Uncertainty drives deviations in normative foraging decision strategies

Nearly all animals forage to acquire energy for survival through efficient search and resource harvesting. Patch exploitation is a canonical foraging behaviour, but there is a need for more tractable and understandable mathematical models describing how foragers deal with uncertainty. To provide such a treatment, we develop a normative theory of patch foraging decisions, proposing mechanisms by which foraging behaviours emerge in the face of uncertainty. Our model foragers statistically and sequentially infer patch resource yields using Bayesian updating based on their resource encounter history. A decision to leave a patch is triggered when the certainty of the patch type or the estimated yield of the patch falls below a threshold. The time scale over which uncertainty in resource availability persists strongly impacts behavioural variables like patch residence times and decision rules determining patch departures. When patch depletion is slow, as in habitat selection, departures are characterized by a reduction of uncertainty, suggesting that the forager resides in a low-yielding patch. Uncertainty leads patch-exploiting foragers to overharvest (underharvest) patches with initially low (high) resource yields in comparison with predictions of the marginal value theorem. These results extend optimal foraging theory and motivate a variety of behavioural experiments investigating patch foraging behaviour.     

Accelerated dynamic MRI exploiting sparsity and low-rank structure: k-t SLR

We introduce a novel algorithm to reconstruct dynamic magnetic resonance imaging (MRI) data from under-sampled k-t space data. In contrast to classical model based cine MRI schemes that rely on the sparsity or banded structure in Fourier space, we use the compact representation of the data in the Karhunen Louve transform (KLT) domain to exploit the correlations in the dataset. The use of the data-dependent KL transform makes our approach ideally suited to a range of dynamic imaging problems, even when the motion is not periodic. In comparison to current KLT-based methods that rely on a two-step approach to first estimate the basis functions and then use it for reconstruction, we pose the problem as a spectrally regularized matrix recovery problem. By simultaneously determining the temporal basis functions and its spatial weights from the entire measured data, the proposed scheme is capable of providing high quality reconstructions at a range of accelerations. In addition to using the compact representation in the KLT domain, we also exploit the sparsity of the data to further improve the recovery rate. Validations using numerical phantoms and in vivo cardiac perfusion MRI data demonstrate the significant improvement in performance offered by the proposed scheme over existing methods.     

X-ray categorization and retrieval on the organ and pathology level, using patch-based visual words

In this study we present an efficient image categorization and retrieval system applied to medical image databases, in particular large radiograph archives. The methodology is based on local patch representation of the image content, using a "bag of visual words" approach. We explore the effects of various parameters on system performance, and show best results using dense sampling of simple features with spatial content, and a nonlinear kernel-based support vector machine (SVM) classifier. In a recent international competition the system was ranked first in discriminating orientation and body regions in X-ray images. In addition to organ-level discrimination, we show an application to pathology-level categorization of chest X-ray data, the most popular examination in radiology. The system discriminates between healthy and pathological cases, and is also shown to successfully identify specific pathologies in a set of chest radiographs taken from a routine hospital examination. This is a first step towards similarity-based categorization, which has a major clinical implications for computer-assisted diagnostics.     

The economics of load management by ripple control

An analysis is presented of the benefits of voluntary load shedding schemes which interrupt electricity supply when generating capacity is insufficient. Supply interruption is by ripple control, in which coded pulses are transmitted through the supply network, or by radio control. An algorithm is devised and illustrated, which evaluates the benefits of load shedding for any system, assuming fixed prices and a constant load duration curve. The algorithm is developed by calculating the expected shed load in a given period and the costs of building additional capacity to meet this load. These costs correspond to the benefits of the load shedding scheme.     

Reconstitution of membrane proteins into polymer-supported membranes for probing diffusion and interactions by single molecule techniques

We have established a robust and versatile analytical platform for probing membrane protein function in a defined lipid environment on solid supports. This approach is based on vesicle capturing onto an ultrathin poly(ethylene glycol) (PEG) polymer brush functionalized with fatty acid moieties and subsequent vesicle fusion into a contiguous membrane. In order to ensure efficient formation of these tethered polymer-supported membranes (PSM), very small unilamellar vesicles (VSUV) containing fluorescent lipids or model transmembrane proteins were generated by detergent depletion with cyclodextrin. Thus, very rapid reconstitution of membrane proteins into PSM was possible in a format compatible with microfluidics. Moreover, surfaces could be regenerated with detergent solution and reused multiple times. Lipid and protein diffusion in these membranes was investigated by fluorescence recovery after photobleaching, single molecule tracking, and fluorescence correlation spectroscopy. Full mobility of lipids and a high degree of protein mobility as well as homogeneous diffusion of both were observed. Quantitative ligand binding studies by solid phase detection techniques confirmed functional integrity of a transmembrane receptor reconstituted into these PSM. Colocomotion of individual ligand-receptor complexes was detected, demonstrating the applicability for single molecule fluorescence techniques.     

Ultrasensitive ambient mass spectrometric analysis with a pin-to-capillary flowing atmospheric-pressure afterglow source

The advent of ambient desorption/ionization mass spectrometry has resulted in a strong interest in ionization sources that are capable of direct analyte sampling and ionization. One source that has enjoyed increasing interest is the flowing atmospheric-pressure afterglow (FAPA). The FAPA has been proven capable of directly desorbing/ionizing samples in any phase (solid, liquid, or gas) and with impressive limits of detection (<100 fmol). The FAPA was also shown to be less affected by competitive-ionization matrix effects than other plasma-based sources. However, the original FAPA design exhibited substantial background levels, cluttered background spectra in the negative-ion mode, and significant oxidation of aromatic analytes, which ultimately compromised analyte identification and quantification. In the present study, a change in the FAPA configuration from a pin-to-plate to a pin-to-capillary geometry was found to vastly improve performance. Background signals in positive- and negative-ionization modes were reduced by 89% and 99%, respectively. Additionally, the capillary anode strongly reduced the amount of atomic oxygen that could cause oxidation of analytes. Temperatures of the gas stream that interacts with the sample, which heavily influences desorption capabilities, were compared between the two sources by means of IR thermography. The performance of the new FAPA configuration is evaluated through the determination of a variety of compounds in positive- and negative-ion mode, including agrochemicals and explosives. A detection limit of 4 amol was found for the direct determination of the agrochemical ametryn and appears to be spectrometer-limited. The ability to quickly screen for analytes in bulk liquid samples with the pin-to-capillary FAPA is also shown.     

Atmospheric CO2 measurements with a 2 μm airborne laser absorption spectrometer employing coherent detection

We report airborne measurements of CO(2) column abundance conducted during two 2009 campaigns using a 2.05 μm laser absorption spectrometer. The two flight campaigns took place in the California Mojave desert and in Oklahoma. The integrated path differential absorption (IPDA) method is used for the CO(2) column mixing ratio retrievals. This instrument and the data analysis methodology provide insight into the capabilities of the IPDA method for both airborne measurements and future global-scale CO(2) measurements from low Earth orbit pertinent to the NASA Active Sensing of CO(2) Emissions over Nights, Days, and Seasons mission. The use of a favorable absorption line in the CO(2) 2 μm band allows the on-line frequency to be displaced two (surface pressure) half-widths from line center, providing high sensitivity to the lower tropospheric CO(2). The measurement repeatability and measurement precision are in good agreement with predicted estimates. We also report comparisons with airborne in situ measurements conducted during the Oklahoma campaign.