956 resultados para Low Speed.


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In a study of socioeconomically disadvantaged children's acquisition of school literacies, a university research team investigated how a group of teachers negotiated critical literacies and explored notions of social power with elementary children in a suburban school located in an area of high poverty. Here we focus on a grade 2/3 classroom where the teacher and children became involved in a local urban renewal project and on how in the process the children wrote about place and power. Using the students' concerns about their neighborhood, the teacher engaged her class in a critical literacy project that not only involved a complex set of literate practices but also taught the children about power and the possibilities for local civic action. In particular, we discuss examples of children's drawing and writing about their neighborhoods and their lives. We explore how children's writing and drawing might be key elements in developing "critical literacies" in elementary school settings. We consider how such classroom writing can be a mediator of emotions, intellectual and academic learning, social practice, and political activism.

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The research explores how community participation can address affordable housing problems of the poor in Dhaka. The research, based on extensive interviews, community focus groups and household surveys in different Dhaka slums, identifies the limiting factors to promote community participation in affordable housing creation. In Dhaka housing options for poor are currently limited to affordable shelters in informal settlements. Public housing programs have failed to reach the poor and meet affordability levels due to a number of factors including lack of beneficiary participation. Beneficiary participation, though widely recognized for success in housing initiatives, often deteriorates in process of implementation into mere involvement, not reflecting community needs and aspirations and thus failing to meet its core objectives. This research identified the most significant impediments as well as opportunities to advance participation in their own housing provisions in Dhaka city.

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Two studies documented the “David and Goliath” rule—the tendency for people to perceive criticism of “David” groups (groups with low power and status) as less normatively permissible than criticism of “Goliath” groups (groups with high power and status). The authors confirmed the existence of the David and Goliath rule across Western and Chinese cultures (Study 1). However, the rule was endorsed more strongly in Western than in Chinese cultures, an effect mediated by cultural differences in power distance. Study 2 identified the psychological underpinnings of this rule in an Australian sample. Lower social dominance orientation (SDO) was associated with greater endorsement of the rule, an effect mediated through the differential attribution of stereotypes. Specifically, those low in SDO were more likely to attribute traits of warmth and incompetence to David versus Goliath groups, a pattern of stereotypes that was related to the protection of David groups from criticism.

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As news communication speeds up, investigative journalists have an increasing responsibility to minimise the risk of harm to vulnerable news sources. In addition, the increased longevity and instant global search-ability of news coverage and investigative journalism outputs such as documentaries, places upon journalists an increased responsibility for accuracy since online coverage cannot be easily corrected or retracted. This paper will examine how the risks to a news source and her family were considered and mitigated during the production of a radio documentary and newspaper story about an intended victim of child sacrifice. Pre-publication considerations included the possible risks to the mental health of the news source, the potential physical risk to her children and the risk to future family relationships. To hear the ABC Radio National documentary, A living sacrifice, on 360 Documentaries prior to the conference, see http://www.abc.net.au/radionational/programs/360/a-living-sacrifice/5359744. To read the Sunday Mail newspaper coverage of the story see http://www.couriermail.com.au/news/queensland/susannah-birch-talks-about-her-throat-being-slit-by-her-mother-when-she-was-a-baby/story-fnihsrf2-1226881911465.

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Nanotubes and nanosheets are low-dimensional nanomaterials with unique properties that can be exploited for numerous applications. This book offers a complete overview of their structure, properties, development, modeling approaches, and practical use. It focuses attention on boron nitride (BN) nanotubes, which have had major interest given their special high-temperature properties, as well as graphene nanosheets, BN nanosheets, and metal oxide nanosheets. Key topics include surface functionalization of nanotubes for composite applications, wetting property changes for biocompatible environments, and graphene for energy storage applications

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Typically, the walking ability of individuals with a transfemoral amputation (TFA) can be represented by the speed of walking (SofW) obtained in experimental settings. Recent developments in portable kinetic systems allow assessing the level of activity of TFA during actual daily living outside the confined space of a gait lab. Unfortunately, only minimal spatio-temporal characteristics could be extracted from the kinetic data including the cadence and the duration on gait cycles. Therefore, there is a need for a way to use some of these characteristics to assess the instantaneous speed of walking during daily living. The purpose of the study was to compare several methods to determine SofW using minimal spatial gait characteristics.

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Background The expression of biomass-degrading enzymes (such as cellobiohydrolases) in transgenic plants has the potential to reduce the costs of biomass saccharification by providing a source of enzymes to supplement commercial cellulase mixtures. Cellobiohydrolases are the main enzymes in commercial cellulase mixtures. In the present study, a cellobiohydrolase was expressed in transgenic corn stover leaf and assessed as an additive for two commercial cellulase mixtures for the saccharification of pretreated sugar cane bagasse obtained by different processes. Results Recombinant cellobiohydrolase in the senescent leaves of transgenic corn was extracted using a simple buffer with no concentration step. The extract significantly enhanced the performance of Celluclast 1.5 L (a commercial cellulase mixture) by up to fourfold on sugar cane bagasse pretreated at the pilot scale using a dilute sulfuric acid steam explosion process compared to the commercial cellulase mixture on its own. Also, the extracts were able to enhance the performance of Cellic CTec2 (a commercial cellulase mixture) up to fourfold on a range of residues from sugar cane bagasse pretreated at the laboratory (using acidified ethylene carbonate/ethylene glycol, 1-butyl-3-methylimidazolium chloride, and ball-milling) and pilot (dilute sodium hydroxide and glycerol/hydrochloric acid steam explosion) scales. We have demonstrated using tap water as a solvent (under conditions that mimic an industrial process) extraction of about 90% recombinant cellobiohydrolase from senescent, transgenic corn stover leaf that had minimal tissue disruption. Conclusions The accumulation of recombinant cellobiohydrolase in senescent, transgenic corn stover leaf is a viable strategy to reduce the saccharification cost associated with the production of fermentable sugars from pretreated biomass. We envisage an industrial-scale process in which transgenic plants provide both fibre and biomass-degrading enzymes for pretreatment and enzymatic hydrolysis, respectively.

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In this paper we present a new method for performing Bayesian parameter inference and model choice for low count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel pseudo-marginal algorithm, which we refer to as alive SMC^2. The advantages of this approach over competing approaches is that it is naturally adaptive, it does not involve between-model proposals required in reversible jump Markov chain Monte Carlo and does not rely on potentially rough approximations. The algorithm is demonstrated on Markov process and integer autoregressive moving average models applied to real biological datasets of hospital-acquired pathogen incidence, animal health time series and the cumulative number of poison disease cases in mule deer.

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While the economic and environmental benefits of fisheries management are well accepted, the costs of effective management in low value fisheries, including the research necessary to underpin such management, may be considerable relative to the total economic benefits they may generate. Co-management is often seen as a panacea in low value fisheries. Increasing fisher participation increases legitimacy of management decision in the absence of detailed scientific input. However, where only a small number of operators exist, the potential benefits of co-management are negated by the high transaction cost to the individual fishers engaging in the management process. From an economic perspective, sole ownership has been identified as the management structure which can best achieve biological and economic sustainability. Moving low value fisheries with a small number of participants to a corporate-cooperative management model may come close to achieving these sole ownership benefits, with lower transaction costs. In this paper we look at the applicability of different management models with industry involvement to low value fisheries with a small number of participants. We provide an illustration as to how a fishery could be transitioned to a corporate-cooperative management model that captures the key benefits of sole management at a low cost and is consistent with societal objectives.

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This presentation provides a beginning discussion about what the literature reports about incarcerated young people. Incarcerated Indigenous and low SES young people typically have very low literacy and mathematics skills which precludes them from future education and or employment opportunities, thus continuing the cycle of disadvantage, exclusion and despair(Payne, 2007). Being locked out of learning, they are stuck in a cycle of underachievement, a scenario which contributes to unacceptably high levels of recidivism(ACER, 2014). Success at education is considered an important protective factor against delinquent behaviours such as offending, substance abuse and truancy. Youth education and training centres provide educational opportunities for the incarcerated Indigenous youth but achievement continues to be lower than expected, particularly in mathematics. This presentation provides an introductory literature review focusing on incarcerated young people and education. It is also the preliminary writing for a small pilot project currently being conducted in one Youth Education and Training Centre in Australia.

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Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.