Publicações

@article{pmid38839961,

title = {Fault-network geometry influences earthquake frictional behaviour},

author = {Jaeseok Lee and Victor C Tsai and Greg Hirth and Avigyan Chatterjee and Daniel T Trugman},

doi = {10.1038/s41586-024-07518-6},

issn = {1476-4687},

year  = {2024},

date = {2024-07-01},

journal = {Nature},

volume = {631},

number = {8019},

pages = {106--110},

abstract = {Understanding the factors governing the stability of fault slip is a crucial problem in fault mechanics. The importance of fault geometry and roughness on fault-slip behaviour has been highlighted in recent lab experiments and numerical models, and emerging evidence suggests that large-scale complexities in fault networks have a vital role in the fault-rupture process. Here we present a new perspective on fault creep by investigating the link between fault-network geometry and surface creep rates in California, USA. Our analysis reveals that fault groups exhibiting creeping behaviour show smaller misalignment in their fault-network geometry. The observation indicates that the surface fault traces of creeping regions tend to be simple, whereas locked regions tend to be more complex. We propose that the presence of complex fault-network geometries results in geometric locking that promotes stick-slip behaviour characterized by earthquakes, whereas simpler geometries facilitate smooth fault creep. Our findings challenge traditional hypotheses on the physical origins of fault creep explained primarily in terms of fault friction and demonstrate the potential for a new framework in which large-scale earthquake frictional behaviour is determined by a combination of geometric factors and rheological yielding properties.},

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pubstate = {published},

tppubtype = {article}

}

@article{pmid37909079,

title = {Complex patch geometry promotes species coexistence through a reverse competition-colonization trade-off},

author = {Nina Rynne and Geneva Birtles and Jamie Bell and Mung Suan Pau Duhlian and Samuel McNeil and Adel Mehrpooya and Blake Noske and Yadursha Vakeesan and Michael Bode},

doi = {10.1098/rspb.2023.1554},

issn = {1471-2954},

year  = {2023},

date = {2023-11-01},

journal = {Proc Biol Sci},

volume = {290},

number = {2010},

pages = {20231554},

abstract = {Explaining the maintenance of diverse species assemblages is a central goal of ecology and conservation. Recent coexistence mechanisms highlight the role of dispersal as a source of the differences that allow similar species to coexist. Here, we propose a new mechanism for species coexistence that is based on dispersal differences, and on the geometry of the habitat patch. In a finite habitat patch with complex boundaries, species with different dispersal abilities will arrange themselves in stable, concentric patterns of dominance. Species with superior competitive and dispersal abilities will dominate the interior of the patch, with inferior species at the periphery. We demonstrate and explain the mechanism on a simple one-dimensional domain, and then on two-dimensional habitat patches with realistic geometries. Finally, we use metrics from landscape ecology to demonstrate that habitat patches with more complex geometries can more easily support coexistence. The factors that underpin this new coexistence mechanism-different dispersal abilities and habitat patches with complex geometries-are common to many marine and terrestrial ecosystems, and it is therefore possible that the mechanism is a common factor supporting diverse species assemblages.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37590888,

title = {Molecular Geometry and Electronic Structure of Copper Corroles},

author = {Rina Bhowmick and Sabyasachi Roy Chowdhury and Bess Vlaisavljevich},

doi = {10.1021/acs.inorgchem.3c01779},

issn = {1520-510X},

year  = {2023},

date = {2023-08-01},

journal = {Inorg Chem},

volume = {62},

number = {34},

pages = {13877--13891},

abstract = {Copper corroles are known for their unique multiconfigurational electronic structures in the ground state, which arise from the transfer of electrons from the π orbitals of the corrole to the d-orbital of copper. While density functional theory (DFT) provides reasonably good molecular geometries, the determination of the ground spin state and the associated energetics is heavily influenced by functional choice, particularly the percentage of the Hartree-Fock exchange. Using extended multireference perturbation theory methods (XMS-CASPT2), the functional choice can be assessed. The molecular geometries and electronic structures of both the unsubstituted and the -triphenyl copper corroles were investigated. A minimal active space was employed for structural characterization, while larger active spaces are required to examine the electronic structure. The XMS-CASPT2 investigations conclusively identify the ground electronic state as a multiconfigurational singlet (S) with three dominant electronic configurations in its lowest energy and characteristic saddled structure. In contrast, the planar geometry corresponds to the triplet state (T), which is approximately 5 kcal/mol higher in energy compared to the S state for both the bare and substituted copper corroles. Notably, the planarity of the T geometry is reduced in the substituted corrole compared with that in the unsubstituted one. By analyzing the potential energy surface (PES) between the S and T geometries using XMS-CASPT2, the multiconfigurational electronic structure is shown to transition toward a single electron configuration as the saddling angle decreases (i.e., as one approaches the planar geometry). Despite the ability of the functionals to reproduce the minimum energy structures, only the TPSSh-D3 PES is reasonably close to the XMS-CASPT2 surface. Significant deviations along the PES are observed with other functionals.},

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pubstate = {published},

tppubtype = {article}

}

@article{pmid37514103,

title = {Tablet Geometry Effect on the Drug Release Profile from a Hydrogel-Based Drug Delivery System},

author = {Seyed-Farid Mohseni-Motlagh and Roshanak Dolatabadi and Majid Baniassadi and Morad Karimpour and Mostafa Baghani},

doi = {10.3390/pharmaceutics15071917},

issn = {1999-4923},

year  = {2023},

date = {2023-07-01},

journal = {Pharmaceutics},

volume = {15},

number = {7},

abstract = {In order to achieve the optimal level of effectiveness and safety of drugs, it is necessary to control the drug release rate. Therefore, it is important to discover the factors affecting release profile from a drug delivery system. Geometry is one of these effective factors for a tablet-shaped drug delivery system. In this study, an attempt has been made to answer a general question of how the geometry of a tablet can affect the drug release profile. For this purpose, the drug release process of theophylline from two hundred HPMC-based tablets, which are categorized into eight groups of common geometries in the production of oral tablets, was simulated using finite element analysis. The analysis of the results of these simulations was carried out using statistical methods including partial least squares regression and ANOVA tests. The results showed that it is possible to predict the drug release profile by knowing the geometry type and dimensions of a tablet without performing numerous dissolution tests. Another result was that, although in many previous studies the difference in the drug release profile from several tablets with different geometries was interpreted only by variables related to the surface, the results showed that regardless of the type of geometry and its dimensions, it is not possible to have an accurate prediction of the drug release profile. Also, the results showed that without any change in the dose of the drug and the ingredients of the tablet and only because of the difference in geometry type, the tablets significantly differ in release profile. This occurred in such a way that, for example, the release time of the entire drug mass from two tablets with the same mass and materials but different geometries can be different by about seven times.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35038587,

title = {Scaffold geometry modulation of mechanotransduction and its influence on epigenetics},

author = {Pingping Han and Guillermo A Gomez and Georg N Duda and Sašo Ivanovski and Patrina S P Poh},

doi = {10.1016/j.actbio.2022.01.020},

issn = {1878-7568},

year  = {2023},

date = {2023-06-01},

journal = {Acta Biomater},

volume = {163},

pages = {259--274},

abstract = {The dynamics of cell mechanics and epigenetic signatures direct cell behaviour and fate, thus influencing regenerative outcomes. In recent years, the utilisation of 2D geometric (i.e. square, circle, hexagon, triangle or round-shaped) substrates for investigating cell mechanics in response to the extracellular microenvironment have gained increasing interest in regenerative medicine due to their tunable physicochemical properties. In contrast, there is relatively limited knowledge of cell mechanobiology and epigenetics in the context of 3D biomaterial matrices, i.e., hydrogels and scaffolds. Scaffold geometry provides biophysical signals that trigger a nucleus response (regulation of gene expression) and modulates cell behaviour and function. In this review, we explore the potential of additive manufacturing to incorporate multi length-scale geometry features on a scaffold. Then, we discuss how scaffold geometry direct cell and nuclear mechanosensing. We further discuss how cell epigenetics, particularly DNA/histone methylation and histone acetylation, are modulated by scaffold features that lead to specific gene expression and ultimately influence the outcome of tissue regeneration. Overall, we highlight that geometry of different magnitude scales can facilitate the assembly of cells and multicellular tissues into desired functional architectures through the mechanotransduction pathway. Moving forward, the challenge confronting biomedical engineers is the distillation of the vast knowledge to incorporate multiscaled geometrical features that would collectively elicit a favourable tissue regeneration response by harnessing the design flexibility of additive manufacturing. STATEMENT OF SIGNIFICANCE: It is well-established that cells sense and respond to their 2D geometric microenvironment by transmitting extracellular physiochemical forces through the cytoskeleton and biochemical signalling to the nucleus, facilitating epigenetic changes such as DNA methylation, histone acetylation, and microRNA expression. In this context, the current review presents a unique perspective and highlights the importance of 3D architectures (dimensionality and geometries) on cell and nuclear mechanics and epigenetics. Insight into current challenges around the study of mechanobiology and epigenetics utilising additively manufactured 3D scaffold geometries will progress biomaterials research in this space.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36936337,

title = {Geometry Optimization for Miniaturized Thermoelectric Generators},

author = {Gustavo G Dalkiranis and João H C Bocchi and Osvaldo N Oliveira and Gregório C Faria},

doi = {10.1021/acsomega.2c07916},

issn = {2470-1343},

year  = {2023},

date = {2023-03-01},

journal = {ACS Omega},

volume = {8},

number = {10},

pages = {9364--9370},

abstract = {Thermoelectric materials capable of converting heat into electrical energy are used in sustainable electric generators, whose efficiency has been normally increased with incorporation of new materials with high figure of merit (ZT) values. Because the performance of these thermoelectric generators (TEGs) also depends on device geometry, in this study we employ the finite element method to determine optimized geometries for highly efficient miniaturized TEGs. We investigated devices with similar fill factors but with different thermoelectric leg geometries (filled and hollow). Our results show that devices with legs of hollow geometry are more efficient than those with filled geometry for the same length and cross-sectional area of thermoelectric legs. This behavior was observed for thermoelectric leg lengths smaller than 0.1 mm, where the leg shape causes a significant difference in temperature distribution along the device. It was found that for reaching highly efficient miniaturized TEGs, one has to consider the leg geometry in addition to the thermal conductivity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38162460,

title = {Geometry and convergence of natural policy gradient methods},

author = {Johannes Müller and Guido Montúfar},

doi = {10.1007/s41884-023-00106-z},

issn = {2511-249X},

year  = {2023},

date = {2023-01-01},

journal = {Inf Geom},

volume = {7},

number = {Suppl 1},

pages = {485--523},

abstract = {We study the convergence of several natural policy gradient (NPG) methods in infinite-horizon discounted Markov decision processes with regular policy parametrizations. For a variety of NPGs and reward functions we show that the trajectories in state-action space are solutions of gradient flows with respect to Hessian geometries, based on which we obtain global convergence guarantees and convergence rates. In particular, we show linear convergence for unregularized and regularized NPG flows with the metrics proposed by Kakade and Morimura and co-authors by observing that these arise from the Hessian geometries of conditional entropy and entropy respectively. Further, we obtain sublinear convergence rates for Hessian geometries arising from other convex functions like log-barriers. Finally, we interpret the discrete-time NPG methods with regularized rewards as inexact Newton methods if the NPG is defined with respect to the Hessian geometry of the regularizer. This yields local quadratic convergence rates of these methods for step size equal to the inverse penalization strength.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35395877,

title = {Geometry meta-optimization},

author = {Daniel Huang and Junwei Lucas Bao and Jean-Baptiste Tristan},

doi = {10.1063/5.0087165},

issn = {1089-7690},

year  = {2022},

date = {2022-04-01},

journal = {J Chem Phys},

volume = {156},

number = {13},

pages = {134109},

abstract = {Recent work has demonstrated the promise of using machine-learned surrogates, in particular, Gaussian process (GP) surrogates, in reducing the number of electronic structure calculations (ESCs) needed to perform surrogate model based (SMB) geometry optimization. In this paper, we study geometry meta-optimization with GP surrogates where a SMB optimizer additionally learns from its past "experience" performing geometry optimization. To validate this idea, we start with the simplest setting where a geometry meta-optimizer learns from previous optimizations of the same molecule with different initial-guess geometries. We give empirical evidence that geometry meta-optimization with GP surrogates is effective and requires less tuning compared to SMB optimization with GP surrogates on the ANI-1 dataset of off-equilibrium initial structures of small organic molecules. Unlike SMB optimization where a surrogate should be immediately useful for optimizing a given geometry, a surrogate in geometry meta-optimization has more flexibility because it can distribute its ESC savings across a set of geometries. Indeed, we find that GP surrogates that preserve rotational invariance provide increased marginal ESC savings across geometries. As a more stringent test, we also apply geometry meta-optimization to conformational search on a hand-constructed dataset of hydrocarbons and alcohols. We observe that while SMB optimization and geometry meta-optimization do save on ESCs, they also tend to miss higher energy conformers compared to standard geometry optimization. We believe that further research into characterizing the divergence between GP surrogates and potential energy surfaces is critical not only for advancing geometry meta-optimization but also for exploring the potential of machine-learned surrogates in geometry optimization in general.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33590321,

title = {Information geometry for phylogenetic trees},

author = {M K Garba and T M W Nye and J Lueg and S F Huckemann},

doi = {10.1007/s00285-021-01553-x},

issn = {1432-1416},

year  = {2021},

date = {2021-02-01},

journal = {J Math Biol},

volume = {82},

number = {3},

pages = {19},

abstract = {We propose a new space of phylogenetic trees which we call wald space. The motivation is to develop a space suitable for statistical analysis of phylogenies, but with a geometry based on more biologically principled assumptions than existing spaces: in wald space, trees are close if they induce similar distributions on genetic sequence data. As a point set, wald space contains the previously developed Billera-Holmes-Vogtmann (BHV) tree space; it also contains disconnected forests, like the edge-product (EP) space but without certain singularities of the EP space. We investigate two related geometries on wald space. The first is the geometry of the Fisher information metric of character distributions induced by the two-state symmetric Markov substitution process on each tree. Infinitesimally, the metric is proportional to the Kullback-Leibler divergence, or equivalently, as we show, to any f-divergence. The second geometry is obtained analogously but using a related continuous-valued Gaussian process on each tree, and it can be viewed as the trace metric of the affine-invariant metric for covariance matrices. We derive a gradient descent algorithm to project from the ambient space of covariance matrices to wald space. For both geometries we derive computational methods to compute geodesics in polynomial time and show numerically that the two information geometries (discrete and continuous) are very similar. In particular, geodesics are approximated extrinsically. Comparison with the BHV geometry shows that our canonical and biologically motivated space is substantially different.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34595161,

title = {Porous Geometry Guided Micro-mechanical Environment Within Scaffolds for Cell Mechanobiology Study in Bone Tissue Engineering},

author = {Feihu Zhao and Yi Xiong and Keita Ito and Bert van Rietbergen and Sandra Hofmann},

doi = {10.3389/fbioe.2021.736489},

issn = {2296-4185},

year  = {2021},

date = {2021-01-01},

journal = {Front Bioeng Biotechnol},

volume = {9},

pages = {736489},

abstract = {Mechanobiology research is for understanding the role of mechanics in cell physiology and pathology. It will have implications for studying bone physiology and pathology and to guide the strategy for regenerating both the structural and functional features of bone. Mechanobiological studies  apply a dynamic micro-mechanical environment to cells  bioreactors. Porous scaffolds are commonly used for housing the cells in a three-dimensional (3D) culturing environment. Such scaffolds usually have different pore geometries (e.g. with different pore shapes, pore dimensions and porosities). These pore geometries can affect the internal micro-mechanical environment that the cells experience when loaded in the bioreactor. Therefore, to adjust the applied micro-mechanical environment on cells, researchers can tune either the applied load and/or the design of the scaffold pore geometries. This review will provide information on how the micro-mechanical environment (e.g. fluid-induced wall shear stress and mechanical strain) is affected by various scaffold pore geometries within different bioreactors. It shall allow researchers to estimate/quantify the micro-mechanical environment according to the already known pore geometry information, or to find a suitable pore geometry according to the desirable micro-mechanical environment to be applied. Finally, as future work, artificial intelligent - assisted techniques, which can achieve an automatic design of solid porous scaffold geometry for tuning/optimising the micro-mechanical environment are suggested.},

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pubstate = {published},

tppubtype = {article}

}