A framework for identification of similarities between multiple algorithms

This thesis in software engineering presents a novel automated framework to identify similar operations utilized by multiple algorithms for solving related computing problems. It provides a new effective solution to perform multi-application based algorithm analysis, employing fundamentally light-weight static analysis techniques compared to the state-of-art approaches. Significant performance improvements are achieved across the objective algorithms through enhancing the efficiency of the identified similar operations, targeting discrete application domains.

Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies

Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

The case for unitary taxation with formulary apportionment in the finance sector and the effect on developing nations

In 2013 the OECD released its 15 point Action plan to deal with base erosion and profit shifting (BEPS). In that plan it was recognised that BEPS has a significant effect on developing countries. This is because the lack of tax revenue can lead to a critical underfunding of public investment that would help promote economic growth. To this end, the BEPS project is aimed at ensuring an inclusive approach to take into account not only views of the G20 and OECD countries but also the perspective of developing nations. With this focus in mind and in the context of developing nations, the purpose of this article is to consider a possible solution to profit shifting which occurs under the current transfer pricing regime, with that solution being unitary taxation with formulary apportionment. It does so using the finance sector as a specific case for application. Multinational financial institutions (MNFIs) play a significant role in financing activities of their clients in developing nations. Consistent with the ‘follow-the-client’ phenomenon which explains financial institution expansion, these entities are increasingly profiting from activities associated with this growing market. Further, not only are MNFIs persistent users of tax havens but also, more than other industries, have opportunities to reduce tax through transfer pricing measures. This article establishes a case for an industry specific adoption of unitary taxation with formulary apportionment as a viable alternative to the current regime. It argues that such a model would benefit not only developed nations but also developing nations which are currently suffering the effects of BEPS. In doing so, it considers the practicalities of such an implementation by examining both definitional issues and a possible formula for MNFIs. This article argues that, while there would be implementation difficulties to overcome, the current domestic models of formulary apportionment provide important guidance as to how the unitary business and business activities of MNFIs should be defined as well as factors that should be included in an allocation formula, along with the appropriate weighting. While it would be difficult for developing nations to adopt such a regime, it is argued that it would be no more difficult than addressing issues they face with the current transfer pricing regime. As such, this article concludes that unitary taxation with formulary apportionment is a viable industry specific alternative for MNFIs which would assist developing nations and aid independent fiscal soundness.

Unitary Taxation of the Finance Sector

Multinational financial institutions (MNFIs) play a significant role in financing the activities of their clients in developing nations. Consistent with the ‘follow-the-customer’ phenomenon which explains financial institution expansion, these entities are increasingly profiting from activities associated with this growing market. However, not only are MNFIs persistent users of tax havens, but also, more than other industries, have the opportunity to reduce tax through transfer pricing measures. This paper establishes a case for an industry-specific adoption of unitary taxation with formulary apportionment as a viable alternative to the current regime. In doing so, it considers the practicalities of implementing this by examining both definitional issues and possible formulas for MNFIs. This paper argues that, while there would be implementation difficulties to overcome, the current domestic models of formulary apportionment provide important guidance as to how the unitary business and business activities of MNFIs should be defined, as well as the factors that should be included in an allocation formula, and the appropriate weighting. This paper concludes that unitary taxation with formulary apportionment is a viable industry-specific alternative for MNFIs.

Comparison of sustainable community rating tools in Australia

The community is the basic unit of urban development, and appropriate assessment tools are needed for communities to evaluate and facilitate decision making concerning sustainable community development and reduce the detrimental effects of urban community actions on the environment. Existing research into sustainable community rating tools focuses primarily on those that are internationally recognized to describe their advantages and future challenges. However, the differences between rating tools due to different regional conditions, situations and characteristics have yet to be addressed. In doing this, this paper examines three sustainable community rating tools in Australia, namely Green Star-Communities PILOT, EnviroDevelopment and VicUrban Sustainability Charter (Master Planned Community Assessment Tool). In order to identify their similarities, differences and advantages these are compared in terms of sustainability coverage, prerequisites, adaptation to locality, scoring and weighting, participation, presentation of results, and application process. These results provide the stakeholders of sustainable community development projects with a better understanding of the available rating tools in Australia and assist with evaluation and decision making.

Generalizing the use of geographical weights in biodiversity modelling

Aim Determining how ecological processes vary across space is a major focus in ecology. Current methods that investigate such effects remain constrained by important limiting assumptions. Here we provide an extension to geographically weighted regression in which local regression and spatial weighting are used in combination. This method can be used to investigate non-stationarity and spatial-scale effects using any regression technique that can accommodate uneven weighting of observations, including machine learning. Innovation We extend the use of spatial weights to generalized linear models and boosted regression trees by using simulated data for which the results are known, and compare these local approaches with existing alternatives such as geographically weighted regression (GWR). The spatial weighting procedure (1) explained up to 80% deviance in simulated species richness, (2) optimized the normal distribution of model residuals when applied to generalized linear models versus GWR, and (3) detected nonlinear relationships and interactions between response variables and their predictors when applied to boosted regression trees. Predictor ranking changed with spatial scale, highlighting the scales at which different species–environment relationships need to be considered. Main conclusions GWR is useful for investigating spatially varying species–environment relationships. However, the use of local weights implemented in alternative modelling techniques can help detect nonlinear relationships and high-order interactions that were previously unassessed. Therefore, this method not only informs us how location and scale influence our perception of patterns and processes, it also offers a way to deal with different ecological interpretations that can emerge as different areas of spatial influence are considered during model fitting.

Experimental and theoretical characterization of 5,10- diminoporphodimethenes: Dearomatized porphyrinoids from palladium-catalyzed hydrazinations of 5,10-diarylporphyrins

A new dearomatized porphyrinoid, 5,10-diiminoporphodimethene (5,10-DIPD), has been prepared by palladium-catalyzed hydrazination of 5,10-dibromo-15,20-bis(3,5-di-tert-butylphenyl)porphyrin and its nickel(II) complex, by using ethyl and 4-methoxybenzyl carbazates. The oxidative dearomatization of the porphyrin ring occurs in high yield. Further oxidation with 2,3-dichloro-5,6-dicyanobenzoquinone forms the corresponding 5,10-bis(azocarboxylates), thereby restoring the porphyrin aromaticity. The UV/visible spectra of the NiII DIPDs exhibit remarkable redshifts of the lowest-energy bands to 780 nm, and differential pulse voltammetry reveals a contracted electrochemical HOMO–LUMO gap of 1.44 V. Density functional theory (DFT) was used to calculate the optimized geometries and frontier molecular orbitals of model 5,10-DIPD Ni7c and 5,10-bis(azocarboxylate) Ni8c. The conformations of the carbamate groups and the configurations of the CNZ unit were considered in conjunction with the NOESY spectra, to generate the global minimum geometry and two other structures with slightly higher energies. In the absence of solution data regarding conformations, ten possible local minimum conformations were considered for Ni8c. Partition of the porphyrin macrocycle into tri- and monopyrrole fragments in Ni7c and the inclusion of terminal conjugating functional groups generate unique frontier molecular orbital distributions and a HOMO–LUMO transition with a strong element of charge transfer from the monopyrrole ring. Time-dependent DFT calculations were performed for the three lowest-energy structures of Ni7c and Ni8c, and weighting according to their energies allowed the prediction of the electronic spectra. The calculations reproduce the lower-energy regions of the spectra and the overall forms of the spectra with high accuracy, but agreement is not as good in the Soret region below 450 nm.

Questionnaire design for airport passenger experience survey

Assessing airport service performance requires understanding of a complete set of passenger experiences covering all activities from departures to arrivals. Weight-based indicator models allow passengers to express their priority on certain evaluation criteria (airport domains) and their service attributes over the others. The application of multilevel regression analysis in questionnaire design is expected to overcome limitations of traditional questionnaires, which require application of all indicators with equal weight. The development of a Taxonomy of Passenger Activities (TOPA), which captures all passenger processing and discretionary activities, has provided a novel perspective in understanding passenger experience in various airport domains. Based on further literature reviews on various service attributes at airport passenger terminals, this paper constitutes questionnaire design to employ a weighting method for all activities from the time passengers enter an airport domain at the departure terminal until leaving the arrival terminal (i.e. seven airport domains for departure, four airport domains during transit, and seven airport domains for arrival). The procedure of multilevel regression analysis is aimed not only at identifying the ranking of each evaluation criterion from the most important to the least important but also to explain the relationship between service attributes in each airport domain and overall service performance.

Weighted rank regression for clustered data analysis

We consider ranked-based regression models for clustered data analysis. A weighted Wilcoxon rank method is proposed to take account of within-cluster correlations and varying cluster sizes. The asymptotic normality of the resulting estimators is established. A method to estimate covariance of the estimators is also given, which can bypass estimation of the density function. Simulation studies are carried out to compare different estimators for a number of scenarios on the correlation structure, presence/absence of outliers and different correlation values. The proposed methods appear to perform well, in particular, the one incorporating the correlation in the weighting achieves the highest efficiency and robustness against misspecification of correlation structure and outliers. A real example is provided for illustration.

Induced smoothing for rank regression with censored survival times

Adaptions of weighted rank regression to the accelerated failure time model for censored survival data have been successful in yielding asymptotically normal estimates and flexible weighting schemes to increase statistical efficiencies. However, for only one simple weighting scheme, Gehan or Wilcoxon weights, are estimating equations guaranteed to be monotone in parameter components, and even in this case are step functions, requiring the equivalent of linear programming for computation. The lack of smoothness makes standard error or covariance matrix estimation even more difficult. An induced smoothing technique overcame these difficulties in various problems involving monotone but pure jump estimating equations, including conventional rank regression. The present paper applies induced smoothing to the Gehan-Wilcoxon weighted rank regression for the accelerated failure time model, for the more difficult case of survival time data subject to censoring, where the inapplicability of permutation arguments necessitates a new method of estimating null variance of estimating functions. Smooth monotone parameter estimation and rapid, reliable standard error or covariance matrix estimation is obtained.

Estimating equations with nonignorably missing response data

Troxel, Lipsitz, and Brennan (1997, Biometrics 53, 857-869) considered parameter estimation from survey data with nonignorable nonresponse and proposed weighted estimating equations to remove the biases in the complete-case analysis that ignores missing observations. This paper suggests two alternative modifications for unbiased estimation of regression parameters when a binary outcome is potentially observed at successive time points. The weighting approach of Robins, Rotnitzky, and Zhao (1995, Journal of the American Statistical Association 90, 106-121) is also modified to obtain unbiased estimating functions. The suggested estimating functions are unbiased only when the missingness probability is correctly specified, and misspecification of the missingness model will result in biases in the estimates. Simulation studies are carried out to assess the performance of different methods when the covariate is binary or normal. For the simulation models used, the relative efficiency of the two new methods to the weighting methods is about 3.0 for the slope parameter and about 2.0 for the intercept parameter when the covariate is continuous and the missingness probability is correctly specified. All methods produce substantial biases in the estimates when the missingness model is misspecified or underspecified. Analysis of data from a medical survey illustrates the use and possible differences of these estimating functions.

Evaluating the risk of mixtures in the indoor air of primary school classrooms

In school environments, children are constantly exposed to mixtures of airborne substances, derived from a variety of sources, both in the classroom and in the school surroundings. It is important to evaluate the hazardous properties of these mixtures, in order to conduct risk assessments of their impact on chil¬dren’s health. Within this context, through the application of a Maximum Cumulative Ratio approach, this study aimed to explore whether health risks due to indoor air mixtures are driven by a single substance or are due to cumulative exposure to various substances. This methodology requires knowledge of the concentration of substances in the air mixture, together with a health related weighting factor (i.e. reference concentration or lowest concentration of interest), which is necessary to calculate the Hazard Index. Maximum cumulative ratio and Hazard Index values were then used to categorise the mixtures into four groups, based on their hazard potential and therefore, appropriate risk management strategies. Air samples were collected from classrooms in 25 primary schools in Brisbane, Australia. Analysis was conducted based on the measured concentration of these substances in about 300 air samples. The results showed that in 92% of the schools, indoor air mixtures belonged to the ‘low concern’ group and therefore, they did not require any further assessment. In the remaining schools, toxicity was mainly governed by a single substance, with a very small number of schools having a multiple substance mix which required a combined risk assessment. The proposed approach enables the identification of such schools and thus, aides in the efficient health risk management of pollution emissions and air quality in the school environment.

Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data

This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

Options for selecting dairy cattle for milk coagulation ability

Lypsylehmien maidon juoksettumiskyvyn jalostuskeinot Väitöskirjassa tutkittiin lypsylehmien maidon juustonvalmistuslaadun parantamista jalostusvalinnan avulla. Tutkimusaihe on tärkeä, sillä yhä suurempi osa maidosta käytetään juustonvalmistukseen. Tutkimuksen kohteena oli maidon juoksettumiskyky, sillä se on yksi keskeisistä juustomäärään vaikuttavista tekijöistä. Maidon juoksettumiskyky vaihteli huomattavasti lehmien, sonnien, karjojen, rotujen ja lypsykauden vaiheiden välillä. Vaikka tankkimaidon juoksettumiskyvyssä olikin suuria eroja karjoittain, karja selitti vain pienen osan juoksettumiskyvyn kokonaisvaihtelusta. Todennäköisesti perinnölliset erot lehmien välillä selittävät suurimman osan karjojen tankkimaitojen juoksettumiskyvyssä havaituista eroista. Hyvä hoito ja ruokinta vähensivät kuitenkin jossain määrin huonosti juoksettuvien tankkimaitojen osuutta karjoissa. Holstein-friisiläiset lehmät olivat juoksettumiskyvyltään ayrshire-rotuisia lehmiä parempia. Huono juoksettuminen ja juoksettumattomuus oli vain vähäinen ongelma holstein-friisiläisillä (10 %), kun taas kolmannes ayrshire-lehmistä tuotti huonosti juoksettuvaa tai juoksettumatonta maitoa. Maitoa sanotaan huonosti juoksettuvaksi silloin, kun juustomassa ei ole riittävän kiinteää leikattavaksi puolen tunnin kuluttua juoksetteen lisäyksestä. Juoksettumattomaksi määriteltävä maito ei saostu lainkaan puolen tunnin aikana ja on siksi erittäin huonoa raaka-ainetta juustomeijereille. Noin 40 % lehmien välisistä eroista maidon juoksettumiskyvyssä selittyi perinnöllisillä tekijöillä. Juoksettumiskykyä voikin sanoa hyvin periytyväksi ominaisuudeksi. Kolme mittauskertaa lehmää kohti riittää varsin hyvin lehmän maidon keskimääräisen juoksettumiskyvyn arvioimiseen. Tällä hetkellä juoksettumiskyvyn suoran jalostamisen ongelmana on kuitenkin automatisoidun, laajamittaiseen käyttöön soveltuvan mittalaitteen puute. Tämän takia väitöskirjassa tutkittiin mahdollisuuksia jalostaa maidon juoksettumiskykyä epäsuorasti, jonkin toisen ominaisuuden kautta. Tällaisen ominaisuuden pitää olla kyllin voimakkaasti perinnöllisesti kytkeytynyt juoksettumiskykyyn, jotta jalostus olisi mahdollista sen avulla. Tutkittavat ominaisuudet olivat sonnien kokonaisjalostusarvossa jo mukana olevat maitotuotos ja utareterveyteen liittyvät ominaisuudet sekä kokonaisjalostusarvoon kuulumattomat maidon valkuais- ja kaseiinipitoisuus sekä maidon pH. Väitöskirjassa tutkittiin myös mahdollisuuksia ns. merkkiavusteiseen valintaan tutkimalla maidon juoksettumattomuuden perinnöllisyyttä ja kartoittamalla siihen liittyvät kromosomialueet. Tutkimuksen tulosten perusteella lehmien utareterveyden jalostaminen parantaa jonkin verran myös maidon juoksettumiskykyä sekä vähentää juoksettumattomuutta ayrshire-rotuisilla lehmillä. Lehmien maitotuotos ja maidon juoksettumiskyky sekä juoksettumattomuus ovat sen sijaan perinnöllisesti toisistaan riippumattomia ominaisuuksia. Myöskin maidon valkuais- ja kaseiinipitoisuuden perinnöllinen yhteys juoksettumiskykyyn oli likimain nolla. Maidon pH:n ja juoksettumiskyvyn välillä oli melko voimakas perinnöllinen yhteys, joten maidon pH:n jalostaminen parantaisi myös maidon juoksettumiskykyä. Todennäköisesti sen jalostaminen ei kuitenkaan vähentäisi juoksettumatonta maitoa tuottavien lehmien määrää. Koska maidon juoksettumattomuus on niin yleinen ongelma suomalaisilla ayrshire-lehmillä, väitöksessä selvitettiin tarkemmin ilmiön taustoja. Kaikissa kolmessa tutkimusaineistoissa noin 10 % ayrshire-lehmistä tuotti juoksettumatonta maitoa. Kahden vuoden kuukausittaisen seurannan aikana osa lehmistä tuotti juoksettumatonta maitoa lähes joka mittauskerralla. Maidon juoksettumattomuus oli yhteydessä lypsykauden vaiheeseen, mutta mikään ympäristötekijöistä ei pystynyt täysin selittämään sitä. Sen sijaan viitteet sen periytyvyydestä vahvistuivat tutkimusten edetessä. Lopuksi tutkimusryhmä onnistui kartoittamaan juoksettumattomuutta aiheuttavat kromosomialueet kromosomeihin 2 ja 18, lähelle DNA-merkkejä BMS1126 ja BMS1355. Tulosten perusteella maidon juoksettumattomuus ei ole yhteydessä maidon juoksettumistapahtumassa keskeisiin kaseiinigeeneihin. Sen sijaan on mahdollista, että juoksettumattomuusongelman aiheuttavat kaseiinigeenien syntetisoinnin jälkeisessä muokkauksessa tapahtuvat virheet. Asia vaatii kuitenkin perusteellista tutkimista. Väitöksen tulosten perusteella maidon juoksettumattomuusgeeniä kantavien eläinten karsiminen jalostuseläinten joukosta olisi tehokkain tapa jalostaa maidon juoksettumiskykyä suomalaisessa lypsykarjapopulaatiossa.

Computational Techniques for Haplotype Inference and for Local Alignment Significance

This thesis which consists of an introduction and four peer-reviewed original publications studies the problems of haplotype inference (haplotyping) and local alignment significance. The problems studied here belong to the broad area of bioinformatics and computational biology. The presented solutions are computationally fast and accurate, which makes them practical in high-throughput sequence data analysis. Haplotype inference is a computational problem where the goal is to estimate haplotypes from a sample of genotypes as accurately as possible. This problem is important as the direct measurement of haplotypes is difficult, whereas the genotypes are easier to quantify. Haplotypes are the key-players when studying for example the genetic causes of diseases. In this thesis, three methods are presented for the haplotype inference problem referred to as HaploParser, HIT, and BACH. HaploParser is based on a combinatorial mosaic model and hierarchical parsing that together mimic recombinations and point-mutations in a biologically plausible way. In this mosaic model, the current population is assumed to be evolved from a small founder population. Thus, the haplotypes of the current population are recombinations of the (implicit) founder haplotypes with some point--mutations. HIT (Haplotype Inference Technique) uses a hidden Markov model for haplotypes and efficient algorithms are presented to learn this model from genotype data. The model structure of HIT is analogous to the mosaic model of HaploParser with founder haplotypes. Therefore, it can be seen as a probabilistic model of recombinations and point-mutations. BACH (Bayesian Context-based Haplotyping) utilizes a context tree weighting algorithm to efficiently sum over all variable-length Markov chains to evaluate the posterior probability of a haplotype configuration. Algorithms are presented that find haplotype configurations with high posterior probability. BACH is the most accurate method presented in this thesis and has comparable performance to the best available software for haplotype inference. Local alignment significance is a computational problem where one is interested in whether the local similarities in two sequences are due to the fact that the sequences are related or just by chance. Similarity of sequences is measured by their best local alignment score and from that, a p-value is computed. This p-value is the probability of picking two sequences from the null model that have as good or better best local alignment score. Local alignment significance is used routinely for example in homology searches. In this thesis, a general framework is sketched that allows one to compute a tight upper bound for the p-value of a local pairwise alignment score. Unlike the previous methods, the presented framework is not affeced by so-called edge-effects and can handle gaps (deletions and insertions) without troublesome sampling and curve fitting.