An analysis of shock isolation characteristics of a head of a woodpecker and its application to a bionic helmet

The effect of a woodpecker’s head structure on shock isolation was investigated from a dynamic point of view. A simplified multi-degree-of-freedom model was set up to study shock isolation characteristics of a woodpecker’s head. The shock-isolation performance of this model was calculated and analyzed by changing the dynamic parameters. And it was evaluated by two indexes: the absolute acceleration of the skull bone and the relative displacement between the skull bone and the beak. A bionic helmet model subjoining the elastic damping layer and the cushion pad was presented. Calculating the three-dimensional shock response surfaces validated it

Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance

Cellular automata (CA) is a powerful tool for modeling the evolution of macroscopic scale phenomena as it couples time, space, and variables together while remaining in a simplified form. However, such application has remained challenging in forest insect epidemics due to the highly dynamic nature of insect behavior. Recent advances in temporal trajectory-based image analysis offer an alternative way to obtain high-frequency model calibration data. In this study, we propose an insect-CA modeling framework that integrates cellular automata, remote sensing, and Geographic Information System to understand the insect ecological processes, and tested it with measured data of mountain pine beetle (MPB) in the Rocky Mountains. The overall accuracy of the predicted MPB mortality pattern in the test years ranged from 88% to 94%, which illuminates its effectiveness in modeling forest insect dynamics. We further conducted sensitivity analysis to examine responses of model performance to various parameter settings. In our case, the ensemble random forest algorithm outperforms the traditional linear regression in constructing the suitability surface. Small neighborhood size is more effective in simulating the MPB movement behavior, indicating that short-distance is the dominating dispersal mode of MPB. The introduction of a stochastic perturbation component did not improve the model performance after testing a broad range of randomness degree, reflecting a relative compact dispersal pattern rather than isolated outbreaks. We conclude that CA with remote sensing observation is useful for landscape insect movement analyses;however, consideration of several key parameters is critical in the modeling process and should be more thoroughly investigated in future work

Panoramic Annular Localizer: Tackling the Variation Challenges of Outdoor Localization Using Panoramic Annular Images and Active Deep Descriptors

Visual localization is an attractive problem that estimates the camera localization from database images based on the query image. It is a crucial task for various applications, such as autonomous vehicles, assistive navigation and augmented reality. The challenging issues of the task lie in various appearance variations between query and database images, including illumination variations, dynamic object variations and viewpoint variations. In order to tackle those challenges, Panoramic Annular Localizer into which panoramic annular lens and robust deep image descriptors are incorporated is proposed in this paper. The panoramic annular images captured by the single camera are processed and fed into the NetVLAD network to form the active deep descriptor, and sequential matching is utilized to generate the localization result. The experiments carried on the public datasets and in the field illustrate the validation of the proposed system.Comment: Accepted by ITSC 201

Editorial: Engineering probiotics for multiple interventions on intestinal diseases

No abstract available

Real-time study of rapid spread of antibiotic resistance plasmid in biofilm using microfluidics

Gene transfer in biofilms is known to play an important role in antibiotic resistance dissemination. However, the process remains poorly understood. In this study, microfluidics with time-lapse imaging was used for real-time monitoring of plasmid-mediated horizontal gene transfer (HGT) in biofilms. Pseudomonas putida KT2440 harboring an antibiotic resistance plasmid RP4 was chosen as the donor while Escherichia coli and activated sludge bacteria were used as the recipient cells. Dynamic features of the transfer process, including the transfer rate, cell growth rate and kinetic changes of the transfer frequency, were determined. It was found that the routes for gene transfer strongly depend on the structure and composition of a biofilm. While intraspecies HGT is essential to initiate a transfer event, the secondary retransfer from transconjugants to the same species is more efficient and can cause cascading gene spread in single-strain biofilms. For the activated sludge biofilm, only small and scattered colonies formed and vertical gene transfer appears to be the dominant route after initial intraspecies transfer. Furthermore, more than 46% of genera in the activated sludge were permissive to plasmid RP4, many of which are associated with human pathogens. These phenomena imply early prevention and interruptions to biofilm structure could provide an effect way to inhibit rapid antibiotic resistance gene spread and reduce the likelihood of catastrophic events associated with antibiotic resistance

Parallel, Multigrid Finite Element Simulator for Fractured/Faulted and Other Complex Reservoirs based on Common Component Architecture (CCA)

Black-oil, compositional and thermal simulators have been developed to address different physical processes in reservoir simulation. A number of different types of discretization methods have also been proposed to address issues related to representing the complex reservoir geometry. These methods are more significant for fractured reservoirs where the geometry can be particularly challenging. In this project, a general modular framework for reservoir simulation was developed, wherein the physical models were efficiently decoupled from the discretization methods. This made it possible to couple any discretization method with different physical models. Oil characterization methods are becoming increasingly sophisticated, and it is possible to construct geologically constrained models of faulted/fractured reservoirs. Discrete Fracture Network (DFN) simulation provides the option of performing multiphase calculations on spatially explicit, geologically feasible fracture sets. Multiphase DFN simulations of and sensitivity studies on a wide variety of fracture networks created using fracture creation/simulation programs was undertaken in the first part of this project. This involved creating interfaces to seamlessly convert the fracture characterization information into simulator input, grid the complex geometry, perform the simulations, and analyze and visualize results. Benchmarking and comparison with conventional simulators was also a component of this work. After demonstration of the fact that multiphase simulations can be carried out on complex fracture networks, quantitative effects of the heterogeneity of fracture properties were evaluated. Reservoirs are populated with fractures of several different scales and properties. A multiscale fracture modeling study was undertaken and the effects of heterogeneity and storage on water displacement dynamics in fractured basements were investigated. In gravity-dominated systems, more oil could be recovered at a given pore volume of injection at lower rates. However, if oil production can be continued at high water cuts, the discounted cumulative production usually favors higher production rates. The workflow developed during the project was also used to perform multiphase simulations in heterogeneous, fracture-matrix systems. Compositional and thermal-compositional simulators were developed for fractured reservoirs using the generalized framework. The thermal-compositional simulator was based on a novel 'equation-alignment' approach that helped choose the correct variables to solve depending on the number of phases present and the prescribed component partitioning. The simulators were used in steamflooding and in insitu combustion applications. The framework was constructed to be inherently parallel. The partitioning routines employed in the framework allowed generalized partitioning on highly complex fractured reservoirs and in instances when wells (incorporated in these models as line sources) were divided between two or more processors

Continuous cell sorting in a flow based on single cell resonance Raman spectra

Single cell Raman spectroscopy measures a spectral fingerprint of the biochemistry of cells, and provides a powerful method for label-free detection of living cells without the involvement of a chemical labelling strategy. However, as the intrinsic Raman signals of cells are inherently weak, there is a significant challenge in discriminating and isolating cells in a flowing stream. Here we report an integrated Raman-microfluidic system for continuous sorting of a stream of cyanobacteria, Synechocystis sp. PCC6803. These carotenoidcontaining microorganisms provide an elegant model system enabling us to determine the sorting accuracy using the subtly different resonance Raman spectra of microorganism cultured in a 12C or 13C carbon source. Central to the implementation of continuous flow sorting is the use of “pressure dividers” that eliminate fluctuations in flow in the detection region. This has enabled us to stabilise the flow profile sufficiently to allow automated operation with synchronisation of Raman acquisition, real-time classification and sorting at flow rates of ca. <100 μm/s, without the need to “trap” the cells. We demonstrate the flexibility of this approach in sorting mixed cell populations with the ability to achieve 96.3% purity of the selected cells at a speed of 0.5 Hz