Who counts as diverse? The strategic broadening and narrowing of diversity

Introduction: A large majority of US organizations profess a commitment to diversity, but their definitions of diversity can vary greatly. While previous research demonstrates a shift in diversity definitions to include fewer protected demographic groups and more non-demographic characteristics, the present research examines whether this shift might be a motivated process among dominant group members related to anti-egalitarian and colorblind belief systems. Methods: Using quantitative and qualitative methods, we explored potential underlying ideologies that may be associated with White Americans’ shifting definitions of diversity. White Americans (N = 498) were asked how they define diversity, as well as who should be included in a range of diversity initiatives. Results: White participants’ higher anti-egalitarian belief was associated with stronger colorblind ideology endorsement, which was then associated with shifting their definition of diversity to include fewer disadvantaged demographic groups, more advantaged demographic groups, and non-demographic groups, as well as employing a colorblind inclusion rhetoric. Discussion: Instead of only “broadening” diversity to include more characteristics than diversity’s original focus, White Americans higher in anti-egalitarian and colorblind motives exhibited a simultaneous “narrowing” of diversity to include fewer protected demographic characteristics. Taken together, these findings have implications for dominant group members’ definition of diversity and the subtle ways in which colorblind ideology may be enacted

Geography and similarity of regional cuisines in China

Food occupies a central position in every culture and it is therefore of great interest to understand the evolution of food culture. The advent of the World Wide Web and online recipe repositories has begun to provide unprecedented opportunities for data-driven, quantitative study of food culture. Here we harness an online database documenting recipes from various Chinese regional cuisines and investigate the similarity of regional cuisines in terms of geography and climate. We found that the geographical proximity, rather than climate proximity is a crucial factor that determines the similarity of regional cuisines. We develop a model of regional cuisine evolution that provides helpful clues to understand the evolution of cuisines and cultures.Comment: 13 pages, 11 figures and 2 table

Seeing Is Not Always Believing: Invisible Collision Attack and Defence on Pre-Trained Models

Large-scale pre-trained models (PTMs) such as BERT and GPT have achieved great success in diverse fields. The typical paradigm is to pre-train a big deep learning model on large-scale data sets, and then fine-tune the model on small task-specific data sets for downstream tasks. Although PTMs have rapidly progressed with wide real-world applications, they also pose significant risks of potential attacks. Existing backdoor attacks or data poisoning methods often build up the assumption that the attacker invades the computers of victims or accesses the target data, which is challenging in real-world scenarios. In this paper, we propose a novel framework for an invisible attack on PTMs with enhanced MD5 collision. The key idea is to generate two equal-size models with the same MD5 checksum by leveraging the MD5 chosen-prefix collision. Afterwards, the two ``same" models will be deployed on public websites to induce victims to download the poisoned model. Unlike conventional attacks on deep learning models, this new attack is flexible, covert, and model-independent. Additionally, we propose a simple defensive strategy for recognizing the MD5 chosen-prefix collision and provide a theoretical justification for its feasibility. We extensively validate the effectiveness and stealthiness of our proposed attack and defensive method on different models and data sets

High-order accurate well-balanced energy stable finite difference schemes for multi-layer shallow water equations on fixed and adaptive moving meshes

This paper develops high-order well-balanced (WB) energy stable (ES) finite difference schemes for multi-layer (the number of layers $M\geqslant 2$) shallow water equations (SWEs) on both fixed and adaptive moving meshes, extending our previous works [20,51]. To obtain an energy inequality, the convexity of an energy function for an arbitrary $M$ is proved by finding recurrence relations of the leading principal minors or the quadratic forms of the Hessian matrix of the energy function with respect to the conservative variables, which is more involved than the single-layer case due to the coupling between the layers in the energy function. An important ingredient in developing high-order semi-discrete ES schemes is the construction of a two-point energy conservative (EC) numerical flux. In pursuit of the WB property, a sufficient condition for such EC fluxes is given with compatible discretizations of the source terms similar to the single-layer case. It can be decoupled into $M$ identities individually for each layer, making it convenient to construct a two-point EC flux for the multi-layer system. To suppress possible oscillations near discontinuities, WENO-based dissipation terms are added to the high-order WB EC fluxes, which gives semi-discrete high-order WB ES schemes. Fully-discrete schemes are obtained by employing high-order explicit SSP-RK methods and proved to preserve the lake at rest. The schemes are further extended to moving meshes based on a modified energy function for a reformulated system, relying on the techniques proposed in [51]. Numerical experiments are conducted for some two- and three-layer cases to validate the high-order accuracy, WB and ES properties, and high efficiency of the schemes, with a suitable amount of dissipation chosen by estimating the maximal wave speed due to the lack of an analytical expression for the eigenstructure of the multi-layer system.Comment: 54 pages, 19 figure

Inequalities related to the S-Divergence

The S-Divergence is a distance like function on the convex cone of positive definite matrices, which is motivated from convex optimization. In this paper, we will prove some inequalities for Kubo-Ando means with respect to the square root of the S-Divergence