551 resultados para Effective Temperature


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This paper investigates a five-factor model of mentoring for effective teaching. A survey was administered to 218 student teachers after student teaching to provide insights into their mentoring experience. Results indicated the five factors, namely, personal attributes, system requirements, pedagogical knowledge, modeling, and feedback, had Cronbach alpha scores of .93, .81, .95, .91, and .91, respectively with mean scale scores ranging from 4.20 to 4.60 (p< .001). Items associated with each factor were analyzed; the lowest percentage response was reviewing lesson plans (71%) and the highest percentage was modeling effective teaching practices (96%). Triangulated data from the survey results suggested that the practices implemented by the mentor teachers were perceived to have supported the student teachers’ development during student teaching. Implications of this study suggest that actively engaging mentor teachers who apply the principles outlined by the five factor areas will serve to ensure highly effective support for the development of student teachers.

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Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

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In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental–numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.

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This thesis has identified the high risk areas of childhood pneumonia and diarrhoea in Queensland and quantified the effects of temperature on emergency department visits for childhood pneumonia and diarrhoea. It adds to the increasing evidence about the impacts of climate variability and change on children's health and may have significant implications for developing climate change adaptation strategies and paediatric care policies.

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Decision-making is such an integral aspect in health care routine that the ability to make the right decisions at crucial moments can lead to patient health improvements. Evidence-based practice, the paradigm used to make those informed decisions, relies on the use of current best evidence from systematic research such as randomized controlled trials. Limitations of the outcomes from randomized controlled trials (RCT), such as “quantity” and “quality” of evidence generated, has lowered healthcare professionals’ confidence in using EBP. An alternate paradigm of Practice-Based Evidence has evolved with the key being evidence drawn from practice settings. Through the use of health information technology, electronic health records (EHR) capture relevant clinical practice “evidence”. A data-driven approach is proposed to capitalize on the benefits of EHR. The issues of data privacy, security and integrity are diminished by an information accountability concept. Data warehouse architecture completes the data-driven approach by integrating health data from multi-source systems, unique within the healthcare environment.

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Study/Objective This paper describes a program of research examining emergency messaging during the response and early recovery phases of natural disasters. The objective of this suite of studies is to develop message construction frameworks and channels that maximise community compliance with instructional messaging. The research has adopted a multi-hazard approach and considers the impact of formal emergency messages, as well as informal messages (e.g., social media posts), on community compliance. Background In recent years, media reports have consistently demonstrated highly variable community compliance to instructional messaging during natural disasters. Footage of individuals watching a tsunami approaching from the beach or being over-run by floodwaters are disturbing and indicate the need for a clearer understanding of decision making under stress. This project’s multi-hazard approach considers the time lag between knowledge of the event and desired action, as well as how factors such as message fatigue, message ambiguity, and the interplay of messaging from multiple media sources are likely to play a role in an individual’s compliance with an emergency instruction. Methods To examine effective messaging strategy, we conduct a critical analysis of the literature to develop a framework for community consultation and design experiments to test the potential for compliance improvement. Results Preliminary results indicate that there is, as yet, little published evidence on which to base decisions about emergency instructional messages to threatened communities. Conclusion The research described here will contribute improvements in emergency instructional message compliance by generating an evidence-based framework that takes into account behavioural compliance theory, the psychology of decision making under stress, and multiple channels of communication including social media.

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This paper describes a program of research examining emergency messaging during the response and early recovery phases of natural disasters. The objective of this suite of studies is to develop message construction frameworks and channels that maximise community compliance with instructional messaging. The research has adopted a multi-hazard approach and considers the impact of formal emergency messages, as well as informal messages (e.g., social media posts), on community compliance. In recent years, media reports have consistently demonstrated highly variable community compliance to instructional messaging during natural disasters. Footage of individuals watching a tsunami approaching from the beach or being over-run by floodwaters are disturbing and indicate the need for a clearer understanding of decision making under stress. This project’s multi-hazard approach considers the time lag between knowledge of the event and desired action, as well as how factors such as message fatigue, message ambiguity, and the interplay of messaging from multiple media sources are likely to play a role in an individual’s compliance with an emergency instruction. To examine effective messaging strategy, we conduct a critical analysis of the literature to develop a framework for community consultation and design experiments to test the potential for compliance improvement. Preliminary results indicate that there is, as yet, little published evidence on which to base decisions about emergency instructional messages to threatened communities. The research described here will contribute improvements in emergency instructional message compliance by generating an evidence-based framework that takes into account behavioural compliance theory, the psychology of decision making under stress, and multiple channels of communication including social media.

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Study/Objective This research examines the types of emergency messages used in Australia during the response and early recovery phases of a natural disaster. The aim of the research is to develop theory-driven emergency messages that increase individual behavioural compliance during a disaster. Background There is growing evidence of non-compliant behaviour in Australia, such as refusing to evacuate and travelling through hazardous areas. This can result in personal injury, loss of life, and damage to (or loss of) property. Moreover, non-compliance can place emergency services personnel in life-threatening situations when trying to save non-compliant individuals. Drawing on message compliance research in psychology and sociology, a taxonomy of message types was developed to ascertain how emergency messaging can be improved to produce compliant behaviour. Method A review of message compliance literature was conducted to develop the taxonomy of message types previously found to achieve compliance. Seven categories were identified: direct-rational, manipulation, negative phrasing, positive phrasing, exchange appeals, normative appeals, and appeals to self. A content analysis was then conducted to assess the emergency messages evident in the Australian emergency management context. The existing messages were aligned with the literature to identify opportunities to improve emergency messaging. Results & Conclusion The results suggest there is an opportunity to improve the effectiveness of emergency messaging to increase compliance during the response and early recovery phases of a natural disaster. While some message types cannot legally or ethically be used in emergency communication (e.g. manipulative messaging), there is an opportunity to create more persuasive messages (e.g. appeals to self) that personalise the individual’s perception of risk, triggering them to comply with the message.

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Typing 2 or 3 keywords into a browser has become an easy and efficient way to find information. Yet, typing even short queries becomes tedious on ever shrinking (virtual) keyboards. Meanwhile, speech processing is maturing rapidly, facilitating everyday language input. Also, wearable technology can inform users proactively by listening in on their conversations or processing their social media interactions. Given these developments, everyday language may soon become the new input of choice. We present an information retrieval (IR) algorithm specifically designed to accept everyday language. It integrates two paradigms of information retrieval, previously studied in isolation; one directed mainly at the surface structure of language, the other primarily at the underlying meaning. The integration was achieved by a Markov machine that encodes meaning by its transition graph, and surface structure by the language it generates. A rigorous evaluation of the approach showed, first, that it can compete with the quality of existing language models, second, that it is more effective the more verbose the input, and third, as a consequence, that it is promising for an imminent transition from keyword input, where the onus is on the user to formulate concise queries, to a modality where users can express more freely, more informal, and more natural their need for information in everyday language.

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The intercalation of an anionic surfactant, sodium dodecylsulfate (SDS), into hydrocalumite (CaAl-LDH-Cl) was investigated in this study. To understand the intercalation behavior, X-ray diffraction (XRD), mid-infrared spectroscopy (MIR), near-infrared spectroscopy (NIR) and scanning electron microscopy (SEM) were undertaken. The near-infrared spectra indicated a special spectral range from 6000 to 5600cm-1and prominent bands of CaAl-LDH-Cl intercalated with SDS around 8388cm-1. This band was assigned to the second overtone of the first fundamental of CH stretching vibrations of SDS, and it could be used to determinate the result of CaAl-LDH-Cl modified by SDS. Moreover, the results revealed that different adsorption behaviors were observed at different (high and low) concentrations of SDS. When the SDS concentration was around 0.2molL-1, anion exchange intercalation occurred and the interlayer distance expanded to about 3.25nm. When SDS concentration was 0.005molL-1, the surface adsorption of DS- was the major anion exchange event.

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We investigate, using scanning tunnelling microscopy, the adsorption of pentacene on Ni(111) at room temperature and the behaviour of these monolayer films with annealing up to 700 °C. We observe the conversion of pentacene into graphene, which begins from as low as 220 °C with the coalescence of pentacene molecules into large planar aggregates. Then, by annealing at 350 °C for 20 minutes, these aggregates expand into irregular domains of graphene tens of nanometers in size. On surfaces where graphene and nickel carbide coexist, pentacene shows preferential adsorption on the nickel carbide phase. The same pentacene to graphene transformation was also achieved on Cu(111), but at a higher activation temperature, producing large graphene domains that exhibit a range of moiré superlattice periodicities.

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This is an ongoing research investigating the use of health information technologies (HIT) to improve clinical decision-making processes. Effective and timely clinical decision-making can lead to positive improvements in patient’s health outcome...

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The 12.7-10.5 Ma Cougar Point Tuff in southern Idaho, USA, consists of 10 large-volume (>10²-10³ km³ each), high-temperature (800-1000 °C), rhyolitic ash-flow tuffs erupted from the Bruneau-Jarbidge volcanic center of the Yellowstone hotspot. These tuffs provide evidence for compositional and thermal zonation in pre-eruptive rhyolite magma, and suggest the presence of a long-lived reservoir that was tapped by numerous large explosive eruptions. Pyroxene compositions exhibit discrete compositional modes with respect to Fe and Mg that define a linear spectrum punctuated by conspicuous gaps. Airfall glass compositions also cluster into modes, and the presence of multiple modes indicates tapping of different magma volumes during early phases of eruption. Equilibrium assemblages of pigeonite and augite are used to reconstruct compositional and thermal gradients in the pre-eruptive reservoir. The recurrence of identical compositional modes and of mineral pairs equilibrated at high temperatures in successive eruptive units is consistent with the persistence of their respective liquids in the magma reservoir. Recurrence intervals of identical modes range from 0.3 to 0.9 Myr and suggest possible magma residence times of similar duration. Eruption ages, magma temperatures, Nd isotopes, and pyroxene and glass compositions are consistent with a long-lived, dynamically evolving magma reservoir that was chemically and thermally zoned and composed of multiple discrete magma volumes.

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The phase relations have been investigated experimentally at 200 and 500 MPa as a function of water activity for one of the least evolved (Indian Batt Rhyolite) and of a more evolved rhyolite composition (Cougar Point Tuff XV) from the 12·8-8·1 Ma Bruneau-Jarbidge eruptive center of the Yellowstone hotspot. Particular priority was given to accurate determination of the water content of the quenched glasses using infrared spectroscopic techniques. Comparison of the composition of natural and experimentally synthesized phases confirms that high temperatures (>900°C) and extremely low melt water contents (<1·5 wt % H₂O) are required to reproduce the natural mineral assemblages. In melts containing 0·5-1·5 wt % H₂O, the liquidus phase is clinopyroxene (excluding Fe-Ti oxides, which are strongly dependent on fO₂), and the liquidus temperature of the more evolved Cougar Point Tuff sample (BJR; 940-1000°C) is at least 30°C lower than that of the Indian Batt Rhyolite lava sample (IBR2; 970-1030°C). For the composition BJR, the comparison of the compositions of the natural and experimental glasses indicates a pre-eruptive temperature of at least 900°C. The composition of clinopyroxene and pigeonite pairs can be reproduced only for water contents below 1·5 wt % H₂O at 900°C, or lower water contents if the temperature is higher. For the composition IBR2, a minimum temperature of 920°C is necessary to reproduce the main phases at 200 and 500 MPa. At 200 MPa, the pre-eruptive water content of the melt is constrained in the range 0·7-1·3 wt % at 950°C and 0·3-1·0 wt % at 1000°C. At 500 MPa, the pre-eruptive temperatures are slightly higher (by 30-50°C) for the same ranges of water concentration. The experimental results are used to explore possible proxies to constrain the depth of magma storage. The crystallization sequence of tectosilicates is strongly dependent on pressure between 200 and 500 MPa. In addition, the normative Qtz-Ab-Or contents of glasses quenched from melts coexisting with quartz, sanidine and plagioclase depend on pressure and melt water content, assuming that the normative Qtz and Ab/Or content of such melts is mainly dependent on pressure and water activity, respectively. The combination of results from the phase equilibria and from the composition of glasses indicates that the depth of magma storage for the IBR2 and BJR compositions may be in the range 300-400 MPa (13 km) and 200-300 MPa (10 km), respectively.

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Skin temperature is an important physiological measure that can reflect the presence of illness and injury as well as provide insight into the localised interactions between the body and the environment. The aim of this systematic review was to analyse the agreement between conductive and infrared means of assessing skin temperature which are commonly employed in in clinical, occupational, sports medicine, public health and research settings. Full-text eligibility was determined independently by two reviewers. Studies meeting the following criteria were included in the review: 1) the literature was written in English, 2) participants were human (in vivo), 3) skin surface temperature was assessed at the same site, 4) with at least two commercially available devices employed—one conductive and one infrared—and 5) had skin temperature data reported in the study. A computerised search of four electronic databases, using a combination of 21 keywords, and citation tracking was performed in January 2015. A total of 8,602 were returned. Methodology quality was assessed by 2 authors independently, using the Cochrane risk of bias tool. A total of 16 articles (n = 245) met the inclusion criteria. Devices are classified to be in agreement if they met the clinically meaningful recommendations of mean differences within ±0.5 °C and limits of agreement of ±1.0 °C. Twelve of the included studies found mean differences greater than ±0.5 °C between conductive and infrared devices. In the presence of external stimulus (e.g. exercise and/or heat) five studies foundexacerbated measurement differences between conductive and infrared devices. This is the first review that has attempted to investigate presence of any systemic bias between infrared and conductive measures by collectively evaluating the current evidence base. There was also a consistently high risk of bias across the studies, in terms of sample size, random sequence generation, allocation concealment, blinding and incomplete outcome data. This systematic review questions the suitability of using infrared cameras in stable, resting, laboratory conditions. Furthermore, both infrared cameras and thermometers in the presence of sweat and environmental heat demonstrate poor agreement when compared to conductive devices. These findings have implications for clinical, occupational, public health, sports science and research fields.