Analysis Of Orientation Data Research Articles

Comparison of Resting State Functional Connectivity in Persons With and Without HIV: A Cross-sectional Study.

This study examined the effects of human immunodeficiency virus (HIV) on resting state functional connectivity (RSFC) in a large cohort of people with HIV (PWH) and healthy controls without HIV (PWoH). Within PWH analyses focused on the effects of viral suppression and cognitive impairment on RSFC. A total of 316 PWH on stable combination antiretroviral therapy and 209 demographically matched PWoH were scanned at a single institution. Effects of the virus were examined by grouping PWH by detectable (viral load > 20 copies/mL; VLD) and undetectable (VLU) viral loads and as being cognitively impaired (CI) (Global Deficit Score ≥ 0.5) or cognitively normal (CN). Regression analysis, object oriented data analysis, and spring embedded graph models were applied to RSFC measures from 298 established brain regions of interest comprising 13 brain networks to examine group differences. No significant RSFC differences were observed between PWH and PWoH. Within PWH, there were no significant differences in RSFC between VLD and VLU subgroups and CI and CN subgroups. There were no significant effects of HIV on RSFC in our relatively large cohort of PWH and PWoH. Future studies could increase the sample size and combine with other imaging modalities.

Effects of Virtual Reality-Based Multimodal Audio-Tactile Cueing in Patients With Spatial Attention Deficits: Pilot Usability Study.

BackgroundVirtual reality (VR) devices are increasingly being used in medicine and other areas for a broad spectrum of applications. One of the possible applications of VR involves the creation of an environment manipulated in a way that helps patients with disturbances in the spatial allocation of visual attention (so-called hemispatial neglect). One approach to ameliorate neglect is to apply cross-modal cues (ie, cues in sensory modalities other than the visual one, eg, auditory and tactile) to guide visual attention toward the neglected space. So far, no study has investigated the effects of audio-tactile cues in VR on the spatial deployment of visual attention in neglect patients.ObjectiveThis pilot study aimed to investigate the feasibility and usability of multimodal (audio-tactile) cueing, as implemented in a 3D VR setting, in patients with neglect, and obtain preliminary results concerning the effects of different types of cues on visual attention allocation compared with noncued conditions.MethodsPatients were placed in a virtual environment using a head-mounted display (HMD). The inlay of the HMD was equipped to deliver tactile feedback to the forehead. The task was to find and flag appearing birds. The birds could appear at 4 different presentation angles (lateral and paracentral on the left and right sides), and with (auditory, tactile, or audio-tactile cue) or without (no cue) a spatially meaningful cue. The task usability and feasibility, and 2 simple in-task measures (performance and early orientation) were assessed in 12 right-hemispheric stroke patients with neglect (5 with and 7 without additional somatosensory impairment).ResultsThe new VR setup showed high usability (mean score 10.2, SD 1.85; maximum score 12) and no relevant side effects (mean score 0.833, SD 0.834; maximum score 21). A repeated measures ANOVA on task performance data, with presentation angle, cue type, and group as factors, revealed a significant main effect of cue type (F30,3=9.863; P<.001) and a significant 3-way interaction (F90,9=2.057; P=.04). Post-hoc analyses revealed that among patients without somatosensory impairment, any cue led to better performance compared with no cue, for targets on the left side, and audio-tactile cues did not seem to have additive effects. Among patients with somatosensory impairment, performance was better with both auditory and audio-tactile cueing than with no cue, at every presentation angle; conversely, tactile cueing alone had no significant effect at any presentation angle. Analysis of early orientation data showed that any type of cue triggered better orientation in both groups for lateral presentation angles, possibly reflecting an early alerting effect.ConclusionsOverall, audio-tactile cueing seems to be a promising method to guide patient attention. For instance, in the future, it could be used as an add-on method that supports attentional orientation during established therapeutic approaches.

Review of ‘Object Oriented Data Analysis’

Review of ‘Object Oriented Data Analysis’

Grain boundary dynamics and selective grain growth in non-ferromagnetic metals in high magnetic fields

Abstract Grain boundary motion can be affected by a magnetic field if the anisotropy of the magnetic susceptibility generates a gradient of the magnetic free-energy density across the boundary. Due to this magnetic driving force, annealing of locally deformed single crystals in high magnetic fields results in growth selection. The character distribution of the boundaries connected to growth selection is found to be far from random. If a magnetic energy density gradient as a driving force is superimposed to a curvature driving force during grain growth, this biases the microstructure evolution with regard to grain size and crystallographic texture, as it is demonstrated on polycrystalline zinc and titanium. Analysis of individual orientation data reveals that the observed asymmetrical texture stems to a large extent from a difference in grain numbers of the individual texture components.

REST-for-Physics, a ROOT-based framework for event oriented data analysis and combined Monte Carlo response

The REST-for-Physics (Rare Event Searches Toolkit for Physics) framework is a ROOT-based solution providing the means to process and analyze experimental or Monte Carlo event data. Special care has been taken to the traceability of the code and the validation of the results produced within the framework, together with the connectivity between code and stored data, registered through specific version metadata members.The framework development was originally motivated to cover the needs of Rare Event Searches experiments (experiments looking for phenomena having extremely low occurrence probability, like dark matter or neutrino interactions or rare nuclear decays). The framework components naturally implement tools to address the challenges in these kinds of experiments. The integration of a detector physics response, the implementation of signal processing routines, or topological algorithms for physical event identification are some examples. Despite this specialization, the framework was conceived thinking in scalability. Other event-oriented applications could benefit from the data processing routines and/or metadata description implemented in REST, being the generic framework tools completely decoupled from dedicated libraries.REST-for-Physics is a consolidated piece of software already serving the needs of different physics experiments - using gaseous Time Projection Chambers (TPCs) as detection technology - for detector data analysis and characterization, as well as generic R&D. Even though REST has been exploited mainly with gaseous TPCs, the code could be easily applied or adapted to other detector technologies. We present in this work an overview of REST-for-Physics, providing a broad perspective to the infrastructure and organization of the project as a whole. The framework and its different components will be described in the text.

A general bi-clustering algorithm for object data with an application to the analysis of a Lombardy railway line

A general and flexible bi-clustering algorithm for the analysis of Hilbert data is presented in the Object Oriented Data Analysis framework. The algorithm, called HC2 (i.e. Hilbert Cheng and Church), is a non-parametric method to bi-cluster Hilbert data indexed in a matrix structure. The Cheng and Church approach is here extended to the general case of data embedded in a Hilbert space and then applied to the analysis of the regional railway service in the Lombardy region with the aim of identifying recurrent patterns in the passengers' daily access to trains and/or stations. The analysed data, modelled as multivariate functional data and time series, allows to measure both overcrowding and travel demand, providing useful insights to best handle the service.

A Multi-Scale Approach for Phase Field Modeling of Ultra-Hard Ceramic Composites.

Diamond-silicon carbide (SiC) polycrystalline composite blends are studied using a computational approach combining molecular dynamics (MD) simulations for obtaining grain boundary (GB) fracture properties and phase field mechanics for capturing polycrystalline deformation and failure. An authentic microstructure, reconstructed from experimental lattice diffraction data with locally refined discretization in GB regions, is used to probe effects of local heterogeneities on material response in phase field simulations. The nominal microstructure consists of larger diamond and SiC (cubic polytype) grains, a matrix of smaller diamond grains and nanocrystalline SiC, and GB layers encasing the larger grains. These layers may consist of nanocrystalline SiC, diamond, or graphite, where volume fractions of each phase are varied within physically reasonable limits in parametric studies. Distributions of fracture energies from MD tension simulations are used in the phase field energy functional for SiC-SiC and SiC-diamond interfaces, where grain boundary geometries are obtained from statistical analysis of lattice orientation data on the real microstructure. An elastic homogenization method is used to account for distributions of second-phase graphitic inclusions as well as initial voids too small to be resolved individually in the continuum field discretization. In phase field simulations, SiC single crystals may twin, and all phases may fracture. The results of MD calculations show mean strengths of diamond-SiC interfaces are much lower than those of SiC-SiC GBs. In phase field simulations, effects on peak aggregate stress and ductility from different GB fracture energy realizations with the same mean fracture energy and from different random microstructure orientations are modest. Results of phase field simulations show unconfined compressive strength is compromised by diamond-SiC GBs, graphitic layers, graphitic inclusions, and initial porosity. Explored ranges of porosity and graphite fraction are informed by physical observations and constrained by accuracy limits of elastic homogenization. Modest reductions in strength and energy absorption are witnessed for microstructures with 4% porosity or 4% graphite distributed uniformly among intergranular matrix regions. Further reductions are much more severe when porosity is increased to 8% relative to when graphite is increased to 8%.

Object oriented spatial analysis of natural concentration levels of chemical species in regional-scale aquifers

We address the problem of characterizing spatially variable Natural Background Levels (NBLs) of concentrations of chemical species of environmental concern in a large-scale groundwater body. Assessment of NBLs is critical to identify significant trends of (possibly hazardous) chemical concentrations in aquifer systems, the latter being typically associated with spatially heterogeneous hydrogeochemical characteristics. Our study considers the entire probability density function (PDF) of the concentration of the chemical species of interest as atom of the statistical analysis. These PDFs are estimated across a network of observation boreholes in the investigated spatial domain, and modeled as random points in a Bayes Hilbert space, in the context of Object Oriented Data Analysis. This approach enables one to take advantage of the entire information content provided by these objects for the purpose of spatial prediction and uncertainty quantification. As a key element of innovation, we investigate the use of depth measures for distributional data with the distinctive aims of (i) detecting central and outlying NBL distributions in the dataset, and (ii) building prediction regions for NBL distribution at unsampled locations. We illustrate the results of the proposed approach to the analysis of NBLs of a selected chemical species detected at an environmental monitoring network within a large-scale alluvial aquifer in Northern Italy.

Density-based clustering of crystal (mis)orientations and the orix Python library.

Crystal orientation mapping experiments typically measure orientations that are similar within grains and misorientations that are similar along grain boundaries. Such (mis)orientation data cluster in (mis)orientation space, and clusters are more pronounced if preferred orientations or special orientation relationships are present. Here, cluster analysis of (mis)orientation data is described and demonstrated using distance metrics incorporating crystal symmetry and the density-based clustering algorithm DBSCAN. Frequently measured (mis)orientations are identified as corresponding to similarly (mis)oriented grains or grain boundaries, which are visualized both spatially and in three-dimensional (mis)orientation spaces. An example is presented identifying deformation twinning modes in titanium, highlighting a key application of the clustering approach in identifying crystallographic orientation relationships and similarly oriented grains resulting from specific transformation pathways. A new open-source Python library, orix, that enabled this work is also reported.

Model-free two-sample test for network-valued data

In the framework of Object Oriented Data Analysis, a permutation approach to the two-sample testing problem for network-valued data is proposed. In detail, the present framework proceeds in four steps: (i) matrix representation of the networks, (ii) computation of the matrix of pairwise (inter-point) distances, (iii) computation of test statistics based on inter-point distances and (iv) embedding of the test statistics within a permutation test. The proposed testing procedures are proven to be exact for every finite sample size and consistent. Two new test statistics based on inter-point distances (i.e., IP-Student and IP-Fisher) are defined and a method to combine them to get a further inferential tool (i.e., IP-StudentFisher) is introduced. Simulated data shows that tests with our statistic exhibit a statistical power that is either the best or second-best but very close to the best on a variety of possible alternatives hypotheses and other statistics. A second simulation study that aims at better understanding which features are captured by specific combinations of matrix representations and distances is presented. Finally, a case study on mobility networks in the city of Milan is carried out. The proposed framework is fully implemented in the R package nevada (NEtwork-VAlued Data Analysis).

Increased Cerebral Metabolic Stress Is Associated with Diminished Functional Connectivity in Pediatric Sickle Cell Anemia

Children with sickle cell anemia (SCA) experience increased metabolic stress in the brain, measured by oxygen extraction fraction (OEF); regions with the highest OEF co-localize with regions at greatest risk for stroke. Yet, SCA affects cognition independent of stroke. We aim to investigate the relationship between metabolic stress and the cognitive effects of SCA. Neurocognitive abilities emerge from functional networks ascertained using unctional connectivity MRI (rs-fcMRI), potentially allowing functional connectivity (fc) to be used as a biomarker for cognitive dysfunction in SCA. We prospectively obtained cognitive testing and brain MRIs in children with SCA (unaffected by overt stroke or vasculopathy, not chronically transfused and without history of transplant) and controls in a single center to test our hypothesis that children with SCA experiencing the greatest metabolic stress will have the greatest disruption in fc. Brain MRI measured OEF (asymmetric spin echo) and fc (resting state BOLD), and the NIH Toolbox Cognition Battery (NIHTB) and Wechsler Abbreviated Scale of Intelligence Second Edition (WASI-II) assessed cognition. OEF processing is described in Fields et al. Blood. 2019; 133(22):2436-2444. Temporal correlation of the BOLD signal between 264 gray matter (GM) regions was calculated and assembled into region x region matrices sorted by 13 pre-defined functional networks. Homotopy, a metric of global connectivity, was measured by correlating GM voxels in the right hemisphere with corresponding left voxels, and averaging across GM. Group comparisons were made with Mann-Whitney U or chi-squared tests. Object oriented data analysis (OODA), post-hoc block permutation testing (p-values corrected for false discovery rate (FDR)), and group comparison of average within network correlations compared fc between cohorts. Bivariate correlations were described with Pearson's r. Significance was specified as p-value &amp;lt; .05, and the Benjamini-Hochberg procedure controlled for a final FDR of 0.05 for group comparison excluding permutation testing. Table 1 describes the 55 participants. There was no difference in cognition between cohorts (Table 1). Homotopy was lower in SCA (0.336 [0.310-0.379]) compared to controls (0.381 [0.341-0.394], p = 0.023). Figure 1 illustrates cohort fc matrices. The intra-network regions demonstrate strong positive correlations and inter-network regions demonstrate lower correlations for each cohort, indicating functional network architecture is similar between cohorts. However, the magnitude of fc is reduced in SCA. Using OODA, there was a significant difference between matrices (p=.001), with SCD selectively affecting the magnitude of fc within specific networks: Salience (Sal), Fronto-Parietal (FP), Cingulo-Opercular (CO), Sensory-Motor (SM), Sensory-Motor Lateral (SM-Lat), and Auditory (Aud) networks when comparing within network Pearson's r between cohorts (Table 1), and the Sal (FDR-corrected p &amp;lt; .001) and SM-Lat (FDR-corrected p = .039) networks using block permutation testing. Whole brain (Wb) OEF correlated with homotopy (r = -.420, p = .002), and the average Pearson r within specific networks: Default Mode (r = -.481, p &amp;lt; .001), CO (r = -.537, p &amp;lt; .001), Sal (r = -.549, p &amp;lt; .001), FP (r = -.461, p &amp;lt; .001), SM (r = -.298, p = .029), SM-Lat (r = -.381, p = .004), Aud (r = -.437, p = .001), and Visual (r = -.344, p = .011) networks (Figure 2). Wb OEF did not correlate with the average Pearson r within the Cerebellar (p = .713), Subcortical (p = .974), Memory (p = .104), Dorsal Attention (p = .228), or Ventral Attention (p = .162) networks. We conclude that there are differences in rs-fcMRI in this cohort of children with SCA unaffected by overt stroke or vasculopathy when compared to controls even though cohort differences were not found with cognitive testing. Differences were found in higher level cortical association systems (Sal, FP and CO) that are associated with executive function, which is known to be affected by SCA. Knowing that there is regional variation in metabolic stress, as measured by OEF, within the brains of children with SCA, we found an association between OEF and fc in select networks. These data suggest that those experiencing the greatest metabolic stress have diminished connectivity within select fc networks, and that these imaging metrics may provide neuroimaging biomarkers for cognitive decline in SCA. Disclosures Fields: Proclara Biosciences: Equity Ownership. Mirro:Nous Imaging Inc: Employment. King:Incyte: Consultancy; WUGEN: Equity Ownership; Tioma Therapeutics (formerly Vasculox, Inc.):: Consultancy; RiverVest: Consultancy; Novimmune: Research Funding; Amphivena Therapeutics: Research Funding; Bioline: Consultancy; Celgene: Consultancy; Cell Works: Consultancy; Magenta Therapeutics: Membership on an entity's Board of Directors or advisory committees.

Discussion: Object-Oriented Data Analysis, Power Metrics, and Graph Laplacians

Object oriented data analysis (OODA) has seen many developments over the past decade since Wang and Marron (2007) introduced the topic, and a broad overview of the field has been given by Marron an...

Bayesian Inference for a New Class of Distributions on Equivalence Classes of Three-Dimensional Orientations With Applications to Materials Science

Experiments in materials science investigating cubic crystalline structures often collect data which are in truth equivalence classes of crystallographically symmetric orientations. These intend to represent how lattice structures of particles are orientated relative to a reference coordinate system. Motivated by a materials science application, we formulate parametric probability models for “unlabeled orientation data.” This amounts to developing models on equivalence classes of three-dimensional rotations. We use a flexible existing model class for random rotations (called uniform-axis-random-spin models) to induce probability distributions on the equivalence classes of rotations. We develop one-sample Bayesian inference for the parameters in these models, and compare this methodology to some likelihood-based approaches. We also contrast the new parametric analysis of unlabeled orientation data with other analyses that proceed as if the data have been preprocessed into honest orientation data. Supplementary materials for this article are available online.

Nanopatterned polymer surfaces with bactericidal properties.

Bacteria that adhere to the surfaces of implanted medical devices can cause catastrophic infection. Since chemical modifications of materials' surfaces have poor long-term performance in preventing bacterial buildup, approaches using bactericidal physical surface topography have been investigated. The authors used Nanoimprint Lithography was used to fabricate a library of biomimetic nanopillars on the surfaces of poly(methyl methacrylate) (PMMA) films. After incubation of Escherichia coli (E. coli) on the structured PMMA surfaces, pillared surfaces were found to have lower densities of adherent cells compared to flat films (67%-91% of densities on flat films). Moreover, of the E. coli that did adhere a greater fraction of them were dead on pillared surfaces (16%-141% higher dead fraction than on flat films). Smaller more closely spaced nanopillars had better performance. The smallest most closely spaced nanopillars were found to reduce the bacterial load in contaminated aqueous suspensions by 50% over a 24-h period compared to flat controls. Through quantitative analysis of cell orientation data, it was determined that the minimum threshold for optimal nanopillar spacing is between 130 and 380 nm. Measurements of bacterial cell length indicate that nanopillars adversely affect E. coli morphology, eliciting a filamentous response. Taken together, this work shows that imprinted polymer nanostructures with precisely defined geometries can kill bacteria without any chemical modifications. These results effectively translate bactericidal nanopillar topographies to PMMA, an important polymer used for medical devices.

A study on the use of planarity for quick identification of potential landslide hazard

Abstract. In this study we focused on identifying a geomorphological feature that controls the location of landslides. The representation of the feature is based on a high-resolution digital elevation model derived from the airborne laser altimetry (LiDAR) and evaluated by the statistical analysis of axial orientation data. The main principle of this analysis is generating eigenvalues from axial orientation data and comparing them. The planarity, a ratio of eigenvalues, would tell the degree of irregularity on the ground surface based on their ratios. Results are compared to the recent landslide case in Korea in order to evaluate the feasibility of the proposed methodology in identifying the potential landslide hazard. The preliminary landslide hazard assessment based on the planarity analysis discriminates features between stable and unstable domain in the study area well, especially in the landslide initiation zones. Results also show it is beneficial to build the landslide hazard inventory mapping, especially where no information on historical records of landslides exists. By combining other physical procedures such as geotechnical monitoring, the landslide hazard assessment using geomorphological features promises a better understanding of landslides and their mechanisms and provides an enhanced methodology to evaluate their hazards and appropriate actions.

The observation of slip phenomena in single crystal Fe samples during in situ micro-mechanical testing through orientation imaging.

This paper reports a study of local orientation change occurring within micro-scale tensile samples as a function of strain. These samples were fabricated from a thin film of single crystal bcc Fe and deformed in tension using an in situ micro-mechanical testing device inside a scanning electron microscope. Samples were loaded along the <110> direction parallel to the specimen axis, strained to different levels, and then subjected to electron backscatter diffraction scans over the entire area of the gauge section. Analysis of the surface orientation data shows that, within a necked zone of the micro-sample gauge section, there are two distinct regions of significant orientation change, in which local crystal rotations occur in opposite directions. These two regions are separated by an intermediate band that shows minimal misorientation from the original state. Crystal rotations within the two regions that develop opposite orientations are found to be consistent with classic single crystal slip, where the slip direction rotates toward the tensile axis. It is shown that increasing tensile strain causes an increasing degree of rotation away from the starting orientation. The tests also illustrate the occurrence of slip on at least two different slip systems, based on the slip traces and orientation change.

Comments on: Overview of object oriented data analysis.

This is a discussion on the paper: "Overview of Object Oriented Data Analysis" by J. Steve Marron and Andrés M. Alonso.

Shape and object data analysis.

This is a discussion of the paper: 'Overview of object oriented data analysis' by J. SteveMarron and Andrés M.Alonso.

Asymptotics for Object Descriptors.

This is a discussion of the following paper: "Overview of object oriented data analysis" by J. Steve Marron and Andrés M. Alonso.

Object Oriented Data Analysis: A few methodological challenges

This is a discussion of the paper "Overview of object oriented data analysis" by J. Steve Marron and Andrés M. Alonso.