Geomolecular dating and the origin of placental mammals

In modern evolutionary divergence analysis the role of geological information extends beyond providing a timescale, to informing molecular rate variation across the tree. Here I consider the implications of this development. I use fossil calibrations to test the accuracy of models of molecular rate evolution for placental mammals, and reveal substantial misspecification associated with life history rate correlates. Adding further calibrations to reduce dating errors at specific nodes unfortunately tends to transfer underlying rate errors to adjacent branches. Thus, tight calibration across the tree is vital to buffer against rate model errors. I argue that this must include allowing maximum bounds to be tight when good fossil records permit, otherwise divergences deep in the tree will tend to be inflated by the interaction of rate errors and asymmetric confidence in minimum and maximum bounds. In the case of placental mammals I sought to reduce the potential for transferring calibration and rate model errors across the tree by focusing on well-supported calibrations with appropriately conservative maximum bounds. The resulting divergence estimates are younger than others published recently, and provide the long-anticipated molecular signature for the placental mammal radiation observed in the fossil record near the 66 Ma Cretaceous–Paleogene extinction event.

The clinical reasoning characteristics of diagnostic experts

The aim of this study was to identify and describe the clinical reasoning characteristics of diagnostic experts. A group of 21 experienced general practitioners were asked to complete the Diagnostic Thinking Inventory (DTI) and a set of 10 clinical reasoning problems (CRPs) to evaluate their clinical reasoning. Both the DTI and the CRPs were scored, and the CRP response patterns of each GP examined in terms of the number and type of errors contained in them. Analysis of these data showed that six GPs were able to reach the correct diagnosis using significantly less clinical information than their colleagues. These GPs also made significantly fewer interpretation errors but scored lower on both the DTI and the CRPs. Additionally, this analysis showed that more than 20% of misdiagnoses occurred despite no errors being made in the identification and interpretation of relevant clinical information. These results indicate that these six GPs diagnose efficiently, effectively and accurately using relatively few clinical data and can therefore be classified as diagnostic experts. They also indicate that a major cause of misdiagnoses is failure to properly integrate clinical data. We suggest that increased emphasis on this step in the reasoning process should prove beneficial to the development of clinical reasoning skill in undergraduate medical students.

Novel fluorescence detection technique for non-contact temperature sensing in microchip PCR

DNA amplification using Polymerase Chain Reaction (PCR) in a small volume is used in Lab-on-a-chip systems involving DNA manipulation. For few microliters of volume of liquid, it becomes difficult to measure and monitor the thermal profile accurately and reproducibly, which is an essential requirement for successful amplification. Conventional temperature sensors are either not biocompatible or too large and hence positioned away from the liquid leading to calibration errors. In this work we present a fluorescence based detection technique that is completely biocompatible and measures directly the liquid temperature. PCR is demonstrated in a 3 ILL silicon-glass microfabricated device using non-contact induction heating whose temperature is controlled using fluorescence feedback from SYBR green I dye molecules intercalated within sensor DNA. The performance is compared with temperature feedback using a thermocouple sensor. Melting curve followed by gel electrophoresis is used to confirm product specificity after the PCR cycles. (c) 2007 Elsevier B.V. All rights reserved.

Accuracy of absorbed dose in external photon beam radiotherapy : what level is sufficient and how to approach it?

Radiation therapy (RT) plays currently significant role in curative treatments of several cancers. External beam RT is carried out mostly by using megavoltage beams of linear accelerators. Tumor eradication and normal tissue complications correlate to dose absorbed in tissues. Normally this dependence is steep and it is crucial that actual dose within patient accurately correspond to the planned dose. All factors in a RT procedure contain uncertainties requiring strict quality assurance. From hospital physicist´s point of a view, technical quality control (QC), dose calculations and methods for verification of correct treatment location are the most important subjects. Most important factor in technical QC is the verification that radiation production of an accelerator, called output, is within narrow acceptable limits. The output measurements are carried out according to a locally chosen dosimetric QC program defining measurement time interval and action levels. Dose calculation algorithms need to be configured for the accelerators by using measured beam data. The uncertainty of such data sets limits for best achievable calculation accuracy. All these dosimetric measurements require good experience, are workful, take up resources needed for treatments and are prone to several random and systematic sources of errors. Appropriate verification of treatment location is more important in intensity modulated radiation therapy (IMRT) than in conventional RT. This is due to steep dose gradients produced within or close to healthy tissues locating only a few millimetres from the targeted volume. The thesis was concentrated in investigation of the quality of dosimetric measurements, the efficacy of dosimetric QC programs, the verification of measured beam data and the effect of positional errors on the dose received by the major salivary glands in head and neck IMRT. A method was developed for the estimation of the effect of the use of different dosimetric QC programs on the overall uncertainty of dose. Data were provided to facilitate the choice of a sufficient QC program. The method takes into account local output stability and reproducibility of the dosimetric QC measurements. A method based on the model fitting of the results of the QC measurements was proposed for the estimation of both of these factors. The reduction of random measurement errors and optimization of QC procedure were also investigated. A method and suggestions were presented for these purposes. The accuracy of beam data was evaluated in Finnish RT centres. Sufficient accuracy level was estimated for the beam data. A method based on the use of reference beam data was developed for the QC of beam data. Dosimetric and geometric accuracy requirements were evaluated for head and neck IMRT when function of the major salivary glands is intended to be spared. These criteria are based on the dose response obtained for the glands. Random measurement errors could be reduced enabling lowering of action levels and prolongation of measurement time interval from 1 month to even 6 months simultaneously maintaining dose accuracy. The combined effect of the proposed methods, suggestions and criteria was found to facilitate the avoidance of maximal dose errors of up to even about 8 %. In addition, their use may make the strictest recommended overall dose accuracy level of 3 % (1SD) achievable.

Factors controlling the surface energy budget over snow and ice

Polar Regions are an energy sink of the Earth system, as the Sun rays do not reach the Poles for half of the year, and hit them only at very low angles for the other half of the year. In summer, solar radiation is the dominant energy source for the Polar areas, therefore even small changes in the surface albedo strongly affect the surface energy balance and, thus, the speed and amount of snow and ice melting. In winter, the main heat sources for the atmosphere are the cyclones approaching from lower latitudes, and the atmosphere-surface heat transfer takes place through turbulent mixing and longwave radiation, the latter dominated by clouds. The aim of this thesis is to improve the knowledge about the surface and atmospheric processes that control the surface energy budget over snow and ice, with particular focus on albedo during the spring and summer seasons, on horizontal advection of heat, cloud longwave forcing, and turbulent mixing during the winter season. The critical importance of a correct albedo representation in models is illustrated through the analysis of the causes for the errors in the surface and near-surface air temperature produced in a short-range numerical weather forecast by the HIRLAM model. Then, the daily and seasonal variability of snow and ice albedo have been examined by analysing field measurements of albedo, carried out in different environments. On the basis of the data analysis, simple albedo parameterizations have been derived, which can be implemented into thermodynamic sea ice models, as well as numerical weather prediction and climate models. Field measurements of radiation and turbulent fluxes over the Bay of Bothnia (Baltic Sea) also allowed examining the impact of a large albedo change during the melting season on surface energy and ice mass budgets. When high contrasts in surface albedo are present, as in the case of snow covered areas next to open water, the effect of the surface albedo heterogeneity on the downwelling solar irradiance under overcast condition is very significant, although it is usually not accounted for in single column radiative transfer calculations. To account for this effect, an effective albedo parameterization based on three-dimensional Monte Carlo radiative transfer calculations has been developed. To test a potentially relevant application of the effective albedo parameterization, its performance in the ground-based retrieval of cloud optical depth was illustrated. Finally, the factors causing the large variations of the surface and near-surface temperatures over the Central Arctic during winter were examined. The relative importance of cloud radiative forcing, turbulent mixing, and lateral heat advection on the Arctic surface temperature were quantified through the analysis of direct observations from Russian drifting ice stations, with the lateral heat advection calculated from reanalysis products.

Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation

This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data. In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed [10] with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models. Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors [9]. Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus. It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.

Generalised regression estimation for domain class frequencies

This study examines the properties of Generalised Regression (GREG) estimators for domain class frequencies and proportions. The family of GREG estimators forms the class of design-based model-assisted estimators. All GREG estimators utilise auxiliary information via modelling. The classic GREG estimator with a linear fixed effects assisting model (GREG-lin) is one example. But when estimating class frequencies, the study variable is binary or polytomous. Therefore logistic-type assisting models (e.g. logistic or probit model) should be preferred over the linear one. However, other GREG estimators than GREG-lin are rarely used, and knowledge about their properties is limited. This study examines the properties of L-GREG estimators, which are GREG estimators with fixed-effects logistic-type models. Three research questions are addressed. First, I study whether and when L-GREG estimators are more accurate than GREG-lin. Theoretical results and Monte Carlo experiments which cover both equal and unequal probability sampling designs and a wide variety of model formulations show that in standard situations, the difference between L-GREG and GREG-lin is small. But in the case of a strong assisting model, two interesting situations arise: if the domain sample size is reasonably large, L-GREG is more accurate than GREG-lin, and if the domain sample size is very small, estimation of assisting model parameters may be inaccurate, resulting in bias for L-GREG. Second, I study variance estimation for the L-GREG estimators. The standard variance estimator (S) for all GREG estimators resembles the Sen-Yates-Grundy variance estimator, but it is a double sum of prediction errors, not of the observed values of the study variable. Monte Carlo experiments show that S underestimates the variance of L-GREG especially if the domain sample size is minor, or if the assisting model is strong. Third, since the standard variance estimator S often fails for the L-GREG estimators, I propose a new augmented variance estimator (A). The difference between S and the new estimator A is that the latter takes into account the difference between the sample fit model and the census fit model. In Monte Carlo experiments, the new estimator A outperformed the standard estimator S in terms of bias, root mean square error and coverage rate. Thus the new estimator provides a good alternative to the standard estimator.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.

Simulation of wavelength/time multiple-pulses-per-row fiber-optic CDMA network

Passive wavelength/time fiber-optic code division multiple access (WIT FO-CDMA) network is a viable option for highspeed access networks. Constructions of 2-D codes, suitable for incoherent WIT FO-CDMA, have been proposed to reduce the time spread of the 1-D sequences. The 2-D constructions can be broadly classified as 1) hybrid codes and 2) matrix codes. In our earlier work [141, we had proposed a new family of wavelength/time multiple-pulses-per-row (W/T MPR) matrix codes which have good cardinality, spectral efficiency and at the same time have the lowest off-peak autocorrelation and cross-correlation values equal to unity. In this paper we propose an architecture for a WIT MPR FO-CDAM network designed using the presently available devices and technology. A complete FO-CDMA network of ten users is simulated, for various number of simultaneous users and shown that 0 --> 1 errors can occur only when the number of interfering users is at least equal to the threshold value.

Maan magneettikentän dipolimallin toimivuus inklinaatiojakauman perusteella

The magnetic field of the Earth is 99 % of the internal origin and generated in the outer liquid core by the dynamo principle. In the 19th century, Carl Friedrich Gauss proved that the field can be described by a sum of spherical harmonic terms. Presently, this theory is the basis of e.g. IGRF models (International Geomagnetic Reference Field), which are the most accurate description available for the geomagnetic field. In average, dipole forms 3/4 and non-dipolar terms 1/4 of the instantaneous field, but the temporal mean of the field is assumed to be a pure geocentric axial dipolar field. The validity of this GAD (Geocentric Axial Dipole) hypothesis has been estimated by using several methods. In this work, the testing rests on the frequency dependence of inclination with respect to latitude. Each combination of dipole (GAD), quadrupole (G2) and octupole (G3) produces a distinct inclination distribution. These theoretical distributions have been compared with those calculated from empirical observations from different continents, and last, from the entire globe. Only data from Precambrian rocks (over 542 million years old) has been used in this work. The basic assumption is that during the long-term course of drifting continents, the globe is sampled adequately. There were 2823 observations altogether in the paleomagnetic database of the University of Helsinki. The effect of the quality of observations, as well as the age and rocktype, has been tested. For comparison between theoretical and empirical distributions, chi-square testing has been applied. In addition, spatiotemporal binning has effectively been used to remove the errors caused by multiple observations. The modelling from igneous rock data tells that the average magnetic field of the Earth is best described by a combination of a geocentric dipole and a very weak octupole (less than 10 % of GAD). Filtering and binning gave distributions a more GAD-like appearance, but deviation from GAD increased as a function of the age of rocks. The distribution calculated from so called keypoles, the most reliable determinations, behaves almost like GAD, having a zero quadrupole and an octupole 1 % of GAD. In no earlier study, past-400-Ma rocks have given a result so close to GAD, but low inclinations have been prominent especially in the sedimentary data. Despite these results, a greater deal of high-quality data and a proof of the long-term randomness of the Earth's continental motions are needed to make sure the dipole model holds true.

Residual noise covariance for Planck low-resolution data analysis

Aims: Develop and validate tools to estimate residual noise covariance in Planck frequency maps. Quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derive analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of map-making approaches. We test these analytical predictions using Monte Carlo simulations and their impact on angular power spectrum estimation. We use simulations to quantify the level of signal errors incurred in different resolution downgrading schemes considered in this work. Results: We find an excellent agreement between the optimal residual noise covariance matrices and Monte Carlo noise maps. For destriping map-makers, the extent of agreement is dictated by the knee frequency of the correlated noise component and the chosen baseline offset length. The significance of signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the sub-percent level at multipoles, ell > 2Nside, where Nside is the HEALPix resolution parameter. We show that sufficient characterization of the residual noise is unavoidable if one is to draw reliable contraints on large scale anisotropy. Conclusions: We have described how to compute the low-resolution maps, with a controlled sky signal level, and a reliable estimate of covariance of the residual noise. We have also presented a method to smooth the residual noise covariance matrices to describe the noise correlations in smoothed, bandwidth limited maps.