Height Threshold Research Articles

Research on Navigation Path Extraction and Obstacle Avoidance Strategy for Pusher Robot in Dairy Farm

Existing push robots mainly use magnetic induction technology. These devices are susceptible to external electromagnetic interference and have a low degree of intelligence. To make up for the insufficiency of the existing material pushing robots, and at the same time solve the problems of labor-intensive, labor-intensive, and inability to push material in time at night, etc., in this study, an autonomous navigation pusher robot based on 3D lidar is designed, and an obstacle avoidance strategy based on the improved artificial potential field method is proposed. Firstly, the 3D point cloud data of the barn is collected by the self-designed pushing robot, the point cloud data of the area of interest is extracted using a direct-pass filtering algorithm, and the 3D point cloud of the barn is segmented using a height threshold. Secondly, the Least-Squares Method (LSM) and Random Sample Consensus (RANSAC) were used to extract fence lines, and then the boundary contour features were extracted by projection onto the ground. Finally, a target influence factor is added to the repulsive potential field function to determine the principle of optimal selection of the parameters of the improved artificial potential field method and the repulsive direction, and to clarify the optimal obstacle avoidance strategy for the pusher robot. It can verify the obstacle avoidance effect of the improved algorithm. The experimental results showed that under three different environments: no noise, Gaussian noise, and artificial noise, the fence lines were extracted using RANSAC. Taking the change in the slope as an indicator, the obtained results were about −0.058, 0.058, and −0.061, respectively. The slope obtained by the RANSAC method has less variation compared to the no-noise group. Compared with LSM, the extraction results did not change significantly, indicating that RANSAC has a certain resistance to various noises, but RANSAC performs better in extraction effect and real-time performance. The simulation and actual test results show that the improved artificial potential field method can select reasonable parameters and repulsive force directions. The optimized path increases the shortest distance of the obstacle point cloud from the navigation path from 0.18 to 0.41 m, where the average time is 0.059 s, and the standard deviation is 0.007 s. This shows that the optimization method can optimize the path in real time to avoid obstacles, basically meet the requirements of security and real-time performance, and effectively avoid the local minimum problem. This research will provide corresponding technical references for pusher robots to overcome the problems existing in the process of autonomous navigation and pushing operation in complex open scenarios.

Mechanical shock-induced nucleation in solution: Is cavitation necessary?

Mechanical shock-induced nucleation (MSIN) of crystals from aqueous supersaturated solutions of ammonium chloride is reported. A simple apparatus was constructed to expose solutions in glass vials to a single impact, while images were recorded using a fast camera. A strong correlation between cavitation in the liquid and nucleation of solid ammonium chloride was revealed. The measured fraction of solutions nucleated as a function of impact height was fitted using a Poisson model. The mean number of solution samples nucleated increased quadratically with impact height above a threshold height. Analysis of images showed that the accelerations achieved were sufficient to induce cavitation based on the cavitation number proposed by Pan et al. [Proc. Natl. Acad. Sci. USA 114 (2017) 8470]. The use of a hydrophobic coating on the internal glass surface was shown to significantly increase both the number of cavities observed and the probability of MSIN of solid crystals. The results presented suggest that MSIN of ammonium chloride salt is mediated by cavitation.

A Robust Gaussian Process-Based LiDAR Ground Segmentation Algorithm for Autonomous Driving

Robust and precise vehicle detection is the prerequisite for decision-making and motion planning in autonomous driving. Vehicle detection algorithms follow three steps: ground segmentation, obstacle clustering and bounding box fitting. The ground segmentation result directly affects the input of the subsequent obstacle clustering algorithms. Aiming at the problems of over-segmentation and under-segmentation in traditional ground segmentation algorithms, a ground segmentation algorithm based on Gaussian process is proposed in this paper. To ensure accurate search of real ground candidate points as training data for Gaussian process, the proposed algorithm introduces the height and slope criteria, which is more reasonable than the use of fixed height threshold for searching. After that, a sparse covariance function is introduced as the kernel function for calculation in Gaussian process. This function is more suitable for ground segmentation situation the radial basis function (RBF). The proposed algorithm is tested on our autonomous driving experimental platform and the public autonomous driving dataset KITTI, compared with the most used RANSAC algorithm and ray ground filter algorithm. Experiment results show that the proposed algorithm can avoid obvious over-segmentation and under-segmentation. In addition, compared with the RBF, the introduction of the sparse covariance function also reduces the computation time by 37.26%.

A heuristic features selection approach for scenario analysis in a regional seismic probabilistic tsunami hazard assessment

Seismic Probabilistic Tsunami Hazard Analysis (SPTHA) is aimed at estimating the annual rate of exceedance of an earthquake-induced tsunami wave of a certain location with reference to a predefined height threshold. The analysis relies on computationally demanding numerical simulations of seismic-induced tsunami wave generation and propagation. A large number of scenarios needs to be simulated to account for uncertainties. However, the exceedance of tsunami wave threshold height is a rare event so that most of the simulated scenarios bring little statistical contribution to the estimation of the annual rate yet increasing the computational burden. To efficiently address this issue, we propose a wrapper-based heuristic approach to select the set of most relevant features of the seismic model, for deciding a priori the seismic scenarios to be simulated. The proposed approach is based on a Multi-Objective Differential Evolution Algorithm (MODEA) and is developed with reference to a case study whose objective is calculating the annual rate of threshold exceedance of the height of tsunami waves caused by subduction earthquakes that might be generated on a section of the Hellenic Arc, and propagated to a set of target sites: Siracusa, on the eastern coast of Sicily, Crotone, on the southern coast of Calabria, and Santa Maria di Leuca, on the southern coast of Puglia. The results show that, in all cases, the proposed approach allows a reduction of 95% of the number of scenarios with half of the features to be considered, and with no appreciable loss of accuracy.

The 21st August 2020 Flood in Douala (Cameroon): A Major Urban Flood Investigated with 2D HEC-RAS Modeling

A major flood event occurred on 21 August 2020 in the densely populated Makèpè Missokè neighborhood in the city of Douala (Cameroon, Africa). Nearly 2210 buildings and 12,376 victims spread over 82 hectares were affected. A 2D HEC-RAS model is applied to simulate and characterize this event. A cross analysis of flood depth and flow velocity is used to classify the flood risk and identify areas exposed from low to high hazard. The simulations provide detailed information on the flood characteristics (extent, depth, velocity, arrival time, and duration). The simulated maximum water surface profiles are consistent with the floods marks with differences ranging from 0.02 m to 0.44 m, indicating a good agreement between the observed and simulated water levels at the peak flow (NSE = 0.94, Erel = 0.92, RMSE = 0.21 m). The maximum inundation level is 4.48 m and the flow velocity is globally low at less than 1 m/s. The average flood arrival time and duration are 5 h and 26 h, respectively, for a threshold height of 0.5 m. These results indicate a fast mobilization of the major river channel for the evacuation of this flood. The level of accuracy of the developed model of the 21 August 2020 flood event is appropriate for flood hazard assessment in the city of Douala and is designed to find operational application in future events.

Numerical investigation of microchannel geometry for effective on-chip biofluid delivery by AC electrothermal effect.

Although there exist tremendous needs for on-chip biofluid delivery, research in this field has yielded limited numbers of devices for real-world applications. One challenge is the difficulty for micropumps to meet the requirements of being low cost to fabricate, easy to integrate and effective for intended applications at the same time. This research focuses on AC electrothermal (ACET) micropumps based on planar interdigitated electrodes, due to their practicality in fabrication and operation, and compatibility with biochemical fluids. Our prior work has optimized the design of electrode dimensions for a fixed microchannel design. This work finds that microchannel dimensions can also affect ACET micropumps significantly, with respect to flow rate and electric impedance loading. This work first considers the constraints arising from impedance loading by ACET micropumps on power supplies, then the investigation describes several key parameters (threshold height, saturation thickness), to arrive at an appropriate microchannel geometry for the effective delivery of biofluids. The optimized microchannel is expected to incorporate well into a multifunctional lab-chip system to transport biofluids efficiently.

Modeling effectiveness of two runoff mitigation measures in the Netherlands

Rainfall that exceeds the soil's maximum infiltration rate is prone to runoff, and the excess rainfall will flow toward open water systems. Nutrients, pesticides or other contaminants may be transported along with this overland flow, thus contaminating surface waters. There are various measures that can be implemented to prevent or reduce runoff, which involve either improving the soil's infiltration capacity or temporarily storing more water at the field scale. The aim of this study was to determine the effectiveness of two mitigation measures, i.e., micro-dams and edge-of-field trenches, in reducing the total number of runoff events and the runoff volume for specific rainfall events. For this purpose, numerical simulations were performed with a deterministic soil–water–atmosphere–plant model for reference situations and for situations involving either of the two mitigation measures. The mitigation measures are implemented as a change in the ponding threshold height above which the model predicts runoff. For this purpose, we considered several soil / groundwater level / crop / intrinsic field soil surface storage situations that are common in the Netherlands. For ridge-furrow cropping systems, micro-dams are more effective than edge-of-field trenches. Depending on the soil type (excluding sand), the minimum effectiveness is 70% and may be >90% in specific situations. For the edge-of-field trench, the reduction in runoff events was mostly in the 24–35% range, while the effectiveness for the runoff volume for a rainfall event that typically occurs once per year was in the 13–48% range (excluding sand). Due to the relatively high hydraulic conductivity at saturation for the sandy soils, runoff was simulated in only a few cases for these soils. The effectiveness was evidently dependent on intrinsic field soil surface storage and soil types, varied slightly between crop types and was very similar across the groundwater level classes considered.

Inverse Association Between Resting-State Putamen Activity and Iowa Gambling Task Performance in Patients With Obsessive-Compulsive Disorder and Control Subjects.

BackgroundSymptoms of obsessive-compulsive disorder (OCD) have been conceptualized as manifestations of decision-making deficits. Patients with OCD exhibit impairment during the decision-making process, as assessed by the Iowa Gambling Task (IGT). This impairment is independent of clinical severity and disease progression. However, the association between the decision-making deficit and resting-state brain activity of patients with OCD has not been examined.MethodsFifty unmedicated patients with OCD and 55 matched control subjects completed IGT. Resting-state brain activity was examined using the fractional amplitude of low-frequency fluctuations (fALFFs). fALFF analysis focused on the slow-4 and 5 bands. Group comparisons were performed to determine the association between IGT performance and fALFFs.ResultsThere was a significant group difference in the association between the IGT total net score and slow-4 fALFFs in the left putamen (voxel height threshold of p < 0.001; cluster size threshold of p < 0.05; family wise error-corrected). Higher putamen slow-4 fALFFs were correlated with lower IGT scores for OCD patients (r = −0.485; p < 0.0005) and higher IGT scores for control subjects (r = 0.402; p < 0.005). There was no group difference in the association between the IGT total net score and slow-5 fALFFs.ConclusionsThese findings in unmedicated patients demonstrate the importance of resting-state putamen activity for decision-making deficit associated with OCD, as measured by IGT. The inverse correlation may be explained by the hypersensitive response of the putamen in patients with OCD.

Quantifying Infant Exploratory Learning.

Exploration is considered essential to infant learning, but few studies have quantified infants' task exploration. The purpose of this study was to quantify how infants explored task space with their feet while learning to activate a kick-activated mobile. Data were analyzed from fifteen 4-month-old infants who participated in a 10-min mobile task on 2-3 consecutive days. Infants learned that their vertical leg movements above a systematically increased threshold height activated the mobile. Five kinematic variables were analyzed: 1) exploration space volume, 2) exploration path length, 3) duration of time in the region of interest around the threshold that activated the mobile, 4) task-specific vertical variance of kicks, and 5) non-task-specific horizontal variance of kicks. The infants increased their general spatial exploration, volume and path, and the infants adapted their exploration by maintaining their feet within the region of interest although the task-specific region increased in height as the threshold increased. The infants used task-specific strategies quantified by the increased variance of kicks in the vertical direction and no change in the horizontal variance of kicks. Quantifying infants' task exploration may provide critical insights into how learning emerges in infancy and enable researchers to more systematically describe, interpret, and support learning.

The response of sub‐adult savanna trees to six successive annual fires: An experimental field study on the role of fire season

Abstract In mesic savannas worldwide, trees experience frequent fires, almost all set by humans. Management fires are set to reduce or enhance tree cover. Success depends greatly on responses of sub‐adult trees to such fires. To date, the number of successive years that sub‐adult trees can resprout nor the number of years that they must resist being top‐killed by successive fires, nor the requisite height, have been reported. In a 6‐year experimental field study in Guinean savannas of West Africa, we monitored annually the heights and responses of 1,765 permanently tagged sub‐adult trees under annual fires set in three different periods of the long dry season: early‐dry season (EDS), mid‐dry season (MDS) and late‐dry season (LDS). Annual MDS fires are the common local management protocols of Guinean savannas, although EDS fires are common in some of the savannas. Results showed that overall, the proportion of sub‐adults that resisted being top‐killed differed across fire seasons. Furthermore, resisting one fire gave a better chance of resisting the next. Only sub‐adults that were able to resist direct damage for three successive EDS and MDS fires reached sufficient height to be recruited to the adult stage. Resistance height (avoiding topkill) was ∼1 m for EDS and ∼2 m for both MDS and LDS fires. Recruitment height (threshold for transition to adult stage) was ∼3 m for EDS and ∼ 3.3 m for MDS fires. No height was great enough for sub‐adult trees to be recruited to adult stages in LDS fire. Synthesis and applications. The results of this novel field study showed clearly that successive early‐ and mi‐dry season fires can enhance tree density and that successive late‐dry season fires alone reduce tree density in Guinean savannas due to the effects of successive fires on sub‐adult trees. The results suggest that a planned regime of these seasons of fire could be used to maintain the desired tree density in Guinean savannas and may inform fire management in other mesic savannas where goals are to increase or decrease tree densities. It also provides relevant information for comparative studies on the mechanisms of recruitment of sub‐adult trees to an adult stage in all mesic savannas, a process that ultimately determines savanna physiognomy.

Parallel density scanned adaptive Kriging to improve local tsunami hazard assessment for coastal infrastructures

Seismic Probabilistic Tsunami Hazard Assessment (SPTHA) is a framework for calculating the probability that seismically induced tsunami waves exceed a specific threshold height, over a given time span and a specific region (i.e. regional SPTHA) or site (i.e. local SPTHA). To account for the uncertainty of the possible sources, SPTHA must integrate the results of a large number of computationally demanding tsunami simulationsIn this work, we innovatively use Parallel density scanned Adaptive Kriging (P-ds AK) to overcome the computational efficiency challenge of local SPTHA within a framework that consists in modeling/retrieving the full spectrum of possible earthquake triggering events at the regional level, filtering sources not relevant for the target, adopting a clustering procedure to select “representative scenarios” for inundation modeling, and, finally, adopt P-ds AK to identify the clusters centroids that most influence the hazard intensity (i.e., wave height) in the areas of interest.This approach is applied in the area of the oil refinery located in Milazzo (Italy). The application shows a consistent reduction of the number of high-resolution tsunami simulations required for the evaluation of the hazard curves over a set of inland Point of Interest (PoIs), either concentrated in one specific area or distributed along the coast.

Vibration-induced segregation characteristics of binary pebble beds in confined containers

This paper presents the study of the segregation characteristics of bi-disperse mixed pebble beds under different confined conditions and vibration conditions by the Discrete Element Method. The Lacey index and the λ index are used to evaluate the degree of particle mixing or segregation. Results show that confined containers can suppress the segregation of the pebble beds when the top free space height is below a threshold. Further simulation reveals that this threshold of the free space height is related to the maximum bed height increment in an unconfined state and impacted by the vibration amplitude and frequency. However, the particle diameter ratio as well as the container shape and size seem to have a limited effect on the threshold. These findings are helpful to clarify the suppression effect of container confinement on the pebble bed segregation and its main resulting factors, and hence provide solutions to controlling vibration-induced segregation.

A Conceptual Model for Detecting Small-Scale Forest Disturbances Based on Ecosystem Morphological Traits

Current LiDAR-based methods for detecting forest change use a host of statistically selected variables which typically lack a biological link with the characteristics of the ecosystem. Consensus of the literature indicates that many authors use LiDAR to derive ecosystem morphological traits (EMTs)—namely, vegetation height, vegetation cover, and vertical structural complexity—to identify small-scale changes in forest ecosystems. Here, we provide a conceptual, biological model for predicting forest aboveground biomass (AGB) change based on EMTs. We show that through use of a multitemporal dataset it is possible to not only identify losses caused by logging in the period between data collection but also identify regions of regrowth from prior logging using EMTs. This sensitivity to the change in forest dynamics was the criterion by which LiDAR metrics were selected as proxies for each EMT. For vegetation height, results showed that the top-of-canopy height derived from a canopy height model was more sensitive to logging than the average or high percentile of raw LiDAR height distributions. For vegetation cover metrics, lower height thresholds for fractional cover calculations were more sensitive to selective logging and the regeneration of understory. For describing the structural complexity in the vertical profile, the Gini coefficient was found to be superior to foliage height diversity for detecting the dynamics occurring over the years after logging. The subsequent conceptual model for AGB estimation obtained a level of accuracy which was comparable to a model that was statistically optimised for that same area. We argue that a widespread adoption of an EMT-based conceptual approach would improve the transferability and comparability of LiDAR models for AGB worldwide.

Quality evaluation of honing surface groove features based on improved Level-Set analyses

Honing groove features of a cylinder liner surface contain helpful information on surface performance. Traditional honing surface evaluation methods do not focus on groove features, which is significant to surface functions. Hence, a topographical feature segmentation algorithm and corresponding evaluation parameters are needed. This paper proposes an improved level-set-based segmentation algorithm for groove feature extraction. The proposed algorithm was tested on a real honing surface dataset compared to some state-of-art algorithms, including the classical height thresholding and watershed segmentation. The results show that the proposed method is robust against initial conditions and improves both segmentation accuracy and computational speed. Specifically, a 30% accuracy improvement over the best-tested level-set algorithm has been observed. Another case study on fold-mental characterization was conducted, which also validated the accuracy and speed performance of the proposed algorithm.

Amyotrophic lateral sclerosis with SOD1 mutations shows distinct brain metabolic changes

PurposeNeuropathological data suggest that ALS with SOD1 mutations (SOD1-ALS) is a distinct form of ALS. We evaluated brain metabolic changes characterizing SOD1-ALS as compared to sporadic ALS (sALS), employing 18fluorodeoxyglucose-positron-emission tomography (18F-FDG-PET).MethodsWe included 18 SOD1-ALS patients, 40 healthy controls (HC), and 46 sALS patients without mutations in SOD1, TARDBP, FUS, and C9ORF72, randomly selected from 665 subjects who underwent brain 18F-FDG-PET at diagnosis between 2008 and 2019 at the ALS Centre of Turin. We excluded patients with frontotemporal dementia. We used the full factorial design in SPM12 to evaluate whether differences among groups exist overall. In case the hypothesis was confirmed, group comparisons were performed through the two-sample t-test model of SPM12. In all the analyses, the height threshold was P < 0.001 (P < 0.05 FWE-corrected at cluster level).ResultsThe full factorial design resulted in a significant main effect of groups. We identified a relative hypometabolism in sALS patients compared to SOD1-ALS cases in the right precentral and medial frontal gyrus, right paracentral lobule, and bilateral postcentral gyrus. SOD1 patients showed a relative hypermetabolism as compared to HC in the right precentral gyrus and paracentral lobule. As compared to HC, sALS patients showed relative hypometabolism in frontal, temporal, and occipital cortices.ConclusionSOD1-ALS was characterized by a relative hypermetabolism in the motor cortex as compared to sALS and HC. Since promising, targeted, therapeutic strategies are upcoming for SOD1-ALS, our data support the use of PET to study disease pathogenesis and to track its course in clinical trials, in both asymptomatic and symptomatic mutation carriers.

On Correlation between Wind and Wave Storms

The paper is focused on the formulation of an adequate criterion for associating wave storm events to the generating wind storm ones, and on the study of correlation between their characteristic parameters. In this context, the sea storm definition commonly used for storm identification from significant wave height data is adapted for wind storm, by processing wind speed data. A sensitivity analysis is proposed as function of the storm thresholds aiming at identifying optimal combination of wind speed and significant wave height thresholds allowing the association of relatively large number of events ensuring high correlation between wind and wave storm parameters. The analysis is carried out using as input data wind speeds and significant wave heights from four meteorological (buoys and anemometers) stations of the National Data Buoy Center moored off the East Coast of the United States. Results reveal that an optimal threshold combination is achieved assuming both wind speed and significant wave height threshold as 1.5 time their respective averages.

Presymptomatic and symptomatic MAPT mutation carriers feature functional connectivity alterations

AbstractBackgroundClinical trials for tauopathies require novel biomarkers for disease detection and monitoring. One previous study found functional connectivity (FC) alterations in presymptomatic (preSx) MAPT mutation carriers (Whitwell et al., 2011), yet studies have not examined FC networks along the MAPT disease continuum. We hypothesized that both symptomatic (Sx) and preSx MAPT mutation carriers would show FC alterations compared to healthy controls (HC).MethodLeveraging task‐free fMRI data from the UCSF Memory and Aging Center and the ARTFL/LEFFTDS Consortia (Boeve et al., 2019), we compared 14 Sx and 33 preSx to 80 HC to characterize their FC profiles. Using a seed‐based approach, we studied FC within networks associated with different MAPT clinical syndromes (i.e., salience network [SN] for behavioral variant frontotemporal dementia, default mode network [DMN] for Alzheimer’s‐like amnestic syndrome, corticobasal syndrome [CBS] and progressive supranuclear palsy [PSP] networks). Complementing the seed‐based approach, we next calculated whole‐brain intra‐/inter‐network FC matrices for 14 networks (Brown et al., 2019), and applied K‐means clustering to assess whether preSx displayed heterogeneous connectivity profiles. ComBat was applied to harmonize multi‐site imaging data (Fortin et al., 2017, 2018). Thresholding was set at a joint height and extent threshold of p&lt;0.05 (uncorrected) with age, sex, education and handedness as nuisance covariates.ResultCompared to HC, Sx featured disrupted FC within key hubs of all four networks, and regions of cerebellar and pontine hyperconnectivity within CBS and PSP networks. As seen in Sx vs. HC, preSx had similar anatomical patterns of SN/CBS network hypoconnectivity and CBS/PSP network hyperconnectivity vs. HC. In contrast to Sx, who had DMN disruption, preSx showed DMN hyperconnectivity vs. HC.Whole‐brain analyses revealed that Sx had disrupted intra‐/inter‐network FC in networks involving the insula/anterior temporal lobe. Clustering analysis identified two preSx subgroups. Compared to HC, preSx1 principally had disrupted FC across networks including those disrupted in Sx, whereas preSx2 mainly demonstrated hyperconnectivity.ConclusionSx and preSx both demonstrated robust FC alterations. Future studies will investigate whether the preSx subgroup whose whole‐brain FC was similar to Sx in that it showed principally FC disruption may be at greater risk for imminent symptom conversion and/or neurodegeneration.

Voxel‐based correlation of 18F‐THK5351 accumulation with gray matter structural networks in cognitively normal older adults

AbstractBackgroundAlthough gray matter (GM) structural networks based on intracortical similarities have been proposed, no studies have yet examined the correlations between GM network measures and tau. Here, we investigated the voxel‐wise correlations of GM network measures and 18F‐THK5351 accumulation in cognitively normal (CN) older adults.MethodWe recruited 47 amyloid‐negative CN older adults (65.0 ± 7.9 y age, 26 female, 14.3 ± 2.4 y education, Mini‐Mental State Examination score 29.3 ± 1.1, Wechsler Memory Scale‐Revised Logical Memory II score 13.4 ± 2.9). All participants underwent 3D T1‐weighted MRI, 11C‐PiB and 18F‐THK5351 PET scans. Single‐subject GM networks extracted from T1‐weighted MRI data based on intracortical similarities were analyzed using the graph theoretical approach. Correlations between four local network measures (betweenness centrality, clustering coefficient, characteristic path length, and degree) and 18F‐THK5351 standardized uptake value ratio (SUVR) images were evaluated at a voxel level using biological parametric mapping (BPM) toolbox in SPM. The results with the following criteria were deemed significant: a height threshold of p &lt; .05 (family‐wise error corrected) with an extent threshold of 100 voxels.ResultSignificant positive correlations between four local network measures and 18F‐THK5351 SUVR images were detected in the bilateral caudate.ConclusionUsing voxel‐based analysis, we detected significant positive correlations between local network measures and 18F‐THK5351 accumulation in the bilateral caudate in CN older adults. Our findings suggest that tau and neuroinflammation in CN elderly may influence local GM network in the caudate.

7T imaging in progressive supranuclear palsy and behavioural variant frontotemporal dementia

AbstractBackgroundProgressive supranuclear palsy (PSP) and behavioural variant frontotemporal dementia (bvFTD) are clinical syndromes associated with frontotemporal lobar degeneration (FTLD). Although distinct diseases, they have in common cognitive and behavioural changes, including personality, motivation and executive function. This phenotypic overlap between bvFTD and PSP is reflected in the MDS‐2017 criteria for the PSP‐F subtype (Höglinger et al., 2017), and frequent parkinsonism seen in bvFTD (Rowe, 2019). This study uses ultra‐high field MRI to identify the atrophy patterns in bvFTD and PSP, complementing neurochemical insights from spectroscopy (Murley, 2020).Method23 Healthy controls, 23 people with probable PSP, and 16 people with bvFTD underwent structural imaging with MP2RAGE sequence (0.7mm isotropic resolution) at ultra‐high field (7T) on a MAGNETOM Siemens TERRA scanner. Clinical and cognitive assessment was undertaken contemporary with imaging. Grey and white matter volumes were compared between groups using independent two‐sample t‐tests, including age and total intracranial volume as covariates of no interest. Significant effects were identified using cluster‐level statistics (p&lt;0.05, family‐wise error corrected for multiple comparisons) above a height threshold of p&lt;0.001 (uncorrected).ResultCompared to controls, both patients with PSP and bvFTD show significant atrophy of the cingulate gyrus, frontal gyri, and the supplementary motor cortex with the parietal and especially occipital lobe being spared (p &lt;0.05, FWE). Patients with PSP show additional white matter atrophy of the brainstem and basal ganglia (p &lt;0.05, FWE). Compared to PSP, patients with bvFTD show more grey matter atrophy in the inferior frontal gyrus, inferior temporal gyrus, temporal pole, as well as the right insula. Patients with PSP show more white matter atrophy of the basal ganglia, brain stem, and superior cerebellum compared to those with bvFTD (p&lt;0.001, uncorrected).ConclusionThis is the first voxel‐based morphometry study comparing bvFTD and PSP at ultra‐high field, with higher resolution imaging than previous studies at 1.5T or 3.T. Although both classified as syndromes associated with FTLD, patients with bvFTD and PSP show both specific and complementary patterns of atrophy compared to those of healthy controls and each other.

Lava Dome Morphology and Viscosity Inferred From Data-Driven Numerical Modeling of Dome Growth at Volcán de Colima, Mexico During 2007-2009

Magma extrusion, lava dome growth, collapse of domes, and associated pyroclastic flow hazards are among important volcanological studies. In this paper, we analyze the influence of the magma viscosity and discharge rates on the lava dome morphology at Volcán de Colima in Mexico during a long dome-building episode lasting from early 2007 to fall 2009 without explosive dome destruction. Camera images of the lava dome growth together with recorded volumes of the erupted lava have been used to constrain numerical modeling and hence to match the history of the dome growth by nudging model forecasts to observations. Our viscosity model incorporates crystal growth kinetics and depends on the characteristic time of crystal content growth (or CCGT) and the crystal-free magma viscosity. Initially, we analyze how this viscosity, CCGT, and the rate of lava extrusion influence the morphology of the growing dome. Several model scenarios of lava dome growth are then considered depending on the crater geometry, the conduit location, the effective viscosity of dome carapace, and the extrusion rates. These rates are determined either empirically by optimizing the fit between the morphological shape of modeled domes and that of the observed dome or from the recorded lava dome volumes. The maximum height of the modeled lava dome and its horizontal extent are in a good agreement with observations in the case of the empirically-derived extrusion rates. It is shown that the topography of the crater at Volcán de Colima is likely to be inclined toward the west. The viscosity of the modeled lava dome (∼1012 Pa s) is in a good agreement with the effective viscosity estimated experimentally from lavas of Volcán de Colima. Due to the interplay between the lava extrusion and the gravity forces, the dome reaches a height threshold, and after that a horizontal gravity spreading starts to play an essential role in the lava dome evolution. The model forecasts that the dome carapace of higher viscosity (∼1014 Pa s) influences the dome growth and its morphology during long dome-building episodes by retarding horizontal advancement and developing steep-sided eastern edge of the dome at the volcano. The developed model can be used in assessments of future effusive eruptions and lava dome growth at Volcán de Colima or elsewhere. History matching modeling of lava dome growth sheds a light on dynamic processes inside the dome and may assist in assessing stress state in the dome carapace and in forecasting the dome failures.