1,325 research outputs found

    Taking Tasers Seriously: The Need for Better Regulation of Stun Guns in New York

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    This report analyzes 851 Taser incident reports from eight police departments across the state as well as 10 departments' policies and guidelines for using the weapons, which deliver up to 50,000 volts of electricity and have caused the deaths of more than a dozen New Yorkers in recent years. The report concludes that police officers throughout New York State are consistently misusing and overusing Tasers

    Adaptive Inner-Loop Rover Control

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    Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design

    Counting Photobleach Steps and the Dynamics of Bacterial Predators

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    poster abstractPhotobleach (PB) counting is used to enumerate proteins by monitoring how the light intensity in some regions decreases by quanta as individual fluorophores photobleach. While it is straightforward in theory, PB counting is often difficult because fluorescence traces are noisy. In this work, we quantify the sources of noise that arise during photobleach counting to construct a principled likelihood function of observing the data given a model. Noise in the signal could arise from background fluorescence, variable fluorophore emission, and fluorophore blinking. In addition, in a completely different direction, we explore the role of hydrodynamic interactions on the dynamics of bacterial predators. Our study shows that Bdellovibrio (BV) - a model predatory bacterium - is susceptible to self-generated hydrodynamic forces. Near surfaces and defects, these hydrodynamic interactions co-localize BV with its prey, and this may enhance BV’s hunting efficiency

    Obliquity-driven expansion of North Atlantic sea ice during the last glacial

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    Author Posting. © American Geophysical Union, 2015. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 42 (2015): 10,382–10,390, doi:10.1002/2015GL066344.North Atlantic late Pleistocene climate (60,000 to 11,650 years ago) was characterized by abrupt and extreme millennial duration oscillations known as Dansgaard-Oeschger (D-O) events. However, during the Last Glacial Maximum (LGM) 23,000 to 19,000 cal years ago (23 to 19 ka), no D-O events are observed in the Greenland ice cores. Our new analysis of the Greenland δ18O record reveals a switch in the stability of the climate system around 30 ka, suggesting that a critical threshold was passed. Climate system modeling suggests that low axial obliquity at this time caused vastly expanded sea ice in the Labrador Sea, shifting Northern Hemisphere westerly winds south and reducing the strength of meridional overturning circulation. The results suggest that these feedbacks tipped the climate system into full glacial conditions, leading to maximum continental ice growth during the LGM.Australian Research Council2016-06-1

    Computational design of syntheses leading to compound libraries or isotopically labelled targets

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    Although computer programs for retrosynthetic planning have shown improved and in some cases quite satisfactory performance in designing routes leading to specific, individual targets, no algorithms capable of planning syntheses of entire target libraries - important in modern drug discovery - have yet been reported. This study describes how network-search routines underlying existing retrosynthetic programs can be adapted and extended to multi-target design operating on one common search graph, benefitting from the use of common intermediates and reducing the overall synthetic cost. Implementation in the Chematica platform illustrates the usefulness of such algorithms in the syntheses of either (i) all members of a user-defined library, or (ii) the most synthetically accessible members of this library. In the latter case, algorithms are also readily adapted to the identification of the most facile syntheses of isotopically labelled targets. These examples are industrially relevant in the context of hitto-lead optimization and syntheses of isotopomers of various bioactive molecules

    Rethinking Cost-sensitive Classification in Deep Learning via Adversarial Data Augmentation

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    Cost-sensitive classification is critical in applications where misclassification errors widely vary in cost. However, over-parameterization poses fundamental challenges to the cost-sensitive modeling of deep neural networks (DNNs). The ability of a DNN to fully interpolate a training dataset can render a DNN, evaluated purely on the training set, ineffective in distinguishing a cost-sensitive solution from its overall accuracy maximization counterpart. This necessitates rethinking cost-sensitive classification in DNNs. To address this challenge, this paper proposes a cost-sensitive adversarial data augmentation (CSADA) framework to make over-parameterized models cost-sensitive. The overarching idea is to generate targeted adversarial examples that push the decision boundary in cost-aware directions. These targeted adversarial samples are generated by maximizing the probability of critical misclassifications and used to train a model with more conservative decisions on costly pairs. Experiments on well-known datasets and a pharmacy medication image (PMI) dataset made publicly available show that our method can effectively minimize the overall cost and reduce critical errors, while achieving comparable performance in terms of overall accuracy

    Associations of combined physical activity and body mass index groups with colorectal cancer survival outcomes

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    BACKGROUND: Physical activity and BMI have been individually associated with cancer survivorship but have not yet been studied in combinations in colorectal cancer patients. Here, we investigate individual and combined associations of physical activity and BMI groups with colorectal cancer survival outcomes. METHODS: Self-reported physical activity levels (MET hrs/wk) were assessed using an adapted version of the International Physical Activity Questionnaire (IPAQ) at baseline in 931 patients with stage I-III colorectal cancer and classified into \u27highly active\u27 and\u27not-highly active\u27(≥ / \u3c 18 MET hrs/wk). BMI (kg/m RESULTS: \u27Not-highly active\u27 compared to \u27highly active\u27 and \u27overweight\u27/ \u27obese\u27 compared to \u27normal weight\u27 patients had a 40-50% increased risk of death or recurrence (HR: 1.41 (95% CI: 0.99-2.06), p = 0.03; HR: 1.49 (95% CI: 1.02-2.21) and HR: 1.51 (95% CI: 1.02-2.26), p = 0.04, respectively). \u27Not-highly active\u27 patients had worse disease-free survival outcomes, regardless of their BMI, compared to \u27highly active/normal weight\u27 patients. \u27Not-highly active/obese\u27 patients had a 3.66 times increased risk of death or recurrence compared to \u27highly active/normal weight\u27 patients (HR: 4.66 (95% CI: 1.75-9.10), p = 0.002). Lower activity thresholds yielded smaller effect sizes. CONCLUSION: Physical activity and BMI were individually associated with disease-free survival among colorectal cancer patients. Physical activity seems to improve survival outcomes in patients regardless of their BMI

    A fully coupled hydro-mechanical model for the modeling of coalbed methane recovery

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    Most coal seams hold important quantities of methane which is recognized as a valuable energy resource. Coal reservoir is considered not conventional because methane is held adsorbed on the coal surface. Coal is naturally fractured, it is a dual-porosity system made of matrix blocks and cleats (i.e fractures). In general, cleats are initially water saturated with the hydrostatic pressure maintaining the gas adsorbed in the coal matrix. Production of coalbed methane (CBM) first requires the mobilization of water in the cleats to reduce the reservoir pressure. Changes of coal properties during methane production are a critical issue in coalbed methane recovery. Indeed, any change of the cleat network will likely translate into modifications of the reservoir permeability. This work consists in the formulation of a consistent hydro-mechanical model for the CBM production modeling. Due to the particular structure of coal, the model is based on a dual-continuum approach to enrich the macroscale with microscale considerations. Shape factors are employed to take into account the geometry of the matrix blocks in the mass exchange between matrix and fractures. The hydro-mechanical model is fully coupled. For example, it captures the sorption-induced volumetric strain or the dependence of permeability on fracture aperture, which evolves with the stress state. The model is implemented in the finite element code Lagamine and is used for the modeling of one production well. A synthetic reservoir and then a real production case are considered. To date, attention has focused on a series of parametric analyses that can highlight the influence of the production scenario or key parameters related to the reservoir
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