Propagating intensity disturbances in polar corona as seen from AIA/SDO

Context. Polar corona is often explored to find the energy source for the acceleration of the fast solar wind. Earlier observations show omni-presence of quasi-periodic disturbances, traveling outward, which is believed to be caused by the ubiquitous presence of outward propagating waves. These waves, mostly of compressional type, might provide the additional momentum and heat required for the fast solar wind acceleration. It has been conjectured that these disturbances are not due to waves but high speed plasma outflows, which are difficult to distinguish using the current available techniques. Aims. With the unprecedented high spatial and temporal resolution of AIA/SDO, we search for these quasi-periodic disturbances in both plume and interplume regions of the polar corona. We investigate their nature of propagation and search for a plausible interpretation. We also aim to study their multi-thermal nature by using three different coronal passbands of AIA. Methods. We chose several clean plume and interplume structures and studied the time evolution of specific channels by making artificial slits along them. Taking the average across the slits, space-time maps are constructed and then filtration techniques are applied to amplify the low-amplitude oscillations. To suppress the effect of fainter jets, we chose wider slits than usual. Results. In almost all the locations chosen, in both plume and interplume regions we find the presence of propagating quasi-periodic disturbances, of periodicities ranging from 10-30 min. These are clearly seen in two channels and in a few cases out to very large distances (approximate to 250 `') off-limb, almost to the edge of the AIA field of view. The propagation speeds are in the range of 100-170 km s(-1). The average speeds are different for different passbands and higher in interplume regions. Conclusions. Propagating disturbances are observed, even after removing the effects of jets and are insensitive to changes in slit width. This indicates that a coherent mechanism is involved. In addition, the observed propagation speed varies between the different passpands, implying that these quasi-periodic intensity disturbances are possibly due to magneto-acoustic waves. The propagation speeds in interplume region are higher than in the plume region.

Fast image reconstruction for fluorescence microscopy

Real-time image reconstruction is essential for improving the temporal resolution of fluorescence microscopy. A number of unavoidable processes such as, optical aberration, noise and scattering degrade image quality, thereby making image reconstruction an ill-posed problem. Maximum likelihood is an attractive technique for data reconstruction especially when the problem is ill-posed. Iterative nature of the maximum likelihood technique eludes real-time imaging. Here we propose and demonstrate a compute unified device architecture (CUDA) based fast computing engine for real-time 3D fluorescence imaging. A maximum performance boost of 210x is reported. Easy availability of powerful computing engines is a boon and may accelerate to realize real-time 3D fluorescence imaging. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4754604]

Efficient asynchronous executions of AMR computations and visualization on a GPU system

Adaptive Mesh Refinement is a method which dynamically varies the spatio-temporal resolution of localized mesh regions in numerical simulations, based on the strength of the solution features. In-situ visualization plays an important role for analyzing the time evolving characteristics of the domain structures. Continuous visualization of the output data for various timesteps results in a better study of the underlying domain and the model used for simulating the domain. In this paper, we develop strategies for continuous online visualization of time evolving data for AMR applications executed on GPUs. We reorder the meshes for computations on the GPU based on the users input related to the subdomain that he wants to visualize. This makes the data available for visualization at a faster rate. We then perform asynchronous executions of the visualization steps and fix-up operations on the CPUs while the GPU advances the solution. By performing experiments on Tesla S1070 and Fermi C2070 clusters, we found that our strategies result in 60% improvement in response time and 16% improvement in the rate of visualization of frames over the existing strategy of performing fix-ups and visualization at the end of the timesteps.

Remote sensing applications in water resources

With the introduction of the earth observing satellites, remote sensing has become an important tool in analyzing the Earth's surface characteristics, and hence in supplying valuable information necessary for the hydrologic analysis. Due to their capability to capture the spatial variations in the hydro-meteorological variables and frequent temporal resolution sufficient to represent the dynamics of the hydrologic processes, remote sensing techniques have significantly changed the water resources assessment and management methodologies. Remote sensing techniques have been widely used to delineate the surface water bodies, estimate meteorological variables like temperature and precipitation, estimate hydrological state variables like soil moisture and land surface characteristics, and to estimate fluxes such as evapotranspiration. Today, near-real time monitoring of flood, drought events, and irrigation management are possible with the help of high resolution satellite data. This paper gives a brief overview of the potential applications of remote sensing in water resources.

Is Granger Causality a Viable Technique for Analyzing fMRI Data?

Multivariate neural data provide the basis for assessing interactions in brain networks. Among myriad connectivity measures, Granger causality (GC) has proven to be statistically intuitive, easy to implement, and generate meaningful results. Although its application to functional MRI (fMRI) data is increasing, several factors have been identified that appear to hinder its neural interpretability: (a) latency differences in hemodynamic response function (HRF) across different brain regions, (b) low-sampling rates, and (c) noise. Recognizing that in basic and clinical neuroscience, it is often the change of a dependent variable (e.g., GC) between experimental conditions and between normal and pathology that is of interest, we address the question of whether there exist systematic relationships between GC at the fMRI level and that at the neural level. Simulated neural signals were convolved with a canonical HRF, down-sampled, and noise-added to generate simulated fMRI data. As the coupling parameters in the model were varied, fMRI GC and neural GC were calculated, and their relationship examined. Three main results were found: (1) GC following HRF convolution is a monotonically increasing function of neural GC; (2) this monotonicity can be reliably detected as a positive correlation when realistic fMRI temporal resolution and noise level were used; and (3) although the detectability of monotonicity declined due to the presence of HRF latency differences, substantial recovery of detectability occurred after correcting for latency differences. These results suggest that Granger causality is a viable technique for analyzing fMRI data when the questions are appropriately formulated.

Co-registration of speech production datasets from electromagnetic articulography and real-time magnetic resonance imaging

This paper describes a spatio-temporal registration approach for speech articulation data obtained from electromagnetic articulography (EMA) and real-time Magnetic Resonance Imaging (rtMRI). This is motivated by the potential for combining the complementary advantages of both types of data. The registration method is validated on EMA and rtMRI datasets obtained at different times, but using the same stimuli. The aligned corpus offers the advantages of high temporal resolution (from EMA) and a complete mid-sagittal view (from rtMRI). The co-registration also yields optimum placement of EMA sensors as articulatory landmarks on the magnetic resonance images, thus providing richer spatio-temporal information about articulatory dynamics. (C) 2014 Acoustical Society of America

Real-time maximum a-posteriori image reconstruction for fluorescence microscopy

Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Prior image based temporally constrained reconstruction algorithm for magnetic resonance guided high intensity focused ultrasound

Purpose: A prior image based temporally constrained reconstruction ( PITCR) algorithm was developed for obtaining accurate temperature maps having better volume coverage, and spatial, and temporal resolution than other algorithms for highly undersampled data in magnetic resonance (MR) thermometry. Methods: The proposed PITCR approach is an algorithm that gives weight to the prior image and performs accurate reconstruction in a dynamic imaging environment. The PITCR method is compared with the temporally constrained reconstruction (TCR) algorithm using pork muscle data. Results: The PITCR method provides superior performance compared to the TCR approach with highly undersampled data. The proposed approach is computationally expensive compared to the TCR approach, but this could be overcome by the advantage of reconstructing with fewer measurements. In the case of reconstruction of temperature maps from 16% of fully sampled data, the PITCR approach was 1.57x slower compared to the TCR approach, while the root mean square error using PITCR is 0.784 compared to 2.815 with the TCR scheme. Conclusions: The PITCR approach is able to perform more accurate reconstructions of temperature maps compared to the TCR approach with highly undersampled data in MR guided high intensity focused ultrasound. (C) 2015 American Association of Physicists in Medicine.

Hydroacoustic surveys: a non-destructive approach to monitoring fish distributions at National Marine Sanctuaries

The science of fisheries acoustics and its applicability to resource management have evolved over the past several decades. This document provides a basic description of fisheries acoustics and recommendations on using this technology for research and monitoring of fish distributions and habitats within sanctuaries. It also describes recent efforts aimed at applying fisheries acoustics to Gray’s Reef National Marine Sanctuary (GRNMS) (Figure 1). Historically, methods to assess the underwater environment have included net trawls, diver censuses, hook and line, video, sonar and other techniques deployed in a variety of ways. Fisheries acoustics, using active sonar, relies on the physics of sound traveling through water to quantify the distribution of biota in the water column. By sending a signal of a given frequency through the water column and recording the time of travel and the strength of the reflected signal, it is possible to determine the size and location of fish and estimate biomass from the acoustic backscatter. As a fisheries assessment tool, active hydroacoustics technology is an efficient, non-intrusive method of mapping the water column at a very fine spatial and temporal resolution. It provides a practical alternative to bottom and mid-water trawls, which are not allowed at GRNMS. Passive acoustics, which uses underwater hydrophones to record man-made and natural sounds such as fish spawning calls and sounds produced by marine mammals for communication and echolocation, can provide a useful, complementary survey tool. This report primarily deals with active acoustics, although the integration of active and passive acoustics is addressed as well. (PDF contains 32 pages)

Variability in the air-sea interaction patterns and timescales within the south-eastern Bay of Biscay, as observed by HF radar data

Two high-frequency (HF) radar stations were installed on the coast of the south-eastern Bay of Biscay in 2009, providing high spatial and temporal resolution and large spatial coverage of currents in the area for the first time. This has made it possible to quantitatively assess the air-sea interaction patterns and timescales for the period 2009-2010. The analysis was conducted using the Barnett-Preisendorfer approach to canonical correlation analysis (CCA) of reanalysis surface winds and HF radar-derived surface currents. The CCA yields two canonical patterns: the first wind-current interaction pattern corresponds to the classical Ekman drift at the sea surface, whilst the second describes an anticyclonic/cyclonic surface circulation. The results obtained demonstrate that local winds play an important role in driving the upper water circulation. The wind-current interaction timescales are mainly related to diurnal breezes and synoptic variability. In particular, the breezes force diurnal currents in waters of the continental shelf and slope of the south-eastern Bay. It is concluded that the breezes may force diurnal currents over considerably wider areas than that covered by the HF radar, considering that the northern and southern continental shelves of the Bay exhibit stronger diurnal than annual wind amplitudes.

Wave Sensor Technologies, St Petersburg, Florida, March 7-9, 2007: workshop proceedings

The Alliance for Coastal Technologies (ACT) convened a workshop on "Wave Sensor Technologies" in St. Petersburg, Florida on March 7-9, 2007, hosted by the University of South Florida (USF) College of Marine Science, an ACT partner institution. The primary objectives of this workshop were to: 1) define the present state of wave measurement technologies, 2) identify the major impediments to their advancement, and 3) make strategic recommendations for future development and on the necessary steps to integrate wave measurement sensors into operational coastal ocean observing systems. The participants were from various sectors, including research scientists, technology developers and industry providers, and technology users, such as operational coastal managers and coastal decision makers. Waves consistently are ranked as a critical variable for numerous coastal issues, from maritime transportation to beach erosion to habitat restoration. For the purposes of this workshop, the participants focused on measuring "wind waves" (i.e., waves on the water surface, generated by the wind, restored by gravity and existing between approximately 3 and 30-second periods), although it was recognized that a wide range of both forced and free waves exist on and in the oceans. Also, whereas the workshop put emphasis on the nearshore coastal component of wave measurements, the participants also stressed the importance of open ocean surface waves measurement. Wave sensor technologies that are presently available for both environments include bottom-mounted pressure gauges, surface following buoys, wave staffs, acoustic Doppler current profilers, and shore-based remote sensing radar instruments. One of the recurring themes of workshop discussions was the dichotomous nature of wave data users. The two separate groups, open ocean wave data users and the nearshore/coastal wave data users, have different requirements. Generally, the user requirements increase both in spatial/temporal resolution and precision as one moves closer to shore. Most ocean going mariners are adequately satisfied with measurements of wave period and height and a wave general direction. However, most coastal and nearshore users require at least the first five Fourier parameters ("First 5"): wave energy and the first four directional Fourier coefficients. Furthermore, wave research scientists would like sensors capable of providing measurements beyond the first four Fourier coefficients. It was debated whether or not high precision wave observations in one location can take the place of a less precise measurement at a different location. This could be accomplished by advancing wave models and using wave models to extend data to nearby areas. However, the consensus was that models are no substitution for in situ wave data.[PDF contains 26 pages]

Genetically engineered sensors of cell signaling

Measuring electrical activity in large numbers of cells with high spatial and temporal resolution is a fundamental problem for the study of neural development and information processing. To address this problem, we have constructed FlaSh: a novel, genetically-encoded probe that can be used to measure trans-membrane voltage in single cells. We fused a modified green fluorescent protein (GFP) into a voltage-sensitive potassium channel so that voltage dependent rearrangements in the potassium channel induce changes in the fluorescence of GFP. A voltage sensor encoded into DNA has the advantage that it may be introduced into an organism non-invasively and targeted to specific developmental stages, brain regions, cell types, and sub-cellular compartments.

We also describe modifications to FlaSh that shift its color, kinetics, and dynamic range. We used multiple green fluorescent proteins to produce variants of the FlaSh sensor that generate ratiometric signal output via fluorescence resonance energy transfer (FRET). Finally, we describe initial work toward FlaSh variants that are sensitive to G-protein coupled receptor (GPCR) activation. These sensors can be used to design functional assays for receptor activation in living cells.

On Ultrafast Time-Domain TeraHertz Spectroscopy in the Condensed Phase: Linear Spectroscopic Measurements of Hydrogen-Bond Dynamics of Astrochemical Ice Analogs and Nonlinear TeraHertz Kerr Effect Measurements of Vibrational Quantum Beats

Much of the chemistry that affects life on planet Earth occurs in the condensed phase. The TeraHertz (THz) or far-infrared (far-IR) region of the electromagnetic spectrum (from 0.1 THz to 10 THz, 3 cm^-1 to 300 cm^-1, or 3000 μm to 30 μm) has been shown to provide unique possibilities in the study of condensed-phase processes. The goal of this work is to expand the possibilities available in the THz region and undertake new investigations of fundamental interest to chemistry. Since we are fundamentally interested in condensed-phase processes, this thesis focuses on two areas where THz spectroscopy can provide new understanding: astrochemistry and solvation science. To advance these fields, we had to develop new instrumentation that would enable the experiments necessary to answer new questions in either astrochemistry or solvation science. We first developed a new experimental setup capable of studying astrochemical ice analogs in both the TeraHertz (THz), or far-Infrared (far-IR), region (0.3 - 7.5 THz; 10 - 250 cm^-1) and the mid-IR (400 - 4000 cm^-1). The importance of astrochemical ices lies in their key role in the formation of complex organic molecules, such as amino acids and sugars in space. Thus, the instruments are capable of performing variety of spectroscopic studies that can provide especially relevant laboratory data to support astronomical observations from telescopes such as the Herschel Space Telescope, the Stratospheric Observatory for Infrared Astronomy (SOFIA), and the Atacama Large Millimeter Array (ALMA). The experimental apparatus uses a THz time-domain spectrometer, with a 1750/875 nm plasma source and a GaP detector crystal, to cover the bandwidth mentioned above with ~10 GHz (~0.3 cm^-1) resolution.

Using the above instrumentation, experimental spectra of astrochemical ice analogs of water and carbon dioxide in pure, mixed, and layered ices were collected at different temperatures under high vacuum conditions with the goal of investigating the structure of the ice. We tentatively observe a new feature in both amorphous solid water and crystalline water at 33 cm^-1 (1 THz). In addition, our studies of mixed and layered ices show how it is possible to identify the location of carbon dioxide as it segregates within the ice by observing its effect on the THz spectrum of water ice. The THz spectra of mixed and layered ices are further analyzed by fitting their spectra features to those of pure amorphous solid water and crystalline water ice to quantify the effects of temperature changes on structure. From the results of this work, it appears that THz spectroscopy is potentially well suited to study thermal transformations within the ice.

To advance the study of liquids with THz spectroscopy, we developed a new ultrafast nonlinear THz spectroscopic technique: heterodyne-detected, ultrafast THz Kerr effect (TKE) spectroscopy. We implemented a heterodyne-detection scheme into a TKE spectrometer that uses a stilbazoiumbased THz emitter, 4-N,N-dimethylamino-4-N-methyl-stilbazolium 2,4,6-trimethylbenzenesulfonate (DSTMS), and high numerical aperture optics which generates THz electric field in excess of 300 kV/cm, in the sample. This allows us to report the first measurement of quantum beats at terahertz (THz) frequencies that result from vibrational coherences initiated by the nonlinear, dipolar interaction of a broadband, high-energy, (sub)picosecond THz pulse with the sample. Our instrument improves on both the frequency coverage, and sensitivity previously reported; it also ensures a backgroundless measurement of the THz Kerr effect in pure liquids. For liquid diiodomethane, we observe a quantum beat at 3.66 THz (122 cm^-1), in exact agreement with the fundamental transition frequency of the υ4 vibration of the molecule. This result provides new insight into dipolar vs. Raman selection rules at terahertz frequencies.

To conclude we discuss future directions for the nonlinear THz spectroscopy in the Blake lab. We report the first results from an experiment using a plasma-based THz source for nonlinear spectroscopy that has the potential to enable nonlinear THz spectra with a sub-100 fs temporal resolution, and how the optics involved in the plasma mechanism can enable THz pulse shaping. Finally, we discuss how a single-shot THz detection scheme could improve the acquisition of THz data and how such a scheme could be implemented in the Blake lab. The instruments developed herein will hopefully remain a part of the groups core competencies and serve as building blocks for the next generation of THz instrumentation that pushes the frontiers of both chemistry and the scientific enterprise as a whole.

Modeling habits as self-sustaining patterns of sensorimotor behavior

In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel "iterant deformable sensorimotor medium (IDSM)," designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated robot, and show that under certain conditions, the IDSM conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the robot's body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor "meso-scale" between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

Seasonal variability in ichthyoplankton abundance and assemblage composition in the northern Gulf of Mexico off Alabama

Multiyear ichthyoplankton surveys used to monitor larval fish seasonality, abundance, and assemblage structure can provide early indicators of regional ecosystem changes. Numerous ichthyoplankton surveys have been conducted in the northern Gulf of Mexico, but few have had high levels of temporal resolution and sample replication. In this study, ichthyoplankton samples were collected monthly (October 2004–October 2006) at a single station off the coast of Alabama as part of a long-term biological survey. Four seasonal periods were identified from observed and historic water temperatures, including a relatively long (June–October) “summer” period (water temperature >26°C). Fish egg abundance, total larval abundance, and larval taxonomic diversity were significantly related to water temperature (but not salinity), with peaks in the spring, spring–summer, and summer periods, respectively. Larvae collected during the survey represented 58 different families, of which engraulids, sciaenids, carangids, and clupeids were the most prominent. The most abundant taxa collected were unidentified engraulids (50%), sand seatrout (Cynoscion arenarius, 7.5%), Atlantic bumper (Chloroscombrus chrysurus, 5.4%), Atlantic croaker (Micropogonias undulatus, 4.4%), Gulf menhaden (Brevoortia patronus, 3.8%), and unidentified gobiids (3.6%). Larval concentrations for dominant taxa were highly variable between years, but the timing of seasonal occurrence for these taxa was relatively consistent. Documented increases in sea surface temperature on the Alabama shelf may have various implications for larval fish dynamics, as indicated by the presence of tropical larval forms (e.g., fistularids, labrids, scarids, and acanthurids) in our ichthyoplankton collections and in recent juvenile surveys of Alabama and northern Gulf of Mexico seagrass habitats.