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  1. We see the external world as consisting not only of objects and their parts, but also of relations that hold between them. Visual analogy, which depends on similarities between relations, provides a clear example of how perception supports reasoning. Here we report an experiment in which we quantitatively measured the human ability to find analogical mappings between parts of different objects, where the objects to be compared were drawn either from the same category (e.g., images of two mammals, such as a dog and a horse), or from two dissimilar categories (e.g., a chair image mapped to a cat image).more »Humans showed systematic mapping patterns, but with greater variability in mapping responses when objects were drawn from dissimilar categories. We simulated the human response of analogical mapping using a computational model of mapping between 3D objects, visiPAM (visual Probabilistic Analogical Mapping). VisiPAM takes point-cloud representations of two 3D objects as inputs, and outputs the mapping between analogous parts of the two objects. VisiPAM consists of a visual module that constructs structural representations of individual objects, and a reasoning module that identifies a probabilistic mapping between parts of the two 3D objects. Model simulations not only capture the qualitative pattern of human mapping performance cross conditions, but also approach human-level reliability in solving visual analogy problems.« less
    Free, publicly-accessible full text available January 1, 2023
  2. Fitch, T. ; Lamm, C. ; Leder, H. ; Teßmar-Raible, K. (Ed.)
    Is analogical reasoning a task that must be learned to solve from scratch by applying deep learning models to massive numbers of reasoning problems? Or are analogies solved by computing similarities between structured representations of analogs? We address this question by comparing human performance on visual analogies created using images of familiar three-dimensional objects (cars and their subregions) with the performance of alternative computational models. Human reasoners achieved above-chance accuracy for all problem types, but made more errors in several conditions (e.g., when relevant subregions were occluded). We compared human performance to that of two recent deep learning models (Siamesemore »Network and Relation Network) directly trained to solve these analogy problems, as well as to that of a compositional model that assesses relational similarity between part-based representations. The compositional model based on part representations, but not the deep learning models, generated qualitative performance similar to that of human reasoners.« less
  3. Acoustic compressional and shear wave velocities (VP, VS) of anhydrous (AHRG) and hydrous rhyolitic glasses (HRG) containing 3.28 wt% (HRG-3) and 5.90 wt% (HRG-6) total water concentra- tion (H2Ot) have been measured using Brillouin light scattering (BLS) spectroscopy up to 3 GPa in a diamond-anvil cell at ambient temperature. In addition, Fourier-transform infrared (FTIR) spectroscopy was used to measure the speciation of H2O in the glasses up to 3 GPa. At ambient pressure, HRG-3 contains 1.58 (6) wt% hydroxyl groups (OH–) and 1.70 (7) wt% molecular water (H2Om) while HRG-6 contains 1.67 (10) wt% OH– and 4.23 (17) wt% H2Ommore »where the numbers in parentheses are ±1σ. With increasing pressure, very little H2Om, if any, converts to OH– within uncertainties in hydrous rhyolitic glasses such that HRG-6 contains much more H2Om than HRG-3 at all experimental pressures. We observe a nonlinear relationship between high-pressure sound velocities and H2Ot, which is attributed to the distinct effects of each water species on acoustic velocities and elastic moduli of hydrous glasses. Near ambient pressure, depolymerization due to OH– reduces VS and G more than VP and KS. VP and KS in both anhydrous and hydrous glasses decrease with increasing pressure up to ~1–2 GPa before increasing with pressure. Above ~1–2 GPa, VP and KS in both hydrous glasses converge with those in AHRG. In particular, VP in HRG-6 crosses over and becomes higher than VP in AHRG. HRG-6 displays lower VS and G than HRG-3 near ambient pressure, but VS and G in these glasses converge above ~2 GPa. Our results show that hydrous rhyolitic glasses with ~2–4 wt% H2Om can be as incompressible as their anhydrous counterpart above ~1.5 GPa. The nonlinear effects of hydration on high-pressure acoustic velocities and elastic moduli of rhyolitic glasses observed here may provide some insight into the behavior of hydrous silicate melts in felsic magma chambers at depth.« less
  4. Abstract The CUORE experiment is a large bolometric array searching for the lepton number violating neutrino-less double beta decay ( $$0\nu \beta \beta $$ 0 ν β β ) in the isotope $$\mathrm {^{130}Te}$$ 130 Te . In this work we present the latest results on two searches for the double beta decay (DBD) of $$\mathrm {^{130}Te}$$ 130 Te to the first $$0^{+}_2$$ 0 2 + excited state of $$\mathrm {^{130}Xe}$$ 130 Xe : the $$0\nu \beta \beta $$ 0 ν β β decay and the Standard Model-allowed two-neutrinos double beta decay ( $$2\nu \beta \beta $$ 2 ν βmore »β ). Both searches are based on a 372.5 kg $$\times $$ × yr TeO $$_2$$ 2 exposure. The de-excitation gamma rays emitted by the excited Xe nucleus in the final state yield a unique signature, which can be searched for with low background by studying coincident events in two or more bolometers. The closely packed arrangement of the CUORE crystals constitutes a significant advantage in this regard. The median limit setting sensitivities at 90% Credible Interval (C.I.) of the given searches were estimated as $$\mathrm {S^{0\nu }_{1/2} = 5.6 \times 10^{24} \, \mathrm {yr}}$$ S 1 / 2 0 ν = 5.6 × 10 24 yr for the $${0\nu \beta \beta }$$ 0 ν β β decay and $$\mathrm {S^{2\nu }_{1/2} = 2.1 \times 10^{24} \, \mathrm {yr}}$$ S 1 / 2 2 ν = 2.1 × 10 24 yr for the $${2\nu \beta \beta }$$ 2 ν β β decay. No significant evidence for either of the decay modes was observed and a Bayesian lower bound at $$90\%$$ 90 % C.I. on the decay half lives is obtained as: $$\mathrm {(T_{1/2})^{0\nu }_{0^+_2} > 5.9 \times 10^{24} \, \mathrm {yr}}$$ ( T 1 / 2 ) 0 2 + 0 ν > 5.9 × 10 24 yr for the $$0\nu \beta \beta $$ 0 ν β β mode and $$\mathrm {(T_{1/2})^{2\nu }_{0^+_2} > 1.3 \times 10^{24} \, \mathrm {yr}}$$ ( T 1 / 2 ) 0 2 + 2 ν > 1.3 × 10 24 yr for the $$2\nu \beta \beta $$ 2 ν β β mode. These represent the most stringent limits on the DBD of $$^{130}$$ 130 Te to excited states and improve by a factor $$\sim 5$$ ∼ 5 the previous results on this process.« less