Gimmelife : listening for dialogic voices in the email self-narratives of gifted young adolescents

The art of listening for voices within narrative research is a positive endeavour that has specific value within research design and subsequent approaches to analysis. This paper details an investigation into the dialogic nature of voices among gifted young adolescents who engaged in the co-construction of email-generated self-narratives. Data are drawn from a study involving ten adolescents, aged between ten and fourteen years, diagnosed as gifted according to Australian guidelines. Individual participants were asked to produce self-managed journal entries written and sent as asynchronous emails to the researcher who was the sole recipient and respondent. Within this approach, specific techniques of listening were used to examine a series of multi-vocal narratives generated over a period of six months. This paper proposes that an adaptation of the everyday convenience of email with the traditional journal format as a self-report mechanism creates a synergy that fosters self-disclosure. Individual excerpts are presented to show that the harnessing of personal narratives within an email context has potential to yield valuable insights into the emotions, personal realities and experiences of gifted young adolescents. Furthermore, the co-construction of self-expressive and explanatory narratives supported by a facilitative adult listener appeared to promote healthy self-awareness amongst participants. This paper contributes to narrative exploration in two distinct ways: first, in using online methods for gaining access to the everyday, emotional realities of participants; and, second, in demonstrating the value of listening as a narrative technique for uncovering layers of voices across a body of texts produced over time. These methods represent an innovative attempt to move beyond face-to-face approaches and away from a focus on content and coding techniques that might oversimplify complex emotions.

Notch and NOXA-related pathways in melanoma cells

Notch receptor-mediated intracellular events represent an ancient cell signaling system, and alterations in Notch expression are associated with various malignancies in which Notch may function as an oncogene or less commonly as a tumor suppressor. Notch signaling regulates cell fate decisions in the epidermis, including influencing stem cell dynamics and growth/differentiation control of cells in skin. Because of increasing evidence that the Notch signaling network is deregulated in human malignancies, Notch receptors have become attractive targets for selective killing of malignant cells. Compared with proliferating normal human melanocytes, melanoma cell lines are characterized by markedly enhanced levels of activated Notch-1 receptor. By using a small molecule gamma-secretase inhibitor (GSI) consisting of a tripeptide aldehyde, N-benzyloxycarbonyl-Leu-Leu-Nle-CHO, which can block processing and activation of all four different Notch receptors, we identified a specific apoptotic vulnerability in melanoma cells. GSI triggers apoptosis in melanoma cells, but only G2/M growth arrest in melanocytes without subsequent cell death. Moreover, GSI treatment induced a pro-apoptotic BH3-only protein, NOXA, in melanoma cells but not in normal melanocytes. The use of GSI to induce NOXA induction overcomes the apoptotic resistance of melanoma cells, which commonly express numerous cell survival proteins such as Mcl-1, Bcl-2, and survivin. Taken together, these results highlight the concept of synthetic lethality in which exposure to GSI, in combination with melanoma cells overexpressing activated Notch receptors, has lethal consequences, producing selective killing of melanoma cells, while sparing normal melanocytes. By identifying signaling pathways that contribute to the transformation of melanoma cells (e.g. Notch signaling), and anti-cancer agents that achieve tumor selectivity (e.g., GSI-induced NOXA), this experimental approach provides a useful framework for future therapeutic strategies in cutaneous oncology.

Juvenile justice and truancy legislation : The move towards parental responsibilisation in Queensland

Much current Queensland media rhetoric, government policy and legislation on truancy and youth justice appears to be based on ideas of responsibilisation – of sheeting responsibility for children’s behaviour back onto their parents. This article examines the evidence of parental responsibility provisions in juvenile justice and truancy legislation in Queensland and the drivers behind this approach. It considers recent legislative initiatives as part of an international trend toward making parents ‘responsible’ for the wrongs of their children. It identifies the parental responsibility rhetoric appearing in recent ministerial statements and associated media reports. It then asks the questions – are these legislative provisions being enforced? And if so, are they successful? Are they simply adding to the administrative burdens placed on teachers and schools, and the socioeconomic burdens placed on already disadvantaged parents? Parental responsibility provisions have been discussed at length in the context of juvenile offending and research suggests that punishing parents for the acts of their children does not decrease delinquency. The paper asks how, as a society, we intend to evaluate these punitive measures against parents?

Work-Related Subjective Experiences, Work-Related Self-Efficacy, and Career Learning Among People with Psychiatric Disabilities

Work-related subjective experiences and work-related self-efficacy were investigated as candidate correlates of career learning among people with schizophrenia and schizoaffective disorder. Work-related self-efficacy was expected to mediate any observed relationship between work-related subjective experiences and employment status, after controlling for demographic, vocational, and clinical covariates. Baseline measures (n 1 = 104) were repeated at six months (n 2 = 94) and 12 months (n 3 = 94). Work-related subjective experiences and work-related self-efficacy were consistently associated with current employment after controlling for covariates. The proposed mediator role of work-related self-efficacy remains a viable hypothesis requiring further investigation. Both work-related subjective experiences and work-related self-efficacy appear promising as components of the social cognitive career learning theory to help explain career development among people with psychiatric disabilities.

Classifying Socially-Valued Role Functioning Among Community Residents with Psychiatric Disorders

An increased emphasis on community-based care has not ensured that people recovering from psychiatric disorders return to active and valued roles in their local communities. Although clinical recovery remains a priority for mental health services there is increasing recognition of the need for functional recovery to be attained and demonstrated in roles valued by the wider community. With this need in mind, a method for classifying socially-valued role functioning among people with schizophrenia or schizoaffective disorder was developed and trialed. Participants (n = 104) were recruited via mental health, psychosocial rehabilitation, and other community support services. Socially-valued roles were investigated via participation in five categories: (1) self-care and home duties; (2) caring for others; (3) self-development, voluntary work or rehabilitation; (4) formal education or training; and (5) employment. Activities were classified by primary role type and role status level at baseline, six, and 12 months. Current role status was assessed along with highest and lowest status in the previous year. Preliminary psychometric results were favorable. Research applications are now recommended for monitoring socially-valued role functioning in community settings.

Work-related self-efficacy among community residents with psychiatric disabilities

A new measure of work-related self-efficacy for people with psychiatric disabilities is reported. The 37-item scale measures self-efficacy in four relevant activity domains: 1) vocational service access and career planning, 2) job acquisition, 3) work-related social skills, and 4) general work skills. The scale was developed in a 12-month longitudinal survey of urban residents diagnosed with schizophrenia or schizoaffective disorder (n = 104). Results indicate validity of both a four-factor structure differentiating four core skill domains, and a single factor representing total work-related self-efficacy. The favorable psychometric properties support further research and trial applications in supported employment and psychiatric vocational rehabilitation.

Work-related subjective experiences among community residents with schizophrenia or schizoaffective disorder

Objective: To develop a self-report scale of subjective experiences of illness perceived to impact on employment functioning, as an alternative to a diagnostic perspective, for anticipating the vocational assistance needs of people with schizophrenia or schizoaffective disorders. Method: A repeated measures pilot study (n1 = 26, n2 = 21) of community residents with schizophrenia identified a set of work-related subjective experiences perceived to impact on employment functioning. Items with the best psychometric properties were applied in a 12 month longitudinal survey of urban residents with schizophrenia or schizoaffective disorder (n1 = 104; n2 = 94; n3 = 94). Results: Construct validity, factor structure, responsiveness, internal consistency, stability, and criterion validity investigations produced favourable results. Work-related subjective experiences provide information about the intersection of the person, the disorder, and expectations of employment functioning, which suggest new opportunities for vocational professionals to explore and discuss individual assistance needs. Conclusion: Further psychometric investigations of test-retest reliability, discriminant and predictive validity, and research applications in supported employment and vocational rehabilitation, are recommended. Subject to adequate psychometric properties, the new measure promises to facilitate exploring: individuals' specific subjective experiences; how each is perceived to contribute to employment restrictions; and the corresponding implications for specialized treatment, vocational interventions and workplace accommodations.

Quantification of particle emission characteristics and development of an emission model for use in transport microenvironments affected by traffic emissions

Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.

Scene invariant crowd counting and crowd occupancy analysis

In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

Trading spaces : on the lore and limitations of latent semantic analysis

Two decades after its inception, Latent Semantic Analysis(LSA) has become part and parcel of every modern introduction to Information Retrieval. For any tool that matures so quickly, it is important to check its lore and limitations, or else stagnation will set in. We focus here on the three main aspects of LSA that are well accepted, and the gist of which can be summarized as follows: (1) that LSA recovers latent semantic factors underlying the document space, (2) that such can be accomplished through lossy compression of the document space by eliminating lexical noise, and (3) that the latter can best be achieved by Singular Value Decomposition. For each aspect we performed experiments analogous to those reported in the LSA literature and compared the evidence brought to bear in each case. On the negative side, we show that the above claims about LSA are much more limited than commonly believed. Even a simple example may show that LSA does not recover the optimal semantic factors as intended in the pedagogical example used in many LSA publications. Additionally, and remarkably deviating from LSA lore, LSA does not scale up well: the larger the document space, the more unlikely that LSA recovers an optimal set of semantic factors. On the positive side, we describe new algorithms to replace LSA (and more recent alternatives as pLSA, LDA, and kernel methods) by trading its l2 space for an l1 space, thereby guaranteeing an optimal set of semantic factors. These algorithms seem to salvage the spirit of LSA as we think it was initially conceived.

An effective approach to verbose queries using a limited dependencies language model

Intuitively, any ‘bag of words’ approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distributions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document’s initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur’s search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.

On forward secrecy in one-round key exchange

Most one-round key exchange protocols provide only weak forward secrecy at best. Furthermore, one-round protocols with strong forward secrecy often break badly when faced with an adversary who can obtain ephemeral keys. We provide a characterisation of how strong forward secrecy can be achieved in one-round key exchange. Moreover, we show that protocols exist which provide strong forward secrecy and remain secure with weak forward secrecy even when the adversary is allowed to obtain ephemeral keys. We provide a compiler to achieve this for any existing secure protocol with weak forward secrecy.

Overview of the INEX 2009 Link the Wiki Track

In the third year of the Link the Wiki track, the focus has been shifted to anchor-to-bep link discovery. The participants were encouraged to utilize different technologies to resolve the issue of focused link discovery. Apart from the 2009 Wikipedia collection, the Te Ara collection was introduced for the first time in INEX. For the link the wiki tasks, 5000 file-to-file topics were randomly selected and 33 anchor-to-bep topics were nominated by the participants. The Te Ara collection does not contain hyperlinks and the task was to cross link the entire collection. A GUI tool for self-verification of the linking results was distributed. This helps participants verify the location of the anchor and bep. The assessment tool and the evaluation tool were revised to improve efficiency. Submission runs were evaluated against Wikipedia ground-truth and manual result set respectively. Focus-based evaluation was undertaken using a new metric. Evaluation results are presented and link discovery approaches are described

Overview of the INEX 2009 Ad Hoc Track

This paper gives an overview of the INEX 2009 Ad Hoc Track. The main goals of the Ad Hoc Track were three-fold. The first goal was to investigate the impact of the collection scale and markup, by using a new collection that is again based on a the Wikipedia but is over 4 times larger, with longer articles and additional semantic annotations. For this reason the Ad Hoc track tasks stayed unchanged, and the Thorough Task of INEX 2002–2006 returns. The second goal was to study the impact of more verbose queries on retrieval effectiveness, by using the available markup as structural constraints—now using both the Wikipedia’s layout-based markup, as well as the enriched semantic markup—and by the use of phrases. The third goal was to compare different result granularities by allowing systems to retrieve XML elements, ranges of XML elements, or arbitrary passages of text. This investigates the value of the internal document structure (as provided by the XML mark-up) for retrieving relevant information. The INEX 2009 Ad Hoc Track featured four tasks: For the Thorough Task a ranked-list of results (elements or passages) by estimated relevance was needed. For the Focused Task a ranked-list of non-overlapping results (elements or passages) was needed. For the Relevant in Context Task non-overlapping results (elements or passages) were returned grouped by the article from which they came. For the Best in Context Task a single starting point (element start tag or passage start) for each article was needed. We discuss the setup of the track, and the results for the four tasks.