Ferrochelatase is a conserved downstream target of the blue light-sensing White collar complex in fungi.

Light is a universal signal perceived by organisms, including fungi, in which light regulates common and unique biological processes depending on the species. Previous research has established that conserved proteins, originally called White collar 1 and 2 from the ascomycete Neurospora crassa, regulate UV/blue light sensing. Homologous proteins function in distant relatives of N. crassa, including the basidiomycetes and zygomycetes, which diverged as long as a billion years ago. Here we conducted microarray experiments on the basidiomycete fungus Cryptococcus neoformans to identify light-regulated genes. Surprisingly, only a single gene was induced by light above the commonly used twofold threshold. This gene, HEM15, is predicted to encode a ferrochelatase that catalyses the final step in haem biosynthesis from highly photoreactive porphyrins. The C. neoformans gene complements a Saccharomyces cerevisiae hem15Delta strain and is essential for viability, and the Hem15 protein localizes to mitochondria, three lines of evidence that the gene encodes ferrochelatase. Regulation of HEM15 by light suggests a mechanism by which bwc1/bwc2 mutants are photosensitive and exhibit reduced virulence. We show that ferrochelatase is also light-regulated in a white collar-dependent fashion in N. crassa and the zygomycete Phycomyces blakesleeanus, indicating that ferrochelatase is an ancient target of photoregulation in the fungal kingdom.

Imaging through turbulence using compressive coherence sensing.

Previous studies have shown that the isoplanatic distortion due to turbulence and the image of a remote object may be jointly estimated from the 4D mutual intensity across an aperture. This Letter shows that decompressive inference on a 2D slice of the 4D mutual intensity, as measured by a rotational shear interferometer, is sufficient for estimation of sparse objects imaged through turbulence. The 2D slice is processed using an iterative algorithm that alternates between estimating the sparse objects and estimating the turbulence-induced phase screen. This approach may enable new systems that infer object properties through turbulence without exhaustive sampling of coherence functions.

Calibrating single-ended fiber-optic Raman spectra distributed temperature sensing data.

Hydrologic research is a very demanding application of fiber-optic distributed temperature sensing (DTS) in terms of precision, accuracy and calibration. The physics behind the most frequently used DTS instruments are considered as they apply to four calibration methods for single-ended DTS installations. The new methods presented are more accurate than the instrument-calibrated data, achieving accuracies on the order of tenths of a degree root mean square error (RMSE) and mean bias. Effects of localized non-uniformities that violate the assumptions of single-ended calibration data are explored and quantified. Experimental design considerations such as selection of integration times or selection of the length of the reference sections are discussed, and the impacts of these considerations on calibrated temperatures are explored in two case studies.

Adaptive temporal compressive sensing for video

This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to realtime implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems. © 2013 IEEE.

Task-driven adaptive statistical compressive sensing of gaussian mixture models

A framework for adaptive and non-adaptive statistical compressive sensing is developed, where a statistical model replaces the standard sparsity model of classical compressive sensing. We propose within this framework optimal task-specific sensing protocols specifically and jointly designed for classification and reconstruction. A two-step adaptive sensing paradigm is developed, where online sensing is applied to detect the signal class in the first step, followed by a reconstruction step adapted to the detected class and the observed samples. The approach is based on information theory, here tailored for Gaussian mixture models (GMMs), where an information-theoretic objective relationship between the sensed signals and a representation of the specific task of interest is maximized. Experimental results using synthetic signals, Landsat satellite attributes, and natural images of different sizes and with different noise levels show the improvements achieved using the proposed framework when compared to more standard sensing protocols. The underlying formulation can be applied beyond GMMs, at the price of higher mathematical and computational complexity. © 1991-2012 IEEE.

Hazard and risk assessment from Hurricane Ivan (2004) in Grenada using Geographical Information Systems and remote sensing

Hurricanes are destructive storms with strong winds, intense storm surges, and heavy rainfall. The resulting impact from a hurricane can include structural damage to buildings and infrastructure, flooding, and ultimately loss of human life. This paper seeks to identify the impact of Hurricane Ivan on the aected population of Grenada, one of the Caribbean islands. Hurricane Ivan made landfall on 7th September 2004 and resulted in 80% of the population being adversely aected. The methods that were used to model these impacts involved performing hazard and risk assessments using GIS and remote sensing techniques. Spatial analyses were used to create a hazard and a risk map. Hazards were identied initially as those caused by storm surges, severe winds speeds, and flooding events related to Hurricane Ivan. These estimated hazards were then used to create a risk map. An innovative approach was adopted, including the use of hillshading to assess the damage caused by high wind speeds. This paper explains in detail the methodology used and the results produced.

Annual westward propagating anomalies near 26 degrees N and eddy generation south of the Canary Islands: remote sensing (altimeter/SeaWIFS) and in situ measurement

Seasonal changes in altimeter data are derived for the North Atlantic Ocean. Altimeter data are then used to examine annually propagating structure along 26 degree N. By averaging the altimeter data into monthly values or by Fourier analysis, a positive anomaly can be followed from 17 degree W to similar to 50 degree W along similar to 26 degree N. The methods give a westward travel speed of 1 degree of longitude a month and a half-life of one year for the average decaying structure. At similar to 50 degree W 26 degree N, the average structure is about 2.8 years old with an elevation signal of similar to 1 cm, having gravelled similar to 3300 km westward. The mean positive anomaly results from the formation of anticyclonic eddies which are generally formed annually south of the Canary Islands by late summer and which then travel westward near 26 degree N. Individual eddy structure along 26 degree N is examined and related to in situ measurements and anomalies in the annual seasonal concentration cycle of SeaWiFS chlorophyll-a.

Ocean structure and climate (Eastern North Atlantic): in situ measurement and remote sensing

Structure and climate of the east North Atlantic are appraised within a framework of in situ measurement and altimeter remote sensing from 0 degree - 60 degree N. Long zonal expendable bathythermograph /conductivity-temperature-depth probe sections show repeating internal structure in the North Atlantic Ocean. Drogued buoys and subsurface floats give westward speeds for eddies and wavelike structure. Records from longterm current meter deployments give the periodicity of the repeating structure. Eddy and wave characteristics of period, size or wavelength, westward propagation speed, and mean currents are derived at 20 degree N, 26 degree N, 32.5 degree N, 36 degree N and 48 degree N from in situ measurements in the Atlantic Ocean. It is shown that ocean wave and eddy-like features measured in situ correlate with altimeter structure. Interior ocean wave crests or cold dome-like temperature structures are cyclonic and have negative surface altimeter anomalies; mesoscale internal wave troughs or warm structures are anticyclonic and have positive surface height anomalies. Along the Eastern Boundary, flows and temperature climate are examined in terms of sla and North Atlantic Oscillation (NAO) Index. Longterm changes in ocean climate and circulation are derived from sla data. It is shown that longterm changes from 1992 to 2002 in the North Atlantic Current and the Subtropical Gyre transport determined from sla data correlate with winter NAO Index such that maximum flow conditions occurred in 1995 and 2000. Minimum circulation conditions occurred between 1996-1998. Years of extreme negative winter NAO Index result in enhanced poleward flow along the Eastern Boundary and anomalous winter warming along the West European Continental Slope as was measured in 1990, 1996, 1998 and 2001.

Position and structure of the subtropical/Azores front region from combined Lagrangian and remote sensing (IR/altimeter/SeaWIFS) measurements

The position and structure of the North Atlantic Subtropical Front is studied using Lagrangian flow tracks and remote sensing (AVHRR imagery: TOPEX/POSEIDON altimetry: SeaWiFS) in a broad region ( similar to 31 degree to similar to 36 degree N) of marked gradient of dynamic height (Azores Current) that extends from the Mid-Atlantic Ridge (MAR), near similar to 40 degree W, to the Eastern Boundary ( similar to 10 degree W). Drogued Argos buoy and ALACE tracks are superposed on infrared satellite images in the Subtropical Front region. Cold (cyclonic) structures, called storms, and warm (anticyclonic) structures of 100-300 km in size can be found on the south side of the Subtropical Front outcrop, which has a temperature contrast of about 1 degree C that can be followed for similar to 2500 km near 35 degree N. Warmer water adjacent to the outcrop is flowing eastward (Azores Current) but some warm water is returned westward about 300 km to the south (southern Counterflow). Estimates of horizontal diffusion in a Storm (D=2.2t10 super(2) m super(2) s super(-1)) and in the Subtropical Front region near 200 m depth (D sub(x)=1.3t10 super(4) m super(2) s super(-1), D sub(y)=2.6t10 super(3) m super(2) s super(-1)) are made from the Lagrangian tracks. Altimeter and in situ measurements show that Storms track westwards. Storms are separated by about 510 km and move westward at 2.7 km d super(-1). Remote sensing reveals that some initial structures start evolving as far east as 23 degree W but are more organized near 29 degree W and therefore Storms are about 1 year old when they reach the MAR (having travelled a distance of 1000 km). Structure and seasonality in SeaWiFS data in the region is examined.