Effect of fiber alignment in gelled electrospun membranes based on poly(vinylidene fluoride) for battery applications

Battery separators based on electrospun membranes of poly(vinylidene fluoride) (PVDF) have been prepared in order to study the effect of fiber alignment on the performance and characteristics of the membrane. The prepared membranes show an average fiber diameter of 272 nm and a degree of porosity of 87 %. The gel polymer electrolytes are prepared by soaking the membranes in the electrolyte solution. The alignment of the fibers improves the mechanical properties for the electrospun membranes. Further, the microstructure of the membrane also plays an important role in the ionic conductivity, being higher for the random electrospun membrane due to the lower tortuosity value. Independently of the microstructure, both membranes show good electrochemical stability up to 5.0 V versus Li/Li+. These results show that electrospun membranes based on PVDF are appropriate for battery separators in lithium-ion battery applications, the random membranes showing a better overall performance.

Conditioning information in mutual fund performance evaluation: Portuguese evidence

We estimate and compare the performance of Portuguese-based mutual funds that invest in the domestic market and in the European market using unconditional and conditional models of performance evaluation. Besides applying both partial and full conditional models, we use European information variables, instead of the most common local ones, and consider stochastically detrended conditional variables in order to avoid spurious regressions. The results suggest that mutual fund managers are not able to outperform the market, presenting negative or neutral performance. The incorporation of conditioning information in performance evaluation models is supported by our findings, as it improves the explanatory power of the models and there is evidence of both time-varying betas and alphas related to the public information variables. It is also shown that the number of lags to be used in the stochastic detrending procedure is a critical choice, as it will impact the significance of the conditioning information. In addition, we observe a distance effect, since managers who invest locally seem to outperform those who invest in the European market. However, after controlling for public information, this effect is slightly reduced. Furthermore, the results suggest that survivorship bias has a small impact on performance estimates.

Real-time 3D interactive segmentation of echocardiographic data through user-based deformation of B-spline explicit active surfaces

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.

Effect of fiber orientation in gelled poly (vinylience fluoride) electrospun membranes for Li-ion battery applications

Battery separators based on electrospun membranes of poly(vinylidene fluoride) (PVDF) have been prepared in order to study the effect of fiber alignment on the performance and characteristics of the membrane. The prepared membranes show an average fiber diameter of ~272 nm and a degree of porosity of ~87 %. The gel polymer electrolytes are prepared by soaking the membranes in the electrolyte solution. The alignment of the fibers improves the mechanical properties for the electrospun membranes. Further, the microstructure of the membrane also plays an important role in the ionic conductivity, being higher for the random electrospun membrane due to the lower tortuosity value. Independently of the microstructure, both membranes show good electrochemical stability up to 5.0 V versus Li/Li+. These results show that electrospun membranes based on PVDF are appropriate for battery separators in lithium-ion battery applications, the random membranes showing a better overall performance.

Information technology supporting healthcare and social care services

The authors are developing a pilot project for a Municipality in the North of Portugal, envisaging the definition and implementation of an e-marketplace for healthcare and social services, in order to facilitate the interaction between healthcare and social services professionals and people with special needs (or their relatives). Based on the results of a survey on user needs analysis and expectations conducted in 2011, the paper discusses the relevance and interest of such platforms and the main drivers and motivations of the population for using such services, as well as which services would motivate citizens to use the platform. The results of the study will be used to select the products and services perceived to be the most desired by the potential users. The paper thus makes three main contributions: (1) the results of the study confirm the interest and the perceived potential of such a service, from the end-users perspective; (2) the findings support the advantage of expanding this pilot project to a full scale implementation; and (3) the performed analysis improves our understanding of the relations between the characteristics of the inquired population and the perceived interest in such platforms.

Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.