The Biopsychosocial Spiritual Model Applied To The Treatment Of women With Breast Cancer, Through Rime Intervention (relaxation, mental Images, Spirituality).

This postdoctoral study on the application of the RIME intervention in women that had undergone mastectomy and were in treatment, aimed to promote psychospiritual and social transformations to improve the quality of life, self-esteem and hope. A total of 28 women participated and were randomized into two groups. Brief Psychotherapy (PB) (average of six sessions) was administered in the Control Group, and RIME (three sessions) and BP (average of five sessions) were applied in the RIME Group. The quantitative results indicated a significant improvement (38.3%) in the Perception of Quality of Life after RIME according to the WHOQOL, compared both to the BP of the Control Group (12.5%), and the BP of the RIME Group (16.2%). There was a significant improvement in Self-esteem (Rosenberg) after RIME (14.6%) compared to the BP of the Control Group (worsened 35.9%), and the BP of the RIME Group (8.3%). The improvement in well-being, considering the focus worked on (Visual Analog Scale), was significant in the RIME Group (bad to good), as well as in the Control Group (unpleasant to good). The qualitative results indicated that RIME promotes creative transformations in the intrapsychic and interpersonal dimensions, so that new meanings and/or new attitudes emerge into the consciousness. It was observed that RIME has more strength of psychic structure, ego strengthening and provides a faster transformation that BP, therefore it can be indicated for crisis treatment in the hospital environment.

Avaliação de técnicas de classificação digital de imagens landsat em diferentes padrões de cobertura da terra em Rondônia

Remotely sensed imagery has been widely used for land use/cover classification thanks to the periodic data acquisition and the widespread use of digital image processing systems offering a wide range of classification algorithms. The aim of this work was to evaluate some of the most commonly used supervised and unsupervised classification algorithms under different landscape patterns found in Rondônia, including (1) areas of mid-size farms, (2) fish-bone settlements and (3) a gradient of forest and Cerrado (Brazilian savannah). Comparison with a reference map based on the kappa statistics resulted in good to superior indicators (best results - K-means: k=0.68; k=0.77; k=0.64 and MaxVer: k=0.71; k=0.89; k=0.70 respectively for three areas mentioned). Results show that choosing a specific algorithm requires to take into account both its capacity to discriminate among various spectral signatures under different landscape patterns as well as a cost/benefit analysis considering the different steps performed by the operator performing a land cover/use map. it is suggested that a more systematic assessment of several options of implementation of a specific project is needed prior to beginning a land use/cover mapping job.