scholarly journals Developing a laboratory model of smoking lapse targeting stress and brief nicotine deprivation.

2018 ◽  
Vol 26 (3) ◽  
pp. 244-250 ◽  
Author(s):  
Lindsay M. S. Oberleitner ◽  
Kelly E. Moore ◽  
Terril Verplaetse ◽  
Walter Roberts ◽  
Sherry A. McKee
Keyword(s):  
Laboratory Model ◽  
Smoking Lapse ◽  
Nicotine Deprivation

scholarly journals Self-control depletion and nicotine deprivation as precipitants of smoking cessation failure: A human laboratory model.

2017 ◽  
Vol 85 (4) ◽  
pp. 381-396 ◽  
Author(s):  
Bryan W. Heckman ◽  
David A. MacQueen ◽  
Nicole S. Marquinez ◽  
James MacKillop ◽  
Warren K. Bickel ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Self Control ◽  
Laboratory Model ◽  
Nicotine Deprivation ◽  
Human Laboratory

scholarly journals Pilot investigation of the effect of carvedilol on stress-precipitated smoking-lapse behavior

2018 ◽  
Vol 32 (9) ◽  
pp. 1003-1009 ◽  
Author(s):  
Terril L Verplaetse ◽  
Andrea H Weinberger ◽  
Rebecca L Ashare ◽  
Brian P Pittman ◽  
Julia M Shi ◽  
...  
Keyword(s):  
Drugs Of Abuse ◽  
Preliminary Investigation ◽  
Clinical Indication ◽  
Laboratory Model ◽  
Self Administration ◽  
Beneficial Effects ◽  
Adrenergic Antagonist ◽  
Smoking Lapse ◽  
Lapse Behavior ◽  
Smoking Outcomes

Introduction: Separate α1- and β-adrenergic antagonists have shown efficacy in reducing nicotine-motivated behaviors in rodents and humans, supporting a role for the noradrenergic system in mediating the reinforcing properties of drugs of abuse. However, the effect of the combined α1- and β-adrenergic antagonist, carvedilol, on stress-related smoking is unknown. Methods: Using a well-established human laboratory model of stress-precipitated smoking-lapse behavior, we examined whether carvedilol (0 or 50 mg/day; between subject, n=17 per group), administered to steady-state, would attenuate the ability to resist smoking following stress imagery (vs. neutral imagery) and reduce subsequent smoking self-administration in nicotine-deprived smokers ( n = 34 total). Tobacco craving, withdrawal, and physiologic reactivity were also assessed. Results: Latency to start smoking and number of cigarettes smoked during the self-administration period did not differ by medication condition. Counter to our hypothesis, tobacco craving demonstrated a medication × time effect, with greater craving in the carvedilol condition. Systolic blood pressure and heart rate demonstrated lower values in the carvedilol versus placebo group, consistent with known effects of carvedilol. Conclusion: While carvedilol attenuated physiologic reactivity consistent with its clinical indication, beneficial effects on smoking outcomes were absent in this preliminary investigation and may suggest possible worsening. Future work may benefit from discerning the single versus combined effects of α1- and β-adrenergic antagonism on smoking outcomes.

Neural Mechanisms Underlying Hypoarousal-Related Abnormal Aggression in a Laboratory Model

2008 ◽  
Author(s):  
Eva Mikics ◽  
Jozsef Halasz ◽  
Mate Toth ◽  
Menno R. Kruk ◽  
Jozsef Haller
Keyword(s):  
Neural Mechanisms ◽  
Laboratory Model

Laboratory model for on-board processing system

1992 ◽  
Author(s):  
F. LORENZO ◽  
J. VALVERDE
Keyword(s):  
Processing System ◽  
Laboratory Model

Virtual Laboratory/Model Abstraction Testbed

1999 ◽  
Author(s):  
Kevin C. Trott
Keyword(s):  
Virtual Laboratory ◽  
Laboratory Model ◽  
Model Abstraction

Continuous Precipitation of Lead Iodide

1994 ◽  
Vol 59 (7) ◽  
pp. 1503-1510
Author(s):  
Stanislav Žáček ◽  
Jaroslav Nývlt
Keyword(s):  
Growth Rate ◽  
Particle Size ◽  
Crystal Size ◽  
Crystal Growth Rate ◽  
Laboratory Model ◽  
Lead Iodide ◽  
Secondary Nucleation ◽  
Equimolar Ratio ◽  
Continuous Precipitation ◽  
The Mean

Lead iodide was precipitated from aqueous solutions of 0.015 - 0.1 M Pb(NO3)2 and 0.03 - 0.2 M KI in the equimolar ratio using a laboratory model of a stirred continuous crystallizer at 22 °C. After reaching the steady state, the PbI2 crystal size distribution was measured sedimentometrically and the crystallization kinetics was evaluated based on the mean particle size. Both the linear crystal growth rate and the nucleation rate depend on the specific output of the crystallizer. The system crystallization constant either points to a significant effect of secondary nucleation by the mechanism of contact of the crystals with the stirrer blade, or depends on the concentrations of the components added due to the micromixing mechanism.

Dynamic Self-Efficacy and Outcome Expectancies: Prediction of Smoking Lapse and Relapse.

2005 ◽  
Vol 114 (4) ◽  
pp. 661-675 ◽  
Author(s):  
Chad J. Gwaltney ◽  
Saul Shiffman ◽  
Mark H. Balabanis ◽  
Jean A. Paty
Keyword(s):  
Self Efficacy ◽  
Outcome Expectancies ◽  
Smoking Lapse

scholarly journals Bridge Damage Detection Approach Using a Roving Camera Technique

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1246 ◽  
Author(s):  
Darragh Lydon ◽  
Myra Lydon ◽  
Rolands Kromanis ◽  
Chuan-Zhi Dong ◽  
Necati Catbas ◽  
...  
Keyword(s):  
Low Cost ◽  
Normal Operation ◽  
Laboratory Model ◽  
Traffic Patterns ◽  
Operational Conditions ◽  
Bridge Model ◽  
Detection Approach ◽  
Bridge Damage ◽  
Computer Vision Technology ◽  
Climate Events

Increasing extreme climate events, intensifying traffic patterns and long-term underinvestment have led to the escalated deterioration of bridges within our road and rail transport networks. Structural Health Monitoring (SHM) systems provide a means of objectively capturing and quantifying deterioration under operational conditions. Computer vision technology has gained considerable attention in the field of SHM due to its ability to obtain displacement data using non-contact methods at long distances. Additionally, it provides a low cost, rapid instrumentation solution with low interference to the normal operation of structures. However, even in the case of a medium span bridge, the need for many cameras to capture the global response can be cost-prohibitive. This research proposes a roving camera technique to capture a complete derivation of the response of a laboratory model bridge under live loading, in order to identify bridge damage. Displacement is identified as a suitable damage indicator, and two methods are used to assess the magnitude of the change in global displacement under changing boundary conditions in the laboratory bridge model. From this study, it is established that either approach could detect damage in the simulation model, providing an SHM solution that negates the requirement for complex sensor installations.

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