Establishing the skill of climate field reconstruction techniques for precipitation with pseudoproxy experiments

This study aims at assessing the skill of several climate field reconstruction techniques (CFR) to reconstruct past precipitation over continental Europe and the Mediterranean at seasonal time scales over the last two millennia from proxy records. A number of pseudoproxy experiments are performed within the virtual reality ofa regional paleoclimate simulation at 45 km resolution to analyse different aspects of reconstruction skill. Canonical Correlation Analysis (CCA), two versions of an Analog Method (AM) and Bayesian hierarchical modeling (BHM) are applied to reconstruct precipitation from a synthetic network of pseudoproxies that are contaminated with various types of noise. The skill of the derived reconstructions is assessed through comparison with precipitation simulated by the regional climate model. Unlike BHM, CCA systematically underestimates the variance. The AM can be adjusted to overcome this shortcoming, presenting an intermediate behaviour between the two aforementioned techniques. However, a trade-off between reconstruction-target correlations and reconstructed variance is the drawback of all CFR techniques. CCA (BHM) presents the largest (lowest) skill in preserving the temporal evolution, whereas the AM can be tuned to reproduce better correlation at the expense of losing variance. While BHM has been shown to perform well for temperatures, it relies heavily on prescribed spatial correlation lengths. While this assumption is valid for temperature, it is hardly warranted for precipitation. In general, none of the methods outperforms the other. All experiments agree that a dense and regularly distributed proxy network is required to reconstruct precipitation accurately, reflecting its high spatial and temporal variability. This is especially true in summer, when a specifically short de-correlation distance from the proxy location is caused by localised summertime convective precipitation events.

Optimized Decoding for Auditory Attention Detection

Thesis (Master's)--University of Washington, 2016-06

PCR-DGGE Fingerprinting Analysis of Plankton Communities and Its Relationship to Lake Trophic Status

Plankton communities in eight lakes of different trophic status near Yangtze, China were characterized by using denatured gradient gel electrophoresis (DGGE). Various water quality parameters were also measured at each collection site. Following extraction of DNA from plankton communities, 16S rRNA and 18S rRNA genes were amplified with specific primers for prokaryotes and eukaryotes, respectively; DNA profiles were developed by DGGE. The plankton community of each lake had its own distinct DNA profile. The total number of bands identified at 34 sampling stations ranged from 37 to 111. Both prokaryotes and eukaryotes displayed complex fingerprints composed of a large number of bands: 16 to 59 bands were obtained with the prokaryotic primer set; 21 to 52 bands for the eukaryotic primer set. The DGGE-patterns were analyzed in relation to water quality parameters by canonical correspondence analysis (CCA). Temperature, pH, alkalinity, and the concentration of COD, TP and TN were strongly correlated with the DGGE patterns. The parameters that demonstrated a strong correlation to the DGGE fingerprints of the plankton community differed among lakes, suggesting that differences in the DGGE fingerprints were due mainly to lake trophic status. Results of the present study suggest that PCR-DGGE fingerprinting is an effective and precise method of identifying changes to plankton community composition, and therefore could be a useful ecological tool for monitoring the response of aquatic ecosystems to environmental perturbations.

Extensive impact of saturated fatty acids on metabolic and cardiovascular profile in rats with diet-induced obesity: A canonical analysis

Background: Although hypercaloric interventions are associated with nutritional, endocrine, metabolic, and cardiovascular disorders in obesity experiments, a rational distinction between the effects of excess adiposity and the individual roles of dietary macronutrients in relation to these disturbances has not previously been studied. This investigation analyzed the correlation between ingested macronutrients (including sucrose and saturated and unsaturated fatty acids) plus body adiposity and metabolic, hormonal, and cardiovascular effects in rats with diet-induced obesity. Methods: Normotensive Wistar-Kyoto rats were submitted to Control (CD; 3.2 Kcal/g) and Hypercaloric (HD; 4.6 Kcal/g) diets for 20 weeks followed by nutritional evaluation involving body weight and adiposity measurement. Metabolic and hormonal parameters included glycemia, insulin, insulin resistance, and leptin. Cardiovascular analysis included systolic blood pressure profile, echocardiography, morphometric study of myocardial morphology, and myosin heavy chain (MHC) protein expression. Canonical correlation analysis was used to evaluate the relationships between dietary macronutrients plus adiposity and metabolic, hormonal, and cardiovascular parameters. Results: Although final group body weights did not differ, HD presented higher adiposity than CD. Diet induced hyperglycemia while insulin and leptin levels remained unchanged. In a cardiovascular context, systolic blood pressure increased with time only in HD. Additionally, in vivo echocardiography revealed cardiac hypertrophy and improved systolic performance in HD compared to CD; and while cardiomyocyte size was unchanged by diet, nuclear volume and collagen interstitial fraction both increased in HD. Also HD exhibited higher relative β-MHC content and β/α-MHC ratio than their Control counterparts. Importantly, body adiposity was weakly associated with cardiovascular effects, as saturated fatty acid intake was directly associated with most cardiac remodeling measurements while unsaturated lipid consumption was inversely correlated with these effects. Conclusion: Hypercaloric diet was associated with glycemic metabolism and systolic blood pressure disorders and cardiac remodeling. These effects directly and inversely correlated with saturated and unsaturated lipid consumption, respectively. © 2013 Oliveira Junior et al.; licensee BioMed Central Ltd.

Statnote 28:Canonical Variate Analysis (CVA)

The pattern of correlation between two sets of variables can be tested using canonical variate analysis (CVA). CVA, like principal components analysis (PCA) and factor analysis (FA) (Statnote 27, Hilton & Armstrong, 2011b), is a multivariate analysis Essentially, as in PCA/FA, the objective is to determine whether the correlations between two sets of variables can be explained by a smaller number of ‘axes of correlation’ or ‘canonical roots’.

Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

Spectroscopic correlation analysis of NMR-based metabonomics in exercise science

Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a 1H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.

Two-Dimensional Correlation Analysis of Temperature-Dependent FT-IR Spectra of Oleic Acid

In the present study, variable temperature FT-IR spectroscopic investigations were used to characterize the spectral changes in oleic acid during heating oleic acid in the temperature range from -30 degrees;C to 22 degrees C. In order to extract more information about the spectral variations taking place during the phase transition process, 2D correlation spectroscopy (2DCOS) was employed for the stretching (C?O) and rocking (CH2) band of oleic acid. However, the interpretation of these spectral variations in the FT-IR spectra is not straightforward, because the absorption bands are heavily overlapped and change due to two processes: recrystallization of the ?-phase and melting of the oleic acid. Furthermore, the solid phase transition from the ?- to the a-phase was also observed between -4 degrees C and -2 degrees C. Thus, for a more detailed 2DCOS analysis, we have split up the spectral data set in the subsets recorded between -30 degrees C to -16 degrees C, -16 degrees C to 10 degrees C, and 10 degrees C to 22 degrees C. In the corresponding synchronous and asynchronous 2D correlation plots, absorption bands that are characteristic of the crystalline and amorphous regions of oleic acid were separated.

Controlling factors of spring-summer phytoplankton succession in Lake Taihu (Meiliang Bay, China)

The spring-summer successions of phytoplankton and crustacean zooplankton were examined weekly in Meiliang Bay of the subtropical Lake Taihu in 2004 and 2005. During the study period, the ecosystem of Meiliang Bay was characterized by (i) clearly declined nitrogen compounds (nitrate, TN, and ammonium) and slowly increased phosphorus compounds (TP and SRP), (ii) increased total phytoplankton density and rapid replacement of chlorophyta (mainly Ulothrix) by cyanobacteria (mainly Microcystis), and (iii) rapid replacement of large-sized crustaceans (Daphnia and Moina) by small-sized ones (Bosmina, Limnoithona, and Ceriodaphnia). Results from the CCA and correlation analysis indicate that the spring-summer phytoplankton succession was primarily controlled by abiotic factors. Cyanobacteria were mainly promoted by increased temperature and decreased concentrations of nitrogen compounds. The pure contribution of crustacean was low for the variation of phytoplankton suggesting a weak top-down control by crustacean zooplankton in the subtropical Lake Taihu.

Bonding and correlation analysis of various SiCO isomers

The structural properties for various SiCO isomers in the singlet and triplet states have been investigated using CASSCF methods with a 6-311 +G* basis set and also using three DFT and MP2 with same basis set for those systems except for the linear singlet state. The detailed bonding character is discussed, and the state-state correlations and the isomerization mechanism are also determined. Results indicate that there are four different isomers for each spin state, and for all isomers, the triplet state is more stable than the corresponding singlet state. The most stable is the linear SiCO ((3)Sigma(-)) species and may be refer-red to the ground state. At the CASSCF-MP2(full)/6-311+G* level, the state-state energy separations of the other triplet states relative to the ground state are 43.2 (cyclic), 45.2 (linear SiOC), and 75.6 kcal/mol (linear CSiO), respectively, whereas the triplet-singlet state excitation energies for each configuration are 17.3 (linear SiCO), 2.2 (cyclic SiCO), 10.2 (linear SiOC), and 18.5 kcal/mol (linear CSiO), respectively. SiCo ((3)Sigma(-)) may be classified as silene (carbonylsilene), and its COdelta- moiety possesses CO- property. The dissociation energy of the ground state is 42.5 kcal/mol at the CASSCF-MP2(full)/6-311+G* level and falls within a range of 36.5-41.5 kcal/mol at DFT level, and of 23.7-28.9 kcal/mol at the wave function-correlated level, whereas the vertical IP is 188.8 kcal/mol at the CASSCF-MP2(full)/6-311+G* level and is very close to the first IP of Si atom. Three linear isomers (SiCO, SiOC, and CSiO) have similar structural bonding character. SiOC may be referred to the iso-carbonyl Si instead of the aether compound, whereas the CSiO isomer may be considered as the combination of C (the analogue of Si) with SiO (the analogue of CO). The bonding is weak for all linear species, and the corresponding potential energy surfaces are flat, and thus these linear molecules are facile. Another important isomer is of cyclic structure, it may be considered as the combination of CO with Si by the side pi bond. This structure has the smallest triplet state-singlet state excitation energy (similar to2.2 kcal/mol); the C-O bonds are longer, and the corresponding vibrational frequencies are significantly smaller than those of the other linear species. This cyclic species is not classified as an epoxy compound. State-state correlation analysis and the isomerization pathway searches have indicated that there are no direct correlations among three linear structures for each spin state, but they may interchange by experiencing two transition states and one cyclic intermediate. The easiest pathway is to break the Si-O bond to go to the linear SiCO, but its inverse process is very difficult. The most difficult process is to break the C-O bond and to go to the linear CSiO.

DCA、CCA和DCCA三种排序方法在中国草地植被群落中的应用现状

排序是用来分析植被与环境之间生态关系的重要手段。该文主要是对除趋势对应分析(DCA)、典范对应分析(CCA)和除趋势典范对应分析(DCCA)这三种排序方法进行总结,讨论它们在中国草地植被群落研究中的应用现状,并得出除趋势对应分析与聚类分析结合使用效果比较好,主要是用来揭示群落之间的关系,并且在实际的应用中也比较多,而典范对应分析和除趋势典范对应分析在揭示种与环境关系方面具有明显的优势,但是由于某些条件的限制,在实际研究中应用的比较少。可见这几种排序方法在实际应用中具有一定的优势,所以应该加强这方面的应用,更加深入的研究草地植被群落,以期对草地生态学及草地植被群落生态关系的研究工作发挥重要的借鉴作用。

Correlation analysis of the structures and stability constants of gadolinium(III) complexes

To simplify the abstraction of descriptors, for the correlation analysis of the stability constants of gadolinium(III) complexes and their ligand structures, aiming at gadolinium(III) complexes, we only considered the ligands and ignored the common parts of the structures, i.e., the metal ions. Quantum-chemical descriptors and topological indices were calculated to describe the structures of the ligands. Multiple regression analysis and neural networks were applied to construct the models between the ligands and the stability constants of gadolinium(III) complexes and satisfactory results were obtained.

Correlation analysis of the structures and pK(a) values of carboxylic acids

The quantum-chemical descriptors were used for QSPR study of the structures of carboxylic acids and their pK(a) values. The algorithm of "Leaps and Bounds" regression was performed for selection of the variables. The CoMFA method was carried out for 3D-QSPR. As the introduction of the charge of oxygen atom(Q(2)), the results obtained by CoMFA were improved greatly.

Correlation analysis of the structures and gas-liquid chromatographic retention indices of amines

Quantitative structure-retention relationship(QSRR) was studied for amines to gas-liquid chromatography on three stationary phases of different polarities with the topological indices A(m) (A(m1), A(m2), A(m3)) and gravitational index GI. The algorithm of "Leaps and Bounds" was performed for selection of the variables. And the multi-regression and the quasi-Newton neural networks were employed for the calculation with better results.