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It is known that Microsetella norvegica feed on phytoplankton and provide an important link to higher trophic levels in Arctic fjords, such as fish sprat (Sprattus sprattus) and three-spined stickleback (Gasterosteus aculeatus). It has recently been suggested that M. norvegica may also contribute substantially to carbon flux attenuation during periods of high abundance. However, we still know very little about how seasonal variations in abundance and vertical distribution of M. norvegica impact the efficiency of the biological carbon pump in Arctic fjords. We investigated the role of Microsetella norvegica, a small harpacticoid copepod, for particulate organic carbon flux attenuation via aggregate feeding in a subarctic fjord. We quantified the vertical distribution and abundance of M. norvegica, phytoplankton, and marine snow simultaneously with a Digital Autonomous Video Plankton Recorder in Porsangerfjord, northern Norway, between August 2013 and November 2014. We estimated the highest abundance of M. norvegica as 4.86x106 individuals m-2 in October. Our results suggest that M. norvegica preferred diatoms over both marine snow and the prymnesiophyte Phaeocystis pouchetii during euphotic bloom conditions. However, during oligotrophic conditions when phytoplankton were scarce, M. norvegica switched to marine snow as a food source. M. norvegica has the potential to explain 1.4% and 0.29% of the total carbon flux attenuation in October and November, respectively. These results suggest that small copepods feed on settling detritus when no alternative food is available. Detritus feeding by M. norvegica may have an ecological impact during the polar night, both via direct carbon flux attenuation, but also as secondary producers in periods with low primary production. Currently small copepods such as M. norvegica are not included in carbon budgets or large-scale modelling, but considering their potentially high abundance they may represent an important but overlooked pathway in both the carbon cycle and trophic level interactions.

Abstract Inorganic nitrate production is critical in atmospheric chemistry that reflects the oxidation capacity and the acidity of the atmosphere. Here we use the oxygen anomaly of nitrate (Δ17O( $$\rm{NO}_{3}^{-}$$ NO 3 − )) in high-time-resolved (3 h) aerosols to explore the chemical mechanisms of nitrate evolution in fine particles during the winter in Nanjing, a megacity of China. The continuous Δ17O( $$\rm{NO}_{3}^{-}$$ NO 3 − ) observation suggested the dominance of nocturnal chemistry (NO3 + HC/H2O and N2O5 + H2O/Cl−) in nitrate formation in the wintertime. Significant diurnal variations of nitrate formation pathways were found. The contribution of nocturnal chemistry increased at night and peaked (72%) at midnight. Particularly, nocturnal pathways became more important for the formation of nitrate in the process of air pollution aggravation. In contrast, the contribution of daytime chemistry (NO2 + OH/H2O) increased with the sunrise and showed a highest fraction (48%) around noon. The hydrolysis of N2O5 on particle surfaces played an important role in the daytime nitrate production on haze days. In addition, the reaction of NO2 with OH radicals was found to dominate the nitrate production after nitrate chemistry was reset by the precipitation events. These results suggest the importance of high-time-resolved observations of Δ17O( $$\rm{NO}_{3}^{-}$$ NO 3 − ) for exploring dynamic variations in reactive nitrogen chemistry.

Abstract Experimentation and Measurement (E&M) capabilities allow organizations to accurately assess the impact of new propositions and to experiment with many variants of existing products. However, until now, the question of measuring the measurer, or valuing the contribution of an E&M capability to organizational success has not been addressed. We tackle this problem by analyzing how, by decreasing estimation uncertainty, E&M platforms allow for better prioritization. We quantify this benefit in terms of expected relative improvement in the performance of all new propositions and provide guidance for how much an E&M capability is worth and when organizations should invest in one.

Joining nanostructured ferritic alloys (NFAs) has proved challenging, as the nano-oxides that provide superior strength, creep resistance, and radiation tolerance at high temperatures tend to agglomerate, redistribute, and coarsen during conventional fusion welding. In this study, capacitive discharge resistance welding (CDRW)—a solid-state variant of resistance welding—was used to join end caps and thin-walled cladding tubes of the NFA 14YWT. The resulting solid-state joints were found to be hermetically sealed and were characterized across the weld region using electron microscopy (macroscopic, microscopic, and nanometer scales) and nanoindentation. Microstructural evolution near the weld line was limited to narrow (~50–200 μm) thermo-mechanically affected zones (TMAZs) and to a reduction in pre-existing component textures. Dispersoid populations (i.e., nano-oxides and larger oxide particles) appeared unchanged by all but the highest energy and power CDRW condition, with this extreme producing only minor nano-oxide coarsening (~2 nm → ~5 nm Ø). Despite a minimal microstructural change, the TMAZs were found to be ~10% softer than the surrounding base material. These findings are considered in terms of past solid-state welding (SSW) efforts—cladding applications and NFA-like materials in particular—and in terms of strengthening mechanisms in NFAs and the potential impacts of localized temperature–strain conditions during SSW.

Zinc electrowinning is an energy-intensive step of hydrometallurgical zinc production in which ohmic drop contributes the second highest overpotential in the process. As the ohmic drop is a result of electrolyte conductivity, three conductivity models (Aalto-I, Aalto-II and Aalto-III) were formulated in this study based on the synthetic industrial electrolyte conditions of Zn (50–70 g/dm3), H2SO4 (150–200 g/dm3), Mn (0–8 g/dm3), Mg (0–4 g/dm3), and temperature, T (30–40 °C). These studies indicate that electrolyte conductivity increases with temperature and H2SO4 concentration, whereas metal ions have negative effects on conductivity. In addition, the interaction effects of temperature and the concentrations of metal ions on solution conductivity were tested by comparing the performance of the linear model (Aalto-I) and interrelated models (Aalto-II and Aalto-III) to determine their significance in the electrowinning process. Statistical analysis shows that Aalto-I has the highest accuracy of all the models developed and investigated in this study. From the industrial validation, Aalto-I also demonstrates a high level of correlation in comparison to the other models presented in this study. Further comparison of model Aalto-I with the existing published models from previous studies shows that model Aalto-I substantially improves the accuracy of the zinc conductivity empirical model.

For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide free services that are valued by billions of people globally.

Numerous studies have examined the relationship between alveolar macrophages (AM) and crystalline silica (SiO2) using in vitro and in vivo immunotoxicity models; however, exactly how exposure to SiO2 alters the functionality of AM and the potential consequences for immunity to respiratory pathogens remains largely unknown. Because recognition and clearance of inhaled particulates and microbes is largely mediated by pattern recognition receptors (PRR) on the surface of AM, we hypothesized that exposure to SiO2 limits the ability of AM to respond to bacterial challenge by altering PRR expression. Alveolar and bone marrow-derived macrophages downregulate TLR2 expression following acute SiO2 exposure (e.g. 4 hours). Interestingly, these responses were dependent upon interactions between SiO2 and the class A scavenger receptor CD204, but not MARCO. Furthermore, SiO2 exposure decreased uptake of fluorescently labeled Pam2CSK4 and Pam3CSK4, resulting in reduced secretion of IL-1β, but not IL-6. Collectively, our data suggest that SiO2 exposure alters AM phenotype, which in turn affects their ability to uptake and respond to bacterial lipoproteins.

Cost effective hydrolysis of biomass into sugars for biofuel production requires high-performance low-cost glycoside hydrolase (GH) cocktails that are active under demanding process conditions. Improving the performance of GH cocktails depends knowledge of many critical parameters including individual enzyme stabilities, optimal reaction conditions, kinetics and specificity of reaction. With this information, rate- and/or yield-limiting reactions that can be potentially improved through substitution, synergistic complementation, or protein engineering. Given the wide range of substrates and methods used for GH characterization, it is difficult to compare results across a myriad of approaches to identify high performance and synergistic combinations of enzymes. Here we describe a platform for systematic screening of GH activities using automatic biomass handling, bioconjugate chemistry, robotic liquid handling, and nanostructure-initiator mass spectrometry (NIMS). Twelve well-characterized substrates spanning the types of glycosidic linkages found in plant cell walls are included in the experimental workflow. To test the application of this platform and substrate panel, we studied the reactivity of three engineered cellulases and their synergy of combination across a range of reaction conditions and enzyme concentrations. We anticipate that large-scale screening using the standardized platform and substrates will generate critical datasets to enable direct comparison of enzyme activities for cocktail design.

The land planarian Platydemus manokwari de Beauchamp, 1963 or “New Guinea flatworm” is a highly invasive species, mainly in the Pacific area, and recently in Europe (France). We report specimens from six additional countries and territories: New Caledonia (including mainland and two of the Loyalty Islands, Lifou and Maré), Wallis and Futuna Islands, Singapore, Solomon Islands, Puerto Rico, and Florida, USA. We analysed the COI gene (barcoding) in these specimens with two sets of primers and obtained 909 bp long sequences. In addition, specimens collected in Townsville (Australia) were also sequenced. Two haplotypes of the COI sequence, differing by 3.7%, were detected: the “World haplotype” found in France, New Caledonia, French Polynesia, Singapore, Florida and Puerto Rico; and the “Australian haplotype” found in Australia. The only locality with both haplotypes was in the Solomon Islands. The country of origin of Platydemus manokwari is New Guinea, and Australia and the Solomon Islands are the countries closest to New Guinea from which we had specimens. These results suggest that two haplotypes exist in the area of origin of the species, but that only one of the two haplotypes (the “World haplotype”) has, through human agency, been widely dispersed. However, since P. manokwari is now recorded from 22 countries in the world and we have genetic information from only 8 of these, with none from New Guinea, this analysis provides only partial knowledge of the genetic structure of the invasive species. Morphological analysis of specimens from both haplotypes has shown some differences in ratio of the genital structures but did not allow us to interpret the haplotypes as different species. The new reports from Florida and Puerto Rico are firsts for the USA, for the American continent, and the Caribbean. P. manokwari is a known threat for endemic terrestrial molluscs and its presence is a matter of concern. While most of the infected territories reported until now were islands, the newly reported presence of the species in mainland US in Florida should be considered a potential major threat to the whole US and even the Americas.

Biological Soil Crusts (BSCs) are organosedimentary assemblages comprised of microbes and minerals in topsoil of terrestrial environments. BSCs strongly impact soil quality in dryland ecosystems (e.g., soil structure and nutrient yields) due to pioneer species such as Microcoleus vaginatus; phototrophs that produce filaments that bind the soil together, and support an array of heterotrophic microorganisms. These microorganisms in turn contribute to soil stability and biogeochemistry of BSCs. Non-cyanobacterial populations of BSCs are less well known than cyanobacterial populations. Therefore, we attempted to isolate a broad range of numerically significant and phylogenetically representative BSC aerobic heterotrophs. Combining simple pre-treatments (hydration of BSCs under dark and light) and isolation strategies (media with varying nutrient availability and protection from oxidative stress) we recovered 402 bacterial and one fungal isolate in axenic culture, which comprised 116 phylotypes (at 97% 16S rRNA gene sequence homology), 115 bacterial and one fungal. Each medium enriched a mostly distinct subset of phylotypes, and cultivated phylotypes varied due to the BSC pre-treatment. The fraction of the total phylotype diversity isolated, weighted by relative abundance in the community, was determined by the overlap between isolate sequences and OTUs reconstructed from metagenome or metatranscriptome reads. Together, more than 8% of relative abundance of OTUs in the metagenome was represented by our isolates, a cultivation efficiency much larger than typically expected from most soils. We conclude that simple cultivation procedures combined with specific pre-treatment of samples afford a significant reduction in the culturability gap, enabling physiological and metabolic assays that rely on ecologically relevant axenic cultures.

Abstract Background Practice-based research networks offer important opportunities to move recent advances into routine clinical practice. If their findings are not only generalizable to dental practices at large, but can also elucidate how practice characteristics are related to treatment outcome, their importance is even further elevated. Our objective was to determine whether we met a key objective for The Dental Practice-Based Research Network (DPBRN): to recruit a diverse range of practitioner-investigators interested in doing DPBRN studies. Methods DPBRN participants completed an enrollment questionnaire about their practices and themselves. To date, more than 1100 practitioners from the five participating regions have completed the questionnaire. The regions consist of: Alabama/Mississippi, Florida/Georgia, Minnesota, Permanente Dental Associates, and Scandinavia (Denmark, Norway, and Sweden). We tested the hypothesis that there are statistically significant differences in key characteristics among DPBRN practices, based on responses from dentists who participated in DPBRN's first network-wide study (n = 546). Results There were statistically significant, substantive regional differences among DPBRN-participating dentists, their practices, and their patient populations. Conclusion Although as a group, participants have much in common with practices at large; their substantial diversity offers important advantages, such as being able to evaluate how practice differences may affect treatment outcomes, while simultaneously offering generalizability to dentists at large. This should help foster knowledge transfer in both the research-to-practice and practice-to-research directions.