Position-dependent effects on stability in tricyclo-DNA modified oligonucleotide duplexes

A series of oligodeoxyribonucleotides and oligoribonucleotides containing single and multiple tricyclo(tc)-nucleosides in various arrangements were prepared and the thermal and thermodynamic transition profiles of duplexes with complementary DNA and RNA evaluated. Tc-residues aligned in a non-continuous fashion in an RNA strand significantly decrease affinity to complementary RNA and DNA, mostly as a consequence of a loss of pairing enthalpy DeltaH. Arranging the tc-residues in a continuous fashion rescues T(m) and leads to higher DNA and RNA affinity. Substitution of oligodeoxyribonucleotides in the same way causes much less differences in T(m) when paired to complementary DNA and leads to substantial increases in T(m) when paired to complementary RNA. CD-spectroscopic investigations in combination with molecular dynamics simulations of duplexes with single modifications show that tc-residues in the RNA backbone distinctly influence the conformation of the neighboring nucleotides forcing them into higher energy conformations, while tc-residues in the DNA backbone seem to have negligible influence on the nearest neighbor conformations. These results rationalize the observed affinity differences and are of relevance for the design of tc-DNA containing oligonucleotides for applications in antisense or RNAi therapy.

Analysis and Prediction of Transient Opacity Spikes Using Dimensional Modeling

Dimensional modeling, GT-Power in particular, has been used for two related purposes-to quantify and understand the inaccuracies of transient engine flow estimates that cause transient smoke spikes and to improve empirical models of opacity or particulate matter used for engine calibration. It has been proposed by dimensional modeling that exhaust gas recirculation flow rate was significantly underestimated and volumetric efficiency was overestimated by the electronic control module during the turbocharger lag period of an electronically controlled heavy duty diesel engine. Factoring in cylinder-to-cylinder variation, it has been shown that the electronic control module estimated fuel-Oxygen ratio was lower than actual by up to 35% during the turbocharger lag period but within 2% of actual elsewhere, thus hindering fuel-Oxygen ratio limit-based smoke control. The dimensional modeling of transient flow was enabled with a new method of simulating transient data in which the manifold pressures and exhaust gas recirculation system flow resistance, characterized as a function of exhaust gas recirculation valve position at each measured transient data point, were replicated by quasi-static or transient simulation to predict engine flows. Dimensional modeling was also used to transform the engine operating parameter model input space to a more fundamental lower dimensional space so that a nearest neighbor approach could be used to predict smoke emissions. This new approach, intended for engine calibration and control modeling, was termed the "nonparametric reduced dimensionality" approach. It was used to predict federal test procedure cumulative particulate matter within 7% of measured value, based solely on steady-state training data. Very little correlation between the model inputs in the transformed space was observed as compared to the engine operating parameter space. This more uniform, smaller, shrunken model input space might explain how the nonparametric reduced dimensionality approach model could successfully predict federal test procedure emissions when roughly 40% of all transient points were classified as outliers as per the steady-state training data.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

Genetic diversity among horse populations with a special focus on the Franches-Montagnes breed

Genetic characterization helps to assure breed integrity and to assign individuals to defined populations. The objective of this study was to characterize genetic diversity in six horse breeds and to analyse the population structure of the Franches-Montagnes breed, especially with regard to the degree of introgression with Warmblood. A total of 402 alleles from 50 microsatellite loci were used. The average number of alleles per locus was significantly lower in Thoroughbreds and Arabians. Average heterozygosities between breeds ranged from 0.61 to 0.72. The overall average of the coefficient of gene differentiation because of breed differences was 0.100, with a range of 0.036-0.263. No significant correlation was found between this parameter and the number of alleles per locus. An increase in the number of homozygous loci with increasing inbreeding could not be shown for the Franches-Montagnes horses. The proportion of shared alleles, combined with the neighbour-joining method, defined clusters for Icelandic Horse, Comtois, Arabians and Franches-Montagnes. A more disparate clustering could be seen for European Warmbloods and Thoroughbreds, presumably from frequent grading-up of Warmbloods with Thoroughbreds. Grading-up effects were also observed when Bayesian and Monte Carlo resampling approaches were used for individual assignment to a given population. Individual breed assignments to defined reference populations will be very difficult when introgression has occurred. The Bayesian approach within the Franches-Montagnes breed differentiated individuals with varied proportions of Warmblood.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.

Eruptive history of Maderas volcano using new 40Ar/39Ar ages and geochemical analyses

Maderas volcano is a small, andesitic stratovolcano located on the island of Ometepe, in Lake Nicaragua, Nicaragua with no record of historic activity. Twenty-one samples were collected from lava flows from Maderas in 2010. Selected samples were analyzed for whole-rock geochemical data using ICP-AES and/or were dated using the 40Ar/39Ar method. The results of these analyses were combined with previously collected data from Maderas as well as field observations to determine the eruptive history of the volcano and create a geologic map. The results of the geochemical analyses indicate that Maderas is a typical Central American andesitic volcano similar to other volcanoes in Nicaragua and Costa Rica and to its nearest neighbor, Concepción volcano. It is different from Concepción in one important way – higher incompatible elements. Determined age dates range from 176.8 ± 6.1 ka to 70.5 ± 6.1 ka. Based on these ages and the geomorphology of the volcano which is characterized by a bisecting graben, it is proposed that Maderas experienced two clear generations of development with three separate phases of volcanism: initial build-up of the older cone, pre-graben lava flows, and post-graben lava flows. The ages also indicate that Maderas is markedly older than Concepción which is historically active. Results were also analyzed regarding geologic hazards. The 40Ar/39Ar ages indicate that Maderas has likely been inactive for tens of thousands of years and the risk of future volcanic eruptions is low. However, earthquake, lahar and landslide hazards exist for the communities around the volcano. The steep slopes of the eroded older cone are the most likely source of landslide and lahar hazards.

DIFFERENTIATING PATH AND SOURCE PROCESSES IN COMPLEX GEOLOGIC STRUCTURE THROUGH PASSIVE SEISMIC STUDIES: BERING GLACIER, ALASKA AND VILLARRICA VOLCANO, CHILE

Measuring shallow seismic sources provides a way to reveal processes that cannot be directly observed, but the correct interpretation and value of these signals depend on the ability to distinguish source from propagation effects. Furthermore, seismic signals produced by a resonating source can look almost identical to those produced by impulsive sources, but modified along the path. Distinguishing these two phenomena can be accomplished by examining the wavefield with small aperture arrays or by recording seismicity near to the source when possible. We examine source and path effects in two different environments: Bering Glacier, Alaska and Villarrica Volcano, Chile. Using three 3-element seismic arrays near the terminus of the Bering Glacier, we have identified and located both terminus calving and iceberg breakup events. We show that automated array analysis provided a robust way to locate icequake events using P waves. This analysis also showed that arrivals within the long-period codas were incoherent within the small aperture arrays, demonstrating that these codas previously attributed to crack resonance were in fact a result of a complicated path rather than a source effect. At Villarrica Volcano, seismometers deployed from near the vent to ~10 km revealed that a several cycle long-period source signal recorded at the vent appeared elongated in the far-field. We used data collected from the stations nearest to the vent to invert for the repetitive seismic source, and found it corresponded to a shallow force within the lava lake oriented N75°E and dipping 7° from horizontal. We also used this repetitive signal to search the data for additional seismic and infrasonic properties which included calculating seismic-acoustic delay times, volcano acoustic-seismic ratios and energies, event frequency, and real-time seismic amplitude measurements. These calculations revealed lava lake level and activity fluctuations consistent with lava lake level changes inferred from the persistent infrasonic tremor.

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

Chromite Deposits Near Red Lodge and Silver Star, Montana

The Red Lodge and Silver Star chromite deposits of Montana have stimulated much interest during periods of war. The Red Lodge deposit is 25 miles southwest of Red Lodge which is also the nearest railroad point. Several workings are scattered throughout the area, exposing lense-like ore bodies averaging 33% chrome oxide. Silver Star is a much smaller deposit 5 miles west of Silver Star, Montana, which is its nearest rail­road point. Lenses of chromite are exposed by pits and trench­es, which average approximately 36% chromic oxide.

Genetic diversity of Swiss sheep breeds in the focus of conservation research

There is constant pressure to improve evaluation of animal genetic resources in order to prevent their erosion. Maintaining the integrity of livestock species as well as their genetic diversity is of paramount interest for long-term agricultural policies. One major use of DNA techniques in conservation is to reveal genetic diversity within and between populations. Forty-one microsatellites were analysed to assess genetic diversity in nine Swiss sheep breeds and to measure the loss of the overall diversity when one breed would become extinct. The expected heterozygosities varied from 0.65 to 0.74 and 10.8% of the total genetic diversity can be explained by the variation among breeds. Based on the proportion of shared alleles, each of the nine breeds were clearly defined in their own cluster in the neighbour-joining tree describing the relationships among the breeds. Bayesian clustering methods assign individuals to groups based on their genetic similarity and infer the number of populations. In STRUCTURE, this approach pooled the Valais Blacknose and the Valais Red. With BAPS method the two Valais sheep breeds could be separated. Caballero & Toro approach (2002) was used to calculate the loss or gain of genetic diversity when each of the breeds would be removed from the set. The changes in diversity based on between-breed variation ranged from -12.2% (Valais Blacknose) to 0% (Swiss Black Brown Mountain and Mirror Sheep); based on within-breed diversity the removal of a breed could also produce an increase in diversity (-0.6% to + 0.6%). Allelic richness ranged from 4.9 (Valais Red) to 6.7 (Brown Headed Meat sheep and Red Engadine Sheep). Breed conservation decisions cannot be limited to genetic diversity alone. In Switzerland, conservation goals are embedded in the desire to carry the cultural legacy over to future generations.

Nicoletella semolina gen. nov., sp. nov., a new member of Pasteurellaceae isolated from horses with airway disease

Gram-negative, nonmotile bacteria that are catalase, oxidase, and urease positive are regularly isolated from the airways of horses with clinical signs of respiratory disease. On the basis of the findings by a polyphasic approach, we propose that these strains be classified as Nicoletella semolina gen. nov, sp. nov., a new member of the family Pasteurellaceae. N. semolina reduces nitrate to nitrite but is otherwise biochemically inert; this includes the lack of an ability to ferment glucose and other sugars. Growth is fastidious, and the isolates have a distinctive colony morphology, with the colonies being dry and waxy and looking like a semolina particle that can be moved around on an agar plate without losing their shape. DNA-DNA hybridization data and multilocus phylogenetic analysis, including 16S rRNA gene (rDNA), rpoB, and infB sequencing, clearly placed N. semolina as a new genus in the family Pasteurellaceae. In all the phylogenetic trees constructed, N. semolina is on a distinct branch displaying approximately 5% 16S rDNA, approximately 16% rpoB, and approximately 20% infB sequence divergence from its nearest relative within the family Pasteurellaceae. High degrees of conservation of the 16S rDNA (99.8%), rpoB (99.6%), and infB (99.7%) sequences exist within the species, indicating that N. semolina isolates not only are phenotypically homogeneous but also are genetically homogeneous. The type strain of N. semolina is CCUG43639(T) (DSM16380(T)).

Strong Down-Valley Low-Level Jets over the Atacama Desert: Observational Characterization

The near-surface wind and temperature regime at three points in the Atacama Desert of northern Chile is described using two-year multi-level measurements from 80-m towers located in an altitude range between 2100 and 2700 m ASL. The data reveal the frequent development of strong nocturnal drainage flows at all sites. Down-valley nose-shaped wind speed profiles are observed with maximum values occurring at heights between 20 m and 60 m AGL. The flow intensity shows considerable inter-daily variability and a seasonal modulation of maximum speeds, which in the cold season can attain hourly average values larger than 20 m s−1. Turbulent mixing appears significant over the full tower layer, affecting the curvature of the nighttime temperature profile and possibly explaining the observed increase of surface temperatures in the down-valley direction. Nocturnal valley winds and temperatures are weakly controlled by upper-air conditions observed at the nearest aerological station. Estimates of terms in the momentum budget for the development and the quasi-stationary phases of the down-valley flows suggest that the pressure gradient force due to the near-surface cooling along the sloping valley axes plays an important role in these drainage flows. A scale for the jet nose height of equilibrium turbulent down-slope jets is proposed, based on surface friction velocity and surface inversion intensity. At one of the sites this scale explains about 70% of the case-to-case observed variance of jet nose heights. Further modeling and observational work is needed, however, in order to better define the dynamics, extent and turbulence structure of this flow system, which has significant wind-energy, climatic and environmental implications.

Geographical Dialectology

This chapter examines how linguists have investigated the very obvious fact that different places house different dialects. We will not look at the results of such work nor how they have been used to answer linguistic and sociolinguistic questions (see Britain 2009, in press). Here we simply examine the steps dialectologists take and have taken to conduct multi-locality research on language variation. In order to do so, five studies from different time periods are presented and critiqued, examining a number of key methodological elements in each: 1. The aim of geographical dialectology is to examine variation across space, in different places. How do dialectologists then decide which places in that space to analyse? Why choose one village and not its neighbour? Why avoid that city? This question goes to the very heart of the geographical motivation of the research. 2. What sorts of speakers will be sampled from these locations? 3. What type of data is to be collected from these speakers? 4. In what circumstances is that data to be recorded? Who will collect it, in what setting and how will the voices of the speakers be captured for later analysis? As we will see, dialectological methodologies always involve compromises, no approach is ever flawless. Ultimately, a good number of difficult practical decisions have to be taken – how long can this research take, and what are the financial restrictions on the project? As we will see geographical dialectology is probably the most expensive and the most time consuming of all forms of language variation research.

A reliable, traffic-adaptive and energy-efficient link layer for wireless sensor networks

The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.