Demonstration of a method for the direct determination of polycyclic aromatic hydrocarbons in submerged sediments

We describe the development of a novel method for real-time in situ characterization of polycyclic aromatic hydrocarbons (PAHs) in submerged freshwater sediments. Laser-induced fluorescence (LIF) spectroscopy, a mature technique for PAH characterization in terrestrial sediments, was adapted for shipboard use. A cone penetrometer-type apparatus was designed for probe penetration at a constant rate (1 cm/s) to a depth of 3 m. A field-portable LIF system was used for in situ measurements in which the output of a pulsed excimer laser was transmitted by optical fiber to a sapphire window (6.4-mm o.d.) in the probe wall; fluorescent emission was collected by a separate optical fiber for transmission to the spectrometer on deck. Four wavelengths (340, 390, 440, 490 nm) were selected via optical delay lines, and multiple-wavelength waveforms were created. These multiple-wavelength waveforms contain information on the fluorescence frequency, intensity, and emission decay rate. Field testing was conducted at 10 sites in Milwaukee Harbor (total PAH concentrations ranged from approximately 10 to 650 microg/g); conventional sediment core samples were collected concurrently. The core samples were analyzed by EPA methods 3545 (pressurized fluid extraction, PFE) and 8270C (gas chromatography-mass spectrometry, GC-MS) for PAHs. A partial least-squares regression (PLSR) model wasthen created based on laboratory LIF measurements and PFE-GC-MS of the core samples. The PLSR model was applied to the in situ field test data, and 13 of the 16 EPA-regulated PAHs were quantified with a relative error of <30% overall (the remaining three PAHs were found at levels insufficient to quantify). We additionally describe preliminary source apportionment relationships that were revealed by the PLSR model for the in situ LIF measurements.     

Oviposition decisions in the seed beetle, Callosobruchus maculatus (Coleoptera: Bruchidae): effects of seed size on superparasitism

The seed parasite Callosobruchus maculatus generally disperses eggs uniformly among seeds. We used cowpeas (Vigna unguiculata) of two class sizes (large and small) to test predictions based on a simple resource threshold model that females will distribute eggs among seeds in a manner that maximizes the amount of resources allocated to each offspring. When females were presented with multiple seeds of the same size, they tended to distribute their eggs relatively uniformly among seeds (I?0.27 where I is the variance/mean ratio, and I=1 reflects a random Poisson distribution). However, when seeds varied in size females distributed their eggs in a manner that maximized the amount of resources per offspring; females distributed eggs as predicted by seed differences in mass rather than as predicted by seed differences in surface area. Therefore, females must evaluate the relative quantity of resources available inside of a seed more accurately than if they compared the ratio of surface areas between seeds of varying size. Instead, females must either use cues other than surface area when estimating seed mass, or must have the ability to extrapolate non-linearly from surface area to seed mass. Females with higher egg loads (4-d-old females) laid more eggs when presented with seeds, but did not distribute their eggs less uniformly, than females with lower egg loads (1-d-old females), indicating that high egg load does not reduce female sensitivity to seed size and the presence of conspecific eggs.     

Emissions of metals associated with motor vehicle roadways

Emissions of metals and other particle-phase species from on-road motor vehicles were measured in two tunnels in Milwaukee, WI during the summer of 2000 and winter of 2001. Emission factors were calculated from measurements of fine (PM2.5) and coarse (PM10) particulate matter at tunnel entrances and exits, and effects of fleet composition and season were investigated. Cascade impactors (MOUDI) were used to obtain size-resolved metal emission rates. Metals were quantified with inductively-coupled plasma mass spectrometry (ICP-MS) and X-ray fluorescence (XRF). PM10 emission rates ranged from 38.7 to 201 mg km(-1) and were composed mainly of organic carbon (OC, 30%), inorganic ions (sulfate, chloride, nitrate, ammonium, 20%), metals (19%), and elemental carbon (EC, 9.3%). PM10 metal emissions were dominated by crustal elements Si, Fe, Ca, Na, Mg, Al, and K, and elements associated with tailpipe emissions and brake and tire wear, including Cu, Zn, Sb, Ba, Pb, and S. Metals emitted in PM2.5 were lower (11.6% of mass). Resuspension of roadway dust was dependent on weather and road surface conditions, and increased emissions were related to higher traffic volumes and fractions of heavy trucks. Emission of noble metals from catalytic converters appeared to be impacted by the presence of older vehicles. Elements related to brake wear were impacted by enriched road dust resuspension, but correlations between these elements in PM2.5 indicate that direct brake wear emissions are also important. A submicrometer particle mode was observed in the emissions of Pb, Ca, Fe, and Cu.     

NMR-based metabonomics detection of differences in the metabolism of hydrolysed versus intact protein of similar amino acid profile

BACKGROUND: Proton nuclear magnetic resonance (NMR)‐based metabonomics has only recently been applied to nutritional research. The limitation of any analytical technique is its sensitivity in detecting the smallest variation. Alterations in nutrition often produce only subtle metabolic modulations. The objective of this study was to determine if NMR‐based metabonomics could detect variations in the metabolic profile of urine from pigs digesting either native casein (NC) or the same casein that had been enzymatically hydrolysed (EHC). NMR permits simultaneous detection of a large number of metabolites, thus allowing detection of unanticipated metabolic fluctuations that may otherwise have gone undetected with the use of only targeted analysis. RESULTS: Partial least squares discriminant analysis identified significantly (P < 0.05) higher urinary excretions of leucine, valine, taurine and glycine by pigs on the EHC‐based diet. CONCLUSION: NMR‐based metabonomics is a sensitive method that can uncover unanticipated metabolic changes brought about by physicochemical changes to the feedstock (i.e. hydrolysis). The data show a lower efficiency of retention by the kidney of some amino acids following ingestion of a hydrolysed protein. Copyright © 2012 Society of Chemical Industry     

Bioeconomics of invasive species: using real options theory to integrate ecology,economics, and risk management

Policy makers face two countervailing incentives in invasive species management—the Pull-incentive to move quickly and the Push-incentive to wait-and-see before making irreversible investments. Real options theory is used to help understand this fundamental trade-off both in design and application. In designing policies, real options theory shows how the management of invasive species should account for the intertwined concepts of ecological risk/ecological irreversibility and economic risk/economic irreversibility. In applying policies, real options theory shows for species spreading slowly with little uncertainty, the push-incentive dominates, advocating a wait-and-see approach. In contrast, for fastspreading species, their diffusion is too fast and too unpredictable to do anything other than act immediately – the pull-incentive dominates. In addition, results indicate both the source and the magnitude of uncertainty matter, but the nature of the impact depends on the irreversibility of the policy decision highlighting the key value of flexibility in policy design and application.     

Tribological Characteristics of Aqueous Graphene Oxide,Graphitic Carbon Nitride,and Their Mixed Suspensions

The tribological performance of graphene oxide (GO), graphitic carbon nitride (g-C₃N₄), and their mixed (g-C₃N₄/GO) aqueous suspensions was investigated. The 0.06 wt% GO, 0.06 wt% g-C₃N₄, and 0.06 wt% 1:1 g-C₃N₄/GO suspensions reduced the coefficient of friction (COF) by 37, 26 and 37% and wear mark radius by 19.1, 16.0 and 19.6%, respectively, in comparison with water. Pure g-C₃N₄ and GO suspensions showed unstable lubrication in the tests with relatively high loads and speeds, while the g-C₃N₄/GO mixed suspension had superior tribological performance in all tested conditions. This is because in the mixed suspension g-C₃N₄ agglomerates became smaller, and GO nanosheets exhibited fewer wrinkles and less stacking, which enabled the formation of a layer of tribo-composite film. As a result, the friction, wear and tribo-corrosion were reduced during sliding.     

Optimization of CdTe thin‐film solar cell efficiency using a sputtered,oxygenated CdS window layer

A major source of loss in cadmium sulfide/cadmium telluride (CdS/CdTe) solar cells results from light absorbed in the CdS window layer, which is not converted to electrical current. This film can be made more transparent by oxygen incorporation during sputter deposition at ambient temperature. Prior to this work, this material has not produced high‐efficiency devices on tin oxide‐coated soda‐lime‐glass substrates used industrially. Numerous devices were fabricated over a variety of process conditions to produce an optimized device. Although the material does not show a consistent increase in band gap with oxygenation, absorption in this layer can be virtually eliminated over the relevant spectrum, leading to an increase in short‐circuit current. Meanwhile, fill factor is maintained, and open‐circuit voltage increases relative to baseline devices with sublimated CdS. The trend of device parameters with oxygenation and thickness is consistent with an increasing conduction band offset at the window/CdTe interface. Optimization considering both initial efficiency and stability resulted in a National Renewable Energy Laboratory verified 15.2%‐efficient cell on 3.2‐mm soda‐lime glass. This window material was shown to be compatible with SnO₂‐based transparent conducting oxide and high resistance transparent coated substrates using in‐line compatible processes. Copyright © 2015 John Wiley & Sons, Ltd     

拉近客户要创新企业获得利润在于双赢

企业和顾客是一根绳上的蚱蜢,也是一对冤家。如何消除销售过程中具有对抗性的一面。成功说服顾客购买自己的产品。是许多企业的难题。     

SARS-CoV-2 Spike Protein Binding of Glycated Serum Albumin—Its Potential Role in the Pathogenesis of the COVID-19 Clinical Syndromes and Bias towards Individuals with Pre-Diabetes/Type 2 Diabetes and Metabolic Diseases

The immune response to SARS-CoV-2 infection requires antibody recognition of the spike protein. In a study designed to examine the molecular features of anti-spike and anti-nucleocapsid antibodies, patient plasma proteins binding to pre-fusion stabilised complete spike and nucleocapsid proteins were isolated and analysed by matrix-assisted laser desorption ionisation–time of flight (MALDI-ToF) mass spectrometry. Amongst the immunoglobulins, a high affinity for human serum albumin was evident in the anti-spike preparations. Careful mass comparison revealed the preferential capture of advanced glycation end product (AGE) forms of glycated human serum albumin by the pre-fusion spike protein. The ability of bacteria and viruses to surround themselves with serum proteins is a recognised immune evasion and pathogenic process. The preference of SARS-CoV-2 for AGE forms of glycated serum albumin may in part explain the severity and pathology of acute respiratory distress and the bias towards the elderly and those with (pre)diabetic and atherosclerotic/metabolic disease.     

Simulating the Feasibility of Using Liquid Micro-Jets for Determining Electron–Liquid Scattering Cross-Sections

The extraction of electron–liquid phase cross-sections (surface and bulk) is proposed through the measurement of (differential) energy loss spectra for electrons scattered from a liquid micro-jet. The signature physical elements of the scattering processes on the energy loss spectra are highlighted using a Monte Carlo simulation technique, originally developed for simulating electron transport in liquids. Machine learning techniques are applied to the simulated electron energy loss spectra, to invert the data and extract the cross-sections. The extraction of the elastic cross-section for neon was determined within 9% accuracy over the energy range 1–100 eV. The extension toward the simultaneous determination of elastic and ionisation cross-sections resulted in a decrease in accuracy, now to within 18% accuracy for elastic scattering and 1% for ionisation. Additional methods are explored to enhance the accuracy of the simultaneous extraction of liquid phase cross-sections.