178 research outputs found
When Clusters become Networks
Policy makers spend large amounts of public resources on the foundation of science parks and other forms of geographically clustered business activities, in order to stimulate regional innovation. Underlying the relation between clusters and innovation is the assumption that co-located firms engaged in innovative activities benefit from knowledge that diffuses locally. In order to access this knowledge, firms are often required to form more- or less formal relations with co-located firms. Empirical evidence shows however that besides some success cases like Silicon Valley and the Emilia- Romagna region where firms collaborate intensively, many regional clusters are mere co-locations of firms. To enhance our understanding of why some clusters become networks of strategic collaboration and others donβt, we study link formation within European biopharmaceutical clusters. More specifically we look at the effect of cluster characteristics such as number of start-up firms, established firms or academic institutions, or the nature of the collaborations on the probability of local link formation
Come Close and Co-create: Proximities in Pharmaceutical Innovation Networks
In studying firm behavior, economists tend to have an under-socialized view of the
firm, while sociologists tend to have an over-socialized view of the firm. Socialization
in this respect refers to the extent to which a firm is embedded in- and affected by its
relational environment. On the one extreme, economists building on transaction costs
economics assume the market to be an anonymous environment where firms can
behave opportunistically without reper
Developing credit risk score using SAS programming
ΠΠ±ΡΠ΅ΠΊΡΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΡΡΡΡ Π΄Π°Π½Π½ΡΠ΅ ΠΎ ΠΊΡΠ΅Π΄ΠΈΡΠΎΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ Π·Π°Π΅ΠΌΡΠΈΠΊΠΎΠ².
ΠΡΠ΅Π΄ΠΌΠ΅Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ: ΠΌΠΎΠ΄Π΅Π»Ρ ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΠΈΡΠΊΠ° ΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΡΠΉ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡ (GUI).
Π¦Π΅Π»Ρ ΠΏΡΠΎΠ΅ΠΊΡΠ° - ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°ΡΡ ΡΠΈΡΡΠ΅ΠΌΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΠΈΡΠΊΠ° Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ SAS, ΡΡΠΎΠ±Ρ ΠΏΠΎΠΌΠΎΡΡ Π±Π°Π½ΠΊΡ Π² ΠΏΡΠΈΠ½ΡΡΠΈΠΈ ΡΠ΅ΡΠ΅Π½ΠΈΠΉ, ΠΊΠΎΠ½ΡΡΠΎΠ»ΠΈΡΠΎΠ²Π°ΡΡ ΡΠΈΡΠΊ ΠΈ Π²ΡΠ±ΠΈΡΠ°ΡΡ Π±ΠΎΠ»Π΅Π΅ Ρ
ΠΎΡΠΎΡΠΈΡ
Π·Π°Π΅ΠΌΡΠΈΠΊΠΎΠ² ΠΈ ΡΠ΄Π°Π»ΡΡΡ ΠΏΠ»ΠΎΡ
ΠΈΡ
Π·Π°Π΅ΠΌΡΠΈΠΊΠΎΠ² ΠΈΠ· Π±Π°Π½ΠΊΠ°.The object of the study is data on the creditworthiness of borrowers.
The subject of the research the credit risk model and make a system interface (GUI).
The objective of the project is to develop the system from credit risk model by using SAS programming to help the bank in decision-making, control the risk and choose more good borrowers and delete bad borrowers from the bank.
In the research project, to learn how to develop credit scoring using SAS programming and create program calculate credit risk score using Python .
As a result of the study, it is show that to improves the accuracy of the assessment of creditworthiness by using logistic regression (selection variables method, evaluation dataset). The conclusion is the program calculator is made
ΠΠ±Π½Π°ΡΡΠΆΠ΅Π½ΠΈΠ΅ Π±ΡΠΎΠ½Ρ ΠΎΠ»Π΅Π³ΠΎΡΠ½ΡΡ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠΎΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π»ΠΎΠΊΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΡΡΠ½ΠΎΡΡΠ΅ΠΉ ΠΈ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ°ΡΠΈΠΈ
Π ΡΠ°Π±ΠΎΡΠ΅ ΠΎΠ±ΡΡΠΆΠ΄Π°ΡΡΡΡ Π°ΡΠΏΠ΅ΠΊΡΡ Π°Π½Π°Π»ΠΈΠ·Π° ΠΈΠ½ΡΠ΅Π»Π»Π΅ΠΊΡΡΠ°Π»ΡΠ½ΡΡ
ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠΎΠ², ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² ΠΈ Π½ΠΎΠ²ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π΄Π»Ρ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠ±Π½Π°ΡΡΠΆΠ΅Π½ΠΈΡ ΠΈ ΡΠ°ΡΠΏΠΎΠ·Π½Π°Π²Π°Π½ΠΈΡ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠΉ. Π¦Π΅Π»ΡΡ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΠ΅ Π½Π°Π΄Π΅ΠΆΠ½ΠΎΠΉ ΠΏΡΠΎΡΠ΅Π΄ΡΡΡ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ°ΡΠΈΠΈ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ ΠΈ ΠΎΠ±Π½Π°ΡΡΠΆΠ΅Π½ΠΈΡ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠΉ Π΄Π»Ρ ΡΠΏΡΠΎΡΠ΅Π½ΠΈΡ ΡΠ°Π±ΠΎΡΡ ΡΠ°Π΄ΠΈΠΎΠ»ΠΎΠ³Π°. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΎΠ±ΡΡΠΆΠ΄Π°ΡΡΡΡ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΠ΅ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡΡ ΠΈ ΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΡΡ
ΡΠ΅ΡΠ΅Π½ΠΈΠΉ Π΄Π»Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΠΠ’-ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ.Analysis of medical instruments, packages and images for automatic detection and recognition of pathologies. Providing image segmentation and pathology detection to simplify the work of a radiologist. Also providing a user friendly interface and testing it to analyse output results
Transcriptomic identification of starfish neuropeptide precursors yields new insights into neuropeptide evolution
Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.This work was supported by a PhD studentship funded by QMUL and awarded to D.C.S. and a Leverhulme Trust grant (RPG-
2013-351) awarded to M.R.E. Sequencing of the A. rubens neural transcriptome was funded by an EPSRC grant (EP/J501360/1
Radical Innovation and Network Evolution
This paper examines how a radical technological innovation affects alliance formation of firms and subsequent network structures. We use longitudinal data of interfirm R&D collaborations in the biopharmaceutical industry in which a new technological regime is established. Our findings suggest that it requires radical technological change for firms to leave their embedded path of existing alliances and form new alliances with new partners. While new partners are mostly found through the firmsβ existing network, we provide some insight into distant link formation with unknown partners, which contributes to our understanding of how βsmall-worldsβ might emerg
The evolution of neuropeptide signalling: insights from echinoderms
This work was supported by Leverhulme Trust grant RGP-2013-351 and BBSRC grant BB/M001644/1 (awarded to M.R.E.).
Dean Semmens has a BSc in Molecular and Cellular Biology (University of Bath, 2011), a PhD in Neurobiology (Queen Mary University of London, 2015) and is a Leverhulme Trust-funded Postdoctoral Fellow.
Maurice Elphick studied at Royal Holloway University of London (BSc Biology, 1988; PhD Neurobiology, 1991) and became Professor of Physiology and Neuroscience at Queen Mary University of London in 2004
Transcriptomic analysis of crustacean neuropeptide signaling during the moult cycle in the green shore crab, Carcinus maenas
Abstract Background Ecdysis is an innate behaviour programme by which all arthropods moult their exoskeletons. The complex suite of interacting neuropeptides that orchestrate ecdysis is well studied in insects, but details of the crustacean ecdysis cassette are fragmented and our understanding of this process is comparatively crude, preventing a meaningful evolutionary comparison. To begin to address this issue we identified transcripts coding for neuropeptides and their putative receptors in the central nervous system (CNS) and Y-organs (YO) within the crab, Carcinus maenas, and mapped their expression profiles across accurately defined stages of the moult cycle using RNA-sequencing. We also studied gene expression within the epidermally-derived YO, the only defined role for which is the synthesis of ecdysteroid moulting hormones, to elucidate peptides and G protein-coupled receptors (GPCRs) that might have a function in ecdysis. Results Transcriptome mining of the CNS transcriptome yielded neuropeptide transcripts representing 47 neuropeptide families and 66 putative GPCRs. Neuropeptide transcripts that were differentially expressed across the moult cycle included carcikinin, crustacean hyperglycemic hormone-2, and crustacean cardioactive peptide, whilst a single putative neuropeptide receptor, proctolin R1, was differentially expressed. Carcikinin mRNA in particular exhibited dramatic increases in expression pre-moult, suggesting a role in ecdysis regulation. Crustacean hyperglycemic hormone-2 mRNAΒ expression was elevated post- and pre-moult whilst that for crustacean cardioactive peptide, which regulates insect ecdysis and plays a role in stereotyped motor activity during crustacean ecdysis, was elevated in pre-moult. In the YO, several putative neuropeptide receptor transcripts were differentially expressed across the moult cycle, as was the mRNA for theΒ neuropeptide, neuroparsin-1. Whilst differential gene expression of putative neuropeptide receptors was expected, the discovery and differential expression of neuropeptide transcripts was surprising. Analysis of GPCR transcript expression between YO and epidermis revealed 11 to be upregulated in the YO and thus are now candidates for peptide control of ecdysis. Conclusions The data presented represent a comprehensive survey of the deduced C. maenas neuropeptidome and putative GPCRs. Importantly, we have described the differential expression profiles of these transcripts across accurately staged moult cycles in tissues key to the ecdysis programme. This study provides important avenues for the future exploration of functionality of receptor-ligand pairs in crustaceans
Untersuchungen zur Struktur und Funktion der Glutathionsynthetase bei der Spalthefe Schizosaccharomyces pombe
In the literature the enzyme glutathione synthetase of the fission yeast S. pombe had been described - in contrast to the homodimeric enzymes of other eucaryotic organisms - as a heterotetramer composed of two βlargeβ 33 kDa and two βsmallβ 26 kDa subunits. The βlargeβ subunit had been assigned to the 3' region of the GSH2 gene. The sequences of the 56 kDa protein encoded by the full length S. pombe GSH2 open reading frame and glutathione synthetases from other eukaryotes show high levels of homology over the whole alignment. Based on this alignment and on the x-ray coordinates of the human enzyme, a structural model of the fission yeast glutathione synthetase was produced. According to this model, the structure of the fission yeast protein is very similar to its human ortholog. The amino acid residues essential for binding of the substrates and cofactors are highly conserved between the two enzymes. The only striking difference involves a 15 amino acid segment (residues 204 - 218), which only exists in the fission yeast protein. The S. pombe GSH2 gene was cloned, and a histidine-tag was attached to the C-terminus of the protein. The protein was expressed in S. pombe and purified by two-step affinity chromatography. The recovered enzyme occurred in two different forms: a homodimeric protein consisting of two identical 56 kDa subunits and a heterotetrameric protein composed of two βsmallβ 24 kDa and two βlargeβ 32 kDa subfragments. Both variants showed glutathione synthetase activity. Both the homodimer and the heterotetramer are encoded by the GSH2 gene. The 56 kDa subunit corresponds to the complete GSH2 open reading frame. By MALDI-TOF-MS and peptide mapping, the βsmallβ subfragment was assigned to the 5' area of the open reading frame. The 24 kDa and the 32 kDa proteins are produced following proteolytic cleavage of the 56 kDa protein. The 24 kDa protein represents the N-terminal, the 32 kDa protein the C-terminal subfragment. Protease inhibition experiments showed that the protease responsible for cleaving belongs to the metalloproteases class. The cleavage site is localized between the amino acid residues alanine and serine at positions 217 and 218, as determined by N-terminal sequencing and MALDI-TOF-MS. Site-directed mutagenesis was performed to obtain a stable homodimer: The region around the cleavage site - the amino acid residues 204 - 218 - which only occur in the fission yeast protein, were deleted. The protein was enzymatically active in vivo and in vitro. The regions of the subfragments of glutathione synthetase were subcloned and co-expressed in S. pombe as independent proteins. A heterotetrameric protein, composed of two 24 kDa and 32 kDa subfragments each, was isolated. The protein was functional in vivo and in vitro, which means that the subfragments assemble correctly within the cell. Moreover, a permuted version of the fission yeast glutathione synthetase was created by interchanging the positions of the two subfragments within the protein. The permutation yielded a catalytically active protein. The presence of the additional 15 amino acid residues in the fission yeast protein may trace back to a permutation event during the evolution of glutathione synthetase. The presence of an exon boundary in the respective region of the human gene might indicate the mechanism by which the insert was eliminated during the evolution of metazoans. In a crystallization screen of the S. pombe glutathione synthetase several conditions were identified under which the protein formed glassy aggregates, similar to very small crystals. In order to get bigger monocrystals, suitable for x-ray structure analysis, the conditions will have to be further optimized. As a result, the extraordinary subunit structure of the fission yeast glutathione synthetase was clarified by this work. The theory of a permutation event during the evolution of the enzyme was reproduced experimentally. Furthermore, the homologous expression of several variants of glutathione synthetase showed that S. pombe can serve as a model organism to provide insight into the mechanisms of protein processing and folding within the cell
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