Searches for vector-like quarks at future colliders and implications for composite Higgs models with dark matter

Many composite Higgs models predict the existence of vector-like quarks with masses outside the reach of the LHC, e.g. mQ 73 2 TeV, in particular if these models contain a dark matter candidate. In such models the mass of the new resonances is bounded from above to satisfy the constraint from the observed relic density. We therefore develop new strategies to search for vector-like quarks at a future 100 TeV collider and evaluate what masses and interactions can be probed. We find that masses as large as 3c 6.4 ( 3c9) TeV can be tested if the fermionic resonances decay into Standard Model (dark matter) particles. We also discuss the complementarity of dark matter searches, showing that most of the parameter space can be closed. On balance, this study motivates further the consideration of a higher-energy hadron collider for a next generation of facilities

Paleo-landscapes of the Northern Patagonian Massif, Argentina

Fil: Aguilera, Emilia Yolanda. Instituto de Geomorfología y Suelos (IGS). Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; ArgentinaFil: Rabassa, Jorge. Laboratorio de Geomorfología y Cuaternario. CADIC. Universidad Nacional de Tierra del Fuego; ArgentinaFil: Aragón, Eugenio. Centro de Investigaciones Geológicas (CIG). Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; Argentin

Opinion dynamics: models, extensions and external effects

Recently, social phenomena have received a lot of attention not only from social scientists, but also from physicists, mathematicians and computer scientists, in the emerging interdisciplinary field of complex system science. Opinion dynamics is one of the processes studied, since opinions are the drivers of human behaviour, and play a crucial role in many global challenges that our complex world and societies are facing: global financial crises, global pandemics, growth of cities, urbanisation and migration patterns, and last but not least important, climate change and environmental sustainability and protection. Opinion formation is a complex process affected by the interplay of different elements, including the individual predisposition, the influence of positive and negative peer interaction (social networks playing a crucial role in this respect), the information each individual is exposed to, and many others. Several models inspired from those in use in physics have been developed to encompass many of these elements, and to allow for the identification of the mechanisms involved in the opinion formation process and the understanding of their role, with the practical aim of simulating opinion formation and spreading under various conditions. These modelling schemes range from binary simple models such as the voter model, to multi-dimensional continuous approaches. Here, we provide a review of recent methods, focusing on models employing both peer interaction and external information, and emphasising the role that less studied mechanisms, such as disagreement, has in driving the opinion dynamics. [...]Comment: 42 pages, 6 figure

Anti-cancer drug validation: the contribution of tissue engineered models

Abstract Drug toxicity frequently goes concealed until clinical trials stage, which is the most challenging, dangerous and expensive stage of drug development. Both the cultures of cancer cells in traditional 2D assays and animal studies have limitations that cannot ever be unraveled by improvements in drug-testing protocols. A new generation of bioengineered tumors is now emerging in response to these limitations, with potential to transform drug screening by providing predictive models of tumors within their tissue context, for studies of drug safety and efficacy. Considering the NCI60, a panel of 60 cancer cell lines representative of 9 different cancer types: leukemia, lung, colorectal, central nervous system (CNS), melanoma, ovarian, renal, prostate and breast, we propose to review current Bstate of art^ on the 9 cancer types specifically addressing the 3D tissue models that have been developed and used in drug discovery processes as an alternative to complement their studyThis article is a result of the project FROnTHERA (NORTE-01-0145-FEDER-000023), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This article was also supported by the EU Framework Programme for Research and Innovation HORIZON 2020 (H2020) under grant agreement n° 668983 — FoReCaST. FCT distinction attributed to Joaquim M. Oliveira (IF/00423/2012) and Vitor M. Correlo (IF/01214/2014) under the Investigator FCT program is also greatly acknowledged.info:eu-repo/semantics/publishedVersio

A two-component pre-seeded dermal-epidermal scaffold

We have developed a bilayered dermal-epidermal scaffold for application in the treatment of full-thickness skin defects. The dermal component gels in situ and adapts to the lesion shape, delivering human dermal fibroblasts in a matrix of fibrin and cross-linked hyaluronic acid modified with a cell adhesion-promoting peptide. Fibroblasts were able to form a tridimensional matrix due to material features such as tailored mechanical properties, presence of protease-degradable elements and cell-binding ligands. The epidermal component is a robust membrane containing cross-linked hyaluronic acid and poly-l-lysine, on which keratinocytes were able to attach and to form a monolayer. Amine-aldehyde bonding at the interface between the two components allows the formation of a tightly bound composite scaffold. Both parts of the scaffold were designed to provide cell-type-specific cues to allow for cell proliferation and form a construct that mimics the skin environment.D.S.K. acknowledges funding from the Biotechnology Research Endowment from the Department of Anesthesiology at Boston Children's Hospital. I.P.M. acknowledges the Portuguese Foundation for Science and Technology for the grant BD/39396/2007 and the MIT-Portugal Program. D.G. acknowledges the Swiss National Science Foundation for a post-doctoral fellowship (PBGEP3-129111). B.P.T. acknowledges an NIR Ruth L. Kirschstein National Research Service Award (F32GM096546)