The impact of M&A on the R&D process. An empirical analysis of the role of technological and market relatedness.

While the impact of M&A on R&D and innovation examined at the aggregate level left inconclusive evidence, we find that at the level of the R&D process both the technological and market relatedness between the target and acquirer are helpful dimensions to identify effects. Using information on 31 in-depth cases of individual M&A deals we show that technological relatedness between M&A partners directly affects the inputs and organizational structure of the R&D process. M&A partners that operate in the same technological fields tend to reduce their R&D effort and rationalize the R&D process after the M&A compared to firms active in complementary technological fields that merge. These firms will furthermore face less technological competition in the technology market, but risk creating a more bureaucratic R&D process with a less motivated workforce. Market relatedness between partners, while having comparable aggregate effects on the R&D process, operates on different dimensions of the R&D process. Former rivals that engage in a M&A are significantly less likely to expand into new R&D fields or leverage their technological competences across the products and markets of the new entity. Non-rival firms that join forces, on the contrary, significantly increase R&D output and productivity through these activities.Competition; Effects; Field; Firms; Information; Innovation; International; M&A; Market; Market relatedness; Markets; Organizational structure; Processes; Product; R&D; Risk; Scale and scope; Structure; Subsidiaries; Technolocal relatedness; Technology diffusion;

Hyperbolic Balance Laws with a Non Local Source

This paper is devoted to hyperbolic systems of balance laws with non local source terms. The existence, uniqueness and Lipschitz dependence proved here comprise previous results in the literature and can be applied to physical models, such as Euler system for a radiating gas and Rosenau regularization of the Chapman-Enskog expansion.Comment: 26 page

Indirect reciprocity and the evolution of prejudicial groups

Prejudicial attitudes are widely seen between human groups, with significant consequences. Actions taken in light of prejudice result in discrimination, and can contribute to societal division and hostile behaviours. We define a new class of group, the prejudicial group, with membership based on a common prejudicial attitude towards the out-group. It is assumed that prejudice acts as a phenotypic tag, enabling groups to form and identify themselves on this basis. Using computational simulation, we study the evolution of prejudicial groups, where members interact through indirect reciprocity. We observe how cooperation and prejudice coevolve, with cooperation being directed in-group. We also consider the co-evolution of these variables when out-group interaction and global learning are immutable, emulating the possible pluralism of a society. Diversity through three factors is found to be influential, namely out-group interaction, out-group learning and number of sub-populations. Additionally populations with greater in-group interaction promote both cooperation and prejudice, while global rather than local learning promotes cooperation and reduces prejudice. The results also demonstrate that prejudice is not dependent on sophisticated human cognition and is easily manifested in simple agents with limited intelligence, having potential implications for future autonomous systems and human-machine interaction

Shimura varieties in the Torelli locus via Galois coverings of elliptic curves

We study Shimura subvarieties of $\mathsf{A}_g$ obtained from families of Galois coverings $f: C \rightarrow C'$ where $C'$ is a smooth complex projective curve of genus $g' \geq 1$ and $g= g(C)$. We give the complete list of all such families that satisfy a simple sufficient condition that ensures that the closure of the image of the family via the Torelli map yields a Shimura subvariety of $\mathsf{A}_g$ for $g' =1,2$ and for all $g \geq 2,4$ and for $g' > 2$ and $g \leq 9$. In a previous work of the first and second author together with A. Ghigi [FGP] similar computations were done in the case $g'=0$. Here we find 6 families of Galois coverings, all with $g' = 1$ and $g=2,3,4$ and we show that these are the only families with $g'=1$ satisfying this sufficient condition. We show that among these examples two families yield new Shimura subvarieties of $\mathsf{A}_g$, while the other examples arise from certain Shimura subvarieties of $\mathsf{A}_g$ already obtained as families of Galois coverings of $\mathbb{P}^1$ in [FGP]. Finally we prove that if a family satisfies this sufficient condition with $g'\geq 1$, then $g \leq 6g'+1$.Comment: 18 pages, to appear in Geometriae Dedicat

SPARC is a new myeloid-derived suppressor cell marker licensing suppressive activities

Myeloid-derived suppressor cells (MDSC) are well-known key negative regulators of the immune response during tumor growth, however scattered is the knowledge of their capacity to influence and adapt to the different tumor microenvironments and of the markers that identify those capacities. Here we show that the secreted protein acidic and rich in cysteine (SPARC) identifies in both human and mouse MDSC with immune suppressive capacity and pro-tumoral activities including the induction of epithelial-to-mesenchymal transition (EMT) and angiogenesis. In mice the genetic deletion of SPARC reduced MDSC immune suppression and reverted EMT. Sparc−/− MDSC were less suppressive overall and the granulocytic fraction was more prone to extrude neutrophil extracellular traps (NET). Surprisingly, arginase-I and NOS2, whose expression can be controlled by STAT3, were not down-regulated in Sparc−/− MDSC, although less suppressive than wild type (WT) counterpart. Flow cytometry analysis showed equal phosphorylation of STAT3 but reduced ROS production that was associated with reduced nuclear translocation of the NF-kB p50 subunit in Sparc−/− than WT MDSC. The limited p50 in nuclei reduce the formation of the immunosuppressive p50:p50 homodimers in favor of the p65:p50 inflammatory heterodimers. Supporting this hypothesis, the production of TNF by Sparc−/− MDSC was significantly higher than by WT MDSC. Although associated with tumor-induced chronic inflammation, TNF, if produced at high doses, becomes a key factor in mediating tumor rejection. Therefore, it is foreseeable that an unbalance in TNF production could skew MDSC toward an inflammatory, anti-tumor phenotype. Notably, TNF is also required for inflammation-driven NETosis. The high level of TNF in Sparc−/− MDSC might explain their increased spontaneous NET formation as that we detected both in vitro and in vivo, in association with signs of endothelial damage. We propose SPARC as a new potential marker of MDSC, in both human and mouse, with the additional feature of controlling MDSC suppressive activity while preventing an excessive inflammatory state through the control of NF-kB signaling pathway

Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks

The PC algorithm is a popular method for learning the structure of Gaussian Bayesian networks. It carries out statistical tests to determine absent edges in the network. It is hence governed by two parameters: (i) The type of test, and (ii) its significance level. These parameters are usually set to values recommended by an expert. Nevertheless, such an approach can suffer from human bias, leading to suboptimal reconstruction results. In this paper we consider a more principled approach for choosing these parameters in an automatic way. For this we optimize a reconstruction score evaluated on a set of different Gaussian Bayesian networks. This objective is expensive to evaluate and lacks a closed-form expression, which means that Bayesian optimization (BO) is a natural choice. BO methods use a model to guide the search and are hence able to exploit smoothness properties of the objective surface. We show that the parameters found by a BO method outperform those found by a random search strategy and the expert recommendation. Importantly, we have found that an often overlooked statistical test provides the best over-all reconstruction results

Influence of vestibular and visual stimulation on split-belt walking

We investigated the influence of vestibular (caloric ear irrigation) and visual (optokinetic) stimulation on slow and fast split-belt walking. The velocity of one belt was fixed (1.5 or 5.0-6.0km/h) and subjects (N=8 for vestibular and N=6 for visual experiments) were asked to adjust the velocity of the other belt to a level at which they perceived the velocity of both the belts as equal. Throughout all experiments, subjects bimanually held on to the space-fixed handles along the treadmill, which provided haptic information on body orientation. While the optokinetic stimulus (displayed on face-mounted virtual reality goggles) had no effect on belt velocity adjustments compared to control trials, cold-water ear irrigation during slow (but not fast) walking effectively influenced belt velocity adjustments in seven of eight subjects. Only two of these subjects decreased the velocity of the ipsilateral belt, consistent with the ipsilateral turning toward the irrigated ear in the Fukuda stepping test. The other five subjects, however, increased the velocity of the ipsilateral belt. A straight-ahead sense mechanism can explain both decreased and increased velocity adjustments. Subjects decrease or increase ipsilateral belt velocity depending on whether the vestibular stimulus is interpreted as an indicator of the straight-ahead direction (decreased velocity) or as an error signal relative to the straight-ahead direction provided by the haptic input from the space-fixed handles along the treadmill (increased velocity). The missing effect during fast walking corroborates the findings by others that the influence of vestibular tone asymmetry on locomotion decreases at higher gait velocitie

Current Knowledge of Trichosporon spp. and Trichosporonosis

Trichosporon spp. are basidiomycetous yeast-like fungi found widely in nature. Clinical isolates are generally related to superficial infections. However, this fungus has been recognized as an opportunistic agent of invasive infections, mostly in cancer patients and those exposed to invasive medical procedures. It is possible that the ability of Trichosporon strains to form biofilms on implanted devices, the presence of glucuronoxylomannan in their cell walls, and the ability to produce proteases and lipases are all factors likely related to the virulence of this genus and therefore may account for the progress of invasive trichosporonosis. Disseminated trichosporonosis has been increasingly reported worldwide and represents a challenge for both diagnosis and species identification. Phenotypic identification methods are useful for Trichosporon sp. screening, but only molecular methods, such as IGS region sequencing, allow the complete identification of Trichosporon isolates at the species level. Methods for the diagnosis of invasive trichosporonosis include PCR-based methods, Luminex xMAP technology, and, more recently, proteomics. Treating patients with trichosporonosis remains a challenge because of limited data on the in vitro and in vivo activities of antifungal drugs against clinically relevant species of the genus. Despite the mentioned limitations, the use of antifungal regimens containing triazoles appears to be the best therapeutic approach.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Federal de São Paulo, Lab Especial Micol, Disciplina Infectol, BR-04023062 São Paulo, BrazilUniv Fed Rio Grande do Norte, Lab Micol Med Mol, Dept Anal Clin Toxicol, BR-59072970 Natal, RN, BrazilUniversidade Federal de São Paulo, Lab Especial Micol, Disciplina Infectol, BR-04023062 São Paulo, BrazilFAPESP: 2005/02006-0FAPESP: 2005/04442-1FAPESP: 2007/08575-1CNPq: 308011/2010-4CAPES: PNPD 02640-09-0Web of Scienc

Deriving amino acid contact potentials from their frequencies of occurence in proteins: a lattice model study

The possibility of deriving the contact potentials between amino acids from their frequencies of occurence in proteins is discussed in evolutionary terms. This approach allows the use of traditional thermodynamics to describe such frequencies and, consequently, to develop a strategy to include in the calculations correlations due to the spatial proximity of the amino acids and to their overall tendency of being conserved in proteins. Making use of a lattice model to describe protein chains and defining a "true" potential, we test these strategies by selecting a database of folding model sequences, deriving the contact potentials from such sequences and comparing them with the "true" potential. Taking into account correlations allows for a markedly better prediction of the interaction potentials