Optimal control in ink-jet printing via instantaneous control

This paper concerns the optimal control of a free surface flow with moving contact line, inspired by an application in ink-jet printing. Surface tension, contact angle and wall friction are taken into account by means of the generalized Navier boundary condition. The time-dependent differential system is discretized by an arbitrary Lagrangian-Eulerian finite element method, and a control problem is addressed by an instantaneous control approach, based on the time discretization of the flow equations. The resulting control procedure is computationally highly efficient and its assessment by numerical tests show its effectiveness in deadening the natural oscillations that occur inside the nozzle and reducing significantly the duration of the transient preceding the attainment of the equilibrium configuration

Topology optimization of multiple anisotropic materials, with application to self-assembling diblock copolymers

We propose a solution strategy for a multimaterial minimum compliance topology optimization problem, which consists in finding the optimal allocation of a finite number of candidate (possibly anisotropic) materials inside a reference domain, with the aim of maximizing the stiffness of the body. As a relevant and novel application we consider the optimization of self-assembled structures obtained by means of diblock copolymers. Such polymers are a class of self-assembling materials which spontaneously synthesize periodic microstructures at the nanoscale, whose anisotropic features can be exploited to build structures with optimal elastic response, resembling biological tissues exhibiting microstructures, such as bones and wood. For this purpose we present a new generalization of the classical Optimality Criteria algorithm to encompass a wider class of problems, where multiple candidate materials are considered, the orientation of the anisotropic materials is optimized, and the elastic properties of the materials are assumed to depend on a scalar parameter, which is optimized simultaneously to the material allocation and orientation. Well-posedness of the optimization problem and well-definition of the presented algorithm are narrowly treated and proved. The capabilities of the proposed method are assessed through several numerical tests

Geographical and ecological factors affect microplastic body burden in marine fish at global scale

Microplastic (MP) contamination has been identified as a worrisome environmental issue at the global level. Fish are the taxonomic group more extensively investigated to assess MP contamination in marine environment. A large variability in MP bioaccumulation (i.e., body burden) was reported in fish but to date there is a dearth of information concerning the drivers underlying this process. The present systematic review aimed at summarizing the results of the scientific literature on MP body burden in the digestive tract of marine fish to quantitatively shed light on the contribution of different geographical (i.e., latitudinal origin of the sample, distance from the coastline and field- or marked-collected) and ecological (i.e., trophic strategy, milieu, and body size) factors driving bioaccumulation. The mean (±SE) MPs/individual was 4.13 ± 2.87, and the mean MPs/ww (i.e., MPs/g) was 5.92 ± 0.94. Overall, MP abundance expressed as MPs/individual of fish from tropical areas was significantly higher compared to the other latitudinal bands, with species sampled close to the coastline that accumulated a larger number of MPs compared to those collected offshore. Neither the trophic strategy, nor the milieu and the market or field origin of fish explained the MP body burden. However, fish body size resulted as a determinant of MP body burden (as MPs/individual), with small fish accumulating a lower amount of MPs compared to larger ones. Qualitatively, but not statistically significant, similar results were generally obtained for MPs/ww, except for an opposite, and significant, variation according to species body size. Our findings showed that geographical, rather than ecological factors represent the main drivers of MP body burden in marine fish, suggesting that environmental variables and/or local pollution sources mainly contribute to explaining the large variability underlying the ingestion and bioaccumulation processes of these contaminants

A Posteriori Error Analysis for a Coupled Stokes-Poroelastic System with Multiple Compartments

The computational effort entailed in the discretization of fluid-poromechanics systems is typically highly demanding. This is particularly true for models of multiphysics flows in the brain, due to the geometrical complexity of the cerebral anatomy - requiring a very fine computational mesh for finite element discretization - and to the high number of variables involved. Indeed, this kind of problems can be modeled by a coupled system encompassing the Stokes equations for the cerebrospinal fluid in the brain ventricles and Multiple-network Poro-Elasticity (MPE) equations describing the brain tissue, the interstitial fluid, and the blood vascular networks at different space scales. The present work aims to rigorously derive a posteriori error estimates for the coupled Stokes-MPE problem, as a first step towards the design of adaptive refinement strategies or reduced order models to decrease the computational demand of the problem. Through numerical experiments, we verify the reliability and optimal efficiency of the proposed a posteriori estimator and identify the role of the different solution variables in its composition

Phospho-proteomic analysis of mantle cell lymphoma cells suggests a pro-survival role of B-cell receptor signaling

BACKGROUND: Mantle cell lymphoma (MCL) is currently an incurable entity, and new therapeutic approaches are needed. We have applied a high-throughput phospho-proteomic technique to MCL cell lines to identify activated pathways and we have then validated our data in both cell lines and tumor tissues. METHODS: PhosphoScan analysis was performed on MCL cell lines. Results were validated by flow cytometry and western blotting. Functional validation was performed by blocking the most active pathway in MCL cell lines. RESULTS: PhosphoScan identified more than 300 tyrosine-phosporylated proteins, among which many protein kinases. The most abundant peptides belonged to proteins connected with B-cell receptor (BCR) signaling. Active BCR signaling was demonstrated by flow cytometry in MCL cells and by western blotting in MCL tumor tissues. Blocking BCR signaling by Syk inhibitor piceatannol induced dose/time-dependent apoptosis in MCL cell lines, as well as several modifications in the phosphorylation status of BCR pathway members and a collapse of cyclin D1 protein levels. CONCLUSION: Our data support a pro-survival role of BCR signaling in MCL and suggest that this pathway might be a candidate for therapy. Our findings also suggest that Syk activation patterns might be different in MCL compared to other lymphoma subtypes

A posteriori error analysis for a coupled Stokes-poroelastic system with multiple compartments

The discretization of fluid-poromechanics systems is typically highly demanding in terms of computational effort. This is particularly true for models of multiphysics flows in the brain, due to the geometrical complexity of the cerebral anatomy - requiring a very fine computational mesh for finite element discretization - and to the high number of variables involved. Indeed, this kind of problems can be modeled by a coupled system encompassing the Stokes equations for the cerebrospinal fluid in the brain ventricles and Multiple-network Poro-Elasticity (MPE) equations describing the brain tissue, the interstitial fluid, and the blood vascular networks at different space scales. The present work aims to rigorously derive a posteriori error estimates for the coupled Stokes-MPE problem, as a first step towards the design of adaptive refinement strategies or reduced order models to decrease the computational demand of the problem. Through numerical experiments, we verify the reliability and optimal efficiency of the proposed a posteriori estimator and identify the role of the different solution variables in its composition.Comment: 23 pages, 3 figure

Structure-preserving neural networks in data-driven rheological models

In this paper we address the importance and the impact of employing structure preserving neural networks as surrogate of the analytical physics-based models typically employed to describe the rheology of non-Newtonian fluids in Stokes flows. In particular, we propose and test on real-world scenarios a novel strategy to build data-driven rheological models based on the use of Input-Output Convex Neural Networks (ICNNs), a special class of feedforward neural network scalar valued functions that are convex with respect to their inputs. Moreover, we show, through a detailed campaign of numerical experiments, that the use of ICNNs is of paramount importance to guarantee the well-posedness of the associated non-Newtonian Stokes differential problem. Finally, building upon a novel perturbation result for non-Newtonian Stokes problems, we study the impact of our data-driven ICNN based rheological model on the accuracy of the finite element approximation.Comment: Submitted for publication in the SIAM Journal on Scientific Computing, 22 pages, 7 figures, 7 table

Impaired natural killer cell functions in patients with signal transducer and activator of transcription 1 (STAT1) gain-of-function mutations

Gain-of-function (GOF) mutations affecting the coiled-coil domain or the DNA-binding domain of signal transducer and activator of transcription 1 (STAT1) cause chronic mucocutaneous candidiasis disease. This condition is characterized by fungal and bacterial infections caused by impaired generation of TH17 cells; meanwhile, some patients with chronic mucocutaneous candidiasis disease might also have viral or intracellular pathogen infections

TEEN-IMMIGRANTS EXPLORE A MATH MOBILE APP

We present the pilot phase of the project "Teenagers Experience Empowerment by Numbers" (TEEN), which is funded by Politecnico di Milano through the Polisocial Award 2018 and concerns the development of a mobile app to teach essential mathematics to young immigrants. The project aims at preparing them for living in a conscious, autonomous way in a Western country, increasing their ability to deal with everyday tasks that require some mathematical understanding. We present the app, some materials and an activity with the learners who have interacted with that. The set of tasks, tested in small groups, is rooted in daily activities, such as shopping at the supermarket, choosing a mobile internet plan, planning a trip. Our theoretical background is related to existing research findings on teaching to immigrants, Rabardel’s instrumental orchestration and feedback