A comparative study of activity and dual sensor: activity and minute ventilation pacing responses to ascending and descending stairs

Previous studies with activity-based rate adaptive pacemakers have shown a somewhat paradoxical response when comparing ascending stairs to descending stairs. The objective of this investigation was to measure dual-sensor rate response provided by activity and minute ventilation (MV) compared with activity alone, and with a control group, during ascending and descending stairs. For dual sensor mode, measured mean peak pacing rate with 72 (92) steps per minute was 111 +/- 13 beats/min (124 +/- 14 beats/min) ascending stairs and 81 +/- 7 beats/min (97 +/- 13 beats/min) for descending. For activity mode alone, mean peak pacing rate was 90 +/- 12 beats/min (108 +/- 19 beats/min) ascending stairs and 97 +/- 12 beats/min (123 +/- 17 beats/min) descending. The mean peak control group heart rate ascending stairs for a step rate of 72 (92) steps/min were 116 +/- 11 beats/min (127 +/- 14 beats/min) ascending stairs and for descending 89 +/- 12 beats/min (95 +/- 11 beats/min). While for dual sensor controlled pacing there was a significant difference for ascending and descending stairs at both step rates, there was no difference between going upstairs and downstairs for activity mode alone. Rates with dual sensor did not significantly differ from respective rates of the control group. The mean correlation coefficient between MV and paced rate was 0.85. Pacing heart rates delivered by the dual sensor mode were appropriate for ascending and descending stairs. In contrast to activity mode alone, the peak heart rates for dual sensor mode are higher during ascending than during descending stairs.     

Application strategies for Sechura phosphate rock use on permanent pasture

At two phosphate (P) responsive sites in hill country the effectiveness of Sechura phosphate rock (SPR) as a direct application P fertilizer for permanent pasture was evaluated. Sechura was applied at two rates, in three different application strategies. The treatments were 16.7 and 50 kgP ha^–1 annually, 25 and 75 kgP ha^–1 biennially, and 50 and 150 kgP ha^–1 triennially giving a total of 50 and 150 kgP ha^–1, respectively, over three years. Single superphosphate (SSP) served as the standard P fertilizer. A comparison was also made between SPR and Chatham Rise phosphorite (CRP), another reactive PR. Total pasture and legume production and P uptake by pasture was measured with all fertilizer treatments over a three year period.In the year of application, SPR was as effective as SSP in stimulating total pasture and legume production and P uptake by pasture. This reflects the very reactive nature of this PR. In the second and third years of measurement, SPR did not show superior residual efffects to SSP. The ability of CRP to stimulate legume growth more than SPR in the second year following application demonstrates the danger of generalizing about the residual effects of reactive PR materials. Of the application strategies evaluated, a biennial appplication of 25 kgP ha^–1 as SPR maintained legume growth at a higher level than a smaller (16.7 kgP ha^–1) annual dressing. The biennial strategy also increased total pasture yield, in addition to legume production to a greater extent in the second and third years than a single (50 kgP ha^–1) triennial application.     

Hexabromocyclododecane: current understanding of chemistry, environmental fate and toxicology and implications for global management

Hexabromocyclododecane (HBCD) is a globally produced brominated flame retardant (BFR) used primarily as an additive FR in polystyrene and textile products and has been the subject of intensified research, monitoring and regulatory interest over the past decade. HBCD is currently being evaluated under the Stockholm Convention on Persistent Organic Pollutants. HBCD is hydrophobic (i.e., has low water solubility) and thus partitions to organic phases in the aquatic environment (e.g., lipids, suspended solids). It is ubiquitous in the global environment with monitoring data generally exhibiting the expected relationship between proximity to known sources and levels; however, temporal trends are not consistent. Estimated degradation half-lives, together with data in abiotic compartments and long-range transport potential indicate HBCD may be sufficiently persistent and distributed to be of global concern. The detection of HBCD in biota in the Arctic and in source regions and available bioaccumulation data also support the case for regulatory scrutiny. Toxicity testing has detected reproductive, developmental and behavioral effects in animals where exposures are sufficient. Recent toxicological advances include a better mechanistic understanding of how HBCD can interfere with the hypothalamic-pituitary-thyroid axis, affect normal development, and impact the central nervous system; however, levels in biota in remote locations are below known effects thresholds. For many regulatory criteria, there are substantial uncertainties that reduce confidence in evaluations and thereby confound management decision-making based on currently available information.     

Electrical conductivity modeling of carbon black/polycarbonate,carbon nanotube/polycarbonate,and exfoliated graphite nanoplatelet/polycarbonate composites

Adding conductive carbon fillers to electrically insulating thermoplastic polymers increases the resulting composite's electrical conductivity, which would enable them to be used in electrostatic dissipative and semiconductive applications. In this study, varying amounts of carbon black (CB: 2 to 10 wt %), multiwalled carbon nanotubes (CNT: 0.5 to 8 wt %), or exfoliated graphite nanoplatelets (GNP: 2 to 15 wt %) were added to polycarbonate (PC) and the resulting composites were tested for electrical conductivity (EC = 1/electrical resistivity). The percolation threshold was ～ 1.2 vol % CNT, ～ 2.4 vol % CB, and ～ 4.6 vol % GNP. In addition, three EC models (Mamunya, additive, and general effective media) were developed for the CB/PC, CNT/PC, and GNP/PC composites. The general effective media (GEM) model showed the best agreement with the experimental results over the entire range of filler concentrations (above and below the percolation threshold) for all three composite systems. In addition, the GEM model can be easily adapted for composites containing combinations of different conductive fillers. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Identification of microglial signal transduction pathways mediating a neurotoxic response to amyloidogenic fragments of beta-amyloid and prion proteins

Microglial interaction with amyloid fibrils in the brains of Alzheimer's and prion disease patients results in the inflammatory activation of these cells. We observed that primary microglial cultures and the THP-1 monocytic cell line are stimulated by fibrillar beta-amyloid and prion peptides to activate identical tyrosine kinase-dependent inflammatory signal transduction cascades. The tyrosine kinases Lyn and Syk are activated by the fibrillar peptides and initiate a signaling cascade resulting in a transient release of intracellular calcium that results in the activation of classical PKC and the recently described calcium-sensitive tyrosine kinase PYK2. Activation of the MAP kinases ERK1 and ERK2 follows as a subsequent downstream signaling event. We demonstrate that PYK2 is positioned downstream of Lyn, Syk, and PKC. PKC is a necessary intermediate required for ERK activation. Importantly, the signaling response elicited by beta-amyloid and prion fibrils leads to the production of neurotoxic products. We have demonstrated in a tissue culture model that conditioned media from beta-amyloid- and prion-stimulated microglia or from THP-1 monocytes are neurotoxic to mouse cortical neurons. This toxicity can be ameliorated by treating THP-1 cells with specific enzyme inhibitors that target various components of the signal transduction pathway linked to the inflammatory responses.     

Creep behavior comparison of CMW1 and palacos R-40 clinical bone cements

The restrained dynamic creep behaviors of two clinical bone cements, Palacos R-40 and CMW1 have been investigated at room temperature and body temperature. It was found that the two cements demonstrated significantly different creep deformations, with Palacos R-40 bone cement demonstrating higher creep strain than CMW1 bone cement at each loading cycle. For both cements, two stages of creep were identified with a higher creep rate during early cycling followed by a steady-state creep rate. The test temperature had a strong effect on the creep performance of the bone cements with higher creep rate observed at body temperature. The relationship between creep deformation and loading cycles can be expressed by single logarithmic model. The SEM examinations revealed that CMW1 bone cement is more sensitive to defects within the specimen especially to the defects at the edges of the specimen than Palacos R-40 bone cement. However, in the absence of micro-cracks or defects within the inner surface layer, the dynamic loading (at less than 10.6 MPa) is unlikely to produce micro-cracks in the CMW1 bone cement. The different behaviors between the two bone cements may be attributed to differences in chemical compositions and molecular weight distributions.     

Prioritizing JUnit Test Cases: An Empirical Assessment and Cost-Benefits Analysis

Test case prioritization provides a way to run test cases with the highest priority earliest. Numerous empirical studies have shown that prioritization can improve a test suite's rate of fault detection, but the extent to which these results generalize is an open question because the studies have all focused on a single procedural language, C, and a few specific types of test suites. In particular, Java and the JUnit testing framework are being used extensively to build software systems in practice, and the effectiveness of prioritization techniques on Java systems tested under JUnit has not been investigated. We have therefore designed and performed a controlled experiment examining whether test case prioritization can be effective on Java programs tested under JUnit, and comparing the results to those achieved in earlier studies. Our analyses show that test case prioritization can significantly improve the rate of fault detection of JUnit test suites, but also reveal differences with respect to previous studies that can be related to the language and testing paradigm. To investigate the practical implications of these results, we present a set of cost-benefits models for test case prioritization, and show how the effectiveness differences observed can result in savings in practice, but vary substantially with the cost factors associated with particular testing processes.     

A Preliminary Study of the Toxicological Properties of Selected Polymer–Ferrocene Conjugates

Prompted by early observations of the cytotoxic and antineoplastic properties of certain ferrocene and ferricenium derivatives, efforts in this laboratory were focused on the synthesis of carrier-bound ferrocene compounds. Subsequent cell culture tests carried out with selected conjugates obtained in that program showed these polymers to be highly active antiproliferative agents. In the present project toxicological work has been performed in vivo on several ferrocene conjugates in an effort to assess their toxic effects in experimental animals (CD-1 mice). The conjugates, all based on an ,-DL-polyaspartamide backbone structure, comprise the ferrocene drug model as a terminal on short side chains containing biofissionable amide or ester links for intracellular drug release. The polymers, dissolved in phosphate-buffered saline, have been injected in predetermined concentrations into the vein of the mice, and the maximum tolerated dose (MTD) levels have been determined, the latter referring to the highest dose levels administered that would allow long-term survival of the test animals. For the five conjugates tested, MTD levels range from about 3 to 30 mg Fe/kg or 0.05–0.66 mmol Fe/kg. Compared on a molar metal-to-metal basis with similarly structured platinum conjugates tested previously (MTD, 0.14–2.66 mmol Pt/kg), these values are indicative of comparatively high toxicity of the ferrocene polymers. Some implications of these findings are discussed.     

Artificial neural networks for the automated detection of trichloroethylene by passive Fourier transform infrared spectrometry

Artificial neural networks are applied to the automated classification of trichloroethylene (TCE) signatures from passive Fourier transform infrared remote sensing interferogram data. Through the use of three data collection methods, a combination of laboratory and field data is acquired that allows the methodology to be evaluated under a variety of infrared background conditions and in the presence of potentially interfering compounds such as sulfur hexafluoride, methyl ethyl ketone, acetone, carbon tetrachloride, and ammonia. To maximize the computational efficiency of the network optimization, experimental design techniques are employed to develop a training protocol for the network that takes into account the relationships among five variables that are related either to the network architecture or to the training process. This protocol is implemented for the case of a back-propagation neural network (BNN) and is used to develop an optimized network for the detection of TCE. The classification performance of the network is assessed by comparing both TCE detection capabilities and false detection rates to similar classification results obtained with the technique of piecewise linear discriminant analysis (PLDA). When applied to prediction data withheld from the optimization of both the BNN and PLDA algorithms, the BNN method is observed to outperform PLDA overall, with TCE detection rates in excess of 99% and false detection rates less than 0.5%.     

Calibration transfer algorithm for automated qualitative analysis by passive Fourier transform infrared spectrometry

The automated qualitative analysis of passive Fourier transform infrared (FT-IR) remote sensing data is made difficult by the presence in the data of background and instrument-specific variation. For data collected with a single instrument, variation in the data arises from changes in the infrared background radiance, changes in the atmospheric composition within the field-of-view of the spectrometer, and changes in the instrument response function arising from temperature variation in the spectrometer. When more than one spectrometer is used, the variation in detector responses and phase signatures between instruments serves to complicate further the task of implementing an automated processing algorithm for detecting the signature of a target compound. In this work, a combination of signal processing and pattern recognition methodology is applied directly to the interferogram data collected by the FT-IR spectrometer to implement an automated compound detection procedure that is independent of background and instrument-specific variation. The key to this algorithm is the use of highly attenuating digital filters to isolate in the interferogram the frequencies associated with an analyte absorption or emission band while suppressing information at other frequencies. For the test compounds, acetone and sulfur hexafluoride, it is demonstrated that when this digital filtering procedure is coupled with either piecewise linear discriminant analysis or a back-propagation neural network, an automated detection algorithm can be developed with data from a primary instrument and then subsequently used to predict the presence of analyte signatures in data collected with a secondary spectrometer. Correct classification rates in excess of 92% are obtained for both compounds when the algorithm is applied to data collected with the secondary instrument.