Enterococcal bacteremia in a medical center

BACKGROUND: The enterococci have become important nosocomial pathogens. They can cause multiple site infections and enterococcal bacteremia becomes more frequently associated with a high mortality rate. Previous studies of enterococcal bacteremia showed a variety of results. To establish the significance and importance of enterococci as nosocomial pathogens in this hospital, to characterize their clinical pictures and to search for the risk factors for mortality, this retrospective study was performed. METHODS: There were 208 cases of enterococcal bacteremia which occurred from 1988 to 1992. Twenty-seven cases had no medical charts, dismissing possibility of evaluation. Finally, 181 cases of enterococcal bacteremia were analysed. RESULTS: One hundred and eighteen episodes were nosocomial infections. Polymicrobial bacteremia occurred in 68.5% of the patients and the most common co-isolate was Pseudomonas aeruginosa. Those patients (78.5%) with underlying diseases and malignancies were the most common underlying problems. The portal of entry could be found in 69.6 percent of patients, with the gastrointestinal tract the most common sources. Antimicrobial susceptibility testing showed high gentamicin resistance rate (89.5%), and ampicillin still had about 80 percent sensitivity rate. The group who received specific antibiotic therapy for enterococcus showed lower mortality (36.4% versus 47.6%). Only one case had infective endocarditis. Forty-nine patients suffered from septic shock, the cause of 30 deaths. Totally 75 patients died during hospitalization. Besides sepsis, another major cause of death was their underlying diseases itself. CONCLUSIONS: Enterococci have no doubt become important nosocomial pathogens and enterococcal bacteremia were associated with high mortality, especially in elderly patients with underlying diseases such as malignancy or diabetes. When clinically dealing with sepsis from the gastrointestinal or biliary tract, especially when previous cephalosporins therapy showed no response, the possibility of enterococcal bacteremia should always be considered.     

Poly(butylene terephthalate)–clay nanocomposites prepared by melt intercalation: morphology and thermomechanical properties

Nanocomposites based on poly(butylene terephthalate) (PBT) and an organoclay (Cloisite 30B) were prepared by melt blending using a twin‐screw extruder. Two kinds of PBTs, ie PBT‐A and PBT‐B, with different inherent viscosities (η_inh), were used for this study (η_inh of PBT‐A and PBT‐B were 0.74 and 1.48, respectively). Dispersion of the clay layers in the PBT nanocomposites was characterized by using X‐ray diffraction (XRD) and transmission electron microscopy (TEM). Tensile and dynamic mechanical properties and non‐isothermal crystallization temperatures of the nanocomposites were also examined. Nanocomposites based on the higher‐viscosity PBT (PBT‐B) showed a higher degree of exfoliation of the clay and a higher reinforcing effect when compared to the composites based on the lower‐viscosity PBT (PBT‐A). The clay nanolayers dispersed in PBT matrices lead to increases in the non‐isothermal crystallization temperatures of the PBTs, with such increases being more significant for the PBT‐B nanocomposites than for the PBT‐A nanoocomposites. Copyright © 2004 Society of Chemical Industry     

Holographic polymer‐dispersed liquid crystal fabrication under electric field

The transmission mode of holographic polymer‐dispersed liquid crystals (HPDLCs) was developed an under electric field. It is reported that orientation of LC molecules under an electric field induces orientation of oligomer molecules giving rise to low off‐state diffraction and small grating shrinkage. Copyright © 2005 Society of Chemical Industry     

Dye adsorption characteristics of alginate/polyaspartate hydrogels

This study examined the removal of some basic dyes, such as Methylene Blue, Malachite Green and Methyl Orange, using alginate or alginate/polyaspartate composite gel beads. The adsorption of dyes from aqueous solutions at 25 °C was examined using a batch sorption technique. The effects of CaCl₂ and the dye concentration on the adsorption were examined. Type-S adsorption isotherms were obtained, which is characteristic of a weak solute–solid interaction. The ionic interaction between the dye molecule and gel matrix appears to be responsible for the efficient adsorption of cationic dyes in this system. These results suggest that an alginate/polyaspartate gel can be used as an effective sorbent for water pollutants such as dyes, and the immobilization of these organic contaminants in the hydrogels from wastewater can solve one of the most important environmental problems in the related industry.     

Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Infinite-dimensional convex optimization in optimal and robustcontrol theory

Many engineering problems can be shown to be equivalent to solving semidefinite programs (SPs), i.e., convex optimization problems involving linear matrix inequalities (LMIs). Powerful computation tools are available for such problems in the finite-dimensional case. However, the problems arising in optimal and robust control theory are often infinite dimensional, and so adequate computation tools are not available. The key to tackling such problems with finite computation tools is to have a primal-dual formulation of the problem without duality gap. In this paper we study infinite-dimensional SPs and present a lifting technique to recast SPs as parameterized linear programs (LPs). This enables the wealth of theoretical tools available for infinite-dimensional LPs to be extended to infinite-dimensional SPs. In particular, we develop some new sufficient conditions for the lack of a duality gap for infinite-dimensional SPs and give an exact characterization of the primal and dual problems for these cases. Both primal and dual problems are formed as infinite-dimensional SP problems, with finite truncations to each giving upper and lower bounds, respectively, on the exact solution to the infinite-dimensional problem. Thus, these results can form the basis of practical computation schemes for infinite-dimensional problems, which require only finite-dimensional computation tools. To illustrate the power of these tools we apply the results to two previously unsolved optimization problems, namely minimizing the l₁ norm of a closed-loop system subject to bounds on the frequency response magnitude at a finite number of points and/or bounds on the H₂ norm     

Adaptive weighted outer-product learning associative memory

Associative-memory neural networks with adaptive weighted outer-product learning are proposed in this paper. For the correct recall of a fundamental memory (FM), a corresponding learning weight is attached and a parameter called signal-to-noise-ratio-gain (SNRG) is devised. The sufficient conditions for the learning weights and the SNRG's are derived. It is found both empirically and theoretically that the SNRG's have their own threshold values for correct recalls of the corresponding FM's. Based on the gradient-descent approach, several algorithms are constructed to adaptively find the optimal learning weights with reference to global- or local-error measure.