Browsing by Author "Morais, A."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
- P-1186 - The recovery process of persons living with psychiatric disabilities: values and principles of nova aurora community association psychosocial rehabilitation programPublication . Marques, António; Morais, A.; Campos, Filipa; Silva, M.; Silva, L.; Almeida, R.The Nova Aurora Community Association psychosocial rehabilitation program was developed based in the most current values of Psychosocial Rehabilitation. Some nuclear assumptions were considered, such as a) suppressing the disease stigma, b) defocusing from the mental ill role, promoting empowerment and self-determination, c) developing personal competencies directly related to the individuals’ social integration specific context (readiness, cognitive, social, emotional stress management, employability).
- Polymorphisms and haplotypes of TOLLIP and MUC5B are associated with susceptibility and survival in patients with fibrotic hypersensitivity pneumonitisPublication . Mota, P.C.; Soares, M.L.; Ferreira, A.C.; F. Santos, Rita; Cavaleiro Rufo, J; Vasconcelos, D.; Carvalho, A.; Guimarães, S.; Vasques-Novo, F.; Cardoso, C.; Melo, N.; Alexandre, A.T.; Coelho, D.; Novais-Bastos, H.; Morais, A.Hypersensitivity pneumonitis (HP) is an interstitial lung disease with diverse clinical features that can present a fibrotic phenotype similar to idiopathic pulmonary fibrosis (IPF) in genetically predisposed individuals. While several single nucleotide polymorphisms (SNPs) have been associated with IPF, the genetic factors contributing to fibrotic HP (fHP) remain poorly understood. This study investigated the association of MUC5B and TOLLIP variants with susceptibility, clinical presentation and survival in Portuguese patients with fH. A case-control study was undertaken with 97 fHP patients and 112 controls. Six SNPs residing in the MUC5B and TOLLIP genes and their haplotypes were analyzed. Associations with risk, survival, and clinical, radiographic, and pathological features of fHP were probed through comparisons among patients and controls. MUC5B rs35705950 and three neighboring TOLLIP variants (rs3750920, rs111521887, and rs5743894) were associated with increased susceptibility to fHP. Minor allele frequencies were greater among fHP patients than in controls (40.7% vs 12.1%, P<0.0001; 52.6% vs 40.2%, P = 0.011; 22.7% vs 13.4%, P = 0.013; and 23.2% vs 12.9%, P = 0.006, respectively). Haplotypes formed by these variants were also linked to fHP susceptibility. Moreover, carriers of a specific haplotype (G-T-G-C) had a significant decrease in survival (adjusted hazard ratio 6.92, 95% CI 1.73–27.64, P = 0.006). Additional associations were found between TOLLIP rs111521887 and rs5743894 variants and decreased lung function at baseline, and the MUC5B SNP and radiographic features, further highlighting the influence of genetic factors in fHP. These findings suggest that TOLLIP and MUC5B variants and haplotypes may serve as valuable tools for risk assessment and prognosis in fibrotic hypersensitivity pneumonitis, potentially contributing to its patient stratification, and offer insights into the genetic factors influencing the clinical course of the condition.
- Using decision tree to select forecasting algorithms in distinct electricity consumption context of an office buildingPublication . Ramos, D.; Faria, Pedro; Morais, A.; Vale, ZitaThe flexibility and management in the storage and control of building expertise in the energy optimization can be enhanced with the support of algorithms involved in forecasting tasks. These play an important role on obtaining anticipated and accurate consumption predictions associated to different contexts through extensive consumption patterns analysis. This paper evaluates the most viable forecasting algorithm for consumption predictions of a building in different contexts according to two alternatives: artificial neural networks and k-nearest neighbors. These algorithms use patterns of data from consumptions integrated in different contexts while retaining additional information from sensors data. The different contexts are classified on a sequence of periods that take place from five-to-five minutes. The decision criterion to evaluate which of the two forecasting algorithms is the most suitable in each five minutes periods is supported with decision trees that select the forecasting algorithms that looks to be more suitable followed by a logical answer that clarifies if the selection was the most viable option. Parameterization updates concerning the depth are studied to understand the forecasting accuracy impact. The decision trees approach has the potential to improve the accuracy of prediction as it plays a promising role in decision making.