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Vahid Satarifard

Publications and source records attributed to Vahid Satarifard.

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Cultural Evolution of Perfumes since 1900

Perfumes are cultural artifacts and works of sensory art, composed from a finite, recombinable palette of notes that together evoke a distinctive scent impression. Here, we assemble the largest perfume corpus compiled to date, spanning multiple independent databases from 1900 to 2024, and study its evolution through a multidisciplinary computational framework. We first characterize perfumes by properties such as complexity and novelty using crowd-sourced data, finding that compositions have grown more minimalist in their scent profiles, yet more novel in their note combinations, a transition that began in the 1990s. Next, we construct copy-lineage networks and examine how notes are selected across successive time windows. We show that although imitation is pervasive, a growing share of notes drifts free of selection, and original creations retain a measurable quality premium, where they last longer, project further, and earn higher regard. Finally, we construct the collaboration network of master perfumers and show that a perfumer's creative style behaves as a social contagion, transmitted through collaboration and decaying with social distance. We discuss the principal forces shaping this evolution, including regulatory restrictions, cultural change, and the consolidation in the industry. Our findings position perfume as a culturally evolving system, akin to music and fashion, through which societies express and communicate hedonic sensory experiences.

physics.soc-ph

Benchmark for Assessing Olfactory Perception of Large Language Models

Here we introduce the Olfactory Perception (OP) benchmark, designed to assess the capability of large language models (LLMs) to reason about smell. The benchmark contains 1,010 questions across eight task categories spanning odor classification, odor primary descriptor identification, intensity and pleasantness judgments, multi-descriptor prediction, mixture similarity, olfactory receptor activation, and smell identification from real-world odor sources. Each question is presented in two prompt formats, compound names and isomeric SMILES, to evaluate the effect of molecular representations. Evaluating 21 model configurations across major model families, we find that compound-name prompts consistently outperform isomeric SMILES, with gains ranging from +2.4 to +18.9 percentage points (mean approx +7 points), suggesting current LLMs access olfactory knowledge primarily through lexical associations rather than structural molecular reasoning. The best-performing model reaches 64.4\% overall accuracy, which highlights both emerging capabilities and substantial remaining gaps in olfactory reasoning. We further evaluate a subset of the OP across 21 languages and find that aggregating predictions across languages improves olfactory prediction, with AUROC = 0.86 for the best performing language ensemble model. LLMs should be able to handle olfactory and not just visual or aural information.

cs.CL

How effective is graphene nanopore geometry on DNA sequencing?

In this paper we investigate the effects of graphene nanopore geometry on homopolymer ssDNA pulling process through nanopore using steered molecular dynamic (SMD) simulations. Different graphene nanopores are examined including axially symmetric and asymmetric monolayer graphene nanopores as well as five layer graphene polyhedral crystals (GPC). The pulling force profile, moving fashion of ssDNA, work done in irreversible DNA pulling and orientations of DNA bases near the nanopore are assessed. Simulation results demonstrate the strong effect of the pore shape as well as geometrical symmetry on free energy barrier, orientations and dynamic of DNA translocation through graphene nanopore. Our study proposes that the symmetric circular geometry of monolayer graphene nanopore with high pulling velocity can be used for DNA sequencing.

physics.bio-ph