We study the spatial correlations between halo neutrons in 6,8He within the complex-energy Gamow Shell Model (GSM). To this end, we calculate the neutron and proton radii, and two-neutron correlations in a large shell model space consisting of the 0p3/2 resonance and non-resonant p-sd scattering continuum. We use schematic forces and the finite-range Modified Minnesota interaction.The calculated charge radii, corrected for the core polarization and spin-orbit effects, are compared to the values extracted from measured atomic isotope shifts.We find that the charge radius of 6He primarily depends on the two-neutron separation energy and the shell-model occupation of the 0p3/2 orbit.We confirm that the ground-state GSM wave function of 6Heis dominated by the S=0 component representing a di-neutron structure. On the other hand, the correlation density of the 2+ resonance in 6He indicates a very weak di-neutron correlations in this state. We study the effect of pairing correlations on the neutron and charge radii of 6He and we confirm the presence of the Pairing-Anti-Halo effect in this light system.Finally, we calculate the charge radius of 8He in the full GSM space with the help of the Density Matrix Renormalization Group (DMRG) technique. The results of our realistic GSM+DMRG studies presented in this work show promise for extending the reach of the realistic complex-energy shell model to heavier halo systems.

This thesis investigates thermalisation, correlations and entanglement in Bose-Einstein condensates. Bose-Einstein condensates are ultra-cold collections of identical bosonic atoms which accumulate in a single quantum state, forming a mesoscopic quantum object. They are clean and controllable quantum many-body systems that permit an unprecedented degree of experimental flexibility compared to other physical systems. Further, a tractable microscopic theory exists which allows a direct and powerful comparison between theory and experiment, propelling the field of quantum atom optics forward at an incredible pace. Here we explore some of the fundamental frontiers of the field, examining how non-classical correlations and entanglement can be created and measured, as well as how non-classical effects can lead to the rapid heating of atom clouds. We first investigate correlations between two weakly coupled condensates, a system analogous to a superconducting Josephson junction. The ground state of this system contains non-classical number correlation arising from the repulsion between the atoms. Such states are of interest because they may lead to more precise measurement devices such as atomic gyroscopes. Unfortunately thermal fluctuations can destroy these correlations, and great care is needed to experimentally observe non-classical effects. We show that adiabatic evolution can drive the isolated quantum system out of thermal equilibrium and decrease thermal noise, in agreement with a recent experiment [Esteve et al. Nature 455, 1216 (2008)]. This technique may be valuable for observing and using quantum correlated states in the future. Next, we analyse the rapid heating that occurs when a condensate is placed in a moving periodic potential. The dynamical instability responsible for the heating was the subject of much uncertainty, which we suggest was due to the inability of the mean-field approximation to account for important spontaneous scattering processes. We show that a model including non-classical spontaneous scattering can describe dynamical instabilities correctly in each of the regimes where they have been observed, and in particular we compare our simulations to an experiment performed at the University of Otago deep inside the spontaneous scattering regime. Finally, we proposed a method to create and detect entangled atomic wave-packets. Entangled atoms are interesting from a fundamental perspective, and may prove useful in future quantum information and precision measurement technologies. Entanglement is generated by interactions, such as atomic collisions in Bose-Einstein condensates. We analyse the type of entanglement generated via atomic collisions and introduce an abstract scheme for detecting entanglement and demonstrating the Einstein-Podolsky-Rosen paradox with ultra-cold atoms. We further this result by proposing an experiment where entangled wave-packets are created and detected. The entanglement is generated by the pairwise scattering that causes the instabilities in moving periodic potentials mentioned above. By careful arrangement, the instability process can be controlled to to produce two well-defined atomic wave-packets. The presence of entanglement can be proven by applying a series of laser pulses to interfere the wave-packets and then measuring the output populations. Realising this experiment is feasible with current technology.

This thesis deals with electron correlation effects within low-dimensional, mesoscopic systems. We study phenomena within two different types of system in which correlations play an important role. The first involves the spectra and spin structure of small symmetric quantum dots, or &quoteartificial atoms&quote. The second is the &quote0.7 structure&quote, a well-known but mysterious anomalous conductance plateau which occurs in the conductance profile of a quantum point contact. Artificial atoms are manufactured mesoscopic devices: quantum dots which resemble real atoms in that their symmetry gives them a &quoteshell structure&quote. We examine two-dimensional circular artificial atoms numerically, using restricted and unrestricted Hartree-Fock simulation. We go beyond the mean-field approximation by direct calculation of second-order correlation terms; a method which works well for real atoms but to our knowledge has not been used before for quantum dots. We examine the spectra and spin structure of such dots and find, contrary to previous theoretical mean-field studies, that Hund's rule is not followed. We also find, in agreement with previous numerical studies, that the shell structure is fragile with respect to a simple elliptical deformation. The 0.7 structure appears in the conductance of a quantum point contact. The conductance through a ballistic quantum point contact is quantised in units of 2e^2/h. On the lowest conductance step, an anomalous narrow conductance plateau at about G = 0.7 x 2e^2/h is known to exist, which cannot be explained in the non-interacting picture. Based on suggestive numerical results, we model conductance through the lowest channel of a quantum point contact analytically. The model is based on the screening of the electron-electron interaction outside the QPC, and our observation that the wavefunctions at the Fermi level are peaked within the QPC. We use a kinetic equation approach, with perturbative account of electron-electron backscattering, to demonstrate that these simple features lead to the existence of a 0.7-like structure in the conductance. The behaviour of this structure reproduces experimentally observed features of the 0.7 structure, including the temperature dependence and the behaviour under applied in-plane magnetic fields.

This thesis investigates thermalisation, correlations and entanglement in Bose-Einstein condensates. Bose-Einstein condensates are ultra-cold collections of identical bosonic atoms which accumulate in a single quantum state, forming a mesoscopic quantum object. They are clean and controllable quantum many-body systems that permit an unprecedented degree of experimental flexibility compared to other physical systems. Further, a tractable microscopic theory exists which allows a direct and powerful comparison between theory and experiment, propelling the field of quantum atom optics forward at an incredible pace. Here we explore some of the fundamental frontiers of the field, examining how non-classical correlations and entanglement can be created and measured, as well as how non-classical effects can lead to the rapid heating of atom clouds. We first investigate correlations between two weakly coupled condensates, a system analogous to a superconducting Josephson junction. The ground state of this system contains non-classical number correlation arising from the repulsion between the atoms. Such states are of interest because they may lead to more precise measurement devices such as atomic gyroscopes. Unfortunately thermal fluctuations can destroy these correlations, and great care is needed to experimentally observe non-classical effects. We show that adiabatic evolution can drive the isolated quantum system out of thermal equilibrium and decrease thermal noise, in agreement with a recent experiment [Esteve et al. Nature 455, 1216 (2008)]. This technique may be valuable for observing and using quantum correlated states in the future. Next, we analyse the rapid heating that occurs when a condensate is placed in a moving periodic potential. The dynamical instability responsible for the heating was the subject of much uncertainty, which we suggest was due to the inability of the mean-field approximation to account for important spontaneous scattering processes. We show that a model including non-classical spontaneous scattering can describe dynamical instabilities correctly in each of the regimes where they have been observed, and in particular we compare our simulations to an experiment performed at the University of Otago deep inside the spontaneous scattering regime. Finally, we proposed a method to create and detect entangled atomic wave-packets. Entangled atoms are interesting from a fundamental perspective, and may prove useful in future quantum information and precision measurement technologies. Entanglement is generated by interactions, such as atomic collisions in Bose-Einstein condensates. We analyse the type of entanglement generated via atomic collisions and introduce an abstract scheme for detecting entanglement and demonstrating the Einstein-Podolsky-Rosen paradox with ultra-cold atoms. We further this result by proposing an experiment where entangled wave-packets are created and detected. The entanglement is generated by the pairwise scattering that causes the instabilities in moving periodic potentials mentioned above. By careful arrangement, the instability process can be controlled to to produce two well-defined atomic wave-packets. The presence of entanglement can be proven by applying a series of laser pulses to interfere the wave-packets and then measuring the output populations. Realising this experiment is feasible with current technology.

As well as the many benefits associated with the evolution of multispectral sensors into hyperspectral sensors there is also a considerable increase in storage space and the computational load to process the data. Consequently the remote sensing ommunity is investigating and developing statistical methods to alleviate these problems. / The research presented here investigates several approaches to reducing the dimensionality of hyperspectral remotely sensed data while maintaining the levels of accuracy achieved using the full dimensionality of the data. It was conducted with an emphasis on applications in maximum likelihood classification (MLC) of hyperspectral image data. An inherent characteristic of hyperspectral data is that adjacent bands are typically highly correlated and this results in a high level of redundancy in the data. The high correlations between adjacent bands can be exploited to realise significant reductions in the dimensionality of the data, for a negligible reduction in classification accuracy. / The high correlations between neighbouring bands is related to their response functions overlapping with each other by a large amount. The spectral band filter functions were modelled for the HyMap instrument that acquires hyperspectral data used in this study. The results were compared with measured filter function data from a similar, more recent HyMap instrument. The results indicated that on average HyMap spectral band filter functions exhibit overlaps with their neighbouring bands of approximately 60%. This is considerable and partly accounts for the high correlation between neighbouring spectral bands on hyperspectral instruments. / A hyperspectral HyMap image acquired over an agricultural region in the south west of Western Australia has been used for this research. The image is composed of 512 × 512 pixels, with each pixel having a spatial resolution of 3.5 m. The data was initially reduced from 128 spectral bands to 82 spectral bands by removing the highly overlapping spectral bands, those which exhibit high levels of noise and those bands located at strong atmospheric absorption wavelengths. The image was examined and found to contain 15 distinct spectral classes. Training data was selected for each of these classes and class spectral mean and covariance matrices were generated. / The discriminant function for MLC makes use of not only the measured pixel spectra but also the sample class covariance matrices. This thesis first examines reducing the parameterization of these covariance matrices for use by the MLC algorithm. The full dimensional spectra are still used for the classification but the number of parameters needed to describe the covariance information is significantly reduced. When a threshold of 0.04 was used in conjunction with the partial correlation matrices to identify low values in the inverse covariance matrices, the resulting classification accuracy was 96.42%. This was achieved using only 68% of the elements in the original covariance matrices. / Both wavelet techniques and cubic splines were investigated as a means of representing the measured pixel spectra with considerably fewer bands. Of the different mother wavelets used, it was found that the Daubechies-4 wavelet performed slightly better than the Haar and Daubechies-6 wavelets at generating accurate spectra with the least number of parameters. The wavelet techniques investigated produced more accurately modelled spectra compared with cubic splines with various knot selection approaches. A backward stepwise knot selection technique was identified to be more effective at approximating the spectra than using regularly spaced knots. A forward stepwise selection technique was investigated but was determined to be unsuited to this process. / All approaches were adapted to process an entire hyperspectral image and the subsequent images were classified using MLC. Wavelet approximation coefficients gave slightly better classification results than wavelet detail coefficients and the Haar wavelet proved to be a more superior wavelet for classification purposes. With 6 approximation coefficients, the Haar wavelet could be used to classify the data with an accuracy of 95.6%. For 11 approximation coefficients this figure increased to 96.1%. / First and second derivative spectra were also used in the classification of the image. The first and second derivatives were determined for each of the class spectral means and for each band the standard deviations were calculated of both the first and second derivatives. Bands were then ranked in order of decreasing standard deviation. Bands showing the highest standard deviations were identified and the derivatives were generated for the entire image at these wavelengths. The resulting first and second derivative images were then classified using MLC. Using 25 spectral bands classification accuracies of approximately 96% and 95% were achieved using the first and second derivative images respectively. These results are comparable with those from using wavelets although wavelets produced higher classification accuracies when fewer coefficients were used.

Thesis (M.S.)--Miami University, Dept. of Physics, 2009. / Title from first page of PDF document. Includes bibliographical references (p. Xx-Xx).

Thesis (M.G.S.)--Miami University, Dept. of Sociology and Gerontology, 2008. / Title from first page of PDF document. Includes bibliographical references (p. 44-47).

Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-10-16T11:30:38Z No. of bitstreams: 1 ENYEDJA KERLLY MARTINS DE ARAÚJO CARVALHO - TESE (PPGRN) 2018.pdf: 1578519 bytes, checksum: f04ba6184fedb18c9ab04049246487a8 (MD5) / Made available in DSpace on 2018-10-16T11:30:38Z (GMT). No. of bitstreams: 1 ENYEDJA KERLLY MARTINS DE ARAÚJO CARVALHO - TESE (PPGRN) 2018.pdf: 1578519 bytes, checksum: f04ba6184fedb18c9ab04049246487a8 (MD5) Previous issue date: 2018-02-27 / CNPq / As variáveis climáticas têm gerado preocupação crescente quanto aos potenciais efeitos à saúde humana, especialmente aqueles relacionados às doenças transmissíveis, pois constituem importante causa de morbimortalidade e afligem milhões de pessoas em diferentes regiões do mundo, especialmente em países subdesenvolvidos. Nesse sentido, a presente pesquisa tem por objetivo analisar a influencia das variáveis meteorológicas (precipitação, temperatura e umidade relativa do ar) e o número de casos acometidos de doenças respiratórias (asma e pneumonia) nos municípios de Campina Grande, PB e Patos, PB, no período de 1998 a 2016. Para tanto, foi realizado um estudo epidemiológico, retrospectivo e descritivo com abordagem quantitativa. Os dados das variáveis meteorológicas adotados nesta pesquisa foram obtidos nas estações meteorológicas do Estado da Paraíba, disponíveis no Instituto Nacional de Meteorologia (INMET). Os dados de internações hospitalares por asma e pneumonia foram obtidos no Sistema de Informações hospitalares (SIH/SUS), disponibilizados pelo Departamento de Informação do Sistema Único de Saúde (DATASUS). O tratamento estatístico utilizado foi composto pelas medidas de associação, correlação de Pearson (r) e pelo Coeficiente de Determinação (R²) para verificar a correlação entre os casos de asma e pneumonia com as variáveis meteorológicas (precipitação, temperatura e umidade do ar). As correlações obtidas constataram que os elementos climáticos interferem em boa medida para o aumento de internações dessas doenças, levando-se em consideração o aspecto da sazonalidade e os valores médios mensais da precipitação, temperatura e umidade do ar. Portanto, as maiores incidência de casos dessas internações hospitalares ocorreram entre os meses de abril a agosto, período em que ocorreram as menores temperaturas do ar e as maiores umidades relativas do ar. As principais contribuições configuram-se como fatores essenciais para compreender as consequências que as mudanças nas variáveis climáticas podem ocasionar na saúde da população dos municípios estudados. Como recomendação destaca-se a limitação do estudo que se relaciona às subnotificações das doenças, falta de oportunidade no registro, diagnósticos incorretos, dentre outros, que podem ocorrer junto às repartições responsáveis pelo fornecimento de informações de saúde. / Climatic variables generated increasing concern about the potential effects on human health, especially those related to communicable diseases, as they are an important cause of morbidity and mortality and afflict millions of people in different regions of the world, especially in underdeveloped countries. In this sense, the present research aims to analyze the influence of meteorological variables (precipitation, temperature and relative air humidity) and the number of cases of respiratory diseases (asthma and pneumonia) in the municipalities of Campina Grande, PB and Patos, PB , from 1998 to 2016. For that, a retrospective and descriptive epidemiological study was carried out with a quantitative approach. The data of the meteorological variables adopted in this research were obtained in the meteorological stations of the State of Paraíba, available at the National Institute of Meteorology (INMET). Data from hospital admissions for asthma and pneumonia were obtained from the Hospital Information System (SIH / SUS), made available by the Department of Information of the National Health System (DATASUS). The statistical treatment was composed of the association measures, Pearson Correlation (r) and the Coefficient of Determination (R²) to verify the correlation between the cases of asthma and pneumonia with the meteorological variables (precipitation, temperature and humidity of the air). The correlations obtained verified that the climatic elements interfere to a great extent for the increase of hospitalizations of these diseases, taking into account the aspect of the seasonality and the average monthly values of precipitation, temperature and humidity of the air. Therefore, the highest incidence of hospitalizations occurred between April and August, when the lowest air temperatures and the highest relative air humidity occurred. The main contributions are essential factors to understand the consequences that changes in climatic variables can cause in the health of the population of the studied municipalities. As a recommendation, we highlight the limitation of the study that relates to underreporting of diseases, lack of opportunity in the registry, incorrect diagnoses, among others, that may occur with the offices responsible for providing health information.

A host can adopt two strategies when facing infection: resistance, where host immune responses prevent or reduce pathogen replication; or tolerance, which refers to all mechanisms that reduce the impact of the infection on host health or performance. Both strategies may be under host genetic control, and could thus be targeted for genetic improvement. Although there is ample evidence of genetic variation in resistance to infection, there is limited evidence to suggest that individuals also differ genetically in tolerance. Furthermore, although resistance and tolerance are typically considered as alternative host defense mechanisms, relatively little is known about the genetic relationship between them and how they change together over time and jointly determine infection outcome. In this thesis, two datasets from experimental challenge infection experiments were considered for investigating tolerance genetics: Porcine Reproductive & Respiratory Syndrome (PRRS), an endemic viral disease which causes loss of growth and mortality in growing pigs; and Listeria monoctyogenes (Lm), a bacterium which causes food-borne infections in mammals. The two datasets differed substantially in size and genetic structure; the PRRS dataset consists of thousands of records from outbred commercial pig populations, whereas the Listeria dataset comprises much fewer records from genetically diverse highly inbred strains of a mice as a model species. The aims of this thesis were to: 1) Identify if genetic variation in host tolerance to infection exists, with case studies in PRRS and listeria, using conventional reaction-norm methodology; 2) Identify if host tolerance, along with resistance, changes longitudinally as infection progresses; 3) Identify whether the WUR genotype is associated with tolerance slope; 4) Analyse the dynamic relationship between host performance and pathogen load over the time-course of infection by examining the relationship at different stages of infection using GWAS; 5) Develop novel trajectory methodology to offer insight into health-infection dynamics, and identify whether there is genetic variation in trajectories; 6) Develop novel trajectory-derived phenotypes that analyse changes in host performance with respect to changes in pathogen load, as an alternative to tolerance, and identify whether genetic variation exists. This study found that conventional reaction-norm methodology is limited to capture genetic variation in tolerance in outbred populations without measures of performance in the absence of infection. However, by utilising repeated longitudinal data on the same dataset, stages of infection (early, mid and late) were defined for each individual, based on host pathogen load. Using these stages of infection, genetic variation in tolerance was identified over all stages of infection and at mid to late stage of infection. Genetic correlation between resistance and tolerance was strong and positive over all stages of infection, and evidence suggested that resistance and tolerance may be under pleiotropic control. Furthermore, this research found that genetic correlations between resistance and growth changed considerably over time, and that individuals who expressed high genetic resistance early in infection tended to grow slower during that time-period, but were more likely to clear the virus by late stage, and thus recover in growth. However, at mid-late stage of infection, those with high virus load also had high growth, indicating potential epidemiological problems with genetic selection of host resilience to infection. Furthermore, genome wide association studies for pathogen load and growth associated with different stages of infection did not identify novel genetic loci associated with these traits than those previously reported for the whole infection period. By adopting conventional methodology, this study found genetic variation in tolerance of genetically diverse mouse strains to Lm and pigs to PRRS, despite statistical problems. The relationship between resistance and tolerance indicated that both traits should be considered in genetic selection programs. By adopting novel trajectory analysis, this study demonstrated that level of expression of resistance and tolerance changed throughout the experimental infection period and, furthermore, that expression of resistance, followed by tolerance, determined survival of infection. Survivors and non-survivors followed different infection trajectories, which were partially determined by genetics. By deriving novel phenotypes from trajectories that explained changes in growth in relation to change in pathogen load at specific time points, and applying these to the PRRS data, this study did not identify genetic variation in these phenotypes. The genetic signal in these phenotypes may have been masked by the fact that individuals were likely at different stages of infection. In summary, this study has shown that genetic improvement of tolerance, in addition to resistance may be desirable, but could be difficult to achieve in practice due to shortcomings in obtaining accurate and unbiased tolerance estimates based on conventional reaction-norms. Infection trajectories have proven to be a promising tool for achieving an optimally timed balance between resistance and tolerance, but further work is needed to incorporate them in genetic improvement programs.

The relationship between linear type traits and productional, longevity traits were analysed for 645 cows first calved between 2000-2016. The aim of study was to evaluate realionships of individual 20 type traits and 4 general conformation characteristics. For analysed herd was evaluated impact of individual type traits to first lactation milk yield in kg, lifetime milk yield in kg and functional longevity in days. Results proved important relations between folowing linear type traits and first lactation milk yield in kg: rump lenght, rump width, body depth, muscularity, pastern, fore udder lenght, rear udder attachment, central ligament, udder depth and front teat placement. Statisticly important relationships were found between all general conformation characteristics and first lactation milk yield. Proved impact between individual linear type traits and lifetime milk yield were found for rump angle, hock and front teat placement. Relationships between general conformation characteristics and lifetime milk yield were not statisticly proved. For analysed herd were also found important relations between rump angle and hock to functional longevity. Important relationships between general conformation characteristics and functional longevity were not found. In overall 192 cows were culled in analysed herd in 2016. The most frequent reason of culling a cow out of breed was caused by fertility disorders which participated in overall culling reasons in 34,9 %.