis was to reduce the large amounts of data to their most salient aspects in an ordered fashion, so as to examine the application of a developmental model of stress with this group of students. There were two key elements to the analysis. First, the raw data were edited to identify the key statements contained in the interviews. Second, the statements were categorised, as a means of summarising the data. The results of the qualitative dataanalysis were then applied to the developmental model. The analysis of data revealed a number of patterns of stress amongst the sample of students. Patterns of academic over-identification, parental conflict and social inadequacy were particularly noteworthy. These patterns consisted of an integration of academic, family and social stresses within a developmental framework. Gender differences with regard to the need for separateness and belonging are highlighted. Appropriate student stress intervention strategies are discussed. Based on the present results, the relationship between stress and development has been highlighted and is recommended as a firm basis for future studies of stress in general and student stress in particular.

Community workers' understandings and practices of resistance

This research is focused on Community Workers located in Southern Ireland, and their understandings and practices of resistance. It is an attempt to explore the ways in which community workers’ understandings and practices of resistance are formed and, in turn, inform their sense of identity and their responses to the wider context of community development work in Ireland today. This study is specifically located but also has wider application and relevance because of the extended international reach of neo-liberal and managerial rationalities, and their implications for politics, policy and practice. The study considers resistance in a number of inter-related ways: as a collective oppositional position (with negative and positive dimensions); a personal and/or professional value (associated with the ‘expansion of contention’); a strategy for negotiating unequal power relations (in a range of levels and spaces of power); an identity (in relation to the sustaining of ‘reflexive subjectivities’); a set of practices, (which take into account the interplay between economic, political and cultural influences); and an educational process through which practitioners assess and enact personal and professional agency. Critical theorisations of community development and of the Irish state over time, trace the ways in which neo-liberalism and managerialism has inflected community development practice and the positions of community workers and communities in that process. The study draws on James C. Scott, Gramsci, Barnes and Prior, among others, which enabled the interrogation of resistance in relation to everyday practices through engaging with ‘hidden transcripts’ and spaces. The method chosen was focus group discussions with three groups of community workers located in different counties in Southern Ireland. This method facilitated a deep discourse analysis of practitioners’ encounters with resistance in the field of community work. Key findings relate to the various interpretations of the role of resistance, practices of resistance (including current restrictions), the value of resistance work and the conditions that may be conducive to practising resistance.

Public evaluations of novel food technologies: a qualitative citizen-scientist deliberative discourse approach

This qualitative research expands understanding of how information about a range of Novel Food Technologies (NFTs) is used and assimilated, and the implications of this on the evolution of attitudes and acceptance. This work enhances theoretical and applied understanding of citizens’ evaluative processes around these technologies. The approach applied involved observations of interactive exchanges between citizens and information providers (i.e. food scientists), during which they discussed a specific technology. This flexible, yet structured, approach revealed how individuals construct meaning around information about specific NFTs. A rich dataset of 42 ‘deliberate discourse’ and 42 postdiscourse transcripts was collected. Data analysis encompassed three stages: an initial descriptive account of the complete dataset based on the top-down bottom-up (TDBU) model of attitude formation, followed by inductive and deductive thematic analysis across the selected technology groups. The hybrid thematic analysis undertaken identified a Conceptual Model, which represents a holistic perspective on the influences and associated features directing ‘sense-making’ and ultimate evaluations around the technology clusters. How individuals make sense of these technologies is shaped by: their beliefs, values and personal characteristics; their perceptions of power and control over the application of the technology; and, the assumed relevance of the technology and its applications within different contexts. These influences form the frame for the creation of sense-making around the technologies. Internal negotiations between these influences are evident and evaluations are based on the relative importance of each influence to the individual, which tend to contribute to attitude ambivalence and instability. The findings indicate the processes of forming and changing attitudes towards these technologies are: complex; dependent on characteristics of the individual, technology, application and product; and, impacted by the nature and forms of information provided. Challenges are faced in engaging with the public about these technologies, as levels of knowledge, understanding and interest vary.

A river of memory: landscape, narrative and identity in the Lee Valley, Co. Cork, Ireland

In moments of rapid social changes, as has been witnessed in Ireland in the last decade, the conditions through which people engage with their localities though memory, individually and collectively, remains an important cultural issue with key implications for questions of heritage, preservation and civic identity. In recent decades, cultural geographers have argued that landscape is more than just a view or a static text of something symbolic. The emphasis seems to be on landscape as a dynamic cultural process – an ever-evolving process being constructed and re-constructed. Hence, landscape seems to be a highly complex term that carries many different meanings. Material, form, relationships or actions have different meanings in different settings. Drawing upon recent and continuing scholarly debates in cultural landscapes and collective memory, this thesis sets out to examine the generation of collective memory and how it is employed as a cultural tool in the production of memory in the landscape. More specifically, the research considers the relationships between landscape and memory, investigating the ways in which places are produced, appropriated, experienced, sensed, acknowledged, imagined, yearned for, appropriated, re-appropriated, contested and identified with. A polyvocal-bricoleur approach aims to get below the surface of a cultural landscape, inject historical research and temporal depth into cultural landscape studies and instil a genuine sense of inclusivity of a wide variety of voices (role of monuments and rituals and voices of people) from the past and present. The polyvocal-bricoleur approach inspires a mixed method methodology approach to fieldsites through archival research, fieldwork and filmed interviews. Using a mixture of mini-vignettes of place narratives in the River Lee valley in the south of Ireland, the thesis explores a number of questions on the fluid nature of narrative in representing the story and role of the landscape in memory-making. The case studies in the Lee Valley are harnessed to investigate the role of the above questions/ themes/ debates in the act of memory making at sites ranging from an Irish War of Independence memorial to the River Lee’s hydroelectric scheme to the valley’s key religious pilgrimage site. The thesis investigates the idea that that the process of landscape extends not only across space but also across time – that the concept of historical continuity and the individual and collective human engagement and experience of this continuity are central to the processes of remembering on the landscape. In addition the thesis debates the idea that the production of landscape is conditioned by several social frames of memory – that individuals remember according to several social frames that give emphasis to different aspects of the reality of human experience. The thesis also reflects on how the process of landscape is represented by those who re-produce its narratives in various media.

Keeping their heads down: Shame and pride in the stories of Protestants in the Irish Republic

This study draws on a number of in-depth interviews to explore the ethnic aspect of Protestantism in the Republic of Ireland. We explore themes of shame and pride around issues of identity, together with a sense of loss of a minority rapidly losing cultural distinctiveness. Following Ireland‘s division, the ordinary Protestants of the south, comprising a range of religious denominations bound by history, intermarriage and culture, found themselves in a society in which their story was rarely told. The dominant narrative was one of a Catholic people, long oppressed by a wealthy Protestant minority. The story of ordinary Protestants, including those in rural and urban poverty, went largely unheard. Today, ordinary Protestants – small farmers, shop keepers, housewives – tell the story of Ireland as seen through their family‘s narratives. Themes of pride and shame, often intertwined, form a thread that binds their testimony, drawing on family, personal and local history, folklore and statements of identity.

Sensitive detection of H2S using gold nanoparticle decorated single-walled carbon nanotubes.

Herein, we demonstrate that highly sensitive conductometric gas nanosensors for H(2)S can be synthesized by electrodepositing gold nanoparticles on single-walled carbon nanotube (SWNT) networks. Adjusting the electrodeposition conditions allowed for tuning of the size and number of gold nanoparticles deposited. The best H(2)S sensing performance was obtained with discrete gold nanodeposits rather than continuous nanowires. The gas nanosensors could sense H(2)S in air at room temperature with a 3 ppb limit of detection. The sensors were reversible, and increasing the bias voltage reduced the sensor recovery time, probably by local Joule heating. The sensing mechanism is believed to be based on the modulation of the conduction path across the nanotubes emanating from the modulation of electron exchange between the gold and carbon nanotube defect sites when exposed to H(2)S.

Making sense of health information technology implementation: A qualitative study protocol.

BACKGROUND: Implementing new practices, such as health information technology (HIT), is often difficult due to the disruption of the highly coordinated, interdependent processes (e.g., information exchange, communication, relationships) of providing care in hospitals. Thus, HIT implementation may occur slowly as staff members observe and make sense of unexpected disruptions in care. As a critical organizational function, sensemaking, defined as the social process of searching for answers and meaning which drive action, leads to unified understanding, learning, and effective problem solving -- strategies that studies have linked to successful change. Project teamwork is a change strategy increasingly used by hospitals that facilitates sensemaking by providing a formal mechanism for team members to share ideas, construct the meaning of events, and take next actions. METHODS: In this longitudinal case study, we aim to examine project teams' sensemaking and action as the team prepares to implement new information technology in a tiertiary care hospital. Based on management and healthcare literature on HIT implementation and project teamwork, we chose sensemaking as an alternative to traditional models for understanding organizational change and teamwork. Our methods choices are derived from this conceptual framework. Data on project team interactions will be prospectively collected through direct observation and organizational document review. Through qualitative methods, we will identify sensemaking patterns and explore variation in sensemaking across teams. Participant demographics will be used to explore variation in sensemaking patterns. DISCUSSION: Outcomes of this research will be new knowledge about sensemaking patterns of project teams, such as: the antecedents and consequences of the ongoing, evolutionary, social process of implementing HIT; the internal and external factors that influence the project team, including team composition, team member interaction, and interaction between the project team and the larger organization; the ways in which internal and external factors influence project team processes; and the ways in which project team processes facilitate team task accomplishment. These findings will lead to new methods of implementing HIT in hospitals.

Genome-wide scan of copy number variation in late-onset Alzheimer's disease.

Alzheimer's disease is a complex and progressive neurodegenerative disease leading to loss of memory, cognitive impairment, and ultimately death. To date, six large-scale genome-wide association studies have been conducted to identify SNPs that influence disease predisposition. These studies have confirmed the well-known APOE epsilon4 risk allele, identified a novel variant that influences disease risk within the APOE epsilon4 population, found a SNP that modifies the age of disease onset, as well as reported the first sex-linked susceptibility variant. Here we report a genome-wide scan of Alzheimer's disease in a set of 331 cases and 368 controls, extending analyses for the first time to include assessments of copy number variation. In this analysis, no new SNPs show genome-wide significance. We also screened for effects of copy number variation, and while nothing was significant, a duplication in CHRNA7 appears interesting enough to warrant further investigation.

The cost of biopharmaceutical R&D: Is biotech different?

The costs of developing the types of new drugs that have been pursued by traditional pharmaceutical firms have been estimated in a number of studies. However, similar analyses have not been published on the costs of developing the types of molecules on which biotech firms have focused. This study represents a first attempt to get a sense for the magnitude of the R&D costs associated with the discovery and development of new therapeutic biopharmaceuticals (specifically, recombinant proteins and monoclonal antibodies [mAbs]). We utilize drug-specific data on cash outlays, development times, and success in obtaining regulatory marketing approval to estimate the average pre-tax R&D resource cost for biopharmaceuticals up to the point of initial US marketing approval (in year 2005 dollars). We found average out-of-pocket (cash outlay) cost estimates per approved biopharmaceutical of $198 million, $361 million, and $559 million for the preclinical period, the clinical period, and in total, respectively. Including the time costs associated with biopharmaceutical R&D, we found average capitalized cost estimates per approved biopharmaceutical of $615 million, $626 million, and $1241 million for the preclinical period, the clinical period, and in total, respectively. Adjusting previously published estimates of R&D costs for traditional pharmaceutical firms by using past growth rates for pharmaceutical company costs to correspond to the more recent period to which our biopharmaceutical data apply, we found that total out-of-pocket cost per approved biopharmaceutical was somewhat lower than for the pharmaceutical company data ($559 million vs $672 million). However, estimated total capitalized cost per approved new molecule was nearly the same for biopharmaceuticals as for the adjusted pharmaceutical company data ($1241 million versus $1318 million). The results should be viewed with some caution for now given a limited number of biopharmaceutical molecules with data on cash outlays, different therapeutic class distributions for biopharmaceuticals and for pharmaceutical company drugs, and uncertainty about whether recent growth rates in pharmaceutical company costs are different from immediate past growth rates. Copyright © 2007 John Wiley & Sons, Ltd.

Ambient aerosol size distributions and number concentrations measured during the Pittsburgh Air Quality Study (PAQS)

Twelve months of aerosol size distributions from 3 to 560nm, measured using scanning mobility particle sizers are presented with an emphasis on average number, surface, and volume distributions, and seasonal and diurnal variation. The measurements were made at the main sampling site of the Pittsburgh Air Quality Study from July 2001 to June 2002. These are supplemented with 5 months of size distribution data from 0.5 to 2.5μm measured with a TSI aerosol particle sizer and 2 months of size distributions measured at an upwind rural sampling site. Measurements at the main site were made continuously under both low and ambient relative humidity. The average Pittsburgh number concentration (3-500nm) is 22,000cm-3 with an average mode size of 40nm. Strong diurnal patterns in number concentrations are evident as a direct effect of the sources of particles (atmospheric nucleation, traffic, and other combustion sources). New particle formation from homogeneous nucleation is significant on 30-50% of study days and over a wide area (at least a hundred kilometers). Rural number concentrations are a factor of 2-3 lower (on average) than the urban values. Average measured distributions are different from model literature urban and rural size distributions. © 2004 Elsevier Ltd. All rights reserved.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.