162 resultados para Oreochromis niloticus (Source: CAB)


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Background Depression is a common psychiatric disorder in older people. The study aimed to examine the screening accuracy of the Geriatric Depression Scale (GDS) and the Collateral Source version of the Geriatric Depression Scale (CS-GDS) in the nursing home setting. Methods Eighty-eight residents from 14 nursing homes were assessed for depression using the GDS and the CS-GDS, and validated against clinician diagnosed depression using the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders (SCID) for residents without dementia and the Provisional Diagnostic Criteria for Depression in Alzheimer Disease (PDCdAD) for those with dementia. The screening performances of five versions of the GDS (30-, 15-, 10-, 8-, and 4-item) and two versions of the CS-GDS (30- and 15-item) were analyzed using receiver operating characteristic (ROC) curves. Results Among residents without dementia, both the self-rated (AUC = 0.75–0.79) and proxy-rated (AUC = 0.67) GDS variations performed significantly better than chance in screening for depression. However, neither instrument adequately identified depression among residents with dementia (AUC between 0.57 and 0.70). Among the GDS variations, the 4- and 8-item scales had the highest AUC and the optimal cut-offs were >0 and >3, respectively. Conclusions The validity of the GDS in detecting depression requires a certain level of cognitive functioning. While the CS-GDS is designed to remedy this issue by using an informant, it did not have adequate validity in detecting depression among residents with dementia. Further research is needed on informant selection and other factors that can potentially influence the validity of proxy-based measures in the nursing home setting.

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Travellers are spoilt by holiday choice, and yet will usually only seriously consider a few destinations during the decision process. With thousands of destination marketing organisations (DMOs) competing for attention, places are becoming increasingly substitutable. The study of destination competitiveness is an emerging field, and thesis contributes to an enhanced understanding by addressing three topics that have received relatively little attention in the tourism literature: destination positioning, the context of short break holidays, and domestic travel in New Zealand. A descriptive model of positioning as a source of competitive advantage is developed, and tested through 12 propositions. The destination of interest is Rotorua, which was arguably New Zealand’s first tourist destination. The market of interest is Auckland, which is Rotorua’s largest visitor market. Rotorua’s history is explored to identify factors that may have contributed to the destination’s current image in the Auckland market. A mix of qualitative and quantitative procedures is then utilised to determine Rotorua’s position, relative to a competing set of destinations. Based on an applied research problem, the thesis attempts to bridge the gap between academia and industry by providing useable results and benchmarks for five regional tourism organisations (RTOs). It is proposed that, in New Zealand, the domestic short break market represents a valuable opportunity not explicitly targeted by the competitive set of destinations. Conceptually, the thesis demonstrates the importance of analysing a destination’s competitive position, from the demand perspective, in a travel context; and then the value of comparing this ‘ideal’ position with that projected by the RTO. The thesis concludes Rotorua’s market position in the Auckland short break segment represents a source of comparative advantage, but is not congruent with the current promotional theme, which is being used in all markets. The findings also have implications for destinations beyond the context of the thesis. In particular, a new definition for ‘destination attractiveness’ is proposed, which warrants consideration in the design of future destination positioning analyses.

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The Source Monitoring Framework is a promising model of constructive memory, yet fails because it is connectionist and does not allow content tagging. The Dual-Process Signal Detection Model is an improvement because it reduces mnemic qualia to a single memory signal (or degree of belief), but still commits itself to non-discrete representation. By supposing that ‘tagging’ means the assignment of propositional attitudes to aggregates of anemic characteristics informed inductively, then a discrete model becomes plausible. A Bayesian model of source monitoring accounts for the continuous variation of inputs and assignment of prior probabilities to memory content. A modified version of the High-Threshold Dual-Process model is recommended to further source monitoring research.

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On the 12th June 2014, Elon Musk, the chief executive officer of the electric car manufacturer, Tesla Motors, announced in a blog that ‘all our patents belong to you.’ He explained that the company would adopt an open source philosophy in respect of its intellectual property in order to encourage the development of the industry of electric cars, and address the carbon crisis. Elon Musk made the dramatic, landmark announcement: Yesterday, there was a wall of Tesla patents in the lobby of our Palo Alto headquarters. That is no longer the case. They have been removed, in the spirit of the open source movement, for the advancement of electric vehicle technology.

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Frequency Domain Spectroscopy (FDS) is one of the major techniques used for determining the condition of the cellulose based paper and pressboard components in large oil/paper insulated power transformers. This technique typically makes use of a sinusoidal voltage source swept from 0.1 mHz to 1 kHz. The excitation test voltage source used must meet certain characteristics, such as high output voltage, high fidelity, low noise and low harmonic content. The amplifier used; in the test voltage source; must be able to drive highly capacitive loads. This paper proposes that a switch-mode assisted linear amplifier (SMALA) can be used in the test voltage source to meet these criteria. A three level SMALA prototype amplifier was built to experimentally demonstrate the effectiveness of this proposal. The developed SMALA prototype shows no discernable harmonic distortion in the output voltage waveform, or the need for output filters, and is therefore seen as a preferable option to pulse width modulated digital amplifiers. The lack of harmonic distortion and high frequency switching noise in the output voltage of this SMALA prototype demonstrates its feasibility for applications in FDS, particularly on highly capacitive test objects such as transformer insulation systems.

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Past research has suggested that social networking sites are the most common source for social engineering-based attacks. Persuasion research shows that people are more likely to obey and accept a message when the source’s presentation appears to be credible. However, many factors can impact the perceived credibility of a source, depending on its type and the characteristics of the environment. Our previous research showed that there are four dimensions of source credibility in terms of social engineering on Facebook: perceived sincerity, perceived competence, perceived attraction, and perceived worthiness. Because the dimensionalities of source credibility as well as their measurement scales can fluctuate from one type of source to another and from one type of context to another, our aim in this study includes validating the existence of those four dimensions toward the credibility of social engineering attackers on Facebook and developing a valid measurement scale for every dimension of them.

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Airborne organic pollutants have significant impacts on health; however their sources, atmospheric characteristics and resulting human exposures are poorly understood. This research characterized chemical composition of atmospheric volatile organic compounds, polycyclic aromatic hydrocarbons and carbonyls in representative number of primary schools in Brisbane Metropolitan Area, quantified their concentrations, assessed their toxicity and apportioned them to their sources. The findings expand scientific knowledge of these pollutants, and will contribute towards science based management of risks associated with pollution emissions and air quality in schools and other urban and indoor environments.

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Polycyclic Aromatic Hydrocarbons (PAHs) represent a major class of toxic pollutants because of their carcinogenic and mutagenic characteristics. People living in urban areas are regularly exposed to PAHs because of abundance of their emission sources. Within this context, this study aimed to: (i) identify and quantify the levels of ambient PAHs in an urban environment; (ii) evaluate their toxicity; and (iii) identify their sources as well as the contribution of specific sources to measured concentrations. Sixteen PAHs were identified and quantified in air samples collected from Brisbane. Principal Component Analysis – Absolute Principal Component Scores (PCA- APCS) was used in order to conduct source apportionment of the measured PAHs. Vehicular emissions, natural gas combustion, petrol emissions and evaporative/unburned fuel were the sources identified; contributing 56%, 21%, 15% and 8% of the total PAHs emissions, respectively, all of which need to be considered for any pollution control measures implemented in urban areas.

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Over recent decades, efforts have been made to reduce human exposure to atmospheric pollutants including polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) through emission control and abatement. Along with the potential changes in their concentrations resulting from these efforts, profiles of emission sources may have also changed over such extended timeframes. However relevant data are quite limited in the Southern Hemisphere. We revisited two sampling sites in an Australian city, where the concentration data in 1994/5 for atmospheric PAHs and PCBs were available. Monthly air samples from July 2013 to June 2014 at the two sites were collected and analysed for these compounds, using similar protocols to the original study. A prominent seasonal pattern was observed for PAHs with elevated concentrations in cooler months whereas PCB levels showed little seasonal variation. Compared to two decades ago, atmospheric concentrations of ∑13 PAHs (gaseous + particle-associated) in this city have decreased by approximately one order of magnitude and the apparent halving time ( t 1 / 2 ) was estimated as 6.2 ± 0.56 years. ∑6 iPCBs concentrations (median value; gaseous + particle-associated) have decreased by 80% with an estimated t 1 / 2 of 11 ± 2.9 years. These trends and values are similar to those reported for comparable sites in the Northern Hemisphere. To characterise emission source profiles, samples were also collected from a bushfire event and within a vehicular tunnel. Emissions from bushfires are suggested to be an important contributor to the current atmospheric concentrations of PAHs in this city. This contribution is more important in cooler months, i.e. June, July and August, and its importance may have increased over the last two decades.

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The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

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Corporate executives require relevant and intelligent business information in real-time to take strategic decisions. They require the freedom to access this information anywhere and anytime. There is a need to extend this functionality beyond the office and on the fingertips of the decision makers. Mobile Business Intelligence Tool (MBIT) aims to provide these features in a flexible and cost-efficient manner. This paper describes the detailed architecture of MBIT to overcome the limitations of existing mobile business intelligence tools. Further, a detailed implementation framework is presented to realize the design. This research highlights the benefits of using service oriented architecture to design flexible and platform independent mobile business applications. © 2009 IEEE.

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Impervious surfaces in an urban catchment are the primary stormwater pollutant contributing areas. Appropriate treatment of stormwater runoff from these impervious surfaces is essential to safeguard the urban water environment. While urban roads have received significant research attention in this regard, roofs have not been well investigated. Key pollutant processes such as build-up on roads and roofs can be different due to the different surface characteristics. This entails different treatment strategies being needed for road and roofs. The research study characterized roof pollutants build-up by differentiating with road surfaces. It was noted that pollutants are more highly concentrated on particles and particularly finer particles in the case of roof surfaces, compared to road surfaces. Additionally, pollutants built-up on roof surfaces tend to be relatively more variable from one day to another in terms of pollutant loads. These results highlight the significance of roofs as a stormwater pollutant source and the important need for a specific stormwater treatment strategy rather than the application of a combined approach for treating stormwater runoff from both, roads and roofs.