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Motivation: Timetrees depict evolutionary relationships between species and the geological times of their divergence. Hundreds of research articles containing timetrees are published in scientific journals every year. The TimeTree project has been manually locating, curating, and synthesizing timetrees from these articles for almost two decades into a TimeTree of Life, delivered through a unique, userfriendly web interface (timetree.org). The manual process of finding articles containing timetrees is becoming increasingly expensive and time-consuming. So, we have explored the effectiveness of textmining approaches and developed optimizations to find research articles containing timetrees automatically. Results: We have developed an optimized machine learning (ML) system to determine if a research article contains an evolutionary timetree appropriate for inclusion in the TimeTree resource. We found that BERT classification fine-tuned on whole-text articles achieved an F1 score of 0.67, which we increased to 0.88 by text-mining article excerpts surrounding the mentioning of figures. The new method is implemented in the TimeTreeFinder tool, TTF, which automatically processes millions of articles to discover timetree-containing articles. We estimate that the TTF tool would produce twice as many timetree-containing articles as those discovered manually, whose inclusion in the TimeTree database would potentially double the knowledge accessible to a wider community.more »Manual inspection showed that the precision on out-of-distribution recently-published articles is 87%. This automation will speed up the collection and curation of timetrees with much lower human and time costs. Availability: https://github.com/marija-stanojevic/time-tree-classification Contact: {marija.stanojevic, s.kumar, zoran.obradovic}@temple.edu Supplementary information: Supplementary data are available at Bioinformatics online« less

In this paper, we show that the Turaev–Viro invariant volume conjecture posed by Chen and Yang is preserved under gluings of toroidal boundary components for a family of 3-manifolds. In particular, we show that the asymptotics of the Turaev–Viro invariants are additive under certain gluings of elementary pieces arising from a construction of hyperbolic cusped 3-manifolds due to Agol. The gluings of the elementary pieces are known to be additive with respect to the simplicial volume. This allows us to construct families of manifolds which have an arbitrary number of hyperbolic pieces and satisfy an extended version of the Turaev–Viro invariant volume conjecture.

The moving contact line between a fluid, liquid and solid is a ubiquitous phenomenon, and determining the maximum speed at which a liquid can wet/dewet a solid is a practically important problem. Using continuum models, previous studies have shown that the maximum speed of wetting/dewetting can be found by calculating steady solutions of the governing equations and locating the critical capillary number, $Ca_{{crit}}$ , above which no steady-state solution can be found. Below $Ca_{{crit}}$ , both stable and unstable steady-state solutions exist and if some appropriate measure of these solutions is plotted against $Ca$ , a fold bifurcation appears where the stable and unstable branches meet. Interestingly, the significance of this bifurcation structure to the transient dynamics has yet to be explored. This article develops a computational model and uses ideas from dynamical systems theory to show the profound importance of the unstable solutions on the transient behaviour. By perturbing the stable state by the eigenmodes calculated from a linear stability analysis it is shown that the unstable branch is an ‘edge’ state that is responsible for the eventual dynamical outcomes and that the system can become transient when $Ca< Ca_{{crit}}$ due to finite-amplitude perturbations. Furthermore, when $Ca>Ca_{{crit}}$ , wemore »show that the trajectories in phase space closely follow the unstable branch.« less

A model for the structure function tensor is proposed, incorporating the e↵ect of anisotropy as a linear perturbation to the standard isotropic form. The analysis extends the spectral approach of Ishihara et al. (2002) to physical space based on Kolmogorov’s theory and is valid in the inertial range of turbulence. Previous results for velocity co-spectra are used to obtain estimates of the model coe"cients. Structure functions measured from direct numerical simulations of channel flow and from experimental measurements in turbulent boundary layers are compared with predicted behaviour and reasonable agreement is found. We note that power-law scaling is more evident in the co-spectra than for the mixed structure functions. New observations are made about countergradient correlation between Fourier modes of wall normal and streamwise velocity components for wavenumbers approaching the Kolmogorov scale.

We present ultraviolet (UV) to near-infrared (NIR) observations and analysis of the nearby Type Ia supernova SN 2021fxy. Our observations include UV photometry from Swift/UVOT, UV spectroscopy from HST/STIS, and high-cadence optical photometry with the Swope 1-m telescope capturing intranight rises during the early light curve. Early B − V colours show SN 2021fxy is the first ‘shallow-silicon’ (SS) SN Ia to follow a red-to-blue evolution, compared to other SS objects which show blue colours from the earliest observations. Comparisons to other spectroscopically normal SNe Ia with HST UV spectra reveal SN 2021fxy is one of several SNe Ia with flux suppression in the mid-UV. These SNe also show blueshifted mid-UV spectral features and strong high-velocity Ca ii features. One possible origin of this mid-UV suppression is the increased effective opacity in the UV due to increased line blanketing from high velocity material, but differences in the explosion mechanism cannot be ruled out. Among SNe Ia with mid-UV suppression, SNe 2021fxy and 2017erp show substantial similarities in their optical properties despite belonging to different Branch subgroups, and UV flux differences of the same order as those found between SNe 2011fe and 2011by. Differential comparisons to multiple sets of synthetic SNmore »Ia UV spectra reveal this UV flux difference likely originates from a luminosity difference between SNe 2021fxy and 2017erp, and not differing progenitor metallicities as suggested for SNe 2011by and 2011fe. These comparisons illustrate the complicated nature of UV spectral formation, and the need for more UV spectra to determine the physical source of SNe Ia UV diversity.

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Conversational agents that respond to user information requests through a natural conversation have the potential to revolutionize how we acquire new information on the Web (i.e., perform exploratory Web searches). Recent advances to conversational search agents use popular Web search engines as a back-end and sophisticated AI algorithms to maintain context, automatically generate search queries, and summarize results into utterances. While showing impressive results on general topics, the potential of this technology for software engineering is unclear. In this paper, we study the potential of conversational search agents to aid software developers as they acquire new knowledge. We also obtain user perceptions of how far the most recent generation of such systems (e.g., Facebook's BlenderBot2) has come in its ability to serve software developers. Our study indicates that users find conversational agents helpful in gaining useful information for software-related exploratory search; however, their perceptions also indicate a large gap between expectations and current state of the art tools, especially in providing high-quality information. Participant responses provide directions for future work.

In multi-objective search, edges are annotated with cost vectors consisting of multiple cost components. A path dominates another path with the same start and goal vertices iff the component-wise sum of the cost vectors of the edges of the former path is 'less than' the component-wise sum of the cost vectors of the edges of the latter path. The Pareto-optimal solution set is the set of all undominated paths from a given start vertex to a given goal vertex. Its size can be exponential in the size of the graph being searched, which makes multi-objective search time-consuming. In this paper, we therefore study how to find an approximate Pareto-optimal solution set for a user-provided vector of approximation factors. The size of such a solution set can be significantly smaller than the size of the Pareto-optimal solution set, which enables the design of approximate multi-objective search algorithms that are efficient and produce small solution sets. We present such an algorithm in this paper, called A*pex. A*pex builds on PPA*, a state-of-the-art approximate bi-objective search algorithm (where there are only two cost components) but (1) makes PPA* more efficient for bi-objective search and (2) generalizes it to multi-objective search for any numbermore »of cost components. We first analyze the correctness of A*pex and then experimentally demonstrate its efficiency advantage over existing approximate algorithms for bi- and tri-objective search.« less

The Pareto-optimal frontier for a bi-objective search problem instance consists of all solutions that are not worse than any other solution in both objectives. The size of the Pareto-optimal frontier can be exponential in the size of the input graph, and hence finding it can be hard. Some existing works leverage a user-specified approximation factor ε to compute an approximate Pareto-optimal frontier that can be significantly smaller than the Pareto-optimal frontier. In this paper, we propose an anytime approximate bi-objective search algorithm, called Anytime Bi-Objective A*-ε (A-BOA*ε). A-BOA*ε is useful when deliberation time is limited. It first finds an approximate Pareto-optimal frontier quickly, iteratively improves it while time allows, and eventually finds the Pareto-optimal frontier. It efficiently reuses the search effort from previous iterations and makes use of a novel pruning technique. Our experimental results show that A-BOA*ε substantially outperforms baseline algorithms that do not reuse previous search effort, both in terms of runtime and number of node expansions. In fact, the most advanced variant of A-BOA*ε even slightly outperforms BOA*, a state-of-the-art bi-objective search algorithm, for finding the Pareto-optimal frontier. Moreover, given only a limited amount of deliberation time, A-BOA*ε finds solutions that collectively approximate the Pareto-optimal frontier muchmore »better than the solutions found by BOA*.« less