Discrete retardance second harmonic generation ellipsometry

A new instrument was constructed to perform discrete retardance nonlinear optical ellipsometry (DR-NOE). The focus of the design was to perform second harmonic generation NOE while maximizing sample and application flexibility and minimizing data acquisition time. The discrete retardance configuration results in relatively simple computational algorithms for performing nonlinear optical ellipsometric analysis. NOE analysis of a disperse red 19 monolayer yielded results that were consistent with previously reported values for the same surface system, but with significantly reduced acquisition times.     

Recasting Florida's insanity defense. Two modest proposals

Three states have established psychiatric security review boards mandated to primarily provide protection from the potentially destructive behavior of insanity acquitees. Each year in Florida there are 100 of these patients; 5% have been involved in capital offenses. These boards, as compared with the extant judiciary system, are more effective and parsimonious and serve the end of primary prevention. It is recommended that the plea, "not guilty by reason of insanity," be changed to "guilty but insane." The change is largely semantic but should result in greater prosecutorial and public acceptance of the insanity plea and be more in keeping with individual freedom for patients as provided under the Constitution.     

A sensitive method for the determination of amitriptyline and nortriptyline in human plasma

The kinetics of the male gametogenesis during the pregonadal period, prespermatogenesis, and "early" spermatogenesis has been described in detail. Concerning spermatogenesis in the adult individual reference is made to the articles of Courot, Hochereau-de Reviers and Ortavant (1970) and of Clermont (1972). The comparison of female and male gametogenesis (Fig. 1) shows that the "gonia stage" (asterisks) of the female germ cells is limited to one proliferation wave only, whereas the "gonia stage" of the male germ cells consists of a first proliferation wave, comparable to that of oogonia, a preparative phase to initiate spermatogenesis, and a second proliferation wave with renewal and differentiation of the spermatogonia. Germ cells in the "gonia stage" are highly sensitive towards ionising radiation and cytostatic drugs.     

Identifying cell-to-cell variability in internalization using flow cytometry

Biological heterogeneity is a primary contributor to the variation observed in experiments that probe dynamical processes, such as the internalization of material by cells. Given that internalization is a critical process by which many therapeutics and viruses reach their intracellular site of action, quantifying cell-to-cell variability in internalization is of high biological interest. Yet, it is common for studies of internalization to neglect cell-to-cell variability. We develop a simple mathematical model of internalization that captures the dynamical behaviour, cell-to-cell variation, and extrinsic noise introduced by flow cytometry. We calibrate our model through a novel distribution-matching approximate Bayesian computation algorithm to flow cytometry data of internalization of anti-transferrin receptor antibody in a human B-cell lymphoblastoid cell line. This approach provides information relating to the region of the parameter space, and consequentially the nature of cell-to-cell variability, that produces model realizations consistent with the experimental data. Given that our approach is agnostic to sample size and signal-to-noise ratio, our modelling framework is broadly applicable to identify biological variability in single-cell data from internalization assays and similar experiments that probe cellular dynamical processes.     

Improved cloud detection in AVHRR daytime and night-time scenes over the ocean

Accurate cloud detection is a requirement of many geophysical applications that use visible and infrared satellite data (e.g. cloud climatologies, multichannel sea surface temperature (MCSST)). Unfortunately, a significant source of residual error in such satellite-based products is undetected cloud. Here, a new, computationally efficient cloud detection procedure for both daytime and night-time Advanced Very High Resolution Radiometer (AVHRR) data is developed. It differs substantially from our prior related work. First, a new clustering procedure is used, which produces more homogeneous and distinct clusters than those produced by either our previous work or the ISODATA algorithm of Ball and Hall. Second, the input information vector is reduced in size, incorporates both radiance and spatial components and each component is normalized. These changes improve the clustering/subsequent classification, tend to decrease execution time, and simplify post-processing of the classified (cloud, clear ocean) data to remove any residual outliers. Third, the enhanced performance makes possible the use of a multipass procedure which is very effective in identifying the complex multilayer cloud structures common in satellite data. Validation with independent lidar observations confirms the accuracy of the new procedure. Marine low stratiform clouds (LSCs-fog, stratus and stratocumulus) are also detected effectively. This advance is important because LSCs are a major source of residual cloud contamination in contemporary sea surface temperature (SST) products. Finally, the method is sufficiently general that it can be adapted to other sensors (e.g. the Along-Track Scanning Radiometer (ATSR), the Moderate Resolution Imaging Spectroradiometer (MODIS)).     

16 Gbit/s all-optical demultiplexing using four-wave mixing

A novel, purely optical technique for demultiplexing high-speed time-division multiplexed data is proposed and demonstrated. The technique uses optical fibre nonlinearity induced four-wave mixing with a data signal and a probe signal located at different wavelengths. Using only semiconductor laser light sources, 1:4 demultiplexing of 20 ps long, subpicojoule, 2/sup 15/-1 RZ pulses at a data rate of 16 Gbit/s with less than 1 dB penalty is demonstrated.<>     

The impact of the Internet in banking: observations and evidence from developed and emerging markets

This paper investigates the risk, efficiency and rate of progress in the implementation of electronic commerce (e-commerce) in a sample of banks from a developed country (the US), and a sample of banks from developing and emerging markets. The results confirm that the US is very advanced in its electronic-banking (e-banking) actuation. There is evidence suggesting that e-banking is driven largely by the prospects of operating costs minimisation and operating revenue maximisation. Costs are lower and revenues higher when banking services are delivered through a branch network. The results also suggest that perceptions of banking risk may be partially driven by similar factors. Using a basic risk-scoring model, bank risk scores (reflecting a bank's ability to repay depositors) are regressed against operating efficiency measures.     

A recurrent neural network classifier for improved retrievals ofareal extent of snow cover

Accurate detection of areal extent of snow in mountainous regions is important. Areal extent of snow is a useful climatic indicator. Moreover, snow melt is a major source of water supply for many arid regions (e.g., western United States, Morocco) and affects regional ecosystems. Unfortunately, accurate satellite retrievals of areal extent of snow have been difficult to achieve. Two approaches to effectively and accurately detect clear land, cloud, and areal extent of snow in satellite data are developed. A feed-forward neural network (FFNN) is used to classify individual images, and a recurrent NN is used to classify sequences of images. The continuous outputs of the NN, combined with a linear mixing model, provide support for mixed-pixel classification. Validation with independent in situ data confirms the classification accuracy (94% for feed-forward NN, 97% for recurrent NN). The combination of rapid temporal sampling (e.g., GOES) and a recurrent NN classifier is recommended (relative to an isolated scene (e.g., AVHRR) and a feed-forward NN classifier)     

The disk loaded monopole antenna

The method of moments (MoM) is used to analyze the disk loaded monopole (DLM) antenna. Results were validated by comparison with mode-matching and wire-model methods as well as with measurements covering a wide range of electrical sizes. A quasistatic treatment is shown to be both rapid and accurate for the electrically small case. Equivalent circuits are obtained for predicting communication system performance. Parameters defining the fundamental limitations of electrically small antennas are extracted and shown to be accurate for system analysis and useful as design tools.