A systematic review of the use of in-vehicle telematics in monitoring driving behaviours.

BACKGROUND: Road traffic deaths are increasing globally, and preventable driving behaviours are a significant cause of these deaths. In-vehicle telematics has been seen as technology that can improve driving behaviour. The technology has been adopted by many insurance companies to track the behaviours of their consumers. This systematic review presents a summary of the ways that in-vehicle telematics has been modelled and analysed. METHODOLOGY: Electronic searches were conducted on Scopus and Web of Science. Studies were only included if they had a sample size of 10 or more participants, collected their data over at least multiple days, and were published during or after 2010. 45 relevant papers were included in the review. 27 of these articles received a rating of "good" in the quality assessment. RESULTS: We found a divide in the literature regarding the use of in-vehicle telematics. Some articles were interested in the utility of in-vehicle telematics for insurance purposes, while others were interested in determining the influence that in-vehicle telematics has on driving behaviour. Machine learning analyses were the most common forms of analysis seen throughout the review, being especially common in articles with insurance-based outcomes. Acceleration, braking, and speed were the most common variables identified in the review. CONCLUSION: We recommend that future studies provide the demographical information of their sample so that the influence of in-vehicle telematics on the driving behaviours of different groups can be understood. It is also recommended that future studies use multi-level models to account for the hierarchical structure of the telematics data. This hierarchical structure refers to the individual trips for each driver.

Boredom proneness, political orientation and adherence to social-distancing in the pandemic.

Research recently showed that boredom proneness was associated with increased social distancing rule-breaking in a sample collected early in the COVID-19 pandemic. Here we explore data collected early in the pandemic to examine what factors might drive this relation. We focus on political affiliation. Given the functional account of boredom as a call to action, we hypothesized that this urge to act may drive individuals towards outlets replete with symbolic value (e.g., ideology, identity). In addition, given the politicization of some social distancing rules (e.g., mask wearing), we explored whether those who adhere to strong political ideologies-particularly conservative ideologies-would be more likely to rule-break. Moderation analyses indicated that boredom proneness and social (but not fiscal) conservatism were indeed predictive of rule-breaking. These results highlight the need for both clear messaging emphasizing the strength of communal identity and action (i.e., that "We are all in this together") and for interventions that emphasize shared collective values in contexts that appeal directly to social conservatives.

Behavioral and electroencephalographic evidence for reduced attentional control and performance monitoring in boredom.

Boredom, the unfulfilled desire to be engaged in a satisfying mental activity, is an aversive state characterized by poor self-regulation. There is ample evidence that both state and trait boredom are associated with failures of attention in both experimental and everyday settings. The neural correlates of boredom, however, remain underexplored. We recorded electroencephalographic signal from 83 participants during a resting state and while performing a go/no-go task. We found a negative correlation between trait boredom proneness and power in the alpha and theta bands during the resting state. Furthermore, higher levels of task-induced boredom were associated with reduced amplitudes for the P3 and error-related negativity event-related potentials. Increased commission error rates were also associated with higher levels of task-induced boredom. We conclude that state and trait boredom are associated with inadequate engagement of attentional resources.

Boredom in the COVID-19 pandemic: Trait boredom proneness, the desire to act, and rule-breaking.

The state of boredom presents a conundrum: When bored, we want to engage with an activity, but we don't want to engage with whatever is currently available. This conflict is exacerbated when external factors impose restrictions on the range of behaviors we can engage in, which is precisely the scenario we are currently facing, at a global level, during this period of social isolation in response to the COVID-19 pandemic. We collected data from 924 North American participants (530 Male, Mean age = 37.7 years) using the internet-based Mturk platform to examine the relation between self-reports of boredom proneness (using the Short Boredom-Proneness Scale) and individual responses to questions about compliance with social-distancing requirements during the COVID-19 pandemic. Our sample replicated recent findings in boredom research, including a negative correlation between boredom proneness and self-control. We also provide novel evidence that highly boredom prone people have been more likely to break the rules of social isolation in a variety of ways (e.g., fewer hours spent in social isolation, poor adherence to social distancing as evidenced by increased likelihood of holding a social gathering and coming into proximity with more people than recommended). We further demonstrated that boredom proneness substantially mediates the association between self-control and rule-breaking. These results indicate that boredom proneness is a critical factor to consider when encouraging adherence to social isolation.

Boredom Proneness and Self-Control as Unique Risk Factors in Achievement Settings.

The state of boredom arises when we have the desire to be engaged in goal pursuit, but for whatever reason we cannot fulfil that desire. Boredom proneness is characterized by both frequent and intense feelings of boredom and is an enduring individual difference trait associated with a raft of negative outcomes. There has been some work in educational settings, but relatively little is known about the consequences of boredom proneness for learning. Here we explored the unique contributions of boredom proneness, self-control and self-esteem to undergraduate self-reported higher grade point average (GPA). Within educational settings, prior research has shown self-control and self-esteem to be associated with better academic performance. In contrast, boredom proneness is associated with lower levels of self-control and self-esteem. Our analyses replicate those previous findings showing that self-control acts as a positive predictor of GPA. Importantly, we further demonstrated, for the first time, that boredom proneness has a unique contribution to GPA over and above the contribution of self-control, such that as boredom proneness increases, GPA decreases. We discuss potential mechanisms through which boredom proneness may influence academic performance.

Air quality impacts and health-benefit valuation of a low-emission technology for rail yard locomotives in Atlanta Georgia.

One of the largest rail yard facilities in the Southeastern US, the Inman and Tilford yards, is located in the northwestern section of Atlanta, Georgia alongside other industries, schools, businesses, and dwellings. It is a significant source of fine particulate (PM2.5) and black carbon (BC) (Galvis, Bergin, & Russell, 2013). We calculate 2011 PM2.5 and BC emissions from the rail yards and primary industrial and on-road mobile sources in the area and determine their impact on local air quality using Gaussian dispersion modeling. We determine the change in PM2.5 and BC concentrations that could be accomplished by upgrading traditional switcher locomotives used in these rail yards to a lower emitting technology and evaluate the health benefits for comparison with upgrade costs. Emissions from the rail yards were estimated using reported fuel consumption data (GAEPD, 2012b) and emission factors previously measured in the rail yards (Galvis et al., 2013). Model evaluation against 2011 monitoring data found agreement between measured and simulated concentrations. Model outputs indicate that the line-haul and switcher activities are responsible for increments in annual average concentrations of approximately 0.5±0.03 µg/m(3) (39%) and 0.7±0.04 µg/m(3) (56%) of BC, and for 1.0±0.1 µg/m(3) (7%) and 1.6±0.2 µg/m(3) (14%) of PM2.5 at two monitoring sites located north and south of the rail yards respectively. Upgrading the switcher locomotives at the yards with a lower emitting technology in this case "mother slug" units could decrease PM2.5 and BC emissions by about 9 and 3 t/year respectively. This will lower annual average PM2.5 concentrations between 0.3±0.1 µg/m(3) and 0.6±0.1 µg/m(3) and BC concentrations between 0.1±0.02 µg/m(3) and 0.2±0.03 µg/m(3) at monitoring sites north and south of the rail yards respectively, and would facilitate PM2.5 NAAQS attainment in the area. We estimate that health benefits of approximately 20 million dollars per year could be gained.

Development of a Childhood Attachment and Relational Trauma Screen (CARTS): a relational-socioecological framework for surveying attachment security and childhood trauma history.

BACKGROUND: Current psychometric measures of childhood trauma history generally fail to assess the relational-socioecological context within which childhood maltreatment occurs, including the relationship of abusers to abused persons, the emotional availability of caregivers, and the respondent's own thoughts, feelings, and actions in response to maltreatment. OBJECTIVE: To evaluate a computerized approach to measuring the relational-socioecological context within which childhood maltreatment occurs. METHOD: The psychometric properties of a Childhood Attachment and Relational Trauma Screen (CARTS) were evaluated as a retrospective survey of childhood maltreatment history designed to be appropriate for completion by adults. Participants were undergraduates (n=222), an internet sample (n=123), and psychiatric outpatients (n=30). RESULTS: The internal reliability, convergent, and concurrent validity of the CARTS were supported across samples. Paired differences in means and correlations between rated item-descriptiveness to self, mothers, and fathers also accorded with findings of prior attachment and maltreatment research, illustrating the utility of assessing the occurrence and effects of maltreatment within a relational-socioecological framework. CONCLUSIONS: Results preliminarily support a new survey methodology for assessing childhood maltreatment within a relational-socioecological framework. Further psychometric evaluation of the CARTS is warranted.

Likelihood of achieving air quality targets under model uncertainties.

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

Quantifying the sources of ozone, fine particulate matter, and regional haze in the Southeastern United States.

A detailed sensitivity analysis was conducted to quantify the contributions of various emission sources to ozone (O3), fine particulate matter (PM2.5), and regional haze in the Southeastern United States. O3 and particulate matter (PM) levels were estimated using the Community Multiscale Air Quality (CMAQ) modeling system and light extinction values were calculated from modeled PM concentrations. First, the base case was established using the emission projections for the year 2009. Then, in each model run, SO2, primary carbon (PC), NH3, NO(x) or VOC emissions from a particular source category in a certain geographic area were reduced by 30% and the responses were determined by calculating the difference between the results of the reduced emission case and the base case. The sensitivity of summertime O3 to VOC emissions is small in the Southeast and ground-level NO(x) controls are generally more beneficial than elevated NO(x) controls (per unit mass of emissions reduced). SO2 emission reduction is the most beneficial control strategy in reducing summertime PM2.5 levels and improving visibility in the Southeast and electric generating utilities are the single largest source of SO2. Controlling PC emissions can be very effective locally, especially in winter. Reducing NH3 emissions is an effective strategy to reduce wintertime ammonium nitrate (NO3NH4) levels and improve visibility; NO(x) emissions reductions are not as effective. The results presented here will help the development of specific emission control strategies for future attainment of the National Ambient Air Quality Standards in the region.

Assessment of biomass burning emissions and their impacts on urban and regional PM2.5: a Georgia case study.

Biomass burning is a major and growing contributor to particulate matter with an aerodynamic diameter less than 2.5 microm (PM2.5). Such impacts (especially individual impacts from each burning source) are quantified using the Community Multiscale Air Quality (CMAQ) Model, a chemical transport model (CTM). Given the sensitivity of CTM results to uncertain emission inputs, simulations were conducted using three biomass burning inventories. Shortcomings in the burning emissions were also evaluated by comparing simulations with observations and results from a receptor model. Model performance improved significantly with the updated emissions and speciation profiles based on recent measurements for biomass burning: mean fractional bias is reduced from 22% to 4% for elemental carbon and from 18% to 12% for organic matter; mean fractional error is reduced from 59% to 50% for elemental carbon and from 55% to 49% for organic matter. Quantified impacts of biomass burning on PM2.5 during January, March, May, and July 2002 are 3.0, 5.1, 0.8, and 0.3 microg m(-3) domainwide on average, with more than 80% of such impacts being from primary emissions. Impacts of prescribed burning dominate biomass burning impacts, contributing about 55% and 80% of PM2.5 in January and March, respectively, followed by land clearing and agriculture field burning. Significant impacts of wildfires in May and residential wood combustion in fireplaces and woodstoves in January are also found.

Risk factors involved in patients with bleeding peptic ulcers: a case-control study.

Our objectives were to (1) identify the risk factors involved in patients with peptic ulcer disease and determine if they predict bleeding in these patients, (2) determine the association between these risk factors, and (3) analyze the cost effectiveness of various tests for Helicobacter pylori (H. pylori). Two-hundred and thirty patients were included in our study between January 2004 and June 2005 (128 bleeding peptic ulcer disease patients constituted the cases, 102 nonbleeding ulcer patients constituted the controls). H. pylori infection was assessed by urease test and biopsy from gastric antrum. There was no statistically significant difference between these groups regarding sex, age, or location of ulcer. Nonsteroidal anti-inflammatory drug (NSAID) use was higher in the case group (P < 0.001), and the rate of H. pylori infection was lower in these patients (P < 0.05). There was no interaction between NSAID use and H. pylori infection in predicting bleeding ulcer risk (P = 0.08). Sensitivity and specificity for urease test in detecting H. pylori was 75% and 99.7%, respectively. So a positive urease test does not need confirmation with biopsy, which is cost effective.

Regional air quality: local and interstate impacts of NO(x) and SO2 emissions on ozone and fine particulate matter in the eastern United States.

While the U.S. air quality management system is largely designed and managed on a state level, many critical air quality problems are now recognized as regional. In particular, concentrations of two secondary pollutants, ozone and particulate matter, are often above regulated levels and can be dependent on emissions from upwind states. Here, impacts of statewide emissions on concentrations of local and downwind states' ozone and fine particulate matter are simulated for three seasonal periods in the eastern United States using a regional Eulerian photochemical model. Impacts of ground level NO(x) (e.g., mobile and area sources), elevated NO(x) (e.g., power plants and large industrial sources), and SO2 emissions are examined. An average of 77% of each state's ozone and PM(2.5) concentrations that are sensitive to the emissions evaluated here are found to be caused by emissions from other states. Delaware, Maryland, New Jersey, Virginia, Kentucky, and West Virginia are shown to have high concentrations of ozone and PM(2.5) caused by interstate emissions. When weighted by population, New York receives increased interstate contributions to these pollutants and contributions to ozone from local emissions are generally higher. When accounting for emission rates, combined states from the western side of the modeling domain and individual states such as Illinois, Tennessee, Indiana, Kentucky, and Georgia are major contributors to interstate ozone. Ohio, Indiana, Tennessee, Kentucky, and Illinois are the major contributors to interstate PM(2.5). When accounting for an equivalent mass of emissions, Tennessee, Kentucky, West Virginia, Virginia, and Alabama contribute large fractions of these pollutants to other states.

An integrated framework for multipollutant air quality management and its application in Georgia.

Air protection agencies in the United States increasingly confront non-attainment of air quality standards for multiple pollutants sharing interrelated emission origins. Traditional approaches to attainment planning face important limitations that are magnified in the multipollutant context. Recognizing those limitations, the Georgia Environmental Protection Division has adopted an integrated framework to address ozone, fine particulate matter, and regional haze in the state. Rather than applying atmospheric modeling merely as a final check of an overall strategy, photochemical sensitivity analysis is conducted upfront to compare the effectiveness of controlling various precursor emission species and source regions. Emerging software enables the modeling of health benefits and associated economic valuations resulting from air pollution control. Photochemical sensitivity and health benefits analyses, applied together with traditional cost and feasibility assessments, provide a more comprehensive characterization of the implications of various control options. The fuller characterization both informs the selection of control options and facilitates the communication of impacts to affected stakeholders and the public. Although the integrated framework represents a clear improvement over previous attainment-planning efforts, key remaining shortcomings are also discussed.

Quantitative analysis of plasma DNA in severe acute pancreatitis.

CONTEXT: Release of genomic DNA into plasma as a result of necrotic and apoptotic pathways is a feature of a range of human tumours. Severe acute pancreatitis is characterized by inflammation but may also be associated with accelerated apoptotic and necrotic pathways. OBJECTIVES: This study uses quantitative real-time PCR to measure free circulating DNA in patients with severe acute pancreatitis. PARTICIPANTS: Forty-three patients with severe acute pancreatitis, 12 patients with pancreatic cancer and 28 non-cancer controls undergoing laparoscopic cholecystectomy. METHODS: Plasma DNA was purified and quantified using the RNase P transcription assay and quantitative PCR. In pancreatitis patients, baseline samples were taken on admission and further samples taken at a median of 5 days into the disease course. RESULTS: Plasma DNA levels on admission in patients with acute pancreatitis (median: 0.40 ng/microL; range: 0.05-0.79 ng/microL) were significantly (P<0.001) lower than in non-cancer controls (median: 1.60 ng/microL; range: 0.45-9.10 ng/microL). In patients with acute pancreatitis, DNA levels significantly (P<0.001) fell during the disease course to a median value of 0.08 ng/microL (range: 0-0.53 ng/microL). CONCLUSION: This is the first study to use quantitative PCR to measure free plasma DNA in severe acute pancreatitis. The results show that plasma DNA is lower in patients with acute pancreatitis compared to control and that values fall further during the disease course.

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility.

As part of the Southern Appalachian Mountains Initiative, a comprehensive air quality modeling system was developed to evaluate potential emission control strategies to reduce atmospheric pollutant levels at the Class I areas located in the Southern Appalachian Mountains. Six multiday episodes between 1991 and 1995 were simulated, and the skill of the modeling system was evaluated. Two papers comprise various parts of this study. Part I details the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. This paper (part II) addresses issues involved with modeling particulate matter (PM) and its relationship to visibility. For most of the episodes, the fractional error was approximately 50% or less for the major constituents of the fine PM (i.e., sulfate [SO4] and organics) in the region. The mean normalized errors and fractional errors are generally larger for the NO3 and soil components, but these components are relatively small. Variations in modeling bias with pollutant levels were also examined. The model showed a systematic overestimation for low levels and an underestimation for high levels for most PM species. For ammonium, the model showed better performance at lower SO4 concentrations when the measured SO4 was assumed to be completely neutralized (ammonium sulfate) and better performance at higher SO4 concentrations when the partially neutralized (ammonium bisulfate) assumption was made. The contributions of various components of PM to reductions in visibility were also calculated; SO4 was found to be the major contributor.

Preliminary evaluation of the Community Multiscale Air Quality model for 2002 over the Southeastern United States.

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance.

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains. Part I: hourly and seasonal ozone.

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI's assessment.

The effect of ankle braces on the prevention of dynamic forced ankle inversion.

BACKGROUND: Athletes often employ prophylactic braces to reduce the risk of ankle injuries. HYPOTHESIS: Ankle braces do not significantly decrease the risk of forced inversion on a standardized one-footed jump landing. STUDY DESIGN: Controlled laboratory study. METHODS: Fourteen healthy men with a mean age of 25.1 years were tested. Three braces, two semirigid (Aircast and Bledsoe) and one lace-up (Swede-O), were fitted to each subject. Forced dynamic ankle inversion of 24 degrees was to be resisted as the subjects landed on one foot with a force of two body weights on a stimulus presented randomly in 5 of 15 jump trial blocks onto a hard, level force plate. Subjects first completed 1 no-brace block of 5 trials to establish baseline performance, then 3 randomly ordered 15-trial blocks testing performance with each of the braces, and then finally a no-brace 5-trial block. RESULTS: The average no-brace success rate was 24%, which demonstrated the challenging nature of the task. All three braces increased the success rate (average, 44%); however, only the two semirigid braces proved to be significantly better than the unbraced state. CONCLUSION: This test holds promise for evaluating brace efficacy when landing with one foot unexpectedly on an object that acts to forcibly invert the ankle.

Gender differences in muscular protection of the knee in torsion in size-matched athletes.

BACKGROUND: Female athletes who participate in sports involving jumping and cutting maneuvers are up to eight times more likely to sustain a rupture of the anterior cruciate ligament than are men participating in the same sports. We tested the hypothesis that healthy young women are able to volitionally increase the apparent torsional stiffness of the knee, by maximally activating the knee muscles, significantly less than are size-matched men participating in the same type of sport. METHODS: Twenty-four NCAA (National Collegiate Athletic Association) Division-I athletes (twelve men and twelve women) competing in sports associated with a high risk of injury to the anterior cruciate ligament (basketball, volleyball, and soccer) were compared with twenty-eight collegiate endurance athletes (fourteen men and fourteen women) participating in sports associated with a low risk of such injuries (bicycling, crew, and running). Male and female pairs were matched for age, height, weight, body mass index, shoe size, and activity level. Testing was performed with a weighted pendulum that applied a medially directed 80-N impulse force to the lateral aspect of the right forefoot. The resulting internal rotation of the leg was measured optically, to the nearest 0.25 degrees, at 30 degrees and 60 degrees of knee flexion, both with and without maximal activation of the knee muscles. RESULTS: Maximal rotations of the leg were greater in women than in men in both the passive and the active muscle state (16% and 27% greater [p = 0.01 and p = 0.02], respectively). Moreover, female athletes exhibited a significantly (18%) smaller volitional increase in apparent torsional stiffness of the knee under internal rotation loading than did the matched male athletes (p = 0.014); this was particularly the case for those who participated in sports involving jumping and pivoting maneuvers (42% difference between genders, p = 0.001). CONCLUSIONS: The collegiate female athletes involved in high-risk sports exhibited less muscular protection of the knee ligaments during external loading of the knee than did size and sport-matched male athletes.