Dynamic contrast agent -enhanced magnetic resonance imaging assessment of tumor microvasculature

Dynamic contrast agent-enhanced magnetic resonance imaging (DCE MRI) data, when analyzed with the appropriate pharmacokinetic models, have been shown to provide quantitative estimates of microvascular parameters important in characterizing the angiogenic activity of malignant tissue. These parameters consist of the whole blood volume per unit volume of tissue, v b, transport constant from the plasma to the extravascular, extracellular space (EES), k1 and the transport constant from the EES to the plasma, k2. Parameters vb and k1 are expected to correlate with microvascular density (MVD) and vascular permeability, respectively, which have been suggested to serve as surrogate markers for angiogenesis. In addition to being a marker for angiogenesis, vascular permeability is also useful in estimating tumor penetration potential of chemotherapeutic agents. ^ Histological measurements of the intratumoral microvascular environment are limited by their invasiveness and susceptibility to sampling errors. Also, MVD and vascular permeability, while useful for characterizing tumors at a single time point, have shown less utility in longitudinal studies, particularly when used to monitor the efficacy of antiangiogenic and traditional chemotherapeutic agents. These limitations led to a search for a non-invasive means of characterizing the microvascular environment of an entire tumor. ^ The overall goal of this project was to determine the utility of DCE MRI for monitoring the effect of antiangiogenic agents. Further applications of a validated DCE MRI technique include in vivo measurements of tumor microvascular characteristics to aid in determining prognosis at presentation and in estimating drug penetration. DCE MRI data were generated using single- and dual-tracer pharmacokinetic models with different molecular-weight contrast agents. The resulting pharmacokinetic parameters were compared to immunohistochemical measurements. The model and contrast agent combination yielding the best correlation between the pharmacokinetic parameters and histological measures was further evaluated in a longitudinal study to evaluate the efficacy of DCE MRI in monitoring the intratumoral microvascular environment following antiangiogenic treatment. ^

Mechanical properties and comparisons of dynamic and static Young's moduli at DSDP Holes 69-504B, 70-504B and 83-504B

From laboratory tests under simulated downhole conditions we tentatively conclude that the higher the triaxial-compressive strength, the lower the drilling rate of basalts from DSDP Hole 504B. Because strength is roughly proportional to Young's modulus of elasticity, which is related in turn to seismic-wave velocities, one may be able to estimate drilling rates from routine shipboard measurements. However, further research is needed to verify that P-wave velocity is a generally useful predictor of relative drilling rate.

Probabilistic models for the prediction of a ship performance in dynamic ice

We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.

(Table 1) Movement parameters of nine adult female snowy owls (Bubo scandiacus) tracked during the winter period 07/08 and 08/09 around Hudson Strait, Canada

Top predators of the arctic tundra are facing a long period of very low prey availability during winter and subsidies from other ecosystems such as the marine environment may help to support their populations. Satellite tracking of snowy owls, a top predator of the tundra, revealed that most adult females breeding in the Canadian Arctic overwinter at high latitudes in the eastern Arctic and spend several weeks (up to 101 d) on the sea-ice between December and April. Analysis of high-resolution satellite images of sea-ice indicated that owls were primarily gathering around open water patches in the ice, which are commonly used by wintering seabirds, a potential prey. Such extensive use of sea-ice by a tundra predator considered a small mammal specialist was unexpected, and suggests that marine resources subsidize snowy owl populations in winter. As sea-ice regimes in winter are expected to change over the next decades due to climate warming, this may affect the wintering strategy of this top predator and ultimately the functioning of the tundra ecosystem.

Abiotic parameters and abundances, dominance and diversity of benthic macro- and meiofauna in Kongsfjord, Spitsbergen

The intertidal and subtidal soft bottom macro- and meiofauna of a glacier fjord on Spitsbergen was studied after complete ice melt in June 2003. The abundances of the benthic fauna were within the range reported from estuaries and similar intertidal areas of boreal regions. The high proportion of juveniles in the eulittoral zone indicated larval recruitment from subtidal areas. The macrobenthic fauna can be divided into an intertidal and a subtidal community, both being numerically dominated by annelids. Deposit feeders were numerically predominant in intertidal sites, whereas suspension feeders were most abundant in the subtidal area. Among the meiofauna, only the benthic copepods were identified to species, revealing ecological adaptations typical for intertidal species elsewhere.

Phytoplankton production, photosynthetic (P vs E) parameters, and particulate organic carbon and nitrogen within distinct water masses of eastern Australian coastal and shelf waters between 29 °S and 36 °S during spring 2010

The present dataset is part of an interdisciplinary project carried out on board the RV Southern Surveyor off New South Wales (Australia) from the 15th to the 31st October 2010. The main objective of the research voyage was to evaluate how the East Australian Current (EAC) affects the optical, chemical, physical, and biological water properties of the continental shelf and slope off the NSW coast.

Dynamic chanel model LMS updating for RSS-based localization

Received signal strength-based localization systems usually rely on a calibration process that aims at characterizing the propagation channel. However, due to the changing environmental dynamics, the behavior of the channel may change after some time, thus, recalibration processes are necessary to maintain the positioning accuracy. This paper proposes a dynamic calibration method to initially calibrate and subsequently update the parameters of the propagation channel model using a Least Mean Squares approach. The method assumes that each anchor node in the localization infrastructure is characterized by its own propagation channel model. In practice, a set of sniffers is used to collect RSS samples, which will be used to automatically calibrate each channel model by iteratively minimizing the positioning error. The proposed method is validated through numerical simulation, showing that the positioning error of the mobile nodes is effectively reduced. Furthermore, the method has a very low computational cost; therefore it can be used in real-time operation for wireless resource-constrained nodes.

Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting

In this work, we propose the Seasonal Dynamic Factor Analysis (SeaDFA), an extension of Nonstationary Dynamic Factor Analysis, through which one can deal with dimensionality reduction in vectors of time series in such a way that both common and specific components are extracted. Furthermore, common factors are able to capture not only regular dynamics (stationary or not) but also seasonal ones, by means of the common factors following a multiplicative seasonal VARIMA(p, d, q) × (P, D, Q)s model. Additionally, a bootstrap procedure that does not need a backward representation of the model is proposed to be able to make inference for all the parameters in the model. A bootstrap scheme developed for forecasting includes uncertainty due to parameter estimation, allowing enhanced coverage of forecasting intervals. A challenging application is provided. The new proposed model and a bootstrap scheme are applied to an innovative subject in electricity markets: the computation of long-term point forecasts and prediction intervals of electricity prices. Several appendices with technical details, an illustrative example, and an additional table are available online as Supplementary Materials.