Fiddle tunes of the old frontier

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Market Thickness, Sunk Entry Costs, Firm Heterogeneity and the Outsourcing Decision: Empirical Evidence of Manufacturing Firms in France

In this paper I investigate, empirically, the outsourcing strategy by firms in French manufacturing industries. I particularly focus on the effect of the market thickness and of firm heterogeneity on the outsourcing strategy. For this purpose, I estimate a dynamic probit model where I link the decision to outsource to previous outsourcing behaviour. I am able to estimate the sunk entry costs incurred by the firms when adopting an outsourcing strategy. The results show that outsourcing is a persistent strategy adopted by more productive firms and larger ones. They also show that market thickness reduces search costs and enhances the establishment of outsourcing relationships.Outsourcing, Firm Heterogeneity, Dynamic Binary Choice Models, Market Thickness

Resurrection of the genus Staphisagria J. Hill, sister to all the other Delphinieae (Ranunculaceae)

Molecular sequence data show that the three species of Delphinium subg. Staphisagria (J. Hill) Peterm. form the sister clade to Aconitum L., Aconitella Spach, Consolida (DC.) S.F. Gray, and all remaining species of Delphinium L. To account for this finding we resurrect Staphisagria J. Hill (1756). Names in Staphisagria are available for two of the species. We here make the required new combination for the third species, Staphisagria picta (Willd.) F. Jabbour, provide a key to the species, and illustrate one of them

A Mining-Based Compression Approach for Constraint Satisfaction Problems

In this paper, we propose an extension of our Mining for SAT framework to Constraint satisfaction Problem (CSP). We consider n-ary extensional constraints (table constraints). Our approach aims to reduce the size of the CSP by exploiting the structure of the constraints graph and of its associated microstructure. More precisely, we apply itemset mining techniques to search for closed frequent itemsets on these two representation. Using Tseitin extension, we rewrite the whole CSP to another compressed CSP equivalent with respect to satisfiability. Our approach contrast with previous proposed approach by Katsirelos and Walsh, as we do not change the structure of the constraints.Comment: arXiv admin note: substantial text overlap with arXiv:1304.441

"Society of Hematologic Oncology (SOHO) State of the Art Updates and Next Questions"-Treatment of ALL.

The outcome of adult acute lymphoblastic leukemia (ALL) has substantially improved by adopting pediatric-inspired regimens, and approximately half of the patients are nowadays cured. The evaluation of minimal residual disease currently represents the most important prognostic indicator, which drives treatment algorithms, which include allogeneic stem cell transplantation (allo-SCT) allocation. Indeed, for high-risk patients, allo-SCT should be pursued as soon as possible, whereas in standard-risk patients this procedure should be avoided also in light of related toxicity and because there are no significant benefits. Furthermore, better characterization of the molecular genetic events can drive therapeutic decisions: a historical example in this respect is represented by the use of tyrosine kinase inhibitors (TKIs) in Philadelphia chromosome-positive ALL; in the upcoming future, TKIs might be used also in other subgroups, such as breakpoint cluster region/Abelson 1-like cases and others with deregulated tyrosine kinases. Finally, the greatest progress is currently achieved with new immunotherapies targeting frequently expressed surface antigens in ALL. It is also a new chance for elderly ALL patients, so far spared from intensive chemotherapy and allo-SCT. These targeted therapies will substantially change this treatment algorithm and the great challenge is to find optimal sequence of the extended therapy options in an individual patient

Learning for Dynamic subsumption

In this paper a new dynamic subsumption technique for Boolean CNF formulae is proposed. It exploits simple and sufficient conditions to detect during conflict analysis, clauses from the original formula that can be reduced by subsumption. During the learnt clause derivation, and at each step of the resolution process, we simply check for backward subsumption between the current resolvent and clauses from the original formula and encoded in the implication graph. Our approach give rise to a strong and dynamic simplification technique that exploits learning to eliminate literals from the original clauses. Experimental results show that the integration of our dynamic subsumption approach within the state-of-the-art SAT solvers Minisat and Rsat achieves interesting improvements particularly on crafted instances