Geometric Morphometry Analysis of the Scapula: Implications for the Determination of Sex and Ancestry

The nascent but growing field of geometric morphometrics has proved to be a useful tool in the investigation of shape differences of skeletal elements of various populations. Until recently, most anthropological studies using geometric morphometrics have focused on shape differences of the skull, largely to the neglect of the postcrania. This research uses coordinate data derived from three-dimensional digitizing to quantify morphological variation in left and right scapulae of Blacks and Whites of both sexes. The sample analyzed was from a collection of present day Americans, making it particularly germane for forensic applications. Left and right scapulae of Black males, Black females, White males, and White females were digitized, producing three-dimensional coordinates that were subsequently subjected to Procrustes analysis, and residuals were analyzed by traditional statistical analyses. Consensus configurations were superimposed using thin-place splines to investigate shape variability among groups. Canonical discriminant function analysis suggested that shape differences exist between scapulae of Blacks and Whites and between the sexes. Principal component analysis showed that principal components loaded differently on the canonical discriminant functions of left and right scapulae. Centroid sizes effectively discriminated between males and females but did not discriminate between Blacks and Whites. The success of this study in differentiating shape variability between scapulae of males and females and between Blacks and Whites demonstrates the benefit of using geometric morphometry to examine biological variability of human subpopulations. In addition, the use of non-traditional landmarks allowed for a more complete analysis of scapular shape. The use of non-traditional landmarks showed that much of the variability in scapular shape between the sexes and between Blacks and Whites lies in previously neglected areas of the scapula

Glosarium Matematika

273 p.; 24 cm

A Quantitative Methodology for Vetting Dark Network Intelligence Sources for Social Network Analysis

Social network analysis (SNA) is used by the DoD to describe and analyze social networks, leading to recommendations for operational decisions. However, social network models are constructed from various information sources of indeterminate reliability. Inclusion of unreliable information can lead to incorrect models resulting in flawed analysis and decisions. This research develops a methodology to assist the analyst by quantitatively identifying and categorizing information sources so that determinations on including or excluding provided data can be made. This research pursued three main thrusts. It consolidated binary similarity measures to determine social network information sources\u27 concordance and developed a methodology to select suitable measures dependent upon application considerations. A methodology was developed to assess the validity of individual sources of social network data. This methodology utilized source pairwise comparisons to measure information sources\u27 concordance and a weighting schema to account for sources\u27 unique perspectives of the underlying social network. Finally, the developed methodology was tested over a variety of generated networks with varying parameters in a design of experiments paradigm (DOE). Various factors relevant to conditions faced by SNA analysts potentially employing this methodology were examined. The DOE was comprised of a 24 full factorial design augmented with a nearly orthogonal Latin hypercube. A linear model was constructed using quantile regression to mitigate the non-normality of the error terms

Amplikoni põhine metsamuldade bakterikoosluse analüüs

Väitekirja elektrooniline versioon ei sisalda publikatsiooneMuldade rikkalike mikroobikoosluste uurimist on siiani palju takistanud tõsiasi, et enamik mulla mikroobe on kultiveerimatud. Seda kitsaskohta aitab leevendada lähenemine nimega metagenoomika, mis tähistab uurimistööd otse keskkonnaproovidest eraldatud geneetilise materjaliga. Selliste andmete kasutamiseks on levinud meetodid, mille abil grupeeritakse (klasterdatakse) kogutud DNA järjestused ad-hoc taksonoomilistesse üksustesse nn. OTU-desse (Operational Taxonomic Unit). Nii võib OTU-desse klasterdatud järjestusi kasutades hinnata bakterikoosluste mitmekesisust ja liigilist koostist. Saadud OTU-de arvukuse numbreid annab kasutada mitmesugustes erinevates analüüsides kui asendajaid tavapärasematele taksonoomilistele üksustele. Niisama kiire, kui on olnud uute sekveneerimistehnoloogiate areng, on ka olnud uute tööriistade arvu kasv – viimase kümnendi jooksul on loodud hulk programme, mis on mõeldud eelpoolmainitud OTU-de moodustamiseks DNA järjestuste andmetest. Antud doktoritöö töö keskendub sellele, kuidas mõjutavad erinevad OTU loomise meetodid edasisi analüüse ning järeldusi. Selleks kasutati järjestusandmeid artiklist “Bacterial community structure and its relationship to soil physico-chemical characteristics in alder stands with different management histories” ning erinevaid OTU klasterdamise meetodeid. OTU-d loodi erinevate programmide abil (Mothur,CROP,UCLUST,Swarm) – seejärel viidi läbi koosluste mitmesugused statistilised analüüsid. OTU andmete analüüs andis üldjoontes samasuguseid tulemusi. Seda visualiseerivad hästi töös olevad joonised. OTU arvude ja mitmekesisusindeksi statistilised testid ei leidnud statistiliselt olulist erinevust eri klasterdusmeetodite vahel. Kasutatud klasterdamismeetoditest jäid parimaina silma paistma CROP ja UCLUST meetodid.Lisaks näitasid analüüsid ka osade statistiliste meetodite eeliseid teiste ees sedasorti OTU andmete käsitlemiselThe soil as a central agent in many ecological processes has received a lot of research attention from many different angles. The investigation of the rich microbiome of the soil has been slowed by the fact that most of the microbes are unculturable. This gap can be filled by the metagenomics which is a field that deals with genetic material directly acquired form environmental samples. The analysis of 16S rDNA data usually begins with the construction of operational taxonomicunits (OTUs): clusters of reads that differ by less than a fixed sequence dissimilarity threshold. Consequently, the obtained sample-by-OTU abundance table serves as the basis for further statistical and exploratory analysis. During the last decade, a plethora of tools based on different principles and having different computational requirements to perform aforementioned OTU clustering has been created. This work we take an interest in the differences of the final outcome of series of analyses when different OTU clustering methods are used and also have a comparision of these methods. We used the dataset published in “Bacterial community structure and its relationship to soil physico-chemical characteristics in alder stands with different management histories” and analysed it using different software packages for processing bioinformatics data: Mothur UCLUST, CROP, Swarm. The results of analyses were on the whole quite similar and comparable.The differences between OTU numbers and diversity indeces were statistically not significant. The CROP and UCLUST methods stood out by their quality and useability. The work also showed the practicality of robust statistical methods when working with OTU data

Learning in the Real World: Constraints on Cost, Space, and Privacy

The sheer demand for machine learning in fields as varied as: healthcare, web-search ranking, factory automation, collision prediction, spam filtering, and many others, frequently outpaces the intended use-case of machine learning models. In fact, a growing number of companies hire machine learning researchers to rectify this very problem: to tailor and/or design new state-of-the-art models to the setting at hand. However, we can generalize a large set of the machine learning problems encountered in practical settings into three categories: cost, space, and privacy. The first category (cost) considers problems that need to balance the accuracy of a machine learning model with the cost required to evaluate it. These include problems in web-search, where results need to be delivered to a user in under a second and be as accurate as possible. The second category (space) collects problems that require running machine learning algorithms on low-memory computing devices. For instance, in search-and-rescue operations we may opt to use many small unmanned aerial vehicles (UAVs) equipped with machine learning algorithms for object detection to find a desired search target. These algorithms should be small to fit within the physical memory limits of the UAV (and be energy efficient) while reliably detecting objects. The third category (privacy) considers problems where one wishes to run machine learning algorithms on sensitive data. It has been shown that seemingly innocuous analyses on such data can be exploited to reveal data individuals would prefer to keep private. Thus, nearly any algorithm that runs on patient or economic data falls under this set of problems. We devise solutions for each of these problem categories including (i) a fast tree-based model for explicitly trading off accuracy and model evaluation time, (ii) a compression method for the k-nearest neighbor classifier, and (iii) a private causal inference algorithm that protects sensitive data

Regularized algorithms for ranking, and manifold learning for related tasks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (leaves 119-127).This thesis describes an investigation of regularized algorithms for ranking problems for user preferences and information retrieval problems. We utilize regularized manifold algorithms to appropriately incorporate data from related tasks. This investigation was inspired by personalization challenges in both user preference and information retrieval ranking problems. We formulate the ranking problem of related tasks as a special case of semi-supervised learning. We examine how to incorporate instances from related tasks, with the appropriate penalty in the loss function to optimize performance on the hold out sets. We present a regularized manifold approach that allows us to learn a distance metric for the different instances directly from the data. This approach allows incorporation of information from related task examples, without prior estimation of cross-task coefficient covariances. We also present applications of ranking problems in two text analysis problems: a) Supervise content-word learning, and b) Company Entity matching for record linkage problems.by Giorgos Zacharia.Ph.D

Potential Effects of Climate Change on the Distribution and Migration of European Breeding Migratory Birds

Aim: This thesis aims to investigate the potential impacts of climatic change on Afro-Palaearctic migratory birds by investigating simulated changes in breeding and non-breeding distribution. Methods: Generalised Additive Models were used to determine those climatic variables that produced the most robust species distribution models. Tests on the performance of three regression-based techniques were undertaken and consensus modelling framework was subsequently chosen. This framework was used in conjunction with three general circulation models and two emission scenarios to model the future distributions of Afro-Palaearctic migratory birds. Changes in both breeding and non-breeding range and migratory distance were examined for groups of species. A vulnerability index was created to indicate those species that were most vulnerable to climate change. Finally, changes in recent population trends observed on the European breeding grounds were related to simulated climatic suitability to investigate the role of climate in recent population changes and determine the vulnerability of populations to climate change. This analysis also enabled a partial validation of species distribution models. Results: The results indicate differential change on the breeding and non-breeding grounds for many species. For many migratory birds a progressive separation of the two ranges is projected, potentially increasing migratory distances in future. However, for some species newly suitable climatic areas may provide non-breeding areas closer to the breeding range, enabling species to adapt to climatic change. Trans-Saharan migrants, species residing in dry environments as well as montane and coastal species are projected to be most vulnerable to climatic change. Although a link between population trends and climatic suitability could be found, the results indicated, as might be expected, that climate is only one of a number of factors potentially contributing to population changes Conclusion: This thesis gives the first broad analysis of the likely direction and magnitude of change of the distribution of migratory birds to climate change, when only climate is considered. The challenge ahead is to refine these coarse scale models to include habitat and demographic data so as to provide more realistic estimates of change and improve conservation strategies that aim to support species under climate change

The Ephemeral City : Songs for the Ghost Quarters

The towers of the Stockholm skyline twine with radio transmissions, flying out over the city, drifting down through the streets and sinking into the underground telephone system below. Stockholm has buildings that have been there for centuries, but is also full of modern and contemporary architectures, all jostling for their place in parallel collective memory. In taking the city up as a subject, this artistic PhD project in music expands allegories to these architectural instruments into the world of the mechanical and the electrical. By taking up and transforming the materials of the cityscape, this project spins ephemeral cities more subtle than the colossal forces transforming the cityscape. The aim is to empower urban dwellers with another kind of ownership of their city.The materials in the project are drawn around themes of urban memory and transformation, psychogeography and the ghosts of the imagined city. There are three questions the artistic works of this project reflect on and address. The first is about the ability of city-dwellers to regain or create some sense of place, history or belonging through the power of their imaginations. The second reflects on the possibility for imagined alternatives to re-empower a sense of place for the people who encounter them. The third seeks out the points where stories, memories, or alternative futures are collective, at what point are they wholly individual, and how the interplay between them plays out in listening.There is an improvisatory practice in how we relate to urban environments: an ever-transforming inter-play between the animate and inanimate. Each individual draws phantoms of memory and imagination onto the cityscape, and this yields subtle ways people can be empowered in their surroundings. The artistic works of this project are made to illuminate those subtleties, centering around a group of compositions, improvisations, artistic collaborations and sound installations in music and sound, utilizing modular synthesizers, field recordings, pipe organs, multi-channel settings; PureData and SuperCollider programs, string ensembles with hurdy-gurdy and nyckelharpa or violin, and sound installations. This choice of instruments is as an allegory to the architecture of Stockholm. The final result is a collection of music and sound works, made to illuminate the imagined city. Taken as a whole, the works of the project create an imaginary city–The Ephemeral City–in order to argue that this evocation of ephemeral space is a way to empower urban dwellers through force of imagination, immune to the vast forces tearing through the fabric of Stockholm life by virtue of the ghostly, transitory and mercurial, as compelling to the inner eye as brick and mortar to the outer life