15 research outputs found

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Three-Dimensional Modeling and Structured Vibration Modes of Two-Stage Helical Planetary Gears Used in Cranes

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    The dynamic investigation of helical planetary gears plays an important role in structure design as the vibration and noise are perceived negatively to the transmission quality. With consideration of the axial deformations of members, the gyroscopic effects, the time-variant meshing stiffness, and the coupling amongst stages, a three-dimensional dynamic model of the two-stage helical planetary gears is established by using of the lumped-parameter method in this paper. The model is applicable to variant number of planets in two stages, different planet phasing, and spacing configurations. Numerical simulation is conducted to detect the structured vibration modes of the equally spaced systems. Furthermore, the unique properties of these vibration modes are mathematically proved. Results show that the vibration modes of the two-stage helical planetary gears can be categorized as five classes: the rigid body mode, the axial translational-rotational mode, the radical translational mode, and the 1st-stage and the 2nd-stage planet mode

    IntroVNMT: An Introspective Model for Variational Neural Machine Translation

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    We propose a novel introspective model for variational neural machine translation (IntroVNMT) in this paper, inspired by the recent successful application of introspective variational autoencoder (IntroVAE) in high quality image synthesis. Different from the vanilla variational NMT model, IntroVNMT is capable of improving itself introspectively by evaluating the quality of the generated target sentences according to the high-level latent variables of the real and generated target sentences. As a consequence of introspective training, the proposed model is able to discriminate between the generated and real sentences of the target language via the latent variables generated by the encoder of the model. In this way, IntroVNMT is able to generate more realistic target sentences in practice. In the meantime, IntroVNMT inherits the advantages of the variational autoencoders (VAEs), and the model training process is more stable than the generative adversarial network (GAN) based models. Experimental results on different translation tasks demonstrate that the proposed model can achieve significant improvements over the vanilla variational NMT model

    Wearables to Command More Access and Inclusion in a Smarter Transportation System

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    69A3351747124Visual place recognition (VPR), technology often associated with navigation of autonomous vehicles, can be critical to meeting every day urban navigation needs of people with vision disabilities. This research addresses two major obstacles to implementing VPR at scale: 1) the need for side-view place recognition, crucial for identification of sidewalk features like storefronts; and 2) privacy concerns that result from capture of street-view images during the most relevant peak commute hours, and potential tension between obfuscation and inaccuracy that must be addressed before VPR database and query construction. Using an open-source dataset consisting of more than 200,000 images captured via camera-mounted taxis over a 2km by 2km area in Manhattan, New York, over the course of one year, researchers present benchmark results of the performance of popular VPR algorithms at both of these challenges. Results indicate that side-view recognition is significantly more challenging for current VPR methods, and that data anonymization has a negligible, or even marginally beneficial effect on performance. This research contributes to the larger body of research in the following ways: \u2022 Benchmarks VPR methods using a unique large-scale dataset of over 200,000 front-view and side-view images over a full year, capturing seasonal and other environmental variation \u2022 Analyzes the causes of the significant challenges of VPR approaches using side-view images \u2022 Using pixel removal as an anonymization technique and demonstrating that this anonymization has negligible impacts to VPR algorithm performance

    Multiple pollutants stress the coastal ecosystem with climate and anthropogenic drivers

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    Coastal ecosystem health is of vital importance to human well-being. Field investigations of major pollutants along the whole coast of China were carried out to explore associations between coastal development activities and pollutant inputs. Measurements of target pollutants such as PFAAs and PAHs uncovered notable levels in small estuary rivers. The Yangtze River was identified to deliver the highest loads of these pollutants to the seas as a divide for the spatial distribution of pollutant compositions. Soil concentrations of the volatile and semi-volatile pollutants showed a cold-trapping effect in pace with increasing latitudinal gradient. The coastal ecosystem is facing high ecological risks from metal pollution, especially copper (Cu) and zinc (Zn), while priority pollutants of high risks vary for different kinds of protected species, and the ecological risks were influenced by both climate and physicochemical properties of environmental matrices, which should be emphasized to protect and restore coastal ecosystem functioning
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