Fast Comparative Analysis of Merge Trees Using Locality Sensitive Hashing.

Scalar field comparison is a fundamental task in scientific visualization. In topological data analysis, we compare topological descriptors of scalar fields-such as persistence diagrams and merge trees-because they provide succinct and robust abstract representations. Several similarity measures for topological descriptors seem to be both asymptotically and practically efficient with polynomial time algorithms, but they do not scale well when handling large-scale, time-varying scientific data and ensembles. In this paper, we propose a new framework to facilitate the comparative analysis of merge trees, inspired by tools from locality sensitive hashing (LSH). LSH hashes similar objects into the same hash buckets with high probability. We propose two new similarity measures for merge trees that can be computed via LSH, using new extensions to Recursive MinHash and subpath signature, respectively. Our similarity measures are extremely efficient to compute and closely resemble the results of existing measures such as merge tree edit distance or geometric interleaving distance. Our experiments demonstrate the utility of our LSH framework in applications such as shape matching, clustering, key event detection, and ensemble summarization.

A Metabolic Intervention for Improving Human Cognitive Performance During Hypoxia.

BACKGROUND: During hypoxia an operators cognitive performance may decline. This decline is linked to altered brain metabolism, resulting in decreased adenosine triphosphate (ATP) production. Ketone bodies are an alternative substrate to glucose for brain metabolic requirements; previous studies have shown that the presence of elevated ketone bodies in the blood maintains brain ATP levels and reduces cerebral glycolysis during hypoxia. Thus, ketones may be a strategy to mitigate cognitive decline in hypoxia. Ketone ester (KE) consumption allows rapid elevation of blood ketone levels; therefore, we investigated the effects of consuming a KE drink on cognitive performance during hypoxia. Here, we report results of a pilot study.METHODS: There were 11 subjects who completed a cognitive performance test battery under conditions of normoxia and hypoxia following consumption of a KE drink and a placebo control drink.RESULTS: Significant hypoxia effects (O2 saturation minimum was found to range between 63 and 88 in subjects) were found for blink duration (Ph2 0.665) and blink rate (Ph2 0.626), indicating that the hypoxia condition was associated with longer blink durations and lower blink rates. Significant hypoxia effects were likewise observed for a code substitution task (Ph2 0.487), indicating that performance on the task was significantly disrupted by the hypoxia stressor. KE consumption had a significant effect on blink duration (Ph2 0.270) and the code substitution task (Ph2 0.309).DISCUSSION: These finding suggest that some effects of acute hypoxia can be mitigated by nutritional ketosis.Coleman K, Phillips J, Sciarini M, Stubbs B, Jackson O, Kernagis D. A metabolic intervention for improving human cognitive performance during hypoxia. Aerosp Med Hum Perform. 2021; 92(7):556562.

Visualization of Big Spatial Data using Coresets for Kernel Density Estimates.

The size of large, geo-located datasets has reached scales where visualization of all data points is inefficient. Random sampling is a method to reduce the size of a dataset, yet it can introduce unwanted errors. We describe a method for subsampling of spatial data suitable for creating kernel density estimates from very large data and demonstrate that it results in less error than random sampling. We also introduce a method to ensure that thresholding of low values based on sampled data does not omit any regions above the desired threshold when working with sampled data. We demonstrate the effectiveness of our approach using both, artificial and real-world large geospatial datasets.

Improving the ecological relevance of toxicity tests on scleractinian corals: Influence of season, life stage, and seawater temperature.

Metal pollutants in marine systems are broadly acknowledged as deleterious: however, very little data exist for tropical scleractinian corals. We address this gap by investigating how life-history stage, season and thermal stress influence the toxicity of copper (Cu) and lead (Pb) in the coral Pocillopora damicornis. Our results show that under ambient temperature, adults and larvae appear to tolerate exposure to unusually high levels of copper (96 h-LC50 ranging from 167 to 251 µg Cu L(-1)) and lead (from 477 to 742 µg Pb L(-1)). Our work also highlights that warmer conditions (seasonal and experimentally manipulated) reduce the tolerance of adults and larvae to Cu toxicity. Despite a similar trend observed for the response of larvae to Pb toxicity to experimentally induced increase in temperature, surprisingly adults were more resistant in warmer condition to Pb toxicity. In the summer adults were less resistant to Cu toxicity (96 h-LC50 = 175 µg L(-1)) than in the winter (251 µg L(-1)). An opposite trend was observed for the Pb toxicity on adults between summer and winter (96 h-LC50 of 742 vs 471 µg L(-1), respectively). Larvae displayed a slightly higher sensitivity to Cu and Pb than adults. An experimentally induced 3 °C increase in temperature above ambient decreased larval resistance to Cu and Pb toxicity by 23-30% (96 h-LC50 of 167 vs 129 µg Cu L(-1) and 681 vs 462 µg Pb L(-1)). Our data support the paradigm that upward excursions in temperature influence physiological processes in corals that play key roles in regulating metal toxicity. These influences are more pronounced in larva versus adult corals. These findings are important when contextualized climate change-driven warming in the oceans and highlight that predictions of ecological outcomes to metal pollutants will be improved by considering environmental context and the life stages of organism under study.

Use of modified barium swallow study to measure posterior airway space in obstructive sleep apnea.

Conclusion Measurement of the posterior airway space (PAS) using modified barium swallow (MBS) appears to correlate well with CT imaging. This data suggests MBS may be a low-cost alternative imaging modality to assess obstructive sleep apnea patients. Objectives Obstructive sleep apnea research has focused on imaging modalities that supplement polysomnography in evaluation of potential sites of airway obstruction. While several techniques have been used to assess the PAS, many incur significant costs and risks to the patient. This study proposes use of MBS as a simple modality to measure PAS. Advantages include its simplicity, lower radiation, and dynamic tongue base visualization, which may help predict surgical outcomes. It is hypothesized that cephalometric measurements obtained using MBS will correlate well with CT. Methods Thirty-six adult patients who underwent both CT imaging and MBS for head and neck cancer were included. Cephalometric measurements of the PAS were obtained using each imaging modality. Statistical analysis focused on correlating measurements taken using CT and MBS. Results The average PAS measurements were 12.53 ± 1.81 mm and 12.80 ± 1.75 mm by MBS and CT imaging, respectively. In comparing the two modalities, Pearson correlation between CT and MBS measurements revealed significant positive correlations between r = 0.769 and 0.937.

Dynamic sensorimotor planning during long-term sequence learning: the role of variability, response chunking and planning errors.

Many everyday skills are learned by binding otherwise independent actions into a unified sequence of responses across days or weeks of practice. Here we looked at how the dynamics of action planning and response binding change across such long timescales. Subjects (N = 23) were trained on a bimanual version of the serial reaction time task (32-item sequence) for two weeks (10 days total). Response times and accuracy both showed improvement with time, but appeared to be learned at different rates. Changes in response speed across training were associated with dynamic changes in response time variability, with faster learners expanding their variability during the early training days and then contracting response variability late in training. Using a novel measure of response chunking, we found that individual responses became temporally correlated across trials and asymptoted to set sizes of approximately 7 bound responses at the end of the first week of training. Finally, we used a state-space model of the response planning process to look at how predictive (i.e., response anticipation) and error-corrective (i.e., post-error slowing) processes correlated with learning rates for speed, accuracy and chunking. This analysis yielded non-monotonic association patterns between the state-space model parameters and learning rates, suggesting that different parts of the response planning process are relevant at different stages of long-term learning. These findings highlight the dynamic modulation of response speed, variability, accuracy and chunking as multiple movements become bound together into a larger set of responses during sequence learning.

Uncertainty Visualization in HARDI based on Ensembles of ODFs.

In this paper, we propose a new and accurate technique for uncertainty analysis and uncertainty visualization based on fiber orientation distribution function (ODF) glyphs, associated with high angular resolution diffusion imaging (HARDI). Our visualization applies volume rendering techniques to an ensemble of 3D ODF glyphs, which we call SIP functions of diffusion shapes, to capture their variability due to underlying uncertainty. This rendering elucidates the complex heteroscedastic structural variation in these shapes. Furthermore, we quantify the extent of this variation by measuring the fraction of the volume of these shapes, which is consistent across all noise levels, the certain volume ratio. Our uncertainty analysis and visualization framework is then applied to synthetic data, as well as to HARDI human-brain data, to study the impact of various image acquisition parameters and background noise levels on the diffusion shapes.

Cerebellar cortical degeneration in adult American Staffordshire Terriers.

Adult-onset cerebellar cortical degeneration recently has been reported in American Staffordshire Terriers. We describe the clinical and histopathologic features of this disease and examine its mode of inheritance in 63 affected dogs. The age at which neurologic deficits 1st were recognized varied from 18 months to 9 years, with the majority of dogs presented to veterinarians between 4 and 6 years of age. Time from onset of clinical signs to euthanasia varied from 6 months to 6.5 years, with the majority of affected dogs surviving from 2 to 4 years. Initial neurologic findings included stumbling, truncal sway, and ataxia exacerbated by lifting the head up and negotiating stairs. Signs progressed to obvious ataxia characterized by dysmetria, nystagmus, coarse intention tremor, variable loss of menace reaction, marked truncal sway, and falling with transient opisthotonus. With continued progression, dogs became unable to walk without falling repeatedly. Cerebellar atrophy was visible on magnetic resonance images and on gross pathology. Histopathologic findings included marked loss of Purkinje neurons with thinning of the molecular and granular layers and increased cellularity of the cerebellar nuclei. The closest common ancestor of the dogs was born in the 1950s and inheritance was most consistent with an autosomal recessive mode of transmission with a prevalence estimated at 1 in 400 dogs. This inherited disease is comparable to the group of diseases known as spinocerebellar ataxias in humans. Many spinocerebellar ataxias in humans are caused by nucleotide repeats, and this genetic aberration merits investigation as a potential cause of the disease in American Staffordshire Terriers.