Montana State University is a public university located in Bozeman, Montana, United States. It is the state's land-grant university and primary campus in the Montana State University System, which is part of the Montana University System. MSU offers baccalaureate degrees in 51 fields, master's degrees in 41 fields, and doctoral degrees in 18 fields through its nine colleges.Almost 15,300 students attend MSU, and the university faculty numbers, including department heads, are 743 full-time and 411 part-time. The university's main campus in Bozeman is home to KUSM television, KGLT radio, and the Museum of the Rockies. MSU provides outreach services to citizens and communities statewide through its eight Agricultural Experiment Stations and 60 county and reservation Extension Offices. Wikipedia.
Montana State University | Date: 2017-07-05
Tunable filter arrays (100) include an array of liquid crystal (LC) tunable Fabry-Perot (FP) microcavities. The microcavities are defined by first and second reflectors (114,116) and an LC layer (115) situated between the reflectors. The tunable filter is secured to an image sensor array (120) so that the LC tunable microcavities are coupled to respective photodetectors of the image sensor array. Patterned electrodes (130) are situated about the LC layer to tune the microcavities.
University Corporation For Atmospheric Research, Montana State University and Nasa | Date: 2016-04-27
A shared optics and telescope, a filter, and a micropulse differential absorption LIDAR are provided, with methods to use the same. The shared optics and telescope includes a pair of axicon lenses, a secondary mirror, a primary mirror including an inner mirror portion and an outer mirror portion, the inner mirror portion operable to expand the deflected annular transmission beam, and the outer mirror portion operable to collect the return signal. The filter includes an etalon and a first filter. The micropulse differential absorption LIDAR includes first and second laser signals, a laser transmission beam selection switch, a first laser return signal switch, and a toggle timer.
The United States As Represented By The Secretary and Montana State University | Date: 2017-06-28
Biomarkers associated with neuroimmunological disease are described. The disclosed biomarkers are secreted proteins identified in cerebral spinal fluid (CSF) samples of patients with neurological disease. The disclosed biomarkers identify patients with intrathecal inflammation, distinguish multiple sclerosis (MS) patients from patients with other types of inflammatory neurological diseases and from subjects without MS, distinguish progressive MS patients from patients with relapsing-remitting MS, identify subjects with non-MS inflammatory neurological diseases, differentiate healthy subjects from patients with any type of neurological disease, and/or identify subjects with increased disability, CNS tissue damage and/or neurodegeneration. Process-specific biomarkers that can be used in place of a brain biopsy to identify immune cell infiltration and/or activation in the CNS are also described. Methods of treating subject with neurological disease, and methods of evaluating the efficacy of particular treatments, based on detection of the disclosed biomarkers are also described.
Peters J.W.,Montana State University |
Broderick J.B.,Montana State University
Annual Review of Biochemistry | Year: 2012
FeFe-hydrogenses and molybdenum (Mo)-nitrogenase are evolutionarily unrelated enzymes with unique complex iron-sulfur cofactors at their active sites. The H cluster of FeFe-hydrogenases and the FeMo cofactor of Mo-nitrogenase require specific maturation machinery for their proper synthesis and insertion into the structural enzymes. Recent insights reveal striking similarities in the biosynthetic pathways of these complex cofactors. For both systems, simple iron-sulfur cluster precursors are modified on assembly scaffolds by the activity of radical S-adenosylmethionine (SAM) enzymes. Radical SAM enzymes are responsible for the synthesis and insertion of the unique nonprotein ligands presumed to be key structural determinants for their respective catalytic activities. Maturation culminates in the transfer of the intact cluster assemblies to a cofactor-less structural protein recipient. Required roles for nucleotide binding and hydrolysis have been implicated in both systems, but the specific role for these requirements remain unclear. In this review, we highlight the progress on FeFe-hydrogenase H cluster and nitrogenase FeMo-cofactor assembly in the context of these emerging paradigms. © 2012 by Annual Reviews. All rights reserved.
Sorek R.,Weizmann Institute of Science |
Lawrence C.M.,Montana State University |
Wiedenheft B.,Montana State University
Annual Review of Biochemistry | Year: 2013
Effective clearance of an infection requires that the immune system rapidly detects and neutralizes invading parasites while strictly avoiding self-antigens that would result in autoimmunity. The cellular machinery and complex signaling pathways that coordinate an effective immune response have generally been considered properties of the eukaryotic immune system. However, a surprisingly sophisticated adaptive immune system that relies on small RNAs for sequence-specific targeting of foreign nucleic acids was recently discovered in bacteria and archaea. Molecular vaccination in prokaryotes is achieved by integrating short fragments of foreign nucleic acids into a repetitive locus in the host chromosome known as a CRISPR (clustered regularly interspaced short palindromic repeat). Here we review the mechanisms of CRISPR-mediated immunity and discuss the ecological and evolutionary implications of these adaptive defense systems. © 2013 by Annual Reviews. All rights reserved.
Kalinowski S.T.,Montana State University
Heredity | Year: 2011
One of the primary goals of population genetics is to succinctly describe genetic relationships among populations, and the computer program STRUCTURE is one of the most frequently used tools for doing so. The mathematical model used by STRUCTURE was designed to sort individuals into Hardy-Weinberg populations, but the program is also frequently used to group individuals from a large number of populations into a small number of clusters that are supposed to represent the main genetic divisions within species. In this study, I used computer simulations to examine how well STRUCTURE accomplishes this latter task. Simulations of populations that had a simple hierarchical history of fragmentation showed that when there were relatively long divergence times within evolutionary lineages, the clusters created by STRUCTURE were frequently not consistent with the evolutionary history of the populations. These difficulties can be attributed to forcing STRUCTURE to place individuals into too few clusters. Simulations also showed that the clusters produced by STRUCTURE can be strongly influenced by variation in sample size. In some circumstances, STRUCTURE simply put all of the individuals from the largest sample in the same cluster. A reanalysis of human population structure suggests that the problems I identified with STRUCTURE in simulations may have obscured relationships among human populations-particularly genetic similarity between Europeans and some African populations. © 2011 Macmillan Publishers Limited All rights reserved.
Agency: NSF | Branch: Standard Grant | Program: | Phase: MAJOR RESEARCH INSTRUMENTATION | Award Amount: 1.11M | Year: 2016
The proposed project seeks to further develop and field a Micro-pulse DIAL (MPD) Lidar system. This system will be used by researchers to advance our knowledge in the areas of measuring water vapor concentration and distribution, convective initiation, and land-atmosphere exchange. This new system will potentially advance our ability to better predict weather, particularly in the area of storm development.
The proposed major research instrumentation (MRI) project seeks to develop and make available to the science community a system of five diode-laser-based, micro-pulse, differential absorption lidar (DIAL) instruments for measuring the spatial and temporal distribution of water vapor in the lower atmosphere. The Micro-Pulse DIAL (MPD) instruments will build on the proven design developed by the PI and Co-PI, including development of enclosures to make the system more field deployable and network attachable for remote access. Once the testing phase is complete, the MPD research instrumentation will be made available to the science community through the National Center for Atmospheric Research (NCAR) Earth Observing Laboratory (EOL) Facilities and Instrument Program.
Agency: NSF | Branch: Standard Grant | Program: | Phase: INFRAST MGMT & EXTREME EVENTS | Award Amount: 549.98K | Year: 2016
Local hazard preparedness is vital to avoid disaster in the face of extreme events. Whereas conventional risk communication relies on scientific information to affect hazard preparedness, such technical information is often ineffectively assimilated into peoples risk perceptions and decisions. Hazard preparedness is largely shaped by factors such as cultural values, cognitive biases, affect, knowledge, information, and experiences, all of which are communicated through stories that people construct and recount to one another. This research will test the effects of an innovative narrative-based risk communication strategy that locates science hazard information in locally produced hazard narratives. Effectively connecting scientific information to individual risk perceptions and decisions through co-produced risk narratives potentially offers an innovative way to improve hazard preparedness that could translate across hazard issues more broadly. With the project focus on flooding events, this research will draw upon expertise in social behavioral sciences, hydrology, and computer science.
This interdisciplinary research effort focuses on testing whether a co-produced, narrative-based risk communication approach is more effective than conventional risk communication at improving hazard preparedness (defined as risk perception and decisions). The first objective is to develop co-produced risk narratives that are both scientifically accurate and locally relevant. Using a community-based participatory research (CBPR) approach, baseline data of flood risk narratives will be collected from river communities to ascertain narrative elements as identified in the Narrative Policy Framework (NPF). Narrative elements include subsets of narrative structure (e.g., use of characters, plot) and narrative content (who is cast in the roles of hero, villain, victim). Whereas narrative structures are stable, content varies across narratives. The characters cast in the narrative and their associated actions are formative in constructing different notions of reality and consequent decisions. Natural Language Processing computational techniques will then be used to identify key narrative content from the CBPR data to obtain the best set of combinations of narrative structure and narrative content situated in local language and images. Subsequently, researchers will quantify, explain, and depict sources of hydrologic uncertainty (data, model, and natural uncertainty) associated with flood frequency analysis in 100-year flood maps for each community. This resulting information will be embedded into the algorithmically enhanced CBPR-based risk narratives to create locally relevant and scientifically accurate flood risk narratives. These risk narratives will be returned to the CBPR groups for adjustment and validation. The second objective focuses on testing the effects of these co-produced risk narratives as narrative treatments on hazard preparedness (i.e., risk perception and intended decisions) with an experimental survey design across the larger population in these river communities. Differently constructed co-produced narratives (i.e., hero-focused, victim-focused, hero & victim focused narratives) will be used as treatments to test the extent to which they influence hazard preparedness in contrast to a non-narrative science statement and a control condition of no treatment. The findings are expected to provide insight into the power of narratives in communicating hazard risk and affecting hazard preparedness. The outcomes are expected to be useful for those local and federal entities involved in hazard preparedness strategies.
Agency: NSF | Branch: Cooperative Agreement | Program: | Phase: RESEARCH INFRASTRUCTURE IMPROV | Award Amount: 6.00M | Year: 2016
This Research Infrastructure Improvement Track-2 Focused EPSCoR Collaboration (RII Track-2 FEC) award is a collaboration among three institutions in Montana, Wyoming, and South Dakota including Montana State University (MSU), University of Wyoming (UW) and University of South Dakota (USD). The project will focus on developing a framework of CO2 mitigation scenarios that would not create conflicts with food security and production of clean energy. The project will offer novel experimental insights, modeling tools, and technological solutions for improving the resiliency of food security and ecosystem services to global climate policies. The modeling activities and extensive field research is expected to generate new data and findings that will lead to new insights into how biogeochemical modeling, agricultural economics, carbon-capture and sequestration, water and biodiversity research can be used within an integrated framework. The project will leverage existing networks and hubs to integrate new data-streams into the modeling exercises. Through involvement with Tribal Colleges and networking with existing programs with Native American student populations, the project will serve to enhance and diversify the STEM workforce in the participating jurisdictions.
The proposed project will evaluate the consequences of a bioenergy, and carbon capture and sequestration (BECCS) economy in the Upper Missouri River Basin (UMRB). In seeking to evaluate how negative CO2 emissions, and the security and economic costs associated with changes to energy policy, the project will address four research objectives: (1) Develop empirical and numerical models to explain recent trends in land use and land-cover change; (2) Apply biogeochemical ecosystem and crop models to evaluate a set of stakeholder-designed regions and scenarios for bioenergy production potential, and use new and existing data and observations to quantify trade-offs between biofuel expansion and food security and other carbon, soil and bioclimate variables; (3) Evaluate the feasibility of BECCS within the context of carbon capture and storage, existing political and institutional constraints, and policy frameworks affecting farmers and Tribal Nations; and (4) Produce a synthesis report addressing the economic feasibility of BECCS and provide the basis for knowledge transfer to collaborators at national and international organizations. The collaborations with several government agencies, non-governmental organizations, and the private sector, in addition to a scientific advisory panel, provide high potential that the project and its findings will transfer to national and international stages.
Agency: NSF | Branch: Continuing grant | Program: | Phase: GEOMORPHOLOGY & LAND USE DYNAM | Award Amount: 92.42K | Year: 2017
Sediment movement across mountain watersheds influences landscape evolution, ecosystem function, and resource management, yet quantitative understanding of sediment connectivity between hillslopes, streams, and downstream is limited. This project will advance understanding of the pace and patterns of and controls on sediment routing and connectivity in mountain watersheds. The resulting process knowledge will be relevant to management and restoration in forested, fire-prone mountain landscapes, as well as to assessment of aquatic habitat in mountain streams and vulnerability to sediment-related disturbances and climate change. Outreach efforts will include development and delivery of webinars targeted toward K-12 teachers, an interactive science-museum exhibit, and dissemination via digital educational resources. The project will also educate and train university students at the undergraduate and graduate levels.
This project will investigate the influences of topography and vegetation on sediment transfer, residence time, and connectivity between hillslopes, streams, and downstream through river networks. Semiarid, snowmelt-dominated, fire-prone landscapes will be targeted. Measurements of erosion and sediment transport at different scales, using isotopic and physical tracers, will be combined with high-resolution topographic data and modeling of sediment storage, mixing, and routing. The project will fill knowledge gaps surrounding multi-scale erosion rates and processes in mountain landscapes by bridging hillslope and fluvial analyses, combining diverse and cutting-edge tools, and incorporating ecogeomorphic perspectives about the influence of vegetation on sediment transfer.