Pushing bacterial biohybrids to in vivo applications

Bacterial biohybrids use the energy of bacteria to manipulate synthetic materials with the goal of solving biomedical problems at the micro- and nanoscale. We explore current in vitro studies of bacterial biohybrids, the first attempts at in vivo biohybrid research, and problems to be addressed for the future

Bayesian Optimization with Conformal Prediction Sets

Bayesian optimization is a coherent, ubiquitous approach to decision-making under uncertainty, with applications including multi-arm bandits, active learning, and black-box optimization. Bayesian optimization selects decisions (i.e. objective function queries) with maximal expected utility with respect to the posterior distribution of a Bayesian model, which quantifies reducible, epistemic uncertainty about query outcomes. In practice, subjectively implausible outcomes can occur regularly for two reasons: 1) model misspecification and 2) covariate shift. Conformal prediction is an uncertainty quantification method with coverage guarantees even for misspecified models and a simple mechanism to correct for covariate shift. We propose conformal Bayesian optimization, which directs queries towards regions of search space where the model predictions have guaranteed validity, and investigate its behavior on a suite of black-box optimization tasks and tabular ranking tasks. In many cases we find that query coverage can be significantly improved without harming sample-efficiency.Comment: For code, see https://www.github.com/samuelstanton/conformal-bayesopt.gi

The Electronic Spectrum of Fullerenes from the Dirac Equation

The electronic spectrum of sheets of graphite (plane honeycomb lattice) folded into regular polihedra is studied. A continuum limit valid for sufficiently large molecules and based on a tight binding approximation is derived. It is found that a Dirac equation describes the flat graphite lattice. Curving the lattice by insertion of odd numbered rings can be mimicked by coupling effective gauge fields. In particular the $C_{60}$ and related molecules are well described by the Dirac equation on the surface of a sphere coupled to a color monopole sitting at its center.Comment: 29 pages, 7 figures. IASSNS-HEP-92/5

Circumlocution in diagnostic medical queries. In:

ABSTRACT Circumlocution is when many words are used to describe what could be said with fewer, e.g., "a machine that takes moisture out of the air" instead of "dehumidifier". Web search is a perfect backdrop for circumlocution where people struggle to name what they seek. In some domains, not knowing the correct term can have a significant impact on the search results that are retrieved. We study the medical domain, where professional medical terms are not commonly known and where the consequence of not knowing the correct term can impact the accuracy of surfaced information, as well as escalation of anxiety, and ultimately the medical care sought. Given a free-form colloquial health search query, our objective is to find the underlying professional medical term. The problem is complicated by the fact that people issue quite varied queries to describe what they have. Machine-learning algorithms can be brought to bear on the problem, but there are two key complexities: creating highquality training data and identifying predictive features. To our knowledge, no prior work has been able to crack this important problem due to the lack of training data. We give novel solutions and demonstrate their efficacy via extensive experiments, greatly improving over the prior art

Dynamics of novel photoactive AgCl microstars and their environmental applications

In the field of micromotors many efforts have been taken to find a substitute for peroxide as fuel. While most approaches turn towards other toxic high energy chemicals such as hydrazine, we introduce here an energy source that is widely used in nature: light. Light is an ideal source of energy and some materials, such as AgCl, have the inherent property to transform light energy for chemical processes, which can be used to achieve propulsion. In the case of silver chloride, one process observed after light exposure is surface modification, which leads to the release of ions, generating chemo-osmotic gradients. Here we present endeavors to use those processes to propel uniquely shaped micro-objects of microstar morphology with a high surfaceto- volume ratio, study their dynamics and present approaches to go towards real environmental applications

PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design

Bayesian optimization offers a sample-efficient framework for navigating the exploration-exploitation trade-off in the vast design space of biological sequences. Whereas it is possible to optimize the various properties of interest jointly using a multi-objective acquisition function, such as the expected hypervolume improvement (EHVI), this approach does not account for objectives with a hierarchical dependency structure. We consider a common use case where some regions of the Pareto frontier are prioritized over others according to a specified $\textit{partial ordering}$ in the objectives. For instance, when designing antibodies, we would like to maximize the binding affinity to a target antigen only if it can be expressed in live cell culture -- modeling the experimental dependency in which affinity can only be measured for antibodies that can be expressed and thus produced in viable quantities. In general, we may want to confer a partial ordering to the properties such that each property is optimized conditioned on its parent properties satisfying some feasibility condition. To this end, we present PropertyDAG, a framework that operates on top of the traditional multi-objective BO to impose this desired ordering on the objectives, e.g. expression $\rightarrow$ affinity. We demonstrate its performance over multiple simulated active learning iterations on a penicillin production task, toy numerical problem, and a real-world antibody design task.Comment: 9 pages, 7 figures. Submitted to NeurIPS 2022 AI4Science Worksho