Correlation between Accurate Electron Density and Linear Optical Properties in Amino Acid Derivatives: L-Histidinium Hydrogen Oxalate

The accurate electron density and linear optical properties of L-histidinium hydrogen oxalate are discussed. Two high-resolution single crystal X-ray diffraction experiments were performed and compared with density functional calculations in the solid state as well as in the gas phase. The crystal packing and the hydrogen bond network are accurately investigated using topological analysis based on quantum theory of atoms in molecules, Hirshfeld surface analysis, and electrostatic potential mapping. The refractive indices are computed from couple perturbed Kohn-Sham calculations and measured experimentally. Moreover, distributed atomic polarizabilities are used to analyze the origin of the linear susceptibility in the crystal, in order to separate molecular and intermolecular causes. The optical properties are also correlated with the electron density distribution. This compound also offers the possibility to test the electron density building block approach for material science and different refinement schemes for accurate positions and displacement parameters of hydrogen atoms, in the absence of neutron diffraction data.

A novel method for evaluating an interaction effect of correlated continuous covariates in a linear model

Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^

Scrapie susceptibility-linked polymorphisms modulate the in vitro conversion of sheep prion protein to protease-resistant forms

Prion diseases are natural transmissible neurodegenerative disorders in humans and animals. They are characterized by the accumulation of a protease-resistant scrapie-associated prion protein (PrPSc) of the host-encoded cellular prion protein (PrPC) mainly in the central nervous system. Polymorphisms in the PrP gene are linked to differences in susceptibility for prion diseases. The mechanisms underlying these effects are still unknown. Here we describe studies of the influence of sheep PrP polymorphisms on the conversion of PrPC into protease-resistant forms. In a cell-free system, sheep PrPSc induced the conversion of sheep PrPC into protease-resistant PrP (PrP-res) similar or identical to PrPSc. Polymorphisms present in either PrPC or PrPSc had dramatic effects on the cell-free conversion efficiencies. The PrP variant associated with a high susceptibility to scrapie and short survival times of scrapie-affected sheep was efficiently converted into PrP-res. The wild-type PrP variant associated with a neutral effect on susceptibility and intermediate survival times was converted with intermediate efficiency. The PrP variant associated with scrapie resistance and long survival times was poorly converted. Thus the in vitro conversion characteristics of the sheep PrP variants reflect their linkage with scrapie susceptibility and survival times of scrapie-affected sheep. The modulating effect of the polymorphisms in PrPC and PrPSc on the cell-free conversion characteristics suggests that, besides the species barrier, polymorphism barriers play a significant role in the transmissibility of prion diseases.

Optimal unravellings for feedback control in linear quantum systems

For quantum systems with linear dynamics in phase space much of classical feedback control theory applies. However, there are some questions that are sensible only for the quantum case: Given a fixed interaction between the system and the environment what is the optimal measurement on the environment for a particular control problem? We show that for a broad class of optimal (state- based) control problems ( the stationary linear-quadratic-Gaussian class), this question is a semidefinite program. Moreover, the answer also applies to Markovian (current-based) feedback.

Exploratory data analysis with non-linear and missing data in geochemistry

Exploratory analysis of data seeks to find common patterns to gain insights into the structure and distribution of the data. In geochemistry it is a valuable means to gain insights into the complicated processes making up a petroleum system. Typically linear visualisation methods like principal components analysis, linked plots, or brushing are used. These methods can not directly be employed when dealing with missing data and they struggle to capture global non-linear structures in the data, however they can do so locally. This thesis discusses a complementary approach based on a non-linear probabilistic model. The generative topographic mapping (GTM) enables the visualisation of the effects of very many variables on a single plot, which is able to incorporate more structure than a two dimensional principal components plot. The model can deal with uncertainty, missing data and allows for the exploration of the non-linear structure in the data. In this thesis a novel approach to initialise the GTM with arbitrary projections is developed. This makes it possible to combine GTM with algorithms like Isomap and fit complex non-linear structure like the Swiss-roll. Another novel extension is the incorporation of prior knowledge about the structure of the covariance matrix. This extension greatly enhances the modelling capabilities of the algorithm resulting in better fit to the data and better imputation capabilities for missing data. Additionally an extensive benchmark study of the missing data imputation capabilities of GTM is performed. Further a novel approach, based on missing data, will be introduced to benchmark the fit of probabilistic visualisation algorithms on unlabelled data. Finally the work is complemented by evaluating the algorithms on real-life datasets from geochemical projects.

Addressing missing data in geochemistry: a non-linear approach

Exploratory analysis of petroleum geochemical data seeks to find common patterns to help distinguish between different source rocks, oils and gases, and to explain their source, maturity and any intra-reservoir alteration. However, at the outset, one is typically faced with (a) a large matrix of samples, each with a range of molecular and isotopic properties, (b) a spatially and temporally unrepresentative sampling pattern, (c) noisy data and (d) often, a large number of missing values. This inhibits analysis using conventional statistical methods. Typically, visualisation methods like principal components analysis are used, but these methods are not easily able to deal with missing data nor can they capture non-linear structure in the data. One approach to discovering complex, non-linear structure in the data is through the use of linked plots, or brushing, while ignoring the missing data. In this paper we introduce a complementary approach based on a non-linear probabilistic model. Generative topographic mapping enables the visualisation of the effects of very many variables on a single plot, while also dealing with missing data. We show how using generative topographic mapping also provides an optimal method with which to replace missing values in two geochemical datasets, particularly where a large proportion of the data is missing.

Structure of the understory community in four stretches of Araucaria forest in the state of São Paulo, Brazil

We analyzed the structure of the understory community in the Atlantic Forest sensu lato, for which phytosociological descriptions of the understory are lacking. We delineated 50 plots of 10 × 20 m each at four sites within an Araucaria forest (a subtype of Atlantic Forest), located in the municipalities of Bananal, Campos do Jordão, Itaberá and Barra do Chapéu, all of which are in the state of São Paulo, Brazil. To sample the resident species of the understory, we randomly selected five 1 × 1 m subplots within each plot, resulting in a total sampling area of 250 m² at each site. We identified differences among the locations, mostly due to proportional differences in growth forms, in terms of species richness and the importance values within the community. Factors potentially influencing the understory structure include macroclimatic and microclimatic conditions, as well as forest fragmentation, the abundance of deciduous trees in the canopy, the surrounding vegetation and geographic location.

Morphology and anatomy of leaf miners in two species of Commelinaceae (Commelina diffusa Burm. f. and Floscopa glabrata (Kunth) Hassk)

In specialized literature, reports on anatomy of miners in host plants are few in number. These agents trigger excavations, or paths, by consumption of plant inner tissues by larvae of several insects. The aim of this work was to investigate leaf miner occurrence in Commelina diffusa (a cosmopolitan plant) and Floscopa glabrata (an amphibious plant) using anatomical techniques. The place where the plants were collected is subjected to seasonal floods, consequently both the species were exposed to the same weather conditions and seasonal floods. This study showed that members of Agromyzidae and Chironomidae families, which are Diptera endophytophagous larvae types, were responsible for the tunnels. Moreover, in Commelina diffusa Agromyzidae larvae were found, while in Floscopa glabrata three Chironomidae cephalic exuviae were found. The miners, as can be seen from anatomical studies, used only mesophyll parenchyma tissues for feeding, causing the formation of linear mines. In addition, in both the species, the epidermis and the medium-sized vascular units were kept intact, showing no structural modification, such as neoformation of tissues.

Ressonância não linear de uma bússola em campos magnéticos

Fenômenos oscilatórios e ressonantes são explorados em vários cursos experimentais de física. Em geral os experimentos são interpretados no limite de pequenas oscilações e campos uniformes. Neste artigo descrevemos um experimento de baixo custo para o estudo da ressonância em campo magnético da agulha de uma bússola fora dos limites acima. Nesse caso, termos não lineares na equação diferencial são responsáveis por fenômenos interessantes de serem explorados em laboratórios didáticos.

Effect of an energy-deficient diet on populations of ciliate protozoans in bovine rumen

Ten young rumen-cannulated crossbred steers were randomly divided into two groups: a control group (C; n=4), which was fed a balanced diet for daily weight gain of 900g; and a pronounced energy-deprived group (PED; n=6), receiving 30% less of the required energy for maintenance. After 140 days of these alimentary regimes, rumen fluid and urine samples were collected for biochemical and functional tests, before feeding and at 1, 3, 6, and 9 hours after feeding. The energy-deprivation diet caused a significant reduction in the number of Entodinium, Eodinium, Isotricha, Dasytricha, Eremoplastron, Eudiplodinium, Metadinium, Charonina, Ostracodinium, and Epidinium protozoa. There was no effect of the time of sampling in both groups on the total number of ciliates in rumen fluid. A higher number of protozoan forms in binary division were recorded in the control group, at the 6th and 9th hours after feeding (P<0.019). There was a high positive correlation between the total count of protozoans in rumen fluid and glucose fermentation, ammonia, and urinary allantoin excretion index; and a negative correlation between the total count of protozoa and metilene blue reduction, and a medium correlation between the total count of protozoa and total volatile fatty acids concentration. The determination of the protozoa populations does not imply in the use of complex and hard-to-execute techniques, although it is time consuming and needs practice. This exam particularly helps in clinical expected diagnosis.

Lysine and zinc chelate in diets for brown laying hens: effects on egg production and composition

It was evaluated the effects of levels of digestible lysine and chelate zinc combined in the diet for laying on the egg quality. It was used 720 birds, from 48 to 60 weeks of age, distributed in a completely randomized design in a 3 × 5 factorial scheme with three levels of zinc and five levels of lysine, applied into six replicates in the experimental units of eight birds per plot. The levels were: 137, 309 and 655 ppm zinc and 0.482, 0.527, 0.582, 0.644 and 0.732% digestible lysine. It was not observed any interaction among digestible lysine and zinc for the primary variables of fractions and egg composition. Levels of zinc reduced egg weight, suggesting the lowest efficiency in nutrient intake. At the highest dietary concentration of zinc, the addition of digestible lysine coincided with a linear increase in shell weight. However, zinc addition, regardless of lysine level in the diet, resulted in the reduction of egg weight and of the percentage of mineral matter in the yolk, limiting the efficiency of mineral deposition in this fraction of the egg. Concentration of zinc that produced the best results was 137 ppm inasmuch as higher quantities limit the use of digestible lysine, with effects harming composition and egg quality. The study indicates the following requirement for digestible lysine: 0.639% from the 48th to the 52nd week, 0.679% from the 52nd to 56th week, and 0.635% from the 56th to the 60th week. Considering the total period from 48th to the 60th week, the level 0.638% of lysine or the daily intake of 707 mg of the amino acid met the requirement for egg quality of semi-heavy layers used in this study.

Differential regulation of PGC-1 alpha expression in rat liver and skeletal muscle in response to voluntary running

Background: The beneficial actions of exercise training on lipid, glucose and energy metabolism and insulin sensitivity appear to be in part mediated by PGC-1 alpha. Previous studies have shown that spontaneously exercised rats show at rest enhanced responsiveness to exogenous insulin, lower plasma insulin levels and increased skeletal muscle insulin sensitivity. This study was initiated to examine the functional interaction between exercise-induced modulation of skeletal muscle and liver PGC-1 alpha protein expression, whole body insulin sensitivity, and circulating FFA levels as a measure of whole body fatty acid (lipid) metabolism. Methods: Two groups of male Wistar rats (2 Mo of age, 188.82 +/- 2.77 g BW) were used in this study. One group consisted of control rats placed in standard laboratory cages. Exercising rats were housed individually in cages equipped with running wheels and allowed to run at their own pace for 5 weeks. At the end of exercise training, insulin sensitivity was evaluated by comparing steady-state plasma glucose (SSPG) concentrations at constant plasma insulin levels attained during the continuous infusion of glucose and insulin to each experimental group. Subsequently, soleus and plantaris muscle and liver samples were collected and quantified for PGC-1 alpha protein expression by Western blotting. Collected blood samples were analyzed for glucose, insulin and FFA concentrations. Results: Rats housed in the exercise wheel cages demonstrated almost linear increases in running activity with advancing time reaching to maximum value around 4 weeks. On an average, the rats ran a mean (Mean +/- SE) of 4.102 +/- 0.747 km/day and consumed significantly more food as compared to sedentary controls (P < 0.001) in order to meet their increased caloric requirement. Mean plasma insulin (P < 0.001) and FFA (P < 0.006) concentrations were lower in the exercise-trained rats as compared to sedentary controls. Mean steady state plasma insulin (SSPI) and glucose (SSPG) concentrations were not significantly different in sedentary control rats as compared to exercise-trained animals. Plantaris PGC-1 alpha protein expression increased significantly from a 1.11 +/- 0.12 in the sedentary rats to 1.74 +/- 0.09 in exercising rats (P < 0.001). However, exercise had no effect on PGC-1 alpha protein content in either soleus muscle or liver tissue. These results indicate that exercise training selectively up regulates the PGC-1 alpha protein expression in high-oxidative fast skeletal muscle type such as plantaris muscle. Conclusion: These data suggest that PGC-1 alpha most likely plays a restricted role in exercise-mediated improvements in insulin resistance (sensitivity) and lowering of circulating FFA levels.

Recursive linear estimation for general discrete-time descriptor systems

This paper considers the optimal linear estimates recursion problem for discrete-time linear systems in its more general formulation. The system is allowed to be in descriptor form, rectangular, time-variant, and with the dynamical and measurement noises correlated. We propose a new expression for the filter recursive equations which presents an interesting simple and symmetric structure. Convergence of the associated Riccati recursion and stability properties of the steady-state filter are provided. (C) 2010 Elsevier Ltd. All rights reserved.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - III. The integrated wheat model (I_WHEAT)

Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.