To develop an arterial injury model for testing hemostatic devices at well-defined high and low bleeding rates.A side-hole arterial injury was created in the carotid artery of sheep. Shed blood was collected in a jugular venous reservoir and bleeding rate at the site of arterial injury was controlled by regulating outflow resistance from the venous reservoir. Two models were studied: uncontrolled exsanguinating hemorrhage and bleeding at controlled rates with blood return to maintain hemodynamic stability. Transcutaneous Duplex ultrasound was used to characterize ultrasound signatures at various bleeding rates.A 2.5 mm arterial side-hole resulted in exsanguinating hemorrhage with an initial bleeding rate of 400 ml/min which, without resuscitation, decreased to below 100 ml/min in 5 minutes. After 17 minutes, bleeding from the injury site stopped and the animal had lost 60% of total blood volume. Reinfusion of shed blood maintained normal hemodynamics and both high and low bleeding rates could be maintained without hemorrhagic shock. Bleeding rate at the arterial injury site was held at 395±78 ml/min for 8 minutes, 110±11 ml/min for 15 minutes, and 12±1 ml/min for 12 minutes. Doppler flow signatures at the site of injury were characterized by high peak and end-diastolic flow velocities at the bleeding site which varied with the rate of hemorrhage.We have developed a hemodynamically stable model of acute arterial injury which can be used to evaluate diagnostic and treatment methods focused on control of the arterial injury site.
The mouths of children of Redbud bled, though, because of poor nutrition and because there was no money for dental care. Scholars who study persuasion tactics know that language can generate fear. If peddlers are hired to speak in favour of the privatization of schools— and there is no reason to expect that they won't be or already are— economic influences on learning will be given short shrift. "The teacher respects learners as individuals with differing personal and family backgrounds and various skills, abilities, perspectives, talents, and interests". The teacher understands that learners bring assets for learning based on their individual experiences, abilities, talents, prior learning, and peer and social group interactions, as well as language, culture, family, and community values". Soto-Manning referred to contemporary teachers as "technicians" who work with standardized curricula rather than as professionals who have opportunities for innovation in their work.
Article Free Access Share on Using a computer-based tool to support collaboration: a field experiment Authors: Bonnie Johnson Corporate Technology Planning - Aetna Life & Casualty Corporation Corporate Technology Planning - Aetna Life & Casualty CorporationView Profile , Geraldine Weaver Corporate Technology Planning - Aetna Life & Casualty Corporation Corporate Technology Planning - Aetna Life & Casualty CorporationView Profile , Margrethe H. Olson New York University New York UniversityView Profile , Robert Dunham MCC Conference on Computer Support for Cooperative Work, Austin, Texas MCC Conference on Computer Support for Cooperative Work, Austin, TexasView Profile , Grady McGonagill MCC Conference on Computer Support for Cooperative Work, Austin, Texas MCC Conference on Computer Support for Cooperative Work, Austin, TexasView Profile Authors Info & Claims CSCW '86: Proceedings of the 1986 ACM conference on Computer-supported cooperative workDecember 1986 Pages 343–352https://doi.org/10.1145/637069.637114Published:03 December 1986Publication History 11citation454DownloadsMetricsTotal Citations11Total Downloads454Last 12 Months37Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Purpose: To determine whether variations in aortic wall motion exist in mammalian species other than humans and to consider the potential implications of such variations. Methods: M-mode ultrasound was used to measure abdominal aortic wall motion in 4 animal species [mice (n=10), rats (n=8), rabbits (n=7), and pigs (n=5)], and humans (n=6). Anterior wall displacement, posterior wall displacement, and diastolic diameter were measured. The ratio of displacement to diameter and cyclic strain were calculated. Results: Body mass varied from 24.1±2.4 g (mouse) to 61.8±13.4 kg (human); aortic diameter varied from 0.53±0.07 mm (mouse) to 1.2±1 mm (human). Anterior wall displacement was 2.5 to 4.0 times greater than posterior among the species studied. The ratios of wall displacement to diastolic diameter were similar for the anterior (range 9.40%–11.80%) and posterior (range 2.49%–3.91%) walls among species. The ratio of anterior to posterior displacement (range 2.47–4.03) and aortic wall circumferential cyclic strain (range 12.1%–15.7%) were also similar. An allometric scaling exponent was experimentally derived relating anterior wall (0.377±0.032, R 2 =0.94) and posterior wall (0.378±0.037, R 2 =0.93) displacement to body mass. Conclusion: Abdominal aortic wall dynamics are similar in animals and humans regardless of aortic size, with more anterior than posterior wall motion. Wall displacement increases linearly with diameter, but allometrically with body mass. These data suggest increased dynamic strain of the anterior wall. Increased strain, corresponding to increased elastin fatigue, may help explain why human abdominal aortic aneurysms initially develop anteriorly. Aortic wall motion should be considered when developing endovascular devices, since asymmetric motion may affect device migration, fixation, and sealing.
Advances in computational thinking and data science have led to a new era of artificial intelligence systems being engineered to adapt to complex situations and develop actionable knowledge. These learning systems are meant to reliably understand the essence of a situation and construct critical decision recommendations to support autonomous and human–machine teaming operations. In parallel, the increasing volume, velocity, variety, veracity, value, and variability of data is confounding the complexity of these new systems – creating challenges in terms of their development and implementation. For artificial systems supporting critical decisions with higher consequences, safety has become an important concern. Methods are needed to avoid failure modes and ensure that only desired behavior is permitted. This paper discusses an approach that promotes self-awareness, or metacognition, within the artificial intelligence systems to understand their external and internal operational environments and use this knowledge to identify potential failures and enable self-healing and self-management for safe and desired behavior.
