REVISED MASS-TO-LIGHT RATIOS FOR NEARBY GALAXY GROUPS AND CLUSTERS

We present a detailed investigation of the cluster stellar mass-to-light (M*/L) ratio and cumulative stellar masses, derived on a galaxy-by-galaxy basis, for 12 massive (M [subscript 500] ~ 10[superscript 14]-10[superscript 15] M [subscript ☉]), nearby clusters with available optical imaging data from the Sloan Digital Sky Survey Data Release 10 and X-ray data from the Chandra X-ray Observatory. Our method involves a statistical cluster membership using both photometric and spectroscopic redshifts when available to maximize completeness while minimizing contamination effects. We show that different methods of estimating the stellar mass-to-light ratio from observed photometry result in systematic discrepancies in the total stellar masses and average mass-to-light ratios of cluster galaxies. Nonetheless, all conversion methodologies point to a lack of correlation between M*/L[subscript i] and total cluster mass, even though low-mass groups contain relatively more blue galaxies. We also find no statistically significant correlation between M*/L[subscript i] and the fraction of blue galaxies (g – i < 0.85). For the mass range covered by our sample, the assumption of a Chabrier initial mass function (IMF) yields an integrated M*/L[subscript i] [~ over bar] 1.7 ± 0.2 M [subscript ☉]/L[subscript i], [subscript ☉], a lower value than used in most similar studies, though consistent with the study of low-mass galaxy groups by Leauthaud et al. A light (diet) Salpeter IMF would imply a ~60% increase in M*/L[subscript i]

Revisiting equilibrium condensation and rocky planet compositions: Introducing the ECCOplanets code

We introduce ECCOplanets, an open-source Python code that simulates condensation in the protoplanetary disk. Our aim is to analyse how well a simplistic model can reproduce the main characteristics of rocky planet formation. For this purpose, we revisited condensation temperatures ($T_c$) as a means to study disk chemistry, and explored their sensitivity to variations in pressure (p) and elemental abundance pattern. We also examined the bulk compositions of rocky planets around chemically diverse stars. Our T-p-dependent chemical equilibrium model is based on a Gibbs free energy minimisation. We derived condensation temperatures for Solar System parameters with a simulation limited to the most common chemical species. We assessed their change ($\Delta T_c$) as a result of p-variation between $10^{-6}$ and 0.1 bar. To analyse the influence of the abundance pattern, key element ratios were varied, and the results were validated using solar neighbourhood stars. To derive the bulk compositions of planets, we explored three different planetary feeding-zone (FZ) models and compared their output to an external n-body simulation. Our model reproduces the external results well in all tests. For common planet-building elements, we derive a Tc that is within $\pm5$ K of literature values, taking a wider spectrum of components into account. The Tc is sensitive to variations in p and the abundance pattern. For most elements, it rises with p and metallicity. The tested pressure range ($10^{-6} - 0.1$ bar) corresponds to $\Delta T_c \approx +350$ K, and for -0.3 $\leq$ [M/H] $\leq$ 0.4 we find $\Delta T_c \approx +100$ K. An increase in C/O from 0.1 to 0.7 results in a decrease of $\Delta T_c \approx -100$ K. Other element ratios are less influential. Dynamic planetary accretion can be emulated well with any FZ model. Their width can be adapted to reproduce gradual changes in planetary composition

PD-1+ IFN-γ+ subset of CD8+ T cell in circulation predicts response to anti–PD-1 therapy in NSCLC

BackgroundTreatment with programmed cell death protein-1 (PD-1) antibodies has minimal response rates in patients with non–small cell lung cancer (NSCLC), and, actually, they are treated with chemotherapy combined with anti–PD-1 therapy clinically. Reliable markers based on circulating immune cell subsets to predict curative effect are still scarce.MethodsWe included 30 patients with NSCLC treated with nivolumab or atezolizumab plus platinum drugs between 2021 and 2022. Whole blood was collected at baseline (before treatment with nivolumab or atezolizumab). The percentage of circulating PD-1+ Interferon-γ (IFN-γ+) subset of CD8+ T cell was determined by flow cytometry. The proportion of PD-1+ IFN-γ+ was calculated after gating on CD8+ T cells. Neutrophil/lymphocyte ratio (NLR), relative eosinophil count (%), and Lactate dehydrogenase (LDH) concentration at baseline of included patients were extracted from electronic medical records.ResultsThe percentage of circulating PD-1+ IFN-γ+ subset of CD8+ T cell at baseline in responders was significantly higher than those in non-responders (P &lt; 0.05). Relative eosinophil count (%) and LDH concentration in responders showed no significance between non-responders and responders. NLR in responders was significantly lower than those in non-responders (P &lt; 0.05). Receiver operation characteristic (ROC) analysis found that the areas under the ROC curve for PD-1+ IFN-γ+ subset of CD8+ T cell and NLR were 0.7781 (95% CI, 0.5937–0.9526) and 0.7315 (95% CI, 0.5169–0.9461). Moreover, high percentage of PD-1+ IFN-γ+ subset in CD8+ T cells was relevant to long progression-free survival in patients with NSCLC treated with chemotherapy combined with anti–PD-1 therapy.ConclusionThe percentage of circulating PD-1+ IFN-γ+ subset of CD8+ T cell could be a potential marker at baseline to predict early response or progression in patients with NSCLC receiving chemotherapy combined with anti–PD-1 therapy

The Multiplicity of M-Dwarfs in Young Moving Groups

We image 104 newly identified low-mass (mostly M-dwarf) pre-main sequence members of nearby young moving groups with Magellan Adaptive Optics (MagAO) and identify 27 binaries with instantaneous projected separation as small as 40 mas. 15 were previously unknown. The total number of multiple systems in this sample including spectroscopic and visual binaries from the literature is 36, giving a raw multiplicity rate of at least $35^{+5}_{-4}\%$ for this population. In the separation range of roughly 1 - 300 AU in which infrared AO imaging is most sensitive, the raw multiplicity rate is at least $24^{+5}_{-4}\%$ for binaries resolved by the MagAO infrared camera (Clio). The M-star sub-sample of 87 stars yields a raw multiplicity of at least $30^{+5}_{-4}\%$ over all separations, $21^{+5}_{-4}\%$ for secondary companions resolved by Clio from 1 to 300 AU ($23^{+5}_{-4}\%$ for all known binaries in this separation range). A combined analysis with binaries discovered by the Search for Associations Containing Young stars shows that multiplicity fraction as a function of mass and age over the range of 0.2 to 1.2 $M_\odot$ and 10 - 200 Myr appears to be linearly flat in both parameters and across YMGs. This suggests that multiplicity rates are largely set by 100 Myr without appreciable evolution thereafter. After bias corrections are applied, the multiplicity fraction of low-mass YMG members ($< 0.6 M_\odot$) is in excess of the field.Comment: 25 page

Cognitive and Action Sequence Prediction using Deductive Reasoning

Early in the process of the development of an aircraft cockpit, although the designers always introduce a set of operational procedures with the expectation that all pilots would follow, it is very difficult to guarantee that the flight crew will do exactly they are expected to do. The deviation of the pilots’ operation from the intended procedures may lead to an unsafe situation, and could also be an indication to the inherent reason for the biases in the pilots’ cognitive process. It became very obvious that a tool that could help to predict a comprehensive set of possible operations that the pilots would operate the aircraft will be very useful both in the flight deck design process and pilot training practices. This paper presents the development of the researches in the “Cognitive and Action Sequence Prediction using Deductive Creation Theory (CASEPREDICT)”. Unlike any human-made system which the response of the system can be predicted to certain degree of accuracy, a human-in-theloop system is always associated with a great deal of uncertainty issues which comes from the cognitive process of human operators