We consider here a cell-centered finite difference approximation of the Richards
equation in three dimensions, averaging for interface values the hydraulic conductivity, a highly nonlinear function, by arithmetic, upstream and harmonic
means. The nonlinearities in the equation can lead to changes in soil conductivity
over several orders of magnitude and discretizations with respect to space variables often produce stiff systems of differential equations. A fully implicit time
discretization is provided by backward Euler one-step formula; the resulting nonlinear algebraic system is solved by an inexact Newton Armijo-Goldstein algorithm,
requiring the solution of a sequence of linear systems involving Jacobian matrices.
We prove some new results concerning the distribution of the Jacobians eigenvalues
and the explicit expression of their entries. Moreover, we explore some connections
between the saturation of the soil and the ill conditioning of the Jacobians. The information on eigenvalues justifies the effectiveness of some preconditioner approaches
which are widely used in the solution of Richards equation. We also propose a new
software framework to experiment with scalable and robust preconditioners suitable
for efficient parallel simulations at very large scales. Performance results on a literature test case show that our framework is very promising in the advance towards
realistic simulations at extreme scale.
We consider a core-radius approach to nonlocal perimeters governed by isotropic kernels having critical and supercritical exponents, extending the nowadays classical notion of s-fractional perimeter, defined for 0<1, to the case s>=1. We show that, as the core-radius vanishes, such core-radius regularized s-fractional perimeters, suitably scaled, ?-converge to the standard Euclidean perimeter. Under the same scaling, the first variation of such nonlocal perimeters gives back regularized s-fractional curvatures which, as the core radius vanishes, converge to the standard mean curvature; as a consequence, we show that the level set solutions to the corresponding nonlocal geometric flows, suitably reparametrized in time, converge to the standard mean curvature flow. Furthermore, we show the same asymptotic behavior as the core-radius vanishes and s->s?>=1 simultaneously. Finally, we prove analogous results in the case of anisotropic kernels with applications to dislocation dynamics.
Fractional perimeters; Gamma-convergence; local and nonlocal geometric evolutions; viscosity solutions; level set formulation; fractional mean curvature flow; dislocation dynamics
A hybrid metaheuristic for the Knapsack Problem with Forfeits
Capobianco Giovanni
;
D'Ambrosio Ciriaco
;
Pavone Luigi
;
Raiconi Andrea
;
Vitale Gaetano
;
Sebastiano Fabio
In this paper, we present a novel hybrid metaheuristic for the Knapsack Problem with Forfeits (KPF). KPF is a recently introduced generalization of the Knapsack Problem. In this variant, a penalty cost incurs whenever both items composing a so-called forfeit pair belong to the solution. Our proposed algorithm, called GA-CG Forfeits, combines the strengths of the Genetic and Carousel Greedy paradigms. In this work, we define the algorithm and compare it with two previously proposed heuristics on a set of benchmark instances. In these tests, GA-CG Forfeits provided significantly better solutions than the other two algorithms on all instances.
Carousel Greedy
Conflicts
Forfeits
Genetic algorithm
Knapsack Problem
Controlled drug delivery from a multilayer spherical capsule is used for several therapeutic applications. Developing a theoretical understanding of mass transfer in the multilayer capsule is critical for understanding and optimizing targeted drug delivery. This paper presents an analytical solution for the mass transport problem in a general multilayer sphere involving diffusion as well as drug immobilization in various layers due to binding reactions. An eigenvalue-based solution for this multilayer diffusion-reaction problem is derived in terms of various non-dimensional quantities including Sherwood and Damköhler numbers. It is shown that unlike diffusion-reaction problems in heat transfer, the present problem does not admit imaginary eigenvalues. The effect of binding reactions represented by the Damköhler numbers and outer surface boundary condition represented by the Sherwood number on drug delivery profile is analyzed. It is shown that a low Sherwood number not only increases drug delivery time, but also reduces the total mass of drug delivered. The mass of drug delivered is also shown to reduce with increasing Damköhler number. The impact of shell thickness is analyzed. The effect of a thin outer coating is accounted for by lumping the mass transfer resistance in series with convective boundary resistance, and a non-dimensional number involving the thickness and diffusion coefficient of the coating is shown to govern its impact on drug delivery characteristics. The analytical model presented here improves the understanding of mass transfer in a multilayer spherical capsule in presence of binding reactions, and may help design appropriate experiments for down-selecting candidate materials and geometries for drug delivery applications of interest.
Drug delivery
Mass transfer
Diffusion-reaction equation
Multilayer Sphere
The present paper was inspired by recent developments in laboratory experiments within the framework of cancer-on-chip technology, an immune-oncology microfluidic chip aiming at studying the fundamental mechanisms of immunocompetent behavior. We focus on the laboratory setting where cancer is treated with chemotherapy drugs, and in this case, the effects of the treatment administration hypothesized by biologists are: the absence of migration and proliferation of tumor cells, which are dying; the stimulation of the production of chemical substances (annexin); the migration of leukocytes in the direction of higher concentrations of chemicals. Here, following the physiological hypotheses made by biologists on the phenomena occurring in these experiments, we introduce an agent-based model reproducing the dynamics of two cell populations (agents), i.e., tumor cells and leukocytes living in the microfluidic chip environment. Our model aims at proof of concept, demonstrating that the observations of the biological phenomena can be obtained by the model on the basis of the explicit assumptions made. In this framework, close adherence of the computational model to the biological results, as shown in the section devoted to the first calibration of the model with respect to available observations, is successfully accomplished.
In this paper we introduce a mathematical model of concrete carbonation Portland cement specimens. The main novelty of this work is to describe the intermediate chemical reactions, occurring in the carbonation process of concrete, involving the interplay of carbon dioxide with the water present into the pores. Indeed, the model here proposed, besides describing transport and diffusion processes inside the porous medium, takes into account both fast and slow phenomena as intermediate reactions of the carbonation process. As a model validation, by using the mathematical based simulation algorithm we are able to describe the effects of the interaction between concrete and CO on the porosity of material as shown by the numerical results in substantial accordance with experimental results of accelerated carbonation taken from literature. We also considered a further reaction: the dissolution of calcium carbonate under an acid environment. As a result, a trend inversion in the evolution of porosity can be observed for long exposure times. Such an increase in porosity results in the accessibility of solutions and pollutants within the concrete leading to an higher permeability and diffusivity thus significantly affecting its durability.
Concrete carbonation · Reaction and diffusion models · Model parameter estimation · Finite difference schemes
The present work is inspired by laboratory experiments, investigating the cross-talk between immune and cancer cells in a confined environment given by a microfluidic chip, the so called Organ-on-Chip (OOC). Based on a mathematical model in form of coupled reaction-diffusion-transport equations with chemotactic functions, our effort is devoted to the development of a parameter estimation methodology that is able to use real data obtained from the laboratory experiments to estimate the model parameters and infer the most plausible chemotactic function present in the experiment. In particular, we need to estimate the model parameters representing the convective and diffusive regimes included in the PDE model, in order to evaluate the diffusivity of the chemoattractant produced by tumor cells and its biasing effect on immune cells. The main issues faced in this work are the efficient calibration of the model against noisy synthetic data, available as macroscopic density of immune cells. A calibration algorithm is derived based on minimization methods which applies several techniques such as regularization terms and multigrids application to improve the results, which show the robustness and accuracy of the proposed algorithm.
We prove that positive solutions of the fractional Lane-Emden equation with homogeneous Dirichlet boundary conditions satisfy pointwise estimates in terms of the best constant in Poincaré's inequality on all open sets, and are isolated in $L^1$ on smooth bounded ones, whence we deduce the isolation of the first non-local semilinear eigenvalue .
In the near future, Exascale systems will need to bridge three technology gaps to achieve high performance while remaining under tight power constraints: energy efficiency and thermal control; extreme computation efficiency via HW acceleration and new arithmetic; methods and tools for seamless integration of reconfigurable accelerators in heterogeneous HPC multi-node platforms. TEXTAROSSA addresses these gaps through a co-design approach to heterogeneous HPC solutions, supported by the integration and extension of HW and SW IPs, programming models, and tools derived from European research.
We describe a signal processing method for demodulation of digital signals based on Hilbert
transform (HT).
We review the signal processing theory and the method of Analytic Signal transformation
(AS) and their algorithms which are implemented by FFT, then we propose a direct method
for the numerical approximation of the Hilbert transform that is a generalization of the al-
gorithm presented in [1].
The proposed algorithm provides the estimate of instantaneous frequency and phase of the
received signals, and can be used for both binary communication based on phased-shifting
keying (PSK) and frequency-shifting keying (BFSK) [2].
Typical applications include data analysis as a bank of matched lters [3], data communi-
cation of electric and acoustic soil response and sea autonomous platforms.
References
[1] M.R. Capobianco, G. Criscuolo, Some Remarks about the Hilbert Transform, Journal
of Research in Applied Mathematics, 5 (2019) pp.16-24
[2] J.C. Goswami, A.E. Hoefel, Algorithms for estimating instantaneous frequency, Signal
Processing 84 (2004) pp.1423-1427
[3] S. Marano, M. Medugno, M. Longo, A real-time parallel application: the de-
tection of gravitational waves by a network of heterogeneous workstations, Jour-
nal of Computational Physics, Vol. 139, No. 1, January 1 1998, pp.15-34,
doi.org/10.1006/jcph.1997.5857
FSK-PSK data processing
approximation
Hilbert transform
Photocurable polymers are used ubiquitously in 3D printing, coatings, adhesives, and composite fillers. In the present work, the free radical polymerization of photocurable compounds is studied using reactive classical molecular dynamics combined with a dynamical approach of the nonequilibrium molecular dynamics (D-NEMD). Different concentrations of radicals and reaction velocities are considered. The mechanical properties of the polymer resulting from 1,6-hexanediol dimethacrylate systems are characterized in terms of viscosity, diffusion constant, and activation energy, whereas the topological ones through the number of cycles (polymer loops) and cyclomatic complexity. Effects like volume shrinkage and delaying of the gel point for increasing monomer concentration are also predicted, as well as the stress-strain curve and Young's modulus. Combining ab initio, reactive molecular dynamics, and the D-NEMD method might lead to a novel and powerful tool to describe photopolymerization processes and to original routes to optimize additive manufacturing methods relying on photosensitive macromolecular systems.
E-commerce is a continuously growing sector worldwide, with important repercussions on the delivery system in urban areas and especially in the Business to Consumer (B2C) sector. The delivery of a package to a consumer's address involves not only high costs for couriers (greater number of kilometres travelled), but also increased congestion and greater environmental pollution (greater volume of pollutants released into the air). To rationalize deliveries in urban areas the use of collection points, equipped with lockers, to store the goods that users have ordered has been considered in literature. This work compares two alternative delivery options: deliveries to the consumer's home versus to Lockers. To make this comparison we used a cluster first route second math-heuristic approach. In the clustering phase, we experimented a new clustering function, while the routing phase consists in solving an instance of the Traveling Salesman Problem for each generated cluster. Finally, we applied the math-heuristic to a real case (the Italian municipality of Dolo near Venice) and compared the two delivery alternatives. We evaluate the performance considering two different fleets of vehicles, with small and medium capacity. In addition, since additional trips might be performed by consumers to pick up parcels at Lockers, a sensitivity analysis was carried out to analyse the sustainability of the proposed city logistics scheme.
City logistics
Freight Urban distribution
Vehicle routing
Math-heuristics
Loss-of-function variants in exon 4 of TAB2 cause a recognizable multisystem disorder with cardiovascular, facial, cutaneous, and musculoskeletal involvement
Purpose: This study aimed to describe a multisystemic disorder featuring cardiovascular, facial, musculoskeletal, and cutaneous anomalies caused by heterozygous loss-of-function variants in TAB2.Methods: Affected individuals were analyzed by next-generation technologies and genomic array. The presumed loss-of-function effect of identified variants was assessed by luciferase assay in cells transiently expressing TAB2 deleterious alleles. In available patients' fibroblasts, variant pathogenicity was further explored by immunoblot and osteoblast differentiation assays. The transcriptomic profile of fibroblasts was investigated by RNA sequencing.Results: A total of 11 individuals from 8 families were heterozygotes for a novel TAB2 variant. In total, 7 variants were predicted to be null alleles and 1 was a missense change. An additional subject was heterozygous for a 52 kb microdeletion involving TAB2 exons 1 to 3. Luciferase assay indicated a decreased transcriptional activation mediated by NF-?B signaling for all point variants. Immunoblot analysis showed a reduction of TAK1 phosphorylation while osteoblast differentiation was impaired. Transcriptomic analysis identified deregulation of multiple pleiotropic pathways, such as TGF?-, Ras-MAPK-, and Wnt-signaling networks.Conclusion: Our data defined a novel disorder associated with loss-of-function or, more rarely, hypomorphic alleles in a restricted linker region of TAB2. The pleiotropic manifestations in this disorder partly recapitulate the 6q25.1 (TAB2) microdeletion syndrome and deserve the definition of cardio-facial-cutaneous-articular syndrome.
In this paper we propose a new approach to detect clusters in undirected graphs with attributed vertices. The aim is to group vertices which are similar
not only in terms of structural connectivity but also in terms of attribute values.
We incorporate structural and attribute similarities between the vertices in an augmented graph by creating additional vertices and edges as proposed in [6, 38]. The
augmented graph is then embedded in a Euclidean space associated to its Laplacian
where a modified K-means algorithm is applied to identify clusters. The modified
K-means relies on a vector distance measure where to each original vertex we assign
a suitable vector-valued set of coordinates depending on both structural connectivity and attribute similarities, so that each original graph vertex is thought as
representative of m + 1 vertices of the augmented graph, if m is the number of
vertex attributes. To define the coordinate vectors we employ our recently proposed algorithm based on an adaptive AMG (Algebraic MultiGrid) method, which
identifies the coordinate directions in the embedding Euclidean space in terms of
algebraically smooth vectors with respect to the augmented graph Laplacian, and
thus extending our previous result for graphs without attributes. We analyze the effectiveness of our proposed clustering method by comparison with some well known
methods, whose software implementation is freely available, and also with results
reported in the literature, on two different types of widely used synthetic graphs
and on some real-world attributed graphs.
Evaluation of HIV-1 integrase variability by combining computational and probabilistic approaches
Davide Vergni
;
Daniele Santoni
;
Yagai Bouba
;
Saverio Lemme
;
Lavinia Fabeni
;
Luca Carioti
;
Ada Bertoli
;
William Gennari
;
Federica Forbici
;
Carlo Federico Perno
;
Roberta Gagliardin
;
Francesca CeccheriniSilberstein
;
Maria Mercedes Santoro
;
on behalf of the HIV drugresistance group
This study aimed at updating previous data on HIV-1 integrase variability, by using effective bioinformatics methods combining different statistical instruments from simple entropy and mutation rate to more specific approaches such as Hellinger distance. A total of 2133 HIV-1 integrase sequences were analyzed in: i) 1460 samples from drug-naïve [DN] individuals; ii) 386 samples from drug-experienced but INI-naïve [IN] individuals; iii) 287 samples from INI-experienced [IE] individuals. Within the three groups, 76 amino acid positions were highly conserved (<=0.2% variation, Hellinger distance: <0.25%), with 35 fully invariant positions; while, 80 positions were conserved (>0.2% to <1% variation, Hellinger distance: <1%). The H12-H16-C40-C43 and D64-D116-E152 motifs were all well conserved. Some residues were affected by dramatic changes in their mutation distributions, especially between DN and IE samples (Hellinger distance >=1%). In particular, 15 positions (D6, S24, V31, S39, L74, A91, S119, T122, T124, T125, V126, K160, N222, S230, C280) showed a significant decrease of mutation rate in IN and/or IE samples compared to DN samples. Conversely, 8 positions showed significantly higher mutation rate in samples from treated individuals (IN and/or IE) compared to DN. Some of these positions, such as E92, T97, G140, Y143, Q148 and N155, were already known to be associated with resistance to integrase inhibitors; other positions including S24, M154, V165 and D270 are not yet documented to be associated with resistance. Our study confirms the high conservation of HIV-1 integrase and identified highly invariant positions using robust and innovative methods. The role of novel mutations located in the critical region of HIV-1 integrase deserves further investigation.
The aim of this talk is to show how de la Vallee Poussin type interpolation based on Chebyshev zeros of rst kind, can be applied to resize an arbitrary color digital image. In fact, using such kind of approximation, we get an image scaling method running for any desired scaling factor or size, in both downscaling and upscaling. The peculiarities and the performance of such method will be discussed.
Image resizing
Lagrange interpolation
Chebyshev zeros
de la Vallée Poussin filtered-interpolation