Wabash College is a private liberal arts men's college in Crawfordsville, Indiana. Founded in 1832 by several Dartmouth College graduates and Midwestern leaders, it enrolls nearly 900 students. The college offers an undergraduate liberal arts curriculum in three academic divisions with 39 majors.
Background: The low-lying level structure of 13Be is still not fully understood; specifically, it has not been ruled out that the first 1/2- state could be located above the isomeric 0+ 2 state of 12Be and decay via that state. Purpose: Search for a possible decay path of 13Be excited states through the isomeric 0+ 2 state in 12Be. Method: The invariant mass technique was used to reconstruct (12Be + n) decay energies from neutron removal reactions of 14Be at 78 MeV/u on a 9Be target in coincidence with delayed gamma rays. Charged particles and neutrons were detected and identified with a telescope and a subset of the Modular Neutron Array (MoNA), respectively, around zero degrees. The CAESium-iodide scintillator ARray (CAESAR) was located around the telescope measuring the gamma rays. Results: No evidence for the population and decay of the 0+ 2 state in 12Be was observed. From the nonobservation of 511 keV gamma rays an upper limit of 6% of the p-wave contribution was extracted. Conclusions: The previously observed p-wave resonance at about 500 keV does not decay via the isomeric state and thus corresponds to the ground state of 13Be decaying to the 12Be ground state.
A single embedding space that covers text, images, video, and audio lets one index serve every query a user can pose. Embedding models built on vision-language backbones now lead text/image/video retrieval benchmarks but lack audio entirely, while audio-text retrieval is led by specialist systems that serve no other modality. We present the Fusion Embedding family, which adds audio to a frozen vision-language embedding base whose parameters are never updated: generation 1 (fusion-embedding-1) trains only a 16.4M-parameter connector between a frozen audio tower and the frozen base, and generation 2 (fusion-embedding-2) adds modality-gated deep adapters (44.2M parameters) whose branch never executes on text, image, or video inputs: their outputs are bit-for-bit those of the released base, verified after every training run. Because the base already binds text, images, and video, aligning audio to text alone makes audio-image retrieval emerge, with zero paired audio-visual training data. Alongside the recipe we map its design space with controlled negative results (rewriting training captions with an LLM, substituting a leaderboard-stronger audio tower, and widening the connector each reduce retrieval) and with training-protocol findings that we expect to transfer to any frozen decoder-LM embedding backbone. Both generations train in hours on a single GPU. Weights, code, and the evaluation harness are openly released.
Multiagent AI systems require consistent communication, but we lack methods to verify that agents share the same understanding of the terms used. Natural language is interpretable but vulnerable to semantic drift, while learned protocols are efficient but opaque. We propose a certification protocol based on the stimulus-meaning model, where agents are tested on shared observable events and terms are certified if empirical disagreement falls below a statistical threshold. In this protocol, agents restricting their reasoning to certified terms ("core-guarded reasoning") achieve provably bounded disagreement. We also outline mechanisms for detecting drift (recertification) and recovering shared vocabulary (renegotiation). In simulations with varying degrees of semantic divergence, core-guarding reduces disagreement by 72-96
Though sanctions on family members of primary targets have become increasingly popular coercive instruments, we know very little about their use, effectiveness, and major legal and human rights consequences. Drawing insight from several targeted sanctions directed at family members of the Russian elite in recent years, this article offers a detailed analysis of (1) why sanctioning states have increasingly opted for family member sanctions, (2) whether targeting family members increases the efficacy of sanctions regimes, (3) to what extent such targeted sanctions are legally and ethically defensible, and (4) whether they undermine human rights of targeted individuals. Our analysis suggests that family member sanctions have limited utility as they are mostly ineffective tools. They could also cause major human rights issues and legal challenges for the sanctioned individuals. Hence, family member sanctions appear to be ethically problematic tools that warrant careful reconsideration.
Charlotte Perkins Gilman, best known for "The Yellow Wallpaper" and Herland, brings a colloquial Machiavellian deception to women's political education in her sorely neglected novel, Benigna Machiavelli. Serialized in her magazine, The Forerunner, which itself is one of Gilman's attempts to generate social change, Benigna Machiavelli gives us the character, Benigna MacAvelly, triply marginalized-female, a child, from a poor family-who becomes a hidden leader. Benigna, following in the footsteps of Ben Franklin and Machiavelli, and advocating associations as a means to preserve liberty, seeks to cultivate women as social, political, and economic actors. Because the man-made world has malformed women, limiting reason's effectiveness as a means to pursue social change, Benigna turns to deception. This paper examines Benigna's-and Gilman's-uses of deception and imagination, respectively, as tools to create a new world, to generate a democratic polity.
