Artículos

ber that a closed subspace M of a real Banach space X is said to be an L2- summand subspace if there exists another closed subspace N of X verifying X = (M ® N)2 (that is, ¡m + n||2 = ||m||2 + ||n||2 for every m e M and every n g N.) The linear projection t?m of X onto M that fixes the elements of M and maps the elements of N to {0} is called the L2-summand projection of X onto M. For a wider perspective about L2-summand subspaces, see [1], [2], and [3]. A vector e of a real Banach space X is an L2-summand vector if Re is an L2- summand subspace. Furthermore, if e A 0 then there exists a functional e* in X*, which is called the L2-summand functional of e, such that ||e*|| = ||e||—1, e* (e) = 1, and 7TRe G) = e* (a:) e for every x £ X. The set of all L2-summand vectors of A' will be denoted by Lx- For a wider perspective about L2-summand vectors, see [1]. Let us recall two relevant results about L2-summand vectors402 pág

Patient Expectations and Health-Related Quality of Life Outcomes Following Total Joint Replacement

AbstractObjectivesPatient psychological factors have been linked to health-related quality of life (HRQoL) outcomes after total joint replacement (TJR). We evaluated the relationship between patient expectations before TJR, their fulfillment and HRQoL outcomes at 3 and 12 months after surgery.MethodsConsecutive patients preparing for TJR of the knee or hip due to primary osteoarthritis in 15 hospitals in Spain were recruited for the study. Patients completed questionnaires before surgery, and 3 and 12 months afterward: five questions about expectations before surgery and their fulfillment at 3 and 12 months; three HRQoL instruments—Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Short Form 12 (SF-12), and European Quality of Life Instrument (EQ-5D); as well as questions about sociodemographic information. Student's t test was used to assess the relationship between fulfillment of expectations and gains in HRQoL.ResultsA total of 881 patients took part in the study. Preintervention expectations for TJR ranged from 85% to 86% of patients, with high expectations for pain relief and ability to walk to 70% with high expectations about interacting with others. Patients who reported having fulfilled their expectations at 3 and 12 months had significantly greater gains in HRQoL than those who did not. Besides, we observed a statistically significant improvement in the percentage of patients who fulfill their expectations from 3 to 12 months.ConclusionsPatients have high expectations for the benefits of TJR, and those who fulfill their expectations have greater gains in HRQoL assessing by SF-12, WOMAC and EQ-5D. Health-care providers should help their patients develop realistic expectations about the impact of TJR

New battery model considering thermal transport and partial charge stationary effects in photovoltaic off-grid applications

The optimization of the battery pack in an off-grid Photovoltaic application must consider the minimum sizing that assures the availability of the system under the worst environmental conditions. Thus, it is necessary to predict the evolution of the state of charge of the battery under incomplete daily charging and discharging processes and fluctuating temperatures over day-night cycles. Much of previous development work has been carried out in order to model the short term evolution of battery variables. Many works focus on the on-line parameter estimation of available charge, using standard or advanced estimators, but they are not focused on the development of a model with predictive capabilities. Moreover, normally stable environmental conditions and standard charge-discharge patterns are considered. As the actual cycle-patterns differ from the manufacturer's tests, batteries fail to perform as expected. This paper proposes a novel methodology to model these issues, with predictive capabilities to estimate the remaining charge in a battery after several solar cycles. A new non-linear state space model is proposed as a basis, and the methodology to feed and train the model is introduced. The new methodology is validated using experimental data, providing only 5% of error at higher temperatures than the nominal one