Kerstin Thompson Architects : exploring affect in interior's sticky design process

Physical things influence emotions and feelings and can contribute to our sense that buildings and rooms are appropriately designed for their purposes. The sense of appropriateness extends, and is often noticed, through the pre-emotive effect of a structure’s shapes and dimensions. In interior discourse the relationship between the physical and pre-emotive is indicated with various terms (such as “affect”) and the design process of achieving appropriateness in objects and affect can be termed “stickiness”. In this paper we extend Sara Ahmed’s characterization of affect as a sticky connective element, which allows objects and ideas to generate attachments with us. And we ask, how can we understand interior practices and design processes through the concept of affect – as sticky? We explore this question first by discussing affect’s stickiness, and second, by an empirical study of the design process of Kerstin Thompson’s Monash University Museum of Art. The specific project involves alternating design methods that Thompson uses: an intuitive hunch-driven process, and a more defined literary-driven process. Our interest is to consider how she shifts from one to the other so we can better understand interior practice and its design process through the concept of affect. Finally, we conclude by addressing how the study of affect contributes to our understanding of interior practice and its design process, and more significantly, how, in exchange, might interior practice offer to recent theories of affect. Interior practice as changeable, spatio-temporal and material processes offer potentially fertile ground to explore affect as mediating layer, bridging human and non-human forces.

Asociación de las violencias física, sexual y comunitaria con el embarazo en adolescentes: análisis multinivel

Objetivos Determinar si existe asociación entre la exposición a violencia, experimentada a nivel individual o municipal, y el embarazo adolescente en mujeres Colombianas entre 13 y 19 años de edad que contestaron la Encuesta de Demografía y Salud en el año 2010. Métodos Estudio de corte transversal, nacional y multinivel. Se tomaron datos de dos niveles jerárquicos: Nivel- 1: Datos individuales de una muestra representativa de 13.313 mujeres entre 13 y 19 años de edad provenientes de La Encuesta Nacional de Demografía y Salud del año 2010 y Nivel- 2: Datos municipales de 258 municipios provenientes de las estadísticas vitales del DANE. Resultados La prevalencia del embarazo adolescente fue del 16.8% IC 95% [16.2-17.4]. El análisis mostró que la asociación entre embarazo adolescente y violencia tanto individual, representada como violencia sexual [OR= 6.99 IC99% 4.80-10.10] y violencia física [OR= 1.74 IC99% 1.47-2.05] así como la violencia municipal medida con tasas de homicidios altas [OR= 1.99 IC99% 1.29-3.07] y muy altas [OR= 2.10 IC99% 1.21-3.61] se mantuvo estadísticamente significativa después de ajustar por las variables: Edad [OR= 1.81 IC99% 1.71-1.91], ocupación [OR= 1.62 IC99% 1.37-1.93], educación primaria o sin educación [OR= 2.20 IC99% 1.47-3.30], educación secundaria [OR= 1.70 IC99% 1.24-2.32], asistir al colegio [OR= 0.18 IC99% 0.15-0.21], conocimiento en la fisiología reproductiva [OR= 1.28 IC99% 1.06-1.54], el índice de riqueza Q1, Q2, Q3 [OR= 2.18 IC99% 1.42-3.34], [OR= 2.00 IC99% 1.39-2.28], [OR= 1.82 IC99% 1.92-2.25] y alto porcentaje de Necesidades básicas insatisfechas a nivel municipal [OR= 2.34 IC99% 1.55-3.52]. Conclusiones Este estudio mostró una relación significativamente estadística entre la violencia sexual y física con el inicio de relaciones sexuales y embarazo adolescente después de controlar por factores sociodemográficos y conocimientos en reproducción sexual en mujeres colombianas de 13 a 19 años en el año 2010. Esta asociación debe continuar siendo estudiada para lograr optimizar las estrategias de prevención y disminuir la tasa actual de embarazos adolescentes en el país y sus consecuencias.

Growth and survival of Sclerolobium paniculatum vogel and the relationship between rainfall and the increment in diameter at different planting spacings.

Sclerolobium paniculatum Vogel is a species that has good potential for reclamation of degraded soils. The aim of the investigation was to evaluate the growth and survival of the species and the influence of rainfall on growth in diameter as a function of different spacings (4 m x 2 m, 4 m x 3 m, and 4 m x 4 m). The results indicate that the temporal analysis (period from November 2007 to August 2013) detected significant differences (p ? 0.05) in height between the 4 m x 2 m and 4 m x 4 m spacings, while no significant difference in diameter was found between the 4 m x 2 m and 4 m x 3 m spacings. However, the statistical differences did not persist when the data was analyzed at seven and half years old. Regarding survival, a significant difference was observed only between the 4 m x 4 m spacing and the others, with superiority to the former. A strong correlation was found between rainfall and the increment in diameter of individuals in the broader spacings (R = 0.80 in the 4 m x 3 m spacing and R = 0.77 in the 4 m x 4 m spacing), while in the denser spacing the correlation was moderate (R = 0.56 in the 4 m x 2 m spacing). Since the spacings adopted did not influence tree growth by the end of the period, the choice will depend on other factors such as survival and costs of implementation and forestry management. Plantations in regions with larger rainfall amplitude may benefit the productivity of the species.

Comparison of multitemporal MODIS-EVI smoothing algorithms and its contribution to crop monitoring.

Crop monitoring and more generally land use change detection are of primary importance in order to analyze spatio-temporal dynamics and its impacts on environment. This aspect is especially true in such a region as the State of Mato Grosso (south of the Brazilian Amazon Basin) which hosts an intensive pioneer front. Deforestation in this region as often been explained by soybean expansion in the last three decades. Remote sensing techniques may now represent an efficient and objective manner to quantify how crops expansion really represents a factor of deforestation through crop mapping studies. Due to the special characteristics of the soybean productions' farms in Mato Grosso (area varying between 1000 hectares and 40000 hectares and individual fields often bigger than 100 hectares), the Moderate Resolution Imaging Spectroradiometer (MODIS) data with a near daily temporal resolution and 250 m spatial resolution can be considered as adequate resources to crop mapping. Especially, multitemporal vegetation indices (VI) studies have been currently used to realize this task [1] [2]. In this study, 16-days compositions of EVI (MODQ13 product) data are used. However, although these data are already processed, multitemporal VI profiles still remain noisy due to cloudiness (which is extremely frequent in a tropical region such as south Amazon Basin), sensor problems, errors in atmospheric corrections or BRDF effect. Thus, many works tried to develop algorithms that could smooth the multitemporal VI profiles in order to improve further classification. The goal of this study is to compare and test different smoothing algorithms in order to select the one which satisfies better to the demand which is classifying crop classes. Those classes correspond to 6 different agricultural managements observed in Mato Grosso through an intensive field work which resulted in mapping more than 1000 individual fields. The agricultural managements above mentioned are based on combination of soy, cotton, corn, millet and sorghum crops sowed in single or double crop systems. Due to the difficulty in separating certain classes because of too similar agricultural calendars, the classification will be reduced to 3 classes : Cotton (single crop), Soy and cotton (double crop), soy (single or double crop with corn, millet or sorghum). The classification will use training data obtained in the 2005-2006 harvest and then be tested on the 2006-2007 harvest. In a first step, four smoothing techniques are presented and criticized. Those techniques are Best Index Slope Extraction (BISE) [3], Mean Value Iteration (MVI) [4], Weighted Least Squares (WLS) [5] and Savitzky-Golay Filter (SG) [6] [7]. These techniques are then implemented and visually compared on a few individual pixels so that it allows doing a first selection between the five studied techniques. The WLS and SG techniques are selected according to criteria proposed by [8]. Those criteria are: ability in eliminating frequent noises, conserving the upper values of the VI profiles and keeping the temporality of the profiles. Those selected algorithms are then programmed and applied to the MODIS/TERRA EVI data (16-days composition periods). Tests of separability are realized based on the Jeffries-Matusita distance in order to see if the algorithms managed in improving the potential of differentiation between the classes. Those tests are realized on the overall profile (comprising 23 MODIS images) as well as on each MODIS sub-period of the profile [1]. This last test is a double interest process because it allows comparing the smoothing techniques and also enables to select a set of images which carries more information on the separability between the classes. Those selected dates can then be used to realize a supervised classification. Here three different classifiers are tested to evaluate if the smoothing techniques as a particular effect on the classification depending on the classifiers used. Those classifiers are Maximum Likelihood classifier, Spectral Angle Mapper (SAM) classifier and CHAID Improved Decision tree. It appears through the separability tests on the overall process that the smoothed profiles don't improve efficiently the potential of discrimination between classes when compared with the original data. However, the same tests realized on the MODIS sub-periods show better results obtained with the smoothed algorithms. The results of the classification confirm this first analyze. The Kappa coefficients are always better with the smoothing techniques and the results obtained with the WLS and SG smoothed profiles are nearly equal. However, the results are different depending on the classifier used. The impact of the smoothing algorithms is much better while using the decision tree model. Indeed, it allows a gain of 0.1 in the Kappa coefficient. While using the Maximum Likelihood end SAM models, the gain remains positive but is much lower (Kappa improved of 0.02 only). Thus, this work's aim is to prove the utility in smoothing the VI profiles in order to improve the final results. However, the choice of the smoothing algorithm has to be made considering the original data used and the classifier models used. In that case the Savitzky-Golay filter gave the better results.

Energy balance model applied to pasture experimental areas in São Paulo State, Brazil.

The Simple Algorithm for Evapotranspiration Retrieving (SAFER) was used to estimate biophysical parameters and theenergy balance components in two different pasture experimental areas, in the São Paulo state, Brazil. The experimentalpastures consist in six rotational (RGS) and three continuous grazing systems (CGS) paddocks. Landsat-8 images from2013 and 2015 dry and rainy seasons were used, as these presented similar hydrological cycle, with 1,600 mm and 1,613mm of annual precipitation, resulting in 19 cloud-free images. Bands 1 to 7 and thermal bands 10 and 11 were used withweather data from a station located nearthe experimental area. NDVI, biomass, evapotranspiration and latent heat flux(λE) temporal values statistically differ CGS from RGS areas. Grazing systems influences the energy partition and theseresults indicate that RGS benefits biomass production, evapotranspiration and the microclimate, due higher LE values.SAFER is a feasible tool to estimate biophysical parameters and energy balance components in pasture and has potentialto discriminate continuous and rotation grazing systems in a temporal analysis.