Numerical modeling of spalling brittle fracture along the (0001) plane in HCP-single crystals under shock loading

Numerical modeling of spalling brittle fracture along the (0001) plane in a zinc single crystal under shock loading by an aluminum projectile was performed in the work. Numerical modeling was carried out by the finite element method in a three-dimensional statement. The mathematical model allows to take into account the anisotropy of bulk compressibility in a single crystal of zinc, auxeticity, anisotropy of the propagation velocities of elastic longitudinal and volume waves. Stresses are determined on the basis of a comparison of velocity profiles of the rear surfaces of targets from zinc single crystal in mutually perpendicular directions when it is destroyed along the (0001) plane in natural experiments and numerical simulation

A Simulation Study of Spectral Cerenkov Luminescence Imaging for Tumour Margin Estimation

Breast cancer is the most common cancer in women in the world. Breast-conserving surgery (BCS) is a standard surgical treatment for breast cancer with the key objective of removing breast tissue, maintaining a negative surgical margin and providing a good cosmetic outcome. A positive surgical margin, meaning the presence of cancerous tissues on the surface of the breast specimen after surgery, is associated with local recurrence after therapy. In this study, we investigate a new imaging modality based on Cerenkov luminescence imaging (CLI) for the purpose of detecting positive surgical margins during BCS. We develop Monte Carlo (MC) simulations using the Geant4 nuclear physics simulation toolbox to study the spectrum of photons emitted given 18F-FDG and breast tissue properties. The resulting simulation spectra show that the CLI signal contains information that may be used to estimate whether the cancerous cells are at a depth of less than 1 mm or greater than 1 mm given appropriate imaging system design and sensitivity. The simulation spectra also show that when the source is located within 1 mm of the surface, the tissue parameters are not relevant to the model as the spectra do not vary significantly. At larger depths, however, the spectral information varies significantly with breast optical parameters, having implications for further studies and system design. While promising, further studies are needed to quantify the CLI response to more accurately incorporate tissue specific parameters and patient specific anatomical details

Modelling of the deformation of highly porous metals and alloys under dynamic loading

The study represents the analysis of numerical simulation of the failure of aluminum targets made of highly porous or solid 2024 alloy under dynamic loading. The calculations employed the finite elements method in three-dimensional formulation with the use of proprietary programs. The article presents the results of the numerical simulation of Taylor’s test for the projectile made of highly porous aluminum 2024 alloy at the velocities of 75 to 175 m/s. These results are in a good agreement with the results of the experiments. The peculiarities of the destruction of highly porous aluminum targets are shown

Self-supervised generative adverrsarial network for depth estimation in laparoscopic images

Dense depth estimation and 3D reconstruction of a surgical scene are crucial steps in computer assisted surgery. Recent work has shown that depth estimation from a stereo image pair could be solved with convolutional neural networks. However, most recent depth estimation models were trained on datasets with per-pixel ground truth. Such data is especially rare for laparoscopic imaging, making it hard to apply supervised depth estimation to real surgical applications. To overcome this limitation, we propose SADepth, a new self-supervised depth estimation method based on Generative Adversarial Networks. It consists of an encoder-decoder generator and a discriminator to incorporate geometry constraints during training. Multi-scale outputs from the generator help to solve the local minima caused by the photometric reprojection loss, while the adversarial learning improves the framework generation quality. Extensive experiments on two public datasets show that SADepth outperforms recent state-of-the-art unsupervised methods by a large margin, and reduces the gap between supervised and unsupervised depth estimation in laparoscopic images

Response Monitoring, Repetitive Behaviour and Anterior Cingulate Abnormalities in Autism Spectrum Disorders (ASD)

Autism spectrum disorders (ASD) are characterized by inflexible and repetitive behaviour. Response monitoring involves evaluating the consequences of behaviour and making adjustments to optimize outcomes. Deficiencies in this function, and abnormalities in the anterior cingulate cortex (ACC) on which it relies, have been reported as contributing factors to autistic disorders. We investigated whether ACC structure and function during response monitoring were associated with repetitive behaviour in ASD. We compared ACC activation to correct and erroneous antisaccades using rapid presentation event-related functional MRI in 14 control and ten ASD participants. Because response monitoring is the product of coordinated activity in ACC networks, we also examined the microstructural integrity of the white matter (WM) underlying this brain region using diffusion tensor imaging (DTI) measures of fractional anisotropy (FA) in 12 control and 12 adult ASD participants. ACC activation and FA were examined in relation to Autism Diagnostic Interview-Revised ratings of restricted and repetitive behaviour. Relative to controls, ASD participants: (i) made more antisaccade errors and responded more quickly on correct trials; (ii) showed reduced discrimination between error and correct responses in rostral ACC (rACC), which was primarily due to (iii) abnormally increased activation on correct trials and (iv) showed reduced FA in WM underlying ACC. Finally, in ASD (v) increased activation on correct trials and reduced FA in rACC WM were related to higher ratings of repetitive behaviour. These findings demonstrate functional and structural abnormalities of the ACC in ASD that may contribute to repetitive behaviour. rACC activity following errors is thought to reflect affective appraisal of the error. Thus, the hyperactive rACC response to correct trials can be interpreted as a misleading affective signal that something is awry, which may trigger repetitive attempts at correction. Another possible consequence of reduced affective discrimination between error and correct responses is that it might interfere with the reinforcement of responses that optimize outcomes. Furthermore, dysconnection of the ACC, as suggested by reduced FA, to regions involved in behavioural control might impair on-line modulations of response speed to optimize performance (i.e. speed-accuracy trade-off) and increase error likelihood. These findings suggest that in ASD, structural and functional abnormalities of the ACC compromise response monitoring and thereby contribute to behaviour that is rigid and repetitive rather than flexible and responsive to contingencies. Illuminating the mechanisms and clinical significance of abnormal response monitoring in ASD represents a fruitful avenue for further research

Spatio-temporal variability and principal components of the particle number size distribution in an urban atmosphere

A correct description of fine (diameter <1 μm) and ultrafine (<0.1 μm) aerosol particles in urban areas is of interest for particle exposure assessment but also basic atmospheric research. We examined the spatio-temporal variability of atmospheric aerosol particles (size range 3–800 nm) using concurrent number size distribution measurements at a maximum of eight observation sites in and around Leipzig, a city in Central Europe. Two main experiments were conducted with different time span and number of observation sites (2 years at 3 sites; 1 month at 8 sites). A general observation was that the particle number size distribution varied in time and space in a complex fashion as a result of interaction between local and far-range sources, and the meteorological conditions. To identify statistically independent factors in the urban aerosol, different runs of principal component (PC) analysis were conducted encompassing aerosol, gas phase, and meteorological parameters from the multiple sites. Several of the resulting PCs, outstanding with respect to their temporal persistence and spatial coverage, could be associated with aerosol particle modes: a first accumulation mode ("droplet mode", 300–800 nm), considered to be the result of liquid phase processes and far-range transport; a second accumulation mode (centered around diameters 90–250 nm), considered to result from primary emissions as well as aging through condensation and coagulation; an Aitken mode (30–200 nm) linked to urban traffic emissions in addition to an urban and a rural Aitken mode; a nucleation mode (5–20 nm) linked to urban traffic emissions; nucleation modes (3–20 nm) linked to photochemically induced particle formation; an aged nucleation mode (10–50 nm). Additional PCs represented only local sources at a single site, or infrequent phenomena. In summary, the analysis of size distributions of high time and size resolution yielded a surprising wealth of statistical aerosol components occurring in the urban atmosphere over one single city. A paradigm on the behaviour of sub-μm urban aerosol particles is proposed, with recommendations how to efficiently monitor individual sub-fractions across an entire city

Mobility particle size spectrometers: Calibration procedures and measurement uncertainties

Mobility particle size spectrometers (MPSS) belong to the essential instruments in aerosol science that determine the particle number size distribution (PNSD) in the submicrometer size range. Following calibration procedures and target uncertainties against standards and reference instruments are suggested for a complete MPSS quality assurance program: (a) calibration of the CPC counting efficiency curve (within 5% for the plateau counting efficiency; within 1 nm for the 50% detection efficiency diameter), (b) sizing calibration of the MPSS, using a certified polystyrene latex (PSL) particle size standard at 203 nm (within 3%), (c) intercomparison of the PNSD of the MPSS (within 10% and 20% of the dN/dlogDP concentration for the particle size range 20–200 and 200–800 nm, respectively), and (d) intercomparison of the integral PNC of the MPSS (within 10%). Furthermore, following measurement uncertainties have been investigated: (a) PSL particle size standards in the range from 100 to 500 nm match within 1% after sizing calibration at 203 nm. (b) Bipolar diffusion chargers based on the radioactive nuclides Kr85, Am241, and Ni63 and a new ionizer based on corona discharge follow the recommended bipolar charge distribution, while soft X-ray-based charges may alter faster than expected. (c) The use of a positive high voltage supply show a 10% better performance than a negative one. (d) The intercomparison of the integral PNC of an MPSS against the total number concentration is still within the target uncertainty at an ambient pressure of approximately 500 hPa

Mobility particle size spectrometers: Calibration procedures and measurement uncertainties

Mobility particle size spectrometers (MPSS) belong to the essential instruments in aerosol science that determine the particle number size distribution (PNSD) in the submicrometer size range. Following calibration procedures and target uncertainties against standards and reference instruments are suggested for a complete MPSS quality assurance program: (a) calibration of the CPC counting efficiency curve (within 5% for the plateau counting efficiency; within 1 nm for the 50% detection efficiency diameter), (b) sizing calibration of the MPSS, using a certified polystyrene latex (PSL) particle size standard at 203 nm (within 3%), (c) intercomparison of the PNSD of the MPSS (within 10% and 20% of the dN/dlogDP concentration for the particle size range 20–200 and 200–800 nm, respectively), and (d) intercomparison of the integral PNC of the MPSS (within 10%). Furthermore, following measurement uncertainties have been investigated: (a) PSL particle size standards in the range from 100 to 500 nm match within 1% after sizing calibration at 203 nm. (b) Bipolar diffusion chargers based on the radioactive nuclides Kr85, Am241, and Ni63 and a new ionizer based on corona discharge follow the recommended bipolar charge distribution, while soft X-ray-based charges may alter faster than expected. (c) The use of a positive high voltage supply show a 10% better performance than a negative one. (d) The intercomparison of the integral PNC of an MPSS against the total number concentration is still within the target uncertainty at an ambient pressure of approximately 500 hPa. Copyright © 2018 Published with license by American Association for Aerosol Research

On Quantifying Local Geometric Structures of Fiber Tracts

International audienceIn diffusion MRI, fiber tracts, represented by densely distributed 3D curves, can be estimated from diffusion weighted images using tractography. The spatial geometric structure of white matter fiber tracts is known to be complex in human brain, but it carries intrinsic information of human brain. In this paper, inspired by studies of liquid crystals, we propose tract-based director field analysis (tDFA) with total six rotationally invariant scalar indices to quantify local geometric structures of fiber tracts. The contributions of tDFA include: 1) We propose orientational order (OO) and orientational dispersion (OD) indices to quantify the degree of alignment and dispersion of fiber tracts; 2) We define the local orthogonal frame for a set of unoriented curves, which is proved to be a generalization of the Frenet frame defined for a single oriented curve; 3) With the local orthogonal frame, we propose splay, bend, and twist indices to quantify three types of orientational distortion of local fiber tracts, and a total distortion index to describe distortions of all three types. The proposed tDFA for fiber tracts is a generalization of the voxel-based DFA (vDFA) which was recently proposed for a spherical function field (i.e., an ODF field). To our knowledge, this is the first work to quantify orientational distortion (splay, bend, twist, and total distortion) of fiber tracts. Experiments show that the proposed scalar indices are useful descriptors of local geometric structures to visualize and analyze fiber tracts