Automorphisms of graphs of cyclic splittings of free groups

We prove that any isometry of the graph of cyclic splittings of a finitely generated free group $F_N$ of rank $N\ge 3$ is induced by an outer automorphism of $F_N$. The same statement also applies to the graphs of maximally-cyclic splittings, and of very small splittings.Comment: 22 pages, 5 figures. Small modifications. To appear in Geometriae Dedicat

Asher Lev at the Israel Museum: Stereotyping art and craft

Jesper Svartvik and Jakob Wirén (Eds.), Religious stereotyping and interreligious relations. New York: Palgrave Macmillan, 2013, reproduced with permission of Palgrave Macmillan. This extract is taken from the author's original manuscript and has not been edited. The definitive, published version of record is available here: http://www.palgrave.com/page/detail/religious-stereotyping-and-interreligious-relations-jesper-svartvik/?K=9781137344601 and http://www.palgraveconnect.com/pc/doifinder/10.1057/978113734267

Holoprosencephaly

Holoprosencephaly (HPE) is a complex brain malformation resulting from incomplete cleavage of the prosencephalon, occurring between the 18th and the 28th day of gestation and affecting both the forebrain and the face. It is estimated to occur in 1/16,000 live births and 1/250 conceptuses. Three ranges of increasing severity are described: lobar, semi-lobar and alobar HPE. Another milder subtype of HPE called middle interhemispheric variant (MIHF) or syntelencephaly is also reported. In most of the cases, facial anomalies are observed in HPE, like cyclopia, proboscis, median or bilateral cleft lip/palate in severe forms, ocular hypotelorism or solitary median maxillary central incisor in minor forms. These latter midline defects can occur without the cerebral malformations and then are called microforms. Children with HPE have many medical problems: developmental delay and feeding difficulties, epilepsy, instability of temperature, heart rate and respiration. Endocrine disorders like diabetes insipidus, adrenal hypoplasia, hypogonadism, thyroid hypoplasia and growth hormone deficiency are frequent. To date, seven genes have been positively implicated in HPE: Sonic hedgehog (SHH), ZIC2, SIX3, TGIF, PTCH, GLI2 and TDGF1. A molecular diagnosis can be performed by gene sequencing and allele quantification for the four main genes SHH, ZIC2, SIX3 and TGIF. Major rearrangements of the subtelomeres can also be identified by multiplex ligation-dependent probe amplification (MLPA). Nevertheless, in about 70% of cases, the molecular basis of the disease remains unknown, suggesting the existence of several other candidate genes or environmental factors. Consequently, a "multiple-hit hypothesis" of genetic and/or environmental factors (like maternal diabetes) has been proposed to account for the extreme clinical variability. In a practical approach, prenatal diagnosis is based on ultrasound and magnetic resonance imaging (MRI) rather than on molecular diagnosis. Treatment is symptomatic and supportive, and requires a multidisciplinary management. Child outcome depends on the HPE severity and the medical and neurological complications associated. Severely affected children have a very poor prognosis. Mildly affected children may exhibit few symptoms and may live a normal life

Event Monitoring System to Classify Unexpected Events for Production Planning

[EN] Production planning prepares companies to a future production scenario. The decision process followed to obtain the production plan considers real data and estimated data of this future scenario. However, these plans can be affected by unexpected events that alter the planned scenario and in consequence, the production planning. This is especially critical when the production planning is ongoing. Thus providing information about these events can be critical to reconsider the production planning. We herein propose an event monitoring system to identify events and to classify them into different impact levels. The information obtained from this system helps to build a risk matrix, which determines the significance of the risk from the impact level and the likelihood. A prototype has been built following this proposal.This research has been carried out in the framework of the project GV/2014/010 funded by the Generalitat Valenciana (Identificacion de la informacion proporcionada por los nuevos sistemas de deteccion accesibles mediante internet en el ambito de las "sensing enterprises" para la mejora de la toma de decisiones en la planificacion de la produccion).Boza, A.; Alarcón Valero, F.; Alemany Díaz, MDM.; Cuenca, L. (2017). Event Monitoring System to Classify Unexpected Events for Production Planning. Lecture Notes in Business Information Processing. 291:140-154. https://doi.org/10.1007/978-3-319-62386-3_7S140154291Barták, R.: On the boundary of planning and scheduling: a study (1999)Buzacott, J.A., Corsten, H., Gössinger, R., Schneider, H.M.: Production Planning and Control: Basics and Concepts. Oldenbourg Wissenschaftsverlag, München (2012)Özdamar, L., Bozyel, M.A., Birbil, S.I.: A hierarchical decision support system for production planning (with case study). Eur. J. Oper. Res. 104(3), 403–422 (1998)Van Wezel, W., Van Donk, D.P., Gaalman, G.: The planning flexibility bottleneck in food processing industries. J. Oper. Manag. 24(3), 287–300 (2006)Shamsuzzoha, A.H., Rintala, S., Cunha, P.F., Ferreira, P.S., Kankaanpää, T., Maia Carneiro, L.: Event monitoring and management process in a non-hierarchical business network. In: Intelligent Non-hierarchical Manufacturing Networks, pp. 349–374. Wiley, Hoboken (2013)Sacala, I.S., Moisescu, M.A., Repta, D.: Towards the development of the future internet based enterprise in the context of cyber-physical systems. In: 19th International Conference on Control Systems and Computer Science, CSCS 2013, pp. 405–412 (2013)Chen, K.C.: Decision support system for tourism development: system dynamics approach. J. Comput. Inf. Syst. 45(1), 104–112 (2004)Boza, A., Alemany, M.M.E., Vicens, E., Cuenca, L.: Event management in decision-making processes with decision support systems. In: 5th International Conference on Computers Communications and Control (2014)Liao, S.-H.: Expert system methodologies and applications–a decade review from 1995 to 2004. Expert Syst. Appl. 28(1), 93–103 (2005)ISO: 73: 2009: Risk management vocabulary. International Organization for Standardization (2009)Chan, F.T.S., Au, K.C., Chan, P.L.Y.: A decision support system for production scheduling in an ion plating cell. Expert Syst. Appl. 30(4), 727–738 (2006)Weinstein, L., Chung, C.-H.: Integrating maintenance and production decisions in a hierarchical production planning environment. Comput. Oper. Res. 26(10–11), 1059–1074 (1999)Poon, T.C., Choy, K.L., Chan, F.T.S., Lau, H.C.W.: A real-time production operations decision support system for solving stochastic production material demand problems. Expert Syst. Appl. 38(5), 4829–4838 (2011)SAP AG: SAP AG 2014. Next-Generation Business and the Internet of Things. Studio SAP | 27484enUS (14/03) (2014)Carneiro, L.M., Cunha, P., Ferreira, P.S., Shamsuzzoha, A.: Conceptual framework for non-hierarchical business networks for complex products design and manufacturing. Procedia CIRP 7, 61–66 (2013)Vargas, A., Cuenca, L., Boza, A., Sacala, I., Moisescu, M.: Towards the development of the framework for inter sensing enterprise architecture. J. Intell. Manuf. 26, 55–72 (2016)Barash, G., Bartolini, C., Wu, L.: Measuring and improving the performance of an IT support organization in managing service incidents, pp. 11–18 (2007)Liu, R., Kumar, A., van der Aalst, W.: A formal modeling approach for supply chain event management. Decis. Support Syst. 43(3), 761–778 (2007)Söderholm, A.: Project management of unexpected events. Int. J. Proj. Manag. 26(1), 80–86 (2008)Bearzotti, L.A., Salomone, E., Chiotti, O.J.: An autonomous multi-agent approach to supply chain event management. Int. J. Prod. Econ. 135(1), 468–478 (2012)Baron, M.M., Pate-Cornell, M.E.: Designing risk-management strategies for critical engineering systems. IEEE Trans. Eng. Manag. 46(1), 87–100 (1999)Bartolini, C., Stefanelli, C., Tortonesi, M.: SYMIAN: analysis and performance improvement of the IT incident management process. IEEE Trans. Netw. Serv. Manag. 7(3), 132–144 (2010)Cox Jr., L.A.: What’s wrong with risk matrices? Risk Anal. Int. J. 28(2), 497–512 (2008)Shim, J.P., Warkentin, M., Courtney, J.F., Power, D.J., Sharda, R., Carlsson, C.: Past, present, and future of decision support technology. Decis. Support Syst. 33(2), 111–126 (2002)Steiger, D.M.: Enhancing user understanding in a decision support system: a theoretical basis and framework (2015). http://dx.doi.org/10.1080/07421222.1998.11518214Turban, E., Aronson, J., Liang, T.-P.: Decision Support Systems and Intelligent Systems, 7th edn. Pearson Prentice Hall, Upper Saddle River (2005)Turban, E., Watkins, P.R.: Integrating expert systems and decision support systems, 10, 121–136 (1986)Cohen, D., Asín, E.: Sistemas de información para los negocios: un enfoque de toma de decisiones. McGraw-Hill, New York City (2001)Boza, A., Cortés, B., Alemany, M.M.E., Vicens, E.: Event monitoring software application for production planning systems. In: Cortés, P., Maeso-González, E., Escudero-Santana, A. (eds.) Enhancing Synergies in a Collaborative Environment. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-14078-0_14Boza, A., Alarcón, F., Alemany, M.M.E., Cuenca, L.: Event classification system to reconsider the production planning. 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The inheritance of seed dormancy in Sinapis arvensis L

Selection for dormant and non-dormant seed in Sinapis arvensis was carried to the seventh and fourteenth generation, respectively. Crosses between the dormant and non-dormant lines clearly showed both a maternal and an embryonic component of seed dormancy. A model for the number of alleles controlling dormancy was constructed and tested. The maternal component of dormancy was shown to be controlled by a single locus with two alleles, the dormant allele being dominant to the non-dormant. No clear picture of the control of the embryonic component of dormancy was found

Effects of Thyroxine Exposure on Osteogenesis in Mouse Calvarial Pre-Osteoblasts

The incidence of craniosynostosis is one in every 1,800-2500 births. The gene-environment model proposes that if a genetic predisposition is coupled with environmental exposures, the effects can be multiplicative resulting in severely abnormal phenotypes. At present, very little is known about the role of gene-environment interactions in modulating craniosynostosis phenotypes, but prior evidence suggests a role for endocrine factors. Here we provide a report of the effects of thyroid hormone exposure on murine calvaria cells. Murine derived calvaria cells were exposed to critical doses of pharmaceutical thyroxine and analyzed after 3 and 7 days of treatment. Endpoint assays were designed to determine the effects of the hormone exposure on markers of osteogenesis and included, proliferation assay, quantitative ALP activity assay, targeted qPCR for mRNA expression of Runx2, Alp, Ocn, and Twist1, genechip array for 28,853 targets, and targeted osteogenic microarray with qPCR confirmations. Exposure to thyroxine stimulated the cells to express ALP in a dose dependent manner. There were no patterns of difference observed for proliferation. Targeted RNA expression data confirmed expression increases for Alp and Ocn at 7 days in culture. The genechip array suggests substantive expression differences for 46 gene targets and the targeted osteogenesis microarray indicated 23 targets with substantive differences. 11 gene targets were chosen for qPCR confirmation because of their known association with bone or craniosynostosis (Col2a1, Dmp1, Fgf1, 2, Igf1, Mmp9, Phex, Tnf, Htra1, Por, and Dcn). We confirmed substantive increases in mRNA for Phex, FGF1, 2, Tnf, Dmp1, Htra1, Por, Igf1 and Mmp9, and substantive decreases for Dcn. It appears thyroid hormone may exert its effects through increasing osteogenesis. Targets isolated suggest a possible interaction for those gene products associated with calvarial suture growth and homeostasis as well as craniosynostosis. © 2013 Cray et al

A canine model of Cohen syndrome: Trapped Neutrophil Syndrome

<p>Abstract</p> <p>Background</p> <p>Trapped Neutrophil Syndrome (TNS) is a common autosomal recessive neutropenia in Border collie dogs.</p> <p>Results</p> <p>We used a candidate gene approach and linkage analysis to show that the causative gene for TNS is <it>VPS13B</it>. We chose <it>VPS13B </it>as a candidate because of similarities in clinical signs between TNS and Cohen syndrome, in human, such as neutropenia and a typical facial dysmorphism. Linkage analysis using microsatellites close to <it>VPS13B </it>showed positive linkage of the region to TNS. We sequenced each of the 63 exons of <it>VPS13B </it>in affected and control dogs and found that the causative mutation in Border collies is a 4 bp deletion in exon 19 of the largest transcript that results in premature truncation of the protein. Cohen syndrome patients present with mental retardation in 99% of cases, but learning disabilities featured in less than half of TNS affected dogs. It has been implied that loss of the alternate transcript of <it>VPS13B </it>in the human brain utilising an alternate exon, 28, may cause mental retardation. Mice cannot be used to test this hypothesis as they do not express the alternate exon. We show that dogs do express alternate transcripts in the brain utilising an alternate exon homologous to human exon 28.</p> <p>Conclusion</p> <p>Dogs can be used as a model organism to explore the function of the alternately spliced transcript of VPS13B in the brain. TNS in Border collies is the first animal model for Cohen syndrome and can be used to study the disease aetiology.</p

The Ups and Downs of Mutation Frequencies during Aging Can Account for the Apert Syndrome Paternal Age Effect

Apert syndrome is almost always caused by a spontaneous mutation of paternal origin in one of two nucleotides in the fibroblast growth factor receptor 2 gene (FGFR2). The incidence of this disease increases with the age of the father (paternal age effect), and this increase is greater than what would be expected based on the greater number of germ-line divisions in older men. We use a highly sensitive PCR assay to measure the frequencies of the two causal mutations in the sperm of over 300 normal donors with a wide range of ages. The mutation frequencies increase with the age of the sperm donors, and this increase is consistent with the increase in the incidence rate. In both the sperm data and the birth data, the increase is non-monotonic. Further, after normalizing for age, the two Apert syndrome mutation frequencies are correlated within individual sperm donors. We consider a mathematical model for germ-line mutation which reproduces many of the attributes of the data. This model, with other evidence, suggests that part of the increase in both the sperm data and the birth data is due to selection for mutated premeiotic cells. It is likely that a number of other genetic diseases have similar features