Oral and intestinal digestion of oligosaccharides as potential sweeteners: A systematic evaluation

The utilisation of oligosaccharides by oral microorganisms and intestinal enzymes are important factors in determining their effectiveness as alternative sweeteners. In this study, classes of naturally occurring sugars were assessed using in vitro models for oral and intestinal digestibility, in order to test the influence of chemical structure on functional properties. Amongst the classes of sucrose isomers, α-glucobioses, β-glucobioses and sucrose-based oligosaccharides, structures were identified that were not utilised by the common oral bacterium Streptococcus mutans, and would therefore contribute to the non-cariogenic potential of a sweetener. Analysis of the rate and products of digestion by a rat glucosidase mixture was used to determine the relative intestinal digestibility. The results showed that oligosaccharides containing a (1 → 6)-β-Glc group, including gentiobiose and gentiobiitol, together with melezitose, a sucrose-derived oligosaccharide containing a α-Glc-(1 → 3)-Fru moiety were resistant to digestion by both S. mutans and mammalian intestinal enzymes, highlighting their potential as dietary sugar substitutes.     

Estimating percent impervious cover from Landsat-based land cover with a simple and transferable regression model

Percent impervious cover (PIC) is a widely used metric in ecological and hydrological analyses because it is highly correlated with pollutant and storm water run-off. The moderate-resolution satellite data (e.g. Landsat), that are typically used to calculate PIC, tend to overestimate PIC for all but very rural and very urban landscapes. Existing models for calibrating PIC estimates (e.g. ISAT, ETIS) are limited in that they are applicable only for specific land cover datasets and may also require population data; furthermore, these models have not been tested for performance outside of the geographic locations in which they were developed. The goal of this study was to explore simple but widely applicable regression models as tools for calibrating PIC estimates based on moderate resolution satellite data. The regression models used impervious land cover, from Landsat-based datasets, as the sole predictor of actual PIC. PIC was calculated for analysis units, ranging in size from 2.25 ha to ≥100 ha, for locations in Connecticut, Massachusetts, and Ohio in the United States. Regression models were fit for each size class of analysis unit at each study location; generalized versions of the models were created by fitting a regression to all size classes of analysis units at a given study location. Calibrated PIC estimates had root mean square error (RMSE) values that ranged from 1.5–10.7%; these values were considerably better than RMSE values for uncalibrated PIC estimates which ranged from 10.1–23.3%. For both calibrated and uncalibrated PIC, the accuracy of the estimates improved with the increasing size of the analysis units. Model regression coefficients were similar regardless of the analysis unit size, geographic location, or land cover dataset; model performance declined only slightly when applied outside the area in which it was developed. The simple regression models developed in this study had similar performance to previous calibration models (i.e. ISAT, ETIS) but are easier to apply and more widely applicable.     

Complex and dynamic population structures: synthesis, open questions, and future directions

The population structure of an evolutionary algorithm influences the dissemination and mixing of advantageous alleles, and therefore affects search performance. Much recent attention has focused on the analysis of complex population structures, characterized by heterogeneous connectivity distributions, non-trivial clustering properties, and degree–degree correlations. Here, we synthesize the results of these recent studies, discuss their limitations, and highlight several open questions regarding (1) unsolved theoretical issues and (2) the practical utility of complex population structures for evolutionary search. In addition, we will discuss an alternative complex population structure that is known to significantly influence dynamical processes, but has yet to be explored for evolutionary optimization. We then shift our attention toward dynamic population structures, which have received markedly less attention than their static counterparts. We will discuss the strengths and limitations of extant techniques and present open theoretical and experimental questions and directions for future research. In particular, we will focus on the prospects of “active linking,” wherein edges are dynamically rewired according to the genotypic or phenotypic properties of individuals, or according to the success of prior inter-individual interactions.     

Tensile stress relaxation in unsaturated granular materials

The mechanics of granular media at low liquid saturation levels remain poorly understood. Macroscopic mechanical properties are affected by microscale forces and processes, such as capillary forces, inter-particle friction, liquid flows, and particle movements. An improved understanding of these microscale mechanisms is important for a range of industrial applications and natural phenomena (e.g. landslides). This study focuses on the transient evolution of the tensile stress of unsaturated granular media under extension. Experimental results suggest that the stress state of the material evolves even after cessation of sample extension. Moreover, we observe that the packing density strongly affects the efficiency of different processes that result in tensile stress relaxation. By comparing the observed relaxation time scales with published data, we conclude that tensile stress relaxation is governed by particle rearrangement and fluid redistribution. An increased packing density inhibits particle rearrangement and only leaves fluid redistribution as the major process that governs tensile stress relaxation.     

Particle–Fluid–Structure Interaction for Debris Flow Impact on Flexible Barriers

Flexible barriers are increasingly used for the protection from debris flow in mountainous terrain due to their low cost and environmental impact. However, the development of a numerical tool for the rational design of such structures is still a challenge. In this work, a hybrid computational framework is presented, using a total Lagrangian formulation of the finite element method to represent a flexible barrier. The actions exerted on the structure by a debris flow are obtained from simultaneous simulations of the flow of a fluid‐grain mixture, using two conveniently coupled solvers: the discrete element method governs the motion of the grains, while the free‐surface non‐Newtonian fluid phase is solved using the lattice Boltzmann method. Simulations on realistic geometries show the dependence of the momentum transfer on the barrier on the composition of the debris flow, challenging typical assumptions made during the design process today. In particular, we demonstrate that both grains and fluid contribute in a nonnegligible way to the momentum transfer. Moreover, we show how the flexibility of the barrier reduces its vulnerability to structural collapse, and how the stress is distributed on its fabric, highlighting potential weak points.     

Experimental studies and thermodynamic assessment of the Ba-Mo-O system by the CALPHAD method

Thermodynamic measurements on BaMoO₄, BaMoO₃ and BaMo₃O₁₀ are reported, that served as input for the development of a thermodynamic model of the Ba-Mo-O system using the CALPHAD methodology. The valence states of molybdenum in BaMoO₄ and BaMoO₃ were confirmed to be VI and IV, respectively, from X-ray Absorption Near Edge Structure Spectroscopy measurements at the Mo K-edge. The heat capacity at low temperatures of these compounds was obtained from thermal-relaxation calorimetry. Phase equilibrium data in the BaMoO₄-MoO₃ section were also measured, and the transition enthalpy associated with the peritectic decomposition of BaMo₃O₁₀ was determined using Differential Scanning Calorimetry. The developed thermodynamic model used the compound energy formalism for intermediate compounds, and an ionic two-sublattice model for the liquid phase. The optimized Gibbs energies were assessed with respect to the known thermodynamic and phase equilibrium data. A good agreement is generally obtained, but a number of ill-defined data were also identified.     

The role of the methyl ester moiety in biodiesel combustion: A kinetic modeling comparison of methyl butanoate and n-butane

Growth of the biodiesel industry has motivated increased study of the combustion characteristics of its constituent molecules and building combustion modeling capability. Understanding how these characteristics differ between bio-derived and conventional diesel fuels can help in evaluating biodiesel performance. A kinetic modeling comparison of methyl butanoate and n-butane, its corresponding alkane, contrasted the combustion of methyl esters and normal alkanes, towards understanding the effect of the methyl ester moiety. Utilizing a combined n-heptane and methyl butanoate kinetic mechanism in shock tube simulations, the results predicted no region of negative temperature coefficient (NTC) behavior for methyl butanoate, compared to a well defined NTC region for n-butane. We observed that oxidation pathways associated with the methyl ester moiety inhibited NTC behavior, through increased production of hydroperoxy radicals (HO₂) instead of hydroxyl radicals (OH). In addition, we compared the evolution of carbon monoxide, carbon dioxide, ethylene and acetylene. The early formation of CO and CO₂, directly from methyl butanoate, revealed unique reaction pathways that also influenced a reduction in soot precursor formation. Overall, these results will help to understand how combustion processes change with the inclusion of oxygenated fuels, which will inform the study and design of combustion technologies.