Wear of polyethylene and hylamer on cobalt-chromium : a knee simulator study

Two tests were conducted to examine the wear characteristics of tibial bearings used in total knee replacement systems. Each test consisted of six A/P Glide Tibial Bearings each having a conical control arm. The plastic portion of the conical bearings were all made of UHMWPe. Each of these bearing systems was mounted onto a Co-Cr alloy tibial platform and Co-Cr alloy LCS (low contact stress) femoral component . These test samples were mounted onto the New Jersey Mark III Knee Simulator System. The simulator was configured to produce flexion and axial rotation to simulates normal gait. Each test ran at 2 Hz with saline being sprayed between articulating surfaces. Simulation I tested six UHMWPe bearings with an off-center load applied to the bearing by the femoral component 25° from the articulating surface segment tangent. Simulation II tested three Hylamer® and three UHMWPe bearings without an off-center load. Hylamer®\u27s volumetric loss and wear rate were found to be higher then UHMWPe. Hylamer® had a maximum volumetric loss of 12.86 mm3 and a maximum wear rate of 6.19 mm3/million cycles while UHMWPe had a maximum volumetric loss of 3.57 mm3 and a maximum wear rate of 1.67 mm3/million cycles. Hylamer increase in crystallinity slightly increases its yield strength and ultimate tensile strength. However, by increasing the crystallinity, stiffness is also increased. This increase in stiffness increases the contact stress which in turn increases the wear. Although a slight increase in strength is gained when using Hylamer®, wear resistance, an important characteristic for total knee replacement systems, is reduced

Introducing Solar Thermal "Net Metering" in an Actual small-scale District Heating System: A Case-study Analysis☆

Abstract An energy and economic analysis on an hypothesis of introduction of prosumers in an actual small-scale district heating system (DHS) in Northern Italy has been carried out. The study was performed by means of dynamic simulations of the DHS. The investigated configurations include the transformation of one or more customers in prosumers, producing and self-consuming solar thermal heat, and supplying the DHS with the excess heat produced. For the considered case-study the solar heat fed into the DHS is basically antagonist of the CHP production. This leads to a decrease in the non-renewable energy share for the whole DHS, to a decrease in the profit of the DHS utility and to a profitable investment for the prosumers

A 1-year aerosol chemical speciation monitor (ACSM) source analysis of organic aerosol particle contributions from anthropogenic sources after long-range transport at the TROPOS research station Melpitz

Atmospheric aerosol particles are a complex combination of primary emitted sources (biogenic and anthropogenic) and secondary aerosol resulting from aging processes such as condensation, coagulation, and cloud processing. To better understand their sources, investigations have been focused on urban areas in the past, whereas rural-background stations are normally less impacted by surrounding anthropogenic sources. Therefore, they are predisposed for studying the impact of long-range transport of anthropogenic aerosols. Here, the chemical composition and organic aerosol (OA) sources of submicron aerosol particles measured by an aerosol chemical speciation monitor (ACSM) and a multi-angle absorption photometer (MAAP) were investigated at Melpitz from September 2016 to August 2017. The location of the station at the frontier between western and eastern Europe makes it the ideal place to investigate the impact of long-range transport over Europe. Indeed, the station is under the influence of less polluted air masses from westerly directions and more polluted continental air masses from eastern Europe. The OA dominated the submicron particle mass concentration and showed strong seasonal variability ranging from 39 % (in winter) to 58 % (in summer). It was followed by sulfate (15 % and 20 %) and nitrate (24 % and 11 %). The OA source identification was performed using the rolling positive matrix factorization (PMF) approach to account for the potential temporal changes in the source profile. It was possible to split OA into five factors with a distinct temporal variability and mass spectral signature. Three were associated with anthropogenic primary OA (POA) sources: hydrocarbon-like OA (HOA; 5.2 % of OA mass in winter and 6.8 % in summer), biomass burning OA (BBOA; 10.6 % and 6.1 %) and coal combustion OA (CCOA; 23 % and 8.7 %). Another two are secondary and processed oxygenated OA (OOA) sources: less oxidized OOA (LO-OOA; 28.4 % and 36.7 %) and more oxidized OOA (MO-OOA; 32.8 % and 41.8 %). Since equivalent black carbon (eBC) was clearly associated with the identified POA factors (sum of HOA, BBOA, and CCOA; R2= 0. 87), eBC's contribution to each of the POA factors was achieved using a multilinear regression model. Consequently, CCOA represented the main anthropogenic sources of carbonaceous aerosol (sum of OA and eBC) not only during winter (56 % of POA in winter) but also in summer (13 % of POA in summer), followed by BBOA (29 % and 69 % of POA in winter and summer, respectively) and HOA (15 % and 18 % of POA in winter and summer, respectively). A seasonal air mass cluster analysis was used to understand the geographical origins of the different aerosol types and showed that during both winter and summer time, PM1 (PM with an aerodynamic diameter smaller than 1 µm) air masses with eastern influence were always associated with the highest mass concentration and the highest coal combustion fraction. Since during wintertime CCOA is a combination of domestic heating and power plant emissions, the summer contribution of CCOA emphasizes the critical importance of coal power plant emissions to rural-background aerosols and its impact on air quality, through long-range transportation.</p

Organic Aerosol source apportionment in London 2013 with ME-2:Exploring the solution space with annual and seasonal analysis

The multilinear engine (ME-2) factorization tool is being widely used following the recent development of the Source Finder (SoFi) interface at the Paul Scherrer Institute. However, the success of this tool, when using the <i>a</i> value approach, largely depends on the inputs (i.e. target profiles) applied as well as the experience of the user. A strategy to explore the solution space is proposed, in which the solution that best describes the organic aerosol (OA) sources is determined according to the systematic application of predefined statistical tests. This includes trilinear regression, which proves to be a useful tool for comparing different ME-2 solutions. Aerosol Chemical Speciation Monitor (ACSM) measurements were carried out at the urban background site of North Kensington, London from March to December 2013, where for the first time the behaviour of OA sources and their possible environmental implications were studied using an ACSM. Five OA sources were identified: biomass burning OA (BBOA), hydrocarbon-like OA (HOA), cooking OA (COA), semivolatile oxygenated OA (SVOOA) and low-volatility oxygenated OA (LVOOA). ME-2 analysis of the seasonal data sets (spring, summer and autumn) showed a higher variability in the OA sources that was not detected in the combined March–December data set; this variability was explored with the triangle plots <i>f</i>44 : <i>f</i>43 <i>f</i>44 : <i>f</i>60, in which a high variation of SVOOA relative to LVOOA was observed in the <i>f</i>44 : <i>f</i>43 analysis. Hence, it was possible to conclude that, when performing source apportionment to long-term measurements, important information may be lost and this analysis should be done to short periods of time, such as seasonally. Further analysis on the atmospheric implications of these OA sources was carried out, identifying evidence of the possible contribution of heavy-duty diesel vehicles to air pollution during weekdays compared to those fuelled by petrol

Quantum symmetries and exceptional collections

We study the interplay between discrete quantum symmetries at certain points in the moduli space of Calabi-Yau compactifications, and the associated identities that the geometric realization of D-brane monodromies must satisfy. We show that in a wide class of examples, both local and compact, the monodromy identities in question always follow from a single mathematical statement. One of the simplest examples is the Z_5 symmetry at the Gepner point of the quintic, and the associated D-brane monodromy identity

Constructing a data-driven receptor model for organic and inorganic aerosol : a synthesis analysis of eight mass spectrometric data sets from a boreal forest site

The interactions between organic and inorganic aerosol chemical components are integral to understanding and modelling climate and health-relevant aerosol physicochemical properties, such as volatility, hygroscopicity, light scattering and toxicity. This study presents a synthesis analysis for eight data sets, of non-refractory aerosol composition, measured at a boreal forest site. The measurements, performed with an aerosol mass spectrometer, cover in total around 9 months over the course of 3 years. In our statistical analysis, we use the complete organic and inorganic unit-resolution mass spectra, as opposed to the more common approach of only including the organic fraction. The analysis is based on iterative, combined use of (1) data reduction, (2) classification and (3) scaling tools, producing a data-driven chemical mass balance type of model capable of describing site-specific aerosol composition. The receptor model we constructed was able to explain 83 +/- 8% of variation in data, which increased to 96 +/- 3% when signals from low signal-to-noise variables were not considered. The resulting interpretation of an extensive set of aerosol mass spectrometric data infers seven distinct aerosol chemical components for a rural boreal forest site: ammonium sulfate (35 +/- 7% of mass), low and semi-volatile oxidised organic aerosols (27 +/- 8% and 12 +/- 7 %), biomass burning organic aerosol (11 +/- 7 %), a nitrate-containing organic aerosol type (7 +/- 2 %), ammonium nitrate (5 +/- 2 %), and hydrocarbon-like organic aerosol (3 +/- 1 %). Some of the additionally observed, rare outlier aerosol types likely emerge due to surface ionisation effects and likely represent amine compounds from an unknown source and alkaline metals from emissions of a nearby district heating plant. Compared to traditional, ionbalance-based inorganics apportionment schemes for aerosol mass spectrometer data, our statistics-based method provides an improved, more robust approach, yielding readily useful information for the modelling of submicron atmospheric aerosols physical and chemical properties. The results also shed light on the division between organic and inorganic aerosol types and dynamics of salt formation in aerosol. Equally importantly, the combined methodology exemplifies an iterative analysis, using consequent analysis steps by a combination of statistical methods. Such an approach offers new ways to home in on physicochemically sensible solutions with minimal need for a priori information or analyst interference. We therefore suggest that similar statisticsbased approaches offer significant potential for un- or semi-supervised machine-learning applications in future analyses of aerosol mass spectrometric data.Peer reviewe

Seasonal variations in aerosol particle composition at the puy-de-Dôme research station in France

Detailed investigations of the chemical and microphysical properties of atmospheric aerosol particles were performed at the puy-de-Dôme (pdD) research station (1465 m) in autumn (September and October 2008), winter (February and March 2009), and summer (June 2010) using a compact Time-of-Flight Aerosol Mass Spectrometer (cToF-AMS). Over the three campaigns, the average mass concentrations of the non-refractory submicron particles ranged from 10 μg m&lt;sup&gt;&amp;minus;3&lt;/sup&gt; up to 27 μg m&lt;sup&gt;&amp;minus;3&lt;/sup&gt;. Highest nitrate and ammonium mass concentrations were measured during the winter and during periods when marine modified airmasses were arriving at the site, whereas highest concentrations of organic particles were measured during the summer and during periods when continental airmasses arrived at the site. The measurements reported in this paper show that atmospheric particle composition is strongly influenced by both the season and the origin of the airmass. The total organic mass spectra were analysed using positive matrix factorisation to separate individual organic components contributing to the overall organic particle mass concentrations. These organic components include a low volatility oxygenated organic aerosol particle (LV-OOA) and a semi-volatile organic aerosol particle (SV-OOA). Correlations of the LV-OOA components with fragments of &lt;i&gt;m/z&lt;/i&gt; 60 and &lt;i&gt;m/z&lt;/i&gt; 73 (mass spectral markers of wood burning) during the winter campaign suggest that wintertime LV-OOA are related to aged biomass burning emissions, whereas organic aerosol particles measured during the summer are likely linked to biogenic sources. Equivalent potential temperature calculations, gas-phase, and LIDAR measurements define whether the research site is in the planetary boundary layer (PBL) or in the free troposphere (FT)/residual layer (RL). We observe that SV-OOA and nitrate particles are associated with air masses arriving from the PBL where as particle composition measured from RL/FT airmasses contain high mass fractions of sulphate and LV-OOA. This study provides unique insights into the effects of season and airmass variability on regional aerosol particles measured at an elevated site

Characterizing the impact of urban emissions on regional aerosol particles: airborne measurements during the MEGAPOLI experiment

The MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) experiment took place in July 2009. The aim of this campaign was to study the aging and reactions of aerosol and gas-phase emissions in the city of Paris. Three ground-based measurement sites and several mobile platforms including instrument equipped vehicles and the ATR-42 aircraft were involved. We present here the variations in particle- and gas-phase species over the city of Paris, using a combination of high-time resolution measurements aboard the ATR-42 aircraft. Particle chemical composition was measured using a compact time-of-flight aerosol mass spectrometer (C-ToF-AMS), giving detailed information on the non-refractory submicron aerosol species. The mass concentration of black carbon (BC), measured by a particle absorption soot photometer (PSAP), was used as a marker to identify the urban pollution plume boundaries. Aerosol mass concentrations and composition were affected by air-mass history, with air masses that spent longest time over land having highest fractions of organic aerosol and higher total mass concentrations. The Paris plume is mainly composed of organic aerosol (OA), BC, and nitrate aerosol, as well as high concentrations of anthropogenic gas-phase species such as toluene, benzene, and NO_x. Using BC and CO as tracers for air-mass dilution, we observe the ratio of ΔOA / ΔBC and ΔOA / ΔCO increase with increasing photochemical age (−log(NO_x / NO_y)). Plotting the equivalent ratios of different organic aerosol species (LV-OOA, SV-OOA, and HOA) illustrate that the increase in OA is a result of secondary organic aerosol (SOA) formation. Within Paris the changes in the ΔOA / &Delta;CO are similar to those observed during other studies in London, Mexico City, and in New England, USA. Using the measured SOA volatile organic compounds (VOCs) species together with organic aerosol formation yields, we were able to predict ~50% of the measured organics. These airborne measurements during the MEGAPOLI experiment show that urban emissions contribute to the formation of OA and have an impact on aerosol composition on a regional scale

Real-time source apportionment of organic aerosols in three European cities.

97% of the urban population in the EU in 2019 were exposed to an annual fine particulate matter level higher than the World Health Organization (WHO) guidelines (5 μg/m3). Organic aerosol (OA) is one of the major air pollutants, and the knowledge of its sources is crucial for designing cost-effective mitigation strategies. Positive matrix factorization (PMF) on aerosol mass spectrometer (AMS) or aerosol chemical speciation monitor (ACSM) data is the most common method for source apportionment (SA) analysis on ambient OA. However, conventional PMF requires extensive human labor, preventing the implementation of SA for routine monitoring applications. This study proposes the source finder real-time (SoFi RT, Datalystica Ltd.) approach for efficient retrieval of OA sources. The results generated by SoFi RT agree remarkably well with the conventional rolling PMF results regarding factor profiles, time series, diurnal patterns, and yearly relative contributions of OA factor on three year-long ACSM data sets collected in Athens, Paris, and Zurich. Although the initialization of SoFi RT requires a priori knowledge of OA sources (i.e., the approximate number of factors and relevant factor profiles) for the sampling site, this technique minimizes user interactions. Eventually, it could provide up-to-date trustable information on timescales useful to policymakers and air quality modelers

Global organization of metabolic fluxes in the bacterium, Escherichia coli

Cellular metabolism, the integrated interconversion of thousands of metabolic substrates through enzyme-catalyzed biochemical reactions, is the most investigated complex intercellular web of molecular interactions. While the topological organization of individual reactions into metabolic networks is increasingly well understood, the principles governing their global functional utilization under different growth conditions pose many open questions. We implement a flux balance analysis of the E. coli MG1655 metabolism, finding that the network utilization is highly uneven: while most metabolic reactions have small fluxes, the metabolism's activity is dominated by several reactions with very high fluxes. E. coli responds to changes in growth conditions by reorganizing the rates of selected fluxes predominantly within this high flux backbone. The identified behavior likely represents a universal feature of metabolic activity in all cells, with potential implications to metabolic engineering.Comment: 15 pages 4 figure