Bayesian Skyline Plots for mtDNA haplogroups H and U in Finland, with European reference data from Fu et al. 2012.

<p>The hatched lines denote 95% confidence intervals. A: MtDNA haplogroups H (red) and U (blue) in Finland. B: Haplogroup H in Finland (red) and in Europe (grey). C: Haplogroup U in Finland (blue) and in Europe (grey).</p

Logistic regression estimates representing the difference in haplogroup frequencies between the SW & NE subpopulations.

<p>Above X-axis: SW dominance, below: NE dominance. The results are shown for division (cf. Fig 2) that maximized the difference. Error bars denote standard deviation, statistical significance is marked with stars. No statistically significant values were obtained in randomized, non-continuous divisions.</p

The strength of NE bias for the main haplogroups plotted against the difference of haplogroup ages in Near Eastern and European populations estimated in (Richards, et al. 2000).

<p>Haplogroups with older estimated ages in Europe than in Near East show stronger eastern bias in Finland, and vice versa.</p

Map of Northern Europe with Finland and the different subpopulations analyzed.

<p>Map of Northern Europe with Finland and the different subpopulations analyzed.</p

Spatial patterns in different marker classes and in archaeological evidence for Combed Ware Culture in Finland.

<p>A: Division maximizing Y-STR haplotype differences, and frequencies of the main Y-haplogroups in Finland. B: Division maximizing the difference between Hunter-Gatherer (H-G: hgs U & V) and Farmer (F: hgs H, T, J & K) mtDNA haplogroups and their frequencies. C: The extent of Corded-Ware Culture (CWC; data from <a href="http://www.nba.fi" target="_blank">www.nba.fi</a>) in Finland, and the approximate location of the first political border between Sweden and Novgorod (AD 1323; hatched blue line).</p

Median-joining network of the 29 ancient mitochondrial haplotypes (grey-black) with 43 modern reference haplotypes (white).

<p>Median-joining network (ε = 0) shows molecular relationships between 30 ancient haplotypes (H01-H03 and H05-H30). Major haplogroups (T1, T2, T3, T5 and Q) and sub-haplogroups (T1f, T3b) are defined by inclusion of 43 modern reference haplotypes from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123821#pone.0123821.ref010" target="_blank">10</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123821#pone.0123821.ref015" target="_blank">15</a>]. Each circle represents one mtDNA haplotype where the size is proportional to the number of individuals in that haplotype. Black diamonds represent hypothetical haplotypes. The length of the branches is proportional to the number of mutations between the haplotypes except the branch between <i>Bos taurus</i> and <i>Bos indicus</i> (32 mutations), which is shortened to fit in the picture. Haplotypes from the Prehistoric, Medieval, and Post-Medieval periods are indicated in black, dark grey, and light grey, respectively.</p

Summary of ancient and modern Y-haplotypes distribution across Eurasia.

<p>Data includes 78 ancient (from Finland, Sweden and Switzerland) and 1621 modern Eurasian bulls. Separate figures for each breed and ancient populations are given in Table E in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123821#pone.0123821.s002" target="_blank">S1 File</a>.</p><p>Summary of ancient and modern Y-haplotypes distribution across Eurasia.</p

Summary statistics of mtDNA variation in ancient North East Baltic Sea region cattle from Prehistoric, Medieval, and Post-Medieval periods.

<p>N is number of individuals sampled; S is the number of segregating sites (excluding indels); h is the number of haplotypes; Hd is the haplotype diversity; K is the average number of differences; θs is ‘Theta’ derived from the observed number of segregating sites (<i>S</i>); D is Tajima′s D statistic value where statistical significances P<0.05 is marked with *.π is the nucleotide diversity*10^–3; The Prehistoric cohort includes two samples from Late Bronze Age and three samples from Late Iron Age.</p><p>^<b>a</b>Based on generation length of 7 years and mutation rate of 43% per million years</p><p>^<b>b</b>Based on generation length of 5 years and mutation rate of 53% per million years</p><p>Summary statistics of mtDNA variation in ancient North East Baltic Sea region cattle from Prehistoric, Medieval, and Post-Medieval periods.</p

Collision detection on transmission lines with optical interferometer

V diplomski nalogi skušamo ugotoviti, v kolikšni meri je možno zaznavati in klasificirati trke na jeklenicah daljnovodov z optičnim interferometrom. Na začetku predstavimo osnovne pojme interferometrije in opišemo uporabljen optični interferometer. V jedru diplomske naloge natančneje opišemo eksperimentalni protokol in obdelavo signalov. Nadaljujemo z implementacijo algoritmov za segmentacijo in klasifikacijo zajetih signalov ter predstavimo dobljene rezultate. Segmentacijo izvedemo v domeni števila prehodov signala skozi ničlo, za klasifikacijo pa uporabimo večplastno nevronsko mrežo z algoritmom vzvratnega učenja. Rezultati študije nakazujejo, da sta implementirani segmentacija in klasifikacija uspešni v 77 % izvedenih trkov različnih predmetov.We analyse feasibility of collision detection on transmission lines with optical interferometer. We first provide a brief introduction into interferometry, along with a description of the optical interferometer used for measurements in this study. Afterwards, we describe the conducted experimental protocol and signal processing methodology. The focus is on implementation of algorithms for signal segmentation and collision classification. We used zero-crossing algorithm to transform signals into segmentation domain. Classification of collisions is done with a multilayer neural network trained by the backpropagation algorithm. The results demonstrate an average success rate of 77% for segmentation and classification of collision with five different objects

Sistematización de la experiencia de un ambiente de aprendizaje enriquecido por TIC durante la práctica clínica en fisioterapia cardiopulmonar en un hospital de nivel II de la ciudad de Cali

Esta investigación se centra en la caracterización de la experiencia de 4 estudiantes de fisioterapia de IX semestre de la Institución Universitaria Escuela Nacional del Deporte (IUEND) durante la implementación de un ambiente de aprendizaje enriquecido con Tecnologías de la Información y la Comunicación (TIC) en la práctica clínico – asistencial en Salud Cardiopulmonar; la cual se fundamenta en el hacer y pone a prueba las bases conceptuales del ciclo de fundamentación; todo esto con el fin de identificar las experiencias significativas que facilitan el aprendizaje y desarrollo de competencias clínicas, además analizar si este tipo de estrategias de enseñanza -aprendizaje permite al estudiante y al docente asesor superar inconvenientes propios de la práctica clínica como: optimizar tiempos de atención a pacientes, estudio independiente y trabajo colaborativo, retomar e integrar gran cantidad de conceptos y procedimientos aprendidos en IV semestre con las nuevas experiencias y la realidad del paciente; y a la vez cumplir con funciones administrativas propios del rol del fisioterapeuta asistencial (estadística, indicadores, desarrollo de guías, etc.) que dificultan el proceso de aprendizaje; concluyendo que los ambientes mediados por TIC pueden lograr superar estas dificultades y favorecer finalmente el aprendizaje significativo (juicio clínico), en el que se fundamenta el ciclo de práctica profesional