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This article discusses how detecting defects within reinforced concrete is vital to the safety and durability of infrastructure. A non-invasive technique, ElectroMagnetic Anomaly Detection (EMAD) is used in this article to provide information into the electromagnetic properties of reinforcing steel for which data analysis is currently performed visually. The first use of two neural network approaches to automate the analysis of this data is investigated in this article. These approaches are called Echo State Networks (ESNs) and Extreme Learning Machines (ELMs) where fast and efficient training procedures allow networks to be trained and evaluated in less time than traditional neural network approaches. Data collected from real-world concrete structures are analyzed in this article using these two approaches as well as using a simple threshold measure and a standard recurrent neural network. Two ESN architectures provided the best performance for a mesh-reinforced concrete structure, while the ELM approach offers a large improvement in the performance of a single tendon-reinforced structure.

X-radiography using the bremsstrahlung of a commercial broad spectrum X-ray source was used to quantify the differences and relationships between complex samples of unknown composition. The samples examined were painted and glazed ceramic mugs. The resulting pseudo-signatures were grey-level transmission spectra which can be usefully compared over a range of acceleration potential settings from 40 to 95 kV, taken at 1 kV intervals. These data are extracted from stacks of registered field-flattened X-ray images. It is shown that it is possible to differentiate between transmission spectra of the samples by concentrating mainly on the paint layers.

In this article, we report on the application of neural networks to the problem of making an element-specific determination of unknown metal targets based on the characteristics of their transmitted X-ray signatures. Our method was applied to two groups of metal targets that we characterised as light elements (atomic numbers between 40 and 50) and heavy elements (atomic numbers between 73 and 83). In all cases their X-ray signatures were pre-processed; randomly allocated into training and testing datasets; and then presented to a self-organising map neural network in order to perform the element-specific determination. The technique was able to make a correct determination of unknown metal targets with an accuracy of 95% for the heavy elements and 99% for the light elements.

In this article element-specific mapping using a broad-spectrum laboratory based X-ray source is reported. Element-specific and element-exempt images of silver nitrate and di-hydrated barium chloride have been obtained from raw images collected either side of the K-edges for silver and barium. The informed positioning of filters between the source and sample narrowed the X-ray spectra, thereby enhancing the final images. For barium, samples with a barium area density of less than 8×10 −5 g mm −2 have been analysed. The system used here can be employed for mapping the distribution of elements from the middle of the second row transition metals to the light lanthanides.

A degassing procedure is necessary prior to taking ultrasonic measurements in aqueous kaolin suspensions as well as many other liquid based colloids. In this work we compare two degassing methods and show that subjecting a sample to a power ultrasound field is easier and less time consuming than exposing it to a vacuum. We also combine degassing and deflocculation procedures to show that air bubbles are trapped in cage-like kaolin flocs and are released when such flocs break up.

Early theories of acoustic propagation such as those by Urick, and Urick and Ament, are attractive because of their computational simplicity, but limited in application. The more complex models of Allegra and Hawley, and Harker and Temple, have since gained application. A wideband ultrasonic attenuation and phase velocity spectrometer have been used to determine the validity of these models for a range of colloidal materials. Measurements taken validate the Allegra and Hawley model for colloids with spherical base particles. The Harker and Temple model is used to infer changes in the flocculation state of kaolin slurries which result from chemical intervention.

This paper investigates the method for object fingerprinting in the context of element specific x-ray imaging. In particular, the use of spectral descriptors that are illumination invariant and viewpoint independent for pattern identification was examined in some detail. To improve generating the relevant "signature", the spectral descriptor constructed is enhanced with a differentiator which has built-in noise filtration capability and good localisation properties, thus facilitating the extraction of element specific features at a coarse-grained level. In addition to the demonstrable efficacy in identifying significant image intensity transitions that are associated with the underlying physical process of interest, the method has the distinct advantage of being conceptually simple and computationally efficient. These latter properties allow the descriptor to be further utilised by an intelligent system capable of performing a fine-grained analysis of the extracted pattern signatures. The performance of the spectral descriptor has been studied in terms of the quality of the signature vectors that it generated, quantitatively based on the established framework of Spectral Information Measure (SIM). Early results suggested that such a multiscale approach of image sequence analysis offers a considerable potential for real-time applications.

By employing a simplified technique of autocerebral hypothermic perfusion (without pump or oxygenator) the monkey brain has been cooled to intracerebral temperatures 5–8°C and rendered ischaemic for 1 h with normal recovery in the animals. The efficiency of isolated cerebral cooling was markedly enhanced with exogenous catecholamines and a cephalic ice helmet.

Cerebral viability (as evidenced by the persistence of EEG activity) has been maintained in situ for many hours by utilizing simplified extracorporeal (pump-oxygenator) perfusion systems to provide cephalo-cerebral circulation, in cardiac-arrested canine and monkey preparations. Additional studies using unicarotid mechanical perfusion and EEG monitoring demonstrated the limitations at present characterizing the pumping elements utilized in isolated cerebral perfusion.

James C. Austin and Donald A. Koch's Popular Literature in America (Bowling Green, Ohio: Bowling Green University Popular Press, 1972—$17.95/3.00) John Fischer's Six in the Easy Chair (Urbana: University of Illinois Press, 1973—$7.95) Fredric [sic] Wertham's The World of Fanzines: A Special; Form of Communication (Carbondale: Southern Illinois University Press, 1973—$10.00) Arthur Asa Berger's The Comic Stripped American (New York: Walker, 1973—$7.95) Mass Comm Review (Department of Journalism, Temple University, Philadelphia, Pa. 19122—$4.00 per year for two issues) Marvin Kimbrough's Black Magazines: An Exploratory Study (Austin: Center for Communication Research of the University of Texas, 1973—$2.00, paper) George R. Allen's The Graduate Students' Guide to Theses and Dissertations: A Practical Manual for Writing and Research (San Francisco: Jossey-Bass, 1973—$7.75)

The ultrasonic Doppler flow meter was used to measure digital blood velocity in two groups of ten male volunteers. In the experimental group, digital blood-flow velocity was measured before and after smoking one cigarette. In the control group, two digital blood-flow velocity measurements were made at the same intervals. Blood-flow velocity remained unchanged in the control group. In the experimental group the Doppler shift was reduced by 40±9% during systole, 48±10% during diastole, and the mean Doppler shift was reduced by 42±6% Since the Doppler shift is proportional to blood-flow velocity, it is concluded that smoking a single cigarette reduces mean blood-flow velocity by 42±6% ( JAMA 229:1327-1328, 1974)