Time filter

Source Type

DuPage County, IL, United States

Corrigan P.W.,Illinois Institute of Technology | Rafacz J.D.,Illinois Institute of Technology | Hautamaki J.,Illinois Institute of Technology | Walton J.,Illinois Institute of Technology | And 6 more authors.
Community Mental Health Journal | Year: 2010

In Our Own Voice (IOOV) is a 90-min anti-stigma program that comprises face-to-face stories of challenges of mental illness and hopes and dreams commensurate with recovery. We pared down IOOV to a 30-min version, using information from two focus groups. In this study, effects of 90- versus 30-min IOOV are contrasted with 30 min of education. Two hundred research participants were randomly assigned to one of these three conditions and completed a measure of stigmatizing perceptions and recollections. People in the education group remembered more negatives than the two IOOV groups. To control for overall response rate, a difference ratio was determined (difference in positive and negative recollection divided by overall recollections). Results showed the two IOOV conditions had significantly better ratios than education. These findings suggest the 30 min version of IOOV is as effective as the 90 min standard. © 2010 Springer Science+Business Media, LLC.

Kuleshov A.,Northumbria University | Mahkamov K.,Northumbria University | Kozlov A.,NAMI | Fadeev Y.,Moscow State Technical University
ASME 2014 Internal Combustion Engine Division Fall Technical Conference, ICEF 2014 | Year: 2014

There is increasing interest in application of various alternative fuels in marine diesel engines, including methanol. One of the challenges in the relevant research is the development of computer codes for simulation of the dual-fuel working process and engineering optimization of engines. In this work the mathematical model is described which simulates a mixture formation and combustion in an engine with a dual-fuel system, in which methanol is used as main fuel and a pilot portion of diesel oil is injected to ignite methanol. The developed combustion model was incorporated into the existing engine full cycle thermodynamic simulation tool, namely DIESEL-RK [1]. The developed combustion model includes the self-ignition delay calculation sub-model based on the detail chemistry simulation of methanol pre-combustion reactions, sub-model of evaporation of methanol droplets, submodels of methanol fuel sprays penetration, spray angle and droplets forming, respectively. The developed computer code allows engineers to account for the arbitrary shape of the combustion chamber. Additionally, each fuel system (for methanol and diesel oil) may include several injectors with arbitrary oriented nozzles with different diameters and central, off-central and side location in the combustion chamber. The fuel sprays evolution model consists of equations with dimensionless parameters to account for fuel properties and incylinder conditions. Specifics of injection pressure profiles and interaction of sprays with the air swirl and between themselves are also considered. The model allows engineers to carry out rapid parametric analysis. Results of modelling for a medium speed dual-fuel diesel engine are presented which demonstrate a good agreement between calculated and experimental heat release curves and integral engine data. © 2014 by ASME This research is supported by EU Marie-Curie International Incoming Fellowship Grant FP7-PEOPLE-2012-IIF/PIIF-GA-2012-328361. Authors would also like to thank VTT Technical Research Centre of Finland for making available experimental results which were used for evaluation of the modified mathematical model.


Nami | Date: 2015-02-12

Computer application software, namely, software for accessing a mobile-based social network designed for individuals living with mental health conditions and their family members and caregivers.

Pickett S.A.,University of Illinois at Chicago | Diehl S.,NAMI | Steigman P.J.,University of Illinois at Chicago | Prater J.D.,Tennessee Mental Health Consumers Association | And 2 more authors.
Psychiatric Rehabilitation Journal | Year: 2010

Objective: Peer-led education interventions have the potential to provide mental health consumers with the knowledge, skills and support they need to live successful and rewarding self-determined lives. However, few studies have explored whether and how these interventions enhance recovery. This study addresses this knowledge gap by examining changes among 160 participants in the Building Recovery of Individual Dreams and Goals (BRIDGES) education program. BRIDGES is a peer-led 8-week course taught by trained instructors who publicly disclose the fact that they are in recovery from mental illness. Method: Structured interviews assessing recovery outcomes were conducted with participants in the month prior to their receipt of BRIDGES, and immediately after receipt of the intervention. Paired f-tests were conducted to examine changes in psychiatric symptoms, hopefulness, social support, self-advocacy, empowerment, adaptive coping, and recovery pre-receipt and post-receipt of BRIDGES. Results: Post-receipt of BRIDGES, participants reported significantly fewer psychiatric symptoms, decreased use of maladaptive coping behaviors, and increased feelings of hopefulness, self-advocacy, empowerment, and recovery. Conclusions: These promising early results from our ongoing study of BRIDGES suggest that peer-led education interventions are a valuable resource. Additional research is needed to better understand the effectiveness of these interventions, including potential long-term post-program participation benefits. Copyright 2010 Trustees of Boston University.

News Article | August 29, 2016
Site: www.techtimes.com

For some odd reason, search companies feel the need to get involved in the self-driving car industry. Google is doing it, Baidu is doing it and Microsoft is also doing so to a degree. Now we have the top Russian search company making similar moves. Yandex is the number one search company in Russia, surpassing both Google and Bing for the top spot. Like Google, Yandex has dabbled outside of search. The company has its own email service and its own cloud hosting business, but now, it's seriously looking into the world of self-driving vehicles. According to a report from Fortune, Yandex has decided to partner with truck maker Kamaz, Daimler and government-sponsored researchers at NAMI in a bid to create a fleet of self-driving minibus shuttle. This could be the first step to something more interesting if it works out as planned. The report claims the self-driving minibus shuttle should be able to carry up to 12 people, and travel up to 124 miles on a single charge. Yandex will be contributing its expertise in artificial intelligence, voice recognition and computer vision to the project. Furthermore, the company will create the user interface of the app. NAMI plans to test the first set of self-driving buses on closed circuit roads come 2017. Due to the type of vehicle, it will likely take a number of years before any of these buses ever see the light of day on public streets. Seeing as other companies in other parts of the world have been testing self-driving vehicles for a number of years now, Yandex and NAMI might find themselves behind the curb when these self-driving vehicles begin to trickle out to the public's domain. If everything goes according to plan, we should look out for Yandex making moves to get its technology into other vehicles. Driverless cars have become a worldwide phenomenon, despite no such vehicles making it to public streets yet. Delphi and Mobileye have recently teamed up to bring self-driving cars to the market by 2019. Mobileye is known for providing the autonomous tech behind Tesla's fleet of vehicles, and was recently released by the company after a fatal crash. As for what's happening in China, search giant Baidu is working on its own fleet of driverless cars. The company recently unveiled an all-electric, self-driving car. Tests will begin soon, and if all goes well, the vehicle should hit public streets in a matter of years. © 2016 Tech Times, All rights reserved. Do not reproduce without permission.

Discover hidden collaborations