SIZING HYDRAULIC STRUCTURES IN COLD REGIONS TO BALANCE FISH PASSAGE, STREAM FUNCTION, AND OPERATION AND MAINTENANCE COST

The purpose of this research was to evaluate how characteristics of hydraulic structures, such as slope or size, used at crossings over waterways relate to operation and maintenance (O&M) effort, fish passage, and stream function. Data on O&M concerns, fish passage concerns, and crossing characteristics were collected from 45 road-stream crossings in Prudhoe Bay, Alaska, during lower and higher water periods in both 2014 and 2015 (four events total). Logistic regression and generalized mixed models were used to examine relationships between O&M effort (response) and five explanatory variables. For all data from all years combined, there were no observable associations among O&M and culvert type or constriction ratio. However, lower constriction ratios were observed for sites with O&M needs in the June 2014 data set. The proportion of sites with both fish passage and O&M concerns was 0.52; comparatively, the proportion of sites with no fish passage concern but with O&M concern was 0.35

Real Time Activity Recognition of Treadmill Usage via Machine Learning

Our objective is to provide real-time classification of treadmill usage patterns based on accelerometer and magnetometer measurements. We collected data from treadmills in the Rose-Hulman Student Recreation Center (SRC) using Shimmer3 sensor units. We identified useful data features and classifiers for predicting treadmill usage patterns. We also prototyped a proof of concept wireless, real-time classification system

Architecture representations for quantum convolutional neural networks

The Quantum Convolutional Neural Network (QCNN) is a quantum circuit model inspired by the architecture of Convolutional Neural Networks (CNNs). The success of CNNs is largely due to its ability to learn high level features from raw data rather than requiring manual feature design. Neural Architecture Search (NAS) continues this trend by learning network architecture, alleviating the need for its manual construction and have been able to generate state of the art models automatically. Search space design is a crucial step in NAS and there is currently no formal framework through which it can be achieved for QCNNs. In this work we provide such a framework by utilizing techniques from NAS to create an architectural representation for QCNNs that facilitate search space design and automatic model generation. This is done by specifying primitive operations, such as convolutions and pooling, in such a way that they can be dynamically stacked on top of each other to form different architectures. This way, QCNN search spaces can be created by controlling the sequence and hyperparameters of stacked primitives, allowing the capture of different design motifs. We show this by generating QCNNs that belong to a popular family of parametric quantum circuits, those resembling reverse binary trees. We then benchmark this family of models on a music genre classification dataset, GTZAN. Showing that alternating architecture impact model performance more than other modelling components such as choice of unitary ansatz and data encoding, resulting in a way to improve model performance without increasing its complexity. Finally we provide an open source python package that enable dynamic QCNN creation by system or hand, based off the work presented in this paper, facilitating search space design.Comment: 18 pages, 9 figure

Variation in Emission and Absorption Lines and Continuum Flux by Orbital Phase in Vela X-1

High resolution spectral studies were undertaken at orbital phases 0, 0.25 and 0.5 on the high-mass X-ray binary (HMXB) Vela X-1 using archival Chandra data. We present (a) the first detailed analysis of the multiple strong narrow emission lines present in phase 0.5 (b) an analysis of the absorption of the continuum in phase 0.5, and (c) the first detection of narrow emission and absorption lines in phase 0.25. Multiple fluorescent and H-and He-like emission lines in the band 1.6 - 20 Angstrom in eclipse are partially obscured at phase 0.25 by the X-ray continuum. The phase 0.25 spectrum displays 3 triplets, 2 with a blue-shifted resonance (r) line in absorption and the intercombination (i) and forbidden (f) lines in emission, and shows in absorption other blue-shifted lines seen in emission in eclipse. At phase 0.5 the soft X-ray continuum diminishes revealing an "eclipse-like" spectrum, however line flux values are around 13-fold those in eclipse. We conclude the narrow emission lines in Vela X-1 become apparent when the continuum is blocked from line of sight, either by eclipse or by scattering and/or absorption from a wake or cloud. The H-and He-like lines arise in warm photoionised regions in the stellar wind, while the fluorescent lines (including a Ni K alpha line) are produced in cooler clumps of gas outside these regions. Absorption of the 5-13 Angstrom continuum at phase 0.5 may be caused by an accretion wake comprised of dense stagnant photoionized plasma inside a Stromgren zone. Multiple fluorescent emission lines may be a common feature of the supergiant category of HMXBs.Comment: 29 pages, 7 figures, accepted for publication in the Astronomical Journa

The Unfolded Protein Response Is Not Necessary for the G1/S Transition, but It Is Required for Chromosome Maintenance in Saccharomyces cerevisiae

BACKGROUND: The unfolded protein response (UPR) is a eukaryotic signaling pathway, from the endoplasmic reticulum (ER) to the nucleus. Protein misfolding in the ER triggers the UPR. Accumulating evidence links the UPR in diverse aspects of cellular homeostasis. The UPR responds to the overall protein synthesis capacity and metabolic fluxes of the cell. Because the coupling of metabolism with cell division governs when cells start dividing, here we examined the role of UPR signaling in the timing of initiation of cell division and cell cycle progression, in the yeast Saccharomyces cerevisiae. METHODOLOGY/PRINCIPAL FINDINGS: We report that cells lacking the ER-resident stress sensor Ire1p, which cannot trigger the UPR, nonetheless completed the G1/S transition on time. Furthermore, loss of UPR signaling neither affected the nutrient and growth rate dependence of the G1/S transition, nor the metabolic oscillations that yeast cells display in defined steady-state conditions. Remarkably, however, loss of UPR signaling led to hypersensitivity to genotoxic stress and a ten-fold increase in chromosome loss. CONCLUSIONS/SIGNIFICANCE: Taken together, our results strongly suggest that UPR signaling is not necessary for the normal coupling of metabolism with cell division, but it has a role in genome maintenance. These results add to previous work that linked the UPR with cytokinesis in yeast. UPR signaling is conserved in all eukaryotes, and it malfunctions in a variety of diseases, including cancer. Therefore, our findings may be relevant to other systems, including humans

Subsurface scientific exploration of extraterrestrial environments (MINAR 5): analogue science, technology and education in the Boulby Mine, UK

The deep subsurface of other planetary bodies is of special interest for robotic and human exploration. The subsurface provides access to planetary interior processes, thus yielding insights into planetary formation and evolution. On Mars, the subsurface might harbour the most habitable conditions. In the context of human exploration, the subsurface can provide refugia for habitation from extreme surface conditions. We describe the fifth Mine Analogue Research (MINAR 5) programme at 1 km depth in the Boulby Mine, UK in collaboration with Spaceward Bound NASA and the Kalam Centre, India, to test instruments and methods for the robotic and human exploration of deep environments on the Moon and Mars. The geological context in Permian evaporites provides an analogue to evaporitic materials on other planetary bodies such as Mars. A wide range of sample acquisition instruments (NASA drills, Small Planetary Impulse Tool (SPLIT) robotic hammer, universal sampling bags), analytical instruments (Raman spectroscopy, Close-Up Imager, Minion DNA sequencing technology, methane stable isotope analysis, biomolecule and metabolic life detection instruments) and environmental monitoring equipment (passive air particle sampler, particle detectors and environmental monitoring equipment) was deployed in an integrated campaign. Investigations included studying the geochemical signatures of chloride and sulphate evaporitic minerals, testing methods for life detection and planetary protection around human-tended operations, and investigations on the radiation environment of the deep subsurface. The MINAR analogue activity occurs in an active mine, showing how the development of space exploration technology can be used to contribute to addressing immediate Earth-based challenges. During the campaign, in collaboration with European Space Agency (ESA), MINAR was used for astronaut familiarization with future exploration tools and techniques. The campaign was used to develop primary and secondary school and primary to secondary transition curriculum materials on-site during the campaign which was focused on a classroom extra vehicular activity simulation

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease