Imipenem resistance in clinical Escherichia coli from Qom, Iran

OBJECTIVE: The emergence of metallo-\u3b2-lactamase-producing Enterobacteriaceae is a worldwide health concern. In this study, the first evaluation of MBL genes, bla IMP and bla VIM , in Escherichia coli resistant to imipenem isolated from urine and blood specimens in Qom, Iran is described. Three hundred urine and blood specimens were analysed to detect the presence of E. coli. Resistance to imipenem and other antimicrobials was determined by disk diffusion and MIC. MBL production was screened using CDDT. PCR was also carried out to determine the presence of bla IMP and bla VIM genes in imipenem-resistant isolates. RESULTS: In total, 160 E. coli isolates were collected from March to May 2016. According to disk diffusion, high-level of resistance (20%) to cefotaxime was observed, whereas the lowest (1%) was detected for tetracycline. In addition, five isolates showed resistance to imipenem with a MIC\u2009 65\u20094 \ub5g/mL. CDDT test confirmed that five isolates were MBL-producing strains, but no bla IMP and bla VIM genes were detected. Results of this study show a very low level of resistance to imipenem in our geographical area

Large eddy simulation of cavitation inception in a high speed flow over an open cavity

Large-eddy simulation of flow over an open cavity corresponding to the experimental setup of Liu and Katz [1] is performed. The flow Reynolds number based on the cavity length and the free stream velocity is 170;000. The filtered, incompressible Navier-Stokes equations are solved using a co-located grid finite-volume solver with the dynamic Smagorinsky model for subgrid scale closure. The computational grid consists of around five million grid points with two million points clustered around the shear layer and the wall-layer over the leading edge is resolved. The only input from the experimental data is the mean velocity profile at the inlet condition. The mean flow is superimposed with turbulent velocity fluctuations generated by solving a forced periodic duct flow at free-stream Reynolds number. The flow statistics, including mean and rms velocity fields and pressure coefficients, are compared with the experimental data to show reasonable agreement. Cavitation inception is investigated using two approaches: (i) a discrete bubble model wherein the bubble dynamics is computed by solving the Rayleigh-Plesset and the bubble motion equations using an adaptive time-stepping procedure, and (ii) a scalar transport model for the liquid volume fraction with source and sink terms for phase change. The cavitation inception occurs near the trailing edge similar to that observed in the experiments. A periodic growth and decay of bubble size and liquid vapor fraction is observed above the trailing edge owing to local variations in pressure minima. The dynamic interactions between traveling vortices in the shear layer and the trailing edge affect the value and location of the pressure minima.http://deepblue.lib.umich.edu/bitstream/2027.42/84268/1/CAV2009-final73.pd

Effect of cusp size, depth and direction on stress concentration

Recently multi-axial machining technology has improved significantly. It has become a widely accepted method of manufacturing components with complex, free form surfaces. Solid billet materials with negligible internal defects are used in this process. This provides increased durability and fatigue life over equivalent cast components. However, multi-axial machining leaves cusps as machining marks. The combination of tool size and step-over generates cusps with different depths and widths. Even though the cusps add extra material on top of the nominal surface, the Finite Element Analysis simulations presented in this paper show that the maximum stress generated within the cusps can be greater than that predicted from the cusp-free geometry. These stress concentrations generated by cusps can reduce the fatigue life and durability of a machined component. In this paper a full factorial analysis of the effect of tool size, cusp width/step-over and cusp direction has been conducted. The analysis uses five different levels of tool size and cusps width and four levels of cusp direction. The results can be used to determine a tool size, cusp width and cusp direction combination with minimum spurious stress raising effect

System and Method for Detecting Cracks and their Location

A system and method are provided for detecting cracks and their location in a structure. A circuit coupled to a structure has capacitive strain sensors coupled sequentially and in parallel to one another. When excited by a variable magnetic field, the circuit has a resonant frequency that is different for unstrained and strained states. In terms of strained states, the resonant frequency is indicative of a region of the circuit that is experiencing strain induced by strain in a region of the structure in proximity to the region of the circuit. An inductor is electrically coupled to one end of each circuit. A magnetic field response recorder wirelessly transmits the variable magnetic field to the inductor and senses the resonant frequency of the circuit so-excited by the variable magnetic field

Synchronization and channel estimation in experimental M-QAM OFDM radio over fiber systems using CAZAC based training preamble

In this paper, we propose a new technique for synchronization and channel estimation in M-QAM OFDM radio over fiber (RoF) system by using constant amplitude zero auto-correlation (CAZAC) sequence based training preamble. Delay and correlate method is used to identify the training sequence in the received signal vector and to correct the symbol timing offset. For an optimum demodulation of OFDM signal, optimum down sampling offset position has to be identified before applying symbol timing algorithm. To solve this issue, we present the iterative method of finding optimum down sampling offset position. We show that the training preamble used for synchronization can also be applied to estimate the channel response using averaging technique. Moreover, we used the least square estimation based channel estimation method using pilot subcarriers and compare the results with training preamble based estimation

Mycobacterium Chimaera Infection Masquerading as a Lung Mass in a Healthcare Worker

Mycobacterium chimaera, a nontuberculous mycobacterium, is a member of the Mycobacterium avium complex (MAC). This microorganism has recently gained significant notoriety for its association with outbreaks in patients exposed to contaminated heater –cooler devices used during open heart surgeries. We report a case of Mycobacterium chimaera pulmonary infection in a healthcare worker who presented with cough, low grade fever and weight loss with evidence of a lung mass that was initially thought to be a tumor on CT scan imaging. The patient underwent partial left lung lobectomy and pathology revealed necrotizing granulomas with acid fast bacilli and a culture grew M. chimaera. The patient received combination antimycobacterial therapy according to susceptibility results for twelve months with complete resolution of his symptoms and radiographic findings. Infection Control investigation could not find a source of infection in the hospital where he worked during the last ten years. However, the patient rotated in different hospitals before coming to work at this facility and assisted in surgeries in several operating rooms where the heater-cooler devices in question were used

A hybrid lagrangian-eulerian approach for simulation of bubble dynamics

A mutiscale numerical approach is developed for the investigation of bubbly flows in turbulent environments. This consists of two different numerical approaches capable of capturing the bubble dynamics at different scales depending upon the relative size of the bubbles compared to the grid resolution: (i) fully resolved simulations (FRS) wherein the bubble dynamics and deformation are completely resolved, and (ii) subgrid, discrete bubble model where the bubbles are not resolved by the computational grid. For fully resolved simulations, a novel approach combining a particle-based, mesh-free technique with a finite-volume flow solver, is developed. The approach uses marker points around the interface and advects the signed distance to the interface in a Lagrangian frame. Interpolation kernel based derivative calculations typical of particle methods are used to extract the interface normal and curvature from unordered marker points. Unlike front-tracking methods, connectivity between the marker points is not necessary. For underresolved bubbles, a mixture-theory based Eulerian-Lagrangian approach accounting for volumetric displacements due to bubble motion and size variations is developed. The bubble dynamics is modeled by Rayleigh-Plesset equations using an adaptive timestepping scheme. A detailed verification and validation study of both approaches is performed to test the accuracy of the method on a variety of single and multiple bubble problems to show good predictive capability. Interaction of bubbles with a traveling vortex tube is simulated and compared with experimental data of Sridhar and Katz [1] to show good agreement.http://deepblue.lib.umich.edu/bitstream/2027.42/84270/1/CAV2009-final74.pd

Multisensory causal inference in the brain

At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from the same object and should be integrated and (2) for the sensations originating from the same object, how best to integrate them. Recent behavioural studies suggest that the human brain solves these problems using optimal probabilistic inference, known as Bayesian causal inference. However, how and where the underlying computations are carried out in the brain have remained unknown. By combining neuroimaging-based decoding techniques and computational modelling of behavioural data, a new study now sheds light on how multisensory causal inference maps onto specific brain areas. The results suggest that the complexity of neural computations increases along the visual hierarchy and link specific components of the causal inference process with specific visual and parietal regions