Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches

We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.

Ultralow-density nanocage-based metal-oxide polymorphs

For two important metal oxides (MO, M=Mg, Zn) we predict, via accurate electronic structure calculations, that new low-density nanoporous crystalline phases may be accessible via the coalescence of nanocluster building blocks. Specifically, we consider the assembly of cagelike (MO)12 clusters exhibiting particularly high gas phase stability, leading to new polymorphs with energetic stabilities rivaling (and sometimes higher) than those of known MO polymorphs.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Fragmentation of massive dense cores down to <~ 1000 AU: relation between fragmentation and density structure

In order to shed light on the main physical processes controlling fragmentation of massive dense cores, we present a uniform study of the density structure of 19 massive dense cores, selected to be at similar evolutionary stages, for which their relative fragmentation level was assessed in a previous work. We inferred the density structure of the 19 cores through a simultaneous fit of the radial intensity profiles at 450 and 850 μm (or 1.2 mm in two cases) and the spectral energy distribution, assuming spherical symmetry and that the density and temperature of the cores decrease with radius following power-laws. Even though the estimated fragmentation level is strictly speaking a lower limit, its relative value is significant and several trends could be explored with our data. We find a weak (inverse) trend of fragmentation level and density power-law index, with steeper density profiles tending to show lower fragmentation, and vice versa. In addition, we find a trend of fragmentation increasing with density within a given radius, which arises from a combination of flat density profile and high central density and is consistent with Jeans fragmentation. We considered the effects of rotational-to-gravitational energy ratio, non-thermal velocity dispersion, and turbulence mode on the density structure of the cores, and found that compressive turbulence seems to yield higher central densities. Finally, a possible explanation for the origin of cores with concentrated density profiles, which are the cores showing no fragmentation, could be related with a strong magnetic field, consistent with the outcome of radiation magnetohydrodynamic simulations.

Model for interevent times with long tails and multifractality in human communications: An application to financial trading

Social, technological, and economic time series are divided by events which are usually assumed to be random, albeit with some hierarchical structure. It is well known that the interevent statistics observed in these contexts differs from the Poissonian profile by being long-tailed distributed with resting and active periods interwoven. Understanding mechanisms generating consistent statistics has therefore become a central issue. The approach we present is taken from the continuous-time random-walk formalism and represents an analytical alternative to models of nontrivial priority that have been recently proposed. Our analysis also goes one step further by looking at the multifractal structure of the interevent times of human decisions. We here analyze the intertransaction time intervals of several financial markets. We observe that empirical data describe a subtle multifractal behavior. Our model explains this structure by taking the pausing-time density in the form of a superstatistics where the integral kernel quantifies the heterogeneous nature of the executed tasks. A stretched exponential kernel provides a multifractal profile valid for a certain limited range. A suggested heuristic analytical profile is capable of covering a broader region.

New approximation to the third-order density : application to the calculation of correlated multicenter indices

In this work we present the formulas for the calculation of exact three-center electron sharing indices (3c-ESI) and introduce two new approximate expressions for correlated wave functions. The 3c-ESI uses the third-order density, the diagonal of the third-order reduced density matrix, but the approximations suggested in this work only involve natural orbitals and occupancies. In addition, the first calculations of 3c-ESI using Valdemoro's, Nakatsuji's and Mazziotti's approximation for the third-order reduced density matrix are also presented for comparison. Our results on a test set of molecules, including 32 3c-ESI values, prove that the new approximation based on the cubic root of natural occupancies performs the best, yielding absolute errors below 0.07 and an average absolute error of 0.015. Furthemore, this approximation seems to be rather insensitive to the amount of electron correlation present in the system. This newly developed methodology provides a computational inexpensive method to calculate 3c-ESI from correlated wave functions and opens new avenues to approximate high-order reduced density matrices in other contexts, such as the contracted Schrödinger equation and the anti-Hermitian contracted Schrödinger equation

Is contextual-potentiated eating dependent on caloric density of food?

One experiment tested whether a specific context could elicit eating in rats as a result of Pavlovian conditioning and whether this effect depended on the caloric density of food. Thirty two deprived rats experienced two contexts. They had access to food in context A, but no food was available in context B. During conditioning, half of the animals received high density caloric food (HD groups) whereas the other half, low density caloric food (LD groups). Then, half of the rats in each type of food group was tested in context A and the other half in context B. The results demonstrated an effect of context conditioning only in HD groups. These findings suggest the relevance of both contextual conditioning and caloric density of food in eating behaviour. Implications for the aetiology of binge eating will be discussed.

A Theoretical investigation of a potential high energy density compound 3,6,7,8-tetranitro-3,6,7,8-tetraaza-tricyclo[3.1.1.1(2,4)]octane

The B3LYP/6-31G (d) density functional theory (DFT) method was used to study molecular geometry, electronic structure, infrared spectrum (IR) and thermodynamic properties. Heat of formation (HOF) and calculated density were estimated to evaluate detonation properties using Kamlet-Jacobs equations. Thermal stability of 3,6,7,8-tetranitro-3,6,7,8-tetraaza-tricyclo [3.1.1.1(2,4)]octane (TTTO) was investigated by calculating bond dissociation energy (BDE) at the unrestricted B3LYP/6-31G(d) level. Results showed the N-NO2 bond is a trigger bond during the thermolysis initiation process. The crystal structure obtained by molecular mechanics (MM) methods belongs to P2(1)/C space group, with cell parameters a = 8.239 Å, b = 8.079 Å, c = 16.860 Å, Z = 4 and r = 1.922 g cm-3. Both detonation velocity of 9.79 km s-1 and detonation pressure of 44.22 GPa performed similarly to CL-20. According to the quantitative standards of energetics and stability, TTTO essentially satisfies this requirement as a high energy density compound (HEDC).

Factors affecting density of airborne Gibberella zeae inoculum

Fusarium head blight (FHB) is a disease of increasing concern in the production of wheat (Triticum aestivum). This work studied some of the factors affecting the density of airborne Gibberella zeae inoculum. Spore samplers were placed at the edge of a field in order to observe spore deposition over a period of 45 days and nights in September and October, the period that coincides with wheat flowering. Gibberella zeae colonies were counted for each period and values transformed to relative density. A stepwise regression procedure was used to identify weather variables helpful in predicting spore cloud density. In general, a predominant night-time spore deposition was observed. Precipitation and daily mean relative humidity over 90% were the factors most hightly associated with peak events of spores in the air. Models for predicting spore cloud density simulated reasonably well with the fluctuation of airborne propagules during both night and day, with potential to be integrated into an FHB risk model framework.

Evaluation of group electronegativities and hardness (softness) of group 14 elements and containing functional groups through density functional theory and correlation with NMR spectra data

Quantum Chemical calculations for group 14 elements of Periodic Table (C, Si, Ge, Sn, Pb) and their functional groups have been carried out using Density Functional Theory (DFT) based reactivity descriptors such as group electronegativities, hardness and softness. DFT calculations were performed for a large series of tetracoordinated Sn compounds of the CH3SnRR'X type, where X is a halogen and R and R' are alkyl, halogenated alkyl, alkoxy, or alkyl thio groups. The results were interpreted in terms of calculated electronegativity and hardness of the SnRR'X groups, applying a methodology previously developed by Geerlings and coworkers (J. Phys. Chem. 1993, 97, 1826). These calculations allowed to see the regularities concerning the influence of the nature of organic groups RR' and inorganic group X on electronegativities and hardness of the SnRR'X groups; in this case, it was found a very good correlation between the electronegativity of the fragment and experimental 119Sn chemical shifts, a property that sensitively reflects the change in the valence electronic structure of molecules. This work was complemented with the study of some compounds of the EX and ER types, where E= C, Si, Ge, Sn and R= CH3, H, which was performed to study the influence that the central atom has on the electronegativity and hardness of molecules, or whether these properties are mainly affected for the type of ligand bound to the central atom. All these calculations were performed using the B3PW91 functional together with the 6-311++G** basis set level for H, C, Si, Ge, F, Cl and Br atoms and the 3-21G for Sn and I atoms.

White mold intensity on common bean in response to plant density, irrigation frequency, grass mulching, Trichoderma spp., and fungicide

The purpose of this study was to evaluate the efficiency of integrated managements on white mold control on common bean. Initially, in vitro testing was made to assess the antagonism of 11 Trichoderma isolates against Sclerotinia sclerotiorum and to investigate fungicides (fluazinam and procymidone) inhibitory effects on those fungi. In two field experiments the following combinations were tested: irrigation frequencies (seven or 14 days), plant densities (six or 12 plants per meter), and three disease controls (untreated control, fungicide or Trichoderma spp.). In a third experiment plant densities were replaced by grass mulching treatments (with or without mulching). Fluazinam was applied at 45 and 55 days after emergence (DAE). The antagonists T. harzianum (experiments 1 and 3) and T. stromatica (experiment 2) were applied through sprinkler irrigation at 10 and 25 DAE, respectively. Most of the Trichoderma spp. were effective against the pathogen in vitro. Fluazinam was more toxic than procymidone to both the pathogen and the antagonist. Fungicide applications increased yield between 32 % and 41 %. In field one application of Trichoderma spp. did not reduce disease intensity and did not increase yield. The reduction from 12 to six plants per meter did not decrease yield, and disease severity diminished in one of the two experiments. It is concluded that of the strategies for white mold control just reduction of plant density and applications of fungicide were efficient.

Macrophomina phaseolina: density and longevity of microsclerotia in soybean root tissues and free on the soil, and competitive saprophytic ability

In field experiments, the density of Macrophomina phaseolina microsclerotia in root tissues of naturally colonized soybean cultivars was quantified. The density of free sclerotia on the soil was determined for plots of crop rotation (soybean-corn) and soybean monoculture soon after soybean harvest. M. phaseolina natural infection was also determined for the roots of weeds grown in the experimental area. To verify the ability of M. phaseolina to colonize dead substrates, senesced stem segments from the main plant species representing the agricultural system of southern Brazil were exposed on naturally infested soil for 30 and 60 days. To quantify the sclerotia, the methodology of Cloud and Rupe (1991) and Mengistu et al. (2007) was employed. Sclerotium density, assessed based on colony forming units (CFU), ranged from 156 to 1,108/g root tissue. Sclerotium longevity, also assessed according to CFU, was 157 days for the rotation and 163 days for the monoculture system. M. phaseolina did not colonize saprophytically any dead stem segment of Avena strigosa,Avena sativa,Hordeum vulgare,Brassica napus,Gossypium hirsutum,Secale cereale,Helianthus annus,Triticosecalerimpaui, and Triticum aestivum. Mp was isolated from infected root tissues of Amaranthus viridis,Bidens pilosa,Cardiospermum halicacabum,Euphorbia heterophylla,Ipomoea sp., and Richardia brasiliensis. The survival mechanisms of M. phaseolina studied in this paper met the microsclerotium longevity in soybean root tissues, free on the soil, as well as asymptomatic colonization of weeds.