A bioinventory of select terrestrial insects at Braidwood Dunes and Savanna Nature Preserve (Will County, Illinois)

We conducted an inventory of select terrestrial insect groups at Braidwood Dunes and Savanna Nature Preserve in 2011 and 2012. A total of 823 unique species, representing 19 orders of Hexapods, were recorded using a variety of sampling methods (including: light trapping, pitfall trapping, sweep net, vacuum sample, litter sample, soil core, wine rope, visual transect). Intensive studies focused on springtails (Collembola), grasshoppers, crickets and katydids (Orthoptera), true bugs (Hemiptera: Heteroptera), leafhoppers and kin (Hemiptera: Auchenorrhyncha), ground beetles (Coleoptera: Carabidae) and butterflies and macromoths (Lepidoptera). We estimate that our records comprise around 11% of the total fauna of Hexapoda that occur at this 315--‐acre site. We evaluated sampling completeness for each group and compared, richness, diversity and evenness across habitat types. Special attention was focused on midwestern remnant dependent species, conservative prairie and savanna insects of the Chicago Wilderness region, and species that appear on Illinois' list of species in greatest need of conservation. We provide the Forest Preserve District of Will County with management recommendations relating to the terrestrial for this site, as well as a large collection of images covering many of the species we encountered. Braidwood Dunes and Savanna Nature Preserve contains a variety of rare and understudied species, some of which have only infrequently been encountered. These animals play a Cover photo: Papaipema speciosissima (Noctuidae), the Osmunda Borer Moth 3 wide variety of roles within the ecosystem and various habitats, and warrant special consideration and appreciation not only by land managers but also by the members of the public with an interest in the natural world.unpublishednot peer reviewe

Searching for solar KDAR with DUNE

The observation of 236 MeV muon neutrinos from kaon-decay-at-rest (KDAR) originating in the core of the Sun would provide a unique signature of dark matter annihilation. Since excellent angle and energy reconstruction are necessary to detect this monoenergetic, directional neutrino flux, DUNE with its vast volume and reconstruction capabilities, is a promising candidate for a KDAR neutrino search. In this work, we evaluate the proposed KDAR neutrino search strategies by realistically modeling both neutrino-nucleus interactions and the response of DUNE. We find that, although reconstruction of the neutrino energy and direction is difficult with current techniques in the relevant energy range, the superb energy resolution, angular resolution, and particle identification offered by DUNE can still permit great signal/background discrimination. Moreover, there are non-standard scenarios in which searches at DUNE for KDAR in the Sun can probe dark matter interactions

Cigarettes and alcohol in relation to colorectal cancer: the Singapore Chinese Health Study

The relations were examined between colorectal cancer and cigarette smoking and alcohol consumption within the Singapore Chinese Health Study, a population-based, prospective cohort of 63 257 middle-aged and older Chinese men and women enrolled between 1993 and 1998, from whom baseline data on cigarette smoking and alcohol consumption were collected through in-person interviews. By 31 December 2004, 845 cohort participants had developed colorectal cancer (516 colon cancer, 329 rectal cancer). Compared with nondrinkers, subjects who drank seven or more alcoholic drinks per week had a statistically significant, 72% increase in risk of colorectal cancer hazard ratio (HR)=1.72; 95% confidence interval (CI)=1.33–2.22). Cigarette smoking was associated with an increased risk of rectal cancer only. Compared with nonsmokers, HRs (95% CIs) for rectal cancer were 1.43 (1.10–1.87) for light smokers and 2.64 (1.77–3.96) for heavy smokers. Our data indicate that cigarette smoking and alcohol use interact in the Chinese population in an additive manner in affecting risk of rectal cancer, thus suggesting that these two exposures may share a common etiologic pathway in rectal carcinogenesis

Push-me-pull-you: how microtubules organize the cell interior

Dynamic organization of the cell interior, which is crucial for cell function, largely depends on the microtubule cytoskeleton. Microtubules move and position organelles by pushing, pulling, or sliding. Pushing forces can be generated by microtubule polymerization, whereas pulling typically involves microtubule depolymerization or molecular motors, or both. Sliding between a microtubule and another microtubule, an organelle, or the cell cortex is also powered by molecular motors. Although numerous examples of microtubule-based pushing and pulling in living cells have been observed, it is not clear why different cell types and processes employ different mechanisms. This review introduces a classification of microtubule-based positioning strategies and discusses the efficacy of pushing and pulling. The positioning mechanisms based on microtubule pushing are efficient for movements over small distances, and for centering of organelles in symmetric geometries. Mechanisms based on pulling, on the other hand, are typically more elaborate, but are necessary when the distances to be covered by the organelles are large, and when the geometry is asymmetric and complex. Thus, taking into account cell geometry and the length scale of the movements helps to identify general principles of the intracellular layout based on microtubule forces

Finding the Cell Center by a Balance of Dynein and Myosin Pulling and Microtubule Pushing: A Computational Study

By comparing computer modeling predictions with observations, we conclude that strong dynein and weaker myosin-generated forces pull the microtubules inward competing with microtubule plus-ends pushing the microtubule aster outward and that the balance of these forces positions the centrosome at the cell center

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1 ± 0.6 % and 84.1 ± 0.6 %, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 103 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype