University of California, Irvine

About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.

Nationwide longitudinal study of psychological responses to September 11

Abstract: ContextThe September 11, 2001, attacks against the United States provide a unique opportunity to examine longitudinally the process of adjustment to a traumatic event on a national scale.ObjectiveTo examine the degree to which demographic factors, mental and physical health history, lifetime exposure to stressful events, September 11–related experiences, and coping strategies used shortly after the attacks predict psychological outcomes over time.Design, Setting, and ParticipantsA national probability sample of 3496 adults received a Web-based survey; 2729 individuals (78% participation rate) completed it between 9 and 23 days (75% within 9 to 14 days) after the terrorist attacks. A random sample of 1069 panelists residing outside New York, NY, were drawn from the wave 1 sample (n = 2729) and received a second survey; 933 (87% participation rate) completed it approximately 2 months following the attacks. A third survey (n = 787) was completed approximately 6 months after the attacks.Main Outcome MeasuresSeptember 11–related symptoms of acute stress, posttraumatic stress, and global distress.ResultsSeventeen percent of the US population outside of New York City reported symptoms of September 11–related posttraumatic stress 2 months after the attacks; 5.8% did so at 6 months. High levels of posttraumatic stress symptoms were associated with female sex (odds ratio [OR], 1.64; 95% confidence interval [CI], 1.17-2.31), marital separation (OR, 2.55; 95% CI, 1.06-6.14), pre–September 11 physician-diagnosed depression or anxiety disorder (OR, 1.84; 95% CI, 1.33-2.56) or physical illness (OR, 0.93; 95% CI, 0.88-0.99), severity of exposure to the attacks (OR, 1.31; 95% CI, 1.11–1.55), and early disengagement from coping efforts (eg, giving up: OR, 1.68; 95% CI, 1.27-2.20; denial: OR, 1.33; 95% CI, 1.07-1.64; and self-distraction: OR, 1.31; 95% CI, 1.07-1.59). In addition to demographic and pre–September 11 health variables, global distress was associated with severity of loss due to the attacks (β = .07; P = .008) and early coping strategies (eg, increased with denial: β = .08; P = .005; and giving up: β = .05; P = .04; and decreased with active coping: β = −.08; P = .002).ConclusionsThe psychological effects of a major national trauma are not limited to those who experience it directly, and the degree of response is not predicted simply by objective measures of exposure to or loss from the trauma. Instead, use of specific coping strategies shortly after an event is associated with symptoms over time. In particular, disengaging from coping efforts can signal the likelihood of psychological difficulties up to 6 months after a trauma.

Global fire emissions estimates during 1997–2016

Abstract: . Climate, land use, and other anthropogenic and natural drivers have the potential to influence fire dynamics in many regions. To develop a mechanistic understanding of the changing role of these drivers and their impact on atmospheric composition, long-term fire records are needed that fuse information from different satellite and in situ data streams. Here we describe the fourth version of the Global Fire Emissions Database (GFED) and quantify global fire emissions patterns during 1997–2016. The modeling system, based on the Carnegie–Ames–Stanford Approach (CASA) biogeochemical model, has several modifications from the previous version and uses higher quality input datasets. Significant upgrades include (1) new burned area estimates with contributions from small fires, (2) a revised fuel consumption parameterization optimized using field observations, (3) modifications that improve the representation of fuel consumption in frequently burning landscapes, and (4) fire severity estimates that better represent continental differences in burning processes across boreal regions of North America and Eurasia. The new version has a higher spatial resolution (0.25°) and uses a different set of emission factors that separately resolves trace gas and aerosol emissions from temperate and boreal forest ecosystems. Global mean carbon emissions using the burned area dataset with small fires (GFED4s) were 2.2 × 1015 grams of carbon per year (Pg C yr−1) during 1997–2016, with a maximum in 1997 (3.0 Pg C yr−1) and minimum in 2013 (1.8 Pg C yr−1). These estimates were 11 % higher than our previous estimates (GFED3) during 1997–2011, when the two datasets overlapped. This net increase was the result of a substantial increase in burned area (37 %), mostly due to the inclusion of small fires, and a modest decrease in mean fuel consumption (−19 %) to better match estimates from field studies, primarily in savannas and grasslands. For trace gas and aerosol emissions, differences between GFED4s and GFED3 were often larger due to the use of revised emission factors. If small fire burned area was excluded (GFED4 without the s for small fires), average emissions were 1.5 Pg C yr−1. The addition of small fires had the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia. This small fire layer carries substantial uncertainties; improving these estimates will require use of new burned area products derived from high-resolution satellite imagery. Our revised dataset provides an internally consistent set of burned area and emissions that may contribute to a better understanding of multi-decadal changes in fire dynamics and their impact on the Earth system. GFED data are available from http://www.globalfiredata.org .

Derivative Dynamic Time Warping.

Abstract: Time series are a ubiquitous form of data occurring in virtually every scientific discipline. A common task with time series data is comparing one sequence with another. In some domains a very simple distance measure, such as Euclidean distance will suffice. However, it is often the case that two sequences have the approximately the same overall component shapes, but these shapes do not line up in X-axis. Figure 1 shows this with a simple example. In order to find the similarity between such sequences, or as a preprocessing step before averaging them, we must "warp" the time axis of one (or both) sequences to achieve a better alignment. Dynamic time warping (DTW), is a technique for efficiently achieving this warping. In addition to data mining (Keogh & Pazzani 2000, Yi et. al. 1998, Berndt & Clifford 1994), DTW has been used in gesture recognition (Gavrila & Davis 1995), robotics (Schmill et. al 1999), speech processing (Rabiner & Juang 1993), manufacturing (Gollmer & Posten 1995) and medicine (Caiani et. al 1998).

Dopamine in drug abuse and addiction: results from imaging studies and treatment implications

Abstract: The involvement of dopamine in drug reinforcement is well recognized but its role in drug addiction is much less clear. Imaging studies have shown that the reinforcing effects of drugs of abuse in humans are contingent upon large and fast increases in dopamine that mimic but exceed in the intensity and duration those induced by dopamine cell firing to environmental events. In addition, imaging studies have also documented a role of dopamine in motivation, which appears to be encoded both by fast as well as smooth DA increases. Since dopamine cells fire in response to salient stimuli, the supraphysiological activation by drugs is likely to be experienced as highly salient (driving attention, arousal conditioned learning and motivation) and may also reset the thresholds required for environmental events to activate dopamine cells. Indeed, imaging studies have shown that in drug-addicted subjects, dopamine function is markedly disrupted (decreases in dopamine release and in dopamine D2 receptors in striatum) and this is associated with reduced activity of the orbitofrontal cortex (neuroanatomical region involved with salience attribution and motivation and implicated in compulsive behaviors) and the cingulate gyrus (neuroanatomical region involved with inhibitory control and attention and implicated in impulsivity). However, when addicted subjects are exposed to drug-related stimuli, these hypoactive regions become hyperactive in proportion to the expressed desire for the drug. We postulate that decreased dopamine function in addicted subjects results in decreased sensitivity to nondrug-related stimuli (including natural reinforcers) and disrupts frontal inhibition, both of which contribute to compulsive drug intake and impaired inhibitory control. These findings suggest new strategies for pharmacological and behavioral treatments, which focus on enhancing DA function and restoring brain circuits disrupted by chronic drug use to help motivate the addicted subject in activities that provide alternative sources of reinforcement, counteract conditioned responses, enhance their ability to control their drive to take drugs and interfere with their compulsive administration.