A New Automated Method and Sample Data Flow for Analysis of Volatile Nitrosamines in Human Urine

Volatile nitrosamines (VNAs) are a group of compounds classified as probable (group 2A) and possible (group 2B) carcinogens in humans. Along with certain foods and contaminated drinking water, VNAs are detected at high levels in tobacco products and in both mainstream and side-stream smoke. Our laboratory monitors six urinary VNAs—N-nitrosodimethylamine (NDMA), N-nitrosomethylethylamine (NMEA), N-nitrosodiethylamine (NDEA), N-nitrosopiperidine (NPIP), N-nitrosopyrrolidine (NPYR), and N-nitrosomorpholine (NMOR)—using isotope dilution GC-MS/ MS (QQQ) for large population studies such as the National Health and Nutrition Examination Survey (NHANES). In this paper, we report for the first time a new automated sample preparation method to more efficiently quantitate these VNAs. Automation is done using Hamilton STARTM and Caliper StaccatoTM workstations. This new automated method reduces sample preparation time from 4 hours to 2.5 hours while maintaining precision (inter-run CV < 10%) and accuracy (85% - 111%). More importantly this method increases sample throughput while maintaining a low limit of detection (<10 pg/mL) for all analytes. A streamlined sample data flow was created in parallel to the automated method, in which samples can be tracked from receiving to final LIMs output with minimal human intervention, further minimizing human error in the sample preparation process. This new automated method and the sample data flow are currently applied in bio-monitoring of VNAs in the US non-institutionalized population NHANES 2013-2014 cycle.

Assessment of Uinta Basin Oil and Natural Gas Well Pad Pneumatic Controller Emissions

In the fall of 2016, a field study was conducted in the Uinta Basin Utah to improve information on oil and natural gas well pad pneumatic controllers (PCs) and emission measurement methods. A total of 80 PC systems at five oil sites (supporting six wells) and three gas sites (supporting 12 wells) were surveyed, and emissions data were produced using a combination of measurements and engineering emission estimates. Ninety-six percent of the PCs surveyed were low actuation frequency intermittent vent type. The overall whole gas emission rate for the study was estimated at 0.36 scf/h with the majority of emissions occurring from three continuous vent PCs (1.1 scf/h average) and eleven (14%) malfunctioning intermittent vent PC systems (1.6 scf/h average). Oil sites employed, on average 10.3 PC systems per well compared to 1.5 for gas sites. Oil and gas sites had group average PC emission rates of 0.28 scf/h and 0.67 scf/h, respectively. This difference was due in part to differing site selection procedures used for oil and gas sites. The PC system types encountered, the engineering emissions estimate approach, and comparisons to measurements are described. Survey methods included identification of malfunctioning PC systems and emission measurements with augmented high volume sampling and installed mass flow meters, each providing a somewhat different representation of emissions that are elucidated through example cases.

Machine-learning informed prediction of high-entropy solid solution formation:Beyond the Hume-Rothery rules

The empirical rules for the prediction of solid solution formation proposed so far in the literature usually have very compromised predictability.Some rules with seemingly good predictability were,however,tested using small data sets.Based on an unprecedented large dataset containing 1252 multicomponent alloys,machine-learning methods showed that the formation of solid solutions can be very accurately predicted(93%).The machine-learning results help identify the most important features,such as molar volume,bulk modulus,and melting temperature.

Interactions of extracellular DNA with aromatized biochar and protection against degradation by DNaseⅠ

With increasing environmental application,biochar(BC)will inevitably interact with and impact environmental behaviors of widely distributed extracellular DNA(eDNA),which however still remains to be studied.Herein,the adsorption/desorption and the degradation by nucleases of eDNA on three aromatized BCs pyrolyzed at 700℃were firstly investigated.The results show that the eDNA was irreversibly adsorbed by aromatized BCs and the pseudo-second-order and Freundlich models accurately described the adsorption process.Increasing solution ionic strength or decreasing pH below 5.0 significantly increased the eDNA adsorption on BCs.However,increasing pH from 5.0 to 10.0 faintly decreased eDNA adsorption.Electrostatic interaction,Ca ion bridge interaction,andπ-πinteraction between eDNA and BC could dominate the eDNA adsorption,while ligand exchange and hydrophobic interactions were minor contributors.The presence of BCs provided a certain protection to eDNA against degradation by DNase I.BC-bound eDNA could be partly degraded by nuclease,while BC-bound nuclease completely lost its degradability.These findings are of fundamental significance for the potential application of biochar in eDNA dissemination management and evaluating the environmental fate of eDNA.

Constraints and Opportunities for Detecting Land Surface Phenology in Drylands

Land surface phenology(LSP)enables global-scale tracking of ecosystem processes,but its utility is limited in drylands due to low vegetation cover and resulting low annual amplitudes of vegetation indices(VIs).Due to the importance of drylands for biodiversity,food security,and the carbon cycle,it is necessary to understand the limitations in measuring dryland dynamics.Here,using simulated data and multitemporal unmanned aerial vehicle(UAV)imagery of a desert shrubland,we explore the feasibility of detecting LSP with respect to fractional vegetation cover,plant functional types,VI uncertainty,and two different detection algorithms.Using simulated data,we found that plants with distinct VI signals,such as deciduous shrubs,can require up to 60%fractional cover to consistently detect LSP.Evergreen plants,with lower seasonal VI amplitude,require considerably higher cover and can have undetectable phenology even with 100%vegetation cover.Our evaluation of two algorithms showed that neither performed the best in all cases.Even with adequate cover,biases in phenological metrics can still exceed 20 days and can never be 100%accurate due to VI uncertainty from shadows,sensor view angle,and atmospheric interference.We showed how high-resolution UAV imagery enables LSP studies in drylands and highlighted important scale effects driven by within-canopy VI variation.With high-resolution imagery,the open canopies of drylands are beneficial as they allow for straightforward identification of individual plants,enabling the tracking of phenology at the individual level.Drylands thus have the potential to become an exemplary environment for future LSP research.

速度——男人最好的朋友

曾有直男坦言:如果让男人去影院挑一部电影,那一定是战车中的裸身男女。这让女伴皱眉的结果暴露了男人的顽劣特性。没错,机械与速度霸占着男人的大半个感官世界,仅仅是飞沙走石的轰鸣声就足以激起肾上腺素,让男人们死盯着赛道握拳呐喊。