Telling stories of culture through literature

Grounded on Raymond Williams‘s definition of knowable community as a cultural tool to analyse literary texts, the essay reads the texts D.H.Lawrence wrote while travelling in the Mediterranean (Twilight in Italy, Sea and Sardinia and Etruscan Places) as knowable communities, bringing to the discussion the wide importance of literature not only as an object for aesthetic or textual readings, but also as a signifying practice which tells stories of culture. Departing from some considerations regarding the historical development of the relationship between literature and culture, the essay analyses the ways D. H. Lawrence constructed maps of meaning, where the readers, in a dynamic relation with the texts, apprehend experiences, structures and feelings; putting into perspective Williams‘s theory of culture as a whole way of life, it also analyses the ways the author communicates and organizes these experiences, creating a space of communication and operating at different levels of reality: on the one hand, the reality of the whole way of Italian life, and, on the other hand, the reality of the reader who aspires to make sense and to create an interpretative context where all the information is put, and, also, the reality of the writer in the poetic act of writing. To read these travel writings as knowable communities is to understand them as a form that invents a community with no other existence but that of the literary text. The cultural construction we find in these texts is the result of the selection, and interpretation done by D.H.Lawrence, as well as the product of the author‘s enunciative positions, and of his epistemological and ontological filigrees of existence, structured by the conditions of possibility. In the rearticulation of the text, of the writer and of the reader, in a dynamic and shared process of discursive alliances, we understand that Lawrence tells stories of the Mediterranean through his literary art.

Quality of Life Predictors and Normative Data

This study identifies predictors and normative data for quality of life (QOL) in a sample of Portuguese adults from general population. A cross-sectional correlational study was undertaken with two hundred and fifty-five (N = 255) individuals from Portuguese general population (mean age 43 years, range 25–84 years; 148 females, 107 males). Participants completed the European Portuguese version of the World Health Organization Quality of Life short-form instrument and the European Portuguese version of the Center for Epidemiologic Studies Depression Scale. Demographic information was also collected. Portuguese adults reported their QOL as good. The physical, psychological and environmental domains predicted 44 % of the variance of QOL. The strongest predictor was the physical domain and the weakest was social relationships. Age, educational level, socioeconomic status and emotional status were significantly correlated with QOL and explained 25 % of the variance of QOL. The strongest predictor of QOL was emotional status followed by education and age. QOL was significantly different according to: marital status; living place (mainland or islands); type of cohabitants; occupation; health. The sample of adults from general Portuguese population reported high levels of QOL. The life domain that better explained QOL was the physical domain. Among other variables, emotional status best predicted QOL. Further variables influenced overall QOL. These findings inform our understanding on adults from Portuguese general population QOL and can be helpful for researchers and practitioners using this assessment tool to compare their results with normative data

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.