Shrimp processing residue as an alternative ingredient for new product development

Shrimp residues were dried (65 °C), grounded, and posteriorly used as an ingredient to the production of ‘spiced shrimp flour’ and ‘shrimp flavoured biscuits’. Both products were packed in modified atmosphere (100% N₂) and stored for 180 days (25 °C) for shelf life evaluation. The centesimal composition, physicochemical, microbiological and sensory analyses were carried out in triplicate. The microbiological analysis (residue and shrimp flour) was within the limits of the legislation, confirming the hygienic–sanitary care during processing. The protein content was the most outstanding (40.13% for the spiced shrimp flour and 20.52% for the shrimp flavoured biscuits). The microbiological evaluation for the ‘spiced shrimp flour’ and ‘shrimp flavoured biscuits’ was below the legal limit, and both products were accepted by sensory analysis. The shelf life evaluation demonstrated stability for 6 months. Thus, we concluded that the Litopenaeus vannamei shrimp residue is a promising ingredient in the food industry.     

Analysis of sustainable materials used in ecovillages: Review of progress in BedZED and Masdar city

This paper explores reclaimed and recycled material used in ecovillages. The models discussed in this paper include BedZED in the United Kingdom and Masdar City in the Middle East. These two communities contain features characterized by the sustainable principles of the ecovillage concept by using non-traditional building materials. The creations of more ecovillages, along with the growth of current ecovillages, play an important role in positively solvening environmental and social problems. The sustainable materials used in the ecovillages also act as a model for communities wishing to implement sustainable development.     

Relevance versus generalization in cognitive engineering

The purpose of this article is to describe how research at the intersection of cognition, technology, and work can be generalized beyond the source context of scientific inquiry and confirmation. Special emphasis is given to resolve confusion about the use of terms such as “ecological validity” and the “real world.” The ultimate goal is to foster a more productive dialog on the merits of where and how research on important cognitive engineering topics, such as cognitive adaptation to change and uncertainty, should be conducted.     

DNA Comet Giemsa Staining for Conventional Bright-Field Microscopy

This study was undertaken to evaluate the compatibility of Giemsa staining protocol with the comet assay. We showed, for the first time, that DNA comets can be visualized and analyzed using Giemsa staining. We generated DNA damage dose response curves for human peripheral blood lymphocytes exposed to X-ray radiation using the comet assay with either SybrGreen I or Giemsa stain. The dose response curves were fitted by linear regressions (R² > 0.977). The SybrGreen I results showed only ~1.2-fold higher slope coefficient (method sensitivity) compared to the Giemsa results. The unexpectedly high sensitivity of Giemsa staining for the comet assay is due to the Romanowsky-Giemsa effect, the stain photo-stability and the higher resolution of bright-field imaging compared to fluorescence imaging. Our results demonstrate that Giemsa staining can effectively be used for measuring DNA damage by the comet assay. The low cost and availability of Giemsa stain makes this method affordable for any low budget research and will facilitate new applications of the comet assay in biology and medicine.     

How verified (or tested) is my code? Falsification-driven verification and testing

Formal verification has advanced to the point that developers can verify the correctness of small, critical modules. Unfortunately, despite considerable efforts, determining if a “verification” verifies what the author intends is still difficult. Previous approaches are difficult to understand and often limited in applicability. Developers need verification coverage in terms of the software they are verifying, not model checking diagnostics. We propose a methodology to allow developers to determine (and correct) what it is that they have verified, and tools to support that methodology. Our basic approach is based on a novel variation of mutation analysis and the idea of verification driven by falsification. We use the CBMC model checker to show that this approach is applicable not only to simple data structures and sorting routines, and verification of a routine in Mozilla’s JavaScript engine, but to understanding an ongoing effort to verify the Linux kernel read-copy-update mechanism. Moreover, we show that despite the probabilistic nature of random testing and the tendency to incompleteness of testing as opposed to verification, the same techniques, with suitable modifications, apply to automated test generation as well as to formal verification. In essence, it is the number of surviving mutants that drives the scalability of our methods, not the underlying method for detecting faults in a program. From the point of view of a Popperian analysis where an unkilled mutant is a weakness (in terms of its falsifiability) in a “scientific theory” of program behavior, it is only the number of weaknesses to be examined by a user that is important.     

Enhanced duckweed detection using bootstrapped SVM classification on medium resolution RGB MODIS imagery

From early 2004, Lake Maracaibo (northwest Venezuela) experienced an unprecedented invasion of duckweed Lemna obscura. Recurrent blooms of the plant in the past 2 years illustrate the need for an automatic monitoring method to follow the plant cover with time and to plan contingency measures. We present an approach that allows the cover of the duckweed to be quantified through the classification of MODIS 250 m RGB composite images available from the internet. The method improves the accuracy of the results of the Support Vector Machine (SVM) algorithm for classification by including a bootstrap step during the training phase. Using only 200 pixels for training (<0.05% of the total), the bootstrapped SVM method allows a better identification of the duckweed class, reducing the number of false negatives by half and improving the KHAT statistic by almost 40% in comparison to the standard SVM method. This method has proved to be a reliable solution in cases where rapid responses are needed and only medium‐resolution, free satellite imagery is available.