Metastability at the Yield-Stress Transition in Soft Glasses

We study the solid-to-liquid transition in a two-dimensional fully periodic soft-glassy model with an imposed spatially heterogeneous stress. The model we consider consists of droplets of a dispersed phase jammed together in a continuous phase. When the peak value of the stress gets close to the yield stress of the material, we find that the whole system intermittently tunnels to a metastable "fluidized" state, which relaxes back to a metastable "solid" state by means of an elastic-wave dissipation. This macroscopic scenario is studied through the microscopic displacement field of the droplets, whose time statistics displays a remarkable bimodality. Metastability is rooted in the existence, in a given stress range, of two distinct stable rheological branches as well as long-range correlations (e.g., large dynamic heterogeneity) developed in the system. Finally, we show that a similar behavior holds for a pressure-driven flow, thus suggesting possible experimental tests.Comment: 13 pages, 11 figure

The multimode covering location problem

In this paper we introduce the Multimode Covering Location Problem. This is a generalization of the Maximal Covering Location Problem that consists in locating a given number of facilities of different types with a limitation on the number of facilities sharing the same site. The problem is challenging and intrinsically much harder than its basic version. Nevertheless, it admits a constant factor approximation guarantee, which can be achieved combining two greedy algorithms. To improve the greedy solutions, we have developed a Variable Neighborhood Search approach, based on an exponential-size neighborhood. This algorithm computes good quality solutions in short computational time. The viability of the approach here proposed is also corroborated by a comparison with a Heuristic Concentration algorithm, which is presently the most effective approach to solve large instances of the Maximal Covering Location Problem

Multimode extensions of combinatorial optimization problems

We review some complexity results and present a viable heuristic approach based on the Variable Neighborhood Search (VNS) framework for multimode extension of combinatorial optimization problems, such as the the Set Covering Problem (SCP) and the Covering Location Problem (CLP)

Warm-season turfgrass species generate sports surfaces with different playability

Synthetic sports surfaces are increasingly subject to standardization of athlete-surface and ball-surface interactions (playability parameters). Such standardizations have led to an increase in the level of the engineering and predictability of these surfaces, and as such may be beneficial also for natural turf. In warm and temperate climates, many natural turf sports surfaces are established with warm-season (C4) turfgrass species due to their suitability to the environment in such areas. This study was aimed at evaluating the Féderation Internationale de Football Association (FIFA)-standard playing characteristics of different sports turf surfaces obtained from three commonly used C4 turfgrass species: 1) ‘Tifway 419’ hybrid bermudagrass (Cynodon dactylon var. dactylon × C. transvaalensis), 2) ‘Zeon’ manilagrass (Zoysia matrella), and 3) ‘Salam’ seashore paspalum (Paspalum vaginatum) for factors concerning leaf tissue (silica, lignin, water content) and canopy structure (shoot density, leaf architecture, stolon density, etc.). Results showed that surfaces of different C4 turfgrass species generate different playability parameters, with seashore paspalum being a harder faster surface, manilagrass being a softer slower surface, and hybrid bermudagrass showing intermediate characteristics. These playing quality results were associated with certain specific canopy biometrical/morphological parameters such as shoot density, horizontal stem density (HSD), leaf section, and, to a lesser extent, to certain plant tissue compounds (lignin, silica)

The Northern Cross Fast Radio Burst project -- III. The FRB-magnetar connection in a sample of nearby galaxies

Fast radio bursts (FRBs) are millisecond radio transients observed at cosmological distances. The nature of their progenitors is still a matter of debate, although magnetars are invoked by most models. The proposed FRB-magnetar connection was strengthened by the discovery of an FRB-like event from the Galactic magnetar SGR J1935+2154. In this work, we aim to investigate how prevalent magnetars such as SGR J1935+2154 are within FRB progenitors. We carried out an FRB search in a sample of seven nearby (< 12 Mpc) galaxies with the Northern Cross radio telescope for a total of 692 h. We detected one 1.8 ms burst in the direction of M101 with a fluence of $58 \pm 5$ Jy ms. Its dispersion measure of 303 pc cm$^{-3}$ places it most-likely beyond M101. Considering that no significant detection comes indisputably from the selected galaxies, we place a 38 yr$^{-1}$ upper limit on the total burst rate (i.e. including the whole sample) at the 95\% confidence level. This upper limit constrains the event rate per magnetar $\lambda_{\rm mag} < 0.42$ magnetar$^{-1}$ yr$^{-1}$ or, if combined with literature observations of a similar sample of nearby galaxies, it yields a joint constraint of $\lambda_{\rm mag} < 0.25$ magnetar$^{-1}$ yr$^{-1}$. We also provide the first constraints on the expected rate of FRBs hypothetically originating from ultraluminous X-ray (ULX) sources, since some of the galaxies observed during our observational campaign host confirmed ULXs. We obtain $< 13$ yr$^{-1}$ per ULX for the total sample of galaxies observed. Our results indicate that bursts with energies $E>10^{34}$ erg from magnetars like SGR J1935+2154 appear more rarely compared to previous observations and further disfavour them as unique progenitors for the cosmological FRB population, leaving more space open to the contribution from a population of more exotic magnetars, not born via core-collapsed supernovae.Comment: 9 pages, 4 figures, published in A&

Glioblastoma endothelium drives bevacizumab-induced infiltrative growth via modulation of PLXDC1

Bevacizumab, a VEGF-targeting monoclonal antibody, may trigger an infiltrative growth pattern in glioblastoma. We investigated this pattern using both a human specimen and rat models. In the human specimen, a substantial fraction of infiltrating tumor cells were located along perivascular spaces in close relationship with endothelial cells. Brain xenografts of U87MG cells treated with bevacizumab were smaller than controls (p = 0.0055; Student t-test), however, bands of tumor cells spread through the brain farther than controls (p < 0.001; Student t-test). Infiltrating tumor Cells exhibited tropism for vascular structures and propensity to form tubules and niches with endothelial cells. Molecularly, bevacizumab triggered an epithelial to mesenchymal transition with over-expression of the receptor Plexin Domain Containing 1 (PLXDC1). These results were validated using brain xenografts of patient-derived glioma stem-like cells. Enforced expression of PLXDC1 in U87MG cells promoted brain infiltration along perivascular spaces. Importantly, PLXDC1 inhibition prevented perivascular infiltration and significantly increased the survival of bevacizumab-treated rats. Our study indicates that bevacizumab-induced brain infiltration is driven by vascular endothelium and depends on PLXDC1 activation of tumor cells

Deregulated expression of the imprinted DLK1-DIO3 region in Glioblastoma Stem-like Cells: tumor suppressor role of lncRNA MEG3

Background: Glioblastoma (GBM) stem-like cells (GSCs) are thought to be responsible for the maintenance and aggressiveness of GBM, the most common primary brain tumor in adults. This study aims at elucidating the involvement of deregulations within the imprinted DLK-DIO3 region on chromosome 14q32 in GBM pathogenesis. Methods: RT-PCR analyses were performed on GSCs and GBM tissues. Methylation analyses, gene expression and Reverse-Phase protein Array profiles were used to investigate the tumor suppressor function of MEG3. Results: Loss of expression of genes and non-coding RNAs within the DLK1-DIO3 region was observed in GSCs and GBM tissues compared to normal brain. This down-regulation is mainly mediated by epigenetic silencing. Kaplan-Meier analysis indicated that low expression of MEG3 and MEG8 lncRNAs significantly correlated with short survival in GBM patients. MEG3 restoration impairs tumorigenic abilities of GSCs in vitro by inhibiting cell growth, migration and colony formation and decreases in vivo tumor growth reducing infiltrative growth. These effects were associated with modulation of genes involved in cell adhesion and Epithelial to Mesenchymal Transition (EMT). Conclusions: In GBM, MEG3 acts as a tumor-suppressor mainly regulating cell adhesion, EMT and cell proliferation, thus providing a potential candidate for novel GBM therapies

Contributo al femminile all’educazione tecnica e scientifica per le materie STEM. Fare rete tra scienziate/i, enti, università, associazioni, media e portatori d’interesse

Questo “contributo al femminile” è stato realizzato da un gruppo di perso- ne che ambisce a contribuire al miglioramento dell’educazione scolastica; è destinato a donne, uomini, ragazze, ragazzi, bambine e bambini per mettere in luce potenzialità, diseguaglianze, specificità di vita e professionali e favorire la parità di genere soprattutto negli ambiti tecnico-scientifici, in particolar modo nelle discipline STEM (Science, Technology, Engineering, Mathematics)

An integer optimization approach for reverse engineering of gene regulatory networks

Gene regulatory networks are a common tool to describe the chemical interactions between genes in a living cell. This paper considers the Weighted Gene Regulatory Network (WGRN) problem, which consists in identifying a reduced set of interesting candidate regulatory elements which can explain the expression of all other genes. We provide an integer programming formulation based on a graph model and derive from it a branch-and-bound algorithm which exploits the Lagrangian relaxation of suitable constraints. This allows to determine lower bounds tighter than CPLEX on most benchmark instances, with the exception of the sparser ones. In order to determine feasible solutions for the problem, which appears to be a hard task for general-purpose solvers, we also develop and compare two metaheuristic approaches, namely a Tabu Search and a Variable Neighborhood Search algorithm. The experiments performed on both of them suggest that diversification is a key feature to solve the problem