A chemical test of critical point isomorphism: reactive dissolution of ionic solids in isobutyric acid + water near the consolute point.

Binary liquid mixtures having a consolute point can be used as solvents for chemical reactions. When excess cerium(IV) oxide is brought into equilibrium with a mixture of isobutyric acid + water, and the concentration of cerium in the liquid phase is plotted in van't Hoff form, a straight line results for temperatures sufficiently in excess of the critical solution temperature. Within 1 K of the critical temperature, however, the concentration becomes substantially suppressed, and the van't Hoff slope diverges toward negative infinity.

The human functional brain network demonstrates structural and dynamical resilience to targeted attack.

In recent years, the field of network science has enabled researchers to represent the highly complex interactions in the brain in an approachable yet quantitative manner. One exciting finding since the advent of brain network research was that the brain network can withstand extensive damage, even to highly connected regions. However, these highly connected nodes may not be the most critical regions of the brain network, and it is unclear how the network dynamics are impacted by removal of these key nodes.

A genetic algorithm for controlling an agent-based model of the functional human brain.

Recently, we introduced a dynamic functional model of the human brain. This model, representing functional connectivity in the brain, is generated from subject-specific physiological data collected using functional magnetic resonance imaging (fMRI). The dynamics of this model are examined using agent-based modeling techniques, wherein a collection of binary agents are embedded as nodes in the network.

Complexity in a brain-inspired agent-based model.

An agent-based model consists of a set of agents representing the components of a system. These agents interact with each other according to rules designed with knowledge of the system in mind. Although rules control the low-level interactions of agents, these models often exhibit emergent behavior at the system level.

Development of PowerMap: a software package for statistical power calculation in neuroimaging studies.

Although there are a number of statistical software tools for voxel-based massively univariate analysis of neuroimaging data, such as fMRI (functional MRI), PET (positron emission tomography), and VBM (voxel-based morphometry), very few software tools exist for power and sample size calculation for neuroimaging studies. Unlike typical biomedical studies, outcomes from neuroimaging studies are 3D images of correlated voxels, requiring a correction for massive multiple comparisons. Thus, a specialized power calculation tool is needed for planning neuroimaging studies.

Universal fractal scaling of self-organized networks.

There is an abundance of literature on complex networks describing a variety of relationships among units in social, biological, and technological systems. Such networks, consisting of interconnected nodes, are often self-organized, naturally emerging without any overarching designs on topological structure yet enabling efficient interactions among nodes. Here we show that the number of nodes and the density of connections in such self-organized networks exhibit a power law relationship.

The ubiquity of small-world networks.

Small-world networks, according to Watts and Strogatz, are a class of networks that are "highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs." These characteristics result in networks with unique properties of regional specialization with efficient information transfer. Social networks are intuitive examples of this organization, in which cliques or clusters of friends being interconnected but each person is really only five or six people away from anyone else.

A new measure of centrality for brain networks.

Recent developments in network theory have allowed for the study of the structure and function of the human brain in terms of a network of interconnected components. Among the many nodes that form a network, some play a crucial role and are said to be central within the network structure. Central nodes may be identified via centrality metrics, with degree, betweenness, and eigenvector centrality being three of the most popular measures.

Surface-induced dissociation of small molecules, peptides, and non-covalent protein complexes.

This article provides a perspective on collisions of ions with surfaces, including surface-induced dissociation (SID) and reactive ion scattering spectrometry (RISS). The content is organized into sections on surface-induced dissociation of small ions, surface characterization of organic thin films by collision of well-characterized ions into surfaces, the use of SID to probe peptide fragmentation, and the dissociation of large non-covalent complexes by SID. Examples are given from the literature with a focus on experiments from the authors' laboratory.