Quasi-Chemical and Structural Analysis of Polarizable Anion Hydration

Quasi-chemical theory is utilized to analyze the roles of solute polarization and size in determining the structure and thermodynamics of bulk anion hydration for the Hofmeister series Cl$^-$, Br$^-$, and I$^-$. Excellent agreement with experiment is obtained for whole salt hydration free energies using the polarizable AMOEBA force field. The quasi-chemical approach exactly partitions the solvation free energy into inner-shell, outer-shell packing, and outer-shell long-ranged contributions by means of a hard-sphere condition. Small conditioning radii, even well inside the first maximum of the ion-water(oxygen) radial distribution function, result in Gaussian behavior for the long-ranged contribution that dominates the ion hydration free energy. The spatial partitioning allows for a mean-field treatment of the long-ranged contribution, leading to a natural division into first-order electrostatic, induction, and van der Waals terms. The induction piece exhibits the strongest ion polarizability dependence, while the larger-magnitude first-order electrostatic piece yields an opposing but weaker polarizability dependence. In addition, a structural analysis is performed to examine the solvation anisotropy around the anions. As opposed to the hydration free energies, the solvation anisotropy depends more on ion polarizability than on ion size: increased polarizability leads to increased anisotropy. The water dipole moments near the ion are similar in magnitude to bulk water, while the ion dipole moments are found to be significantly larger than those observed in quantum mechanical studies. Possible impacts of the observed over-polarization of the ions on simulated anion surface segregation are discussed.Comment: slight revision, in press at J. Chem. Phy

Switched Linear Model Predictive Controllers for Periodic Exogenous Signals

This paper develops linear switched controllers for periodic exogenous signals using the framework of a continuous-time model predictive control. In this framework, the control signal is generated by an algorithm that uses receding horizon control principle with an on-line optimization scheme that permits inclusion of operational constraints. Unlike traditional repetitive controllers, applying this method in the form of switched linear controllers ensures rumpless transfer from one controller to another. Simulation studies are included to demonstrate the efficacy of the design with or without hard constraints

Method and apparatus for detecting the presence of an object

A method and apparatus for detecting and classifying an object, including a human intruder. The apparatus includes one or more passive thermal radiation sensors that generate a plurality of signals responsive to thermal radiation. A calculation circuit compares the plurality of signals to a threshold condition and outputs an alarm signal when the threshold condition is met, indicating the presence of the object. The method includes detecting thermal radiation from an object at a first and second wavelength and generating a first and second responsive signal. The signals are compared to a threshold condition that indicates whether the object is an intruder.Board of Regents, University of Texas Syste

“And to the Republic for Which It Stands”: Guaranteeing a Republican Form of Government

Most scholars who have addressed voter initiatives suggest only that the Guarantee Clause requires that the Supreme Court take a more active role in reviewing the constitutionality of state initiative measures. In contrast, we argue in this Essay that the Guarantee Clause establishes a per se prohibition against state initiatives. Part I of this Essay briefly examines the historical origins of the Guarantee Clause and the Founders’ apprehensions of direct democracy. Part II observes how modern state initiatives provide contemporary illustrations of the Founders’ philosophical concerns about direct democracy. Part III concludes that state initiative measures constitute per se violations of the Guarantee Clause and, accordingly, must be summarily rejected. In so concluding, this Essay rejects proposals that courts review direct legislation or certain genres of direct legislation under heightened scrutiny

Predicting host taxonomic information from viral genomes: a comparison of feature representations

The rise in metagenomics has led to an exponential growth in virus discovery. However, the majority of these new virus sequences have no assigned host. Current machine learning approaches to predicting virus host interactions have a tendency to focus on nucleotide features, ignoring other representations of genomic information. Here we investigate the predictive potential of features generated from four different ‘levels’ of viral genome representation: nucleotide, amino acid, amino acid properties and protein domains. This more fully exploits the biological information present in the virus genomes. Over a hundred and eighty binary datasets for infecting versus non-infecting viruses at all taxonomic ranks of both eukaryote and prokaryote hosts were compiled. The viral genomes were converted into the four different levels of genome representation and twenty feature sets were generated by extracting k-mer compositions and predicted protein domains. We trained and tested Support Vector Machine, SVM, classifiers to compare the predictive capacity of each of these feature sets for each dataset. Our results show that all levels of genome representation are consistently predictive of host taxonomy and that prediction k-mer composition improves with increasing k-mer length for all k-mer based features. Using a phylogenetically aware holdout method, we demonstrate that the predictive feature sets contain signals reflecting both the evolutionary relationship between the viruses infecting related hosts, and host-mimicry. Our results demonstrate that incorporating a range of complementary features, generated purely from virus genome sequences, leads to improved accuracy for a range of virus host prediction tasks enabling computational assignment of host taxonomic information

Computational optimization of synthetic water channels.

Membranes for liquid and gas separations and ion transport are critical to water purification, osmotic energy generation, fuel cells, batteries, supercapacitors, and catalysis. Often these membranes lack pore uniformity and robustness under operating conditions, which can lead to a decrease in performance. The lack of uniformity means that many pores are non-functional. Traditional membranes overcome these limitations by using thick membrane materials that impede transport and selectivity, which results in decreased performance and increased operating costs. For example, limitations in membrane performance demand high applied pressures to deionize water using reverse osmosis. In contrast, cellular membranes combine high flux and selective transport using membrane-bound protein channels operating at small pressure differences. Pore size and chemistry in the cellular channels is defined uniformly and with sub-nanometer precision through protein folding. The thickness of these cellular membranes is limited to that of the cellular membrane bilayer, about 4 nm thick, which enhances transport. Pores in the cellular membranes are robust under operating conditions in the body. Recent efforts to mimic cellular water channels for efficient water deionization produced a significant advance in membrane function. The novel biomimetic design achieved a 10-fold increase in membrane permeability to water flow compared to commercial membranes and still maintained high salt rejection. Despite this success, there is a lack of understanding about why this membrane performs so well. To address this lack of knowledge, we used highperformance computing to interrogate the structural and chemical environments experienced by water and electrolytes in the newly created biomimetic membranes. We also compared the solvation environments between the biomimetic membrane and cellular water channels. These results will help inform future efforts to optimize and tune the performance of synthetic biomimetic membranes for applications in water purification, energy, and catalysis

Drosophila EB1 is important for proper assembly, dynamics, and positioning of the mitotic spindle

EB1 is an evolutionarily conserved protein that localizes to the plus ends of growing microtubules. In yeast, the EB1 homologue (BIM1) has been shown to modulate microtubule dynamics and link microtubules to the cortex, but the functions of metazoan EB1 proteins remain unknown. Using a novel preparation of the Drosophila S2 cell line that promotes cell attachment and spreading, we visualized dynamics of single microtubules in real time and found that depletion of EB1 by RNA-mediated inhibition (RNAi) in interphase cells causes a dramatic increase in nondynamic microtubules (neither growing nor shrinking), but does not alter overall microtubule organization. In contrast, several defects in microtubule organization are observed in RNAi-treated mitotic cells, including a drastic reduction in astral microtubules, malformed mitotic spindles, defocused spindle poles, and mispositioning of spindles away from the cell center. Similar phenotypes were observed in mitotic spindles of Drosophila embryos that were microinjected with anti-EB1 antibodies. In addition, live cell imaging of mitosis in Drosophila embryos reveals defective spindle elongation and chromosomal segregation during anaphase after antibody injection. Our results reveal crucial roles for EB1 in mitosis, which we postulate involves its ability to promote the growth and interactions of microtubules within the central spindle and at the cell cortex