Land Snail Diversity at Rocky Branch Nature Preserve, Clark County, Illinois

Terrestrial, shell-bearing gastropods were collected at Rocky Branch Nature Preserve, Clark County, Illinois. A total of three hundred nineteen specimens were collected representing five families and fifteen species. Two species of the family Endodontidae, eight species of the family Polygyridae, three species of the family Zonitidae, and one species in each of the families Pupillidae and Succineidae were collected. In addition, an attempt was made to find the relationship between species diversity and dominant woody vegetation and soil quality. The land at Rocky Branch Nature Preserve ranges from lowland flood plain to high second growth forest. The dominant trees of the lowland were maple and elm, which produce an alkaline soil with high concentrations of calcium. The dominant trees of the second growth upland forest are oak and hickory, which produce an acid soil and lower calcium concentrations. More specimens of land snails were collected (one hundred and ninety-nine) from the upland forest than from the flood plain (one hundred twenty) . There seemed to be a direct relationship between calcium and pH, but relationship of these two physical properties to organic matter is more complex. Quantitative levels of organic matter appeared meaningless without qualitative data of the tree species involved

Land Snail Diversity at Rocky Branch Nature Preserve, Clark County, Illinois

Terrestrial, shell-bearing gastropods were collected at Rocky Branch Nature Preserve, Clark County, Illinois. A total of three hundred nineteen specimens were collected representing five families and fifteen species. Two species of the family Endodontidae, eight species of the family Polygyridae, three species of the family Zonitidae, and one species in each of the families Pupillidae and Succineidae were collected. In addition, an attempt was made to find the relationship between species diversity and dominant woody vegetation and soil quality. The land at Rocky Branch Nature Preserve ranges from lowland flood plain to high second growth forest. The dominant trees of the lowland were maple and elm, which produce an alkaline soil with high concentrations of calcium. The dominant trees of the second growth upland forest are oak and hickory, which produce an acid soil and lower calcium concentrations. More specimens of land snails were collected (one hundred and ninety-nine) from the upland forest than from the flood plain (one hundred twenty) . There seemed to be a direct relationship between calcium and pH, but relationship of these two physical properties to organic matter is more complex. Quantitative levels of organic matter appeared meaningless without qualitative data of the tree species involved

Quantum adiabatic machine learning by zooming into a region of the energy surface

Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific application to Higgs boson classification. We propose QAML-Z, an algorithm that iteratively zooms in on a region of the energy surface by mapping the problem to a continuous space and sequentially applying quantum annealing to an augmented set of weak classifiers. Results on a programmable quantum annealer show that QAML-Z matches classical deep neural network performance at small training set sizes and reduces the performance margin between QAML and classical deep neural networks by almost 50% at large training set sizes, as measured by area under the receiver operating characteristic curve. The significant improvement of quantum annealing algorithms for machine learning and the use of a discrete quantum algorithm on a continuous optimization problem both opens a class of problems that can be solved by quantum annealers and suggests the approach in performance of near-term quantum machine learning towards classical benchmarks

Simple parametrization for the ground-state energy of the infinite Hubbard chain incorporating Mott physics, spin-dependent phenomena and spatial inhomogeneity

Simple analytical parametrizations for the ground-state energy of the one-dimensional repulsive Hubbard model are developed. The charge-dependence of the energy is parametrized using exact results extracted from the Bethe-Ansatz. The resulting parametrization is shown to be in better agreement with highly precise data obtained from fully numerical solution of the Bethe-Ansatz equations than previous expressions [Lima et al., Phys. Rev. Lett. 90, 146402 (2003)]. Unlike these earlier proposals, the present parametrization correctly predicts a positive Mott gap at half filling for any U>0. The construction is extended to spin-dependent phenomena by parametrizing the magnetization-dependence of the ground-state energy using further exact results and numerical benchmarking. Lastly, the parametrizations developed for the spatially uniform model are extended by means of a simple local-density-type approximation to spatially inhomogeneous models, e.g., in the presence of impurities, external fields or trapping potentials. Results are shown to be in excellent agreement with independent many-body calculations, at a fraction of the computational cost.Comment: New Journal of Physics, accepte

Strong-coupling approach to the Mott--Hubbard insulator on a Bethe lattice in Dynamical Mean-Field Theory

We calculate the Hubbard bands for the half-filled Hubbard model on a Bethe lattice with infinite coordination number up to and including third order in the inverse Hubbard interaction. We employ the Kato--Takahashi perturbation theory to solve the self-consistency equation of the Dynamical Mean-Field Theory analytically for the single-impurity Anderson model in multi-chain geometry. The weight of the secondary Hubbard sub-bands is of fourth order so that the two-chain geometry is sufficient for our study. Even close to the Mott--Hubbard transition, our results for the Mott--Hubbard gap agree very well with those from numerical Dynamical Density-Matrix Renormalization Group (DDMRG) calculations. The density of states of the lower Hubbard band also agrees very well with DDMRG data, apart from a resonance contribution at the upper band edge which cannot be reproduced in low-order perturbation theory.Comment: 40 pages, 7 figure

Increasing Collegiate Flight Training Fleet Utilization Through the Use of an Aircraft Assignment Algorithm

The operational efficiency of fleet aircraft employed for student flight training in collegiate aviation programs is strongly influenced by scheduling, among other factors. The average utilization rate for the fleet operated by the Purdue University School of Aviation and Transportation Systems was found to be 24% (Avery, 2014), and there is no data to suggest that that this rate is atypical in similar institutional programs. Mott and Bullock (2015) identified several means by which the utilization rate could be increased, and improvements in the dispatch and scheduling process were a key component of those recommendations. This article describes a scheduling algorithm that was implemented at Purdue University in the fall semester of 2015. The algorithm is a linear programming technique that incorporates optimization constraints unique to collegiate flight training operations. The resulting improvements in aircraft utilization will facilitate an increased matriculation rate of students into the flight program, thereby allowing the allocation of fixed costs over a wider user base and the reduction of overall program fees for all students. Those improvements are validated through measurement of the reduction of the cumulative turn times between aircraft operations

Ologism: Normalising Science One Lyric at a Time

Like many other countries, Australia is concerned about the public\u27s declining interest and performance in science. Many agencies and organisations, including Australia\u27s Commonwealth Scientific and Industrial Research Organisation (CSIRO), are exploring ways to engage the public in science. CSIRO Education sponsors a band called Ologism that writes and performs songs about science. Our goal was to develop a website to display the band\u27s lyrics and interpret and embellish on the science concepts they present to better engage adults aged 17–30. Through rapid prototyping we evaluated the content, design, and functionality of the website, and determined how Ologism and CSIRO Education could develop the site further to engage a larger audience more effectively

Quantum adiabatic machine learning by zooming into a region of the energy surface

Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific application to Higgs boson classification. We propose QAML-Z, an algorithm that iteratively zooms in on a region of the energy surface by mapping the problem to a continuous space and sequentially applying quantum annealing to an augmented set of weak classifiers. Results on a programmable quantum annealer show that QAML-Z matches classical deep neural network performance at small training set sizes and reduces the performance margin between QAML and classical deep neural networks by almost 50% at large training set sizes, as measured by area under the receiver operating characteristic curve. The significant improvement of quantum annealing algorithms for machine learning and the use of a discrete quantum algorithm on a continuous optimization problem both opens a class of problems that can be solved by quantum annealers and suggests the approach in performance of near-term quantum machine learning towards classical benchmarks

Mitochondrial respiration contributes to the interferon gamma response in antigen presenting cells [preprint]

The immunological synapse allows antigen presenting cells (APC) to convey a wide array of functionally distinct signals to T cells, which ultimately shape the immune response. The relative effect of stimulatory and inhibitory signals is influenced by the activation state of the APC, which is determined by an interplay between signal transduction and metabolic pathways. While toll-like receptor ligation relies on glycolytic metabolism for the proper expression of inflammatory mediators, little is known about the metabolic dependencies of other critical signals such as interferon gamma (IFNγ). Using CRISPR-Cas9, we performed a series of genome-wide knockout screens in macrophages to identify the regulators of IFNγ-inducible T cell stimulatory or inhibitory proteins MHCII, CD40, and PD-L1. Our multi-screen approach enabled us to identify novel pathways that control these functionally distinct markers. Further integration of these screening data implicated complex I of the mitochondrial respiratory chain in the expression of all three markers, and by extension the IFNγ signaling pathway. We report that the IFNγ response requires mitochondrial respiration, and APCs are unable to activate T cells upon genetic or chemical inhibition of complex I. These findings suggest a dichotomous metabolic dependency between IFNγ and toll-like receptor signaling, implicating mitochondrial function as a fulcrum of innate immunity