The College Admissions Contribution to the Labor Market Beauty Premium

Beautiful people earn more. Surprisingly, this premium is larger for men than for women and is independent of the degree of customer contact. Overlooked is the possibility that beauty can influence college admissions. We explore this academic contributor to the labor market beauty earnings premium by sampling 1,800 social media profiles of students from universities ranked from 1 to 200 in China and the US. Chinese universities use only standardized test scores for admissions. In contrast, US universities use also grades and extracurricular activities, which are not necessarily beauty-blind. Consistent with beauty-blind admissions, alumni’s beauty is uncorrelated with the rank of college attended in China. In the US, White men from higher ranked colleges are better-looking. As expected, the correlation is insignificant for White men who attended tech colleges and is highest for those who attended private colleges. We also find that White women and minorities of either gender are not better-looking at higher ranked colleges. Our evidence indicates a college admissions contribution to the labor market beauty premium for US White men, but not for students in China of either gender, White women, or minorities of either gender in the US, or for White men who attended technology colleges. We discuss the college admissions preference for athletes as a potential channel for the positive correlation we find between college and beauty rank for White men

Surface Roughness Gradients Reveal Topography‐Specific Mechanosensitive Responses in Human Mesenchymal Stem Cells

The topographic features of an implant, which mechanically regulate cell behaviors and functions, are critical for the clinical success in tissue regeneration. How cells sense and respond to the topographical cues, e.g., interfacial roughness, is yet to be fully understood and even debatable. Here, the mechanotransduction and fate determination of human mesenchymal stem cells (MSCs) on surface roughness gradients are systematically studied. The broad range of topographical scales and high‐throughput imaging is achieved based on a catecholic polyglycerol coating fabricated by a one‐step‐tilted dip‐coating approach. It is revealed that the adhesion of MSCs is biphasically regulated by interfacial roughness. The cell mechanotransduction is investigated from focal adhesion to transcriptional activity, which explains that cellular response to interfacial roughness undergoes a direct force‐dependent mechanism. Moreover, the optimized roughness for promoting cell fate specification is explored

γ\gamma-hadron spectra in p + Pb collisions at sNN=5.02\sqrt{s_{\rm NN}}=5.02 TeV

Under the assumption that a quark-gluon plasma droplet is produced and its evolution can be described by hydrodynamics in p + A collisions, $\gamma$-triggered hadron spectra are studied within a next-to-leading-order perturbative QCD parton model with the medium-modified parton fragmentation functions. The initial conditions and space-time evolution of the small QGP droplet are provided by the superSONIC hydrodynamic model simulations and parton energy loss in such a medium is described by the high-twist (HT) approach. The scaled jet transport coefficient $\hat{q}/T^3$ in this HT approach is extracted from single hadron suppression in central A + A collisions at the same colliding energy. Numerical results for this scenario show that $\gamma$-hadron spectra at $p_{\rm T}^\gamma=12-40$ GeV/$c$ are suppressed by 5\% $\sim$ 10\% in the most central 0 - 10\% p + Pb collisions at $\sqrt{s_{\rm NN}}=5.02$ TeV. The suppression becomes weaker at higher transverse momentum of the $\gamma$ trigger. As a comparison, $\gamma$-hadron suppression in Pb + Pb collisions at $\sqrt{s_{\rm NN}}=2.76$ and 5.02 TeV is also predicted.Comment: 15 pages, 15 figures. v2: published versio

Frozen Transformers in Language Models Are Effective Visual Encoder Layers

This paper reveals that large language models (LLMs), despite being trained solely on textual data, are surprisingly strong encoders for purely visual tasks in the absence of language. Even more intriguingly, this can be achieved by a simple yet previously overlooked strategy -- employing a frozen transformer block from pre-trained LLMs as a constituent encoder layer to directly process visual tokens. Our work pushes the boundaries of leveraging LLMs for computer vision tasks, significantly departing from conventional practices that typically necessitate a multi-modal vision-language setup with associated language prompts, inputs, or outputs. We demonstrate that our approach consistently enhances performance across a diverse range of tasks, encompassing pure 2D and 3D visual recognition tasks (e.g., image and point cloud classification), temporal modeling tasks (e.g., action recognition), non-semantic tasks (e.g., motion forecasting), and multi-modal tasks (e.g., 2D/3D visual question answering and image-text retrieval). Such improvements are a general phenomenon, applicable to various types of LLMs (e.g., LLaMA and OPT) and different LLM transformer blocks. We additionally propose the information filtering hypothesis to explain the effectiveness of pre-trained LLMs in visual encoding -- the pre-trained LLM transformer blocks discern informative visual tokens and further amplify their effect. This hypothesis is empirically supported by the observation that the feature activation, after training with LLM transformer blocks, exhibits a stronger focus on relevant regions. We hope that our work inspires new perspectives on utilizing LLMs and deepening our understanding of their underlying mechanisms. Code is available at https://github.com/ziqipang/LM4VisualEncoding.Comment: 23 pages, 13 figures. Code at https://github.com/ziqipang/LM4VisualEncodin

Global constraint on the jet transport coefficient from single-hadron, dihadron, and γ-hadron spectra in high-energy heavy-ion collisions

Modifications of large transverse momentum single-hadron, dihadron, and γ-hadron spectra in relativistic heavy-ion collisions are direct consequences of parton-medium interactions in the quark-gluon plasma (QGP). The interaction strength and underlying dynamics can be quantified by the jet transport coefficient q. We carry out the first global constraint on q using a next-to-leading order pQCD parton model with higher-twist parton energy loss and combining world experimental data on single-hadron, dihadron, and γ-hadron suppression at both RHIC and LHC energies with a wide range of centralities. The global Bayesian analysis using the information field (IF) priors provides the most stringent constraint on q(T). We demonstrate in particular the progressive constraining power of the IF Bayesian analysis on the strong temperature dependence of q using data from different centralities and colliding energies. We also discuss the advantage of using both inclusive and correlation observables with different geometric biases. As a verification, the obtained q(T) is shown to describe data on single-hadron anisotropy at high transverse momentum well. Predictions for future jet quenching measurements in oxygen-oxygen collisions are also provided

(Z)-N-(3-Nicotinoyl-1,3-thia­zolidin-2-yl­idene)cyanamide

In the title compound, C10H8N4OS, the dihedral angle between the pyridine and thia­zolidine rings is 52.5 (5)°. Inter­molecular C—H⋯N inter­actions help to stabilize the crystal structure