Institution
Michigan Technological University
Education•Houghton, Michigan, United States•
About: Michigan Technological University is a education organization based out in Houghton, Michigan, United States. It is known for research contribution in the topics: Population & Volcano. The organization has 8023 authors who have published 17422 publications receiving 481780 citations. The organization is also known as: MTU & Michigan Tech.
Topics: Population, Volcano, Catalysis, Asphalt, Computer science
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a long-term field experiment was initiated to simulate chronic atmospheric N deposition, a widespread phenomenon in industrial regions of the world, and the authors found that atmospheric nitrogen deposition may rapidly saturate some northern hardwood ecosystems across an entire biome in the upper Great Lakes Region of the USA.
Abstract: A long-term field experiment was initiated to simulate chronic atmospheric N deposition, a widespread phenomenon in industrial regions of the world. Eight years of experimental nitrate (
$${\text{NO}}_{\text{3}}^-- $$
) additions (3 g
$${\text{NO}}_{\text{3}}^-- $$
-N m−2 per year) to four different northern hardwood forests located along a 500 km geographic gradient dramatically increased leaching losses of
$${\text{NO}}_{\text{3}}^-- $$
-N, dissolved organic carbon (DOC), and dissolved organic nitrogen (DON). During the last two water years, the average increase in solution
$${\text{NO}}_{\text{3}}^-- $$
-N and DON leaching from the
$${\text{NO}}_{\text{3}}^-- $$
-amended plots was 2.2 g N m−2, equivalent to 72% of the annual experimental N addition. Results indicate that atmospheric N deposition may rapidly saturate some northern hardwood ecosystems across an entire biome in the upper Great Lakes Region of the USA. Changes in soil C and N cycling induced by chronic N deposition have the potential in this landscape to significantly alter the flux of DOC and DON from upland to aquatic ecosystems. Michigan Gradient study site characteristics are similar to those of European forests most susceptible to N saturation.
218 citations
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TL;DR: In this paper, an indirect injection diesel engine, typical of those in use in underground mines, was operated using a soy-derived, fatty acid mono-ester (or biodiesel) fuel and an oxidation catalytic converter (OCC).
Abstract: This study was conducted to obtain additional information on exhaust emissions with potential health importance from an indirect injection diesel engine, typical of those in use in underground mines, when operated using a soy-derived, fatty-acid mono-ester (or biodiesel) fuel and an oxidation catalytic converter (OCC). Compared to emis sions with the diesel fuel without the OCC, use of the diesel (D2) and biodiesel fuel with the OCC had similar reductions (50−80%) in total particulate matter (TPM). The solid portion of the TPM was lowered with the biodiesel fuel. Particle-associated polynuclear aromatic hydrocarbon and 1-nitropyrene emissions were lower with use of the biodiesel fuel as compared to the D2 fuel, with or without the OCC. Vapor-phase PAH emissions were reduced (up to 90%) when the OCC was used with either fuel. Use of the OCC resulted in over 50% reductions in both particle and vapor-phase-associated mutagenic activity with both fuels. No vapor-phase-associated mutagenic activity was detecte...
218 citations
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TL;DR: In this paper, the authors used remote sensing studies of volcanic ash clouds with field measurement and sampling, and lab experiments are required to fill current gaps in knowledge surrounding the theory of ash aggregate formation.
Abstract: Most volcanic ash particles with diameters <63 lm settle from eruption clouds as particle aggregates that cumulatively have larger sizes, lower densities, and higher terminal fall velocities than individual constituent particles. Particle aggregation reduces the atmospheric residence time of fine ash, which results in a proportional increase in fine ash fallout within 10–100 s km from the volcano and a reduction in airborne fine ash mass concentrations 1000 s km from the volcano. Aggregate characteristics vary with distance from the volcano: proximal aggregates are typically larger (up to cm size) with concentric structures, while distal aggregates are typically smaller (sub-millimetre size). Particles comprising ash aggregates are bound through hydro-bonds (liquid and ice water) and electrostatic forces, and the rate of particle aggregation correlates with cloud liquid water availability. Eruption source parameters (including initial particle size distribution, erupted mass, eruption column height, cloud water content and temperature) and the eruption plume temperature lapse rate, coupled with the environmental parameters, determines the type and spatiotemporal distribution of aggregates. Field studies, lab experiments and modelling investigations have already provided important insights on the process of particle aggregation. However, new integrated observations that combine remote sensing studies of ash clouds with field measurement and sampling, and lab experiments are required to fill current gaps in knowledge surrounding the theory of ash aggregate formation.
217 citations
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TL;DR: In this article, a method is developed to search for air showers initiated by photons using data recorded by the surface detector of the Auger Observatory, based on observables sensitive to the longitudinal shower development, the signal risetime and the curvature of the shower front.
217 citations
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TL;DR: The RepRap as discussed by the authors is an open-source self-replicating rapid prototyper for low-cost 3D printing, which is now a technically viable form of distributed manufacturing.
Abstract: With the recent development of the RepRap, an open-source self-replicating rapid prototyper, low-cost three-dimensional (3D) printing is now a technically viable form of distributed manufacturing o...
217 citations
Authors
Showing all 8104 results
Name | H-index | Papers | Citations |
---|---|---|---|
Anil K. Jain | 183 | 1016 | 192151 |
Marc W. Kirschner | 162 | 457 | 102145 |
Yonggang Huang | 136 | 797 | 69290 |
Hong Wang | 110 | 1633 | 51811 |
Fei Wang | 107 | 1824 | 53587 |
Emanuele Bonamente | 105 | 219 | 40826 |
Haoshen Zhou | 104 | 519 | 37609 |
Nicholas J. Turro | 104 | 1131 | 53827 |
Yang Shao-Horn | 102 | 458 | 49463 |
Richard P. Novick | 99 | 295 | 34542 |
Markus J. Buehler | 95 | 609 | 33054 |
Martin L. Yarmush | 91 | 702 | 34591 |
Alan Robock | 90 | 346 | 27022 |
Patrick M. Schlievert | 90 | 444 | 32037 |
Lonnie O. Ingram | 88 | 316 | 22217 |