Integrating the voices of ordinary peopel in the understanding of well-being

The aim of this communication in the II Scientific Meeting in Psychology is to present some of the research, that is being done at the University of Évora, around the construct of Well-being, and to discuss the importance of integrating the voices of ordinary people in the understanding of Well-being. We will invite and argue for qualitative research that includes and facilitates our research participants’ thoughtful contributions about Well-being, in a rigorous and system- atic way. We will also briefly discuss some findings of a previous study, about former psychotherapy patients perspectives about Well-being, to empirically illustrate our thoughts.FC

Digital Image Analysis of Actinomycetes Colonies as a Potential Aid for Rapid Taxonomic Identification

High frequency isolation of actinomycetes poses a challenge for the taxonomists hence simple and rapid identification methods are required. Our work to catalogue biodiversity of actinomycetes of Goa yielded several distinct morphotypes. After their tentative identification, the feasibility to distinguish these using digital image analyses (DIA) was explored. Digital images of wild colony morphotypes were processed using public domain SCION image analysis software. DIA revealed some intricate digital characters. A combination of these with standard morphological and microscopic characters could be potentially useful for preparing a digital identification key of the actinomycetes strains with potential application in rapid taxonomic identification

Exploring hidden dimensions of soil fungal biodiversity: A simple technique to detect soil fungi resistant to antifungal compounds

Soils are known to be ultimate and complex reservoirs of microbial diversity. The complex dimensions of bacterial and fungal diversity in tropical soils and microbial community dynamics are underexplored. Isolation techniques aimed at Actinomycetes generally employ highly selective media, powerful antibiotics and antifungal compounds to suppress undesirable bacteria and fungi. However some soil fungi may show their resistance towards these antifungal compounds. During our work to explore soil actinomycetes diversity, slides coated with Arginine Vitamin agar (AVA) incorporating a cocktail of antibiotics and antifungal compounds such as Nystatin, Cycloheximide, Terbinafin, Griseofulvin, and Fluconazole were exposed to soil environment and were retrieved at intervals of 4, 7, 15 and 28 days for detail microscopic studies of surface colonies. Along with actinomycetes the presence of unidentified aseptate and septate fungi was revealed indicating their resistance to combination and concentration of antifungals. Heat treatment of the soil was found to cause considerable decrease in fungal contamination probably due to elimination of heat labile fungi. Our results have led us to develop a simple procedure to sample the interesting and industrially useful strains of soil fungi resistant to common antifungal compounds. Some fungal strains are reported resistant to certain antifungals with resulting therapeutic failures as use of these antifungals inevitably selects resistant fungi, thereby pressing the urge for continuing and cyclical need of new antifungals (Augustin et al., 2004). This technique could prove useful to detect novel antifungal resistant strains with potential to emerge as novel human pathogens. It has not escaped our notice that the probability of such finding could also help to verify whether these fungi could utilize such antifungal compounds through use of hitherto undiscovered metabolic pathways and novel enzymes leading to identification of genes responsible for antifungal resistance

Day-night differences in Cunene horse mackerel (Trachurus trecae) acoustic relative densities off Angola

The assessment and the management of the Cunene horse mackerel in Angola rely heavily on abundance estimates from hydroacoustic surveys. Acoustic data collected from 1994 to 1999 were analysed to quantify diurnal variation in relative acoustic densities at 38 kHz. The nautical-area scattering coefficient (s(A), m(2) nautical mile(-2)) was characterized by clear day night differences: s(A) values recorded during the day were significantly higher (mean s(A): 135 m(2) nautical mile(-2)) than the corresponding night-time values (mean s(A) 83 m(2) nautical mile(-2)). This pattern is associated with differences in behaviour and horizontal and vertical distributions between day and night: by day, the fish school near the seabed, and by night, they move into the pelagic zone and disperse into widespread scattering layers. More than 40% of the total backscatter by day originated from the bottom 10 m, but at night this proportion decreased to <10%. The findings demonstrate considerable influences of behaviour and aggregation dynamics on acoustic measurements. Possible implications for the estimates of acoustic abundance are discussed in the light of the differences.Norwegian Agency for Development Cooperation (NORAD); Dr Fridtjof Nansen programme; Gulbenkian Foundationinfo:eu-repo/semantics/publishedVersio

Dual two-state mean-field games

In this paper, we consider two-state mean-field games and its dual formulation. We then discuss numerical methods for these problems. Finally, we present various numerical experiments, exhibiting different behaviours, including shock formation, lack of invertibility, and monotonicity loss

Data Assimilation by Artificial Neural Networks for an Atmospheric General Circulation Model: Conventional Observation

This paper presents an approach for employing artificial neural networks (NN) to emulate an ensemble Kalman filter (EnKF) as a method of data assimilation. The assimilation methods are tested in the Simplified Parameterizations PrimitivE-Equation Dynamics (SPEEDY) model, an atmospheric general circulation model (AGCM), using synthetic observational data simulating localization of balloon soundings. For the data assimilation scheme, the supervised NN, the multilayer perceptrons (MLP-NN), is applied. The MLP-NN are able to emulate the analysis from the local ensemble transform Kalman filter (LETKF). After the training process, the method using the MLP-NN is seen as a function of data assimilation. The NN were trained with data from first three months of 1982, 1983, and 1984. A hind-casting experiment for the 1985 data assimilation cycle using MLP-NN were performed with synthetic observations for January 1985. The numerical results demonstrate the effectiveness of the NN technique for atmospheric data assimilation. The results of the NN analyses are very close to the results from the LETKF analyses, the differences of the monthly average of absolute temperature analyses is of order 0.02. The simulations show that the major advantage of using the MLP-NN is better computational performance, since the analyses have similar quality. The CPU-time cycle assimilation with MLP-NN is 90 times faster than cycle assimilation with LETKF for the numerical experiment.Comment: 17 pages, 16 figures, monthly weather revie