Cluster Volume Research Articles

Vision-based extraction of spatial information in grape clusters for harvesting robots

Grapes are likely to have collisions and be damaged by manipulations when harvesting grape clusters. To conduct an undamaged robotic harvesting, this paper focuses mainly on locating the spatial coordinates of the cutting points on a peduncle of grape clusters for the end-effector and determining the bounding volume of the grape clusters for the motion planner of the manipulator. A method for acquiring spatial information from grape clusters is presented based on binocular stereo vision. This method includes four steps: (1) calibrating the binocular cameras and rectifying the images, (2) detecting the cutting points on the peduncle and the centres of the grape berries, (3) extracting three-dimensional spatial coordinates of the points detected in step 2, and (4) calculating the bounding volume of the grape clusters. A total of 300 images were captured in the vineyard and were tested to validate the method for the cutting point detection, and the success rate was approximately 87%. The accuracy of the localisation of the cutting points was determined under outdoor conditions, and the accuracy in the Z and X directions was 12 mm and 9 mm, respectively. The acquired bounding volume of the grape cluster was compared with manual measurements, and errors in the height and maximum diameter were less than 17 mm and 19 mm, respectively. The elapsed time of the whole algorithm was less than 0.7 s. The demonstrated performance of this developed method indicated that it could be used on harvesting robots.

Generalized Boltzmann kinetic theory for EMMS-based two-fluid model

It has long been recognized that the solid particles in circulating fluidized bed risers are distributed heterogeneously in the form of clusters. In response to this fundamental phenomenon, an EMMS-based two-fluid model has been developed recently from the viewpoint of continuum mechanics, however, its microscopic foundation remains unknown. In this study, the statistical mechanics foundation of EMMS-based two-fluid model was presented using generalized Boltzmann kinetic theory. With respect to the gas phase, a new method was developed by considering the fluctuations at different scales simultaneously, with which we can for the first time derive the correct governing equations of gas phase via kinetic theory, in the sense that both the molecular stress and the Reynolds (or pseudo-Reynolds) stress can be obtained simultaneously, whereas all previous kinetic theory analyses failed to predict the appearance of Reynolds (or pseudo-Reynolds) stress in the momentum conservation equation of gas phase due to the assumption of uniform structure, although it is physically always existent no matter how small the Reynolds number is. In case of particle phase, the generalized Boltzmann equation considering the spatio-temporal variation of the volume, density and velocity of clusters was firstly derived, a set of macroscopic transport equations was then derived in different phase spaces. It was shown that the governing equations of dense phase in the EMMS-based two-fluid model derived from continuum mechanics viewpoint corresponds to the macroscopic transport equations at (r,t) space. Therefore, present study launches a solid microscopic foundation of EMMS-based two-fluid model. Finally, CFD simulations have been carried out to validate EMMS-based two-fluid model and to study the effect of gas phase pseudo-turbulence.

Effect of Dispersion Methods on Oxygen Reduction and Ammonia Oxidation Reactions for Multiwall Carbon Nanotube Supported Pt

When the activity of a catalyst was estimated by a rotating ring disk electrode (RRDE) method, the modified glassy carbon (GC) electrode was generally fabricated by casting catalyst suspension prepared by various methods, followed by drying under various conditions. There are many preparation methods for catalyst suspension. And it is known that the dispersivity of the catalyst on the GC electrode, which affects collection efficiency of H2O2as well as current density, depends on the above methods and conditions. Since an optimum method and condition often varies with the kinds of catalysts, researchers have to find them. However, it is difficult to evaluate the dispersivity on the electrode and reproducibility quantitatively. In this study, the dispersivity of multi wall carbon nanotube supported Pt catalyst (Pt/MWCNT) on the modified electrode prepared by various methods was estimated by digitizing height data of the electrode using a laser surface roughness meter. 30 wt% Pt/MWCNT (Pt particle size: 4.26 ± 0.09 nm) catalyst was synthesized by a microwave polyol process. 2 mg/mL of 30 wt% Pt/MWCNT-0.1 wt% various alcohol (MeOH, EtOH, and 2-PrOH) suspensions were prepared by ultrasonication for 10 min. 10 μL of the suspensions cast on a GC electrode, and the electrode allowed to dry by three method: 1) in air for 1 h (abbreviated as Air), 2) in saturated ethanol vapor pressure for 1 h (EV), and 3) in air with infrared irradiation for 10 min at 60 °C (IR). The samples were named as [solvent] – [drying method]. The modified electrodes were observed with a digital microscope (MSP-3080, PANRICO). And the surface height data of the modified electrodes were digitized with a laser surface roughness meter (SV-C4500 CNC, Mitutoyo), and the data were analyzed by a software "Roughness Analyzer" developed by our laboratory. The software detects secondary particles of the catalyst (clusters) on the electrode and the user can obtain the volumes, the average height, and the area of the clusters as well as the distribution of the catalysts from the center of the electrode. Fig. 1 (a) shows cumulative cluster volume distribution for MeOH–Air, 2-PrOH-Air and EtOH–EV. The electrode surface prepared by the EtOH-EV method had the clusters up to 1.9×10-3 mm3, whereas those prepared by MeOH-Air and EtOH-EV had the clusters up to 6.7×10-4 mm3 and 1.9×10-3 mm3, respectively, suggesting that the EtOH-EV method tend to be aggregated to produce large secondary particles. Fig. 1 (b) shows the average cluster heights of the samples. The standard deviation of the average cluster height for 2-PrOH-Air was the smallest of the three methods, indicating that the 2-PrOH-Air method is the most reproducible casting method of the three methods. Some quantification methods will be reported in the meeting. Figure 1

Anvil Productivities of Tropical Deep Convective Clusters and Their Regional Differences

The anvil productivities of tropical deep convection are investigated and compared among eight climatological regions using 4 yr of collocated and combined CloudSat and CALIPSO data. For all regions, the convective clusters become deeper while they become wider and tend to be composed of multiple rainy cores. Two strong detrainment layers from deep convection are observed at 6–8 km and above 10 km, which is consistent with the trimodal characteristics of tropical convection that are associated with different divergence, cloud detrainment, and fractional cloudiness. The anvil productivity of tropical deep convection depends on the convection scale, convective life stage or intensity, and large-scale environment. Anvil ice mass ratio related to the whole cluster starts to level off or decrease when the cluster effective scales Weff (the dimension of an equivalent rectangular with the same volume and height as the original cluster) increase to about 200 km wide, while the ratios of anvil scale and volume keep increasing from 0.4 to 0.6 and 0.15 to 0.4, respectively. The anvil clouds above 12 km can count for more than 20% of cluster volume, or more than 50% of total anvil volume, but they only count less than about 2% of total ice mass in the cluster. Anvil production of younger convection of the same Weff is higher than that of the decaying convection. The regional difference in the composite anvil productivities of tropical convective clusters sorted by Weff is subtle, while the occurrence frequencies of different scales of convection vary substantially.

Brain PET metabolic abnormalities in patients with long-lasting macrophagic myofasciitis

Background Macrophagic myofasciitis (MMF) is characterized by abnormal long-term persistence of aluminum hydroxide within macrophages at the site of previous immunization. Patients present with diffuse arthromyalgias, chronic fatigue, and cognitive dysfunction. The aim of this study was to characterize brain PET metabolic abnormalities in patients with aluminum hydroxide adjuvant-induced macrophagic myofasciitis, and relation with cognitive dysfunction. Methods FDG-PET brain imaging and a comprehensive battery of neuropsychological tests were performed in 100 consecutive MMF patients (mean age, 45.9 ± 11.8 y; women, 74%) followed in our Reference Center for Rare Neuromuscular Diseases. Images were analyzed using statistical parametric mapping (SPM12). Using ANCOVA analysis, all FDG-PET brain images of MMF patients were compared to normal reference samples from 44 healthy subjects matched for age ( p = 0.87) and gender ( p = 0.88) with the whole population of patients (mean age, 45.4 ± 16 y; women, 73%). All results were collected at a p -value k ≥ 200 voxels (corrected for cluster volume) with adjustment for age and gender. The neuropsychological assessment identified four categories of patients with: (i) no significant cognitive impairment ( n = 42); (ii) frontal sub-cortical (FSC) dysfunction ( n = 29); (iii) papezian dysfunction ( n = 22); and (iv) callosal disconnection ( n = 7). Results In comparison with healthy subjects, ANCOVA analysis of the whole population of patients with MMF exhibited a pattern of hypometabolism ( p Conclusions Our study identified a cerebral glucose metabolic biomarker in patients with long-lasting aluminum hydroxide-induced MMF. The pattern appeared mostly marked in MMF patients with FSC dysfunction.

Morphological Characterization of Acinar Cluster in Mouse Lung Using a Multiscale-based Segmentation Algorithm on Synchrotron Micro-CT Images.

Understanding the three-dimensional morphology of pulmonary acini is essential when exploring the biomechanics of respiratory function. In this study, we characterized the morphology of individual acini and a cluster of acini stemming from the same terminal conducting airway using a quantitative approach based on the semi-automatic segmentation of synchrotron micro-CT images of mouse lung. The volume and surface area of five clusters of mouse acini including 50 individual acini were estimated based on the voxel and surface mesh of segmented acini at FRC. The pathway length and width were estimated for one cluster including 15 acini based on the skeleton of segmented acini. The acinar volume was 0.09 ± 0.07 mm(3) (mean ± SD), and the surface area was 6.82 ± 4.49 mm(2) , in agreement with previous studies. The volume of the acinar clusters was 0.89 ± 0.34 mm(3) , and the surface area was 68.18 ± 17.66 mm(2) . The largest volume acinus per cluster was found in the distal region of the terminal conducting airway, and apparent respiratory bronchioles were observed only in large-volume acini. The generation number of pathways per acinus was 8 ± 2 (range: 6-12). The pathway length at lower generations (generations 2-6) increased with the generation number in a single cluster, while did not significantly change at lower generations in some acinar groups. The pathway width increased with increasing generation numbers. Our approach characterized the quantitative morphology of pulmonary acinar clusters in mouse lung, and the results can be used in further biomechanical simulation studies. Anat Rec, 299:1424-1434, 2016. © 2016 Wiley Periodicals, Inc.

Bimetallic PtCu core-shell nanoparticles in PtCu/C electrocatalysts: Structural and electrochemical characterization

Composite metal-carbon electrocatalysts PtCu/C containing core-shell bimetallic PtCu nanoparticles were synthesized by sequential chemical reduction of Cu (II) and Pt (IV) in carbon suspension, prepared on the basis of ethylene glycol–water solvent. The characterization of “as prepared” and obtained after the acid treatment PtCu nanoparticles was performed by TEM, XRD, Pt L3- and Cu K-edge extended X-ray absorption fine structures (EXAFS). The technique and computational code were proposed for visualization of components distribution over the volume of cluster, which represents the mean bimetallic nanoparticle, according to the values of structural parameters derived from EXAFS. By this technique, the cluster models of PtCu nanoparticles before and after acid treatment, reflecting the character of components’ distribution, were generated. The study of electrochemical performances of the obtained PtCu/C electrocatalyst revealed the similar oxygen reduction reaction (ORR) activity and increased durability compared to commercial Pt/C electrocatalyst E-TEK 20.

Dose-dependent genotype effects of BDNF Val66Met polymorphism on default mode network in early stage Alzheimer's disease.

In humans, brain-derived neurotrophic factor (BDNF) has been shown to play a pivotal role in neurocognition, and its gene contains a functional polymorphism (Val66Met) that may explain individual differences in brain volume and memory-related activity.In this study, we enrolled 186 Alzheimer's disease (AD) patients who underwent 3D T1 magnetic resonance imaging, and explored the gray matter (GM) structural covariance networks (SCN). The patients were divided into three groups according to their genotype: Met/Met (n = 45), Val/Met (n = 86) and Val/Val (n = 55). Seed-based analysis was performed focusing on four SCN networks. Neurobehavioral scores served as the major outcome factor.Only peak cluster volumes of default mode medial temporal lobe network showed significant genotype interactions, of which the interconnected peak clusters showed dose-dependent genotype effects. There were also significant correlations between the cognitive test scores and interconnected-cluster volumes, especially in the orbitofrontal cortex.These findings support the hypothesis that BDNF rs6265 polymorphisms modulate entorhinal cortex-interconnected clusters and the valine allele was associated with stronger structural covariance patterns that determined the cognitive outcomes.

Influence of the critical Fe atomic volume on the magnetism of Fe-rich metallic glasses evidenced by pressure-dependent measurements

Despite the intensive studies for decades, it is still not well understood how qualitatively different magnetic behaviors can occur in a narrow composition range for the Fe-rich Fe-transition metal (TM) amorphous alloys. In this study of amorphous $\mathrm{F}{\mathrm{e}}_{100\ensuremath{-}x}\mathrm{Z}{\mathrm{r}}_{x}$ ($x=7$, 9, 12) metallic glasses, normal ferromagnetism (FM) is found at 12 % Zr where only the FM-paramagnetic (PM) transition is observed at the Curie temperature, ${T}_{C}$. In contrast, spin-glass (SG)-PM transition at a temperature, ${T}_{g}$, called SG temperature, is only observed at 7 % Zr, while in the transient re-entrant composition range $(x=8\ensuremath{-}11)$, an SG-FM transition at a temperature, ${T}_{f}$, called spin-freezing temperature, is also observed at low temperature besides the normal FM-PM transition at ${T}_{C}$. In order to understand this unusual behavior, a detailed characterization of pressure (atomic volume), composition, and temperature dependence of the magnetic properties is coupled with high pressure synchrotron x-ray diffraction determination of the pressure dependence of the atomic volume. The results on $\mathrm{F}{\mathrm{e}}_{100\ensuremath{-}x}\mathrm{Z}{\mathrm{r}}_{x}$ ($x=7$, 9, 12) are compared to those obtained for the FM $\mathrm{C}{\mathrm{o}}_{91}\mathrm{Z}{\mathrm{r}}_{9}$ metallic glass not showing any kind of anomalous magnetic properties. It is confirmed that the unusual behavior is caused by a granularlike magnetic structure where weakly coupled magnetic clusters are embedded into a FM bulk matrix. Since the mechanism of the magnetization reversal was found to be of the curling type rather than homogeneous rotation, the energy barrier determining the blocking temperature of the clusters is calculated as AR, where A is the exchange constant and R is the cluster size, in contrast to the usual characterization of the energy barrier by KV where K is the anisotropy energy and V is the cluster volume. The volume fraction of the FM part is a fast changing function of the bulk composition: Almost 100% FM fraction is found at 12 % of Zr while no trace of real FM is observed at 7 at % Zr. The driving force of this surprising magnetic character is the atomic volume: The lower the Zr content, the higher is the fraction of Fe atoms with compressed atomic volume having low magnetic moment. The percolation of their network separates the clusters from the FM bulk. The complex magnetic behavior of the Fe-rich Fe-Zr amorphous system at low temperatures can thus be interpreted with the only assumption of a cluster-size distribution and a weak coupling of the clusters to the FM matrix. The introduction of this coupling is able to explain the opposite pressure dependence of ${T}_{g}$ and ${T}_{f}$. The threshold atomic volume in the low magnetic moment regions is found to be comparable to the atomic volume characteristic to the low-spin limit of the face-centered-cubic Fe alloys. The extensive literature results on the anomalous magnetism for various Fe-rich Fe-TM amorphous alloys and especially for the Fe-rich Fe-Zr glassy system are also found to be in agreement with this granular magnetic behavior.

Clinical workflow for personalized foot pressure ulcer prevention

Foot pressure ulcers are a common complication of diabetes because of patient's lack of sensitivity due to neuropathy. Deep pressure ulcers appear internally when pressures applied on the foot create high internal strains nearby bony structures. Monitoring tissue strains in persons with diabetes is therefore important for an efficient prevention. We propose to use personalized biomechanical foot models to assess strains within the foot and to determine the risk of ulcer formation. Our workflow generates a foot model adapted to a patient's morphology by deforming an atlas model to conform it to the contours of segmented medical images of the patient's foot. Our biomechanical model is composed of rigid bodies for the bones, joined by ligaments and muscles, and a finite element mesh representing the soft tissues. Using our registration algorithm to conform three datasets, three new patient models were created. After applying a pressure load below these foot models, the Von Mises equivalent strains and “cluster volumes” (i.e. volumes of contiguous elements with strains above a given threshold) were measured within eight functionally meaningful foot regions. The results show the variability of both location and strain values among the three considered patients. This study also confirms that the anatomy of the foot has an influence on the risk of pressure ulcer.

Influence of Wettability on Residual Gas Trapping and Enhanced Oil Recovery in Three-Phase Flow: A Pore-Scale Analysis by Use of Microcomputed Tomography

Summary We imaged an intermediate-wet sandstone in three dimensions at high resolution (1–3.4 µm3) with X-ray microcomputed tomography (micro-CT) at various saturation states. Initially the core was at connate-water saturation and contained a large amount of oil (94%), which was produced by a waterflood [recovery factor Rf = 52% of original oil in place (OOIP)] or a direct gas flood (Rf = 66% of OOIP). Subsequent waterflooding and/or gasflooding (water-alternating-gas process) resulted in significant incremental-oil recovery (Rf = 71% of OOIP), whereas a substantial amount of gas could be stored (approximately 50%)—significantly more than in an analog water-wet plug. The oil- and gas-cluster-size distributions were measured and followed a power-law correlation N ∝ V−τ , where N is the frequency with which clusters of volume V are counted, and with decays exponents τ between 0.7 and 1.7. Furthermore, the cluster volume V plotted against cluster surface area A also correlated with a power-law correlation A ∝ Vp, and p was always ≈ 0.75. The measured τ- and p-values are significantly smaller than predicted by percolation theory, which predicts p ≈ 1 and τ = 2.189; this raises increasing doubts regarding the applicability of simple percolation models. In addition, we measured curvatures and capillary pressures of the oil and gas bubbles in situ, and analyzed the detailed pore-scale fluid configurations. The complex variations in fluid curvatures, capillary pressures, and the fluid/fluid or fluid/fluid/fluid pore-scale configurations (exact spatial locations also in relation to each other and the rock surface) are the origin of the well-known complexity of three-phase flow through rock.

Development of a predictive power law relationship for polymer composites based on newtonial carrier concentrated slurries

A new theory that predicts the power law “n” for Newtonian carrier particulate composites has been developed using percolation theory concepts. Many polymer composites, such as sheet molding compound, polyurethanes based on polymer‐polyols, and highly filled epoxy compounds, are generated using highly filled Newtonian carriers. Essentially, all of slurries that have a high concentration of filler become shear thinning at some shear rate. Several sizes of calcium carbonate were initially investigated because of their extensive use in many industries as fillers. A new function was found that linearly correlates the power law constant, n, to the concentration of the filler above the percolation concentration. The behavior of this function suggests that the Newtonian to power law behavior may be dominated by percolation processes. A new percolation theory based model was developed that theoretically predicted the power law from the volume of the nondissipating clusters. A theory is proposed that relates the plug volume in tube flow to the power law, n. The central plug in tube flow was experimentally shown to be a nondissipating volume in the flowing slurry. Data were taken in Poiseuille flow that correlates the power law, n, calculated in the classical manner using pressure drop along the tube with the power law, n, calculated from the percolation‐based theory. POLYM. COMPOS., 39:1172–1191, 2018. © 2016 Society of Plastics Engineers

Anterior Thalamic Deep Brain Stimulation: Functional Activation Patterns in a Large Animal Model

Deep brain stimulation (DBS) of the anterior thalamic nucleus (ATN) exerts its effects by modulating neural circuits involved in seizures. However, these networks remain incompletely characterized. Investigate the effects of ATN DBS on network activity in a large animal model using 3-T fMRI. Anesthetized swine underwent ATN DBS using stimulation parameters applied in the Stimulation of the Anterior Thalamus for the Treatment of Epilepsy (SANTE) trial. Stimulation amplitude, frequency, and temporal paradigm were varied and the resulting blood oxygen level-dependent signal was measured. ATN DBS resulted in activation within temporal, prefrontal, and sensorimotor cortex. An amplitude-dependent increase in cluster volume was observed at 60 Hz and 145 Hz stimulation. ATN DBS in swine induced parameter-dependent activation in cortical regions including but not limited to the Papez circuit. These findings may hold clinical implications for treatment of epilepsy in patients with temporal or extratemporal seizure foci.

PECULIAR VELOCITY CONSTRAINTS FROM FIVE-BAND SZ EFFECT MEASUREMENTS TOWARD RX J1347.5−1145 WITH MUSIC AND BOLOCAM FROM THE CSO

ABSTRACT We present Sunyaev-Zel’dovich (SZ) effect measurements from wide-field images toward the galaxy cluster RX J1347.5−1145 obtained from the Caltech Submillimeter Observatory with the Multiwavelength Submillimeter Inductance Camera at 147, 213, 281, and 337 GHz and with Bolocam at 140 GHz. As part of our analysis, we have used higher frequency data from Herschel–SPIRE and previously published lower frequency radio data to subtract the signal from the brightest dusty star-forming galaxies behind RX J1347.5−1145 and from the AGN in RX J1347.5−1145’s BCG. Using these five-band SZ effect images, combined with X-ray spectroscopic measurements of the temperature of the intra-cluster medium (ICM) from Chandra, we constrain the ICM optical depth to be τ e = 7.33 − 0.97 + 0.96 × 10 − 3 ?> and the ICM line of sight peculiar velocity to be v pec = − 1040 − 840 + 870 ?> km s−1. The errors for both quantities are limited by measurement noise rather than calibration uncertainties or astrophysical contamination, and significant improvements are possible with deeper observations. Our best-fit velocity is in good agreement with one previously published SZ effect analysis and in mild tension with the other, although some or all of that tension may be because that measurement samples a much smaller cluster volume. Furthermore, our best-fit optical depth implies a gas mass slightly larger than the Chandra-derived value, implying the cluster is elongated along the line of sight.

Correlation of frontal atrophy with behavioral changes in amyotrophic lateral sclerosis

AbstractBackgroundRecent studies have linked cognitive impairment in amyotrophic lateral sclerosis to frontotemporal pathology.AimWe examined possible associations between behavior changes and regional gray matter volume in early amyotrophic lateral sclerosis, and assessed whether the volume changes were independent of physical impairments.MethodsA total of 17 amyotrophic lateral sclerosis patients with Mini‐Mental State Examination score ≥ 24, no need for assistance in daily life and normal respiratory tests (respiratory function test and arterial blood gas analytes), and 11 age‐matched controls underwent structural magnetic resonance imaging. Behavioral changes were assessed with family‐rating Frontal Systems Behavior Scale. We applied voxel‐based morphometry to investigate the correlation between the Frontal Systems Behavior Scale and gray matter volume, and assessed the correlation of volume with amyotrophic lateral sclerosis Functional Rating Scale and respiratory tests.ResultsCurrent Frontal Systems Behavior Scale scores were significantly higher than retrospective scores assessing the status before onset, most notably in apathy. The volumes of right middle and left medial frontal gyri in amyotrophic lateral sclerosis were negatively correlated with the Frontal Systems Behavior Scale, whereas they were not correlated with amyotrophic lateral sclerosis Functional Rating Scale and respiratory tests. The volume of the right frontal cluster, but not the left medial frontal cluster, was significantly smaller than that of controls.ConclusionsRegional atrophy within the frontal lobe was associated with behavioral dysfunction in early amyotrophic lateral sclerosis, this association was independent of physical factors.

Effects of solute elements on hardening and microstructural evolution in neutron-irradiated and thermally-aged reactor pressure vessel model alloys

ABSTRACTNanometer-sized Cu-enriched solute clusters containing Mn, Ni, and Si atoms are considered as the primary embrittling feature in reactor pressure vessel steels. In order to understand the effects of solute atoms Mn, Ni, and Si on hardening and cluster formation, reactor pressure vessel model alloys FeCu, FeCuSi, FeCuNi, and FeCuNiMn were irradiated at 290 °C in a research reactor. Thermal ageing at 450 °C was also carried out to compare with the results in the neutron irradiation. The addition of Mn resulted in larger hardening and higher cluster number density in both thermal ageing and neutron irradiation. In FeCu0.8NiMn alloy, the size distribution of Cu-enriched clusters formed in 62-h thermal ageing (almost peak hardening) was very similar to that formed in the neutron irradiation, indicating they are on a similar growing stage. But the average Ni and Mn composition in clusters formed in neutron irradiation was higher. A good linear relationship between hardening and the square root of cluster volume fraction for both neutron irradiation and thermal ageing data was found.

Temporal epilepsy lesions may be detected by the voxel-based quantitative analysis of brain FDG-PET images using an original block-matching normalization software.

Statistical parametric mapping (SPM) provides useful voxel-by-voxel analyses of brain images from (18)F-fluorodesoxyglucose positron emission tomography (FDG-PET) after an initial step of spatial normalization through an anatomical template model. In the setting of the preoperative workup of patients with temporal epilepsy, this study aimed at assessing a block-matching (BM) normalization method, where most transformations are computed through small blocks, a principle that minimizes artefacts and overcomes additional image-filtering. Brain FDG-PET images from 31 patients with well-characterised temporal lobe epilepsy and among whom 22 had common mesial temporal lobe epilepsy were retrospectively analysed using both BM and conventional SPM normalization methods and with PET images from age-adjusted controls. Different threshold p values corrected for cluster volume were considered (0.01, 0.005, and 0.001). The use of BM provided equivalent values to those of SPM with regard to the overall volumes of temporal and extra-temporal hypometabolism, as well as similar sensitivity for detecting the involved temporal lobe, reaching 87 and 94% for SPM and BM, respectively, at a threshold p value of 0.01. However, the ability to more accurately localize brain lesions within the mesial portion of the temporal lobe was a little higher with BM than with SPM with respective sensitivities reaching 78% for BM and 45% for SPM (p<0.05). BM normalization compares well with conventional SPM for the voxel-based quantitative analysis of the FDG-PET images from temporal epilepsy patients. Further studies in different population are needed to determine whether BM is truly an accurate alternative to SPM in this setting.

Prognostication of cardiac arrest survivors using low apparent diffusion coefficient cluster volume

IntroductionWe developed a new neuroprognostication method for cardiac arrest (CA) using the relative volume of the most dominant cluster of low apparent diffusion coefficient (ADC) voxels and tested its performance in a multicenter setting. MethodsAdult (>15 years) out-of-hospital CA patients from three different facilities who underwent an MRI 12h after resuscitation were retrospectively analyzed. Patients with unknown long-term prognosis or poor baseline neurologic function were excluded. Average ADCs (mean and median), LADCV (relative volume of low-ADC voxels) and DC-LADCV (relative volume of most dominant cluster of low-ADC voxels) were extracted using different thresholds between 400 and 800×10−6mm2s−1 at 10×10−6mm2s−1 intervals. Area under the receiver operating characteristic curve (AUROC) and sensitivity for poor outcome (6-month cerebral performance category score >2) while maintaining 100% specificity were measured. Results110 patients were analyzed. Average ADCs showed fair performance with an AUROC of 0.822 (95% confidence interval [CI], 0.744–0.900) for the mean and 0.799 (95% CI, 0.716–0.882) for the median. LADCV showed better performance with a higher AUROC (maximum, 0.925) in an ADC threshold range of 400 to 690×10−6mm2s−1. DC-LADCV showed the best performance with a higher AUROC (maximum, 0.955) compared with LADCV in an ADC threshold range of 600 to 680×10−6mm2s−1. DC-LADCV had a high sensitivity for poor outcomes (>80%) in a wide threshold range from 400 to 580×10−6mm2s−1 with a maximum of 89.2%. ConclusionsQuantitative analysis using DC-LADCV showed impressive performance in determining the prognosis of out-of-hospital CA patients in a multicenter setting.

Grid-Free Octree Approach for Modeling Heat Transfer to Complex Geometries

The grid-free octree direct simulation Monte–Carlo algorithm has been explored to simulate flows through and heat transfer to highly irregular geometries for finite Knudsen numbers. The approach was extended to accurately compute the volume of irregular octree clusters as well as a line-of-sight test before performing collisions in octree clusters that are intersected by a solid boundary. The modified grid-free octree direct simulation Monte–Carlo algorithm was tested for the classic Fourier and micro-Poiseuille flows. A single sphere as well as an aggregate of spheres were modeled in a 500 K heat bath and supersonic flow. For the heat bath case, it was observed that a two-level Cartesian grid direct simulation Monte–Carlo code was able to achieve the same heat flux to a single sphere as the octree approach if 10 times more computational particles were used. Furthermore, even with increased computational load, the two-level Cartesian approach encountered a difference of 15% from the octree calculation for heat flux for interior spheres due to shielding by outer spheres. It was found that, for supersonic flows surrounding a single sphere and an aggregate, the octree approach was able to resolve the detached bow shock as well as the wake region, and in the aggregate case, the spatial resolution was sufficient to capture distinct multiple shocks in terms of temperature jump and pressure contours. Computational efficiency in terms of central processing unit–graphical processing unit computing is also discussed.

INFRARED OBSERVATIONAL MANIFESTATIONS OF YOUNG DUSTY SUPER STAR CLUSTERS

ABSTRACT The growing evidence pointing at core-collapse supernovae as large dust producers makes young massive stellar clusters ideal laboratories to study the evolution of dust immersed in a hot plasma. Here we address the stochastic injection of dust by supernovae, and follow its evolution due to thermal sputtering within the hot and dense plasma generated by young stellar clusters. Under these considerations, dust grains are heated by means of random collisions with gas particles which result in the appearance of infrared spectral signatures. We present time-dependent infrared spectral energy distributions that are to be expected from young stellar clusters. Our results are based on hydrodynamic calculations that account for the stochastic injection of dust by supernovae. These also consider gas and dust radiative cooling, stochastic dust temperature fluctuations, the exit of dust grains out of the cluster volume due to the cluster wind, and a time-dependent grain size distribution.