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Phase-contrast imaging of multiply-scattering extended objects at atomic resolution by reconstruction of the scattering matrix
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Phase and contrast moiré signatures in two-dimensional cone beam interferometry
Neutron interferometry has played a distinctive role in fundamental science and characterization of materials. Moiré neutron interferometers are candidate next-generation instruments: they offer microscopy-like magnification of the signal, enabling direct camera recording of interference patterns across the full neutron wavelength spectrum. Here we demonstrate the extension of phase-grating moiré interferometry to two-dimensional geometries. Our fork-dislocation phase gratings reveal phase singularities in the moiré pattern, and we explore orthogonal moiré patterns with two-dimensional phase gratings. Our measurements of phase topologies and gravitationally induced phase shifts are in good agreement with theory. These techniques can be implemented in existing neutron instruments to advance interferometric analyses of emerging materials and precision measurements of fundamental constants. Published by the American Physical Society 2024
Influence of surface relaxation on the contrast of threading edge dislocations in synchrotron X-ray
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Contrastive Meta-Learner for Automatic Text Labeling and Semantic Textual Similarity
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CGAP: A Hybrid Contrastive and Graph-Based Active Learning Pipeline to Detect Water and Sediment in Multispectral Images
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Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification
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Substrate quality drives fungal necromass decay and decomposer community structure under contrasting vegetation types
Fungal mycelium is increasingly recognized as a central component of soil biogeochemical cycling, yet our current understanding of the ecological controls on fungal necromass decomposition is limited to single sites and vegetation types. By deploying common fungal necromass substrates in a temperate oak savanna and hardwood forest in the midwestern USA, we assessed the generality of the rate at which high- and low-quality fungal necromass decomposes; further, we investigated how the decomposer ‘necrobiome’ varies both across and within sites under vegetation types dominated by either arbuscular or ectomycorrhizal plants. In this work, the effects of necromass quality on decay rate were robust to site and vegetation type differences, with high-quality fungal necromass decomposing, on average, 2.5 times faster during the initial stages of decay. Across vegetation types, bacterial and fungal communities present on decaying necromass differed from bulk soil microbial communities and were influenced by necromass quality. Moulds, yeasts and copiotrophic bacteria consistently dominated the necrobiome of high-quality fungal substrates. Synthesis. We show that regardless of differences in decay environments, high-quality fungal substrates decompose faster and support different types of decomposer micro-organisms when compared with low-quality fungal tissues. These findings help to refine our theoretical understanding of the dominant factors affecting fast cycling components of soil organic matter and the microbial communities associated with rapid decay.
Contrasting student and staff perceptions of preclinical‐to‐clinical transition at a Chilean dental school
Abstract Introduction Dental education is a challenging and demanding field of study as students are expected to acquire various competencies to fulfil their professional requirements after graduation. The objective of this study was to investigate and compare dental students' and clinical staff instructors' perceptions of the preclinical‐to‐clinical transition training at a Dental School in Santiago, Chile. Material and Methods Two questionnaires containing 11 quantitative and one qualitative item were developed to assess our year three, four and five ( n = 244) dental undergraduate students' challenges when they begin treating patients, and clinical staff ( n = 78) perceptions of the preparedness to treat patients of the same students. Both questionnaires were voluntarily and anonymously implemented eight weeks after the beginning of the 2019 academic year. Responses were analysed using a Chi‐squared test for each quantitative question, while qualitative comments were studied to form themes and dimensions. RESULTS A total of 234 (96%) students and 60 (77%) instructors completed their respective questionnaire. There were considerable variations between students in the different years of the programme, as well as between students and staff members. Students and instructors felt the former had enough knowledge to treat patients though it was difficult for them to apply it in clinical practice. Again, both believed they could communicate with patients, but third year students asked for more training on this. Regarding practical skills, fourth‐ and fifth‐year students felt prepared but not third year students, who preferred to work in pairs with senior students, a preference that was shared by the instructors. All student groups asked clinical staff to provide more frequent, constructive and consistent feedback and felt that the difference between simulation and clinical environments and the amount of clinical work to fulfil clinical requirements made them feel stressed. Another mentioned stressor was students' low self‐confidence when working with patients. Among the requested improvements, students requested better training on how the dental clinic works to save time. Conclusions Preclinical‐to‐clinical transition training presents several challenges. Some of the problems highlighted by both students and clinical staff members persisted with the transition after three, four and even five years of training, which needs to be addressed.
Salinization and sedimentation drive contrasting assembly mechanisms of planktonic and sediment‐bound bacterial communities in agricultural streams
Abstract Agriculture is the most dominant land use globally and is projected to increase in the future to support a growing human population but also threatens ecosystem structure and services. Bacteria mediate numerous biogeochemical pathways within ecosystems. Therefore, identifying linkages between stressors associated with agricultural land use and responses of bacterial diversity is an important step in understanding and improving resource management. Here, we use the Mississippi Alluvial Plain (MAP) ecoregion, a highly modified agroecosystem, as a case study to better understand agriculturally associated drivers of stream bacterial diversity and assembly mechanisms. In the MAP, we found that planktonic bacterial communities were strongly influenced by salinity. Tolerant taxa increased with increasing ion concentrations, likely driving homogenous selection which accounted for ~90% of assembly processes. Sediment bacterial phylogenetic diversity increased with increasing agricultural land use and was influenced by sediment particle size, with assembly mechanisms shifting from homogenous to variable selection as differences in median particle size increased. Within individual streams, sediment heterogeneity was correlated with bacterial diversity and a subsidy‐stress relationship along the particle size gradient was observed. Planktonic and sediment communities within the same stream also diverged as sediment particle size decreased. Nutrients including carbon, nitrogen, and phosphorus, which tend to be elevated in agroecosystems, were also associated with detectable shifts in bacterial community structure. Collectively, our results establish that two understudied variables, salinity and sediment texture, are the primary drivers of bacterial diversity within the studied agroecosystem, whereas nutrients are secondary drivers. Although numerous macrobiological communities respond negatively, we observed increasing bacterial diversity in response to agricultural stressors including salinization and sedimentation. Elevated taxonomic and phylogenetic bacterial diversity likely increases the probability of detecting community responses to stressors. Thus, bacteria community responses may be more reliable for establishing water quality goals within highly modified agroecosystems that have experienced shifting baselines.
Contrasting fungal responses to wildfire across different ecosystem types
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Contrasting anther glucose–6–phosphate dehydrogenase activities between two bean varieties suggest an important role in reproductive heat tolerance
Common beans (Phaseolus vulgaris) are highly sensitive to elevated temperatures, and rising global temperatures threaten bean production. Plants at the reproductive stage are especially susceptible to heat stress due to damage to male (anthers) and female (ovary) reproductive tissues, with anthers being more sensitive to heat. Heat damage promotes early tapetal cell degradation, and in beans this was shown to cause male infertility. In this study, we focus on understanding how changes in leaf carbon export in response to elevated temperature stress contribute to heat-induced infertility. We hypothesize that anther glucose-6-phosphate dehydrogenase (G6PDH) activity plays an important role at elevated temperature and promotes thermotolerance. To test this hypothesis, we compared heat-tolerant and susceptible common bean genotypes using a combination of phenotypic, biochemical, and physiological approaches. Our results identified changes in leaf sucrose export, anther sugar accumulation and G6PDH activity and anther H 2 O 2 levels and antioxidant-related enzymes between genotypes at elevated temperature. Further, anther respiration rate was found to be lower at high temperature in both bean varieties. Overall, our results support the hypothesis that enhanced male reproductive heat tolerance involves changes in the anther oxidative pentose phosphate pathway, which supplies reductants to critical H 2 O 2 scavenging enzymes.
Genome-scale phylogeny and contrasting modes of genome evolution in the fungal phylum Ascomycota
Ascomycota, the largest and most well-studied phylum of fungi, contains three subphyla: Saccharomycotina (budding yeasts), Pezizomycotina (filamentous fungi), and Taphrinomycotina (fission yeasts). Despite its importance, we lack a comprehensive genome-scale phylogeny or understanding of the similarities and differences in the mode of genome evolution within this phylum. By examining 1107 genomes from Saccharomycotina (332), Pezizomycotina (761), and Taphrinomycotina (14) species, we inferred a robust genome-wide phylogeny that resolves several contentious relationships and estimated that the Ascomycota last common ancestor likely originated in the Ediacaran period. Comparisons of genomic properties revealed that Saccharomycotina and Pezizomycotina differ greatly in their genome properties and enabled inference of the direction of evolutionary change. The Saccharomycotina typically have smaller genomes, lower guanine-cytosine contents, lower numbers of genes, and higher rates of molecular sequence evolution compared with Pezizomycotina. These results provide a robust evolutionary framework for understanding the diversity and ecological lifestyles of the largest fungal phylum.
Parallel Embeddings: a Visualization Technique for Contrasting Learned Representations
We introduce ``Parallel Embeddings'', a new technique that generalizes the classical Parallel Coordinates visualization technique from a sequence of features within a single matrix to a sequence of multiple feature matrices. This is accomplished by separately embedding each matrix in the sequence into a 2-D frame, juxtaposing these 2-D representations, then connecting points between frames. We outline how this visualization can be used for several ``model comparison'' tasks in machine learning. We compare user performance with Parallel Embeddings to a baseline using the TensorFlow Embedding Projector for estimating model accuracy and understanding conceptual model differences. We found that users were more accurate with Parallel Embeddings for model comparison and that users learned how to use Parallel Embeddings more quickly than TensorFlow Embedding Projector. Furthermore, users' analytical process using Embedding Projector was positively affected by using Parallel Embeddings beforehand.
Contrasting Trends in Colorado Fire Weather Index from Reanalysis and Observations
Recent wildfires in Colorado raise the question of whether rising global temperatures have increased fire weather occurrences in Colorado. The U.S. National Weather Service defines fire weather as when “forecast weather conditions will result in a significant threat for the ignition and/or spread of wildfires.” We use two datasets to address the question: “How has the occurrence of fire weather changed in Colorado?” Using 22 years of observed weather conditions from a meteorological tower at the National Renewable Energy Laboratory and 67 years of ERA5 reanalysis data, we assess changing trends in Colorado fire weather as defined by hot, dry, and windy conditions. Additionally, we explore if the difference in recorded wind speeds between observational data and reanalysis data can be explained by differences in spatial and temporal resolution and what are the implications in the context of quantifying fire weather occurrences. The observational data are limited in temporal extent and spatial representativeness, but they capture exact real-world conditions at a location in complex terrain. The reanalysis data are available for an extended period of time and for the entire state, but the data are of relatively coarse spatial and temporal resolution and may fail to capture extremes. To quantify fire risk, we calculate the hot–dry–windy index (HDWI), which relies on wind speed and vapor pressure deficit. No statistically significant trend in the HDWI appears in the observational dataset. However, according to the reanalysis data, strong increasing trends in HDWI values emerge across all of Colorado. This apparent conflict between observational and reanalysis data suggests that reanalysis data may not be representative. Further, more long-term observational datasets are required to assess fire risk.
Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types
Abstract The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the United Kingdom, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF Model and has hybrid bin–bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based, and satellite observations for all three cases. Filtered concentrations of ice (>0.1–0.2 mm) agree with those observed at all sampled levels. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity. In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5–1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80%–90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett–Mossop process and fragmentation in ice–ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes <10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity. In the simulated APPRAISE case, the main causes of persistence of long-lived clouds and precipitation are predicted to be SIP in weak embedded convection and reactivation following recirculation of dust particles in supercooled layer cloud.
Preoperative Radiomic Approach to Evaluate Tumor-Infiltrating CD8{sup +} T Cells in Hepatocellular Carcinoma Patients Using Contrast-Enhanced Computed Tomography
Background: To help identify potential hepatocellular carcinoma (HCC) candidates for immunotherapies, we aimed to develop and validate a radiomics-based biomarker (Rad score) to predict the infiltration of tumor-infiltrating CD8{sup +} T cells in HCC patients, and to evaluate the correlation of Rad score with tumor immune characteristics. Methods: Overall, 142 HCC patients (n = 100 and n = 42 in the training and validation sets, respectively) were subjected to radiomic feature extraction. Imaging features and immunochemistry data of patients in the training set were subjected to elastic-net regularized regression analysis to predict the level of CD8{sup +} T cell infiltration. Results: A Rad score for CD8{sup +} T-cell infiltration, which contained seven variables, was developed and was validated in the validation set (area under the curve [AUC]: training set 0.751, 95% confidence interval [CI] 0.656–0.846; validation set 0.705, 95% CI 0.547–0.863). The decision curve indicated the clinical usefulness of the Rad score. A higher Rad score correlated with superior overall and disease-free survival outcomes (p = 0.012 and 0.0088, respectively). Using the pathological slides, we found that the Rad score positively correlated with the percentage of tumor-infiltrating lymphocytes (TILs; Spearman rho = 0.51, p < 0.0001). Moreover, the Rad score could also discriminate inflamed tumors from immune-desert and immune-excluded tumors (Kruskal–Wallis, p < 0.0001), and higher Rad scores could be found in patients with positive programmed cell death ligand 1 expression in tumor/immune cells, as well as those with positive programmed cell death protein 1 expression. Conclusion: The newly developed Rad score was a powerful predictor of CD8{sup +} T-cell infiltration, which could be useful in identifying potential HCC patients who can benefit from immunotherapies when validated in large-scale prospective cohorts.