Adaptation and validation of HIV Antibody Testing Attitude Scale in Portuguese

Introduction; The awareness of HIV positiveness is important for health of the individual and of the comunity. The identicatio of HIV antibodies is possible both using conventional lab tests and quick result tests. In the bibliography it was made clear that there are no instruments in Portuguese to assert the reactions to the HIV quick tests and it was therefore considered it would be useful to adapt and validate a scale in Portuguese, since the language is the official language of 7 different countries and spoken by more than 250 milion people, Objectives: the purpose is to validate a version in European Portuguese of the HIV Antibody Testing Attitude Scale. Methods: the study refers to methodological research for the adaptation and validation of an instrument of attitude measurement. A translation and back-translation was prepared and a trial test was then carried out. A total of 317 students, lectures and co-workers of a Portuguese University was interviewes. Ethical principles were taken into consideration. the pool was obtained in the seven components of the University campus. Results: 3 trials of factorial testing of the main components of 5, 4 and 3 factors. It ended up a solution of 3 factors that explains 50.82% of the variability. In the analysis of the inter-items correlation values of between 0.018 and 0.749 were observed. The internal consistency reveals an alpha Cronbach coefficient of 0.860 as a whole, and in between 0,865 and 0.659 in the 3 factors. Conclusions: this version of the instrument shows that the psychometric properties allow its use in the Portuguese speaking countries.

Social competence and career development: validation of a scale with secondary students

This paper presents a validation study of the Perceived Social Competence in Career Scale (SCCarS). The sample included 571 adolescents, 283 girls (49.6%) and 287 boys (50.3%), aged 14 to 25 years old (ì=16.33±1.41), 10th and 11th grade students attending secondary schools in the northern, central and southern Portugal. Exploratory factor analysis indicates the presence of eight factors, with eigenvalues superior to 1.00, explaining 79.16% of the total variance of the items. Confirmatory factor analysis provided support to the factorial structure of eight factors, with adequate fit indices (X2/df=4.229, CFI= 0.909, GFI= 0.869, RMSEA= 0.079, p= 0.000). These results are consistent with the factorial structure found in previous studies carried out with Portuguese samples from 8th grade. Implications are drawn related to the need for further study of the psychometric characteristics of the SCCarS with young people from different age groups

Effects of small scale non-mechanised forest management and high impact and mechanised forest management on the forest dynamics and growth of the residual trees.

This study was perfonned in PSPs located at the CPAr-ACRE EMORAPA expcrirnental area and at the PC Peixoto management areas. AI CPA F-ACR E the managed area was meehanically exploited in 1992 and at PC Peixoto animal traction was used to extract the planks.

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin.

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin.

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.

Satellite based multi-scale methods to support governance of Brazil's low-carbon agriculture (ABC Plan).

Brazil's Low Carbon Agriculture is one the initiatives that puts the climate in the agricultural agenda towards a more sustainable and adapted agriculture under global changes. Among the several practices listed and supported by the ABC Plan, zero tillage and integrated crop-livestock-forestry systems including the recovery of degraded pasture are the most relevant ones. The objective of this paper is to present the Geo-ABC Project, a procedure to monitor the implementation of the Brazil?s Low Carbon Agriculture (ABC Plan) and aiming at the development of remote sensing methods to monitor agricultural systems listed in the ABC Plan and adopted at local scale.

Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.

Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.