Predicting H{\alpha} emission line galaxy counts for future galaxy redshift surveys

Knowledge of the number density of H$\alpha$ emitting galaxies is vital for assessing the scientific impact of the Euclid and WFIRST missions. In this work we present predictions from a galaxy formation model, Galacticus, for the cumulative number counts of H$\alpha$-emitting galaxies. We couple Galacticus to three different dust attenuation methods and examine the counts using each method. A $\chi^2$ minimisation approach is used to compare the model predictions to observed galaxy counts and calibrate the dust parameters. We find that weak dust attenuation is required for the Galacticus counts to be broadly consistent with the observations, though the optimum dust parameters return large values for $\chi^2$, suggesting that further calibration of Galacticus is necessary. The model predictions are also consistent with observed estimates for the optical depth and the H$\alpha$ luminosity function. Finally we present forecasts for the redshift distributions and number counts for two Euclid-like and one WFIRST-like survey. For a Euclid-like survey with redshift range $0.9\leqslant z\leqslant 1.8$ and H$\alpha+{\rm [NII]}$ blended flux limit of $2\times 10^{-16}{\rm erg}\,{\rm s}^{-1}\,{\rm cm}^{-2}$ we predict a number density between 3900--4800 galaxies per square degree. For a WFIRST-like survey with redshift range $1\leqslant z\leqslant 2$ and blended flux limit of $1\times 10^{-16}{\rm erg}\,{\rm s}^{-1}\,{\rm cm}^{-2}$ we predict a number density between 10400--15200 galaxies per square degree.Comment: 21 pages (including appendix), 12 figures, 6 tables. Accepted b

Students’ satisfaction with general practitioners’ feedback to their reflective writing: a randomized controlled trial

Background: Reflective Writing (RW) is increasingly being implemented in medical education. Feedback to students’ reflective writing (RW) is essential, but resources for individualized feedback often lack. We aimed to determine whether general practitioners (GPs) teaching students clinical skills could also provide feedback to RW and whether an instruction letter specific to RW feedback increases students’ satisfaction.Methods: GPs were randomized to the two study arms using block randomization. GPs in both groups received an instruction letter on giving students feedback on clinical skills. Additionally, intervention group GPs received specific instructions on providing feedback to students’ RW. Students completed satisfaction questionnaires on feedback received on clinical skills and RW. T-tests were employed for all statistical analysis to compare groups.Results: Eighty-three out of 134 physicians participated: 38 were randomized to the control, 45 to the intervention group. Students were very satisfied with the feedback on RW and clinical skills regardless of tutors’ group allocation. A specific instruction letter had no additional effect on students’ satisfaction.Conclusion: Based on student satisfaction, GPs who give students feedback on clinical skills are also well suited to provide feedback on RW. This approach can facilitate the introduction of mandatory RW into the regular medical curriculum

Experimental and Computational Study on the Microfluidic Control of Micellar Nanocarrier Properties

Microfluidic-based synthesis is a powerful technique to prepare well-defined homogenous nanoparticles (NPs). However, the mechanisms defining NP properties, especially size evolution in a microchannel, are not fully understood. Herein, microfluidic and bulk syntheses of riboflavin (RF)-targeted poly(lactic-co-glycolic acid)-poly(ethylene glycol) (PLGA-PEG-RF) micelles were evaluated experimentally and computationally. Using molecular dynamics (MD), a conventional "random"model for bulk self-assembly of PLGA-PEG-RF was simulated and a conceptual "interface"mechanism was proposed for the microfluidic self-assembly at an atomic scale. The simulation results were in agreement with the observed experimental outcomes. NPs produced by microfluidics were smaller than those prepared by the bulk method. The computational approach suggested that the size-determining factor in microfluidics is the boundary of solvents in the entrance region of the microchannel, explaining the size difference between the two experimental methods. Therefore, this computational approach can be a powerful tool to gain a deeper understanding and optimize NP synthesis. © 2021 The Authors. Published by American Chemical Society

Drivers of beta diversity in modern and ancient reef-associated soft-bottom environments

Beta diversity, the compositional variation among communities, is often associated with environmental gradients. Other drivers of beta diversity include stochastic processes, priority effects, predation, or competitive exclusion. Temporal turnover may also explain differences in faunal composition between fossil assemblages. To assess the drivers of beta diversity in reef-associated soft-bottom environments, we investigate community patterns in a Middle to Late Triassic reef basin assemblage from the Cassian Formation in the Dolomites, Northern Italy, and compare results with a Recent reef basin assemblage from the Northern Bay of Safaga, Red Sea, Egypt. We evaluate beta diversity with regard to age, water depth, and spatial distance, and compare the results with a null model to evaluate the stochasticity of these differences. Using pairwise proportional dissimilarity, we find very high beta diversity for the Cassian Formation (0.91 ± 0.02) and slightly lower beta diversity for the Bay of Safaga (0.89 ± 0.04). Null models show that stochasticity only plays a minor role in determining faunal differences. Spatial distance is also irrelevant. Contrary to expectations, there is no tendency of beta diversity to decrease with water depth. Although water depth has frequently been found to be a key factor in determining beta diversity, we find that it is not the major driver in these reef-associated soft-bottom environments. We postulate that priority effects and the biotic structuring of the sediment may be key determinants of beta diversity

Familial Occurrence of Multiple Sclerosis with Thyroid Disease and Systemic Lupus Erythematosus

Multiple sclerosis (MS) has some features which suggest it is an autoimmune disease. Autoimmune diseases frequently occur in families, and patients and families often have more than one type of autoimmune disease. However, there are few reports of MS occurring in patients or families with other autoimmune conditions. It is difficult to make a separate diagnosis of MS in a patient who has a systemic autoimmune disease such as systemic lupus erythematosus (SLE) or Sjogren's syndrome, because these diseases can affect the nervous system directly. However, it is possible to make independent diagnoses of MS and an autoimmune disease confined to another single organ in the same patient, or diagnoses of MS and SLE (or other autoimmune diseases) in different family members. Here we describe clinically definite MS in 2 sisters, one of whom had Graves' disease, and the other of whom had a daughter with SLE and with a high titre of anti-thyroid antibodies. Other female family members over 4 generations had histories of thyroid disease, MS and Addison's disease. Available family members were HLA typed. The MS patients were positive for HLA DR2. All but one of the affected family members were related to the proband on the maternal side, and all of these affected females shared an HLA haplotype. However, this haplotype was also present in unaffected individuals. Thus HLA type alone cannot account for the familial occurrence of these disorders. We conclude that, in this family, MS, like autoimmune thyroid disease and SLE, may be an autoimmune disease developing in genetically predisposed individuals

Multilingual RECIST classification of radiology reports using supervised learning.

OBJECTIVES The objective of this study is the exploration of Artificial Intelligence and Natural Language Processing techniques to support the automatic assignment of the four Response Evaluation Criteria in Solid Tumors (RECIST) scales based on radiology reports. We also aim at evaluating how languages and institutional specificities of Swiss teaching hospitals are likely to affect the quality of the classification in French and German languages. METHODS In our approach, 7 machine learning methods were evaluated to establish a strong baseline. Then, robust models were built, fine-tuned according to the language (French and German), and compared with the expert annotation. RESULTS The best strategies yield average F1-scores of 90% and 86% respectively for the 2-classes (Progressive/Non-progressive) and the 4-classes (Progressive Disease, Stable Disease, Partial Response, Complete Response) RECIST classification tasks. CONCLUSIONS These results are competitive with the manual labeling as measured by Matthew's correlation coefficient and Cohen's Kappa (79% and 76%). On this basis, we confirm the capacity of specific models to generalize on new unseen data and we assess the impact of using Pre-trained Language Models (PLMs) on the accuracy of the classifiers

Milliwatt terahertz harmonic generation from topological insulator metamaterials

Achieving efficient, high-power harmonic generation in the terahertz spectral domain has technological applications, for example in sixth generation (6G) communication networks. Massless Dirac fermions possess extremely large terahertz nonlinear susceptibilities and harmonic conversion efficiencies. However, the observed maximum generated harmonic power is limited, because of saturation effects at increasing incident powers, as shown recently for graphene. Here, we demonstrate room-temperature terahertz harmonic generation in a Bi$_2$Se$_3$ topological insulator and topological-insulator-grating metamaterial structures with surface-selective terahertz field enhancement. We obtain a third-harmonic power approaching the milliwatt range for an incident power of 75 mW - an improvement by two orders of magnitude compared to a benchmarked graphene sample. We establish a framework in which this exceptional performance is the result of thermodynamic harmonic generation by the massless topological surface states, benefiting from ultrafast dissipation of electronic heat via surface-bulk Coulomb interactions. These results are an important step towards on-chip terahertz (opto)electronic applications