In this work we developed a mathematical model describing the crystallization process of salt dissolved in water flowing within a porous medium (in this case the common brick). Starting from this model a numerical tool was developed that allows to describe the effects of salt penetrating inside porous media and to forecast the effects of the application of crystallization inibitors.

t. The present work was inspired by the recent developments in laboratory experiments made on chip, where culturing of multiple cell species waspossible. The model is based on coupled reaction-diffusion-transport equationswith chemotaxis, and takes into account the interactions among cell populations and the possibility of drug administration for drug testing effects.Our effort was devoted to the development of a simulation tool that is able toreproduce the chemotactic movement and the interactions between differentcell species (immune and cancer cells) living in microfluidic chip environment.The main issues faced in this work are the introduction of mass-preservingand positivity-preserving conditions involving the balancing of incoming andoutgoing fluxes passing through interfaces between 2D and 1D domains of thechip and the development of mass-preserving and positivity preserving numerical conditions at the external boundaries and at the interfaces between 2Dand 1D domains

SUNBIM (Supramolecular and sUbmolecular Nano- and Biomaterials X-ray IMaging) is a computer suite of integrated programs which, through a user-friendly graphical interface, is able to perform a number of functions for (GI)SAXS-(GI)WAXS data analysis [1] such as: centering, q-scale calibration, two-dimensional to one-dimensional folding of small- and wide-angle X-ray scattering (SAXS/WAXS) data, also in grazing-incidence (GISAXS/GIWAXS); indexing of two-dimensional GISAXS frames and extraction of one-dimensional GISAXS profiles along specific cuts; quantitative scanning microscopy in absorption and SAXS contrast. SUNBIM consists of five main programs: (1) Calibration package, a set of functions allow one to find all of the geometrical parameters needed to extract a one-dimensional profile out of a two-dimensional image; (2) Batch Script & 2D Mesh Composite, to prepare batch script files (ASCII files) to run a sequential acquisition of two-dimensional frames (in scanning mode) and to perform a composite of the as-collected two-dimensional SAXS frames into a single image; (3) Single-scan (GI)SAXS and (GI)WAXS data analysis, to calibrate and fold the two-dimensional data, in order to extract relevant information from the experimental data and to fold 2D data into 1D profiles; (4) Multi-scan SAXS and WAXS data analysis, to fold each two-dimensional frame of the mesh into a one-dimensional profile and extract scattering features of the sample with a multi-modal imaging approach; (5) One-D Data Analysis Manager, a package that in addition to basic operations on one dimensional profiles (such as change of the plot representation from pixels to q, change from linear scale to logarithmic scale of the axes, choice of colors and plot thickness, inserting the legend, etc. as well as import, trigger, save and export plots) gives the possibility to denoise the folded profile and/or to deconvolute the primary beam angular divergence from the SAXS/WAXS profiles, particularly useful for a complete data analysis. SUNBIM combines in the same package both originally developed algorithms (i.e denoising, beam centering etc.) and reliable methods documented in the literature (multi-modal imaging [2], GIXAXS three-dimensional frame indexing [3]). New tools have been developed to enrich SUNBIM suite. The main novelty is the possibility to perform a deeper data reduction including dark current subtraction, background evaluation and subtraction, normalization of the SAXS intensity against the local sample thickness derived from absorption contrast maps. The advances of the new release with respect to previous one include also an automatic background subtraction from the 1D profile of the azimuthal integration to enhance peak visibility at large scattering angles (WAXS), to correct geometric aberration for small sample-to-detector distance. The previous release of the software has already been used successfully to analyse several nano-structured samples [4][5][6]. We are confident that the new features will allow a more correct and extensive analysis of the (GI)SAXS/(GI)WAXS data. SUNBIM is developed in the MATLAB language and it is distributed free of charge to the academic user (downloadable after a valid registration from http://www.ba.ic.cnr.it/softwareic/sunbimweb/)

Background: High-throughput technologies enable the cost-effective collection and analysis of DNA methylation data throughout the human genome. This naturally entails missing values management that can complicate the analysis of the data. Several general and specific imputation methods are suitable for DNA methylation data. However, there are no detailed studies of their performances under different missing data mechanisms -(completely) at random or not- and different representations of DNA methylation levels (beta andM-value).

Meta-analysis is a powerful means for leveraging the hundreds of experiments being run worldwide into more statistically powerful analyses. This is also true for the analysis of omic data, including genome-wide DNA methylation. In particular, thousands of DNA methylation profiles generated using the Illumina 450k are stored in the publicly accessible Gene Expression Omnibus (GEO) repository. Often, however, the intensity values produced by the BeadChip (raw data) are not deposited, therefore only pre-processed values-obtained after computational manipulation-are available. Pre-processing is possibly different among studies and may then affect meta-analysis by introducing non-biological sources of variability. Introduction

We discuss the well-posedness of the "transient eddy current" magneto-quasi-static approximation of Maxwell's initial value problem with bounded and measurable conductivity, with sources, on a domain. We prove the existence and uniqueness of weak solutions, and we provide global Hölder estimates for the magnetic part.

The ongoing COVID-19 pandemic still requires fast and effective efforts from all fronts, including epidemiology, clinical practice, molecular medicine, and pharmacology. A comprehensive molecular framework of the disease is needed to better understand its pathological mechanisms, and to design successful treatments able to slow down and stop the impressive pace of the outbreak and harsh clinical symptomatology, possibly via the use of readily available, off-the-shelf drugs. This work engages in providing a wider picture of the human molecular landscape of the SARS-CoV-2 infection via a network medicine approach as the ground for a drug repurposing strategy. Grounding on prior knowledge such as experimentally validated host proteins known to be viral interactors, tissue-specific gene expression data, and using network analysis techniques such as network propagation and connectivity significance, the host molecular reaction network to the viral invasion is explored and exploited to infer and prioritize candidate target genes, and finally to propose drugs to be repurposed for the treatment of COVID-19. Ranks of potential target genes have been obtained for coherent groups of tissues/organs, potential and distinct sites of interaction between the virus and the organism. The normalization and the aggregation of the different scores allowed to define a preliminary, restricted list of genes candidates as pharmacological targets for drug repurposing, with the aim of contrasting different phases of the virus infection and viral replication cycle.

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson's disease. The review offers valuable insights and informs the research in DL and SM.

Simulated data are crucial for evaluating epistasis detection tools in genome-wide association studies. Existing simulators are limited, as they do not account for linkage disequilibrium (LD), support limited interaction models of single nucleotide polymorphisms (SNPs) and only dichotomous phenotypes or depend on proprietary software. In contrast, EpiGEN supports SNP interactions of arbitrary order, produces realistic LD patterns and generates both categorical and quantitative phenotypes.EpiGEN is implemented in Python 3 and is freely available at https://github.com/baumbachlab/epigen.Supplementary data are available at Bioinformatics online.

This paper describes the effect of perturbation of the kernel on the solutions of linear Volterra integral equations on time scales and proposes a new perspective for the stability analysis of numerical methods.

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on Science and Technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ- and symptom-based medical concepts toward network- and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management.

Active fluids comprise a variety of systems composed of elements immersed in a fluid environment which can convert some form of energy into directed motion; as such they are intrinsically out-of-equilibrium in the absence of any external force. A fundamental problem in the physics of active matter concerns the understanding of how the characteristics of autonomous propulsion and agent-agent interactions determine the collective dynamics of the system. We study numerically the suspensions of self-propelled diffusiophoretic colloids, in (quasi)-2d configurations, accounting for both dynamically resolved solute-mediated phoretic interactions and solvent-mediated hydrodynamic interactions. Our results show that the system displays different scenarios at changing the colloid-solute affinity and it develops a cluster phase in the chemoattractive case. We study the statistics of cluster sizes and cluster morphologies for different magnitudes of colloidal activity. Finally, we provide evidences that hydrodynamics plays a relevant role in the aggregation kinetics and cluster morphology, significantly hindering cluster growth.

The dynamics of active colloids is very sensitive to the presence of boundaries and interfaces which therefore can be used to control their motion. Here we analyze the dynamics of active colloids adsorbed at a fluid-fluid interface. By using a mesoscopic numerical approach which relies on an approximated numerical solution of the Navier-Stokes equation, we show that when adsorbed at a fluid interface, an active colloid experiences a net torque even in the absence of a viscosity contrast between the two adjacent fluids. In particular, we study the dependence of this torque on the contact angle of the colloid with the fluid-fluid interface and on its surface properties. We rationalize our results via an approximate approach which accounts for the appearance of a local friction coefficient. By providing insight into the dynamics of active colloids adsorbed at fluid interfaces, our results are relevant for two-dimensional self assembly and emulsion stabilization by means of active colloids.

Bandelt and Mulder's structural characterization of bipartite distance hereditary graphs 16 asserts that such graphs can be built inductively starting from a single vertex and by re- 17 peatedly adding either pendant vertices or twins (i.e., vertices with the same neighborhood 18 as an existing one). Dirac and Duffin's structural characterization of 2-connected series- 19 parallel graphs asserts that such graphs can be built inductively starting from a single edge 20 by adding either edges in series or in parallel. In this paper we give an elementary proof 21 that the two constructions are the same construction when bipartite graphs are viewed as 22 the fundamental graphs of a graphic matroid. We then apply the result to re-prove known 23 results concerning bipartite distance hereditary graphs and series-parallel graphs and to 24 provide a new class of polynomially-solvable instances for the integer multi-commodity 25 flow of maximum value.

This paper deals with the solution of an inverse problem for the heat equation aimed at nondestructive evaluation of fractures, emerging on the accessible surface of a slab, by means of Active Thermography. In real life, this surface is heated with a laser and its temperature is measured for a time interval by means of an infrared camera. A fundamental step in iterative inversion methods is the numerical solution of the underlying direct mathematical model. Usually, this step requires specific techniques in order to limit an abnormal use of memory resources and computing time due to excessively fine meshes necessary to follow a very thin fracture in the domain. Our contribution to this problem consists in decomposing the temperature of the damaged specimen as a sum of a term (with known analytical form) due to an infinite virtual fracture and the solution of an initial boundary value problem for the heat equation on one side of the fracture (i.e. on a rectangular domain). The depth of the fracture is a variable parameter in the boundary conditions that must be estimated from additional data (usually, measurements of the surface temperature). We apply our method to the detection of simulated cracks in concrete and steel specimens.

A composite specimen, made of two slabs and an interface A is heated through one of its sides S, in order to evaluate the thermal conductance H of A. The direct model consists of a system of Initial Boundary Value Problems completed by suitable transmission conditions. Thanks to the properties of multilayer diffusion, we reduce the problem to the slab between A and S only. In this case evaluating the thermal resistance of A means to identify a coefficient in a Robin boundary condition. We evaluate H numerically by means of Thin Plate Approximation.

A new class of multiscale scheme is presented for micro-hydrodynamic problems based on a dual representation of the fluid observables. The hybrid model is first tested against the classical flow between two parallel plates and then applied to a plug flow within a micrometer-sized striction and a shear flow within a microcavity. Both cases demonstrate the capability of the multiscale approach to reproduce the correct macroscopic hydrodynamics also in the presence of refined grids (one and two levels), while retaining the correct thermal fluctuations, embedded in the multiparticle collision method. This provides the first step toward a novel class of fully mesoscale hybrid approaches able to capture the physics of fluids at the micro- and nanoscales whenever a continuum representation of the fluid falls short of providing the complete physical information, due to a lack of resolution and thermal fluctuations.

We present an extension of the multiparticle collision dynamics method for flows with complex interfaces, including supramolecular near-contact interactions mimicking the effect of surfactants. The new method is demonstrated for the case of (i) short range repulsion of droplets in close contact, (ii) arrested phase separation, and (iii) different pattern formation during spinodal decomposition of binary mixtures.

Fluid flows hosting electrical phenomena are the subject of a fascinating and highly interdisciplinary scientific field. In recent years, the extraordinary success of electrospinning and solution-blowing technologies for the generation of polymer nanofibers has motivated vibrant research aiming at rationalizing the behavior of viscoelastic jets under applied electric fields or other stretching fields including gas streams. Theoretical models unveiled many original aspects in the underpinning physics of polymer solutions in jets and provided useful information to improve experimental platforms. This review examines advances in the theoretical description and numerical simulation of polymer solution jets in electrospinning and solution blowing. Instability phenomena of electrical and hydrodynamic origin, which play a crucial role in the relevant flow physics, are highlighted. Specifications leading to accurate and computationally viable models are formulated. Electrohydrodynamic modeling, theories on jet bending instability, recent advances in Lagrangian approaches to describe the jet flow, including strategies for dynamic refinement of simulations, and effects of strong elongational flow on polymer networks are reviewed. Finally, the current challenges and future perspectives in the field are outlined and discussed, including the task of correlating the physics of the jet flows with the properties of relevant materials, as well as the development of multiscale techniques for modeling viscoelastic jets.

Bicontinuous interfacially jammed emulsion gels ("bijels") represent a new class of soft materials made of a densely packed monolayer of solid particles sequestered at the interface of a bicontinuous fluid. Their mechanical properties are relevant to many applications, such as catalysis, energy conversion, soft robotics, and scaffolds for tissue engineering. While their stationary bulk properties have been covered in depth, much less is known about their behavior in the presence of an external shear. In this paper, we numerically study the dynamics of a bijel confined within a three-dimensional rectangular domain and subject to a symmetric shear flow sufficiently intense to break the material. Extensive numerical simulations reveal that the shear flow generally promotes the detachment of a sizable amount of particles from the fluid interface and their accumulation in the bulk. Fluid interfaces undergo large stretching and deformations along the flow direction, an effect that reduces their capability of entrapping particles. These results are supported by a series of quantitative indicators such as (i) curvature of the fluid interface, (ii) spatial distribution of the colloidal particles, and (iii) fluid flow structure within the microchannel. (c) 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).