University of Lisbon

About: University of Lisbon is a education organization based out in Lisbon, Lisboa, Portugal. It is known for research contribution in the topics: Population & Context (language use). The organization has 19122 authors who have published 48503 publications receiving 1102623 citations. The organization is also known as: Universidade de Lisboa & Lisbon University.

Depression Rating Scales in Parkinson’s Disease: Critique and Recommendations

Abstract: Depression is a common comorbid condition in Parkinson's disease (PD) and a major contributor to poor quality of life and disability. However, depression can be difficult to assess in patients with PD due to overlapping symptoms and difficulties in the assessment of depression in cognitively impaired patients. As several rating scales have been used to assess depression in PD (dPD), the Movement Disorder Society commissioned a task force to assess their clinimetric properties and make clinical recommendations regarding their use. A systematic literature review was conducted to explore the use of depression scales in PD and determine which scales should be selected for this review. The scales reviewed were the Beck Depression Inventory (BDI), Hamilton Depression Scale (Ham-D), Hospital Anxiety and Depression Scale (HADS), Zung Self-Rating Depression Scale (SDS), Geriatric Depression Scale (GDS), Montgomery-Asberg Depression Rating Scale (MADRS), Unified Parkinson's Disease Rating Scale (UPDRS) Part I, Cornell Scale for the Assessment of Depression in Dementia (CSDD), and the Center for Epidemiologic Studies Depression Scale (CES-D). Seven clinical researchers with clinical and research experience in the assessment of dPD were assigned to review the scales using a structured format. The most appropriate scale is dependent on the clinical or research goal. However, observer-rated scales are preferred if the study or clinical situation permits. For screening purposes, the HAM-D, BDI, HADS, MADRS, and GDS are valid in dPD. The CES-D and CSDD are alternative instruments that need validation in dPD. For measurement of severity of depressive symptoms, the Ham-D, MADRS, BDI, and SDS scales are recommended. Further studies are needed to validate the CSDD, which could be particularly useful for the assessment of severity of dPD in patients with comorbid dementia. To account for overlapping motor and nonmotor symptoms of depression, adjusted instrument cutoff scores may be needed for dPD, and scales to assess severity of motor symptoms (e.g., UPDRS) should also be included to help adjust for confounding factors. The HADS and the GDS include limited motor symptom assessment and may, therefore, be most useful in rating depression severity across a range of PD severity; however, these scales appear insensitive in severe depression. The complex and time-consuming task of developing a new scale to measure depression specifically for patients with PD is currently not warranted.

DepSky: Dependable and Secure Storage in a Cloud-of-Clouds

Abstract: The increasing popularity of cloud storage services has lead companies that handle critical data to think about using these services for their storage needs. Medical record databases, large biomedical datasets, historical information about power systems and financial data are some examples of critical data that could be moved to the cloud. However, the reliability and security of data stored in the cloud still remain major concerns. In this work we present DepSky, a system that improves the availability, integrity, and confidentiality of information stored in the cloud through the encryption, encoding, and replication of the data on diverse clouds that form a cloud-of-clouds. We deployed our system using four commercial clouds and used PlanetLab to run clients accessing the service from different countries. We observed that our protocols improved the perceived availability, and in most cases, the access latency, when compared with cloud providers individually. Moreover, the monetary costs of using DepSky in this scenario is at most twice the cost of using a single cloud, which is optimal and seems to be a reasonable cost, given the benefits.

How does knowledge management influence innovation and competitiveness

Abstract: Is concerned with human value management, examines the relationships between organizations’ competitiveness, innovation advancements, and knowledge management and presents a set of considerations regarding how these relationships affect strategic management and the formulation of competitive strategies. By considering how knowledge development is related with personal characteristics and personal development, this article attempts to provide useful insights on the linkages between innovation and competitiveness. These considerations point out the importance of knowledge development and the role of knowledge management in order to assure competitiveness. This work proposes also a conceptual model, with special focus on the relationships between knowledge management, competitiveness, and innovation. The major factors are presented and directions for future research are suggested according to the proposed model.

The role of communication and trust in explaining customer loyalty: An extension to the ECSI model

Abstract: Loyalty has, over the past decade, become a crucial construct in marketing, and particularly in the burgeoning field of customer relationship management. This paper shows that customer loyalty can be explained to a substantial degree by customer satisfaction, trust, and communication, and shows the direct and indirect effects among those constructs and other constructs in an extension of the European Customer Satisfaction Index (ECSI) model. Both ECSI model and the extended model are estimated with data from a survey carried out among customers of the banking sector. Within the limitations of the study, the theoretical and managerial implications of these findings are discussed.