Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain

Hierarchical temporal dynamics are a fundamental computational property of the brain; however, there are no whole-brain, noninvasive investigations into timescales of neural processing in animal models. To that end, we used the spatial resolution and sensitivity of ultra-high field fMRI to probe timescales across the whole macaque brain. We uncovered within-species consistency between timescales estimated from fMRI and electrophysiology. Crucially, we were not only able to demonstrate that we can replicate existing electrophysiological hierarchies, but we extended these to whole brain topographies. Our results validate the complementary use of hemodynamic and electrophysiological intrinsic timescales, establishing a basis for future translational work. Second, with those results in hand, we were able to show that one facet of the high-dimensional FC topography of any region in the brain is closely related to hierarchical temporal dynamics. We demonstrated that intrinsic timescales are organized along spatial gradients that closely match functional connectivity gradient topographies across the whole brain. We conclude that intrinsic timescales are an unifying organizational principle of neural processing across the whole brain.

Fast, Efficient Fragment-Based Coordinate Generation for Open Babel

<div>Rapidly predicting an accurate three dimensional geometry of a molecule is a crucial task in cheminformatics and a range of molecular modeling. Fast, accurate, and open implementation of structure prediction is necessary for reproducible cheminformatics research. We introduce fragment-based coordinate generation for Open Babel, a widely accepted open source toolkit for cheminformatics. The new implementation significant improves speed and stereochemical accuracy, while retaining or improving accuracy of bond lengths, bond angles, and dihedral torsions. We first separate an input molecule into fragments by cutting at rotatable bonds. Coordinates of fragments are set according to the fragment library, which is prepared from open crystallographic databases. Since coordinates of multiple atoms are decided at once, coordinate prediction is accelerated over the previous rules-based implementation or the widely-used distance geometry methods in RDKit. This new implementation will be beneficial for a wide range of applications, including computational property prediction in polymers, molecular materials and drug design.</div>

Fast, Efficient Fragment-Based Coordinate Generation for Open Babel

<div>Rapidly predicting an accurate three dimensional geometry of a molecule is a crucial task in cheminformatics and a range of molecular modeling. Fast, accurate, and open implementation of structure prediction is necessary for reproducible cheminformatics research. We introduce fragment-based coordinate generation for Open Babel, a widely accepted open source toolkit for cheminformatics. The new implementation significant improves speed and stereochemical accuracy, while retaining or improving accuracy of bond lengths, bond angles, and dihedral torsions. We first separate an input molecule into fragments by cutting at rotatable bonds. Coordinates of fragments are set according to the fragment library, which is prepared from open crystallographic databases. Since coordinates of multiple atoms are decided at once, coordinate prediction is accelerated over the previous rules-based implementation or the widely-used distance geometry methods in RDKit. This new implementation will be beneficial for a wide range of applications, including computational property prediction in polymers, molecular materials and drug design.</div>

Fast, Efficient Fragment-Based Coordinate Generation for Open Babel

<div>Rapidly predicting an accurate three dimensional geometry of a molecule is a crucial task in cheminformatics and a range of molecular modeling. Fast, accurate, and open implementation of structure prediction is necessary for reproducible cheminformatics research. We introduce fragment-based coordinate generation for Open Babel, a widely accepted open source toolkit for cheminformatics. The new implementation significant improves speed and stereochemical accuracy, while retaining or improving accuracy of bond lengths, bond angles, and dihedral torsions. We first separate an input molecule into fragments by cutting at rotatable bonds. Coordinates of fragments are set according to the fragment library, which is prepared from open crystallographic databases. Since coordinates of multiple atoms are decided at once, coordinate prediction is accelerated over the previous rules-based implementation or the widely-used distance geometry methods in RDKit. This new implementation will be beneficial for a wide range of applications, including computational property prediction in polymers, molecular materials and drug design.</div>

Toward a predictive theory of correlated materials

Correlated electron materials display a rich variety of notable properties ranging from unconventional superconductivity to metal-insulator transitions. These properties are of interest from the point of view of applications but are hard to treat theoretically, as they result from multiple competing energy scales. Although possible in more weakly correlated materials, theoretical design and spectroscopy of strongly correlated electron materials have been a difficult challenge for many years. By treating all the relevant energy scales with sufficient accuracy, complementary advances in Green’s functions and quantum Monte Carlo methods open a path to first-principles computational property predictions in this class of materials.

Strict Locality and Phonological Maps

In this article, we identify Strict Locality as a strong computational property of a certain class of phonological maps from underlying to surface forms. We show that these maps can be modeled with Input Strictly Local functions, a previously undefined class of subregular relations. These functions extend the conception of locality from the Strictly Local formal languages (recognizers/acceptors) ( McNaughton and Papert 1971 , Rogers and Pullum 2011 , Rogers et al. 2013 ) to maps (transducers/functions) and therefore formalize the notion of phonological locality. We discuss the insights such computational properties provide for phonological theory, typology, and learning.

FRACTIONAL MODELING OF HYPERBOLIC BIOHEAT TRANSFER EQUATION DURING THERMAL THERAPY

In this paper, we have developed a fractional hyperbolic bioheat transfer (FHBHT) model by applying fractional Taylor series formula to the single-phase-lag constitutive relation. A new hybrid numerical scheme that combines the multi-resolution and multi-scale computational property of Legendre wavelets based on fractional operational matrix has been used to find the numerical solution of the present problem. This study demonstrates that FHBHT model can provide a unified approach for analyzing heat transfer within living biological tissues, as standard hyperbolic bioheat transfer (SHBHT) and Pennes models are particular cases of FHBHT model. The effect of phase lag time and order of fractional derivative on temperature distribution within living biological tissues for both SHBHT and FHBHT models have been studied and shown graphically. It has been observed that thermal signal propagates more easily with larger values of order of fractional derivative within living biological tissues. The time interval for achieving temperature range of thermal treatment for different models have been studied and compared. It is least for Pennes model, highest for FHBHT model and in between them for SHBHT model. The whole analysis is presented in dimensionless form.

The Strict Locality of Phonological Processes

<p>This paper addresses the question of ‘what is a possible phonological <span>process’ from a computational perspective. Many previous studies have offered explanations </span>for why certain processes are attested and/or common while others are unattested or rare <span>(see Hume &amp; Johnson 2001, Hayes et al. 2004, Blevins 2004, among others). Following work on phonotactics by Heinz (2007, 2009, 2010), the goal of the present study is to demonstrate </span>the extent to which computational properties can distinguish the subset of what is phonologically possible from the larger set of logically possible processes. <span>Specifically, I identify a strong computational property of the mapping from underlying </span>representation (UR) to surface representation (SR) in local phonological processes. This property is called Input Strict Locality (ISL) after the well-studied Strictly Local formal languages (McNaughton &amp; Papert 1971, Rogers &amp; Pullum 2011, Rogers et al. 2013). I demonstrate <span>that this property has broad empirical coverage and describe its </span>utility in phonological learning.</p>

Learning Phonological Mappings by Learning Strictly Local Functions

<p>In this paper we identify strict locality as a defining computational property of the input-output mapping that underlies local phonological processes. We provide an automata-theoretic characterization for the class of Strictly Local functions, which are based on the well-studied Strictly Local formal languages (McNaughton &amp; Papert 1971; Rogers &amp; Pullum 2011; Rogers et al. 2013), and show how they can model a range of phonological processes. We then present a learning algorithm, the SLFLA, which uses the defining property of strict locality as an inductive principle to learn these mappings from finite data. The algorithm is a modification of an algorithm developed by Oncina et al. (1993) (called OSTIA) for learning the class of subsequential functions, of which the SL functions are a proper subset. We provide a proof that the SLFLA learns the class of SL functions and discuss these results alongside previous studies on using OSTIA to learn phonological mappings (Gildea and Jurafsky 1996).</p>