The other-race effect in children from a multiracial population: A cross-cultural comparison

The role of experience with other-race faces on the development of the ORE was investigated through a cross-cultural comparison between 5- to 6-year-old (n = 83) and 13- to 14-year-old (n = 66) children raised in a monoracial (British-White) and a multiracial (Malaysian-Chinese) population. British-White children showed an ORE to three other-race faces (Chinese, Malay, and African-Black) that was stable across age. Malaysian-Chinese children showed recognition deficit for less experienced faces (African-Black) but showed a recognition advantage for faces of which they have direct or indirect experience. Interestingly, younger (Malaysian-Chinese) children showed no ORE for female faces such that they can recognize all female faces regardless of race. These findings point to the importance of early race and gender experiences in re-organizing the face representation to accommodate changes in experience across development

In infancy, the developmental time course of the other-race effect is dependent on face gender

Poorer recognition of other-race faces relative to own-race faces is well documented from late infancy to adulthood. Research has revealed an increase in the other race effect (ORE) during the first year of life, but there is some disagreement regarding the age at which it emerges. Using cropped faces to eliminate discrimination based on external features, visual paired comparison and spontaneous visual preference measures were used to investigate the relationship between ORE and face gender at 3-4 and 8-9 months. Caucasian-White 3- to 4-month-olds' discrimination of Chinese, Malay, and Caucasian-White faces showed an own-race advantage for female faces alone whereas at 8-9 months the own-race advantage was general across gender. This developmental effect is accompanied by a preference for female over male faces at 4 months and no gender preference at 9 months. The pattern of recognition advantage and preference suggests that there is a shift from a female-based own-race recognition advantage to a general own-race recognition advantage, in keeping with a visual and social experience-based account of ORE

A new hot gas cleanup filter design methodology

The fluid dynamics of Hot Gas Cleanup (HGCU) systems having complex geometrical configurations are typically analyzed using computational fluid dynamics codes (CFD) or bench-scale laboratory test facilities called cold-flow models (CFM). At the present time, both CFD and CFM can be effectively used for simple flows limited to one or two characteristic length scales with well defined boundary conditions. This is not the situation with HGCU devices. These devices have very complex geometries, low Reynolds number, multi-phase flows that operate on multiple-length scales. For this reason, both CFD and CFM analysis cannot yet be considered as a practical engineering analysis tool for modeling the entire flow field inside HGCU systems. The thrust of this work is to provide an aerodynamic analysis methodology that can be easily applied to the complex geometries characteristic of HGCU filter vessels, but would not require the tedious numerical solution to the entire set of transport equations. The analysis methodology performs the following tasks: Predicts problem areas where ash deposition will most likely occur; Predicts residence times for particles at various locations inside the filter vessel; Lends itself quickly to major design changes; Provides a sound technical basis for more appropriate use of CFD and CFM analysis; and Provides CFD and CFM analysis in a more focused way where if is needed

A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge

This work proposes a method to accelerate the acquisition of high-quality edited magnetic resonance spectroscopy (MRS) scans using machine learning models taking the sample covariance matrix as input. The method is invariant to the number of transients and robust to noisy input data for both synthetic as well as in-vivo scenarios

The Colorado Plateau Coring Project (CPCP): 100 Million Years of Earth System History

Lasting over 100 million years, the early Mesozoic (252 to 145 Ma) is punctuated by two of the five major mass extinctions of the Phanerozoic (Permo-Triassic and Triassic-Jurassic) plus several smaller extinction events. It witnessed the evolutionary appearance of the modem terrestrial biota including frogs, salamanders, turtles, lizards, crocodilians, dinosaurs, birds, and mammals, and spans a time of dramatic climate changes on the continents. What is arguably the richest record of these events lies in the vast (- 2.5 million km2) complex of epicontinental basins in the western part of Pangea, now largely preserved on the Colorado Plateau (Fig.l). Since the mid-19th century, classic studies of these basins, their strata, and their fossils have made this succession instrumental in framing our context of the early Mesozoic Earth system as reflected in the international literature. Despite this long and distinguished history of study of the Colorado Plateau region, striking ambiguities in temporal resolution, major uncertainties in global correlations, and significant doubts about paleolatitudinal position hamper incorporation of the huge amount of information from the region into-tests of major competing climatic, biotic, and tectonic hypotheses and a fundamental understanding of Earth system processes

A review of machine learning applications for the proton MR spectroscopy workflow

This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured overview of the state-of-the-art methods. Specifically, we examine and summarize studies published between 2017 and 2023 from major journals in the MR field. We categorize these studies based on a typical MRS workflow, including data acquisition, processing, analysis, and artificial data generation. Our review reveals that ML in MRS is still in its early stages, with a primary focus on processing and analysis techniques, and less attention given to data acquisition. We also found that many studies use similar model architectures, with little comparison to alternative architectures. Additionally, the generation of artificial data is a crucial topic, with no consistent method for its generation. Furthermore, many studies demonstrate that artificial data suffers from generalization issues when tested on in vivo data. We also conclude that risks related to ML models should be addressed, particularly for clinical applications. Therefore, output uncertainty measures and model biases are critical to investigate. Nonetheless, the rapid development of ML in MRS and the promising results from the reviewed studies justify further research in this field.</p

[¹⁸F]FDG Uptake and Expression of Immunohistochemical Markers Related to Glycolysis, Hypoxia, and Proliferation in Indeterminate Thyroid Nodules

Purpose: The current study explored the association between 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) uptake and the quantitative expression of immunohistochemical markers related to glucose metabolism, hypoxia, and cell proliferation in benign and malignant thyroid nodules of indeterminate cytology. Procedures: Using a case–control design, 24 patients were selected from participants of a randomized controlled multicenter trial (NCT02208544) in which [18F]FDG-PET/CT and thyroid surgery were performed for Bethesda III and IV nodules. Three equally sized groups of [18F]FDG-positive malignant, [18F]FDG-positive benign, and [18F]FDG-negative benign nodules were included. Immunohistochemical staining was performed for glucose transporters (GLUT) 1, 3, and 4; hexokinases (HK) 1 and 2; hypoxia-inducible factor-1 alpha (HIF1α; monocarboxylate transporter 4 (MCT4); carbonic anhydrase IX (CA-IX); vascular endothelial growth factor (VEGF); sodium-iodide symporter (NIS); and Ki-67. Marker expression was scored using an immunoreactive score. Unsupervised cluster analysis was performed. The immunoreactive score was correlated to the maximum and peak standardized uptake values (SUVmax, SUVpeak) and SUVmax ratio (SUVmax of nodule/background SUVmax of contralateral, normal thyroid) of the [18F]FDG-PET/CT using the Spearman’s rank correlation coefficient and compared between the three groups using Kruskal–Wallis tests. Results: The expression of GLUT1, GLUT3, HK2, and MCT4 was strongly positively correlated with the SUVmax, SUVpeak, and SUVmax ratio. The expression of GLUT1 (p = 0.009), HK2 (p = 0.02), MCT4 (p = 0.01), and VEGF (p = 0.007) was statistically significantly different between [18F]FDG-positive benign nodules, [18F]FDG-positive thyroid carcinomas, and [18F]FDG-negative benign nodules. In both [18F]FDG-positive benign nodules and [18F]FDG-positive thyroid carcinomas, the expression of GLUT1, HK2, and MCT4 was increased as compared to [18F]FDG-negative benign nodules. VEGF expression was higher in [18F]FDG-positive thyroid carcinomas as compared to [18F]FDG-negative and [18F]FDG-positive benign nodules. Conclusions: Our results suggest that [18F]FDG-positive benign thyroid nodules undergo changes in protein expression similar to those in thyroid carcinomas. To expand the understanding of the metabolic changes in benign and malignant thyroid nodules, further research is required, including correlation with underlying genetic alterations.</p

Advancing GABA-edited MRS Research through a Reconstruction Challenge

Purpose To create a benchmark for the comparison of machine learning-based Gamma-Aminobutyric Acid (GABA)-edited Magnetic Resonance Spectroscopy (MRS) reconstruction models using one quarter of the transients typically acquired during a complete scan.Methods The Edited-MRS reconstruction challenge had three tracks with the purpose of evaluating machine learning models trained to reconstruct simulated (Track 1), homogeneous in vivo (Track 2), and heterogeneous in vivo (Track 3) GABA-edited MRS data. Four quantitative metrics were used to evaluate the results: mean squared error (MSE), signal-to-noise ratio (SNR), linewidth, and a shape score metric that we proposed. Challenge participants were given three months to create, train and submit their models. Challenge organizers provided open access to a baseline U-NET model for initial comparison, as well as simulated data, in vivo data, and tutorials and guides for adding synthetic noise to the simulations.Results The most successful approach for Track 1 simulated data was a covariance matrix convolutional neural network model, while for Track 2 and Track 3 in vivo data, a vision transformer model operating on a spectrogram representation of the data achieved the most success. Deep learning (DL) based reconstructions with reduced transients achieved equivalent or better SNR, linewidth and fit error as conventional reconstructions with the full amount of transients. However, some DL models also showed the ability to optimize the linewidth and SNR values without actually improving overall spectral quality, pointing to the need for more robust metrics.Conclusion The edited-MRS reconstruction challenge showed that the top performing DL based edited-MRS reconstruction pipelines can obtain with a reduced number of transients equivalent metrics to conventional reconstruction pipelines using the full amount of transients. The proposed metric shape score was positively correlated with challenge track outcome indicating that it is well-suited to evaluate spectral quality.Competing Interest StatementThe authors have declared no competing interest

New Insights into White-Light Flare Emission from Radiative-Hydrodynamic Modeling of a Chromospheric Condensation

(abridged) The heating mechanism at high densities during M dwarf flares is poorly understood. Spectra of M dwarf flares in the optical and near-ultraviolet wavelength regimes have revealed three continuum components during the impulsive phase: 1) an energetically dominant blackbody component with a color temperature of T $\sim$ 10,000 K in the blue-optical, 2) a smaller amount of Balmer continuum emission in the near-ultraviolet at lambda $<$ 3646 Angstroms and 3) an apparent pseudo-continuum of blended high-order Balmer lines. These properties are not reproduced by models that employ a typical "solar-type" flare heating level in nonthermal electrons, and therefore our understanding of these spectra is limited to a phenomenological interpretation. We present a new 1D radiative-hydrodynamic model of an M dwarf flare from precipitating nonthermal electrons with a large energy flux of $10^{13}$ erg cm$^{-2}$ s$^{-1}$. The simulation produces bright continuum emission from a dense, hot chromospheric condensation. For the first time, the observed color temperature and Balmer jump ratio are produced self-consistently in a radiative-hydrodynamic flare model. We find that a T $\sim$ 10,000 K blackbody-like continuum component and a small Balmer jump ratio result from optically thick Balmer and Paschen recombination radiation, and thus the properties of the flux spectrum are caused by blue light escaping over a larger physical depth range compared to red and near-ultraviolet light. To model the near-ultraviolet pseudo-continuum previously attributed to overlapping Balmer lines, we include the extra Balmer continuum opacity from Landau-Zener transitions that result from merged, high order energy levels of hydrogen in a dense, partially ionized atmosphere. This reveals a new diagnostic of ambient charge density in the densest regions of the atmosphere that are heated during dMe and solar flares.Comment: 50 pages, 2 tables, 13 figures. Accepted for publication in the Solar Physics Topical Issue, "Solar and Stellar Flares". Version 2 (June 22, 2015): updated to include comments by Guest Editor. The final publication is available at Springer via http://dx.doi.org/10.1007/s11207-015-0708-

Optimization and testing of dried antibody tube: The EuroFlow LST and PIDOT tubes as examples

Within EuroFlow, we recently developed screening tubes for hematological malignancies and immune deficiencies. Pipetting of antibodies for such 8-color 12-marker tubes however is time-consuming and prone to operational mistakes. We therefore evaluated dried formats of the lymphocytosis screening tube (LST) and of the primary immune deficiency orientation tube (PIDOT). Both tubes were evaluated on normal and/or on patient samples, comparing the mean fluorescence intensity of specific lymphocyte populations. Our data show that the dried tubes and liquid counterparts give highly comparable staining results, particularly when analyzed in multidimensional plots. In addition, the use of dried tubes may result in a reduced staining variability between different samples and thereby contributes to the generation of more robust data. Therefore, by using ready-to-use reagents in a dried single test tube format, the laboratory efficiency and quality will be improved