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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Quantum control landscape of bipartite systems

The control landscape of a quantum system A interacting with another quantum system B is studied. Only system A is accessible through time dependent controls, while system B is not accessible. The objective is to find controls that implement a desired unitary transformation on A, regardless of the evolution on B, at a sufficiently large final time. The freedom in the evolution on B is used to define an extended control landscape on which the critical points are investigated in terms of kinematic and dynamic gradients. A spectral decomposition of the corresponding extended unitary system simplifies the landscape analysis which provides: (i) a sufficient condition on the rank of the dynamic gradient of the extended landscape that guarantees a trap free search for the final time unitary matrix of system A, and (ii) a detailed decomposition of the components of the overall dynamic gradient matrix. Consequently, if the rank condition is satisfied, a gradient algorithm will find the controls that implements the target unitary on system A. It is shown that even if the dynamic gradient with respect to the controls alone is not full rank, the additional flexibility due to the parameters that define the extended landscape still can allow for the rank condition of the extended landscape to hold. Moreover, satisfaction of the latter rank condition subsumes any assumptions about controllability, reachability and control resources. Here satisfaction of the rank condition is taken as an assumption. The conditions which ensure that it holds remain an open research question. We lend some numerical support with two common examples for which the rank condition holds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning–based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 10 3 particles with mean process times scaling as N 0.5 . Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Impacts of Nitrogen Rate and Landscape Position on Soils and Switchgrass Root Growth Parameters

Core Ideas Nitrogen rate did not affect soil properties for Oklahoma, South Dakota, and Virginia. Landscape position affected soil properties under higher slope. Nitrogen rate affected root N, surface area, and weight for the total profile. Landscape position affected the root C and N. Switchgrass roots can increase C accumulation and reduce risk of N loss in soils. ABSTRACT Switchgrass ( Panicum virgatum L.) has been recognized as a potential bioenergy feedstock, and can positively impact soils and the environment. The experimental sites were established in 2008 at three locations with each in Oklahoma (OK), South Dakota (SD), and Virginia (VA) to assess the impacts of N fertilization rate (N rate; low, 0 kg ha −1 ; high, 112 kg ha −1 ) and landscape position (shoulder, backslope, and footslope) on select soil properties and root growth parameters. Data indicate that N rate did not affect soil bulk density (BD), pH, electrical conductivity (EC), soil organic carbon (SOC), and total nitrogen (TN) for any of five depths. Landscape position impacted some of these properties by depth, depending on location. The N rate influenced root weight (RW), root surface area (RSA), and root total nitrogen (RTN) for the total profile (0–100‐cm depth) depending on local site conditions. The landscape position impacted RW, root total carbon (RTC), and RTN for total profile according to different site conditions. The interactions of landscape position by N rate on switchgrass root parameters were significant. The findings in this study indicate that the root system of switchgrass could improve soils and increase C accumulation and reduce the risk of N loss to benefit the environment.

09 BIOMASS FUELS↗
NASA NTRS2004

Modeling Forest Understory Fires in an Eastern Amazonian Landscape

Forest understory fires are an increasingly important cause of forest impoverishment in Ammonia, but little is known of the landscape characteristics and climatic phenomena that determine their occurrence. We developed empirical functions relating the occurrence of understory fires to landscape features near Paragominas, a 35- yr-old ranching and logging center in eastern Ammonia. An historical sequence of maps of forest understory fire was created based on field interviews With local farmers and Landsat TM images. Several landscape features that might explain spatial variations in the occurrence of understory fires were also mapped and co-registered for each of the sample dates, including: forest fragment size and shape, forest impoverishment through logging and understory fires, source of ignition (settlements and charcoal pits), roads, forest edges, and others. The spatial relationship between forest understory fire and each landscape characteristic was tested by regression analyses. Fire probability models were then developed for various combinations of landscape characteristics. The analyses were conducted separately for years of the El Nino Southern Oscillation (ENSO), which are associated with severe drought in eastern Amazonia, and non-ENS0 years. Most (91 %) of the forest area that burned during the 10-yr sequence caught fire during ENSO years, when severe drought may have increased both forest flammability and the escape of agricultural management fires. Forest understory fires were associated with forest edges, as reported in previous studies from Ammonia. But the strongest predictor of forest fire was the percentage of the forest fragment that had been previously logged or burned. Forest fragment size, distance to charcoal pits, distance to agricultural settlement, proximity to forest edge, and distance to roads were also correlated with forest understory fire. Logistic regression models using information on fragment degradation and distance to ignition sources accurately predicted the location of lss than 80% of the forest fires observed during the ENSO event of 1997- 1998. In this Amazon landscape, forest understory fire is a complex function of several variables that influence both the flammability and ignition exposure of the forest.

Alencar, A. A. C.↗
DOE OSTI2024

Wildfire management decisions outweigh mechanical treatment as the keystone to forest landscape adaptation

Modern land management faces unprecedented uncertainty regarding future climates, novel disturbance regimes, and unanticipated ecological feedbacks. Mitigating this uncertainty requires a cohesive landscape management strategy that utilizes multiple methods to optimize benefits while hedging risks amidst uncertain futures. We used a process-based landscape simulation model (LANDIS-II) to forecast forest management, growth, climate effects, and future wildfire dynamics, and we distilled results using a decision support tool allowing us to examine tradeoffs between alternative management strategies. We developed plausible future management scenarios based on factorial combinations of restoration-oriented thinning prescriptions, prescribed fire, and wildland fire use. Results were assessed continuously for a 100-year simulation period, which provided a unique assessment of tradeoffs and benefits among seven primary topics representing social, ecological, and economic aspects of resilience. Projected climatic changes had a substantial impact on modeled wildfire activity. In the Wildfire Only scenario (no treatments, but including active wildfire and climate change), we observed an upwards inflection point in area burned around mid-century (2060) that had detrimental impacts on total landscape carbon storage. While simulated mechanical treatments (~ 3% area per year) reduced the incidence of high-severity fire, it did not eliminate this inflection completely. Scenarios involving wildland fire use resulted in greater reductions in high-severity fire and a more linear trend in cumulative area burned. Mechanical treatments were beneficial for subtopics under the economic topic given their positive financial return on investment, while wildland fire use scenarios were better for ecological subtopics, primarily due to a greater reduction in high-severity fire. Benefits among the social subtopics were mixed, reflecting the inevitability of tradeoffs in landscapes that we rely on for diverse and countervailing ecosystem services. This study provides evidence that optimal future scenarios will involve a mix of active and passive management strategies, allowing different management tactics to coexist within and among ownerships classes. Our results also emphasize the importance of wildfire management decisions as central to building more robust and resilient future landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Linking Soil Moisture Variation and Abundance of Plants to Geomorphic Processes: A Generalized Model for Erosion-Uplifting Landscapes

American Geophysical Union. All Rights Reserved. The diffusive and advective erosion-created landscapes have similar structure (hillslopes and channels) across different scales regardless of variations in drivers and controls. The relative magnitude of diffusive erosion to advective erosion ( D/K ratio) in a landscape development model controls hillslope length, shape, and drainage density, which regulate soil moisture variation, one of the critical resources of plants, through the contributing area ( A ) and local slope ( S ) represented by a topographic index (TI). Here we explore the theoretical relation between geomorphic processes, TI, and the abundance and distribution of plants. We derived an analytical model that expresses the TI with D, K , and A . This gives us the relation between soil moisture variation and geomorphic processes. Plant tolerance curves are used to link plant performance to soil moisture. Using the hypothetical tolerance curves of three plants, we show that the abundance and distribution of xeric, mesic, and hydric plants on the landscape are regulated by the D/K ratio. Where diffusive erosion is the major erosion process (large D/K ratio), mesic plants have higher abundance relative to xeric and hydric plants and the landscape has longer and convex-upward hillslope and low channel density. Finally, increasing the dominance of advective erosion increases relative abundance of xeric and hydric plants dominance, and the landscape has short and concave hillslope and high channel density.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Evaluating the influence of life‐history characteristics on genetic structure: a comparison of small mammals inhabiting complex agricultural landscapes

Abstract Conversion of formerly continuous native habitats into highly fragmented landscapes can lead to numerous negative demographic and genetic impacts on native taxa that ultimately reduce population viability. In response to concerns over biodiversity loss, numerous investigators have proposed that traits such as body size and ecological specialization influence the sensitivity of species to habitat fragmentation. In this study, we examined how differences in body size and ecological specialization of two rodents (eastern chipmunk; Tamias striatus and white‐footed mouse; Peromyscus leucopus ) impact their genetic connectivity within the highly fragmented landscape of the Upper Wabash River Basin ( UWB ), Indiana, and evaluated whether landscape configuration and complexity influenced patterns of genetic structure similarly between these two species. The more specialized chipmunk exhibited dramatically more genetic structure across the UWB than white‐footed mice, with genetic differentiation being correlated with geographic distance, configuration of intervening habitats, and complexity of forested habitats within sampling sites. In contrast, the generalist white‐footed mouse resembled a panmictic population across the UWB , and no landscape factors were found to influence gene flow. Despite the extensive previous work in abundance and occupancy within the UWB , no landscape factor that influenced occupancy or abundance was correlated with genetic differentiation in either species. The difference in predictors of occupancy, abundance, and gene flow suggests that species‐specific responses to fragmentation are scale dependent.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Initiation and Development of Wetlands in Southern Florida Karst Landscape Associated With Accumulation of Organic Matter and Vegetation Evolution

Biological processes can exert important controls on geomorphic evolution in karst landscapes, because carbonate mineral dissolution is augmented and spatially focused by the production of CO 2 and biogenic acids from organic matter (OM) decomposition. In Big Cypress National Preserve (BICY) in southwest Florida (USA), depressional wetlands embedded in a mosaic of pine uplands exhibit regular patterning. To understand the impact of OM decomposition as well as different OM sources on carbonate dissolution and landscape patterning, we measured bulk OM property and biomarker proxies (fatty acids and lignin phenols) in different zones (center vs. edge) of the depressional wetlands. We also constructed age profiles of sediment accretion and pattern genesis using 210Pb activities and compound- specific radiocarbon analysis (CSRA) of long-chain fatty acids. Bulk OM and biomarker data indicate rapid OM accumulation in wetland centers resulting from high primary production and near permanent inundation, in contrast to negligible OM accumulation at wetland edges. Age discontinuities suggest episodic periods of near complete OM loss due to decomposition and/or fire. Based on CSRA, landscape patterning likely initiated in the mid-to-late Holocene, with wetlands at slight higher elevation initiated earlier than wetlands at lower elevation. Bulk stable isotope and lignin phenol biomarkers indicate wetland vegetation was initially dominated by herbaceous species and shifted to woody dominated vegetation as landscape hydrology adjusted to changing precipitation. The rate of weathering is likely impacted by hydrological conditions, vegetation dynamics and environmental perturbations like precipitation and fires, suggesting that this karst landscape is a manifestation of complex ecosystem feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Landscape fragmentation overturns classical metapopulation thinking

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally (“residents”) were often more resilient to fragmentation than long-ranging “migrants.” This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Designing Iowa Agricultural Landscapes to Improve Environmental Co-Benefits of Bioenergy Production

Cellulosic bioenergy feedstocks are needed to improve carbon (C) management while provisioning biomass for bioproducts and biofuel. The transition to increased cellulosic biomass production can be guided by land management plans designed to improve economic, environmental, and ecological performance. We constructed a sustainability model to compare landscape designs for biofuel production from corn (Zea mays L.) stover and switchgrass (Panicum virgatum L.) in central Iowa, USA. We used the model to compare environmental and socioeconomic outcomes associated with four landscape management strategies, with and without cellulosic biomass markets. We evaluated (1) a fuelshed area containing over 1.2 million ha (3 million acres) of corn and soybean (Glycine max (L.) Merr.) within 80 km (50 miles) of a commercial-scale cellulosic biorefinery in Nevada, Iowa, and (2) the South Fork watershed containing over 72,000 ha (178,000 acres) of these row crops within eight north central Iowa HUC-12 (hydrologic unit code) watersheds. At both landscape scales, we found that it is possible to achieve multiple environmental and socioeconomic benefits concomitantly with cellulosic biomass production by strategically collecting corn stover and converting the 10% of the lowest-profitability row crop land to perennial switchgrass. Potential benefits from landscape design include increased biodiversity, soil and water quality improvements, increased soil carbon sequestration for climate change mitigation, and reduced fertilizer use and cost. Our model results showed that increasing benefits can accrue when complementary conservation practices (e.g., reduced tillage, use of a rye cover crop) are combined and integrated throughout a fuelshed or watershed area. We conclude that ecologically based landscape designs offer valuable insights about costs and benefits of land management alternatives, with relevance for achieving stakeholder goals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Developing an Interactive Landscape for Mobility Resources: Preprint

As the world continues to be increasingly driven by data, the ways researchers and professionals sort and collect this data is critical. In the world of mobility data, new levels of data from public transportation systems, location services, and other means are being lost due to how little organization exists. Much of the data is proprietary, and there are few if any de jure or even de facto standards connecting data. There is also little knowledge about the gaps that exist in the data. In this project, we created an interactive landscape where mobility resources are categorized and organized in an easy to use, living document. We made this landscape with open-source code from the CNCF Cloud Native Landscape and repurposed it to the mobility data's needs. Additionally, unlike previous sources that organize mobility data, this document can be updated through GitHub by those in the field to keep its sources relevant. Following the creation of a beta version of the landscape, we conducted several interviews with industry researchers and professionals to ensure the landscape would be useful. The result is an online hub where mobility researchers and resource creators can easily access research and collaborate.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Explicit modeling of abiotic and landscape factors reveals precipitation and forests associated with aphid abundance

Abstract Increases in natural or noncrop habitat surrounding agricultural fields have been shown to be correlated with declines in insect crop pests. However, these patterns are highly variable across studies suggesting other important factors, such as abiotic drivers, which are rarely included in landscape models, may also contribute to variability in insect population abundance. The objective of this study was to explicitly account for the contribution of temperature and precipitation, in addition to landscape composition, on the abundance of a widespread insect crop pest, the soybean aphid ( Aphis glycines Matsumura), in Wisconsin soybean fields. We hypothesized that higher soybean aphid abundance would be associated with higher heat accumulation (e.g., growing degree days) and increasing noncrop habitat in the surrounding landscape, due to the presence of the overwintering primary hosts of soybean aphid. To evaluate these hypotheses, we used an ecoinformatics approach that relied on a large dataset collected across Wisconsin over a 9‐year period (2003–2011), for an average of 235 sites per year ( n = 2,110 fields total). We determined surrounding landscape composition (1.5‐km radius) using publicly available satellite‐derived land cover imagery and interpolated daily temperature and precipitation information from the National Weather Service COOP weather station network. We constructed linear mixed models for soybean aphid abundance based on abiotic and landscape explanatory variables and applied model averaging for prediction using an information theoretic framework. Over this broad spatial and temporal extent in Wisconsin, we found that variation in growing season precipitation was positively related to soybean aphid abundance, while higher precipitation during the nongrowing season had a negative effect on aphid populations. Additionally, we found that aphid populations were higher in areas with proportionally more forest but were lower in areas where minor crops, such as small grains, were more prevalent. Thus, our findings support our hypothesis that including abiotic drivers increases our understanding of crop pest abundance and distribution. Moreover, by explicitly modeling abiotic factors, we may be able to explore how variable climate in tandem with land cover patterns may affect current and future insect populations, with potentially critical implications for crop yields and agricultural food webs.

Stack Whitney, Kaitlin↗
DOE OSTI2019

LHC SUSY and WIMP dark matter searches confront the string theory landscape

The string theory landscape of vacua solutions provides physicists with some understanding as to the magnitude of the cosmological constant. Similar reasoning can be applied to the magnitude of the soft SUSY breaking terms in supersymmetric models of particle physics: there appears to be a statistical draw towards large soft terms which is tempered by the anthropic requirement of the weak scale lying not too far from ~100 GeV. For a mild statistical draw of m softn with n = 1 (as expected from SUSY breaking due to a single F term) then the light Higgs mass is preferred at ~125 GeV while sparticles are all pulled beyond LHC bounds. We confront a variety of LHC and WIMP dark matter search limits with the statistical expectations from a fertile patch of string theory landscape. The end result is that LHC and WIMP dark matter detectors see exactly that which is expected from the landscape: a Standard Model-like Higgs boson of mass 125 GeV but as yet no sign of sparticles or WIMP dark matter. SUSY from the n = 1 landscape is most likely to emerge at LHC in the soft opposite-sign dilepton plus jet plus MET channel. Multi-ton noble liquid WIMP detectors should be able to completely explore the n = 1 landscape parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

A Landscape Perspective on Sustainability of Agricultural Systems

Landscape sustainability of agricultural systems considers effects of farm activities on social, economic, and ecosystem services at local and regional scales. Sustainable agriculture entails: defining sustainability, developing easily measured indicators of sustainability, moving toward integrated agricultural systems, and offering incentives or imposing regulations to affect farmer behavior. A landscape perspective is useful because landscape ecology provides theory and methods for dealing with spatial heterogeneity, scaling, integration, and complexity. To implement agricultural sustainability, we propose adopting a systems perspective, recognizing spatial heterogeneity, addressing the influences of context, and integrating landscape-design principles. Topics that need further attention at local and regional scales include (1) protocols for quantifying material and energy flows; (2) effects of management practices; (3) incentives for enhancing social, economic, and ecosystem services; (4) integrated landscape planning and management; (5) monitoring and assessment; (6) effects of societal demand; and (7) consistent and holistic policies for promoting agricultural sustainability.

Context↗
DOE OSTI2019

Linear downscaling from MODIS to landsat: connecting landscape composition with ecosystem functions

The open and free access to Landsat and MODIS products have greatly promoted scientific investigations on spatiotemporal change in land mosaics and ecosystem functions at landscape to regional scales. Unfortunately, there is a major mismatch in spatial resolution between MODIS products at coarser resolution (≥ 250 m) and landscape structure based on classified Landsat scenes at finer resolution (30 m). Based on practical needs for downscaling popular MODIS products at 500 m resolution to match classified land cover at Landsat 30 m resolution, we proposed an innovative modelling approach so that landscape structure and ecosystem functions can be directly studied for their interconnections. As a proof-of-concept of our downscaling approach, we selected the watershed of the Kalamazoo River in southwestern Michigan, USA as the testbed. MODIS products for three fundamental variables of ecosystem function are downscaled to ensure the approach can be extrapolated to multiple functional measurements. They are blue-sky albedo (0–1), evapotranspiration (ET, mm), and gross primary production (GPP, Mg C ha -1 year -1 ). An object-oriented classification of Landsat images in 2011 was processed to generate a land cover map for landscape structure. The downscaling model was tested for the five Level IV ecoregions within the watershed. We achieved satisfactory downscaling models for albedo, ET, and GPP for all five ecoregions. The adjusted R2 was > 0.995 for albedo, 0.915–0.997 for ET, and 0.902–0.962 for GPP. The estimated albedo, ET, and GPP values appear different in the region. The estimated albedo was the lowest for water (0.076–0.107) and the highest for cropland (0.166–0.172). Estimated ET was the highest for the built-up cover type (525.6–687.1 mm) and the lowest for forest (209.7–459.7 mm). The estimated GPP was the highest for the build-up cover type (8.65–9.85 Mg C ha -1 year -1 ) and the lowest for forest. Estimated values for albedo, ET, and GPP appear reasonable for their ranges in the Kalamazoo River region and are consistent with values reported in the literature. Despite these promising results, the downscaling approach relies on strong assumptions and can carry substantial uncertainty. Finally, it is only valid at a spatial scale where similar climate, soil, and landforms exist (i.e., values in isolated patches of the same cover type are similar). Plausibly, the uncertainties associated with each estimation, as well as the model residuals, can be explored for other pattern-process relationships within the landscape.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Integration of historical map and aerial imagery to characterize long-term land-use change and landscape dynamics: An object-based analysis via Random Forests

Tracking Earth’s past helps us to move from hindsight to foresight in seeking landscape sustainability, a pursuit aided by modern mapping capabilities but hindered by a dearth of historical landscape information. To fill the data gap and exemplify the use of old map for land-use change sciences, we combined a paper-based US civil war map and aerial photos to derive land-use history and landscape dynamics at fine scales for a region near Chancellorsville, VA, USA, from 1867 to 2014. We also tested how advanced algorithms—object-based analysis and random forests (RF)—could aid in data processing. Automatic classification of the 1867 map proved difficult, but its manual digitization could benefit from object-based image segmentation. Classifying digital aerial images was more accurate via the object-based than pixel-based method, but only if the images were segmented appropriately. In the object-based classification, spectral-based features were much more important than shape/geometry features, as ranked by RF. During the 147 years, 32% of the region changed in land type. Settlement and roads increased in extent by 1850% and 691%, respectively, and woodland decreased by 19%. These changes fragmented the landscape, altered the hydrological regime, and affected river morphology. The utility of old maps exemplified here provides an impetus for exploring and leveraging extant old maps or historical records to support land-use and global change research. Our study also connotes the importance of geotagging current data, such as photos and videos, that may serve as a baseline to document future landscape change.

Historical map, object-based, Random Forests, old ↗
DOE OSTI2015

A method proposal for cumulative environmental impact assessment based on the landscape vulnerability evaluation

Cumulative environmental impact assessment deals with the occasional use in practical application of environmental impact assessment process. The main reasons are the difficulty of cumulative impact identification caused by lack of data, inability to measure the intensity and spatial effect of all types of impacts and the uncertainty of their future evolution. This work presents a method proposal to predict cumulative impacts on the basis of landscape vulnerability evaluation. For this purpose, qualitative assessment of landscape ecological stability is conducted and major vulnerability indicators of environmental and socio-economic receptors are specified and valuated. Potential cumulative impacts and the overall impact significance are predicted quantitatively in modified Argonne multiple matrixes while considering the vulnerability of affected landscape receptors and the significance of impacts identified individually. The method was employed in the concrete environmental impact assessment process conducted in Slovakia. The results obtained in this case study reflect that this methodology is simple to apply, valid for all types of impacts and projects, inexpensive and not time-consuming. The objectivity of the partial methods used in this procedure is improved by quantitative landscape ecological stability evaluation, assignment of weights to vulnerability indicators based on the detailed characteristics of affected factors, and grading impact significance. - Highlights: • This paper suggests a method proposal for cumulative impact prediction. • The method includes landscape vulnerability evaluation. • The vulnerability of affected receptors is determined by their sensitivity. • This method can increase the objectivity of impact prediction in the EIA process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Graph representation of protein free energy landscape

The thermodynamics and kinetics of protein folding and protein conformational changes are governed by the underlying free energy landscape. However, the multidimensional nature of the free energy landscape makes it difficult to describe. We propose to use a weighted-graph approach to depict the free energy landscape with the nodes on the graph representing the conformational states and the edge weights reflecting the free energy barriers between the states. Our graph is constructed from a molecular dynamics trajectory and does not involve projecting the multi-dimensional free energy landscape onto a low-dimensional space defined by a few order parameters. The calculation of free energy barriers was based on transition-path theory using the MSMBuilder2 package. We compare our graph with the widely used transition disconnectivity graph (TRDG) which is constructed from the same trajectory and show that our approach gives more accurate description of the free energy landscape than the TRDG approach even though the latter can be organized into a simple tree representation. The weighted-graph is a general approach and can be used on any complex system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗