Benefits of and barriers to involving users in medical device technology development and evaluation

Objectives: This study investigated the benefits of, and barriers to user involvement in medical device technology development and evaluation. Methods: A structured review of published literature in peer-reviewed journals. Results: This review revealed that the main benefits of user involvement were an increased access to user needs, experiences and ideas; improvements in medical device designs and user interfaces; and an increase in the functionality, usability and quality of the devices. On the other hand, resource issues, particularly those of time and money were found the key impediments to involving users in the development and evaluation of medical device technologies. This study has categorised both the benefits and barriers to user involvement also. Conclusions: The involvement of users in MDTD&E requires resources, which are limited; however, it is essential from both users and manufacturers perspectives

A survey of statistical network models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Comment: 96 pages, 14 figures, 333 reference

Persistence with Mammography Screening and Stage at Breast Cancer Diagnosis among Elderly Appalachia-West Virginia Women

The objective of this study is to evaluate the association between persistence with mammography screening and stage at breast cancer diagnosis in elderly Appalachia-West Virginia women diagnosed with first incident breast cancer. The study utilized West Virginia Cancer Registry-Medicare linked database to identify women age 70 and above diagnosed with first incident breast cancer in 2007. Persistence to mammography screening was defined as having had at least three mammography screenings before breast cancer diagnosis. A multiple logistic regression was conducted to assess the association between persistence with mammography screening and stage at breast cancer diagnosis in these women. Of the 221 elderly Appalachia-West Virginia women included in the analysis, 113 women (51.1%) were persistent to mammography screening before their diagnosis with breast cancer. In a multiple logistic regression after adjusting for all the variables, as compared to elderly women who were not persistent with mammography screening, women who were persistent with mammography screening were significantly more likely to be diagnosed with early stage breast cancer (adjusted odds ratio=4.25, 95% confidence interval=1.96-9.19). Persistence with mammography screening is significantly associated with earlier stages of breast cancer in the rural and underserved Appalachia-West Virginia women. The study findings suggest targeting interventions to encourage regular mammography in these women for whom there are no clear guidelines

Permanent Draft Genome Sequence of Frankia sp. Strain BR, a Nitrogen-Fixing Actinobacterium Isolated from the Root Nodules of Casuarina equisetifolia

Frankia sp. strain BR is a member of Frankia lineage Ic and is able to reinfect plants of the Casuarinaceae family. Here, we report a 5.2-Mbp draft genome sequence with a G+C content of 70.0% and 4,777 candidate protein-encoding genes

The Effects of Biogeotextiles on the Stabilization of Roadside Slopes in Lithuania.

Soil erosion, Water erosion, Soil conservation, Geotextiles, Geotextile mats, Roadside slopes, Vegetation cover, Biogeotextiles , Palm mat geotextiles - Borassus aethiopum - Mauritia flexuosa - Buriti mats - BORASSUS Project - LithuaniaBiogeotextiles constructed from the leaves of Borassus aethiopum and Mauritia flexuosa are investigated at the Kaltinėnai Research Station of the Lithuanian Institute of Agriculture, which is participating in the EU-funded BORASSUS Project. Biogeotextiles are potentially excellent biodegradable and environmentally-friendly materials useful for soil conservation. Field studies on a steep (21–25°) roadside slope in Lithuania suggest biogeotextile mats are an effective and sustainable soil conservation technique. Biogeotextiles have a potential as a biotechnical soil conservation method for slope stabilization and protection from water erosion on steep industrial slopes and may be integrated with the use of perennial grasses to optimize protection from water erosion. The investigations demonstrated that a cover of Borassus and Buriti mats improved the germination and growth of sown perennial grasses. The biomass of perennial grasses increased by 52.0–63.4% under cover of Borassus mats and by 18.6–28.2% under cover of Buriti mats. Over 2 years, the biogeotextiles (Borassus and Buruti, respectively) decreased soil losses from bare fallow soil by 90.8% and 81.5% and from plots covered by perennial grasses by 87.9% and 79.0%, respectively

Multiangle social network recommendation algorithms and similarity network evaluation

Multiangle social network recommendation algorithms (MSN) and a new assessmentmethod, called similarity network evaluation (SNE), are both proposed. From the viewpoint of six dimensions, the MSN are classified into six algorithms, including user-based algorithmfromresource point (UBR), user-based algorithmfromtag point (UBT), resource-based algorithm fromtag point (RBT), resource-based algorithm from user point (RBU), tag-based algorithm from resource point (TBR), and tag-based algorithm from user point (TBU). Compared with the traditional recall/precision (RP) method, the SNE is more simple, effective, and visualized. The simulation results show that TBR and UBR are the best algorithms, RBU and TBU are the worst ones, and UBT and RBT are in the medium levels