For over a decade studies of the strong interaction in extremely dense nuclear environments have been done at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory. It is hypothesized that colliding two beams of Au nuclei at relativistic speeds creates an environment of hot dense nuclear matter where the quarks and gluons inside the nucleus, which are normally confined within the protons and neutrons, become deconfined into a soup called the quark-gluon plasma. Since direct observation of this short-lived phase is impossible, many sophisticated analysis techniques attempt to study the early interactions via the final state particles. What has emerged from analyses of the data are two, contradictory paradigms for understanding the results. On the one hand the colliding quarks and gluons are thought to strongly interact and reach thermal equilibrium. The other view is that primary parton-parton scattering leads directly to jet fragmentation with little effect from re-scattering. It is in principle possible to distinguish and perhaps falsify one or both of these models of relativistic heavy ion collisions via the analysis of two-particle correlations among all charged particles produced in [mathematical symbols] = 200 GeV Au+Au collisions at the STAR experiment at RHIC. This dissertation presents studies of two-particle correlations, whose derivation can be traced back to Pearson's correlation coefficient, in transverse momentum and angular space. In momentum space a broad peak is observed extending from 0.5-4.0 GeV/c which, as a function of nuclear overlap, remains at a fixed position while monotonically increasing in amplitude. Comparisons to theoretical models suggests this peak is from jet fragmentation. In a complementary study the momentum distribution of correlations in ([eta],[phi]) space is investigated. The momentum distribution of correlated pairs that contribute to the peak near the origin, commonly associated with jet fragmentation, is peaked around 1.5 GeV/c and does not soften with increased centrality. These measurements present important aspects of the available six dimensional correlation space and provide definitive tests for theoretical models. Preliminary findings do not appear to support the hypothesis of a strongly interacting QGP where back-to-back jets are expected to be significantly suppressed. / text

Looking at newspapers nowadays, you are likely to see reports about public projects which turn out to be more expensive than estimated, sometimes even fourteen times the planned cost budget as in the case of the Sydney Opera. In order to gain a new insight on how this problematic could be improved, this paper aims to find correlations between the causes of deviations in public procurement and in the private market. Data from a on a global scale operating firm has been analyzed and compared to causes found in prior research. The questions this paper aims to answer are “Are causes and correlations found in smaller, private projects consistent with causes of cost overruns in public procurement?” and “Which implications and recommendations can be derived from the smaller dimension for the larger dimension of public procurement?”   After introducing the theoretical framework and its theories, the individual cost deviations and correlations of the different segments are introduced and analysed. As a result, one can see how the rational behaviour model and asymmetric information influence the estimated cost and that, in order to decrease the problematic of cost overruns, estimation techniques and especially the way contracts are constructed have to be improved. Furthermore, positive correlations between the size of cost deviations and number of employees, possible chain of events and pay offs between

Upland cotton (Gossypium hirsutum) is cultivated in many contrasting production environments and is often subjected to a combination of abiotic stresses such as high temperature (heat) and water deficit (drought) stress. In the present dissertation, two recombinant inbred line populations were constructed from heat-tolerant and -susceptible parental lines and evaluated in multiple environments under the presence of two treatments, well-watered (heat stress) and water-limited in the presence of high temperature (combination of heat and drought stresses). We assessed two agronomic traits, seed cotton yield and lint yield, as well as six fiber traits, lint percent, micronaire, length, strength, uniformity, and elongation. Fiber traits had moderate to very high broad-sense heritabilities, while heritabilities of agronomic traits were lower for both populations in each irrigation regime. Correlations between traits were not effected by the irrigation regimes. A stability analysis across the range of environments tested demonstrated that high seed cotton yield performance and greater stability may play a role in tolerance to the combination of heat and drought stresses. Additionally, we constructed linkage maps for both recombinant inbred line populations and mapped QTL controlling variation all eight traits. A total of 138 QTL were identified across populations for the eight traits. Climate change in the form of rising temperatures and reduced water availability will increase the occurrence of the combination of heat and drought stresses in a farmer's field. Thus, current cotton breeding programs will need to focus on the development of cotton varieties tolerant to heat, drought, and the combination of the two.

A growing concern among investors for social responsibility in relation to the business world and its effect on the environment, society, and government has increased and therefore different types of stock indices and funds that incorporate socially responsible ideals have been developed. However, a literature review revealed that there does not seem to be much information about the volatility of Green Funds or Socially Responsible Investments (SRI). Volatility is an important part of understanding the financial markets and is used by many to understand asset allocation, risk management, option pricing and many other functions. Therefore, the purpose of this thesis is to investigate the volatility performance of SRIs, REFs and Conventional Indices by using different models CAPM, SR, JA and EGARCH, and monthly and daily data from the US, UK, Japan and Eurozone financial markets to compare results.   This thesis has been conducted by following an objective ontological and positivist epistemological position, because the data used for analysis in this thesis is independent from the author and has studied what actually exists, not what the author seeks to interpret. The research approach is functionalist, because this thesis sought to explain how the investments function in relation to volatility comparisons in different financial markets and if this volatility can be predicted through a framework of rules designed by previous researchers. The design is a deductive study of quantitative, longitudinal, secondary data, because hypotheses are derived from theory to test the volatility of time series data between the year 2007 and 2012 through empirical evidence.   Statistical evidence was found to suggest that the EGARCH model for volatility measurement is the best fit to model volatility and daily data can give more information and better consistency between results. SRIs were found to be less volatile than CIs in all financial markets; REFs were found more volatile than CIs in the US and Eurozone markets but not in the UK and Japan markets; REFs were found to be more volatile than SRIs in all markets except the UK; REFs were also found to be more volatile than SRIs and CIs during a recession in all markets except the UK. Evidence also indicated that the correlations between REFs and SRIs in the US and Eurozone were significant, but not significant in the UK and Japan market samples. The correlations were low between the UK and Japan SRIs, Japan and Eurozone SRIs and Japan SRI and Eurozone REF, which suggest that an investor may consider to diversify between these investments. However, all other statistically significant correlations between financial markets were high and could consequentially deliver poor long term investment performance.

This thesis focuses on the interplay of the spin-orbit coupling, the electronic correlations and the bandwidth energy scales, along with the lattice distortions seen in perovskite iridates. In particular, we study the magnetic phases in these materials and the insulator to metal transition that occurs as the dimensionality of the system is changed. Motivated by the novel magnetic phases seen in the Sr2IrO4 system, we study the band structures of three materials in the Sr(n+1)Ir(n)O(3n+1) Ruddlesden-Popper series by use of a tight-binding model. From the effect of spin-orbit coupling, we see that the relevant bands near the Fermi energy are indeed made of effective J=1/2 states. This spin-orbit separation of the bands creates effectively smaller bandwidth which can then be split via magnetic ordering driven by electronic correlations. By the use of a self-consistent mean-field theory, we derive the ordering for each of the three materials studied and show that the nature of the magnetic ordering is highly dependent on the lattice structure. The ordering in the bilayer Sr3Ir2O7, which has been a topic of debate in recent experimental studies, is understood within the current approach to be a collinear antiferromagnetic order, in agreement with the latest results. Given that the iridate systems have large spin-orbit coupling, and that the topic of topological insulators has become a very popular subject of research, we discuss the proximity of the perovskite iridates to topological insulators. Since the SrIrO3 material displays a semimetal structure with nodal dispersion near the Fermi level, we looked at an extra term in the Hamiltonian that could lift the nodal lines and turn the system into an insulator. Further studies of the parity eigenvalues of the bands at each time reversal invariant momentum point confirms that for a range of this extra term, a topological phase can be achieved. A discussion on material realization of such a phase is also given where we suggest that a Sr2IrRhO6 superstructure might be a good candidate to achieve this state.

This thesis focuses on the interplay of the spin-orbit coupling, the electronic correlations and the bandwidth energy scales, along with the lattice distortions seen in perovskite iridates. In particular, we study the magnetic phases in these materials and the insulator to metal transition that occurs as the dimensionality of the system is changed. Motivated by the novel magnetic phases seen in the Sr2IrO4 system, we study the band structures of three materials in the Sr(n+1)Ir(n)O(3n+1) Ruddlesden-Popper series by use of a tight-binding model. From the effect of spin-orbit coupling, we see that the relevant bands near the Fermi energy are indeed made of effective J=1/2 states. This spin-orbit separation of the bands creates effectively smaller bandwidth which can then be split via magnetic ordering driven by electronic correlations. By the use of a self-consistent mean-field theory, we derive the ordering for each of the three materials studied and show that the nature of the magnetic ordering is highly dependent on the lattice structure. The ordering in the bilayer Sr3Ir2O7, which has been a topic of debate in recent experimental studies, is understood within the current approach to be a collinear antiferromagnetic order, in agreement with the latest results. Given that the iridate systems have large spin-orbit coupling, and that the topic of topological insulators has become a very popular subject of research, we discuss the proximity of the perovskite iridates to topological insulators. Since the SrIrO3 material displays a semimetal structure with nodal dispersion near the Fermi level, we looked at an extra term in the Hamiltonian that could lift the nodal lines and turn the system into an insulator. Further studies of the parity eigenvalues of the bands at each time reversal invariant momentum point confirms that for a range of this extra term, a topological phase can be achieved. A discussion on material realization of such a phase is also given where we suggest that a Sr2IrRhO6 superstructure might be a good candidate to achieve this state.

Box and Jenkins methodologies have massively contributed to the analysis of time series data. However, the assumptions used in these methods impose constraints on the type of the data. As a result, difficulties arise when we apply those tools to a more generalized type of data (e.g. count, categorical or integer-valued data) rather than the classical continuous or more specifically Gaussian type. Papers in the literature proposed alternate methods to model discrete-valued time series data, among these methods is Pegram's operator (1980). We use this operator to build an AR(p) model for integer-valued time series (including both positive and negative integers). The innovations follow the differenced Poisson distribution, or Skellam distribution. While the model includes the usual AR(p) correlation structure, it can be made more general. In fact, the operator can be extended in a way where it is possible to have components which contribute to positive correlation, while at the same time have components which contribute to negative correlation. As an illustration, the process is used to model the change in a stock’s price, where three variations are presented: Variation I, Variation II and Variation III. The first model disregards outliers; however, the second and third include large price changes associated with the effect of large volume trades and market openings. Parameters of the model are estimated using Maximum Likelihood methods. We use several model selection criteria to select the best order for each variation of the model as well as to determine which is the best variation of the model. The most adequate order for all the variations of the model is $AR(3)$. While the best fit for the data is Variation II, residuals' diagnostic plots suggest that Variation III represents a better correlation structure for the model.

Thesis (Ph. D.)--Kent State University, 2007. / Title from PDF t.p. (viewed July 15, 2008). Advisor: John W. Watson. Includes bibliographical references (p. 125-129).

Η εργασία αποτελεί αντικείμενο ενασχόλησης της οικονομικής θεωρίας, της διοίκησης επιχειρήσεων και της κοινωνιολογίας. Η θεωρία της απασχόλησης, ο καταμερισμός της εργασίας, η εργασία σαν αξία και η ικανοποίηση από την εργασία αποτελούν μερικές πτυχές στον προβληματισμό των παραπάνω επιστημονικών περιοχών. Με τη βοήθεια ερωτηματολογίων και του στατιστικού πακέτου spss αναλύεται η προτίμηση που έχουν εργαζόμενοι από διάφορους κλάδους ανάλογα με το χρόνο απασχόλησης. Αρχικά, αναφέρονται μερικά στατιστικά μέτρα που αναλύονται παρακάτω και περιγράφεται η μέθοδος με την οποία γίνεται η ανάλυση του ερωτηματολογίου και οι συσχετίσεις ανάμεσα στις μεταβλητές. Οι κύριες μέθοδοι που χρησιμοποιούνται είναι ο χι – τετράγωνο έλεγχος και ο συντελεστής συσχέτισης Gamma. Έπειτα, γίνεται ανάλυση του δείγματος παρουσιάζοντας στατιστικούς πίνακες, ραβδογράμματα, διαγράμματα και κυκλικά διαγράμματα που έχουν προκύψει από το spss. Επιπροσθέτως, γίνεται η ανάλυση των συσχετίσεων ανάμεσα στις μεταβλητές και παρουσιάζονται οι πιο ισχυρές συσχετίσεις. Βέβαια, σε κάθε επάγγελμα υπάρχουν επιπλέον ερωτήσεις οι οποίες παρουσιάζονται ξεχωριστά από τις κύριες μεταβλητές που είναι κοινές σε όλο το δείγμα. Τέλος, εξάγονται τα συμπεράσματα από την ανάλυση του δείγματος και στο παράρτημα παρουσιάζεται το ερωτηματολόγιο με όλες τις ερωτήσεις. / The work adds up to the subject of foray among economic theory, business administration and social science. The theory of working time, the division of labor, the work as value and the desire of working described analytically. Using questionnaire and the statistical SPSS elaborated the preference have workers from any department about working time. In the first place, we refer some statistical measures and described the method with which assayed the questionnaires and correlations among variables. The main methods that used are chi – square tests and correlation coefficient Gamma. Consequently, displayed the results by statistical tables, bar graphs and pie charts. Later, we refer the stronger correlations. In addition, we display some extra questions that haw any occupation.

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