The nesting problem, also known as irregular packing problem, belongs to the generic class of cutting and packing (C&P) problems. It di↵ers from other 2-D C&P problems in the irregular shape of the pieces. This paper proposes a new mixed-integer model in which binary decision variables are associated with each discrete point of the board (a dot) and with each piece type. It is much more flexible than previously proposed formulations and solves to optimality larger instances of the nesting problem, at the cost of having its precision dependent on board discretization. To date no results have been published concerning optimal solutions for nesting problems with more than 7 pieces. We ran computational experiments on 45 problem instances with the new model, solving to optimality 34 instances with a total number of pieces ranging from 16 to 56, depending on the number of piece types, grid resolution and the size of the board. A strong advantage of the model is its insensitivity to piece and board geometry, making it easy to extend to more complex problems such as non-convex boards, possibly with defects. Additionally, the number of binary variables does not depend on the total number of pieces but on the number of piece types, making the model particularly suitable for problems with few piece types. The discrete nature of the model requires a trade-o↵ between grid resolution and problem size, as the number of binary variables grows with the square of the selected grid resolution and with board size.

When the genotype of primary tumors is compared with the genotype of LNMs, the concordance is high for all the genes studied. On the other hand, distant metastases show an enrichment in TERTp mutations and a decrease in BRAF mutations. TERTp mutations may play a role in distant metastases.

Research data management is rapidly becoming a regular concern for researchers, and institutions need to provide them with platforms to support data organization and preparation for publication. Some institutions have adopted institutional repositories as the basis for data deposit, whereas others are experimenting with richer environments for data description, in spite of the diversity of existing workflows. This paper is a synthetic overview of current platforms that can be used for data management purposes. Adopting a pragmatic view on data management, the paper focuses on solutions that can be adopted in the longtail of science, where investments in tools and manpower are modest. First, a broad set of data management platforms is presented-some designed for institutional repositories and digital libraries-to select a short list of the more promising ones for data management. These platforms are compared considering This paper is an extended version of a previously published comparative study. Please refer to the WCIST 2015 conference proceedings

When rhTSH was used, stimulated Tg at ablation had independent predictive value for disease-free status 1 year later. A low stimulated Tg at rhTSH-aided ablation may be considered a favorable prognosis factor.