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People traditionally divine the future by interpreting natural phenomena as oracular signals, especially in societies adhering to traditional beliefs like China. With the advent of Generative AI (GenAI), people gain access to new ways of probing digital oracles for predicting the future. To understand how people use and interpret GenAI for divination in China, we interviewed 22 participants who habitually use GenAI platforms for fortune-telling, complemented by a three-week digital ethnography with 1,842 community posts. Qualitative analysis showed that people who seek psychological comfort are particularly receptive to GenAI-based decision-making. Users valued GenAI's accessibility, convenience, and efficiency while perceiving its lack of spiritual mystique. We observed community dynamics forming around GenAI tools, where users reinforce interpretations by sharing and discussing with each other, repeating queries until responses align with expectations. Our work uncovers how AI technologies change the way people and communities engage in traditional cultural practices while yearning for the same goals.

The proliferation of low-altitude intelligent agents is increasing the demand for timely and socially responsible collaborative sensing in dynamic urban environments. However, jointly addressing heterogeneous spatiotemporal demands, environmental uncertainty, and human-centered operational constraints remains challenging. This paper studies 3D multi-UAV path planning and task assignment under uncertain ground PoI demands. Unlike existing work assuming static and fully known PoIs, we model persistent, temporally predictable, and emergent demands within a unified framework. We further incorporate altitude-dependent societal and environmental costs, including noise exposure and public safety risks, to balance sensing performance with socially compliant operations. To solve the resulting large-scale mixed-integer nonlinear problem, we propose FORTUNE, a hierarchical offline-online framework. Offline, a Transformer predicts Type-II PoI activation windows, while an enhanced sparrow search algorithm generates coordinated flight plans through priority-aware decoding and danger-aware evolution. Online, a lightweight refinement module accommodates emerging Type-III PoIs while preserving glob

We study the family of complex rational functions known as Generalized McMullen maps, F(z) = z^n + a/z^n+b, for integer n at least 3 fixed, and complex parameters a, b with a nonzero. In prior work by the same authors, we provided a combinatorial model for a large class of maps whose Julia sets contain both infinitely many homeomorphic copies of quadratic Julia sets conjugate to the ``basilica'', and infinitely many subsets homeomorphic to a set which is obtained by starting with the basilica, then changing a finite number of pairs of external ray landing point identifications, following an algorithm we described. In this article, we generalize beyond the basilica, and provide a catalog of additional types of hyperbolic Julia sets of Generalized McMullen maps, where the ``baby'' Julia set can be any rabbit, aeroplane, or Kokopelli quadratic Julia set; that is, where the c-value can be taken from any bulb attached to the main cardioid of the Mandelbrot set, or from the main cardioid of any principal baby Mandelbrot set (no renormalizations).

This speculative video piece showcases participants interacting with a career counseling AI agent, unaware that the responses were actually derived from the fortunetelling of a mudang (a Korean traditional shaman). Our work captures this deception and documents participants' reactions, showcasing shifts in their initial perceptions of the agent's advice following the reveal. Notably, even after learning that the advice came from a mudang rather than an AI, participants did not change their initial attitudes toward the advice they received. This raises questions about the perceived importance of AI's explainability and accuracy. By juxtaposing scientific and pre-scientific approaches, we aim to provoke discussions on human agency in the age of AI. We argue that, regardless of AI's advancements, we continue to navigate life in fundamentally human ways -- wonderfully messy and uncertain.

AstroForge seeks to mine platinum group metals (PGM) from asteroids. Asteroid reserves appear to be unlimited, and at current market price the gross margin of asteroid mining would be very high. It is natural to ask: when AstroForge successfully demonstrates economic space mining of PGM, will they cause the PGM market to collapse? We answer the question with a non-steady system dynamics model of the PGM market. We find that the market price for PGM will eventually drop towards the much lower cost of asteroid mining, but only after the entire supply has shifted off-world. In the meanwhile, huge fortunes will be made. And everybody on Earth will benefit from new applications of lower-price PGM.

Over the past decades, superplatforms, digital companies that integrate a vast range of third-party services and applications into a single, unified ecosystem, have built their fortunes on monopolizing user attention through targeted advertising and algorithmic content curation. Yet the emergence of AI agents driven by large language models (LLMs) threatens to upend this business model. Agents can not only free user attention with autonomy across diverse platforms and therefore bypass the user-attention-based monetization, but might also become the new entrance for digital traffic. Hence, we argue that superplatforms have to attack AI agents to defend their centralized control of digital traffic entrance. Specifically, we analyze the fundamental conflict between user-attention-based monetization and agent-driven autonomy through the lens of our gatekeeping theory. We show how AI agents can disintermediate superplatforms and potentially become the next dominant gatekeepers, thereby forming the urgent necessity for superplatforms to proactively constrain and attack AI agents. Moreover, we go through the potential technologies for superplatform-initiated attacks, covering a brand-new,

A gambler with an initial fortune $x$ starts by betting a dollar, then doubles the bet after every win and halves the bet after every loss. Let $p\in (0,1)$ be the probability of winning for each round. We show that the gambler survives with positive probability if and only if $p < 1/2$ and $x > 2$. Moreover, the ruin probability is increasing and real-analytic in $p$, but a singular, Hölder continuous function of $x$.

The Ichimura-Austern-Vincent (IAV) model provides a powerful theoretical framework for describing inclusive breakup reactions. However, its post-form representation presents significant numerical challenges due to the absence of a natural cutoff in the transition matrix integration. This work presents a systematic assessment of convergence methods for post-form IAV calculations, comparing the bin method and the Vincent-Fortune approach. We demonstrate that while the bin method offers implementation simplicity, it exhibits strong parameter dependence that compromises numerical stability. In contrast, the Vincent-Fortune method, which employs complex contour integration, achieves reliable convergence without arbitrary parameters. We further introduce a novel hybrid approach that integrates finite-range distorted wave Born approximation (DWBA) with the Vincent-Fortune technique, combining the accuracy of finite-range treatment at short distances with the numerical stability of zero-range approximations in the asymptotic region. Numerical results for deuteron and $^6$Li-induced reactions confirm the efficacy of this hybrid method, showing consistent agreement with experimental data whi

Superstition and religious belief system have historically shaped human behavior, offering powerful psychological motivations and persuasive frameworks to guide actions. Inspired by Feng Shui -- an ancient Chinese superstition -- this paper proposes a pseudo-theoretical framework that integrates superstition-like heuristics into visualization design. Rather than seeking empirical truth, this framework leverages culturally resonant (superstitious) narratives and symbolic metaphors as persuasive tools to encourage desirable design practices, such as clarity, accessibility, and audience-centered thinking. We articulate a set of visualization designs into a Feng Shui compass, reframing empirical design principles and guidelines within an engaing mythology. We present how visualization design principles can be intepreted in Feng Shui narratives, discussing the potential of these metaphorical principles in reducing designer anxiety, fostering community norms, and enhancing the memorability and internalization of visualization design guidelines. Finally, we discuss Feng Shui visualization theory as a set of cognitive shortcuts that can exert persuasive power through playful, belief-like a

For the family of complex rational functions known as "Generalized McMullen maps", F(z) = z^n + a/z^n+b, for complex parameters a and b, with a nonzero, and any integer n at least 3 fixed, we reveal, and provide a combinatorial model for, some new dynamical behavior. In particular, we describe a large class of maps whose Julia sets contain both infinitely many homeomorphic copies of quadratic Julia sets and infinitely many subsets homeomorphic to a set which is obtained by starting with a quadratic Julia set, then changing a finite number of pairs of external ray landing point identifications, following an algorithm we will describe.

This paper introduces an innovative entanglement-based protocol that accomplishes multiparty quantum private comparison leveraging maximally entangled GHZ3 triplets. The primary motivation is the design of a protocol that can be executed by contemporary quantum computers. This is made possible because the protocol uses only GHZ3 triplets, irrespective of the number of millionaires. While more complex multi-particle entangled states are possible, they are challenging to produce with existing quantum apparatus, leading to extended preparation time and complexity, particularly in scenarios involving numerous participants. By relying on GHZ3 states, which are the easiest to produce after Bell states, we avoid these drawbacks, and take a step towards the practical implementation of the protocol. An important quantitative characteristic of this protocol is that the required quantum resources are linear both in the number of millionaires and the volume of information to be compared. A notable aspect of the protocol is its suitability for both parallel and sequential execution. Although the execution of the quantum part of the protocol is envisioned to take place completely in parallel, it

This article revisits earlier work by the second author together with Kay Magaard. We correct several little results and we briefly discuss why, fortunately, the errors hardly affect our main theorems and in particular do not affect the classification of simple groups that act with fixity 2. As an addition to the submitted article, this version also contains GAP code in a little appendix at the end.

``Calabi-Yau Manifolds: a Bestiary for Physicists'' by Tristan Hubsch in 1992 was a classic that served to introduce algebraic geometry to physicists when the first string theory revolution of 1984 - 94 brought, inter alia, the subject of Calabi-Yau manifolds to the staple of high-energy theorists. We are fortunate that a substantially expanded and updated new edition of the Bestiary will shortly appear. This brief note will serve as an afterword to the much anticipated volume.

In this paper, we prove that the foliated Rosenberg index of a possibly noncompactly enlargeable, spin foliation is nonzero. It generalizes our previous result. The difficulty brought by the noncompactness is reflected in the infinite dimensionality of some vector bundles which, fortunately, can be reduced to finite dimensional vector bundles by the idea of relative index theorem and $KK$-equivalence between the $C^\ast$-algebra of compact operators and $\mathbb{C}$.

Making ideal decisions as a product leader in a web-facing company is extremely difficult. In addition to navigating the ambiguity of customer satisfaction and achieving business goals, one must also pave a path forward for ones' products and services to remain relevant, desirable, and profitable. Data and experimentation to test product hypotheses are key to informing product decisions. Online controlled experiments by A/B testing may provide the best data to support such decisions with high confidence, but can be time-consuming and expensive, especially when one wants to understand impact to key business metrics such as retention or long-term value. Offline experimentation allows one to rapidly iterate and test, but often cannot provide the same level of confidence, and cannot easily shine a light on impact on business metrics. We introduce a novel, lightweight, and flexible approach to investigating hypotheses, called scenario analysis, that aims to support product leaders' decisions using data about users and estimates of business metrics. Its strengths are that it can provide guidance on trade-offs that are incurred by growing or shifting consumption, estimate trends in long-t

In recent years, pretrained language models have revolutionized the NLP world, while achieving state of the art performance in various downstream tasks. However, in many cases, these models do not perform well when labeled data is scarce and the model is expected to perform in the zero or few shot setting. Recently, several works have shown that continual pretraining or performing a second phase of pretraining (inter-training) which is better aligned with the downstream task, can lead to improved results, especially in the scarce data setting. Here, we propose to leverage sentiment-carrying discourse markers to generate large-scale weakly-labeled data, which in turn can be used to adapt language models for sentiment analysis. Extensive experimental results show the value of our approach on various benchmark datasets, including the finance domain. Code, models and data are available at https://github.com/ibm/tslm-discourse-markers.

Certain areas of scientific research flourish while others lose advocates and attention. We are interested in whether structural patterns within citation networks correspond to the growth or decline of the research areas to which those networks belong. We focus on three topic areas within optical physics as a set of cases; those areas have developed along different trajectories: one continues to expand rapidly; another is on the wane after an earlier peak; the final area has re-emerged after a short waning period. These three areas have substantial overlaps in the types of equipment they use and general methodology; at the same time, their citation networks are largely independent of each other. For each of our three areas, we map the citation networks of the top-100 most-cited papers, published pre-1999. In order to quantify the structures of the selected articles' citation networks, we use a modified version of weak tie theory in tandem with entropy measures. Although the fortunes of a given research area are most obviously the result of accumulated innovations and impasses, our preliminary study provides evidence that these citation networks' emergent structures reflect those de

Classes started in the newly established Physics Department of Calcutta University Science College in 1916. Raman, Bose and Saha were three young members of the small physics faculty consisting of barely half a dozen faculty members. Within about one decade, three extraordinary discoveries came from these young men---Saha ionization equation in 1920, Bose statistics in 1924, Raman effect in 1928. However, fortunes of Calcutta University quickly got intertwined with India's freedom struggle led by Mahatma Gandhi exactly at the same time and the physics group got tragically disrupted. Indian physics never succeeded in reaching that height again. This paper discusses the difficulties in reconstructing a critical history of this Calcutta school of physics during the very short epoch of unmatched brilliance.

When the probability of measuring a particular value of some quantity varies inversely as a power of that value, the quantity is said to follow a power law, also known variously as Zipf's law or the Pareto distribution. Power laws appear widely in physics, biology, earth and planetary sciences, economics and finance, computer science, demography and the social sciences. For instance, the distributions of the sizes of cities, earthquakes, solar flares, moon craters, wars and people's personal fortunes all appear to follow power laws. The origin of power-law behaviour has been a topic of debate in the scientific community for more than a century. Here we review some of the empirical evidence for the existence of power-law forms and the theories proposed to explain them.