Simultaneous multilayer scanning and detection for multiphoton fluorescence microscopy

Fast three-dimensional (3D) imaging requires parallel optical slicing of a specimen with an efficient detection scheme. The generation of multiple localized dot-like excitation structures solves the problem of simultaneous slicing multiple specimen layers, but an efficient detection scheme is necessary. Confocal theta detection (detection at 90 degrees to the optical axis) provides a suitable detection platform that is capable of cross-talk-free fluorescence detection from each nanodot (axial dimension approximate to 150 nm). Additionally, this technique has the unique feature of imaging a specimen at a large working distance with super-resolution capabilities. Polarization studies show distinct field structures for fixed and fluid samples, indicating a non-negligible field-dipole interaction. The realization of the proposed imaging technique will advance and diversify multiphoton fluorescence microscopy for numerous applications in nanobioimaging and optical engineering.

Object Tracking Using Motion Direction Detection

We present an algorithm for tracking objects in a video sequence, based on a novel approach for motion detection. We do not estimate the velocity �eld. In-stead we detect only the direction of motion at edge points and thus isolate sets of points which are moving coherently. We use a Hausdor� distance based matching algorithm to match point sets in local neighborhood and thus track objects in a video sequence. We show through some examples the e�ectiveness of the algo- rithm.

Understanding How the Brain Changes Its Mind: Microstimulation in the Macaque Frontal Eye Field Reveals How Saccade Plans Are Changed

Accumulator models that integrate incoming sensory information into motor plans provide a robust framework to understand decision making. However, their applicability to situations that demand a change of plan raises an interesting problem for the brain. This is because interruption of the current motor plan must occur by a competing motor plan, which is necessarily weaker in strength. To understand how changes of mind get expressed in behavior, we used a version of the double-step task called the redirect task, in which monkeys were trained to modify a saccade plan. We microstimulated the frontal eye fields during redirect behavior and systematically measured the deviation of the evoked saccade from the response field to causally track the changing saccade plan. Further, to identify the underlying mechanisms, eight different computational models of redirect behavior were assessed. It was observed that the model that included an independent, spatially specific inhibitory process, in addition to the two accumulators representing the preparatory processes of initial and final motor plans, best predicted the performance and the pattern of saccade deviation profile in the task. Such an inhibitory process suppressed the preparation of the initial motor plan, allowing the final motor plan to proceed unhindered. Thus, changes of mind are consistent with the notion of a spatially specific, inhibitory process that inhibits the current inappropriate plan, allowing expression of the new plan.

Delay Optimal Event Detection on Ad Hoc Wireless Sensor Networks

We consider a small extent sensor network for event detection, in which nodes periodically take samples and then contend over a random access network to transmit their measurement packets to the fusion center. We consider two procedures at the fusion center for processing the measurements. The Bayesian setting, is assumed, that is, the fusion center has a prior distribution on the change time. In the first procedure, the decision algorithm at the fusion center is network-oblivious and makes a decision only when a complete vector of measurements taken at a sampling instant is available. In the second procedure, the decision algorithm at the fusion center is network-aware and processes measurements as they arrive, but in a time-causal order. In this case, the decision statistic depends on the network delays, whereas in the network-oblivious case, the decision statistic does not. This yields a Bayesian change-detection problem with a trade-off between the random network delay and the decision delay that is, a higher sampling rate reduces the decision delay but increases the random access delay. Under periodic sampling, in the network-oblivious case, the structure of the optimal stopping rule is the same as that without the network, and the optimal change detection delay decouples into the network delay and the optimal decision delay without the network. In the network-aware case, the optimal stopping problem is analyzed as a partially observable Markov decision process, in which the states of the queues and delays in the network need to be maintained. A sufficient decision statistic is the network state and the posterior probability of change having occurred, given the measurements received and the state of the network. The optimal regimes are studied using simulation.

Fluoranthene based fluorescent chemosensors for detection of explosive nitroaromatics

A novel fluoranthene based fluorescent chemosensor for the detection of picric acid (PA) at the parts per billion (ppb) level was evaluated. Static fluorescence quenching was the dominant process by intercalative pi-pi interaction between fluoranthene (S-1) and nitroaromatics.

Incremental Cycle Detection, Topological Ordering, and Strong Component Maintenance

We present two online algorithms for maintaining a topological order of a directed n-vertex acyclic graph as arcs are added, and detecting a cycle when one is created. Our first algorithm handles m arc additions in O(m(3/2)) time. For sparse graphs (m/n = O(1)), this bound improves the best previous bound by a logarithmic factor, and is tight to within a constant factor among algorithms satisfying a natural locality property. Our second algorithm handles an arbitrary sequence of arc additions in O(n(5/2)) time. For sufficiently dense graphs, this bound improves the best previous bound by a polynomial factor. Our bound may be far from tight: we show that the algorithm can take Omega(n(2)2 root(2lgn)) time by relating its performance to a generalization of the k-levels problem of combinatorial geometry. A completely different algorithm running in Theta (n(2) log n) time was given recently by Bender, Fineman, and Gilbert. We extend both of our algorithms to the maintenance of strong components, without affecting the asymptotic time bounds.

Mutual inhibition and capacity sharing during parallel preparation of serial eye movements

Many common activities, like reading, scanning scenes, or searching for an inconspicuous item in a cluttered environment, entail serial movements of the eyes that shift the gaze from one object to another. Previous studies have shown that the primate brain is capable of programming sequential saccadic eye movements in parallel. Given that the onset of saccades directed to a target are unpredictable in individual trials, what prevents a saccade during parallel programming from being executed in the direction of the second target before execution of another saccade in the direction of the first target remains unclear. Using a computational model, here we demonstrate that sequential saccades inhibit each other and share the brain's limited processing resources (capacity) so that the planning of a saccade in the direction of the first target always finishes first. In this framework, the latency of a saccade increases linearly with the fraction of capacity allocated to the other saccade in the sequence, and exponentially with the duration of capacity sharing. Our study establishes a link between the dual-task paradigm and the ramp-to-threshold model of response time to identify a physiologically viable mechanism that preserves the serial order of saccades without compromising the speed of performance.

Vehicle Detection Tool - VDtect

The report talks about the implementation of Vehicle Detection tool using opensource software - WxPython. The main functionality of this tool includes collection of data, plotting of magnetometer data and the count of the vehicles detected. The report list about how installation process and various functionality of the tool.

Ultrasonic Guided Wave Characterization and Damage Detection in Foam-core Sandwich Panel using PWAS and LDV

Lamb wave type guided wave propagation in foam core sandwich structures and detectability of damages using spectral analysis method are reported in this paper. An experimental study supported by theoretical evaluation of the guided wave characteristics is presented here that shows the applicability of Lamb wave type guided ultrasonic wave for detection of damage in foam core sandwich structures. Sandwich beam specimens were fabricated with 10 mm thick foam core and 0.3 mm thick aluminum face sheets. Thin piezoelectric patch actuators and sensors are used to excite and sense guided wave. Group velocity dispersion curves and frequency response of sensed signal are obtained experimentally. The nature of damping present in the sandwich panel is monitored by measuring the sensor signal amplitude at various different distances measured from the center of the linear phased array. Delaminations of increasing width are created and detected experimentally by pitch-catch interrogation with guided waves and wavelet transform of the sensed signal. Signal amplitudes are analyzed for various different sizes of damages to differentiate the damage size/severity. A sandwich panel is also fabricated with a planer dimension of 600 mm x 400 mm. Release film delamination is introduced during fabrication. Non-contact Laser Doppler Vibrometer (LDV) is used to scan the panel while exciting with a surface bonded piezoelectric actuator. Presence of damage is confirmed by the reflected wave fringe pattern obtained from the LDV scan. With this approach it is possible to locate and monitor the damages by tracking the wave packets scattered from the damages.

Guided Wave based Damage Detection in a Composite T-joint using 3D Scanning Laser Doppler Vibrometer

Composite T-joints are commonly used in modern composite airframe, pressure vessels and piping structures, mainly to increase the bending strength of the joint and prevents buckling of plates and shells, and in multi-cell thin-walled structures. Here we report a detailed study on the propagation of guided ultrasonic wave modes in a composite T-joint and their interactions with delamination in the co-cured co-bonded flange. A well designed guiding path is employed wherein the waves undergo a two step mode conversion process, one is due to the web and joint filler on the back face of the flange and the other is due to the delamination edges close to underneath the accessible surface of the flange. A 3D Laser Doppler Vibrometer is used to obtain the three components of surface displacements/velocities of the accessible face of the flange of the T-joint. The waves are launched by a piezo ceramic wafer bonded on to the back surface of the flange. What is novel in the proposed method is that the location of any change in material/geometric properties can be traced by computing a frequency domain power flow along a scan line. The scan line can be chosen over a grid either during scan or during post-processing of the scan data off-line. The proposed technique eliminates the necessity of baseline data and disassembly of structure for structural interrogation.