955 resultados para Portland (Vic.) -- Description and travel


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Despite China's rapid growth in inbound tourism, the nature of its Canadian tourist market has been insufficiently studied. In response to this need, the objectives of this study are to identify China's destination image in Canadian students' minds, their possible internal motivations for visiting China as well as examining demographic influences on people's destination image formation. The study reviews image formation process and travel motivation categorisation, discusses their relationship, and implements Baloglu and McCleary's (1999) perceptual and affective image formation model and "push and pull factors" theory as its framework. A self-administered survey was applied to 424 undergraduate students in a Canadian university in early 2004. Exploratory factor analyses were conducted to identify perceived images and travel motivation. Summated means were calculated to illustrate the affective attitudes. A series of f-test and ANOVA tests were employed to examine the influence of demographics. An open-ended question format was adopted to analyse other images, motivations and visitation barriers that students may have. Findings demonstrate that cultural and natural attractions are the predominant image which the Canadian students have of China'; some stereotypes and negative images still influence the students' perception; travel service quality is largely unknown; increasing knowledge and seeking excitement and fun are the significant motivators in the likelihood of the Canadian students choosing to visit China; and personal interests may be a factor that significantly influences an individual's destination image and travel motivation. Raising awareness and increasing familiarity through promotion are suggested as methods to create a positive destination image of China.

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Samdahl and Jekubovich (1997) view constraints as a subset of reasons for not engaging in a particular behavior. There is limited empirical research on the role of demographic and socioeconomic variables as travel constraints. This study investigates the relationships between a wide range of short and long trip planning and travel behaviors and sociodemographic constraints comprised of age, income and life cycle.

This research uses data generated from a cross-sectional, self-completed survey on travel and tourism which was collected during 2003 and 2004 from 49,105 Australian respondents. This paper utilizes binomial regression to find that age, income and life stage have significant differential and interactive effects on travel behavior. The results show that sociodemographic variables act in different ways to constrain/free different types of travel behavior. Implications are provided for national and state based tourism authorities. There is a need to understand these phenomena. Current research is addressing these issues.

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Results of fauna and vegetation surveys conducted around Portland Aluminium smelter between 1979 and 2004 found small mammal abundance and diversity had declined and changes in vegetation communities were related to changes in fire patterns, vegetation fragmentation and weed invasion. Small mammal numbers were greater in nearby National Parks.

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Commuting to work is one of the most important and regular routines of transportation in towns and cities. From a geographic perspective, the length of people’s commute is influenced, to some degree, by the spatial separation of their home and workplace and the transport infrastructure. The rise of car ownership in Australia from the 1950s to the present was accompanied by a considerable decrease of public transport use. Currently there is an average of 1.4 persons per car in Australia, and private cars are involved in approximately 90% of the trips, and public transportation in only 10%. Increased personal mobility has fuelled the trend of decentralised housing development, mostly without a clear planning for local employment, or alternative means of transportation. Transport sector accounts for 14% of Australia’s net greenhouse gas emissions. Without further policy action, Australia’s emissions are projected to continue to increase. The Australian Federal Government and the new Department of Climate Change have recently published a set of maps showing that rising seas would submerge large parts of Victoria coastal region. Such event would lead to major disruption in planned urban growth areas in the next 50 years with broad scale inundation of dwellings, facilities and road networks. The Greater Geelong Region has well established infrastructure as a major urban centre and tourist destination and hence attracted the attention of federal and state governments in their quest for further development and population growth. As a result of its natural beauty and ecological sensitivity, scenarios for growth in the region are currently under scrutiny from local government as well as development agencies, scientists, and planners. This paper is part of a broad research in the relationship between transportation system, urban form, trip demand, and emissions, as a paramount in addressing the challenges presented by urban growth. Progressing from previous work focused on private cars, this present paper investigates the use of public transport as a mode for commuting in the Greater Geelong Region. Using a GIS based interaction model, it characterises the current use of the existing public transportation system, and also builds a scenario of increased use of the existing public transportation system, estimating potencial reductions in CO2 emissions. This study provides an improved understanding of the extent to which choices of transport mode and travel activity patterns, affect emissions in the context of regional networks. The results indicate that emissions from commuting by public transportation are significantly lower than those from commuting by private car, and emphasise that there are opportunities for large abatment in the greenhouse emissions from the transportation sector related to efforts in increasing the use of existing public transportation system.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The aim of this study was to evaluate the antimicrobial activity of different root-end filling materials - Sealer 26, Sealapex with zinc oxide, zinc oxide and eugenol, white and gray Portland cement, white and gray MTA-Angelus, and gray Pro Root MTA - against six different microorganism strains. The agar diffusion method was used. A base layer was made using Müller-Hinton agar (MH) and wells were formed by removing the agar. The materials were placed in the wells immediately after manipulation. The microorganisms used were: Micrococcus luteus (ATCC9341), Staphylococcus aureus (ATCC6538), Escherichia coli (ATCC10538), Pseudomonas aeruginosa (ATCC27853), Candida albicans (ATCC 10231), and Enterococcus faecalis (ATCC 10541). The plates were kept at room temperature for 2 h for prediffusion and then incubated at 37 degrees C for 24 h. Triphenyltetrazolium chloride 0.05% gel was added for optimization, and the zones of inhibition were measured. Data were subjected to the Kruskal-Wallis and Dunn tests at a 5% significance level. The results showed that all materials had antimicrobial activity against all the tested strains. Analysis of the efficacy of the materials against the microbial strains showed that Sealapex with zinc oxide, zinc oxide and eugenol and Sealer 26 created larger inhibition halos than the MTA-based and Portland cements (P < 0.05). On the basis of the methodology used, it may be concluded that all endodontic sealers, MTA-based and Portland cements evaluated in this study possess antimicrobial activity, particularly the endodontic sealers.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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A reassessment of the taxonomic status of Amblyomma cajennense based on the morphological analyses of ticks from the whole distribution area of the species resulted in the redescription of A. cajennense, the validation of 2 species which had been reduced to synonymy in the past, Amblyomma mixtum and Amblyomma sculptum, and the description and definition of 3 new species, Amblyomma tonelliae n. sp., Amblyomma interandinum n. sp., and Amblyomma patinoi n. sp. This study provides descriptions and redescriptions, scanning electron microscopic and stereomicroscopic images, updated synonymies, information on geographical distributions, and host associations for each of the 6 species. Amblyomma cajennense s.s. is found in the Amazonian region of South America, A. interandinum is reported from the northern part of the Inter-Andean valley of Peru, A. mixtum is present from Texas (U.S.A.) to western Ecuador, A. patinoi occurs in the Eastern Cordillera of Colombia, A. tonelliae is associated with the dry areas of the Chaco region which spans from central-northern Argentina to Bolivia and Paraguay, whereas A. sculptum is distributed from the humid areas of northern Argentina, to the contiguous regions of Bolivia and Paraguay and the coastal and central-western states of Brazil.

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La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

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During the last years cities around the world have invested important quantities of money in measures for reducing congestion and car-trips. Investments which are nothing but potential solutions for the well-known urban sprawl phenomenon, also called the “development trap” that leads to further congestion and a higher proportion of our time spent in slow moving cars. Over the path of this searching for solutions, the complex relationship between urban environment and travel behaviour has been studied in a number of cases. The main question on discussion is, how to encourage multi-stop tours? Thus, the objective of this paper is to verify whether unobserved factors influence tour complexity. For this purpose, we use a data-base from a survey conducted in 2006-2007 in Madrid, a suitable case study for analyzing urban sprawl due to new urban developments and substantial changes in mobility patterns in the last years. A total of 943 individuals were interviewed from 3 selected neighbourhoods (CBD, urban and suburban). We study the effect of unobserved factors on trip frequency. This paper present the estimation of an hybrid model where the latent variable is called propensity to travel and the discrete choice model is composed by 5 alternatives of tour type. The results show that characteristics of the neighbourhoods in Madrid are important to explain trip frequency. The influence of land use variables on trip generation is clear and in particular the presence of commercial retails. Through estimation of elasticities and forecasting we determine to what extent land-use policy measures modify travel demand. Comparing aggregate elasticities with percentage variations, it can be seen that percentage variations could lead to inconsistent results. The result shows that hybrid models better explain travel behavior than traditional discrete choice models.

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The number of seniors in the U.S. today is growing rapidly because of longer life expectancies and the aging Baby Boomer generation. This age groups' travel behavior will have substantial impacts on transportation, economics, safety, and the environment. This research used a mixed-methods approach to address issues of mobility and aging in Denver, Colorado. A quantitative approach was used to answer broad questions about travel behavior and the effects of age, gender, work status, disability, residential location and socio-economic status on mobility. Qualitative interviews with seniors in the Denver metro area were conducted to identify barriers to mobility, decision-making processes and travel decisions, and seniors' perceptions of public transit. The results of the quantitative and qualitative analyses show that residential location is an important variable for determining seniors' travel behaviors and transportation options. Perceptions of public transit were positive, but accessibility and information barriers exist that prevent older adult from using transit. The findings of this study will help to provide transportation and service recommendations to policymakers and planners in the Denver area as well as to inform studies of other North American cities with large aging populations.

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Purpose - To study how the threats of terrorism are being handled by a variety of UK companies in the travel and leisure sector in the UK in the post 9/11 era. Design/methodology/approach - A review of the literature of risk management in a world that is perceived to be more risky as a result of the terrorist attacks on the US on 11 September 2001 (9/11) is presented. Describes the application of theories of organizational resilience and institutions to frame an understanding of how managers make sense of terrorism risk and comprehend uncertainty. Reports a qualitative analysis of themes in interviews conducted with 25 managers from 6 unnamed organizations in the aviation industry (3 organizations) and the UK travel and leisure industry (3 organizations), representing a catering supplier, an airport, an airline, a tour company, a convention centre, and an arts and entertainment centre. Findings - The results indicated that the three organizations in the aviation industry prioritize threats from terrorism, whilst the three organizations in the leisure and travel sector do not, suggesting that the managers in the travel and leisure industry apply a probabilistic type of thinking and believe the likelihood of terrorism to be low. Reports that they give precedence to economic concerns and numerous other threats to the industry. Concludes that managers fall prey to the 'ludic fallacy', which conceives all odds as being calculable and hence managers conceive the terrorism risk as low while also expecting institutional factors to pre-empt and control terrorism threats, a reaction which the authors believe to be rather complacent and dangerous. Originality/value - Contributes to the research literature on risk management by revealing the gap in the ability of existing management tools and methodologies to deal with current and uncertain threats facing organizations due to terrorism.