Pi (antitrypsin) typing methods. A comparison of acid starch-gel electrophoresis and isoelectric focusing

The Pi typing methods acid starch-gel electrophoresis (ASGE) and isoelectric focusing (IEF) have been compared by three reference laboratories: 564 samples of phenotypes Pi M, MS and MZ were tested in each of the three laboratories with a 96% agreement on initial typing. The discrepancies are recorded and reasons for disagreement discussed. IEF is a reliable method for Pi typing and gives results comparable to those obtained by ASGE.     

Sexual preference biases in counseling: An information processing approach.

Used an illusory correlation paradigm to measure the effect of stereotyping by mental health professionals on processing information about individuals identified according to sex and sexual preference (SP). 34 23–58 yr old mental health professionals (17 males and 17 females) rated themselves on an SP scale, were presented a series of cards that identified hypothetical persons according to sex and SP, and ascribed to these persons 2 randomly selected stereotypic characteristics associated with 1 of the SP groups. After studying the cards, Ss were asked to make judgments about the relationship between SP and sex and the stereotypic characteristics. Fewer errors were made on those items for which a stereotypic response was congruent with prevailing stereotypes than on those items for which the stereotypic response was incongruent, indicating that stereotyping did affect the processing of information relative to the sex and SP group. Ss had more difficulty correctly processing information attributed to gay men and lesbian women than information attributed to heterosexual men and women. (19 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A bayesian approach to real-time obstacle avoidance for a mobile robot

Real-time obstacle avoidance is essential for the safe operation of mobile robots in a dynamically changing environment. This paper investigates how an industrial mobile robot can respond to unexpected static obstacles while following a path planned by a global path planner. The obstacle avoidance problem is formulated using decision theory to determine an optimal response based on inaccurate sensor data. The optimal decision rule minimises the Bayes risk by trading between a sidestep maneuver and backtracking to follow an alternative path. Real-time implementation is emphasised here as part of a framework for real world applications. It has been successfully implemented both in simulation and in reality using a mobile robot.     

Exploiting nonacoustic sensors for speech encoding

The intelligibility of speech transmitted through low-rate coders is severely degraded when high levels of acoustic noise are present in the acoustic environment. Recent advances in nonacoustic sensors, including microwave radar, skin vibration, and bone conduction sensors, provide the exciting possibility of both glottal excitation and, more generally, vocal tract measurements that are relatively immune to acoustic disturbances and can supplement the acoustic speech waveform. We are currently investigating methods of combining the output of these sensors for use in low-rate encoding according to their capability in representing specific speech characteristics in different frequency bands. Nonacoustic sensors have the ability to reveal certain speech attributes lost in the noisy acoustic signal; for example, low-energy consonant voice bars, nasality, and glottalized excitation. By fusing nonacoustic low-frequency and pitch content with acoustic-microphone content, we have achieved significant intelligibility performance gains using the DRT across a variety of environments over the government standard 2400-bps MELPe coder. By fusing quantized high-band 4-to-8-kHz speech, requiring only an additional 116 bps, we obtain further DRT performance gains by exploiting the ear's insensitivity to fine spectral detail in this frequency region.     

The hysteresis loops of magnetic ferrites and the processes involved in their formation

It is shown that a specimen's microstructure affects the form of its magnetization curves but notM _s, the saturation magnetic moment per cm³ norH _s, the applied field strength required for saturation. A procedure is then given for the precise determination ofM _s andH _s using data derived from the hysteresis loops of polycrystalline isotropic specimens. The procedure is simple to use and avoids the laborious extrapolation requirements of the “law of approach”. Finally, the magnetization processes involved in forming the hysteresis loops betweenH _s and —H _s are described.     

A parallel processing architecture for sensor-based control of intelligent mobile robots

Parallel processing plays an important role in sensor-based control of intelligent mobile robots. This paper describes the design and implementation of a parallel processing architecture used for real-time, sensor-based control of mobile robots. This architecture takes the form of a network of sensing and control nodes, based on a novel module that we call Locally Intelligent Control Agent (LICA). It is a hybrid control architecture containing low-level feedback control loops and high-level decision making components. All the sensing, planning, and control tasks for intelligent control of a mobile robot are distributed across such a network, and operate in parallel. It has been used successfully in many experiments to perform planning and navigation tasks in real-time. Such a generic architecture can be readily applied to many diverse applications.