Purpose Globally, the age-standardised prevalence of type 2 diabetes mellitus (T2DM) has nearly doubled from 1980 to 2014, rising from 4.7% to 8.5% with an estimated 422 million adults living with the chronic disease. The MULTI sTUdy Diabetes rEsearch (MULTITUDE) consortium was recently established to harmonise data from 17 independent cohort studies and clinical trials and to facilitate a better understanding of the determinants, risk factors and outcomes associated with T2DM. Participants Participants range in age from 3 to 88 years at baseline, including both individuals with and without T2DM. MULTITUDE is an individual-level pooled database of demographics, comorbidities, relevant medications, clinical laboratory values, cardiac health measures, and T2DM-associated events and outcomes across 45 US states and the District of Columbia. Findings to date Among the 135 156 ongoing participants included in the consortium, almost 25% (33 421) were diagnosed with T2DM at baseline. The average age of the participants was 54.3, while the average age of participants with diabetes was 64.2. Men (55.3%) and women (44.6%) were almost equally represented across the consortium. Non-whites accounted for 31.6% of the total participants and 40% of those diagnosed with T2DM. Fewer individuals with diabetes reported being regular smokers than their non-diabetic counterparts (40.3% vs 47.4%). Over 85% of those with diabetes were reported as either overweight or obese at baseline, compared with 60.7% of those without T2DM. We observed differences in all-cause mortality, overall and by T2DM status, between cohorts. Future plans Given the wide variation in demographics and all-cause mortality in the cohorts, MULTITUDE consortium will be a unique resource for conducting research to determine: differences in the incidence and progression of T2DM; sequence of events or biomarkers prior to T2DM diagnosis; disease progression from T2DM to disease-related outcomes, complications and premature mortality; and to assess race/ethnicity differences in the above associations.
High-efficiency particulate air (HEPA) filtration in combination with an electrostatic precipitator (ESP) can be a cost-effective approach to reducing indoor particulate exposure, but ESPs produce ozone. The health effect of combined ESP-HEPA filtration has not been examined. We conducted an intervention study in 89 volunteers. At baseline, the air-handling units of offices and residences for all subjects were comprised of coarse, ESP, and HEPA filtration. During the 5-week long intervention, the subjects were split into 2 groups, 1 with just the ESP removed and the other with both the ESP and HEPA removed. Each subject was measured for cardiopulmonary risk indicators once at baseline, twice during the intervention, and once 2 weeks after baseline conditions were restored. Measured indoor and outdoor PM2.5 and ozone concentrations, coupled with time-activity data, were used to calculate exposures. Removal of HEPA filters increased 24-hour mean PM2.5 exposure by 38 (95% CI: 31, 45) mug/m(3) . Removal of ESPs decreased 24-hour mean ozone exposure by 2.2 (2.0, 2.5) ppb. No biomarkers were significantly associated with HEPA filter removal. In contrast, ESP removal was associated with a -16.1% (-21.5%, -10.4%) change in plasma-soluble P-selectin and a -3.0% (-5.1%, -0.8%) change in systolic blood pressure, suggesting reduced cardiovascular risks.
We focus on the COM-type negative binomial distribution with three parameters, which belongs to COM-type (a, b, 0) class distributions and family of equilibrium distributions of arbitrary birth-death process. Besides, we show abundant distributional properties such as overdispersion and underdispersion, log-concavity, log-convexity (infinite divisibility), pseudo compound Poisson, stochastic ordering, and asymptotic approximation. Some characterizations including sum of equicorrelated geometrically distributed random variables, conditional distribution, limit distribution of COM-negative hypergeometric distribution, and Stein’s identity are given for theoretical properties. COM-negative binomial distribution was applied to overdispersion and ultrahigh zero-inflated data sets. With the aid of ratio regression, we employ maximum likelihood method to estimate the parameters and the goodness-of-fit are evaluated by the discrete Kolmogorov-Smirnov test.
Plume rise parameterizations calculate the rise of pollutant plumes due to effluent buoyancy and exit momentum. Some form of these parameterizations is used by most air quality models. In this paper, the performance of the commonly used Briggs plume rise algorithm was extensively evaluated, through a comparison of the algorithm's results when driven by meteorological observations with direct observations of plume heights in the Athabasca oil sands region. The observations were carried out as part of the Canada-Alberta Joint Oil Sands Monitoring Plan in August and September of 2013. Wind and temperature data used to drive the algorithm were measured in the region of emissions from various platforms, including two meteorological towers, a radio-acoustic profiler, and a research aircraft. Other meteorological variables used to drive the algorithm include friction velocity, boundary-layer height, and the Obukhov length. Stack emissions and flow parameter information reported by continuous emissions monitoring systems (CEMSs) were used to drive the plume rise algorithm. The calculated plume heights were then compared to interpolated aircraft SO2 measurements, in order to evaluate the algorithm's prediction for plume rise. We demonstrate that the Briggs algorithm, when driven by ambient observations, significantly underestimated plume rise for these sources, with more than 50 % of the predicted plume heights falling below half the observed values from this analysis. With the inclusion of the effects of effluent momentum, the choice of different forms of parameterizations, and the use of different stability classification systems, this essential finding remains unchanged. In all cases, approximately 50 % or more of the predicted plume heights fall below half the observed values. These results are in contrast to numerous plume rise measurement studies published between 1968 and 1993. We note that the observations used to drive the algorithms imply the potential presence of significant spatial heterogeneity in meteorological conditions; we examine the potential impact of this heterogeneity in our companion paper (Akingunola et al., 2018). It is suggested that further study using long-term in situ measurements with currently available technologies is warranted to investigate this discrepancy, and that wherever possible, meteorological input variables are observed in the immediate vicinity of the emitting stacks.
Completely understanding the working mechanisms of sophisticated supramolecular self-assembly exhibiting competing paths is very important for chemists en route to acquiring the ability of constructing supramolecular systems with controlled structures and designed functions. Here, the self-aggregation behaviors of an N-heterocyclic aromatic dicarboximide molecule 1, boasting two competing paths that give rise to different supramolecular structures and exhibit distinct thermodynamic features, are carefully examined. First, a group of H-aggregates are observed when providing a medium driving force for aromatic stacking, and their formation is manifested as an anticooperative process. When exposed to enhanced strength of aromatic interactions, these H-aggregates are found to transform into J-aggregates via a cooperative assembly mechanism. With the assistance of a mathematic model accommodating two competing polymerization pathways, calculations are conducted to simulate and explain the thermodynamic equilibria of such a unique supramolecular system. The calculation results are highly consistent with the experimental observations, and some important properties are elucidated. Specifically, the anticooperative assembly mechanism generally promotes the formation of low to medium oligomers, whereas the cooperative path is more competent at producing high polymers. If the anticooperative and cooperative routes coexist and compete for the same molecule, the cooperative formations of high polymers are significantly suppressed unless a very high degree of polymerization can be achieved. Such a unique feature of concurring anticooperative and cooperative paths emerges to the H- and J-aggregates of molecule 1 and thus brings about the interesting sequential appearances of the two types of aggregates under conditions of continuously enlarged driving force for self-aggregation. Finally, based on the knowledge acquired from this study and by analyzing the steric features of 1 that influence its supramolecular packing motifs, a slightly modified molecular structure is designed, with which the intermediate H-aggregation state was successfully suppressed, and a single cooperative J-aggregation path is manifested.
Nanoelectronic devices with specifically designed structures for performance promotion or function expansion are of great interest, aiming for diversified advanced nanoelectronic systems. In this work, we report a dual-material gate (DMG) carbon nanotube (CNT) device with multiple functions, which can be configured either as a high-performance p-type field-effect transistor (FET) or a diode by changing the input manners of the device. When operating as a FET, the device exhibits a large current on/off ratio of more than 108 and a drain-induced barrier lowering of 97.3 mV V−1. When configured as a diode, the rectification ratio of the device can be greater than 105. We then demonstrate configurable analog and digital integrated circuits that are enabled by utilizing these devices. The configurability enables the realization of transformable functions in a single device or circuits, which gives future electronic systems the flexibility to adapt to the diverse requirements of their applications and/or ever-changing operating environments.
