Aerospace medicine and biology: A continuing bibliography with indexes, supplement 204

This bibliography lists 140 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980

Categorical semantics and composition of tree transducers

In this thesis we see two new approaches to compose tree transducers and more general to fuse functional programs. The first abroach is based on initial algebras. We prove a new variant of the acid rain theorem for mutually recursive functions where the build function is substituted by a concrete functor. Moreover, we give a symmetric form (i.e. consumer and producer have the same syntactic form) of our new acid rain theorem where fusion is composition in a category and thus in particular associative. Applying this to compose top-down tree transducers yields the same result (on a syntactic level) as the classical top-down tree transducer composition. The second approach is based on free monads and monad transformers. In the same way as monoids are used in the theory of character string automata, we use monads in the theory of tree transducers. We generalize the notion of a tree transducer defining the monadic transducer, and we prove an according fusion theorem. Moreover, we prove that homomorphic monadic transducers are semantically equivalent. The latter makes it possible to compose syntactic classes of tree transducers (or particular functional programs) by simply composing endofunctors

Bioreactor scalability: laboratory-scale bioreactor design influences performance, ecology, and community physiology in expanded granular sludge bed bioreactors

Studies investigating the feasibility of new, or improved, biotechnologies, such as wastewater treatment digesters, inevitably start with laboratory-scale trials. However, it is rarely determined whether laboratory-scale results reflect full-scale performance or microbial ecology. The Expanded Granular Sludge Bed (EGSB) bioreactor, which is a high-rate anaerobic digester configuration, was used as a model to address that knowledge gap in this study. Two laboratory-scale idealizations of the EGSB—a one-dimensional and a three- dimensional scale-down of a full-scale design—were built and operated in triplicate under near-identical conditions to a full-scale EGSB. The laboratory-scale bioreactors were seeded using biomass obtained from the full-scale bioreactor, and, spent water from the distillation of whisky from maize was applied as substrate at both scales. Over 70 days, bioreactor performance, microbial ecology, and microbial community physiology were monitored at various depths in the sludge-beds using 16S rRNA gene sequencing (V4 region), specific methanogenic activity (SMA) assays, and a range of physical and chemical monitoring methods. SMA assays indicated dominance of the hydrogenotrophic pathway at full-scale whilst a more balanced activity profile developed during the laboratory-scale trials. At each scale, Methanobacterium was the dominant methanogenic genus present. Bioreactor performance overall was better at laboratory-scale than full-scale. We observed that bioreactor design at laboratory-scale significantly influenced spatial distribution of microbial community physiology and taxonomy in the bioreactor sludge-bed, with 1-D bioreactor types promoting stratification of each. In the 1-D laboratory bioreactors, increased abundance of Firmicutes was associated with both granule position in the sludge bed and increased activity against acetate and ethanol as substrates. We further observed that stratification in the sludge-bed in 1-D laboratory-scale bioreactors was associated with increased richness in the underlying microbial community at species (OTU) level and improved overall performance

Kinetic and Compositional Study of Phenolic Extraction from Olive Leaves (var.Serrana) by Using Power Ultrasound

[EN] Power ultrasound is being used as a novel technique for process intensification. In this study, the feasibility of using power ultrasound to improve the phenolic extraction from olive leaves was approached taking both compositional and kinetic issues into account and also determining the influence of the main process parameters (the electric power supplied, emitter surface and temperature). For this purpose, the extraction kinetics were monitored by measuring the total phenolic content and antioxidant capacity and mathematically described by Naik's model, and HPLC DAD/MS MS was used to identify and quantify the main polyphenols. The electric power supplied and the emitter surface greatly affected the effective ultrasonic power applied to the medium, and hence the extraction rate. However, the influence of temperature on ultrasound assisted extraction was not clear. Compared with conventional extraction, ultrasound assisted extraction reduced the extraction time from 24 h to 15 min and did not modify the extract composition. Industrial relevance: Olive crop produces a significant quantity of byproducts (leaves, branches, solid and liquid wastes), coming from the tree pruning, fruit harvest and oil production, which are rich in phenolic compounds with bioactive properties. The extraction of the bioactive compounds could be an interesting option with which to increase the value of these byproducts, as it requires efficient extraction techniques in order to reduce processing costs and improve productivity. In this sense, ultrasound assisted extraction is considered a novel technique used as ameans of intensifying a slow process, such as the leaching of polyphenols fromvegetablematrices. In order to further address the industrial applications of ultrasound assisted extraction, a kinetic study should be carried out determining both the effective energy introduced into the medium, as well as its influence on the extract quality.The authors thank the Generalitat Valenciana (PROMETEO/2010/062 and PROMETEO/2012/007) for its financial support. M. H. Ahmad Qasem was the recipient of a fellowship from Ministerio de Educacion, Cultura y Deporte of Spain (Programa de Formacion de Profesorado Universitario del Programa Nacional de Formacion de Recursos Humanos de Investigacion).Ahmad-Qasem Mateo, MH.; Canovas, J.; Barrajon-Catalan, E.; Micol, V.; Cárcel Carrión, JA.; García Pérez, JV. (2013). Kinetic and Compositional Study of Phenolic Extraction from Olive Leaves (var.Serrana) by Using Power Ultrasound. Innovative Food Science and Emerging Technologies. (17):120-129. https://doi.org/10.1016/j.ifset.2012.11.008S1201291

Confusion modelling for lip-reading

Lip-reading is mostly used as a means of communication by people with hearing di�fficulties. Recent work has explored the automation of this process, with the aim of building a speech recognition system entirely driven by lip movements. However, this work has so far produced poor results because of factors such as high variability of speaker features, diffi�culties in mapping from visual features to speech sounds, and high co-articulation of visual features. The motivation for the work in this thesis is inspired by previous work in dysarthric speech recognition [Morales, 2009]. Dysathric speakers have poor control over their articulators, often leading to a reduced phonemic repertoire. The premise of this thesis is that recognition of the visual speech signal is a similar problem to recog- nition of dysarthric speech, in that some information about the speech signal has been lost in both cases, and this brings about a systematic pattern of errors in the decoded output. This work attempts to exploit the systematic nature of these errors by modelling them in the framework of a weighted finite-state transducer cascade. Results indicate that the technique can achieve slightly lower error rates than the conventional approach. In addition, it explores some interesting more general questions for automated lip-reading

Acoustic cavitation by means ultrasounds in the extra virgin olive oil extraction process

Abstract The virgin olive oil extraction process has changed very little over the past 20 years when the mechanical crushers, malaxers, horizontal and vertical centrifuges, took place in the olive mills. However, malaxation process remains the main critical step due to the discontinuity of this process. In previous activities, the same authors demonstrated how application of new emerging technologies could offer an interesting number of advantages to remove this bottleneck and, among the others, the ultrasound (US) technology is the most promising one, due to its mechanical and thermal effects due to the acoustic cavitation phenomenon. Acoustic cavitation, provided by means of low frequency high power ultrasounds, increases the quality, the work capacity and efficiency of the extraction plant, guaranteeing the sustainability. The paper shows how the authors have designed, realized and tested the first in the world continuous ultrasonic full-scale device for the extra virgin olive oil industry, with the aim to obtain the best product quality at the highest efficiency. Considering the heterogeneity of the olive paste, which is composed of different tissues, and considering the large number of parameters able to influence the process, a 3D multiphase CFD analysis was used as auxiliary tool in the design a so-called Sono-Heat-Exchanger (SHE). This innovative device, to be placed between the crusher and the decanter, is a combination of a heat-exchanger with plate-shape ultrasonic transducers. Finally, experimental results about yields and phenols contents demonstrated the relevance of this innovation

Graph Kernels

We present a unified framework to study graph kernels, special cases of which include the random walk (Gärtner et al., 2003; Borgwardt et al., 2005) and marginalized (Kashima et al., 2003, 2004; Mahé et al., 2004) graph kernels. Through reduction to a Sylvester equation we improve the time complexity of kernel computation between unlabeled graphs with n vertices from O(n^6) to O(n^3). We find a spectral decomposition approach even more efficient when computing entire kernel matrices. For labeled graphs we develop conjugate gradient and fixed-point methods that take O(dn^3) time per iteration, where d is the size of the label set. By extending the necessary linear algebra to Reproducing Kernel Hilbert Spaces (RKHS) we obtain the same result for d-dimensional edge kernels, and O(n^4) in the infinite-dimensional case; on sparse graphs these algorithms only take O(n^2) time per iteration in all cases. Experiments on graphs from bioinformatics and other application domains show that these techniques can speed up computation of the kernel by an order of magnitude or more. We also show that certain rational kernels (Cortes et al., 2002, 2003, 2004) when specialized to graphs reduce to our random walk graph kernel. Finally, we relate our framework to R-convolution kernels (Haussler, 1999) and provide a kernel that is close to the optimal assignment kernel of Fröhlich et al. (2006) yet provably positive semi-definite