1,368,744 research outputs found
Solid-state fermentation : modelling fungal growth and activity
No full textIn solid-state fermentation (SSF) research, it is not possible to separate biomass quantitatively from the substrate. The evolution of biomass dry weight in time can therefore not be measured. Of the aiternatives to dry weight available, glucosamine content is most promising.Glucosamine is the monomer of the cell-wall component chitin. Glucosamine content of a fermented substrate is therefore related to the biomass present. The concentration of glucosamine in biomass, however, might vary in time end with culture conditions.Instead of using the glucosamine content to calculate how much biomass dry weight is present as was done previously, in this research biomass growth and activity are directly related to glucosamine. With these descriptions a mathematical model is constructed which allows prediction of biomass glucosamine and temperature patterns in an SSF bed.The research is done with Trichoderma reesei QM9414 growing on wheat bran as a model SSF. The fermentations are carried out in Petri dishes containing 5 g moistened inoculated and sterilized wheat bran which are placed in an incubator with constant temperature and ambient relative humidity. Samples for analysis ware drawn by taking Petri dishes from the incubator. In this way, accurate measurement of dry-matter weight loss, respiration activfty and glucosamine was possible with a standard deviation of less than 7%. Measurement of ATP and cellulase activity proved not to be as accurate. This was attributed to handling of the fermented substrate during necessary pretreatment procedures for ATP measurement and interactions between enzyme and substrate, respectively.Respiration activities, i.e. oxygen consumption rate and carbon-dioxide production rate, were measured simuitaneously. During a 125 h fermentation ca. 9 mmol CO2, and 02 per gram initial dry matter were produced and consumed, respectively. The decrease in dry matter in this period amounted to ca. 0.20 g per gram initial dry matter. The increase in glucosamine could be described with a logistic equation, with initial and final level of 0.02 and 8.1 mg glucosamine per gram initial dry matter, respectively. The maximum specific growth rate amounted to 0.123 per hour.The specific respiration activities were calculated per quantity of glucosamine. The correlation with maximum specific growth rate deviated from Pirts linear-growth model. These deviations ware attributed to the different forms in which fungal biomass can be present (active growing and active non-growing). These deviations are, however, of minor importance in modelling fungal activity since they appear only at the initial stage of fermentation where the amount of fungal biomass is small.There was a pronounced decline in respiration activity after growth has stopped. This decline, called inactivation, was ascribed to a decrease in amount of active non-growing biomass. The rate of decline seemed constant in time under isothermal conditions, but increased exponentially with increasing temperature above the maximum temperature for growth.The influence of temperature on specific growth rate, maximum attainabie biomass glucosamine level end yield of glucosamine on oxygen consumption or carbon-dioxide production could be described with a (modified) Ratkowsky equation or a Gaussian curve. The influence of temperature on the maintenance coefficient was negligible.These mathematical equations were combined with conservation laws describing mess and heat transfer in a simulation model. lnactivation, as described under isothermal conditions, was implemented in three different ways, which resuited in the models M part , M temp , and M cont . In the M part , model, inactivation starts when the specific growth rate becomes equal to or less than 1 % of its maximum value. The inactivation continues until no activity is left. In the M temp model, inactivation starts for the same reason, but stops when the specific growth rate is more than 1 % of its maximum value again. In the M cont model, inactivation is continuously effective, immediately from the start of fermentation.The temperature end biomass evolution in a tray SSF predicted by these three models are compared with a model in which inactivation is omitted. The results show the importance of describing the inactivation in modelling SSF. Without this, irrealistic temperature and biomass glucosamine patterns are predicted.The M part , model, representing inactivation due to substrate limitation or product toxicity, predicts temperature and blomass patterns described in the literature: restricted biomass growth end decrease in temperature at the end of fermentation. The mathematical models reported thus far in the literature predict restricted growth or a decrease in temperature.Although the combination of the logistic equation, for describing fungal biomass in time, and the linear-growth model, for correlating the respiration activity to biomass, is most often used in scientific literature on modelling SSF, it is insufficiently detailed. The logistic equation is shown to be applicabie to the glucosamine measurement results, but the glucosamine determination cannot distinguish between active growing, active non-growing end inactive biomass. The totalamount of these three types of biomass is described by the logistic equation, while the linear-growth model only describes the first two types. It is therefore suggested to focus research efforts on the description of the evolution of these three different forms of fungal biomass in time. Sensitive image analysis techniques, combined with computer technology, applied to fungal biomass growing under SSF conditions have the potential of being powerful tools to accomplish this target
Academic Correspondence, Stanford and Other Universities 1959-1960: Helen Smits, January 25, 1960
No full textLetter from Fayez Sayegh to Helen Smits, Editorial Assistant for The Annals of the American Academy of Political and Social Science, January 25, 1960, inquiring whether or not a paper of his had been published and requesting copies if so
Reliability and validity of DTI-based indirect disconnection measures
No full textData accompanying the paper: Reliability and validity of DTI-based indirect disconnection measures.Authors: A.R. Smits, M.J.E. van Zandvoort, N.F. Ramsey, E.H.F. de Haan, M. RaemaekersAbstractWhite matter connections enable the interaction within and between brain networks. Brain lesions can cause structural disconnections that disrupt networks and thereby cognitive functions supported by them. In recent years, novel methods have been developed to quantify the extent of structural disconnection after focal lesions, using tractography data from healthy controls. These methods, however, are indirect and their reliability and validity have yet to be fully established. In this study, we present our implementation of this approach, in a toolkit supplemented by uncertainty metrics for the predictions overall and at voxel-level. These metrics give an indication of the reliability and are used to compare predictions with direct measures from patients’ diffusion tensor imaging (DTI) data in a sample of 95 first-ever stroke patients. Results show that, except for small lesions, our toolkit can predict fiber loss with high reliability and compares well to direct patient DTI estimates. Clinical utility of the method was demonstrated using lesion data from a subset of patients suffering from hemianopia. Both tract-based measures outperformed lesion localization in mapping visual field defects and showed a network consistent with the known anatomy of the visual system. This study offers an important contribution to the validation of structural disconnection mapping. We show that indirect measures of structural disconnection can be a reliable and valid substitute for direct estimations of fiber loss after focal lesions. Moreover, based on these results, we argue that indirect structural disconnection measures may even be preferable to lower-quality single subject diffusion MRI when based on high-quality healthy control datasets.Files/Folders: (1) Lesion overlap map(2) SnPM lesion-symptom maps: contains the thresholded p-value maps for the SnPM analysis for visual field defects, based on predictions of the 3 databases, the lesion maps, and the visitation-map based on the patient’s DTI as input.(3) Toolkit cod
Interview with Howard G. Smits
No full textAn interview in February 1979 with Caltech alumnus Howard G. Smits, former president of the Pacific Iron and Steel Company, who graduated with a BS (1931) and MS (1933) in civil engineering. He discusses the different focus, in Caltech’s early days, of engineers vis-à-vis theoretical scientists. He was a member of the Gnomes, and he reminisces about fraternity life and the disbanding of the fraternities in 1931 in favor of student housing—a move mandated by Caltech’s head, Robert A. Millikan. Comments on Millikan’s motives, the change in atmosphere on campus, and the makeup of the four new student houses. Recalls his part in fostering new traditions and interhouse athletic competitions; extracurricular activities. Economics courses with Horace Gilbert and Philip Fogg; history with William Bennett Munro. Anecdote about Albert Einstein and Beno Gutenberg; bonfires before annual football game with Occidental; visits to Scripps College. Recollections of working with architect Richard Neutra. Course in structural engineering with Romeo Martel. Concludes with comments on his membership in the Caltech Associates
De orgelmakers Smits te Reek (bij Grave)
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170240.pdf (Publisher’s version ) (Open Access)In the little village of Reek, in the northeast of the province of North Brabant, Klaas Smits (1791-1831) set up a workshop around 1820 in order to build an organ for his own parish church of St. Antonius Abt. Although Smits was an autodidact, he laid the foundations for a company which remained in business for over one hundred years and produced more than one hundred instruments. Through three generations (indicated in the present study by I, II and III), six members of the Smits family were in full-time employment as organ builders.
Klaas Smits (I) gained experience by examining these instruments and undertaking minor repairs. From about 1826 Klaas Smits was assisted in building the Reek organ by his brother Frans (Franciscus Cornelius I), and together they founded the company Gebroeders Smits, Orgelmakers te Reek by Grave.
After the decease of F.C. Smits (I) in 1876, his son F.C. Smits (II) took over the workshop. Since several brothers were also employed, Frans (II) continued the company under the original name Gebroeders Smits, orgelmakers te Reek by Grave.
Henri W.J. Smits (III) maintained the workshop unaltered until his death in 1944. This again typifies the members of the family; in Henri’s own words: I have left everything intact, and if somebody would like to have a good organ I could begin tomorrow.
Today, nineteen Smits organs still sound in the churches for which they were built; twelve others have found new locations, and there are also five older instruments to which Smits added a second manual. The many church closures of recent times form a threat to the future of a number of these instruments.Radboud Universiteit, 09 mei 2017Promotores : Koldeweij, A.M., Nissen, P.J.A.694 p
Smits
No full textDutch family of organbuilders. Born to a well-to-do Roman Catholic family, Nicolaas Klaas Smits (b. Reek, North Brabant, 1 April 1791; d. 19 Oct 1831) carried out maintenance work on organs in Maasland, South Holland, from around 1810 on. His brother (Franciscus) Frans Cornelius Smits I (b. 20 Aug 1802; d. 28 March 1876) was appointed organist at Reek, where his brother subsequently built a new organ (1829). In that year, Frans I joined the workshop, continuing it after his brother's death. The brothers were self-taught, having gleaned their knowledge from examining organs in the area and from François BEDOS DE CÉLLES'S 'L'art du facteur d'orgues' (1766-78) and Jan van Heurn's 'De orgelmaaker' (1804-5). Frans I brought the business to prosperity, building a few dozen organs between 1831 and 1865
Combining Preferences to Control a Natural Language Processing Chain
No full text@inproceedings{AI-SMI-06, author = {Grégory SMITS, Christine CHARDENON}, booktitle = {Proceedings of Multidisciplinary ECAI'06 Workshop on Advances in Preferences Handling}, date-added = {2006-09-08 18:07:05 +0200}, date-modified = {2006-09-08 18:12:33 +0200}, editor = {ITC}, keywords = {personal publications}, pages = {128-134}, title = {Combining Preferences to Control a Natural Language Processing Chain}, year = {2006}, address = {Trento, Italy} }International audienc
Beyond Access. The multifaceted water supply in urban and peri-urban areas of Bandung and Jakarta, Indonesia
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175602.pdf (Publisher’s version ) (Open Access)Radboud University, 20 september 2017Promotores : Smits, A.J.M., Muntalif, B.S. Co-promotores : Meijerink, S.V., Roosmini, D., Sudradjat, A.185 p
Water Affordability, Water Quality and their Consequences for Health and Education in Indonesia
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178391.pdf (Publisher’s version ) (Open Access)Radboud University, 19 oktober 2017Promotor : Jong, E. de Co-promotor : Smits, J.P.J.M.148 p
Cohort Differences in Big Five Personality Factors Over a Period of 25 Years
No full textThis dataset comprises scores of 8,954 first-year psychology students from the University of Amsterdam (1982-2007) on the ‘Vijf PersoonlijkheidsFactoren Test’ or 5PFT (Elshout & Akkerman, 1975), which is an instrument to measure the Big Five personality factors Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience. Selection of participants as described in Smits et al. on page 1126 and in their Table 1.
This dataset formed the basis of the article "Cohort Differences in Big Five Personality Factors Over a Period of 25 Years" (See the link to the DOI in the Relationfield) authored by Iris A. M. Smits, Conor V. Dolan, Harrie C.M. Vorst, Jelte M. Wicherts, & Marieke E. Timmerman.
A data paper about this data is available at: Smits, Iris A. M., Dolan, C. V., Vorst, H. C. M., Wicherts, J M., Timmerman, M. E. Data from ‘Cohort Differences in Big Five Personality Factors Over a Period of 25 Years’. Journal of Open Psychology Data 1(1). (See the link to the DOI in the Relationfield)
This data is released under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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