Transportation, Routine Activities, and Unmet Travel Needs Among Older Vietnamese Immigrants in the United States.

INTRODUCTION: Transportation barriers can affect travel needs and quality of life. METHODS: This survey examined transportation, routine activities, and unmet travel needs among older Vietnamese immigrants, focusing on gender differences. RESULTS: Women were more likely to ride with others, less likely to drive, had fewer types of routine activities, and went out for activities less than men. Over 1/4 of the sample had at least one unmet travel need in the previous month (the most common was for visiting family and friends). DISCUSSION: Interventions to enhance mobility should address age- and gender-based transportation differences and assess for unmet travel needs.

Life-Space Mobility, Transportation, and the Companionship Network of Members of a Hispanic Senior Center.

OBJECTIVES: Companions (i.e., friends who spend time together) are important for the well-being of older adults. Senior centers in the United States are places for older adults to participate in group activities and form and maintain companionships. However, differences in mobility and transportation may affect the ability of older adults to leverage senior center activities into actual companionships. METHODS: This social network analysis was conducted to characterize the companionship network among members of a senior center in relation to their life-space mobility and transportation resources. An exponential random graph model was estimated to identify mobility- and transportation-related correlates of the likelihood of a companionship tie among senior center members (N = 42). RESULTS: Members had an average of 2 companionships with one another (M = 2.2, SD = 2.7). Companionships were more likely for members with greater life-space mobility (p = .009), who attended the senior center more frequently (p = .004), with automobile ownership in their households (p = .034), and who were not transportation cost-burdened (i.e., spent less than 15% of their income on transportation, p = .005). Demographic characteristics, limitations on instrumental activities of daily living, and being at risk for depression were not significantly associated with the likelihood of companionships. DISCUSSION: These findings extend previous knowledge of the role of life-space mobility and transportation in supporting general social participation for older adults to include the importance of transportation and mobility for having companions within a senior center.

Novel gas exposure system for the controlled exposure of plants to gaseous hydrogen fluoride.

Plants can serve as sensitive bioindicators of the presence of contaminant vapors in the atmosphere. This work describes a novel laboratory-based gas exposure system capable of calibrating plants as bioindicators for the detection and delineation of the atmospheric contaminant hydrogen fluoride (HF) as a preparatory step for monitoring release emissions. To evaluate changes in plant phenotype and stress-induced physiological effects attributed to HF alone, the gas exposure chamber must have additional controls to simulate otherwise optimal plant growth conditions including variables such as light intensity, photoperiod, temperature, and irrigation. The exposure system was designed to maintain constant growth conditions during a series of independent experiments that varied between optimal (control) and stressful (HF exposure) conditions. The system was also designed to ensure the safe handling and application of HF. An initial system calibration introduced HF gas into the exposure chamber and monitored HF concentrations by cavity ring-down spectroscopy for a 48-h period. Stable concentrations inside the exposure chamber were observed after approximately 15 h, and losses of HF to the system ranged from 88 to 91%. A model plant species (Festuca arundinacea) was then exposed to HF for 48 h. Visual phenotype stress-induced responses aligned with symptoms reported in the literature for fluoride exposure (tip dieback and discoloration along the dieback transition margin). Fluoride concentrations in exposed tissues compared to control tissues confirmed enhanced fluoride uptake due to HF exposure. The system described herein can be applied to other reactive atmospheric pollutants of interest in support of bioindicator research.

Nightly sleep duration predicts grade point average in the first year of college.

Academic achievement in the first year of college is critical for setting students on a pathway toward long-term academic and life success, yet little is known about the factors that shape early college academic achievement. Given the important role sleep plays in learning and memory, here we extend this work to evaluate whether nightly sleep duration predicts change in end-of-semester grade point average (GPA). First-year college students from three independent universities provided sleep actigraphy for a month early in their winter/spring academic term across five studies. Findings showed that greater early-term total nightly sleep duration predicted higher end-of-term GPA, an effect that persisted even after controlling for previous-term GPA and daytime sleep. Specifically, every additional hour of average nightly sleep duration early in the semester was associated with an 0.07 increase in end-of-term GPA. Sensitivity analyses using sleep thresholds also indicated that sleeping less than 6 h each night was a period where sleep shifted from helpful to harmful for end-of-term GPA, relative to previous-term GPA. Notably, predictive relationships with GPA were specific to total nightly sleep duration, and not other markers of sleep, such as the midpoint of a student's nightly sleep window or bedtime timing variability. These findings across five studies establish nightly sleep duration as an important factor in academic success and highlight the potential value of testing early academic term total sleep time interventions during the formative first year of college.

Transportation Among Returning Citizens: "You Just Want to Stay Down and Get High".

The United States is releasing more individuals from prisons than ever before. However, returning citizens face numerous challenges transitioning back into community life and many communities remain ill-equipped in successfully supporting them. This study focuses on transportation as in integral component to the success of returning citizens. Rapid and rigorous qualitative data analysis (RADaR technique) is applied to interviews (n = 15) with individuals having returned to their community about the impact of transportation on their reentry. Analysis resulted in three primary themes; interviewees reinforced existing knowledge of the issues with transportation disadvantage, transportation is an extension of freedom, and transportation is directly connected to reentry success. These findings suggest a tiered structure of transportation freedom for returning citizens. This model of transportation will aid future researchers and policymakers in considering how to better resource returning citizens to maximize their success.

Alignment Between Heart Rate Variability From Fitness Trackers and Perceived Stress: Perspectives From a Large-Scale In Situ Longitudinal Study of Information Workers.

BACKGROUND: Stress can have adverse effects on health and well-being. Informed by laboratory findings that heart rate variability (HRV) decreases in response to an induced stress response, recent efforts to monitor perceived stress in the wild have focused on HRV measured using wearable devices. However, it is not clear that the well-established association between perceived stress and HRV replicates in naturalistic settings without explicit stress inductions and research-grade sensors. OBJECTIVE: This study aims to quantify the strength of the associations between HRV and perceived daily stress using wearable devices in real-world settings. METHODS: In the main study, 657 participants wore a fitness tracker and completed 14,695 ecological momentary assessments (EMAs) assessing perceived stress, anxiety, positive affect, and negative affect across 8 weeks. In the follow-up study, approximately a year later, 49.8% (327/657) of the same participants wore the same fitness tracker and completed 1373 EMAs assessing perceived stress at the most stressful time of the day over a 1-week period. We used mixed-effects generalized linear models to predict EMA responses from HRV features calculated over varying time windows from 5 minutes to 24 hours. RESULTS: Across all time windows, the models explained an average of 1% (SD 0.5%; marginal R2) of the variance. Models using HRV features computed from an 8 AM to 6 PM time window (namely work hours) outperformed other time windows using HRV features calculated closer to the survey response time but still explained a small amount (2.2%) of the variance. HRV features that were associated with perceived stress were the low frequency to high frequency ratio, very low frequency power, triangular index, and SD of the averages of normal-to-normal intervals. In addition, we found that although HRV was also predictive of other related measures, namely, anxiety, negative affect, and positive affect, it was a significant predictor of stress after controlling for these other constructs. In the follow-up study, calculating HRV when participants reported their most stressful time of the day was less predictive and provided a worse fit (R2=0.022) than the work hours time window (R2=0.032). CONCLUSIONS: A significant but small relationship between perceived stress and HRV was found. Thus, although HRV is associated with perceived stress in laboratory settings, the strength of that association diminishes in real-life settings. HRV might be more reflective of perceived stress in the presence of specific and isolated stressors and research-grade sensing. Relying on wearable-derived HRV alone might not be sufficient to detect stress in naturalistic settings and should not be considered a proxy for perceived stress but rather a component of a complex phenomenon.

Snoozing: an examination of a common method of waking.

STUDY OBJECTIVES: Snoozing was defined as using multiple alarms to accomplish waking, and considered as a method of sleep inertia reduction that utilizes the stress system. Surveys measured snoozing behavior including who, when, how, and why snoozing occurs. In addition, the physiological effects of snoozing on sleep were examined via wearable sleep staging and heart rate (HR) activity, both over a long time scale, and on the days that it occurs. We aimed to establish snoozing as a construct in need of additional study. METHODS: A novel survey examined snoozing prevalence, how snoozing was accomplished, and explored possible contributors and motivators of snoozing behavior in 450 participants. Trait- and day-level surveys were combined with wearable data to determine if snoozers sleep differently than nonsnoozers, and how snoozers and nonsnoozers differ in other areas, such as personality. RESULTS: 57% of participants snoozed. Being female, younger, having fewer steps, having lower conscientiousness, having more disturbed sleep, and being a more evening chronotype increased the likelihood of being a snoozer. Snoozers had elevated resting HR and showed lighter sleep before waking. Snoozers did not sleep less than nonsnoozers nor did they feel more sleepiness or nap more often. CONCLUSIONS: Snoozing is a common behavior associated with changes in sleep physiology before waking, both in a trait- and state-dependent manner, and is influenced by demographic and behavioral traits. Additional research is needed, especially in detailing the physiology of snoozing, its impact on health, and its interactions with observational studies of sleep.

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study.

BACKGROUND: Studies that use ecological momentary assessments (EMAs) or wearable sensors to track numerous attributes, such as physical activity, sleep, and heart rate, can benefit from reductions in missing data. Maximizing compliance is one method of reducing missing data to increase the return on the heavy investment of time and money into large-scale studies. OBJECTIVE: This paper aims to identify the extent to which compliance can be prospectively predicted from individual attributes and initial compliance. METHODS: We instrumented 757 information workers with fitness trackers for 1 year and conducted EMAs in the first 56 days of study participation as part of an observational study. Their compliance with the EMA and fitness tracker wearing protocols was analyzed. Overall, 31 individual characteristics (eg, demographics and personalities) and behavioral variables (eg, early compliance and study portal use) were considered, and 14 variables were selected to create beta regression models for predicting compliance with EMAs 56 days out and wearable compliance 1 year out. We surveyed study participation and correlated the results with compliance. RESULTS: Our modeling indicates that 16% and 25% of the variance in EMA compliance and wearable compliance, respectively, could be explained through a survey of demographics and personality in a held-out sample. The likelihood of higher EMA and wearable compliance was associated with being older (EMA: odds ratio [OR] 1.02, 95% CI 1.00-1.03; wearable: OR 1.02, 95% CI 1.01-1.04), speaking English as a first language (EMA: OR 1.38, 95% CI 1.05-1.80; wearable: OR 1.39, 95% CI 1.05-1.85), having had a wearable before joining the study (EMA: OR 1.25, 95% CI 1.04-1.51; wearable: OR 1.50, 95% CI 1.23-1.83), and exhibiting conscientiousness (EMA: OR 1.25, 95% CI 1.04-1.51; wearable: OR 1.34, 95% CI 1.14-1.58). Compliance was negatively associated with exhibiting extraversion (EMA: OR 0.74, 95% CI 0.64-0.85; wearable: OR 0.67, 95% CI 0.57-0.78) and having a supervisory role (EMA: OR 0.65, 95% CI 0.54-0.79; wearable: OR 0.66, 95% CI 0.54-0.81). Furthermore, higher wearable compliance was negatively associated with agreeableness (OR 0.68, 95% CI 0.56-0.83) and neuroticism (OR 0.85, 95% CI 0.73-0.98). Compliance in the second week of the study could help explain more variance; 62% and 66% of the variance in EMA compliance and wearable compliance, respectively, was explained. Finally, compliance correlated with participants' self-reflection on the ease of participation, usefulness of our compliance portal, timely resolution of issues, and compensation adequacy, suggesting that these are avenues for improving compliance. CONCLUSIONS: We recommend conducting an initial 2-week pilot to measure trait-like compliance and identify participants at risk of long-term noncompliance, performing oversampling based on participants' individual characteristics to avoid introducing bias in the sample when excluding data based on noncompliance, using an issue tracking portal, and providing special care in troubleshooting to help participants maintain compliance.

The impact of social networks on sleep among a cohort of college students.

BACKGROUND: Sleep duration and quality are associated with physical and mental wellbeing. This paper examines social network effects on individual level change in the sleep quantity and quality from late adolescence to emerging adulthood and its associated factors, including the influence of peers on sleep behavior and the impact of changes in network size. METHODS: We use sleep data from 619 undergraduates at the University of Notre Dame obtained via Fitbit devices as part of the NetHealth project. The data were collected between August 16, 2015 and May 13, 2017. We model trends in sleep behaviors using latent growth-curve models. RESULTS: Controlling for the many factors known to impact sleep quantity and quality, we find two social network effects: increasing network size is associated with less sleep and a student's sleep levels are influenced by his or her peers. While we do not find any consistent decline in sleep quantity over the 637 days, daily fluctuations in sleep quantity are associated with changes in network size and the composition of a student's network. As a student's network gets bigger, s/he sleeps less, and when a student's contacts sleep more (or less) than s/he does, the student becomes more like his or her contacts and sleeps more (or less). CONCLUSIONS: Social networks can and do impact sleep, especially sleep quantity. In contexts where students want to have larger networks, the difficulties of increasing network size and maintaining larger networks negatively impact sleep. Because of peer influence, the effectiveness of interventions designed to improve sleep practices could be increased by leveraging student social networks to help diffuse better sleep habits.

Examining Response to Negative Life Events Through Fitness Tracker Data.

Negative life events, such as the death of a loved one, are an unavoidable part of life. These events can be overwhelmingly stressful and may lead to the development of mental health disorders. To mitigate these adverse developments, prior literature has utilized measures of psychological responses to negative life events to better understand their effects on mental health. However, psychological changes represent only one aspect of an individual's potential response. We posit measuring additional dimensions of health, such as physical health, may also be beneficial, as physical health itself may be affected by negative life events and measuring its response could provide context to changes in mental health. Therefore, the primary aim of this work was to quantify how an individual's physical health changes in response to negative life events by testing for deviations in their physiological and behavioral state (PB-state). After capturing post-event, PB-state responses, our second aim sought to contextualize changes within known factors of psychological response to negative life events, namely coping strategies. To do so, we utilized a cohort of professionals across the United States monitored for 1 year and who experienced a negative life event while under observation. Garmin Vivosmart-3 devices provided a multidimensional representation of one's PB-state by collecting measures of resting heart rate, physical activity, and sleep. To test for deviations in PB-state following negative life events, One-Class Support Vector Machines were trained on a window of time prior to the event, which established a PB-state baseline. The model then evaluated participant's PB-state on the day of the life event and each day that followed, assigning each day a level of deviance relative to the participant's baseline. Resulting response curves were then examined in association with the use of various coping strategies using Bayesian gamma-hurdle regression models. The results from our objectives suggest that physical determinants of health also deviate in response to negative life events and that these deviations can be mitigated through different coping strategies. Taken together, these observations stress the need to examine physical determinants of health alongside psychological determinants when investigating the effects of negative life events.

The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing.

Previous studies of seasonal effects on sleep have yielded unclear results, likely due to methodological differences and limitations in data size and/or quality. We measured the sleep habits of 216 individuals across the U.S. over four seasons for slightly over a year using objective, continuous, and unobtrusive measures of sleep and local weather. In addition, we controlled for demographics and trait-like constructs previously identified to correlate with sleep behavior. We investigated seasonal and weather effects of sleep duration, bedtime, and wake time. We found several small but statistically significant effects of seasonal and weather effects on sleep patterns. We observe the strongest seasonal effects for wake time and sleep duration, especially during the spring season: wake times are earlier, and sleep duration decreases (compared to the reference season winter). Sleep duration also modestly decreases when day lengths get longer (between the winter and summer solstice). Bedtimes and wake times tend to be slightly later as outdoor temperature increases.

Higher post-encoding cortisol benefits the selective consolidation of emotional aspects of memory.

Emotional experiences create durable memory traces in the brain, especially when these memories are consolidated in the presence of stress hormones such as cortisol. Although some research suggests cortisol elevation can increase long-term memory for emotional relative to neutral content, the impact of stress and cortisol on the consolidation of emotional and neutral aspects of memories when they are part of the same experience remains unknown. Here, after encoding complex scenes consisting of negative or neutral objects placed on neutral backgrounds, participants were exposed to a psychosocial stressor (or matched control condition) in order to examine the impact of stress and cortisol on early consolidation processes. The next day, once cortisol levels had returned to baseline, specific and gist recognition memory were tested separately for objects and backgrounds. Results indicate that while there was a numerical increase in memory for negative objects in the stress group, higher endogenous cortisol concentrations were specifically associated with decreased memory for the neutral backgrounds originally paired with negative objects. Moreover, across all participants, cortisol levels were positively correlated with the magnitude of the emotional memory trade-off effect. Specifically, while memory for negative objects was preserved, elevated cortisol during early consolidation was associated with decreased memory for neutral backgrounds that were initially paired with negative objects. These memory effects were observed in both the stricter specific measure of memory and the less conservative measure of gist memory. Together, these findings suggest that rather than influencing all aspects of an experience similarly, elevated cortisol during early consolidation selectively preserves what is most emotionally salient and adaptive to remember while allowing the loss of memory for less important neutral information over time.

Deviations from normal bedtimes are associated with short-term increases in resting heart rate.

Despite proper sleep hygiene being critical to our health, guidelines for improving sleep habits often focus on only a single component, namely, sleep duration. Recent works, however, have brought to light the importance of another aspect of sleep: bedtime regularity, given its ties to cognitive and metabolic health outcomes. To further our understanding of this often-neglected component of sleep, the objective of this work was to investigate the association between bedtime regularity and resting heart rate (RHR): an important biomarker for cardiovascular health. Utilizing Fitbit Charge HRs to measure bedtimes, sleep and RHR, 255,736 nights of data were collected from a cohort of 557 college students. We observed that going to bed even 30 minutes later than one's normal bedtime was associated with a significantly higher RHR throughout sleep (Coeff +0.18; 95% CI: +0.11, +0.26 bpm), persisting into the following day and converging with one's normal RHR in the early evening. Bedtimes of at least 1 hour earlier were also associated with significantly higher RHRs throughout sleep; however, they converged with one's normal rate by the end of the sleep session, not extending into the following day. These observations stress the importance of maintaining proper sleep habits, beyond sleep duration, as high variability in bedtimes may be detrimental to one's cardiovascular health.

Using crowd sourcing to locate and characterize conflicts for vulnerable modes.

Most agencies and decision-makers rely on crash and crash severity (property damage only, injury or fatality) data to assess transportation safety; however, in the context of public health where perceptions of safety may influence the willingness to adopt active transportation modes (e.g. bicycling and walking), pedestrian-motor vehicle and other similar conflicts types may define a better performance measure for safety assessment. In the field of transportation safety, an absolute conflict occurs when two parties' paths cross and one of the parties must undertake an evasive maneuver (e.g. change direction or stop) to avoid a crash. Other less severe conflicts where paths cross but no evasive maneuver is required may also impact public perceptions of safety especially for vulnerable modes. Most of the existing literature focuses on vehicle conflicts. While in the past several years, more research has investigated bicycle and pedestrian conflicts, most of this has focused on the intersection environment. A comprehensive analysis of conflicts appears critical. The major objective of this study is two fold: 1) Development of an innovative and cost effective conflict data collection technique to better understand the conflicts (and their severity) involving vulnerable road users (e.g. bicycle/pedestrian, bicycle/motor vehicle, and pedestrian/motor vehicle) and their severity. 2) Test the effectiveness and practicality of the approach taken and its associated crowd sourced data collection. In an endeavor to undertake these objectives, the researchers developed an android-based crowd-sourced data collection app. The crowd-source data collected using the app is compared with traditional fatality data for hot spot analysis. At the end, the app users provide feedback about the overall competency of the app interface and the performance of its features to the app developers. If widely adopted, the app will enable communities to create their own data collection efforts to identify dangerous sites within their neighborhoods. Agencies will have a valuable data source at low-cost to help inform their decision making related to bicycle and pedestrian education, encouragement, enforcement, programs, policies, and infrastructure design and planning.

The impact of cognitive challenges in major depression: the role of the primary care physician.

Nearly 1 in 5 Americans will struggle with major depression in their lives; some will have recurring bouts. Recent psychiatric research has given new attention to the prevalence of cognitive deficits in major depression and the impact such deficits have on remission and overall life functioning. When depression is partially treated i.e., leaving residual symptoms, patients have higher rates of relapse and lower functional outcomes. Impaired cognitive functioning is a frequent residual symptom, persisting in about 45% of patients even when emotional symptoms have improved, and results in a disproportionate share of the functional impairment, particularly in the workplace. Patients with depression have disrupted circuitry in brain regions responsible for cognition and it is therefore important to screen depressed patients for cognitive as well as emotional symptoms. Cognitive dysfunction should be evaluated in every mood disordered patient with validated self-report scales such as the Patient Health Questionnaire-9 or the Beck Depression Inventory and objective measures of cognitive function are also very very useful. Two easily administered tests are the Trails B Test and the Digit Symbol Substitution Test. Each take less than two minutes and measure working memory, executive function, and processing speed and can track cognitive improvement in depressed patients. Treatment of cognitive dysfunction in major depression is complicated by the 'serotonin conundrum': SSRI's frequently do not treat to full remission, and can cause cognitive blunting-actually adding to cognitive problems. Based on recent data including results from a recently completed meta-analysis by McIntyre and colleagues, an evidence-based algorithm for treating cognitive symptoms in depression is presented. A hierarchy of antidepressants and augmentation strategies based on the best available evidence is discussed. In conclusion, cognitive symptoms in major depressive disorder have been recognized as a target of therapeutic improvement by the FDA and have become a focus of clinical importance.

(67/68)Galmydar: A metalloprobe for monitoring breast cancer resistance protein (BCRP)-mediated functional transport activity.

INTRODUCTION: For stratification of chemotherapeutic choices, radiopharmaceuticals capable of imaging breast cancer resistance protein (BCRP/ABCG2)-mediated functional transport are desired. To accomplish this objective, Galmydar, a fluorescent and moderately hydrophobic Ga(III) cationic complex and its (67/68)Ga-radiolabeled counterparts were interrogated in HEK293 cells stably transfected with BCRP and their WT counterparts transfected with empty vector. Additionally, the sensitivity and specificity of (68)Ga-Galmydar to evaluate functional expression of BCRP at the blood-brain barrier (BBB) was investigated in gene-knockout mdr1a/1b(-/-) (double knockout, dKO) and mdr1a/1b(-/-)ABCG2(-/-) (triple knockout, tKO) mouse models. METHODS: For radiotracer uptake assays and live cell fluorescence imaging, either (67)Ga-Galmydar or its unlabeled counterpart was incubated in HEK293 cells transfected with BCRP (HEK293/BCRP) and their WT counterparts at 37°C under a continuous flux of CO2 (5%) in the presence or absence of Ko143, a potent BCRP antagonist, and cellular uptake was measured to assess the sensitivity of Galmydar to probe BCRP-mediated functional transport activity in cellulo. For assessing the potential of Galmydar to enable diagnostic imaging of targeted tissues in vivo, the (67)Ga-radiolabeled counterpart was incubated in either human serum albumin or human serum at 37°C and the percentage of unbound (67)Ga-Galmydar was determined. To evaluate the sensitivity of (68)Ga-Galmydar for molecular imaging of BCRP-mediated efflux activity in vivo, microPET/CT brain imaging was performed in dKO and tKO mice and their age-matched WT counterparts, 60min post-intravenous injection. RESULTS: (67)Ga-Galmydar shows uptake profiles in HEK293 cells inversely proportional to BCRP expression, and antagonist (Ko143) induced accumulation in HEK293/BCRP cells, thus indicating target sensitivity and specificity. Furthermore, employing the fluorescent characteristics of Galmydar, optical imaging in HEK293/BCRP cells shows an excellent correlation with the radiotracer cellular accumulation data. (67)Ga-Galmydar shows > 85% unbound fraction and presence of parental compound in human serum. Finally, microPET/CT imaging shows higher retention of (68)Ga-Galmydar in brains of dKO and tKO mice compared to their age-matched WT counterparts, 60min post-intravenous tail-vein injection. CONCLUSIONS: Combined data indicate that Galmydar could provide a template scaffold for development of a PET tracer for imaging BCRP-mediated functional transport activity in vivo.

Weathering of field-collected floating and stranded Macondo oils during and shortly after the Deepwater Horizon oil spill.

Chemical analysis of large populations of floating (n=62) and stranded (n=1174) Macondo oils collected from the northern Gulf of Mexico sea surface and shorelines during or within seven weeks of the end of the Deepwater Horizon oil spill demonstrates the range, rates, and processes affecting surface oil weathering. Oil collected immediately upon reaching the sea surface had already lost most mass below n-C8 from dissolution of soluble aliphatics, monoaromatics, and naphthalenes during the oil's ascent with further reductions extending up to n-C13 due to the onset of evaporation. With additional time, weathering of the floating and stranded oils advanced with total PAH (TPAH50) depletions averaging 69±23% for floating oils and 94±3% for stranded oils caused by the combined effects of evaporation, dissolution, and photo-oxidation, the latter of which also reduced triaromatic steroid biomarkers. Biodegradation was not evident among the coalesced floating oils studied, but had commenced in some stranded oils.

Psychophysiological arousal at encoding leads to reduced reactivity but enhanced emotional memory following sleep.

While sleep's role in emotional memory processing is gaining increasing support, its effect on emotion regulation remains equivocal. Moreover, little is known about the link between emotional reactivity at the time of encoding and subsequent sleep-based emotional memory consolidation. This study examined whether sleep would potentiate, protect, or depotentiate measures of heart rate and skin conductance in response to scenes containing emotional and neutral objects, and assessed how these measures of reactivity would predict subsequent memory for the objects across delays of sleep and wake. Heart rate deceleration (HRD) and skin conductance response (SCR) data were collected at encoding and recognition. Although HRD and SCR reactivity to objects were depotentiated after a sleep-filled delay, they remained unchanged after a delay containing wakefulness. Moreover, increased arousal responses to negative scenes at encoding as measured by HRD and SCR responses were positively correlated with subsequent memory for the negative objects of scenes, but only in the sleep group. This suggests that larger reactions to negative images at the time of encoding set the stage for the preferential consolidation of these images during a night of sleep. Although arousal responses are often thought to account for emotional enhancement in long-term memory, these findings suggest that both an arousal response at encoding and a subsequent period of sleep are needed to optimize selective emotional memory consolidation.

Gas emissions, minerals, and tars associated with three coal fires, Powder River Basin, USA.

Ground-based surveys of three coal fires and airborne surveys of two of the fires were conducted near Sheridan, Wyoming. The fires occur in natural outcrops and in abandoned mines, all containing Paleocene-age subbituminous coals. Diffuse (carbon dioxide (CO(2)) only) and vent (CO(2), carbon monoxide (CO), methane, hydrogen sulfide (H(2)S), and elemental mercury) emission estimates were made for each of the fires. Additionally, gas samples were collected for volatile organic compound (VOC) analysis and showed a large range in variation between vents. The fires produce locally dangerous levels of CO, CO(2), H(2)S, and benzene, among other gases. At one fire in an abandoned coal mine, trends in gas and tar composition followed a change in topography. Total CO(2) fluxes for the fires from airborne, ground-based, and rate of fire advancement estimates ranged from 0.9 to 780mg/s/m(2) and are comparable to other coal fires worldwide. Samples of tar and coal-fire minerals collected from the mouth of vents provided insight into the behavior and formation of the coal fires.