Thermogravimetric evaluation of perennial ryegrass (Lolium perenne) for the prediction of in vitro dry matter digestibility

Thermogravimetry (TG) can be used for assessing the compositional differences in grasses that relate to dry matter digestibility (DMD) determined by pepsin-cellulase assay. This investigation developed regression models for predicting DMD of herbage grass during one growing season using TG results. The calibration samples were obtained from a field trial of eight cultivars and two breeding lines. The harvested materials from five cuts were analysed by TG to identify differences in the combustion patterns within the range of 30-600 degrees C. The discrete results including weight loss, peak height, area, temperature, widths and residue of three decomposition peaks were regressed against the measured DMD values of the calibration samples. Similarly, continuous weight loss results of the same samples were also utilised to generate DMD models. The r(2) for validation of the discrete and the best continuous models were 0.90 and 0.95, respectively, and the two calibrations were validated using independent samples from 24 plots from a trial carried out in 2004. The standard error for prediction of the 24 samples by the discrete model (4.14%) was higher than that by the continuous model (2.98%). This study has shown that DMD of grass could be predicted from the TG results. The benefit of thermal analysis is the ability to detect and show changes in composition of cell wall fractions of grasses during different cuts in a year.

Prediction of ionic liquid properties. I. Volumetric properties as a function of temperature at 0.1 MPa

The prediction of molar volumes and densities of several ionic liquids has been achieved using a group contribution model as a function of temperature between (273 and 423) K at atmospheric pressure. It was observed that the calculation of molar volumes or densities could be performed using the "ideal" behavior of the molar volumes of mixtures of ionic liquids. This model is based on the observations of Canongia Lopes et al. (J. Phys. Chem. B 2005, 109, 3519-3525) which showed that this ideal behavior is independent of the temperature and allows the molar volume of a given ionic liquid to be calculated by the sum of the effective molar volume of the component ions. Using this assumption, the effective molar volumes of ions constituting more than 220 different ionic liquids were calculated as a function of the temperature at 0.1 MPa using more than 2150 data points. These calculated results were used to build up a group contribution model for the calculation of ionic liquid molar volumes and densities with an estimated repeatability and uncertainty of 0.36% and 0.48%, respectively. The impact of impurities (water and halide content) in ionic liquids as well as the method of determination were also analyzed and quantified to estimate the overall uncertainty. © 2008 American Chemical Society.

Heat capacities of ionic liquids as a function of temperature at 0.1 MPa. measurement and prediction

Heat capacities of nine ionic liquids were measured from (293 to 358) K by using a heat flux differential scanning calorimeter. The impact of impurities (water and chloride content) in the ionic liquid was analyzed to estimate the overall uncertainty. The Joback method for predicting ideal gas heat capacities has been extended to ionic liquids by the generation of contribution parameters for three new groups. The principle of corresponding states has been employed to enable the subsequent calculation of liquid heat capacities for ionic liquids, based on critical properties predicted using the modified Lydersen-Joback-Reid method, as a function of the temperature from (256 to 470) K. A relative absolute deviation of 2.9% was observed when testing the model against 961 data points from 53 different ionic liquids reported previously and measured within this study.

Evaluation of Gas Solubility Prediction in Ionic Liquids using COSMOthermX

As the range of available ionic liquids increases, methods by which important engineering parameters such as gas solubilities can be estimated from simple structural information become ever more desirable. COSMO-based thermodynamic models, such as that used by COSMOthermX, allow the determination of such data for pure and mixed component systems. Herein, we evaluate the predictive capability of COSMOthermX through a comparison with literature data obtained from the IUPAC database which contains data for 15 gases in 27 ionic liquids, To determine any effect inherent to ionic liquids, gas solubility predictions were first performed for selected molecular solvents at constant temperature and pressure. Further estimations of gas solubility at temperatures ranging from (278 to 368) K at 0.1 MPa in water were performed for 14 gases. The Study has demonstrated that COSMOthermX is capable of predicting, qualitatively, gas solubilities in ionic liquids and, hence, reducing the amount of unnecessary experimental measurements prior to specific applications using ionic liquids.

Prediction of bisolute dye adsorption isotherms on activated carbon

The removal of acid dyes, Tectilon Blue 4R, Tectilon Red 2B and Tectilon Orange 3G, from single solute, bisolute and trisolute solutions by adsorption on activated carbon (GAC F400) has been investigated in isotherm experiments. Results from these experiments were modelled using the Langmuir and Freundlich adsorption isotherm theories with the Langmuir model proving to be the more suitable. The Ideal Adsorbed Solution (IAS) model was coupled with the Langmuir isotherm to predict binary adsorption on the dyes. The application of the IAS theory accurately simulated the experimental data with an average deviation of approximately 3% between modelled and experimental data.

Prediction of Fresh and Hardened Properties of Self-Consolidating Concrete Using Neurofuzzy Approach

Self-consolidating concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work conditions and also reduce the impact on the environment by elimination of the need for compaction. This investigation aimed at exploring the potential use of the neurofuzzy (NF) approach to model the fresh and hardened properties of SCC containing pulverised fuel ash (PFA) as based on experimental data investigated in this paper. Twenty six mixes were made with water-to-binder ratio ranging from 0.38 to 0.72, cement content ranging from 183 to 317 kg/m3 , dosage of PFA ranging from 29 to 261 kg/m3 , and percentage of superplasticizer, by mass of powder, ranging from 0 to 1%. Nine properties of SCC mixes modeled by NF were the slump flow, JRing combined to the Orimet, JRing combined to cone, V-funnel, L-box blocking ratio, segregation ratio, and the compressive strength at 7, 28, and 90 days. These properties characterized the filling ability, the passing ability, the segregation resistance of fresh SCC, and the compressive strength. NF model is constructed by training and testing data using the experimental results obtained in this study. The results of NF models were compared with experimental results and were found to be quite accurate. The proposed NF models offers useful modeling approach of the fresh and hardened properties of SCC containing PFA.

Prediction of the formation and stabilities of energetic salts and ionic liquids based on ab initio electronic structure calculations

A computational approach to predict the thermodynamics for forming a variety of imidazolium-based salts and ionic liquids from typical starting materials is described. The gas-phase proton and methyl cation acidities of several protonating and methylating agents, as well as the proton and methyl cation affinities of many important methyl-, nitro-, and cyano- substituted imidazoles, have been calculated reliably by using the computationally feasible DFT (B3LYP) and MP2 (extrapolated to the complete basis set limit) methods. These accurately calculated proton and methyl cation affinities of neutrals and anions are used in conjunction with an empirical approach based on molecular volumes to estimate the lattice enthalpies and entropies of ionic liquids, organic solids, and organic liquids. These quantities were used to construct a thermodynamic cycle for salt formation to reliably predict the ability to synthesize a variety of salts including ones with potentially high energetic densities. An adjustment of the gas phase thermodynamic cycle to account for solid- and liquid-phase chemistries provides the best overall assessment of salt formation and stability. This has been applied to imidazoles (the cation to be formed) with alkyl, nitro, and cyano substituents. The proton and methyl cation donors studied were as follows: HCl, HBr, HI, (HO)(2)SO2, HSO3CF3 (TfOH), and HSO3(C6H4)CH3 (TsOH); CH3Cl, CH3Br, CH3I, (CH3O)(2)SO2, CH3SO3CF3 (TfOCH3) and CH3SO3(C6H4)CH3 (TsOCH3). As substitution of the cation with electron-withdrawing groups increases, the triflate reagents appear to be the best overall choice as protonating and methylating agents. Even stronger alkylating agents should be considered to enhance the chances of synthetic success. When using the enthalpies of reaction for the gas-phase reactants (eq 6) to form a salt, a cutoff value of - 13 kcal mol(-1) or lower (more negative) should be used as the minimum value for predicting whether a salt can be synthesized.

Using time-to-contact information to assess potential collision modulates both visual and temporal prediction networks

Accurate estimates of the time-to-contact (TTC) of approaching objects are crucial for survival. We used an ecologically valid driving simulation to compare and contrast the neural substrates of egocentric (head-on approach) and allocentric (lateral approach) TTC tasks in a fully factorial, event-related fMRI design. Compared to colour control tasks, both egocentric and allocentric TTC tasks activated left ventral premotor cortex/frontal operculum and inferior parietal cortex, the same areas that have previously been implicated in temporal attentional orienting. Despite differences in visual and cognitive demands, both TTC and temporal orienting paradigms encourage the use of temporally predictive information to guide behaviour, suggesting these areas may form a core network for temporal prediction. We also demonstrated that the temporal derivative of the perceptual index tau (tau-dot) held predictive value for making collision judgements and varied inversely with activity in primary visual cortex (V1). Specifically, V1 activity increased with the increasing likelihood of reporting a collision, suggesting top-down attentional modulation of early visual processing areas as a function of subjective collision. Finally, egocentric viewpoints provoked a response bias for reporting collisions, rather than no-collisions, reflecting increased caution for head-on approaches. Associated increases in SMA activity suggest motor preparation mechanisms were engaged, despite the perceptual nature of the task.

Prediction of microRNAs affecting mRNA expression during retinal development.

Background: MicroRNAs (miRNAs) are small RNA molecules (similar to 22 nucleotides) which have been shown to play an important role both in development and in maintenance of adult tissue. Conditional inactivation of miRNAs in the eye causes loss of visual function and progressive retinal degeneration. In addition to inhibiting translation, miRNAs can mediate degradation of targeted mRNAs. We have previously shown that candidate miRNAs affecting transcript levels in a tissue can be deduced from mRNA microarray expression profiles. The purpose of this study was to predict miRNAs which affect mRNA levels in developing and adult retinal tissue and to confirm their expression.

Results: Microarray expression data from ciliary epithelial retinal stem cells (CE-RSCs), developing and adult mouse retina were generated or downloaded from public repositories. Analysis of gene expression profiles detected the effects of multiple miRNAs in CE-RSCs and retina. The expression of 20 selected miRNAs was confirmed by RT-PCR and the cellular distribution of representative candidates analyzed by in situ hybridization. The expression levels of miRNAs correlated with the significance of their predicted effects upon mRNA expression. Highly expressed miRNAs included miR-124, miR-125a, miR-125b, miR-204 and miR-9. Over-expression of three miRNAs with significant predicted effects upon global mRNA levels resulted in a decrease in mRNA expression of five out of six individual predicted target genes assayed.

Conclusions: This study has detected the effect of miRNAs upon mRNA expression in immature and adult retinal tissue and cells. The validity of these observations is supported by the experimental confirmation of candidate miRNA expression and the regulation of predicted target genes following miRNA over-expression. Identified miRNAs are likely to be important in retinal development and function. Misregulation of these miRNAs might contribute to retinal degeneration and disease. Conversely, manipulation of their expression could potentially be used as a therapeutic tool in the future.