A new mild hyperthermia device to treat vascular involvement in cancer surgery

Abstract Surgical margin status in cancer surgery represents an important oncologic parameter affecting overall prognosis. The risk of disease recurrence is minimized and survival often prolonged if margin-negative resection can be accomplished during cancer surgery. Unfortunately, negative margins are not always surgically achievable due to tumor invasion into adjacent tissues or involvement of critical vasculature. Herein, we present a novel intra-operative device created to facilitate a uniform and mild heating profile to cause hyperthermic destruction of vessel-encasing tumors while safeguarding the encased vessel. We use pancreatic ductal adenocarcinoma as an in vitro and an in vivo cancer model for these studies as it is a representative model of a tumor that commonly involves major mesenteric vessels. In vitro data suggests that mild hyperthermia (41–46 °C for ten minutes) is an optimal thermal dose to induce high levels of cancer cell death, alter cancer cell’s proteomic profiles and eliminate cancer stem cells while preserving non-malignant cells. In vivo and in silico data supports the well-known phenomena of a vascular heat sink effect that causes high temperature differentials through tissues undergoing hyperthermia, however temperatures can be predicted and used as a tool for the surgeon to adjust thermal doses delivered for various tumor margins

Optical Flow on Moving Manifolds

Optical flow is a powerful tool for the study and analysis of motion in a sequence of images. In this article we study a Horn-Schunck type spatio-temporal regularization functional for image sequences that have a non-Euclidean, time varying image domain. To that end we construct a Riemannian metric that describes the deformation and structure of this evolving surface. The resulting functional can be seen as natural geometric generalization of previous work by Weickert and Schn\"orr (2001) and Lef\`evre and Baillet (2008) for static image domains. In this work we show the existence and wellposedness of the corresponding optical flow problem and derive necessary and sufficient optimality conditions. We demonstrate the functionality of our approach in a series of experiments using both synthetic and real data.Comment: 26 pages, 6 figure

LOW-COST STRUCTURED-LIGHT 3D CAPTURE SYSTEM DESIGN

To date, three-dimensional measurement is a very important and popular topic in computer vision. Most of the 3D capture products currently in the market are high-end and pricey. They are not targeted for consumers, but rather for research, medical, or industrial usage. Very few aim to provide a solution for home and small business applications. Our goal is to fill in this gap by only using low-cost components to build a 3D capture system that can satisfy the needs of this market segment. In our research, we present a low-cost 3D capture system based on the structured-light method. The system is built around the HP TopShot LaserJet Pro M275. For our capture device, we use the 8.0 Mpixel camera that is part of the M275. We augment this hardware with two 3M MPro 150 VGA (640×480) pocket projectors. We also describe an analytical approach to predicting the achievable resolution of the reconstructed 3D object based on differentials and small signal theory, and an experimental procedure for validating that the system under test meets the specifications for reconstructed object resolution that are predicted by our analytical model. By comparing our experimental measurements from the camera-projector system with the simulation results based on the model for this system, we conclude that our prototype system has been correctly configured and calibrated and that with the analytical models, we have an effective means for specifying system parameters to achieve a given target resolution for the reconstructed object

A multidisciplinary approach to investigate the osteobiography of the Roman Imperial population from Muracciola Torresina (Palestrina, Rome, Italy)

The present research provides the osteobiographical reconstruction of the Roman Imperial population of the rural area of Muracciola Torresina (Palestrina, Rome, Italy) through an innovative multidisciplinary approach, combining evidence from skeletal biology, biomolecules and archaeobotany. The excavation of the site, unearthed 76 individuals: 84.2% adults and 15.8% non-adults. Morphological examination showed a higher prevalence of females with respect to males (M:F = 0.89). Musculoskeletal stress marker analysis highlighted a probable division of daily tasks between sexes; the observed modifications mainly affected the upper limbs with a particular involvement of shoulder and elbow joints. The population seems to have experienced physically strenuous life conditions, as suggested by the high frequency of degenerative and infectious diseases. Carbon and nitrogen stable isotope data supported an omnivorous diet mainly based on C3 plants and terrestrial animal protein. No statistically significant difference was found between sexes or age classes, even though a discrete variability of nitrogen isotopic values was observed which was hypothesized to reflect the consumption of pulses by certain individuals with the lowest values. Microscopic analysis of dental calculus detected Triticeae starch granules in the majority of the analyzed individuals. Chromatographic profiles additionally revealed the presence of ephedrine derivatives in the calculus of two individuals, an alkaloid which might indicate the consumption of Ephedra species used as medicinal plant due to its bronchodilator, nasal decongestant and vasoconstrictor properties. This use of multiple cutting-edge techniques has revealed a detailed snapshot of the diet and lifeways of the first Roman Imperial population to be recovered from the area of ancient Praeneste

Optimization Of Zonal Wavefront Estimation And Curvature Measurements

Optical testing in adverse environments, ophthalmology and applications where characterization by curvature is leveraged all have a common goal: accurately estimate wavefront shape. This dissertation investigates wavefront sensing techniques as applied to optical testing based on gradient and curvature measurements. Wavefront sensing involves the ability to accurately estimate shape over any aperture geometry, which requires establishing a sampling grid and estimation scheme, quantifying estimation errors caused by measurement noise propagation, and designing an instrument with sufficient accuracy and sensitivity for the application. Starting with gradient-based wavefront sensing, a zonal least-squares wavefront estimation algorithm for any irregular pupil shape and size is presented, for which the normal matrix equation sets share a pre-defined matrix. A Gerchberg–Saxton iterative method is employed to reduce the deviation errors in the estimated wavefront caused by the pre-defined matrix across discontinuous boundary. The results show that the RMS deviation error of the estimated wavefront from the original wavefront can be less than λ/130~ λ/150 (for λ equals 632.8nm) after about twelve iterations and less than λ/100 after as few as four iterations. The presented approach to handling irregular pupil shapes applies equally well to wavefront estimation from curvature data. A defining characteristic for a wavefront estimation algorithm is its error propagation behavior. The error propagation coefficient can be formulated as a function of the eigenvalues of the wavefront estimation-related matrices, and such functions are established for each of the basic estimation geometries (i.e. Fried, Hudgin and Southwell) with a serial numbering scheme, where a square sampling grid array is sequentially indexed row by row. The results show that with the wavefront piston-value fixed, the odd-number grid sizes yield lower error propagation than the even-number grid sizes for all geometries. The Fried geometry either allows sub-sized wavefront estimations within the testing domain or yields a two-rank deficient estimation matrix over the full aperture; but the latter usually suffers from high error propagation and the waffle mode problem. Hudgin geometry offers an error propagator between those of the Southwell and the Fried geometries. For both wavefront gradient-based and wavefront difference-based estimations, the Southwell geometry is shown to offer the lowest error propagation with the minimum-norm least-squares solution. Noll’s theoretical result, which was extensively used as a reference in the previous literature for error propagation estimate, corresponds to the Southwell geometry with an odd-number grid size. For curvature-based wavefront sensing, a concept for a differential Shack-Hartmann (DSH) curvature sensor is proposed. This curvature sensor is derived from the basic Shack-Hartmann sensor with the collimated beam split into three output channels, along each of which a lenslet array is located. Three Hartmann grid arrays are generated by three lenslet arrays. Two of the lenslets shear in two perpendicular directions relative to the third one. By quantitatively comparing the Shack-Hartmann grid coordinates of the three channels, the differentials of the wavefront slope at each Shack-Hartmann grid point can be obtained, so the Laplacian curvatures and twist terms will be available. The acquisition of the twist terms using a Hartmann-based sensor allows us to uniquely determine the principal curvatures and directions more accurately than prior methods. Measurement of local curvatures as opposed to slopes is unique because curvature is intrinsic to the wavefront under test, and it is an absolute as opposed to a relative measurement. A zonal least-squares-based wavefront estimation algorithm was developed to estimate the wavefront shape from the Laplacian curvature data, and validated. An implementation of the DSH curvature sensor is proposed and an experimental system for this implementation was initiated. The DSH curvature sensor shares the important features of both the Shack-Hartmann slope sensor and Roddier’s curvature sensor. It is a two-dimensional parallel curvature sensor. Because it is a curvature sensor, it provides absolute measurements which are thus insensitive to vibrations, tip/tilts, and whole body movements. Because it is a two-dimensional sensor, it does not suffer from other sources of errors, such as scanning noise. Combined with sufficient sampling and a zonal wavefront estimation algorithm, both low and mid frequencies of the wavefront may be recovered. Notice that the DSH curvature sensor operates at the pupil of the system under test, therefore the difficulty associated with operation close to the caustic zone is avoided. Finally, the DSH-curvature-sensor-based wavefront estimation does not suffer from the 2π-ambiguity problem, so potentially both small and large aberrations may be measured

The quantitative analysis of transonic flows by holographic interferometry

This thesis explores the feasibility of routine transonic flow analysis by holographic interferometry. Holography is potentially an important quantitative flow diagnostic, because whole-field data is acquired non-intrusively without the use of particle seeding. Holographic recording geometries are assessed and an image plane specular illumination configuration is shown to reduce speckle noise and maximise the depth-of-field of the reconstructed images. Initially, a NACA 0012 aerofoil is wind tunnel tested to investigate the analysis of two-dimensional flows. A method is developed for extracting whole-field density data from the reconstructed interferograms. Fringe analysis errors axe quantified using a combination of experimental and computer generated imagery. The results are compared quantitatively with a laminar boundary layer Navier-Stokes computational fluid dynamics (CFD) prediction. Agreement of the data is excellent, except in the separated wake where the experimental boundary layer has undergone turbulent transition. A second wind tunnel test, on a cone-cylinder model, demonstrates the feasibility of recording multi-directional interferometric projections using holographic optical elements (HOE’s). The prototype system is highly compact and combines the versatility of diffractive elements with the efficiency of refractive components. The processed interferograms are compared to an integrated Euler CFD prediction and it is shown that the experimental shock cone is elliptical due to flow confinement. Tomographic reconstruction algorithms are reviewed for analysing density projections of a three-dimensional flow. Algebraic reconstruction methods are studied in greater detail, because they produce accurate results when the data is ill-posed. The performance of these algorithms is assessed using CFD input data and it is shown that a reconstruction accuracy of approximately 1% may be obtained when sixteen projections are recorded over a viewing angle of ±58°. The effect of noise on the data is also quantified and methods are suggested for visualising and reconstructing obstructed flow regions

Mechanisms of place recognition and path integration based on the insect visual system

Animals are often able to solve complex navigational tasks in very challenging terrain, despite using low resolution sensors and minimal computational power, providing inspiration for robots. In particular, many species of insect are known to solve complex navigation problems, often combining an array of different behaviours (Wehner et al., 1996; Collett, 1996). Their nervous system is also comparatively simple, relative to that of mammals and other vertebrates. In the first part of this thesis, the visual input of a navigating desert ant, Cataglyphis velox, was mimicked by capturing images in ultraviolet (UV) at similar wavelengths to the ant’s compound eye. The natural segmentation of ground and sky lead to the hypothesis that skyline contours could be used by ants as features for navigation. As proof of concept, sky-segmented binary images were used as input for an established localisation algorithm SeqSLAM (Milford and Wyeth, 2012), validating the plausibility of this claim (Stone et al., 2014). A follow-up investigation sought to determine whether using the sky as a feature would help overcome image matching problems that the ant often faced, such as variance in tilt and yaw rotation. A robotic localisation study showed that using spherical harmonics (SH), a representation in the frequency domain, combined with extracted sky can greatly help robots localise on uneven terrain. Results showed improved performance to state of the art point feature localisation methods on fast bumpy tracks (Stone et al., 2016a). In the second part, an approach to understand how insects perform a navigational task called path integration was attempted by modelling part of the brain of the sweat bee Megalopta genalis. A recent discovery that two populations of cells act as a celestial compass and visual odometer, respectively, led to the hypothesis that circuitry at their point of convergence in the central complex (CX) could give rise to path integration. A firing rate-based model was developed with connectivity derived from the overlap of observed neural arborisations of individual cells and successfully used to build up a home vector and steer an agent back to the nest (Stone et al., 2016b). This approach has the appeal that neural circuitry is highly conserved across insects, so findings here could have wide implications for insect navigation in general. The developed model is the first functioning path integrator that is based on individual cellular connections

Li-ion batteries monitoring for electrified vehicles applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Novel Approaches for Structural Health Monitoring

The thirty-plus years of progress in the field of structural health monitoring (SHM) have left a paramount impact on our everyday lives. Be it for the monitoring of fixed- and rotary-wing aircrafts, for the preservation of the cultural and architectural heritage, or for the predictive maintenance of long-span bridges or wind farms, SHM has shaped the framework of many engineering fields. Given the current state of quantitative and principled methodologies, it is nowadays possible to rapidly and consistently evaluate the structural safety of industrial machines, modern concrete buildings, historical masonry complexes, etc., to test their capability and to serve their intended purpose. However, old unsolved problematics as well as new challenges exist. Furthermore, unprecedented conditions, such as stricter safety requirements and ageing civil infrastructure, pose new challenges for confrontation. Therefore, this Special Issue gathers the main contributions of academics and practitioners in civil, aerospace, and mechanical engineering to provide a common ground for structural health monitoring in dealing with old and new aspects of this ever-growing research field