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Institution

Missouri University of Science and Technology

EducationRolla, Missouri, United States
About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Control theory & Artificial neural network. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.


Papers
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Journal ArticleDOI
TL;DR: The described method of retrieving particle-containing brine from fluid inclusions offers a robust approach for assessing the antiquity of microorganisms associated with evaporites.
Abstract: Halite crystals were selected from a 186 m subsurface core taken from the Badwater salt pan, Death Valley, California to ascertain if halophilic Archaea and their associated 16S rDNA can survive over several tens of thousands of years. Using a combined microscope microdrill/micropipette system, fluids from brine inclusions were aseptically extracted from primary, hopper texture, halite crystals from 8 and 85 metres below the surface (mbls). U-Th disequilibrium dating indicates that these halite layers were deposited at 9,600 and 97,000 years before present (ybp) respectively. Extracted inclusions were used for polymerase chain reaction (PCR) analysis with haloarchaea-specific 16S rDNA primers or placed into haloarchaea culture medium. Enrichment cultures were obtained from 97 kyr halite crystal inclusion fluid and haloarchaea-containing prepared crystals (positive controls), whereas inclusions from crystals of 9.6 kyr halite and the haloarchaea-free halite crystals (negative controls) resulted in no growth. Phylogenetic analysis (16S rDNA) of the 97 kyr isolate, designated BBH 001, revealed a homology of 100% with Halobacterium salinarum. DNA-DNA hybridization experiments confirmed that BBH 001 was closely related to H. salinarum (81-75% hybridization) and its ascription to this haloarchaea species. The described method of retrieving particle-containing brine from fluid inclusions offers a robust approach for assessing the antiquity of microorganisms associated with evaporites.

116 citations

Journal ArticleDOI
07 Feb 2020-Science
TL;DR: It is found that sodium ion (Na+)–gated water-conduction nanochannels could be created by assembling NaA zeolite crystals into a continuous, defect-free separation membrane through a rationally designed method.
Abstract: Robust, gas-impeding water-conduction nanochannels that can sieve water from small gas molecules such as hydrogen (H2), particularly at high temperature and pressure, are desirable for boosting many important reactions severely restricted by water (the major by-product) both thermodynamically and kinetically. Identifying and constructing such nanochannels into large-area separation membranes without introducing extra defects is challenging. We found that sodium ion (Na+)–gated water-conduction nanochannels could be created by assembling NaA zeolite crystals into a continuous, defect-free separation membrane through a rationally designed method. Highly efficient in situ water removal through water-conduction nanochannels led to a substantial increase in carbon dioxide (CO2) conversion and methanol yield in CO2 hydrogenation for methanol production.

116 citations

Journal ArticleDOI
B. P. Abbott1, Richard J. Abbott1, T. D. Abbott2, Sheelu Abraham3  +1257 moreInstitutions (142)
TL;DR: The null result constrains the coalescence rate of monochromatic (delta function) distributions of nonspinning in primordial black hole binary formation scenario and strengthens the presently placed bounds from microlensing surveys of massive compact halo objects (MACHOs) provided by the MACHO and EROS Collaborations.
Abstract: We present a search for subsolar mass ultracompact objects in data obtained during Advanced LIGO’s second observing run. In contrast to a previous search of Advanced LIGO data from the first observing run, this search includes the effects of component spin on the gravitational waveform. We identify no viable gravitational-wave candidates consistent with subsolar mass ultracompact binaries with at least one component between 0.2 M⊙–1.0 M⊙. We use the null result to constrain the binary merger rate of (0.2 M⊙, 0.2 M⊙) binaries to be less than 3.7×105 Gpc-3 yr-1 and the binary merger rate of (1.0 M⊙, 1.0 M⊙) binaries to be less than 5.2×103 Gpc-3 yr-1. Subsolar mass ultracompact objects are not expected to form via known stellar evolution channels, though it has been suggested that primordial density fluctuations or particle dark matter with cooling mechanisms and/or nuclear interactions could form black holes with subsolar masses. Assuming a particular primordial black hole (PBH) formation model, we constrain a population of merging 0.2 M⊙ black holes to account for less than 16% of the dark matter density and a population of merging 1.0 M⊙ black holes to account for less than 2% of the dark matter density. We discuss how constraints on the merger rate and dark matter fraction may be extended to arbitrary black hole population models that predict subsolar mass binaries.

116 citations

Journal ArticleDOI
01 Aug 2010
TL;DR: In this paper, two uppermost Carboniferous-Lower Triassic fluvial-lacustrine sections in the Tarlong-Taodonggou half-graben, southern Bogda Mountains, NW China, comprise a 1834m-thick, relatively complete sedimentary and paleoclimatic record of the east coast of mid-latitude NE Pangea.
Abstract: Two uppermost Carboniferous–Lower Triassic fluvial–lacustrine sections in the Tarlong–Taodonggou half-graben, southern Bogda Mountains, NW China, comprise a 1834 m-thick, relatively complete sedimentary and paleoclimatic record of the east coast of mid-latitude NE Pangea. Depositional environmental interpretations identified three orders (high, intermediate, and low) of sedimentary cycles. High-order cycles (HCs) have five basic types, including fluvial cycles recording repetitive changes of erosion and deposition and lacustrine cycles recording repetitive environmental changes associated with lake expansion and contraction. HCs are grouped into intermediate-order cycles (ICs) on the basis of systematic changes of thickness, type, and component lithofacies of HCs. Nine low-order cycles (LCs) are demarcated by graben-wide surfaces across which significant long-term environmental changes occurred. A preliminary cyclostratigraphic framework provides a foundation for future studies of terrestrial climate, tectonics, and paleontology in mid-latitude NE Pangea. Climate variabilities at the intra-HC, HC, IC, and LC scales were interpreted from sedimentary and paleosol evidence. Four prominent climatic shifts are present: 1) from the humid–subhumid to highly-variable subhumid–semiarid conditions at the beginning of Sakamarian; 2) from highly-variable subhumid–semiarid to humid–subhumid conditions across the Artinskian-Capitanian unconformity; 3) from humid–subhumid to highly-variable subhumid–semiarid conditions at early Induan; and 4) from the highly-variable subhumid–semiarid to humid–subhumid conditions across the Olenekian-Anisian unconformity. The stable humid–subhumid condition from Lopingian to early Induan implies that paleoclimate change may not have been the cause of the end-Permian terrestrial mass extinction. A close documentation of the pace and timing of the extinction and exploration of other causes are needed. In addition, the semiarid–subhumid conditions from Sakamarian to Artinskian–Kungurian (?) and from middle Induan to end of Olenekian are in conflict with modern mid-latitude east coast meso- and macrothermal humid climate. Extreme continentality, regional orographic effect, and/or abnormal circulation of Paleo-Tethys maybe are possible causes. Our work serves as a rare data point at mid-latitude NE Pangea for climate modeling to seek explanations on the origin(s) of climate variability in NE Pangea from latest Carboniferous to Early Triassic.

116 citations

Journal ArticleDOI
TL;DR: A detailed trading model that provides a more effective and intelligent way for recognizing trading signals and assisting investors with trading decisions by utilizing a system that adapts both the inputs and the prediction model based on the desired output is led.
Abstract: The system provides an automated and adaptive model selection process.The system predicts the stock price direction, rather than the forecasted level.Particle swarm optimization is used to reduce computation time.Denoising is used to deal with stock market volatility. Predicting the direction and movement of stock index prices is difficult, often leading to excessive trading, transaction costs, and missed opportunities. Often traders need a systematic method to not only spot trading opportunities, but to also provide a consistent approach, thereby minimizing trading errors and costs. While mechanical trading systems exist, they are usually designed for a specific stock, stock index, or other financial asset, and are often highly dependent on preselected inputs and model parameters that are expected to continue providing trading information well after the initial training or back-tested model development period. The following research leads to a detailed trading model that provides a more effective and intelligent way for recognizing trading signals and assisting investors with trading decisions by utilizing a system that adapts both the inputs and the prediction model based on the desired output. To illustrate the adaptive approach, multiple inputs and modeling techniques are utilized, including neural networks, particle swarm optimization, and denoising. Simulations with stock indexes illustrate how traders can generate higher returns using the developed adaptive decision support system model. The benefits of adding adaptive and intelligent decision making to forecasts are also discussed.

116 citations


Authors

Showing all 9433 results

NameH-indexPapersCitations
Robert Stone1601756167901
Tobin J. Marks1591621111604
Jeffrey R. Long11842568415
Xiao-Ming Chen10859642229
Mark C. Hersam10765946813
Michael Schulz10075950719
Christopher J. Chang9830736101
Marco Cavaglia9337260157
Daniel W. Armstrong9375935819
Sajal K. Das85112429785
Ming-Liang Tong7936423537
Ludwig J. Gauckler7851725926
Rodolphe Clérac7850622604
David W. Fahey7731530176
Kai Wang7551922819
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202330
2022162
20211,047
20201,180
20191,195
20181,108