Multi-robot cooperative stereo for outdoor scenarios

13th International Conference on Autonomous Robot Systems (Robotica), 2013

Effect of the acoustic impedance in ultrasonic emitter transducers using digital modulations

In an underwater environment it is difficult to implement solutions for wireless communications. The existing technologies using electromagnetic waves or lasers are not very efficient due to the large attenuation in the aquatic environment. Ultrasound reveals a lower attenuation, and thus has been used in underwater long-distance communications. The much slower speed of acoustic propagation in water (about 1500 m/s) compared with that of electromagnetic and optical waves, is another limiting factor for efficient communication and networking. For high data-rates and real-time applications it is necessary to use frequencies in the MHz range, allowing communication distances of hundreds of meters with a delay of milliseconds. To achieve this goal, it is necessary to develop ultrasound transducers able to work at high frequencies and wideband, with suitable responses to digital modulations. This work shows how the acoustic impedance influences the performance of an ultrasonic emitter transducer when digital modulations are used and operating at frequencies between 100 kHz and 1 MHz. The study includes a Finite Element Method (FEM) and a MATLAB/Simulink simulation with an experimental validation to evaluate two types of piezoelectric materials: one based on ceramics (high acoustic impedance) with a resonance design and the other based in polymer (low acoustic impedance) designed to optimize the performance when digital modulations are used. The transducers performance for Binary Amplitude Shift Keying (BASK), On-Off Keying (OOK), Binary Phase Shift Keying (BPSK) and Binary Frequency Shift Keying (BFSK) modulations with a 1 MHz carrier at 125 kbps baud rate are compared.

Advantages of digital holographic microscopy for real-time full field absolute phase imaging

Different interferometric techniques were developed last decade to obtain full field, quantitative, and absolute phase imaging, such as phase-shifting, Fourier phase microscopy, Hilbert phase microscopy or digital holographic microscopy (DHM). Although, these techniques are very similar, DHM combines several advantages. In contrast, to phase shifting, DHM is indeed capable of single-shot hologram recording allowing a real-time absolute phase imaging. On the other hand, unlike to Fourier phase or Hilbert phase microscopy, DHM does not require to record in focus images of the specimen on the digital detector (CCD or CMOS camera), because a numerical focalization adjustment can be performed by a numerical wavefront propagation. Consequently, the depth of view of high NA microscope objectives is numerically extended. For example, two different biological cells, floating at different depths in a liquid, can be focalized numerically from the same digital hologram. Moreover, the numerical propagation associated to digital optics and automatic fitting procedures, permits vibrations insensitive full- field phase imaging and the complete compensation for a priori any image distortion or/and phase aberrations introduced for example by imperfections of holders or perfusion chamber. Examples of real-time full-field phase images of biological cells have been demonstrated. ©2008 COPYRIGHT SPIE

Bayesian Markov chain Monte Carlo inversion of geophysical data for the purpose of estimating the hydraulic properties of the unsaturated zone

Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.

State-to-state reaction probabilities within the quantum transition state framework

Rigorous quantum dynamics calculations of reaction rates and initial state-selected reaction probabilities of polyatomic reactions can be efficiently performed within the quantum transition state concept employing flux correlation functions and wave packet propagation utilizing the multi-configurational time-dependent Hartree approach. Here, analytical formulas and a numerical scheme extending this approach to the calculation of state-to-state reaction probabilities are presented. The formulas derived facilitate the use of three different dividing surfaces: two dividing surfaces located in the product and reactant asymptotic region facilitate full state resolution while a third dividing surface placed in the transition state region can be used to define an additional flux operator. The eigenstates of the corresponding thermal flux operator then correspond to vibrational states of the activated complex. Transforming these states to reactant and product coordinates and propagating them into the respective asymptotic region, the full scattering matrix can be obtained. To illustrate the new approach, test calculations study the D + H2(ν, j) → HD(ν′, j′) + H reaction for J = 0.

Real-time monitoring of the silicidation process of tungsten filaments at high temperature used as catalysers for silane decomposition

The scope of this work is the systematic study of the silicidation process affecting tungsten filaments at high temperature (1900ºC) used for silane decomposition in the hot-wire chemical vapour deposition technique (HWCVD). The correlation between the electrical resistance evolution of the filaments, Rfil(t), and the different stages of the their silicidation process is exposed. Said stages correspond to: the rapid formation of two WSi2 fronts at the cold ends of the filaments and their further propagation towards the middle of the filaments; and, regarding the hot central portion of the filaments: a initial stage of silicon dissolution into the tungsten bulk, with a random duration for as-manufactured filaments, followed by the inhomogeneous nucleation of W5Si3 (which is later replaced by WSi2) and its further growth towards the filaments core. An electrical model is used to obtain real-time information about the current status of the filaments silicidation process by simply monitoring their Rfil(t) evolution during the HWCVD process. It is shown that implementing an annealing pre-treatment to the filaments leads to a clearly repetitive trend in the monitored Rfil(t) signatures. The influence of hydrogen dilution of silane on the filaments silicidation process is also discussed.

A treatment planning method for sequentially combining radiopharmaceutical therapy and external radiation therapy.

PURPOSE: Effective cancer treatment generally requires combination therapy. The combination of external beam therapy (XRT) with radiopharmaceutical therapy (RPT) requires accurate three-dimensional dose calculations to avoid toxicity and evaluate efficacy. We have developed and tested a treatment planning method, using the patient-specific three-dimensional dosimetry package 3D-RD, for sequentially combined RPT/XRT therapy designed to limit toxicity to organs at risk. METHODS AND MATERIALS: The biologic effective dose (BED) was used to translate voxelized RPT absorbed dose (D(RPT)) values into a normalized total dose (or equivalent 2-Gy-fraction XRT absorbed dose), NTD(RPT) map. The BED was calculated numerically using an algorithmic approach, which enabled a more accurate calculation of BED and NTD(RPT). A treatment plan from the combined Samarium-153 and external beam was designed that would deliver a tumoricidal dose while delivering no more than 50 Gy of NTD(sum) to the spinal cord of a patient with a paraspinal tumor. RESULTS: The average voxel NTD(RPT) to tumor from RPT was 22.6 Gy (range, 1-85 Gy); the maximum spinal cord voxel NTD(RPT) from RPT was 6.8 Gy. The combined therapy NTD(sum) to tumor was 71.5 Gy (range, 40-135 Gy) for a maximum voxel spinal cord NTD(sum) equal to the maximum tolerated dose of 50 Gy. CONCLUSIONS: A method that enables real-time treatment planning of combined RPT-XRT has been developed. By implementing a more generalized conversion between the dose values from the two modalities and an activity-based treatment of partial volume effects, the reliability of combination therapy treatment planning has been expanded.

Identification of reference genes for expression analysis by real-time quantitative PCR in drought-stressed soybean

The objective of this work was to validate, by quantitative PCR in real time (RT-qPCR), genes to be used as reference in studies of gene expression in soybean in drought-stressed trials. Four genes commonly used in soybean were evaluated: Gmβ-actin, GmGAPDH, GmLectin and GmRNAr18S. Total RNA was extracted from six samples: three from roots in a hydroponic system with different drought intensities (0, 25, 50, 75 and 100 minutes of water stress), and three from leaves of plants grown in sand with different soil moistures (15, 5 and 2.5% gravimetric humidity). The raw cycle threshold (Ct) data were analyzed, and the efficiency of each primer was calculated for an overall analysis of the Ct range among the different samples. The GeNorm application was used to evaluate the best reference gene, according to its stability. The GmGAPDH was the least stable gene, with the highest mean values of expression stability (M), and the most stable genes, with the lowest M values, were the Gmβ-actin and GmRNAr18S, when both root and leaves samples were tested. These genes can be used in RT-qPCR as reference gene for expression analysis.

Dynamic range extension of SiPM detectors with the time-gated operation

The silicon photomultiplier (SiPM) is a novel detector technology that has undergone a fast development in the last few years, owing to its single-photon resolution and ultra-fast response time. However, the typical high dark count rates of the sensor may prevent the detection of low intensity radiation fluxes. In this article, the time-gated operation with short active periods in the nanosecond range is proposed as a solution to reduce the number of cells fired due to noise and thus increase the dynamic range. The technique is aimed at application fields that function under a trigger command, such as gated fluorescence lifetime imaging microscopy.

Selection of internal control genes for real-time quantitative PCR in ovary and uterus of sows across pregnancy

Reproductive traits play a key role in pig production in order to reduce costs and increase economic returns. Among others, gene expression analyses represent a useful approach to study genetic mechanisms underlying reproductive traits in pigs. The application of reverse-transcription quantitative PCR requires the selection of appropriate reference genes, whose expression levels should not be affected by the experimental conditions, especially when comparing gene expression across different physiological stages.

In situ spectroellipsometric study of the nucleation and growth of amorphous silicon

A detailed in situ spectroellipsometric analysis of the nucleation and growth of hydrogenated amorphous silicon (a:Si:H) is presented. Photoelectronic quality a‐Si:H films are deposited by plasma‐enhanced chemical vapor deposition on smooth metal (NiCr alloy) and crystalline silicon (c‐Si) substrates. The deposition of a‐Si:H is analyzed from the first monolayer up to a final thickness of 1.2 μm. In order to perform an improved analysis, real time ellipsometric trajectories are recorded, using fixed preparation conditions, at various photon energies ranging from 2.2 to 3.6 eV. The advantage of using such a spectroscopic experimental procedure is underlined. New insights into the nucleation and growth mechanisms of a‐Si:H are obtained. The nucleation mechanism on metal and c‐Si substrates is very accurately described assuming a columnar microstructural development during the early stage of the growth. Then, as a consequence of the incomplete coalescence of the initial nuclei, a surface roughness at the 10-15 Å scale is identified during the further growth of a‐Si:H on both substrates. The bulk a‐Si:H grows homogeneously beneath the surface roughness. Finally, an increase of the surface roughness is evidenced during the long term growth of a‐Si:H. However, the nature of the substrate influenced the film growth. In particular, the film thickness involved in the nucleation‐coalescence phase is found lower in the case of c‐Si (67±8 Å) as compared to NiCr (118±22 Å). Likewise films deposited on c‐Si present a smaller surface roughness even if thick samples are considered (>1 μm). More generally, the present study illustrates the capability of in situ spectroellipsometry to precisely analyze fundamental processes in thin‐film growth, but also to monitor the preparation of complex structures on a few monolayers scale.

Dynamic range extension of SiPM detectors with the time-gated operation

The silicon photomultiplier (SiPM) is a novel detector technology that has undergone a fast development in the last few years, owing to its single-photon resolution and ultra-fast response time. However, the typical high dark count rates of the sensor may prevent the detection of low intensity radiation fluxes. In this article, the time-gated operation with short active periods in the nanosecond range is proposed as a solution to reduce the number of cells fired due to noise and thus increase the dynamic range. The technique is aimed at application fields that function under a trigger command, such as gated fluorescence lifetime imaging microscopy.

Serological and virological surveys of the influenza A viruses in Antarctic and sub-Antarctic penguins

To evaluate the avian influenza virus (AIV) circulation in Antarctic and sub-Antarctic penguins we carried out a serosurvey on six species from Livingston, Marion and Gough islands. Seropositivity against AIV was performed on serum samples using a competitive enzyme-linked immunosorbent assay and haemagglutination and neuraminidase inhibition assays. Some oropharyngeal and cloacal swabs were also assayed to detect influenza virus genomes by real time reverse transcription-polymerase chain reaction. Overall, 12.1% (n = 140) penguins were seropositive to AIV. By species, we detected 5% (n = 19) and 11% (n = 18) seroprevalence in sub-Antarctic rockhopper penguins (Eudyptes spp.) from Gough and Marion islands, respectively, 42% (n = 33) seroprevalence in macaroni penguins (Eudyptes chysolophus Brandt), but no positives in the three other species, gentoo (Pygoscelis papua Forster; n = 25) and chinstrap penguins (P. antarctica Forster; n = 16), from Livingston Island and king penguins (Aptenodytes patagonicus Miller; n = 27) from Marion Island. While seropositivity reflected previous exposure to the AIV, the influenza genome was not detected. Our results indicate that AIV strains have circulated in penguin species in the sub-Antarctic region, but further studies are necessary to determine the precise role that such penguin species play in AIV epidemiology and if this circulation is species (or genus) specific.

Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images

The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

Real-time simulation of multibody systems with applications for working mobile vehicles

This dissertation describes an approach for developing a real-time simulation for working mobile vehicles based on multibody modeling. The use of multibody modeling allows comprehensive description of the constrained motion of the mechanical systems involved and permits real-time solving of the equations of motion. By carefully selecting the multibody formulation method to be used, it is possible to increase the accuracy of the multibody model while at the same time solving equations of motion in real-time. In this study, a multibody procedure based on semi-recursive and augmented Lagrangian methods for real-time dynamic simulation application is studied in detail. In the semirecursive approach, a velocity transformation matrix is introduced to describe the dependent coordinates into relative (joint) coordinates, which reduces the size of the generalized coordinates. The augmented Lagrangian method is based on usage of global coordinates and, in that method, constraints are accounted using an iterative process. A multibody system can be modelled as either rigid or flexible bodies. When using flexible bodies, the system can be described using a floating frame of reference formulation. In this method, the deformation mode needed can be obtained from the finite element model. As the finite element model typically involves large number of degrees of freedom, reduced number of deformation modes can be obtained by employing model order reduction method such as Guyan reduction, Craig-Bampton method and Krylov subspace as shown in this study The constrained motion of the working mobile vehicles is actuated by the force from the hydraulic actuator. In this study, the hydraulic system is modeled using lumped fluid theory, in which the hydraulic circuit is divided into volumes. In this approach, the pressure wave propagation in the hoses and pipes is neglected. The contact modeling is divided into two stages: contact detection and contact response. Contact detection determines when and where the contact occurs, and contact response provides the force acting at the collision point. The friction between tire and ground is modelled using the LuGre friction model, which describes the frictional force between two surfaces. Typically, the equations of motion are solved in the full matrices format, where the sparsity of the matrices is not considered. Increasing the number of bodies and constraint equations leads to the system matrices becoming large and sparse in structure. To increase the computational efficiency, a technique for solution of sparse matrices is proposed in this dissertation and its implementation demonstrated. To assess the computing efficiency, augmented Lagrangian and semi-recursive methods are implemented employing a sparse matrix technique. From the numerical example, the results show that the proposed approach is applicable and produced appropriate results within the real-time period.