ComWeb: An electronic classroom for teaching computer literacy

We have developed an electronic classroom environment based on an analog/digital hybrid network, ComWeb. This environment supplements traditional methods of presentation by providing powerful communication tools between the students and the teacher directed from the instructor's workstation. The instructor can access every student's workstation at any time to monitor the student's work or to transmit information from any source. ComWeb has facilities for individual and group supervision. It can be adapted for teaching deaf or hard of hearing students in a mainstream environment. We describe the implementation of a ComWeb-based classroom at our site. The performance of students in conventional sections of a computer literacy course is compared with that in a section using ComWeb. For most of the material, performance of students in the ComWeb based section was markedly superior.     

Essential contribution of caspase 3/CPP32 to apoptosis and its associated nuclear changes

Caspases are fundamental components of the mammalian apoptotic machinery, but the precise contribution of individual caspases is controversial. CPP32 (caspase 3) is a prototypical caspase that becomes activated during apoptosis. In this study, we took a comprehensive approach to examining the role of CPP32 in apoptosis using mice, embryonic stem (ES) cells, and mouse embryonic fibroblasts (MEFs) deficient for CPP32. CPP32(ex3-/-) mice have reduced viability and, consistent with an earlier report, display defective neuronal apoptosis and neurological defects. Inactivation of CPP32 dramatically reduces apoptosis in diverse settings, including activation-induced cell death (AICD) of peripheral T cells, as well as chemotherapy-induced apoptosis of oncogenically transformed CPP32(-/-) MEFs. As well, the requirement for CPP32 can be remarkably stimulus-dependent: In ES cells, CPP32 is necessary for efficient apoptosis following UV- but not gamma-irradiation. Conversely, the same stimulus can show a tissue-specific dependence on CPP32: Hence, TNFalpha treatment induces normal levels of apoptosis in CPP32 deficient thymocytes, but defective apoptosis in oncogenically transformed MEFs. Finally, in some settings, CPP32 is required for certain apoptotic events but not others: Select CPP32(ex3-/-) cell types undergoing cell death are incapable of chromatin condensation and DNA degradation, but display other hallmarks of apoptosis. Together, these results indicate that CPP32 is an essential component in apoptotic events that is remarkably system- and stimulus-dependent. Consequently, drugs that inhibit CPP32 may preferentially disrupt specific forms of cell death.     

Measurement and prediction of pressure drop in two-phase flow

Experimental data for air–water two-phase co-current flow in two different pipe diameters were used to test the prediction of pressure drop by a number of existing theories and correlations. Several models are shown to be useful for prediction, particularly with the stratified regimes which have proved difficult to handle in the past. The model suggested by Olujic proved to be of particular value.     

Application of the recurrent multilayer perceptron in modelingcomplex process dynamics

A nonlinear dynamic model is developed for a process system, namely a heat exchanger, using the recurrent multilayer perceptron network as the underlying model structure. The perceptron is a dynamic neural network, which appears effective in the input-output modeling of complex process systems. Dynamic gradient descent learning is used to train the recurrent multilayer perceptron, resulting in an order of magnitude improvement in convergence speed over a static learning algorithm used to train the same network. In developing the empirical process model the effects of actuator, process, and sensor noise on the training and testing sets are investigated. Learning and prediction both appear very effective, despite the presence of training and testing set noise, respectively. The recurrent multilayer perceptron appears to learn the deterministic part of a stochastic training set, and it predicts approximately a moving average response of various testing sets. Extensive model validation studies with signals that are encountered in the operation of the process system modeled, that is steps and ramps, indicate that the empirical model can substantially generalize operational transients, including accurate prediction of instabilities not in the training set. However, the accuracy of the model beyond these operational transients has not been investigated. Furthermore, online learning is necessary during some transients and for tracking slowly varying process dynamics. Neural networks based empirical models in some cases appear to provide a serious alternative to first principles models.     

Evaluating Ozone as a Remedial Treatment for Removing RDX from Unsaturated Soils

Years of wastewater discharge at the Department of Energy’s Pantex Plant have contaminated the vadose zone and underlying perched aquifer with hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Because the vadose zone is acting as a continual source of groundwater contamination, removing RDX from the unsaturated zone is paramount to prevent further contamination. We determined the efficacy of ozone to degrade and mineralize RDX. Solution experiments showed that ozone (27?mg?L?1; 150?mL?min?1) was effective in mineralizing 80% of the RDX (30?mg?RDX?L?1) provided that some Pantex soil was present to buffer the solution pH. Soil columns treated with ozone produced 50% RDX mineralization within 1 day and >80% within 7 day. Experiments designed to evaluate aerobic biodegradation following partial ozonation of a RDX solution showed that ozone-generated RDX products were much more biodegradable than untreated controls in aerobic microcosms (35 versus <0.3% cumulative mineralization). These results support the use of ozone as a remedial treatment for the contaminated vadose zone at the Pantex facility.     

Impact of dams on point bar habitat: a case for the extirpation of the Sacramento Valley Tiger Beetle,C. hirticollis abrupta

Quantitative analyses of flow and stage data, remote sensing and geographic information systems analysis, and field studies were used to assess the impact of dams and diversions on the point bar habitat of the Sacramento Valley Tiger Beetle (Cicindela hirticollis abrupta). The reaches of interest include sites of known historic populations of C. h. abrupta along the Sacramento River from approximately 8 km north of Colusa southward to the confluence with the Feather River and along the Feather River between Yuba City and its confluence with the Sacramento River. The results from this study show that construction of two major dams has altered flows such that prolonged and increased flows during summer, fall, and early winter have most likely disrupted life cycles, flooded larvae, drowned overwintering adults and led to high mortality. Additionally, habitat availability has decreased over time because point bars have decreased in number and area causing increased distances between populations and isolation of populations. Moreover, point bar armouring, channel scouring, altered flows, redirected flows through weirs, and lithologic controls have produced a bimodal distribution of mean grain sizes in the Sacramento River in which the more northern bars contain gravel deposits and more southern bars possess fine sands. These conditions negatively alter moisture retention and sediment compaction and, consequently, burrowing conditions needed by this tiger beetle. Additionally, more stabilized flows (reduced variability) and increased fine‐grained deposition have enabled development and encroachment of vegetation onto the sand bars. Finally, human stresses, such as foot traffic and vehicular traffic may have interfered with burrowing, ovipositing, and foraging. The combination of these stress factors has most likely led to a reduction in source populations and, ultimately, the apparent extirpation of the entire metapopulation. Copyright © 2006 John Wiley & Sons, Ltd.     

A scheme to randomly generate surface dust points for the 3D complex variable boundary element method (CVBEM)

A scheme to randomly generate dust points on the surface of a three-dimensional (3D) object is proposed. This scheme will potentially eliminate the bias of a density of points which are approximately equally spaced on the surface, as well as eliminate possible weighting requirements for areas of higher density. This method has the potential to reduce computational effort, as fewer points might be required to define the surface area. The global trial function vector can be assigned to these dust points and then entered into the complex variable boundary element method (CVBEM) commercial code. This scheme can be applied to each piece of a system that is comprised of a connected multiple geometry. A noticeable benefit of this approach is that the same problem can be studied several times, using a new random distribution of surface points each time. The smallest error can then be determined and that run selected. The Mathematica code used to generate the scheme is attached as an appendix.