Bacteriological study of surgical site infections in a tertiary care hospital at Miraj, Maharashtra state, India

Background: Surgical site infections (SSI) are one of the common post-operative complications. Apart from bacterial contamination of wound, various patient and environment related factors play role in development and outcome of SSI. The present study is undertaken to study the frequency of SSI with reference to factors contributing to it and the antimicrobial susceptibility pattern of the causative organisms.Methods: This single-observer, cross-sectional, complete-enumeration prospective study was carried out over a period of one year. 196 pus samples from cases of surgical site infections were processed for gram staining, culture, biochemical identification tests and antimicrobial susceptibility testing. Methicillin-Resistant Staphylococcus aureus (MRSA) strains were detected by using oxacillin and cefoxitin disk diffusion and minimum inhibitory concentration (MIC) of oxacillin was tested by broth dilution technique.Results: The overall frequency of SSI was 6.17%. Most common isolates were Staphylococcus aureus, coagulase negative Staphylococci (CONS), E. coli and Pseudomonas aeruginosa. The frequency of MRSA was 8.6%. The maximum frequency was among patients operated on emergency basis in surgical department.Conclusions: The most important determinants for SSI were emergency surgery and presence of co-morbid conditions. The frequency of occurrence was age-dependent, with maximum rate of SSI in males and females in the third and sixth decades of life, respectively

Model Guided Application for Investigating Particle Number (PN) Emissions in GDI Spark Ignition Engines

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Model guided application (MGA) combining physico-chemical internal combustion engine simulation with advanced analytics offers a robust framework to develop and test particle number (PN) emissions reduction strategies. The digital engineering workflow presented in this paper integrates the &lt;i&gt;k&lt;/i&gt;inetics &amp;amp; SRM Engine Suite with parameter estimation techniques applicable to the simulation of particle formation and dynamics in gasoline direct injection (GDI) spark ignition (SI) engines. The evolution of the particle population characteristics at engine-out and through the sampling system is investigated. The particle population balance model is extended beyond soot to include sulphates and soluble organic fractions (SOF). This particle model is coupled with the gas phase chemistry precursors and is solved using a sectional method. The combustion chamber is divided into a wall zone and a bulk zone and the fuel impingement on the cylinder wall is simulated. The wall zone is responsible for resolving the distribution of equivalence ratios near the wall, a factor that is essential to account for the formation of soot in GDI SI engines. In this work, a stochastic reactor model (SRM) is calibrated to a single-cylinder test engine operated at 12 steady state load-speed operating points. First, the flame propagation model is calibrated using the experimental in-cylinder pressure profiles. Then, the population balance model parameters are calibrated based on the experimental data for particle size distributions from the same operating conditions. Good agreement was obtained for the in-cylinder pressure profiles and gas phase emissions such as NO&lt;sub&gt;x&lt;/sub&gt;. The MGA also employs a reactor network approach to align with the particle sampling measurements procedure, and the influence of dilution ratios and temperature on the PN measurement is investigated. Lastly, the MGA and the measurements procedure are applied to size-resolved chemical characterisation of the emitted particles.&lt;/div&gt;&lt;/div&gt;</jats:p

Coexistence and Phase Separation in Sheared Complex Fluids

We demonstrate how to construct dynamic phase diagrams for complex fluids that undergo transitions under flow, in which the conserved composition variable and the broken-symmetry order parameter (nematic, smectic, crystalline, etc.) are coupled to shear rate. Our construction relies on a selection criterion, the existence of a steady interface connecting two stable homogeneous states. We use the (generalized) Doi model of lyotropic nematic liquid crystals as a model system, but the method can be easily applied to other systems, provided non-local effects are included.Comment: 4 pages REVTEX, 5 figures using epsf macros. To appear in Physical Review E (Rapid Communications

Phase Separation of Rigid-Rod Suspensions in Shear Flow

We analyze the behavior of a suspension of rigid rod-like particles in shear flow using a modified version of the Doi model, and construct diagrams for phase coexistence under conditions of constant imposed stress and constant imposed strain rate, among paranematic, flow-aligning nematic, and log-rolling nematic states. We calculate the effective constitutive relations that would be measured through the regime of phase separation into shear bands. We calculate phase coexistence by examining the stability of interfacial steady states and find a wide range of possible ``phase'' behaviors.Comment: 23 pages 19 figures, revised version to be published in Physical Review

Mechanical quantum sensing in the search for dark matter

Numerous astrophysical and cosmological observations are best explained by the existence of dark matter, a mass density which interacts only very weakly with visible, baryonic matter. Searching for the extremely weak signals produced by this dark matter strongly motivate the development of new, ultra-sensitive detector technologies. Paradigmatic advances in the control and readout of massive mechanical systems, in both the classical and quantum regimes, have enabled unprecedented levels of sensitivity. In this white paper, we outline recent ideas in the potential use of a range of solid-state mechanical sensing technologies to aid in the search for dark matter in a number of energy scales and with a variety of coupling mechanisms