Effects Of Local Parameters Research Articles

Monitoring Protein Global and Local Parameters in Unfolding and Binding Studies: The Extended Applicability of the Diffusion Coefficient─Molecular Size Empirical Relations.

Protein unfolding and denaturation are main issues in biochemical and pharmaceutical research. Using a global parameter, the translational diffusion coefficient D, folded, unfolded, and intrinsically disordered proteins of a given molar mass M can be distinguished based on their distinct hydrodynamic properties. For broader applications, we provide generalized, PFG-NMR-based empirical D-M relations validated at different temperatures and ready to use with the corresponding corrections in different media. We demonstrate that these relations enable a more accurate molecular mass determination and show fewer potential errors than those of the common methods based on small-molecular diffusion standards. We monitor unfolding of three model proteins using 8 M urea and dimethyl sulfoxide (DMSO)-water mixtures as denaturing agents, highlighting the effect of disulfide bonds. Denaturation in 8 M urea is pH-dependent; in addition, for proteins with highly stable disulfide bonds, a reducing agent (TCEP) is required to achieve complete unfolding. Regarding the effect of local parameters, we show that at low DMSO concentrations─common conditions in pharmaceutical binding studies─the PFG-NMR-derived global parameters are not significantly affected. Still, the atomic environments can change, and the bound solvent molecule can inhibit the binding of a partner molecule. Using proteins with natural isotopic abundance, this effect can be proven by fast 1H-15N 2D correlation spectra. Our results enable fast and easy estimation of protein molecular mass and the degree of folding in various media; moreover, the effect of the cosolvent on the atomic-level structure can be traced without the need of isotope labeling.

Sink-to-source: Influence of offshore dynamics on upstream processes

Abstract When we model fluvial sedimentation and the resultant alluvial stratigraphy, we typically focus on the effects of local parameters (e.g., sediment flux, water discharge, grain size) and the effects of regional changes in boundary conditions applied in the source region (i.e., climate, tectonics) and at the shoreline (i.e., sea level). In recent years this viewpoint has been codified into the “source‐to‐sink” paradigm, wherein major shifts in sediment flux, grain‐size fining trends, channel‐stacking patterns, floodplain deposition and larger stratigraphic systems tracts are interpreted in terms of (1) tectonic and climatic signals originating in the hinterland that propagate downstream; and (2) eustatic fluctuation, which affects the position of the shoreline and dictates the generation of accommodation. Within this paradigm, eustasy represents the sole means by which downstream processes may affect terrestrial depositional systems. Here, we detail three experimental cases in which coastal rivers are strongly influenced by offshore and slope transport systems via the clinoform geometries typical of prograding sedimentary bodies. These examples illustrate an underdeveloped, but potentially important “sink‐to‐source” influence on the evolution of fluvial‐deltaic systems. The experiments illustrate the effects of (1) submarine hyperpycnal flows, (2) submarine delta front failure events, and (3) deformable substrates within prodelta and offshore settings. These submarine processes generate (1) erosional knickpoints in coastal rivers, (2) increased river channel occupancy times, (3) rapid rates of shoreline movement, and (4) localized zones of significant offshore sediment accumulation. Ramifications for coastal plain and deltaic stratigraphic patterns include changes in the hierarchy of scour surfaces, fluvial sand‐body geometries, reconstruction of sea‐level variability and large‐scale stratal geometries, all of which are linked to the identification and interpretation of sequences and systems tracts.

Comparison of spatial and aspatial logistic regression models for landmine risk mapping

Landmines continue to affect the lives of millions of people living in war-torn countries. One major challenge in humanitarian mine action (HMA) is finding new and integrated approaches to land release, which remains a slow and costly process. The use of geographic information systems (GIS) in HMA can improve the land release process by efficient mapping and prioritizing of landmine risk areas. This study explores the usage of aspatial and spatial regression techniques to construct a predictive geo-statistical model for landmine risk mapping in a small 160 km2 municipality in Bosnia and Herzegovina (BiH) and a large 4500 km2 region in Colombia. The first application of logistic geographically weighted regression to landmine risk mapping is presented. The results show that in the BiH study area, the effect of local parameters that influence the distribution of landmine risk varies significantly across the study area. Conversely, in the Colombia case study the effect of explanatory variables remains more homogeneous over the study area. We produced two landmine risk maps for each study area, based on aspatial and spatial regression models. Risk maps are classified into five classes, i.e. very low, low, medium, high, and very high risk. The landmine risk maps created through the usage of these innovative methodologies improve the assessment of risk and prioritization of the land release process in mine-contaminated areas, compared to existing approaches.

Effect of Local Parameters on Gas Turbine Emissions

Gas turbine engine inlet parameters reflect changes in local atmospheric conditions. The pollutant emissions for the engine reflects these changes. In attempting to model the effect of the changing ambient conditions on the emissions it was found that these emissions exhibit an extreme sensitivity to some of the details of the combustion process such as the local fuel-air ratio and the size of the drops in the fuel spray. Fuel-air ratios have been mapped under nonburning conditions using a single JT8D-17 combustion can at simulated idle conditions, and significant variations in the local values have been found. Modelling of the combustor employs a combination of perfectly stirred and plug flow reactors including a finite rate vaporization treatment of the fuel spray. Results show that a small increase in the mean drop size can lead to a large increase in hydrocarbon emissions and decreasing the value of the CO-OH rate constant can lead to large increases in the carbon monoxide emissions. These emissions may also be affected by the spray characteristics with larger drops retarding the combustion process. Hydrocarbon, carbon monoxide, and oxides of nitrogen emissions calculated using the model accurately reflect measured emission variations caused by changing engine inlet conditions.