106 research outputs found
Distributed design of product oriented manufacturing systems
Manufacturing leanness and agility are requirements of today’s manufacturing
systems. Leanness call for a best fit of the manufacturing systems to products,
therefore requiring product oriented manufacturing systems (POMS).
Manufacturing agility can be achieved through easy systems reconfiguration to
fit changing manufacturing requirements, which may mean dynamically
configuring POMS. For this a suitable design system is required. Due to
complexity of this design, and to the need for using suitable design methods,
which may not be available locally, distributed sources of design services can
be used. This paper presents and describes a prototype of a Distributed Design
system for POMS based on a POMS design methodology and distributed
suppliers of design services
Machine-Part cell formation through visual decipherable clustering of Self Organizing Map
Machine-part cell formation is used in cellular manufacturing in order to
process a large variety, quality, lower work in process levels, reducing
manufacturing lead-time and customer response time while retaining flexibility
for new products. This paper presents a new and novel approach for obtaining
machine cells and part families. In the cellular manufacturing the fundamental
problem is the formation of part families and machine cells. The present paper
deals with the Self Organising Map (SOM) method an unsupervised learning
algorithm in Artificial Intelligence, and has been used as a visually
decipherable clustering tool of machine-part cell formation. The objective of
the paper is to cluster the binary machine-part matrix through visually
decipherable cluster of SOM color-coding and labelling via the SOM map nodes in
such a way that the part families are processed in that machine cells. The
Umatrix, component plane, principal component projection, scatter plot and
histogram of SOM have been reported in the present work for the successful
visualization of the machine-part cell formation. Computational result with the
proposed algorithm on a set of group technology problems available in the
literature is also presented. The proposed SOM approach produced solutions with
a grouping efficacy that is at least as good as any results earlier reported in
the literature and improved the grouping efficacy for 70% of the problems and
found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure
Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins
<p>Abstract</p> <p>Background</p> <p>Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites.</p> <p>Results</p> <p>We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information.</p> <p>Conclusion</p> <p>While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structure-based P-site prediction method has been made available at <url>http://phos3d.mpimp-golm.mpg.de</url>.</p
The Mass Distribution and Rotation Curve in the Galaxy
The mass distribution in the Galaxy is determined by dynamical and
photometric methods. Rotation curves are the major tool for determining the
dynamical mass distribution in the Milky Way and spiral galaxies. The
photometric (statistical) method utilizes luminosity profiles from optical and
infrared observations, and assumes empirical values of the mass-to-luminosity
(M/L) ratio to convert the luminosity to mass. In this chapter the dynamical
method is described in detail, and rotation curves and mass distribution in the
Milky Way and nearby spiral galaxies are presented. The dynamical method is
categorized into two methods: the decomposition method and direct method. The
former fits the rotation curve by calculated curve assuming several mass
components such as a bulge, disk and halo, and adjust the dynamical parameters
of each component. Explanations are given of the mass profiles as the de
Vaucouleurs law, exponential disk, and dark halo profiles inferred from
numerical simulations. Another method is the direct method, with which the mass
distribution can be directly calculated from the data of rotation velocities
without employing any mass models. Some results from both methods are
presented, and the Galactic structure is discussed in terms of the mass.
Rotation curves and mass distributions in external galaxies are also discussed,
and the fundamental mass structures are shown to be universal.Comment: 54 pages, 25 figures, in 'Planets, Stars and Stellar Systems',
Springer, Vol. 5, ed. G. Gilmore, Chap. 19. Note: Preprint with full figures
is available from http://www.ioa.s.u-tokyo.ac.jp/~sofue/htdocs/2013psss
Gravitational-wave research as an emerging field in the Max Planck Society. The long roots of GEO600 and of the Albert Einstein Institute
On the occasion of the 50th anniversary since the beginning of the search for
gravitational waves at the Max Planck Society, and in coincidence with the 25th
anniversary of the foundation of the Albert Einstein Institute, we explore the
interplay between the renaissance of general relativity and the advent of
relativistic astrophysics following the German early involvement in
gravitational-wave research, to the point when gravitational-wave detection
became established by the appearance of full-scale detectors and international
collaborations. On the background of the spectacular astrophysical discoveries
of the 1960s and the growing role of relativistic astrophysics, Ludwig Biermann
and his collaborators at the Max Planck Institute for Astrophysics in Munich
became deeply involved in research related to such new horizons. At the end of
the 1960s, Joseph Weber's announcements claiming detection of gravitational
waves sparked the decisive entry of this group into the field, in parallel with
the appointment of the renowned relativist Juergen Ehlers. The Munich area
group of Max Planck institutes provided the fertile ground for acquiring a
leading position in the 1970s, facilitating the experimental transition from
resonant bars towards laser interferometry and its innovation at increasingly
large scales, eventually moving to a dedicated site in Hannover in the early
1990s. The Hannover group emphasized perfecting experimental systems at pilot
scales, and never developed a full-sized detector, rather joining the LIGO
Scientific Collaboration at the end of the century. In parallel, the Max Planck
Institute for Gravitational Physics (Albert Einstein Institute) had been
founded in Potsdam, and both sites, in Hannover and Potsdam, became a unified
entity in the early 2000s and were central contributors to the first detection
of gravitational waves in 2015.Comment: 94 pages. Enlarged version including new results from further
archival research. A previous version appears as a chapter in the volume The
Renaissance of General Relativity in Context, edited by A. Blum, R. Lalli and
J. Renn (Boston: Birkhauser, 2020
Persistence of self-injurious behaviour in autism spectrum disorder over 3Â years: a prospective cohort study of risk markers
BackgroundThere are few studies documenting the persistence of self-injury in individuals with autism spectrum disorder (ASD) and consequently limited data on behavioural and demographic characteristics associated with persistence. In this longitudinal study, we investigated self-injury in a cohort of individuals with ASD over 3 years to identify behavioural and demographic characteristics associated with persistence.MethodsCarers of 67 individuals with ASD (Median age of individuals with ASD in years = 13.5, Interquartile Range = 10.00–17.00), completed questionnaires relating to the presence and topography of self-injury at T1 and three years later at T2. Analyses were conducted to evaluate the persistence of self-injury and to evaluate the behavioural and demographic characteristics associated with persistence of self-injury.ResultsAt T2 self-injurious behaviour had persisted in 77.8 % of individuals. Behavioural correlates of being non-verbal, having lower ability and higher levels of overactivity, impulsivity and repetitive behaviour, were associated with self-injury at both time points. Risk markers of impulsivity (p = 0.021) and deficits in social interaction (p = 0.026) at T1 were associated with the persistence of self-injury over 3 years.ConclusionsImpulsivity and deficits in social interaction are associated with persistent self-injury in ASD and thus may act as behavioural risk markers. The identification of these risk markers evidences a role for behaviour dysregulation in the development and maintenance of self-injury. The findings have clinical implications for proactive intervention; these behavioural characteristics may be utilised to identify ‘at risk’ individuals for whom self-injury is likely to be persistent and therefore those individuals for whom early intervention may be most warranted.<br/
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