Impact of Reaction Conditions on MnO2 Genesis during Permanganate Oxidation

To enhance the understanding of the behavior and effects of the precipitation of MnO2 particles in the subsurface generated during in situ chemical oxidation (ISCO) using permanganate, laboratory batch experiments were completed to examine the influence that varied reaction matrix conditions have on the generation and properties of manganese oxides. The conditions examined include organic material type and concentration, permanganate concentration, pH, and the presence of calcium (as a representative divalent cation) in solution. Experimental studies included: (1) spectrophotometric examination of permanganate depletion and manganese oxides generation over time during reactions with trichloroethene; (2) scanning electron microscopy analyses of manganese particle morphology; (3) particle size distribution (filtration) characterization studies; and (4) optical particle sizing and numeration studies. Bench-scale, batch experiments were conducted to focus on fundamental chemical properties affecting particle development under varied potential environmental conditions. The amount of manganese oxides particles that develop, grow, and potentially settle as a result of permanganate ISCO of organic contaminants is a function of the particle size and concentration, the time allowed for particle development, and the impact of matrix conditions on the ability of particles to agglomerate.     

The role of perspective in the accessibility of goals during reading.

An implicit assumption of several causal reasoning models is that readers adopt the goals of a narrative's protagonist during text comprehension. In apparent violation of this assumption, readers participating in Experiment 1 of the present study drew inferences relevant to a protagonist's goal even when that goal was already satisfied from the perspective of the protagonist. In Experiments 2 and 3, participants were explicitly asked to view the text situation from the point of view of the protagonist. In this case, the goals of the reader and the protagonist should be the same. In these experiments, participants focused on the goals of the protagonist only when those goals had not been satisfied from the perspective of the protagonist. These results are discussed in terms of reader- and character-based perspectives and in terms of text characteristics that cue perspective taking. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Experience With Nocturnal Hemodialysis

In order to provide a highly efficient, long-duration form of hemodialysis, we developed nocturnal hemodialysis. Patients were dialyzed nightly at home for 8 – 10 hours, 6 – 7 nights/week. We kept the dialysate flow at 100 mL/min and the blood flow at 250 – 300 mL/min. Patients were monitored remotely from the hospital through a computer connection. An internal jugular line was used as an access. We have trained 12 patients over 30 months and have accumulated 160 patient-months worth of data. The patients tolerated the dialysis very well and slept through the night. There was a significant improvement in their sense of well-being. Nightly Kt/V was 0.99. Weekly removal of phosphate was two times as high and β ₂ -microglobulin four times as high as conventional hemodialysis. All patients have discontinued their phosphate binders and have increased their dietary phosphate and protein intake. Hypertension was controlled with fewer medications, and erythropoietin dosages decreased. Complications were infrequent and included catheter occlusion and infections. Reusing the dialyzers decreased the cost of the treatment to levels similar to continuous ambulatory peritoneal dialysis. Nocturnal hemodialysis represents a viable dialysis modality that combines high quality, low cost, and excellent tolerance.     

Contextualizing is not nullifying: Reply to Mills (2005).

In omitting crucial words and sentencees, neglecting relevant citations, and overlooking important distinctions, Jon Mills' (see record 2005-04819-001) critique of relational psychoanalysis significantly misrepresents the authors' viewpoint. This viewpoint seeks to contextualize, but not to nullify, individual worlds of experience and their limiting horizons. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

H2S optimization for lignite liquefaction

Two lignite samples, Beulah No. 3 and Big Brown No. 1, were liquefied at 420 °C using H₂ and synthesis gas to determine the optimum beneficial amount of H₂S in the batch autoclave reactor. Under the conditions employed, 50–100 psi partial pressure of H₂S, nominally 4–10 wt% of daf lignite, was optimum for both samples. Synthesis gas outperformed H₂ with and without H₂S for the liquefaction of the two coals.     

An Analysis of Scheduling Policies In Multiechelon Production Systems

Results of a simulation study of the economics of frequency of rescheduling Material Requirements Planning (MRP) systems are presented for a single-product, two-stage system in which demand is uncertain. The results indicate that for systems with moderate demand uncertainty, frequent rescheduling to maintain customer service may be uneconomical when compared with the alternative of more stable schedules in conjunction with safety stock. This result arises primarily because the cost of “emergency” production setups which occur when rescheduling is frequent exceeds the cost of safety stock required to “protect” stable schedules.     

Integration of prior knowledge of measurement noise in kernel density classification

Samples can be measured with different precisions and reliabilities in different experiments, or even within the same experiment. These varying levels of measurement noise may deteriorate the performance of a pattern recognition system, if not treated with care. Here we seek to investigate the benefit of incorporating prior knowledge about measurement noise into system construction. We propose a kernel density classifier which integrates such prior knowledge. Instead of using an identical kernel for each sample, we transform the prior knowledge into a distinct kernel for each sample. The integration procedure is straightforward and easy to interpret. In addition, we show how to estimate the diverse measurement noise levels in a real world dataset. Compared to the basic methods, the new kernel density classifier can give a significantly better classification performance. As expected, this improvement is more obvious for small sample size datasets and large number of features.