Parasitism and branchitis in various fish species from 4 Cook County, Illinois inland freshwater lakes, 5-year survey, 2017-2021.

We investigated disease trends of concern for fish or public health in a 5-y (2017-2021) prospective survey of fish in Cook County, IL, inland lakes. Lesions were assessed in relation to fish species, lake type and location, season and collection year, and lake water chemistry parameters. Fish included bullheads (n = 98), common carp (n = 99), bluegill (n = 114), and largemouth bass (n = 118). Annually, fish collection and point-source water sampling were conducted in spring, summer, and fall from both seepage and impoundment lakes. Examinations included autopsy, wet-mount cytologic assessment for ectoparasites, and histopathology. No lesions of public health concern were detected. The most common abnormalities were branchitis (261 of 429; 60.8%) and endoparasitism (312 of 429; 72.7%). Branchitis was mild in most cases (189 of 261; 72.4%) and concurrent with branchial parasitism in 175 of 261 (67%) cases. Monogeneans were the most common gill parasites but did not influence branchitis severity (Kruskal-Wallis, p = 0.484). Using generalized ordered logistic regression, predictors of branchitis severity included fish species (p < 0.001), the interaction of lake or location and alkalinity (p < 0.001), and water temperature or season (p < 0.001). Endoparasites included tissue larval trematodes (metacercaria), nematodes, and cestodes (plerocercoids), enteric acanthocephalans, gastric trematodes, renal myxosporidia, biliary and gall bladder myxosporidia, enteric cestodes, and tissue microsporidia. Using generalized ordered logistic regression, variables influencing endoparasitism severity included species (p < 0.001), year (p < 0.001), chloride level (p = 0.009), and the interaction of year and chloride level (p < 0.001). Our results suggested overall good health of fish in sampled Cook County inland lakes and provide a foundation for continued monitoring of ecosystem and public health in the urban environment.

Coordinating Amoebots via Reconfigurable Circuits.

We consider an extension to the geometric amoebot model that allows amoebots to form so-called circuits. Given a connected amoebot structure, a circuit is a subgraph formed by the amoebots that permits the instant transmission of signals. We show that such an extension allows for significantly faster solutions to a variety of problems related to programmable matter. More specifically, we provide algorithms for leader election, consensus, compass alignment, chirality agreement, and shape recognition. Leader election can be solved in Θ(logn) rounds, with high probability (w.h.p.), consensus in O(1) rounds, and both, compass alignment and chirality agreement, can be solved in O(logn) rounds, w.h.p. For shape recognition, the amoebots have to decide whether the amoebot structure forms a particular shape. We show that the amoebots can detect a shape composed of triangles within O(1) rounds. Finally, we show how the amoebots can detect a parallelogram with linear and polynomial side ratio within Θ(logn) rounds, w.h.p.

Universal Aging Mechanism for Static and Sliding Friction of Metallic Nanoparticles.

The term "contact aging" refers to the temporal evolution of the interface between a slider and a substrate usually resulting in increasing friction with time. Current phenomenological models for multiasperity contacts anticipate that such aging is not only the driving force behind the transition from static to sliding friction, but at the same time influences the general dynamics of the sliding friction process. To correlate static and sliding friction on the nanoscale, we show experimental evidence of stick-slip friction for nanoparticles sliding on graphite over a wide dynamic range. We can assign defined periods of aging to the stick phases of the particles, which agree with simulations explicitly including contact aging. Additional slide-hold-slide experiments for the same system allow linking the sliding friction results to static friction measurements, where both friction mechanisms can be universally described by a common aging formalism.

Influence of contact aging on nanoparticle friction kinetics.

One of the oldest concepts in tribology is stick-slip dynamics, where a disruptive sequence of stick and slip phases determine the overall resistance in sliding friction. While the mechanical energy dissipates in the sudden slip phase, the stick phase has been shown to be characterized by contact strengthening mechanisms, also termed contact aging. We present experiments of sliding nanoparticles, where friction is measured as a function of sliding velocity and interface temperature. The resulting complex interdependence is in good agreement with Monte Carlo simulations, in which the energy barrier for contact breaking increases logarithmically with time, at a rate governed by thermal activation.

Scaling laws of structural lubricity.

"Structural lubricity" refers to a unique friction state in which two flat surfaces are sliding past each other with ultralow resistance due to incommensurate atomic lattice structures. In this case, theory anticipates sublinear scaling for the area dependence of friction. Here, we experimentally confirm these predictions by measuring the sliding resistance of amorphous antimony and crystalline gold nanoparticles on crystalline graphite. For the amorphous particles a square root relation between friction and contact area is observed. For crystalline gold particles we find a more complex scaling behavior related to variations in particle shape and orientation. These results allow us to link mesoscopic friction to atomic principles.

Ageing of a microscopic sliding gold contact at low temperatures.

Nanometer-scale friction measurements on a Au(111) surface have been performed at temperatures between 30 and 300 K by means of atomic force microscopy. Stable stick slip with atomic periodicity is observed at all temperatures, showing only weak dependence on temperature between 300 and 170 K. Below 170 K, friction increases with time and a distortion of the stick-slip characteristic is observed. Low friction and periodic stick slip can be reestablished by pulling the tip out of contact and subsequently restoring the contact. A comparison with molecular dynamics simulations indicates that plastic deformation within a growing gold junction leads to the observed frictional behavior at low temperatures. The regular stick slip with atomic periodicity observed at room temperature is the result of a dynamic equilibrium shape of the contact, as microscopic wear damage is observed to heal in the sliding contact.

An optimized initialization algorithm to ensure accuracy in quantum Monte Carlo calculations.

Quantum Monte Carlo (QMC) calculations require the generation of random electronic configurations with respect to a desired probability density, usually the square of the magnitude of the wavefunction. In most cases, the Metropolis algorithm is used to generate a sequence of configurations in a Markov chain. This method has an inherent equilibration phase, during which the configurations are not representative of the desired density and must be discarded. If statistics are gathered before the walkers have equilibrated, contamination by nonequilibrated configurations can greatly reduce the accuracy of the results. Because separate Markov chains must be equilibrated for the walkers on each processor, the use of a long equilibration phase has a profoundly detrimental effect on the efficiency of large parallel calculations. The stratified atomic walker initialization (STRAW) shortens the equilibration phase of QMC calculations by generating statistically independent electronic configurations in regions of high probability density. This ensures the accuracy of calculations by avoiding contamination by nonequilibrated configurations. Shortening the length of the equilibration phase also results in significant improvements in the efficiency of parallel calculations, which reduces the total computational run time. For example, using STRAW rather than a standard initialization method in 512 processor calculations reduces the amount of time needed to calculate the energy expectation value of a trial function for a molecule of the energetic material RDX to within 0.01 au by 33%.

Manager-worker-based model for the parallelization of quantum Monte Carlo on heterogeneous and homogeneous networks.

A manager-worker-based parallelization algorithm for Quantum Monte Carlo (QMC-MW) is presented and compared with the pure iterative parallelization algorithm, which is in common use. The new manager-worker algorithm performs automatic load balancing, allowing it to perform near the theoretical maximal speed even on heterogeneous parallel computers. Furthermore, the new algorithm performs as well as the pure iterative algorithm on homogeneous parallel computers. When combined with the dynamic distributable decorrelation algorithm (DDDA) [Feldmann et al., J Comput Chem 28, 2309 (2007)], the new manager-worker algorithm allows QMC calculations to be terminated at a prespecified level of convergence rather than upon a prespecified number of steps (the common practice). This allows a guaranteed level of precision at the least cost. Additionally, we show (by both analytic derivation and experimental verification) that standard QMC implementations are not "perfectly parallel" as is often claimed.

Efficient algorithm for "on-the-fly" error analysis of local or distributed serially correlated data.

We describe the Dynamic Distributable Decorrelation Algorithm (DDDA) which efficiently calculates the true statistical error of an expectation value obtained from serially correlated data "on-the-fly," as the calculation progresses. DDDA is an improvement on the Flyvbjerg-Petersen renormalization group blocking method (Flyvberg and Peterson, J Chem Phys 1989, 91, 461). This "on-the-fly" determination of statistical quantities allows dynamic termination of Monte Carlo calculations once a specified level of convergence is attained. This is highly desirable when the required precision might take days or months to compute, but cannot be accurately estimated prior to the calculation. Furthermore, DDDA allows for a parallel implementation which requires very low communication, O(log(2)N), and can also evaluate the variance of a calculation efficiently "on-the-fly." Quantum Monte Carlo calculations are presented to illustrate "on-the-fly" variance calculations for serial and massively parallel Monte Carlo calculations.

Aminomethanol water elimination: theoretical examination.

The mechanism for the formation of hexamethylenetetraamine predicts the formation of aminomethanol from the addition of ammonia to formaldehyde. This molecule subsequently undergoes unimolecular decomposition to form methanimine and water. Aminomethanol is the predicted precursor to interstellar glycine, and is therefore of great interest for laboratory spectroscopic study, which would serve as the basis for observational searches. The height of the water loss barrier is therefore useful in the determination of an appropriate experimental approach for spectroscopic characterization of aminomethanol. We have determined the height of this barrier to be 55 kcalmol at ambient temperatures. In addition, we have determined the infinite-pressure Rice-Ramsperger-Kassel-Marcus unimolecular decomposition rate to be <10(-25) s(-1) at 300 K, indicating gas-phase kinetic stability for typical laboratory and hot core temperatures. Therefore, spectroscopic characterization of and observational searches for this molecule should be straightforward provided an efficient formation mechanism can be found.