Isolation of Salmonella agona (4, 12:f, g, 5:-) from commercial frozen boiled clam meat

Details are given of the morphological, biochemical and serological characteristics of a specimen of Salmonella agona isolated from a sample of frozen boiled clam meat (Villorita cyprinoides) processed in a factory at Cochin. Possible association of this serotype with human salmonellosis is considered briefly.

Texturised meat from low cost fish

A comparative study of the suitability of five species of fish, namely, threadfin bream (Nemipterous [sic] japonicus), cat fish (Tachysurus fella), ribbon fish (Trichiurus spp.), barracuda (Sphyraena jello) and jew fish (Pseudosciaena spp.) for the production of texturised meat has indicated that all these species are good source for the purpose. Protein content of the final product from all the species was higher than that prescribed for FPC type A. The product had excellent rehydration capacity and firm and elastic texture. No significant difference was observed in the rehydration capacity of the texturised meat from all the species studied. Salt concentration was found to influence the texture and salt content of 1.5 to 2% was found to result in the desirable firm and elastic texture. Rehydration capacity was not influenced to any significant extent by the salt content.

Nutritional evaluation of texturised meat from Nemipterus japonicus

Evaluation of the nutritional quality of texturised fish meat from threadfin bream (Nemipterus japonicus) is reported. Proximate composition and amino acid analysis showed that its protein content is very high with all the essential amino acids present in higher levels than those prescribed for man in the 1973 FAO/WHO amino acid scoring pattern. Lysine amounted to 11.0 g per 16 g N of which 75 percent is biologically available. Studies on PER and NPU also corroborate the excellent nutritional quality of the texturised meat.

Effect of water washing on biochemical and gel characteristics of minced meat from croaker fish (Johnius gangeticus)

Quality of analog fishery products invariably depends on the gel characteristics and nutritional status of minced meat. With an objective to find out the effect of water washing on kamaboko gel, the minced meat from Croaker fish was washed for four times (5 minutes each) using chilled water at a temperature of 8-10°C. Results reflected noticeable improvement in folding test and SSN% of kamaboko with essential decrease in fat content, water soluble proteins, expressible water and quality parameters like NPN, VBN, TMA, FFA and PV denoting superior gel quality than control sample after repeated washing. The results indicated that there was a definite improvement in functional properties such as gel forming ability, expressible water content of the croaker minced meat essential decrease in fat content, water soluble proteins, expressible water and quality parameters after each wash, but two washes of 5 minutes duration each was necessary to achieve satisfactory results.

Standardization of setting temperature and time for fish meat

Meat to water ratio used for washing was 1:3 for oil sardine and mackerel; but for pink perch and croaker, it was 1:2. Again the washing process was repeated three times for oil sardine and mackerel; but two times for pink perch and croaker. The washed meat was mixed with 2.5% NaC1 and set at +5°C and +40°C for 1, 2 and 3hrs. The gel strength and expressible water content was measured. Basing on this study, setting temperature at +40°C was selected and with respect to time 1hr for sardine and mackerel and 3hrs for pink perch and croaker was selected.

Detection of large-scale concrete columns for automated bridge inspection

There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame. This is because manually inspecting bridges is a time-consuming and costly task, and some state Departments of Transportation (DOT) cannot afford the essential costs and manpower. In this paper, a novel method that can detect large-scale bridge concrete columns is proposed for the purpose of eventually creating an automated bridge condition assessment system. The method employs image stitching techniques (feature detection and matching, image affine transformation and blending) to combine images containing different segments of one column into a single image. Following that, bridge columns are detected by locating their boundaries and classifying the material within each boundary in the stitched image. Preliminary test results of 114 concrete bridge columns stitched from 373 close-up, partial images of the columns indicate that the method can correctly detect 89.7% of these elements, and thus, the viability of the application of this research.

Large Scale Column Detection for Bridge Inspection

Manually inspecting bridges is a time-consuming and costly task. There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame as some state DOTs cannot afford the essential costs and manpower. This paper presents a novel method that can detect bridge concrete columns from visual data for the purpose of eventually creating an automated bridge condition assessment system. The method employs SIFT feature detection and matching to find overlapping areas among images. Affine transformation matrices are then calculated to combine images containing different segments of one column into a single image. Following that, the bridge columns are detected by identifying the boundaries in the stitched image and classifying the material within each boundary. Preliminary test results using real bridge images indicate that most columns in stitched images can be correctly detected and thus, the viability of the application of this research.

Machine Vision Enhanced Post-Earthquake Inspection and Rapid Loss Estimation

Manual inspection is required to determine the condition of damaged buildings after an earthquake. The lack of available inspectors, when combined with the large volume of inspection work, makes such inspection subjective and time-consuming. Completing the required inspection takes weeks to complete, which has adverse economic and societal impacts on the affected population. This paper proposes an automated framework for rapid post-earthquake building evaluation. Under the framework, the visible damage (cracks and buckling) inflicted on concrete columns is first detected. The damage properties are then measured in relation to the column's dimensions and orientation, so that the column's load bearing capacity can be approximated as a damage index. The column damage index supplemented with other building information (e.g. structural type and columns arrangement) is then used to query fragility curves of similar buildings, constructed from the analyses of existing and on-going experimental data. The query estimates the probability of the building being in different damage states. The framework is expected to automate the collection of building damage data, to provide a quantitative assessment of the building damage state, and to estimate the vulnerability of the building to collapse in the event of an aftershock. Videos and manual assessments of structures after the 2009 earthquake in Haiti are used to test the parts of the framework.

Machine Vision Enhanced Post-earthquake Inspection

Camera motion estimation is one of the most significant steps for structure-from-motion (SFM) with a monocular camera. The normalized 8-point, the 7-point, and the 5-point algorithms are normally adopted to perform the estimation, each of which has distinct performance characteristics. Given unique needs and challenges associated to civil infrastructure SFM scenarios, selection of the proper algorithm directly impacts the structure reconstruction results. In this paper, a comparison study of the aforementioned algorithms is conducted to identify the most suitable algorithm, in terms of accuracy and reliability, for reconstructing civil infrastructure. The free variables tested are baseline, depth, and motion. A concrete girder bridge was selected as the "test-bed" to reconstruct using an off-the-shelf camera capturing imagery from all possible positions that maximally the bridge's features and geometry. The feature points in the images were extracted and matched via the SURF descriptor. Finally, camera motions are estimated based on the corresponding image points by applying the aforementioned algorithms, and the results evaluated.

An analytical model for guided wave inspection optimization for prismatic structures of any cross section.

This paper presents an analytical modeling technique for the simulation of long-range ultrasonic guided waves in structures. The model may be used to predict the displacement field in a prismatic structure arising from any excitation arrangement and may therefore be used as a tool to design new inspection systems. It is computationally efficient and relatively simple to implement, yet gives accuracy similar to finite element analysis and semi-analytical finite element analysis methods. The model has many potential applications; one example is the optimization of part-circumferential arrays where access to the full circumference of the pipe is restricted. The model has been successfully validated by comparison with finite element solutions. Experimental validation has also been carried out using an array of piezoelectric transducer elements to measure the displacement field arising from a single transducer element in an 88.9-mm-diameter pipe. Good agreement has been obtained between the two models and the experimental data.