Ozone and Mortality: A Meta-Analysis of Time-Series Studies and Comparison to a Multi-City Study (The National Morbidity, Mortality, and Air Pollution Study)

While many time-series studies of ozone and daily mortality identified positive associations,others yielded null or inconclusive results. We performed a meta-analysis of 144 effect estimates from 39 time-series studies, and estimated pooled effects by lags, age groups,cause-specific mortality, and concentration metrics. We compared results to estimates from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), a time-series study of 95 large U.S. cities from 1987 to 2000. Both meta-analysis and NMMAPS results provided strong evidence of a short-term association between ozone and mortality, with larger effects for cardiovascular and respiratory mortality, the elderly, and current day ozone exposure as compared to other single day lags. In both analyses, results were not sensitive to adjustment for particulate matter and model specifications. In the meta-analysis we found that a 10 ppb increase in daily ozone is associated with a 0.83 (95% confidence interval: 0.53, 1.12%) increase in total mortality, whereas the corresponding NMMAPS estimate is 0.25%(0.12, 0.39%). Meta-analysis results were consistently larger than those from NMMAPS,indicating publication bias. Additional publication bias is evident regarding the choice of lags in time-series studies, and the larger heterogeneity in posterior city-specific estimates in the meta-analysis, as compared with NMAMPS.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

Application of Time-Delay Estimation to Mixed Reality Multisensor Tracking

Spatial tracking is one of the most challenging and important parts of Mixed Reality environments. Many applications, especially in the domain of Augmented Reality, rely on the fusion of several tracking systems in order to optimize the overall performance. While the topic of spatial tracking sensor fusion has already seen considerable interest, most results only deal with the integration of carefully arranged setups as opposed to dynamic sensor fusion setups. A crucial prerequisite for correct sensor fusion is the temporal alignment of the tracking data from several sensors. Tracking sensors are typically encountered in Mixed Reality applications, are generally not synchronized. We present a general method to calibrate the temporal offset between different sensors by the Time Delay Estimation method which can be used to perform on-line temporal calibration. By applying Time Delay Estimation on the tracking data, we show that the temporal offset between generic Mixed Reality spatial tracking sensors can be calibrated. To show the correctness and the feasibility of this approach, we have examined different variations of our method and evaluated various combinations of tracking sensors. We furthermore integrated this time synchronization method into our UBITRACK Mixed Reality tracking framework to provide facilities for calibration and real-time data alignment.

The long arm of time pressure at work: Cognitive failure and commuting near-accidents

This study tests whether cognitive failures mediate effects of work-related time pressure and time control on commuting accidents and near-accidents. Participants were 83 employees (56% female) who each commuted between their regular place of residence and place of work using vehicles. The Workplace Cognitive Failure Scale (WCFS) asked for the frequency of failure in memory function, failure in attention regulation, and failure in action execution. Time pressure and time control at work were assessed by the Instrument for Stress Oriented Task Analysis (ISTA). Commuting accidents in the last 12 months were reported by 10% of participants, and half of the sample reported commuting near-accidents in the last 4 weeks. Cognitive failure significantly mediated the influence of time pressure at work on near-accidents even when age, gender, neuroticism, conscientiousness, commuting duration, commuting distance, and time pressure during commuting were controlled for. Time control was negatively related to cognitive failure and neuroticism, but no association with commuting accidents or near-accidents was found. Time pressure at work is likely to increase cognitive load. Time pressure might, therefore, increase cognitive failures during work and also during commuting. Hence, time pressure at work can decrease commuting safety. The result suggests a reduction of time pressure at work should improve commuting safety.

Penetrating or stricturing diseases are the major determinants of time to first and repeat resection surgery in Crohn's disease

BACKGROUND About 80% of patients with Crohn's disease (CD) require bowel resection and up to 65% will undergo a second resection within 10 years. This study reports clinical risk factors for resection surgery (RS) and repeat RS. METHODS Retrospective cohort study, using data from patients included in the Swiss Inflammatory Bowel Disease Cohort. Cox regression analyses were performed to estimate rates of initial and repeated RS. RESULTS Out of 1,138 CD cohort patients, 417 (36.6%) had already undergone RS at the time of inclusion. Kaplan-Meier curves showed that the probability of being free of RS was 65% after 10 years, 42% after 20 years, and 23% after 40 years. Perianal involvement (PA) did not modify this probability to a significant extent. The main adjusted risk factors for RS were smoking at diagnosis (hazard ratio (HR) = 1.33; p = 0.006), stricturing with vs. without PA (HR = 4.91 vs. 4.11; p < 0.001) or penetrating disease with vs. without PA (HR = 3.53 vs. 4.58; p < 0.001). The risk factor for repeat RS was penetrating disease with vs. without PA (HR = 3.17 vs. 2.24; p < 0.05). CONCLUSION The risk of RS was confirmed to be very high for CD in our cohort. Smoking status at diagnosis, but mostly penetrating and stricturing diseases increase the risk of RS.

Search for long-lived stopped R-hadrons decaying out-of-time with pp collisions using the ATLAS detector

An updated search is performed for gluino, top squark, or bottom squark R-hadrons that have come to rest within the ATLAS calorimeter, and decay at some later time to hadronic jets and a neutralino, using 5.0 and 22.9 fb(-1) of pp collisions at 7 and 8 TeV, respectively. Candidate decay events are triggered in selected empty bunch crossings of the LHC in order to remove pp collision backgrounds. Selections based on jet shape and muon system activity are applied to discriminate signal events from cosmic ray and beam-halo muon backgrounds. In the absence of an excess of events, improved limits are set on gluino, stop, and sbottom masses for different decays, lifetimes, and neutralino masses. With a neutralino of mass 100 GeV, the analysis excludes gluinos with mass below 832 GeV (with an expected lower limit of 731 GeV), for a gluino lifetime between 10 mu s and 1000 s in the generic R-hadron model with equal branching ratios for decays to q (q) over bar(chi) over tilde (0) and g (chi) over tilde (0). Under the same assumptions for the neutralino mass and squark lifetime, top squarks and bottom squarks in the Regge R-hadron model are excluded with masses below 379 and 344 GeV, respectively.

Improvement of the processes around the radiology workplace : avoidance of time delays

Radiologists have been confronted with multiple new challenges in recent years. While there has been a steady increase in the number of radiological examinations and imaging material per examination, examination protocols have become more complex and highly time-consuming whereas case-based remuneration is on the decline. The identification of inefficient components in examination processes and reporting is therefore essential. Where and why do time delays occur? How can they be avoided? The following article provides a brief overview and is designed to stimulate discussion.

Mobile Temporalities: Place, Ruination and the Dialectics of Time

In this chapter I explore the ambiguous, contradictory and often transient ways the past enters into our lives. I shed light on the interplay of mobility and temporality in the lifeworlds of two Somalis who left Mogadishu with the outbreak of the war in the 1990s. Looking into the ways they actively make sense of this crucial ‘memory-place’ (Ricoeur 2004), a place that that has been turned into a landscape of ruins and rubble, alternative understandings of memory and temporality will emerge. Instead of producing a continuum between here and there, and now and then, the stories and photographs discussed in this chapter form dialectical images – images that refuse to be woven into a coherent picture of the past. By emphasising the dialectical ways these two individuals make sense of Mogadishu’s past and presence, I am following Walter Benjamin’s cue to rethink deeply modern analytical categories such as history, memory and temporality by highlighting the brief, fragmented moments of their appearance in everyday life.

Automatic assessment of time-resolved OCT images for selective retina therapy

Purpose In recent years, selective retina laser treatment (SRT), a sub-threshold therapy method, avoids widespread damage to all retinal layers by targeting only a few. While these methods facilitate faster healing, their lack of visual feedback during treatment represents a considerable shortcoming as induced lesions remain invisible with conventional imaging and make clinical use challenging. To overcome this, we present a new strategy to provide location-specific and contact-free automatic feedback of SRT laser applications. Methods We leverage time-resolved optical coherence tomography (OCT) to provide informative feedback to clinicians on outcomes of location-specific treatment. By coupling an OCT system to SRT treatment laser, we visualize structural changes in the retinal layers as they occur via time-resolved depth images. We then propose a novel strategy for automatic assessment of such time-resolved OCT images. To achieve this, we introduce novel image features for this task that when combined with standard machine learning classifiers yield excellent treatment outcome classification capabilities. Results Our approach was evaluated on both ex vivo porcine eyes and human patients in a clinical setting, yielding performances above 95 % accuracy for predicting patient treatment outcomes. In addition, we show that accurate outcomes for human patients can be estimated even when our method is trained using only ex vivo porcine data. Conclusion The proposed technique presents a much needed strategy toward noninvasive, safe, reliable, and repeatable SRT applications. These results are encouraging for the broader use of new treatment options for neovascularization-based retinal pathologies.

Transaction Costs, Production Costs, and the Passage of Time

No abstract available.