Canine Mammary Tumor Histopathological Image Classification via Computer-Aided Pathology: An Available Dataset for Imaging Analysis.

Histopathology, the gold-standard technique in classifying canine mammary tumors (CMTs), is a time-consuming process, affected by high inter-observer variability. Digital (DP) and Computer-aided pathology (CAD) are emergent fields that will improve overall classification accuracy. In this study, the ability of the CAD systems to distinguish benign from malignant CMTs has been explored on a dataset-namely CMTD-of 1056 hematoxylin and eosin JPEG images from 20 benign and 24 malignant CMTs, with three different CAD systems based on the combination of a convolutional neural network (VGG16, Inception v3, EfficientNet), which acts as a feature extractor, and a classifier (support vector machines (SVM) or stochastic gradient boosting (SGB)), placed on top of the neural net. Based on a human breast cancer dataset (i.e., BreakHis) (accuracy from 0.86 to 0.91), our models were applied to the CMT dataset, showing accuracy from 0.63 to 0.85 across all architectures. The EfficientNet framework coupled with SVM resulted in the best performances with an accuracy from 0.82 to 0.85. The encouraging results obtained by the use of DP and CAD systems in CMTs provide an interesting perspective on the integration of artificial intelligence and machine learning technologies in cancer-related research.

Quasiequilibrium multistate cellular automata.

In our effort to tackle the problem of letting nontrivial interactions, thermodynamic equilibrium, and full synchronicity coexist, and in the hope of reviving interest in cellular automata as promising tools for the quantitative, large-scale investigation of multiparticle systems, we built a fully synchronous cellular automaton rule for the simulation of occupancy-based lattice systems with multistate cells and neighboring interactions. The core of this rule, which constitutes an actual synchronous sampling scheme, is a negotiation stage; it produces cell occupancy distributions in very good agreement with their sequential Monte Carlo counterparts, and it satisfies a cellwise detailed balance principle thanks to the use of "mixed" intermediate states that allow for the computation of locally averaged acceptance probabilities. We took a square lattice (but the rule itself is not bound by dimensionality) as a basis for comparison with sequential Monte Carlo for showing that this synchronous rule leads to quasiequilibrium; the fulfillment of cellwise detailed balance is shown through results obtained for a small one-dimensional system, where the transition matrix could be computed exactly.

Scaling-Up Simulations of Diffusion in Microporous Materials.

We introduce and demonstrate the coarse-graining of static and dynamical properties of host-guest systems constituted by methane in two different microporous materials. The reference systems are mapped to occupancy-based pore-scale lattice models. Each coarse-grained model is equipped with an appropriate coarse-grained potential and a local dynamical operator, which represents the probability of interpore molecular jumps between different cages. Coarse-grained thermodynamics and dynamics are both defined based on small-scale atomistic simulations of the reference systems. We considered two host materials: the widely studied ITQ-29 zeolite and the LTA-zeolite-templated carbon, which was recently theorized. Our method allows for representing with satisfactory accuracy and a considerably reduced computational effort the reference systems while providing new interesting physical insights in terms of static and diffusive properties.

Molecular QCA embedding in microporous materials.

We propose an environment for information encoding and transmission via a nanoconfined molecular Quantum Dot Cellular Automata (QCA) wire, composed of a single row of head-to-tail interacting 2-dots molecular switches. While most of the research in the field refers to dots-bearing molecules bound on some type of surface, forming a bidimensional array of square cells capable of performing QCA typical functions, we propose here to embed the information bearing elements within the channels of a microporous matrix. In this way molecules would self-assemble in a row as a consequence of adsorption inside the pores of the material, forming an encased wire, with the crystalline environment giving stability and protection to the structure. DFT calculations on a diferrocenyl carborane, previously proposed and synthesized [J. A. Christie, R. P. Forrest, S. A. Corcelli, N. A. Wasio, R. C. Quardokus, R. Brown, S. A. Kandel, Y. Lu, C. S. Lent and K. W. Henderson, Angew. Chem., Int. Ed., 2015, 54, 15448], were performed both in vacuum and inside the channels of zeolite ITQ-51, indicating that information encoding and transmission is possible within the nanoconfined environment.

Local free energies for the coarse-graining of adsorption phenomena: The interacting pair approximation.

We investigate the coarse-graining of host-guest systems under the perspective of the local distribution of pore occupancies, along with the physical meaning and actual computability of the coarse-interaction terms. We show that the widely accepted approach, in which the contributions to the free energy given by the molecules located in two neighboring pores are estimated through Monte Carlo simulations where the two pores are kept separated from the rest of the system, leads to inaccurate results at high sorbate densities. In the coarse-graining strategy that we propose, which is based on the Bethe-Peierls approximation, density-independent interaction terms are instead computed according to local effective potentials that take into account the correlations between the pore pair and its surroundings by means of mean-field correction terms without the need for simulating the pore pair separately. Use of the interaction parameters obtained this way allows the coarse-grained system to reproduce more closely the equilibrium properties of the original one. Results are shown for lattice-gases where the local free energy can be computed exactly and for a system of Lennard-Jones particles under the effect of a static confining field.

Reverse Mössbauer effect as a possible source of "hot" molecules absorbed in crystalline solids at low temperature.

As an attempt to explain some of the many anomalies and unresolved problems which have been reported about the dynamic behavior of particles and molecules absorbed in crystalline solids, the "reverse Mössbauer effect" (RME) is proposed. RME theory posits that a particle in non-equilibrium state with respect to a crystal (colliding with the crystal or absorbed in it, but set out of thermal equilibrium by some external cause) is scattered by the whole crystal with a momentum proportional to a vector representing a reciprocal lattice point. The scattering is expected to occur with a well-defined probability and the momentum transferable to the particle is expected to follow a predictable distribution. The RME theory, in practice, is an extension of the Bragg-von Laue scattering law to high-energy colliding particles, in general, and can be applied to any particle or molecule colliding with the surface of a crystalline solid or absorbed in it, but not in thermal equilibrium with the crystal lattice. We verified the RME theory by considering a well-defined unresolved problem. In an experimental study about methane adsorbed in the zeolite Na-ZSM-5 [H. Jobic, Chem. Phys. Lett. 170, 217 (1990)] reporting neutron inelastic-scattering spectra (recoiled bands) at 10 K, the translational kinetic energy of methane resulted to be much higher than equilibrium expected value, namely, about 85 K (or 7.3 meV). The author concluded that "the interpretation of this unusual behavior has yet to be found." In the present study, on the basis of the RME, an explanation of this behavior is put forward.

Partial Charges in Periodic Systems: Improving Electrostatic Potential (ESP) Fitting via Total Dipole Fluctuations and Multiframe Approaches.

Two major improvements to the state-of-the-art Repeating Electrostatic Potential Extracted Atomic (REPEAT) method, for generating accurate partial charges for molecular simulations of periodic structures, are here developed. The first, D-REPEAT, consists in the simultaneous fit of the electrostatic potential (ESP), together with the total dipole fluctuations (TDF) of the framework. The second, M-REPEAT, allows the fit of multiple ESP configurations at once. When both techniques are fused into one, DM-REPEAT method, the resulting charges become remarkably stable over a large set of fitting regions, giving a robust and physically sound solution to the buried atoms problem. The method capabilities are extensively studied in ZIF-8 framework, and subsequently applied to IRMOF-1 and ITQ-29 crystal structures. To our knowledge, this is the first time that this approach is proposed in the context of periodic systems.

A network of discrete events for the representation and analysis of diffusion dynamics.

We developed a coarse-grained description of the phenomenology of diffusive processes, in terms of a space of discrete events and its representation as a network. Once a proper classification of the discrete events underlying the diffusive process is carried out, their transition matrix is calculated on the basis of molecular dynamics data. This matrix can be represented as a directed, weighted network where nodes represent discrete events, and the weight of edges is given by the probability that one follows the other. The structure of this network reflects dynamical properties of the process of interest in such features as its modularity and the entropy rate of nodes. As an example of the applicability of this conceptual framework, we discuss here the physics of diffusion of small non-polar molecules in a microporous material, in terms of the structure of the corresponding network of events, and explain on this basis the diffusivity trends observed. A quantitative account of these trends is obtained by considering the contribution of the various events to the displacement autocorrelation function.

The interplay between dynamic heterogeneities and structure of bulk liquid water: A molecular dynamics simulation study.

In order to study the interplay between dynamical heterogeneities and structural properties of bulk liquid water in the temperature range 130-350 K, thus including the supercooled regime, we use the explicit trend of the distribution functions of some molecular properties, namely, the rotational relaxation constants, the atomic mean-square displacements, the relaxation of the cross correlation functions between the linear and squared displacements of H and O atoms of each molecule, the tetrahedral order parameter q and, finally, the number of nearest neighbors (NNs) and of hydrogen bonds (HBs) per molecule. Two different potentials are considered: TIP4P-Ew and a model developed in this laboratory for the study of nanoconfined water. The results are similar for the dynamical properties, but are markedly different for the structural characteristics. In particular, for temperatures higher than that of the dynamic crossover between "fragile" (at higher temperatures) and "strong" (at lower temperatures) liquid behaviors detected around 207 K, the rotational relaxation of supercooled water appears to be remarkably homogeneous. However, the structural parameters (number of NNs and of HBs, as well as q) do not show homogeneous distributions, and these distributions are different for the two water models. Another dynamic crossover between "fragile" (at lower temperatures) and "strong" (at higher temperatures) liquid behaviors, corresponding to the one found experimentally at T(∗) ∼ 315 ± 5 K, was spotted at T(∗) ∼ 283 K and T(∗) ∼ 276 K for the TIP4P-Ew and the model developed in this laboratory, respectively. It was detected from the trend of Arrhenius plots of dynamic quantities and from the onset of a further heterogeneity in the rotational relaxation. To our best knowledge, it is the first time that this dynamical crossover is detected in computer simulations of bulk water. On the basis of the simulation results, the possible mechanisms of the two crossovers at molecular level are discussed.

Thermodynamics of the one-dimensional parallel Kawasaki model: exact solution and mean-field approximations.

The adsorption isotherm for the recently proposed parallel Kawasaki (PK) lattice-gas model [Phys. Rev. E 88, 062144 (2013)] is calculated exactly in one dimension. To do so, a third-order difference equation for the grand-canonical partition function is derived and solved analytically. In the present version of the PK model, the attraction and repulsion effects between two neighboring particles and between a particle and a neighboring empty site are ruled, respectively, by the dimensionless parameters ϕ and θ. We discuss the inflections induced in the isotherms by situations of high repulsion, the role played by finite lattice sizes in the emergence of substeps, and the adequacy of the two most widely used mean-field approximations in lattice gases, namely, the Bragg-Williams and the Bethe-Peierls approximations.

Combining off-lattice Monte Carlo and cellular automata for the simulation of hard-sphere systems.

In the present work we show how the update rule of a diffusive cellular automaton with mutual exclusion can be exploited in off-lattice Monte Carlo simulations of hard spheres to obtain a synchronous Monte Carlo sampling that satisfies the detailed balance principle.

A coarse-grained method based on the analysis of short molecular dynamics trajectories for the simulation of non-Markovian dynamics of molecules adsorbed in microporous materials.

We developed a coarse-grained model suitable for the study of adsorbed molecules in microporous materials. A partition of the space available to the motion of adsorbed molecules was carried out, which allows to formulate the dynamics in terms of jumps between discrete regions. The probabilities of observing given pairs of successive jumps were calculated from Molecular Dynamics (MD) simulations, performed on small systems, and used to drive the motion of molecules in a lattice-gas model. Dynamics is thus reformulated in terms of event-space dynamics and this allows to treat the system despite its inherent non markovity. Despite the assumptions enforced in the algorithm, results show that it can be applied to various spherical molecules adsorbed in the all-silica zeolite ITQ-29, establishing a suitable direct bridge between MD simulation results and coarse-grained models.

Synchronous equilibrium model for the diffusion of mutually exclusive particles in a heterogeneous lattice of adsorption sites.

Through straight synchronization and proper manipulation of a sequential Monte Carlo glass-forming rule introduced by Fröbose and Jäckle [J. Stat. Phys. 42, 551 (1986)], we constructed a synchronous, non-glass-forming rule for diffusion of mutually exclusive particles in a lattice of adsorption sites. The rule satisfies detailed balance in the presence of both homogeneous and heterogeneous adsorption energies. Our model differs from the usual lattice-gas cellular automata diffusion rules in that the mutual exclusion holds on the lattice sites rather than on the channels which connect neighboring sites, and from the mass-conserving cellular automata rules in the use of a no-partitioning scheme. The first aim of this work is to show that, although some prescriptions in the synchronous rule are introduced just to allow that both detailed balance and mutual exclusion can coexist with synchronicity, the diffusion process produced by the rule is not anomalous so that the rule can be regarded as a diffusion model. We then compare the diffusion isotherms of several test systems with the ones obtained by means of sequential Monte Carlo simulations of Arrhenius jumps of particles on a lattice. Finally, we apply the rule to the case of a (100) fcc model surface and estimate the amount of time correlation in the migration process, and show that the synchronous rule produces higher correlations and slightly lower diffusivity than the sequential Monte Carlo counterpart.

Conciliating synchronicity with spatial discretization, exclusion, interactions, and detailed balance.

The construction of a discrete stochastic system of interacting particles that evolves through a fully synchronous evolution rule while satisfying detailed balance is a highly demanding task. As a consequence, the presence of nontrivial interaction fields can make synchronicity and thermodynamic equilibrium look as two conflicting counterparts. We show that, with the proper prescriptions, the process of migration of particles in a lattice of mutually exclusive nodes can be simulated with a fully synchronous algorithm, which we call parallel Kawasaki dynamics (PKD), that incorporates site exclusion, local interactions, and detailed balance without the need of system partitioning schemes. We show that the underlying pseudo-Hamiltonian (which is derived from the PKD dynamics instead of being assumed a priori as usual in a sequential Monte Carlo scheme) is temperature dependent and causes the resulting equilibrium properties to differ substantially from the conventional hopping model when the system is near critical conditions.

Chemical potential evaluation in NVT lattice-gas simulations.

The discrete nature of the partition function of a lattice-gas system can be exploited to build an efficient strategy for the evaluation of the chemical potential of a periodic lattice-gas with arbitrarily ranged interactions during a simulation in the canonical ensemble, with the need of no additional sampling as it were required instead by the Widom insertion/deletion approach. The present method is based on the main concepts of the small system grand ensemble [for details, see G. Soto-Campos, D. S. Corti, and H. Reiss, J. Chem. Phys. 108, 2563 (1998)], whose key idea is to study the properties of a sublattice (called small system) and of its complementary (the reservoir sublattice) as they were two separated subsystems. The accuracy of the measured chemical potential can be further improved by artificially "restoring" the missing connections among the reservoir sublattice sites located at the boundaries with the small system. We first illustrate the theory and then we compare µVT with NVT simulation results on several test systems.

A parallelizable block cellular automaton for the study of diffusion of binary mixtures containing CO2 in microporous materials.

We applied a method based on a block cellular automaton (BCA) algorithm to the study of diffusion of various binary mixtures adsorbed in a model microporous material, such as zeolite ZK4. Our aim was to test the capability of our model to cope with systems in which more than one species is present, using a set of parameters based on heuristic considerations from the molecular dynamics (MD) results present in the literature. A rigorous methodology for the assignment of suitable adsorption energies and diffusion activation barriers for our BCA has not been developed yet, nonetheless the results were quite interesting at this stage and we obtained a good qualitative agreement with MD data in the literature. The mixtures we investigated contain CO(2), which causes the so-called segregation-effect, a strong suppression of self-diffusivity of co-adsorbed species. This effect gives rise to relevant problems in the application of some well established and robust methods, while our model proved to be able to reproduce both the common features and the segregation anomaly in the trends of diffusion.

Speeding up simulation of diffusion in zeolites by a parallel synchronous kinetic Monte Carlo algorithm.

Understanding the behaviors of molecules in tight confinement is a challenging task. Standard simulation tools like kinetic Monte Carlo have proven to be very effective in the study of adsorption and diffusion phenomena in microporous materials, but they turn out to be very inefficient when simulation time and length scales are extended. In this paper we have explored the possibility of application of a discrete version of the synchronous parallel kinetic Monte Carlo algorithm introduced by Martínez et al. [J. Comput. Phys. 227, 3804 (2008)] to the study of aromatic hydrocarbons diffusion in zeolites. The efficiency of this algorithm is investigated as a function of the number of processors and domain size. We show that with an accurate choice of domains size it is possible to achieve very good efficiencies thus permitting us to effectively extend space and time scales of the simulated system.

Estimation of Partial Charges in Small Zeolite Imidazolate Frameworks from Density Functional Theory Calculations.

Zeolitic Imidazolate Frameworks (ZIFs) are the new frontier in the field of metal-organic materials. They incorporate the confining properties of the more traditional aluminosilicate zeolites together with the catalytic activity provided by transition metal ions and organic links. Computation of atomic point charges for these hybrid materials is important in the field of molecular simulations for substantial prediction of experimental results. However, due to the structural complexity of advanced materials in general, studies involving derivation of point charges for these materials are truly scarce. In this article, we have derived the atomic point charges of ZIF-8 through fitting of the quantum electrostatic potential obtained systematically from density functional theory (DFT) calculations both on finite clusters of increasing size and on the periodic system. For the periodic system, fluctuations on the atomic charges have been studied through ab initio molecular dynamics simulations. Using the latter approach, we have extended the study to ZIF-2 and ZIF-3, where it has been found that charge fluctuations are, as well as for ZIF-8, very narrow, therefore justifying the use of the point charge approximation for these materials.

From thermodynamic cell models to partitioning cellular automata for diffusion in zeolites. I. Structure of the algorithm.

In the study of adsorption of simple adsorbates in microporous materials like zeolites, thermodynamic models of small grand-canonical cells with very local interactions [e.g., see K. G. Ayappa, J. Chem. Phys. 111, 4736 (1999)] have been proven to be able to produce thermodynamic properties in very good agreement with the results of experiments and atomistic simulations. In this paper we present in details the structure and implementation of a thermodynamic partitioning cellular automaton (PCA) devised as a dynamical version of thermodynamic cell models and proposed as an easy environment to perform coarse-grained simulations of adsorption/diffusion of simple interacting molecules in microporous materials. Local evolution rules and memory effects are introduced to make our PCA able to complete the static picture provided by thermodynamic cell models with the simulation of transport properties.

From thermodynamic cell models to partitioning cellular automata for diffusion in zeolites. II. Static and dynamic properties.

In this second paper we exploit our thermodynamic partitioning cellular automaton (PCA) developed in Paper I [Pazzona et al., J. Chem. Phys. 131, 234703 (2009)] to study interacting molecules adsorbed in microporous materials. We present a mean-field theory of the single cell model at equilibrium followed by a detailed description of the procedure we propose to calculate the chemical potential in the canonical ensemble. Finally we use our approach to simulate transport properties starting from the parameterization devised by Ayappa [J. Chem. Phys. 111, 4736 (1999)] to reproduce the adsorption properties of xenon in zeolite NaA. We report how the correlations included in the PCA evolution rule affect the estimated self-diffusion coefficient.