Symbolic Techniques for the Selection of Test Frequencies in Analog Fault Diagnosis

In this work symbolic methods are used for implementing a procedure for the selection of test frequencies in multifrequency parametric fault diagnosis of analog linear circuits. The proposed approach is based on the evaluation of the condition number and the norm of a sensitivity matrix of the circuit under test. This matrix is determined by exploiting the testability and ambiguity group concepts. A Test Error Index (T.E.I.) is obtained which permits to select the set of frequencies which better leads to locate parametric faults in analog linear circuits. A program implementing the proposed procedure has been realized by using symbolic techniques. Examples of application are also included.     

CW laser operation of Nd:YLF

CW laser operation of Nd:YLF is reported for the first time and, in a comparison to Nd:YAG, exhibits a lower threshold and higher single-mode average power. The TEM00mode volume of Nd: YLF was observed to be a factor of four larger than Nd:YAG, resulting in twice the TEM00mode average power. This result is attributed to the substantially lower thermal lensing of YLF with respect to YAG. In comparative measurements the stimulated emission cross section of Nd:YLF was found to be1.8 times 10^{-19}cm²for the π oscillation and1.2 times 10^{-19}cm²for the σ oscillation, as compared to2.4 times 10^{-19}cm²for Nd:YAG. The spectroscopic and lasing parameters of Nd:YLF indicate a potential for this material in high peak and average powerQ-switched applications.     

A new multi-valued neural network for the extraction of lumped models of analog circuits

A novel identification technique for lumped models of general distributed circuits (i.e. microwave transmission lines, monolithic integrated circuits and filters) is presented. The approach is based on a hybrid multi-valued neuron neural network with a modified layer and learning process, whose convergence allows the validation of the approximated lumped model. The modified layer is generated by symbolic analysis of the model under exam. The inputs of the neural network are geometrical parameters, while the outputs represent the estimation of the lumped circuit parameters.     

Chemical and structural changes in dry-cured hams (Bayonne hams) during processing and effects of the dehairing technique

Pigs of similar genetic backgrounds and feeding regimes were slaughtered in two abattoirs, one carrying out dehairing by scalding and the other by singeing. One ham from each of 80 carcasses was retained. Sixteen fresh hams (8 from each dehairing technique) were used for analysis while 64 hams were processed into dry-cured ham. Sixteen hams (8 from each dehairing technique) were taken for analysis at end of salting (day 14), end of rest (day 78), mid-processing (day 127) and end of processing (day 251). During processing, the water content of all muscles decreased while the salt content increased. The salt concentration in muscle water tended to equalize in all muscles. The nitrogen content of desalted dry matter (i.e. dry muscle tissue) decreased in both Biceps femoris and Semimembranosus. The content of every free amino acid increased with time, except for taurine and glutamine. Electrophoresis of the low ionic strength-soluble fractions showed all protein bands decreased during processing. Electrophoresis of the myofibrillar fractions indicated changes in all bands except actin (42kDa). These changes were more marked in the Semimembranosus than the Biceps femoris in the earlier processing steps. Ultrastructural changes were more marked in Semimembranosus than Biceps femoris. Hardness and chewiness increased in both muscles during the first half of processing then returned to values close to the initial ones in Semimembranosus but changed little in Biceps femoris. The scalded hams lost more weight than the singed ones during processing. The salt content was higher in scalded hams. Water-soluble nitrogen and NPN were higher in singed hams at the end of processing. The scalded hams were saltier and pungent. They had more pronounced aromas of dry ham, rancidity and hazelnut, and less aroma of fresh meat. Their texture was drier and less mellow.     

Survey of handheld computing among medical students

The purpose of this study was to identify trends in the utilization and acceptance of handheld computers (personal digital assistants) among medical students during preclinical and clinical training. We surveyed 366 medical students and collected information on computer expertise, current handheld computer use, predicted future use, and user acceptance. Handheld computers were primarily used for personal applications by students during their preclinical training and as drug references and clinical calculators during their clinical training. In the future, all participants predicted they would use handheld computers at significantly higher rates and on a broader range of medical applications. The adoption of handheld computing was independent of user satisfaction. Those with more clinical experience were less satisfied with handheld computers, suggesting that the expectations of the more experienced users were not met. The lack of institutional support was seen as a key limitation.     

Assimilating synthetic GOES-R radiances in cloudy conditions using an ensemble-based method

The weather research and forecasting (WRF) model and the maximum likelihood ensemble filter (MLEF) data assimilation approach are used to examine the potential impact of observations from the future Geostationary Operational Environmental Satellite, generation R (GOES-R) on improving our knowledge about clouds. Synthetic radiances are assimilated from the 10.35 μm channel of the GOES-R advanced baseline imager (ABI) employing a ‘non-identical twins’ experimental setup. The experimental results are examined for an extratropical cyclone named Kyrill that produced unusually strong winds, widespread damage and fatalities in Western Europe in January 2007. The data assimilation problem is especially challenging for this case, as there is a large error in the model-simulated radiances resulting from incorrect cloud location. Although this problem is difficult to eliminate, data assimilation results indicate the potential of GOES-R data to significantly reduce these errors.     

Synthetic satellite imagery for current and future environmental satellites

During the next decade, data from a new generation of US geostationary and polar orbiting satellites will become available. To prepare for these data, representative imagery of these satellites is desirable. Two independent methods have been developed to create imagery from future satellites before they are placed into orbit. One method uses data from current operational and experimental satellites. Data obtained this way are referred to as simulated imagery. Another method generates satellite imagery by using numerical models. Data obtained by this method are referred to as synthetic imagery. Each method has some weaknesses that can be overcome by using both methods together. Synthetic imagery for two future US sensors is introduced in this paper. Emphasis is placed on a severe thunderstorm event.     

Low‐Temperature Spark Plasma Sintering of Pure Nano WC Powder

For the first time we have demonstrated the densification of high‐purity nanostructured (d_avg ≈ 60 nm) tungsten carbide by High Pressure Spark Plasma Sintering (HPSPS) in the unusually low temperature range of 1200°C–1400°C. The high‐pressure sintering (i.e., 300 MPa) produced dense material at a temperature as low as 1400°C. In comparison with more conventional sintering techniques, such as SPS (80 MPa) or hot isostatic pressing, HPSPS lowered the temperature required for full densification by 400°C–500°C. High Pressure Spark Plasma Sintering, even in absence of any sintering aid or grain growth inhibitor, retained a very fine microstructure resulting in a significant improvement in both hardness (2721 HV₁₀) and fracture toughness (7.2 MPa m^1/2).