scholarly journals The rise of private–public collaboration in nanotechnology

Nano Today ◽  
2019 ◽  
Vol 25 ◽  
pp. 7-9 ◽  
Author(s):  
Raphael Zingg ◽  
Marius Fischer
Keyword(s):  
Public Collaboration

scholarly journals Private-Public Collaboration to Reintroduce Fire into the Changing Ecosystems of the Southwestern Borderlands Region

Fire Ecology ◽  
2009 ◽  
Vol 5 (1) ◽  
pp. 85-99 ◽  
Author(s):  
Gerald J. Gottfried ◽  
Larry S. Allen ◽  
Peter L. Warren ◽  
Bill McDonald ◽  
Ronald J. Bemis ◽  
...  
Keyword(s):  
Public Collaboration ◽  
Southwestern Borderlands

scholarly journals Review of the Content and Quality of Mobile Applications About Alzheimer’s Disease and Related Dementias

2018 ◽  
Vol 39 (6) ◽  
pp. 601-608 ◽  
Author(s):  
Seul Ki Choi ◽  
Brooks Yelton ◽  
Victor K. Ezeanya ◽  
Kristie Kannaley ◽  
Daniela B. Friedman
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Health Care ◽  
Health Care Providers ◽  
Mobile Applications ◽  
Rating Scale ◽  
Care Providers ◽  
Technical Functions ◽  
Public Collaboration

This study reviewed the content of mobile applications (apps) providing Alzheimer’s disease or related dementias (ADRD) information and assessed quality of the apps. Characteristics, content, and technical aspects of 36 apps in the U.S. Google Play Store and App Store were coded, and quality of the apps was evaluated using the Mobile Application Rating Scale. Caregiving (62.1%) and disease management (55.6%) content was frequently provided. Few apps had an app community (8.3%) or a reminder function (8.3%). Overall, quality of the apps was acceptable; apps by health care–related developers had higher quality scores than those by non-health care–related developers. This analysis showed that ADRD-related apps provide a range of content and have potential to benefit caregivers, individuals with ADRD, health care providers, and the general public. Collaboration of ADRD experts and technology experts is needed to provide evidence-based information using effective technical functions that make apps to meet users’ needs.

Openness in Private-Public Collaboration

Science ◽  
1999 ◽  
Vol 284 (5417) ◽  
pp. 1123d-1123
Author(s):  
R. O. McClellan
Keyword(s):  
Public Collaboration

Police Misconduct and Political Legitimacy in Central America

2015 ◽  
Vol 47 (2) ◽  
pp. 251-283 ◽  
Author(s):  
JOSÉ MIGUEL CRUZ
Keyword(s):  
Central America ◽  
Police Officers ◽  
Public Support ◽  
Political Legitimacy ◽  
Political Regime ◽  
The Political ◽  
Police Misconduct ◽  
Police Corruption ◽  
Political Impact ◽  
Public Collaboration

AbstractWhat is the political impact of police corruption and abuse? From the literature, we know that police misconduct destroys people's confidence in police forces and hampers public collaboration with the criminal-justice system; but, what about the political regime, especially in countries striving for democratic governance? Does police wrongdoing affect the legitimacy of the overall regime? Focusing on Central America, this article provides empirical evidence showing that corruption and abuse perpetrated by police officers erode public support for the political order. Results indicate that, under some circumstances, police transgressions can have a greater impact on the legitimacy of the political system than crime or insecurity. They also show that police misconduct not only affects democratising regimes, such as El Salvador and Guatemala, but also consolidated democracies, such as Costa Rica.

scholarly journals FL-QSAR: a federated learning based QSAR prototype for collaborative drug discovery

2020 ◽  
Author(s):  
Shaoqi Chen ◽  
Dongyu Xue ◽  
Guohui Chuai ◽  
Qiang Yang ◽  
Qi Liu
Keyword(s):  
Drug Discovery ◽  
Quantitative Structure Activity Relationship ◽  
Privacy Preserving ◽  
Qsar Modeling ◽  
Qsar Analysis ◽  
Source Codes ◽  
Shared Information ◽  
Financial Interests ◽  
Collaborative Drug Discovery ◽  
Public Collaboration

AbstractMotivationQuantitative structure-activity relationship (QSAR) analysis is commonly used in drug discovery. Collaborations among pharmaceutical institutions can lead to a better performance in QSAR prediction, however, intellectual property and related financial interests remain substantially hindering inter-institutional collaborations in QSAR modeling for drug discovery.ResultsFor the first time, we verified the feasibility of applying the horizontal federated learning (HFL), which is a recently developed collaborative and privacy-preserving learning framework to perform QSAR analysis. A prototype platform of federated-learning-based QSAR modeling for collaborative drug discovery, i.e, FL-QSAR, is presented accordingly. We first compared the HFL framework with a classic privacy-preserving computation framework, i.e., secure multiparty computation (MPC) to indicate its difference from various perspective. Then we compared FL-QSAR with the public collaboration in terms of QSAR modeling. Our extensive experiments demonstrated that (1) collaboration by FL-QSAR outperforms a single client using only its private data, and (2) collaboration by FL-QSAR achieves almost the same performance as that of collaboration via cleartext learning algorithms using all shared information. Taking together, our results indicate that FL-QSAR under the HFL framework provides an efficient solution to break the barriers between pharmaceutical institutions in QSAR modeling, therefore promote the development of collaborative and privacy-preserving drug discovery with extendable ability to other privacy-related biomedical areas.Availability and implementationThe source codes of the federated learning simulation and FL-QSAR are available on the GitHub: https://github.com/bm2-lab/FL-QSAR

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