This paper examines how science fiction destabilises ontological categories by measuring conceptual permeability across the terms human, animal, and machine using masked language modelling (MLM). Drawing on corpora of science fiction (Gollancz SF Masterworks) and general fiction (NovelTM), we operationalise Darko Suvin's theory of estrangement as computationally measurable deviation in token prediction, using RoBERTa to generate lexical substitutes for masked referents and classifying them via Gemini. We quantify conceptual slippage through three metrics: retention rate, replacement rate, and entropy, mapping the stability or disruption of category boundaries across genres. Our findings reveal that science fiction exhibits heightened conceptual permeability, particularly around machine referents, which show significant cross-category substitution and dispersion. Human terms, by contrast, maintain semantic coherence and often anchor substitutional hierarchies. These patterns suggest a genre-specific restructuring within anthropocentric logics. We argue that estrangement in science fiction operates as a controlled perturbation of semantic norms, detectable through probabilistic model
Gaussian random polytopes have received a lot of attention especially in the case where the dimension is fixed and the number of points goes to infinity. Our focus is on the less studied case where the dimension goes to infinity and the number of points is proportional to the dimension $d$. We study several natural quantities associated to Gaussian random polytopes in this setting. First, we show that the expected number of facets is equal to $C(α)^{d+o(d)}$ where $C(α)$ is some constant which depends on the constant of proportionality $α$. We also extend this result to the expected number of $k$-facets. We then consider the more difficult problem of the asymptotics of the expected number of pairs of $\textit{estranged facets}$ of a Gaussian random polytope. When $n=2d$, we determined the constant $C$ so that the expected number of pairs of estranged facets is equal to $C^{d+o(d)}$.
Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, has recently received significant attention for mass communication and commercial marketing. Existing research efforts dedicated to the IM problem depend on a strong assumption: the selected seed users are willing to spread the information after receiving benefits from a company or organization. In reality, however, some seed users may be reluctant to spread the information, or need to be paid higher to be motivated. Furthermore, the existing IM works pay little attention to capture user's influence propagation in the future period as well. In this paper, we target a new research problem, named Reconnecting Top-l Relationships (RTlR) query, which aims to find l number of previous existing relationships but being stranged later, such that reconnecting these relationships will maximize the expected benefit of influenced users by the given group in a future period. We prove that the RTlR problem is NP-hard. An efficient greedy algorithm is proposed to answer the RTlR queries with the influence estimation technique and the well-chosen link predicti
We study phase diagrams of charge-conserving `class A' non-interacting fermions, focusing on the trivial phase in various dimensions. Such phases are usually termed `featureless' to distinguish them from those others with either symmetry-broken or topological order. We show that the presence of non-trivial topological families of states, including charge pumps and their generalizations, results in phase diagrams being endowed with non-trivial topological textures that can be visualized through Berry phases and their higher-dimensional generalizations. We show that for non-interacting fermion systems with translation invariance, these `higher' Berry phases can be computed using integrals of non-abelian Chern-Simons forms of the Berry-Bloch connection over momentum and parameter spaces. Singularities in these textures correspond to gap-closing loci of `diabolical points', which represent the obstruction to contracting topologically non-trivial families of states, and bulk-boundary correspondence results in a locus of robust boundary modes that terminate at the bulk diabolical points. In the presence of finite chemical potential, we argue that the edge modes are generically robust wit
Efficiently utilizing discriminative features is crucial for convolutional neural networks to achieve remarkable performance in medical image segmentation and is also important for model generalization across multiple domains, where letting model recognize domain-specific and domain-invariant information among multi-site datasets is a reasonable strategy for domain generalization. Unfortunately, most of the recent disentangle networks are not directly adaptable to unseen-domain datasets because of the limitations of offered data distribution. To tackle this deficiency, we propose Contrastive Domain Disentangle (CDD) network for generalizable medical image segmentation. We first introduce a disentangle network to decompose medical images into an anatomical representation factor and a modality representation factor. Then, a style contrastive loss is proposed to encourage the modality representations from the same domain to distribute as close as possible while different domains are estranged from each other. Finally, we propose a domain augmentation strategy that can randomly generate new domains for model generalization training. Experimental results on multi-site fundus image datas
Cancer research reflects an implicit conflict. On the one hand, there is an overwhelming desire to control the disease. We all wish that. On the other hand, we would like to understand why cancer follows so many clearly defined yet puzzling patterns. Why is there such regularity in the rates of progression? Why do different tissues vary so much? There should, of course, be no conflict between control and understanding. But the history of cancer research seems to say that those different goals remain oddly estranged. Peto's 1977 article locates the seeds of this conflict most clearly. He describes what is still the most powerful theoretical perspective for analyzing the causes of cancer. He presents many key unsolved puzzles within that context. He also says why most cancer researchers are not interested in these fundamental issues. The subsequent decades of research grew around this rift, blindly, in the way that research disciplines often grow. Let us revisit Peto, almost 40 years ago. We can learn much about the current nature of cancer research.
A new study suggests the brain begins making decisions much earlier than scientists previously thought。 Researchers found that even primary sensory regions are influenced by higher brain areas through rapid feedback loops, rather than simply passing information forward。 This more dynamic view of brain function could help engineers design future AI
A strange "chirping" signal from a distant supernova has revealed the birth of a magnetar, confirming that these incredibly magnetic neutron stars can power the universe's brightest stellar explosions。 The discovery also marks the first time Einstein's general relativity has been used to explain the mechanics of a supernova
New research overturns assumption that abstinent younger drinkers are behind weak demand
A new book claims AI has been built on a flawed assumption dating back to Alan Turing's famous 1950 paper。 Denning argues that the most important parts of human intelligence, including common sense, intuition, culture, and practical know-how, cannot be encoded into computers。 He believes this makes true human-level AI impossible, regardless of how
Scientists have uncovered new evidence that fireworks can pollute both the air and water in ways that extend beyond the visible smoke。 The findings show that leftover debris, fine particles, and airborne chemicals may affect ecosystems and increase people's exposure to air pollution during major celebrations
Two newly confirmed "super-puff" planets are so diffuse that they are less dense than cotton candy, despite being about the size of Jupiter。 Their rare orbital relationship and enormous, lightweight atmospheres could provide valuable clues about how some of the strangest planets in the galaxy come to exist
An unusual gravitational wave signal has renewed hopes that primordial black holes, long considered purely theoretical, may finally be within reach of discovery。 If confirmed, they could solve one of astronomy's greatest mysteries by explaining the nature of dark matter
AG: Deal will bring "higher prices, lower quality, and less content for film and TV
Physicists from Heinrich Heine University Düsseldorf (HHU) have examined a fundamental property of quantum mechanics in collaboration with the German Aerospace Center (DLR)。 In the scientific journal Physical Review Letters, they show that this theory does not necessarily need to be formulated with imaginary numbers – real numbers can in fact also