Development of Surface Acoustic Wave Electronic Nose

The paper proposes an effective method to design and develop surface acoustic wave (SAW) sensor array-based electronic nose systems for specific target applications. The paper suggests that before undertaking full hardware development empirically through hit and trial for sensor selection, it is prudent to develop accurate sensor array simulator for generating synthetic data and optimising sensor array design and pattern recognition system. The latter aspects are most time-consuming and cost-intensive parts in the development of an electronic nose system. This is because most of the electronic sensor platforms, circuit components, and electromechanical parts are available commercially-off-the-shelve (COTS), whereas knowledge about specific polymers and data analysis software are often guarded due to commercial or strategic interests. In this study, an 11-element SAW sensor array is modelled to detect and identify trinitrotoluene (TNT) and dinitrotoluene (DNT) explosive vapours in the presence of toluene, benzene, di-methyl methyl phosphonate (DMMP) and humidity as interferents. Additive noise sources and outliers were included in the model for data generation. The pattern recognition system consists of: (i) a preprocessor based on logarithmic data scaling, dimensional autoscaling, and singular value decomposition-based denoising, (ii) principal component analysis (PCA)-based feature extractor, and (iii) an artificial neural network (ANN) classifier. The efficacy of this approach is illustrated by presenting detailed PCA analysis and classification results under varied conditions of noise and outlier, and by analysing comparative performance of four classifiers (neural network, k-nearest neighbour, naïve Bayes, and support vector machine).Defence Science Journal, 2010, 60(4), pp.364-376, DOI:http://dx.doi.org/10.14429/dsj.60.49

Evaluation of genotoxicity of the acute gamma radiation on earthworm Eisenia fetida using single cell gel electrophoresis technique (Comet assay)

Earthworms (Eisenia fetida) most suitable biological indicators of radioactive pollution. Radiation-induced lesions in DNA can be considered to be molecular markers for early effects of ionizing radiation. Gamma radiation produces a wide spectrum of DNA. Some of these lesions, i.e., DNA strand breaks and alkali labile sites can be detected by the single-cell gel electrophoresis (SCGE) or comet assay by measuring the migration of DNA from immobilized nuclear DNA. E. fetida were exposed to different doses of gamma radiation, i.e., 1, 5, 10, 20, 30, 40 and 50 Gy, and comet assay was performed for all the doses along with control at 1, 3 and 5 h post irradiation to evaluate the genotoxicity of gamma radiation in this organism. The DNA damage was measured as percentage of comet tail DNA. A significant increase in DNA damage was observed in samples exposed to 5 Gy and above, and the increase in DNA damage was dose dependent i.e., DNA damage was increased with increased doses of radiation. The highest DNA damage was noticed at 1 h post irradiation and gradually decreased with time, i.e., at 3 and 5 h post irradiation. The present study reveals that gamma radiation induces DNA damage in E. fetida and the comet assay is a sensitive and rapid method for its detection to detect genotoxicity of gamma radiation. © 2015 Elsevier B.V

Breeding, genetics, and genomics approaches for improving Fusarium Wilt resistance in major grain legumes

Fusarium wilt (FW) disease is the key constraint to grain legume production worldwide. The projected climate change is likely to exacerbate the current scenario. Of the various plant protection measures, genetic improvement of the disease resistance of crop cultivars remains the most economic, straightforward and environmental-friendly option to mitigate the risk. We begin with a brief recap of the classical genetic efforts that provided first insights into the genetic determinants controlling plant response to different races of FW pathogen in grain legumes. Subsequent technological breakthroughs like sequencing technologies have enhanced our understanding of the genetic basis of both plant resistance and pathogenicity. We present noteworthy examples of targeted improvement of plant resistance using genomics-assisted approaches. In parallel, modern functional genomic tools like RNA-seq are playing a greater role in illuminating the various aspects of plant-pathogen interaction. Further, proteomics and metabolomics have also been leveraged in recent years to reveal molecular players and various signaling pathways and complex networks participating in host-pathogen interaction. Finally, we present a perspective on the challenges and limitations of high-throughput phenotyping and emerging breeding approaches to expeditiously develop FW-resistant cultivars under the changing climate

Effects of acute gamma radiation on the reproductive ability of the earthworm Eisenia fetida

Earthworms are the most suitable biological indicators of radioactive pollution because they are the parts of nutritional webs, and are present in relatively high numbers. Four months old Eisenia fetida were exposed to different doses of gamma radiation, namely 1, 2, 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55 & 60 Gy to study the effects of radiation on different reproductive parameters. The number of cocoons laid and the hatchlings emerged were recorded for all the selected doses. There was no reduction in cocoon production, however; decreasing size and weight of the cocoons was observed from the samples exposed to 20 Gy and above doses. Significant reductions in the hatchlings were recorded in earthworms exposed to 10 Gy and above doses. The dose response curves for a percentage reduction in hatchlings were constructed. Exposure to radiation dose of 1 and 2 Gy did not show any reduction, however, there was ≈10%, ≈50% and ≈90% decrease in the hatchlings in samples exposed to 3, 15 and 45, 50, 55 and 60 Gy doses respectively. Delayed hatchability was also reported at al exposure level. Histology of irradiated earthworms revealed that the structural damage in the seminal vesicles was prominent at the exposed dose of 3 Gy onwards with complete degeneration on exposure to 60 Gy of gamma radiation

Evaluation of gamma radiation-induced DNA damage in Aedes aegypti using the comet assay

The study was undertaken to evaluate gamma radiation-induced DNA damage in Aedes aegypti. The comet assay was employed to demonstrate the extent of DNA damage produced in adult male A. aegypti exposed to seven different doses of gamma radiation, ranging from 1 Gy to 50 Gy. DNA damage was measured as the percentage of comet tail DNA. A significant linear increase in DNA damage was observed in all samples; the extent of damage being proportional to the dose of gamma radiation the organism received, except in those treated with 1 Gy. The highest amount of DNA damage was noticed at 1 h postirradiation, which decreased gradually with time, that is, at 3, 6 and 12 h postirradiation. This may indicate repair of the damaged DNA and/or loss of heavily damaged cells as the postirradiation time increased. The comet assay serves as a sensitive and rapid technique to detect gamma radiation-induced DNA damage in A. aegypti. This could be used as a potential biomarker for environmental risk assessment. © 2017, © The Author(s) 2017

Effect of gamma radiation on life history traits of Aedes aegypti (L.)

AbstractAedes aegypti is an important vector for Dengue and Dengue hemorrhagic fever. Considering its medical importance and its relevance as a model system, this study was undertaken to evaluate the impact of different doses of gamma radiation for three generations of A. aegypti. Two to three days old virgin males of A. aegypti were irradiated with 15 doses of gamma radiation, ranging from 1 to 50Gy and were immediately mass mated with the same aged virgin females. Observations were made for changes on their life history traits, particularly fecundity, hatchability, adult emergence, sex ratio and longevity, for three generations. Adult males exposed 30, 35, 40, 45 and 50Gy doses showed a significant decrease in fecundity in F0 generations. While hatchability was observed to have decreased with increasing radiation doses from 3Gy onwards in the F1 generation, samples irradiated with 30, 35, 40, 45 and 50Gy maintained significant decline in hatchability in their succeeding generations, F2 and F3 also. Similarly, a decline was observed in adult emergence from 3Gy onwards in all three generations. A male favoring sex ratio distortion was observed at the doses of 35, 40, 45 and 50Gy in all three generations. Following exposure to 4Gy, parental males and the resultant progeny showed increased longevity by 10.56 and 8.66days respectively. Similarly, the F1 generations of samples irradiated with 30, 35 and 40Gy exhibited an increase in longevity by 7.16, 7.44 and 6.64days respectively. Dose response curve for fertility among the three generations was drawn and presented. The effect of radiological exposure on the life history traits of A. aegypti varies with dose for the three generations studied. These results have potential implications in mutational studies and risk assessment and also contribute to a better understanding towards employment of the sterile insect technique in A. aegypti, plausibly paving the way to an effective mosquito genetic control program

Does exposure of male Drosophila melanogaster to acute gamma radiation influence egg to adult development time and longevity of F1–F3 offspring?

Two- to three-day-old male Drosophila melanogaster flies were irradiated with 1, 2, 4, 6, 8, 10, 20, 25, 30, 40 and 50 Gy doses of gamma radiation. The longevity and rate of development were observed for three successive generations to assess the impact of irradiation. The mean lifespan of irradiated flies was significantly increased at 1, 2 and 8 Gy, while it was vice versa for high doses at 30, 40 and 50 Gy. Paternal irradiation had an impact on F1 generation, with significantly increased mean longevity at 2 (female), 4, 6, 8 and 10 and decreased mean longevity at 40 and 50 Gy (male and female). Significant increase in the longevity was observed in the F2 generation of the 8 (male and female) and 10 Gy (male) irradiated groups, while decreased longevity was observed in F2 female progeny at 40 Gy. In the case of F3 progeny of irradiated flies, longevity did not show significant difference with the control. Paternal exposure to radiation had a significant impact on the mean egg to adult developmental time of the F1 generation; it was shortened at 2 Gy and extended at 25, 30, 40 and 50 Gy compared to the control. Mean development time at 30, 40 and 50 Gy was significantly increased in the F2 generation, while there were no significant changes in the F3 generation. The present study concludes that the effect of acute gamma irradiation on longevity and “egg to adult” development time of D. melanogaster may persist to following generations

Learning and Designing Stochastic Processes from Logical Constraints

Continuous time Markov Chains (CTMCs) are a convenient mathematical model for a broad range of natural and computer systems. As a result, they have received considerable attention in the theoretical computer science community, with many important techniques such as model checking being now mainstream. However, most methodologies start with an assumption of complete specification of the CTMC, in terms of both initial conditions and parameters. While this may be plausible in some cases (e.g. small scale engineered systems) it is certainly not valid nor desirable in many cases (e.g. biological systems), and it does not lead to a constructive approach to rational design of systems based on specific requirements. Here we consider the problems of learning and designing CTMCs from observations/ requirements formulated in terms of satisfaction of temporal logic formulae. We recast the problem in terms of learning and maximising an unknown function (the likelihood of the parameters) which can be numerically estimated at any value of the parameter space (at a non-negligible computational cost). We adapt a recently proposed, provably convergent global optimisation algorithm developed in the machine learning community, and demonstrate its efficacy on a number of non-trivial test cases

Time for Statistical Model Checking of Real-Time Systems

Abstract. We propose the first tool for solving complex (some unde-cidable) problems of timed systems by using Statistical Model Checking (SMC). The tool monitors several runs of the system, and then relies on statistical algorithms to get an estimate of the correctness of the entire design. Contrary to other existing toolsets, ours relies on i) a natural stochastic semantics for networks of timed systems, ii) an engine capable to solve problems that are beyond the scope of classical model checkers, and iii) a friendly user interface.