Three Dimensional Quantification of Angiotensin II-Induced Murine Abdominal Aortic Aneurysms Using High Frequency Ultrasound

Abdominal aortic aneurysms (AAAs), a localized dilation of the vessel wall of 50% or more above normal, claims approximately 14,000 U.S. lives yearly due to aortic rupture. This commonly asymptomatic disease can only be treated by endovascular stent grafts or invasive surgery, usually after the AAA diameter reaches 5 cm. Because these treatment methods carry serious risk, stem cell therapy is being explored in order to provide a low risk option for managing smaller AAAs. To determine if stem cell therapy, once administered, could stabilize or reduce AAA growth, baseline 3D ultrasound measurements in a control group were first needed. High frequency ultrasound was used on apolipoprotein E-deficient (apoE-/-) mice given angiotensin II (AngII) from subcutaneously implanted osmotic mini pumps. This mouse model developed dissecting AAAs, containing a false and true lumen, which were clearly visualized and quantified using 3D ultrasound imaging. With this ultrasound technique, we found that aneurysm diameter, total volume, and false lumen volume all increased steadily over a period of 28 days once AAAs formed. These data suggest our noninvasive, 3D ultrasound technique can be used to monitor the progression of aneurysms that may be delayed once stem cell therapy is administered

OPEN COMMUNITY HEALTH: WORKSHOP REPORT

This report summarizes key outcomes from a workshop on open community health conducted at the University of Nebraska at Omaha in April 2018. Workshop members represented research and practice communities across Citizen Science, Open Source, and Wikipedia. The outcomes from the workshop include (1) comparisons among these communities, (2) how a shared understanding and assessment of open community health can be developed, and (3) a taxonomical comparison to begin a conversation between these communities that have developed disparate languages

Prediction models for diagnosis and prognosis of covid-19: : systematic review and critical appraisal

Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity. Funding: LW, BVC, LH, and MDV acknowledge specific funding for this work from Internal Funds KU Leuven, KOOR, and the COVID-19 Fund. LW is a postdoctoral fellow of Research Foundation-Flanders (FWO) and receives support from ZonMw (grant 10430012010001). BVC received support from FWO (grant G0B4716N) and Internal Funds KU Leuven (grant C24/15/037). TPAD acknowledges financial support from the Netherlands Organisation for Health Research and Development (grant 91617050). VMTdJ was supported by the European Union Horizon 2020 Research and Innovation Programme under ReCoDID grant agreement 825746. KGMM and JAAD acknowledge financial support from Cochrane Collaboration (SMF 2018). KIES is funded by the National Institute for Health Research (NIHR) School for Primary Care Research. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. GSC was supported by the NIHR Biomedical Research Centre, Oxford, and Cancer Research UK (programme grant C49297/A27294). JM was supported by the Cancer Research UK (programme grant C49297/A27294). PD was supported by the NIHR Biomedical Research Centre, Oxford. MOH is supported by the National Heart, Lung, and Blood Institute of the United States National Institutes of Health (grant R00 HL141678). ICCvDH and BCTvB received funding from Euregio Meuse-Rhine (grant Covid Data Platform (coDaP) interref EMR187). The funders played no role in study design, data collection, data analysis, data interpretation, or reporting.Peer reviewedPublisher PD

Investigating Information: A qualitative analysis of designers’ information representation and structuring behaviors

Information plays a vital role in society, business and daily life. Similarly, information utilization and organization are integral to the design and development of creative ideas. Studies have shown that information utilized in the design process takes on a variety of characteristics, dimensions and forms. Navigating this sea of information can be challenging, even for experienced designers. Therefore, deep analysis of how designers utilize and organize information will provide qualitative insights into their information representation and information structuring behaviors. To accomplish this, three professionals in the software design and development field in the Omaha area were recruited for individual 3-hour design sessions. During this session, the designers were asked to generate ideas for a simple design problem (reducing pedestrian accidents in Omaha). They were asked to only use the provided design information, which was specifically created for this study by the researchers using rigorous pilot testing. The 16 pieces of information were based on the previously developed Typological Framework of Design Information. The study results shed light on how designers conceptualize and organize design information during the early phases of the design proces

Blinded by function? Investigating implicit trust behavior towards home automation devices

Trust has been shown to play arole in information technologyadoption and usage. One example of technology that has been becoming more popular is the home automation field due to its ambitions of improving the daily lives of its residents byproviding them with comfort, healthcare, energy efficiency, and security benefits. These devices require close interaction with its users to achieve these goals, yet there is relatively littleresearch that clearly links user trust with home automationdevices. Therefore, the purpose of this study is to empirically explore the influence of design considerations on the perceived trustworthiness of a home automation device. Specifically, this study will utilize a web-based smart lock simulation and one-liner scenarios to investigate user’s trust behavior towards that smart lock. Trust behavior was measured using user data that was automatically captured as users interacted with the smart lock simulation. Preliminary analysis was conducted on the log data using the automation location (office / home) and the gender of the agent’s voice (female / male) as design variables. The findings shed light on users actual and perceived trust behavior towards a home automation device

From information to ideas: how designers structure information to support idea generation

This abstract has been removed to protect the intellectual property of the project

Designing For Trust: Factors Influencing User Perceptions of Trust in Home Automa

The potential of smart home devices for improving the comfort, convenience, and security of its residents has been noted by researchers and adopters of these technologies. In addition, home automation devices have the ability increase energy efficiency and save costs, leading to increasing adoption of these devices. Despite these advantages and advances in home automation technology, their adoption has not been as widespread as anticipated by experts. Existing research has shown that the lack of trust in home devices is a significant deterrent to widespread adoption. This perceived trustworthiness of the system can be impacted by the location that the device operates in, and the perceived gender of the automated agent within the device. However, there is little data on how these factors may affect the perceived trustworthiness of a home automation system, or how to best design products that respond to these variations in trust. Therefore, this study addresses this knowledge gap by exploring the role of agent location and gender on perceptions of trustworthiness in a controlled laboratory setting. The results of this study shed light on users’ perceptions of trust with home automation devices, and provide directions for future research and development of trustworthy home automation devices

Identifying Smart City Leaders and Followers with Machine Learning

Smart cities have been a popular topic for the city stakeholders. A smart city is the next urban lifestyle that citizens expect. Due to the hypercompetitive and globalized economy, many cities have already started or are about to start their smart city projects. There is no uniform benchmark to evaluate the smart cities’ performance. Several organizations use their own indicators to evaluate smart cities worldwide or nationwide. This research paper leverages fuzzy logic to label smart city leaders and followers based on various organization’s evaluation meta results and then uses machine learning techniques to identify the key characteristics of leaders and followers. Based on the training data performance, the Support Vector Machine (SVM) is used to predict who will be the next smart city leader or follower. According to the proposed prediction framework, we have successfully predicted 30 smart city leaders and 20 followers