The issue of reproducibility of computational models and the related FAIR principles (findable, accessible, interoperable, and reusable) are examined in a specific test case. I analyze a ...computational model of the segment polarity network in
embryos published in 2000. Despite the high number of citations to this publication, 23 years later the model is barely accessible, and consequently not interoperable. Following the text of the original publication allowed successfully encoding the model for the open source software COPASI. Subsequently saving the model in the SBML format allowed it to be
in other open source software packages. Submission of this SBML encoding of the model to the BioModels database enables its
and
. This demonstrates how the FAIR principles can be successfully enabled by using open source software, widely adopted standards, and public repositories, facilitating reproducibility and reuse of computational cell biology models that will outlive the specific software used.
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•Addresses gaps in review literature by proposing a comprehensive mechanistic view for heterogenous nickel-acid catalysts.•Highlights relevant conditions to steer product ...distributions of ethylene oligomerization towards desirable products.•Focuses on environmentally-friendly and flexlble catalysts to produce a range of products for ever-changing market demands.
Light alkene oligomerization on heterogeneous acidic catalysts is widely and successfully used in current commercial processes. However, ethylene oligomerization remains inefficient due to ethylene’s inability to form reaction intermediates to a sufficient extent on acid sites. Adding Ni(II) on solid acids can more efficiently catalyze ethylene oligomerization and selectively produce butenes to fuel range products. The review proposes a complete and detailed mechanism of heterogenous Ni-catalyzed oligomerization, whose structures are supported by combining various studies throughout recent literature, and focuses on the bifunctional effects of the nickel and acid sites on ethylene oligomerization. Using experiments, first-principles calculations, and kinetic modeling, Ni2+ has been shown to selectively oligomerize ethylene to light, linear alkenes via the Cossee-Arlman mechanism, while Brønsted H+ sites catalyze further alkylation, cracking, and isomerization reactions. The effects of reaction conditions and catalyst properties on selectivity and activity for oligomerization are systematically discussed. Tuning the relative nickel-to-acid site ratio and the framework support can allow for an optimal catalyst design directed towards desirable products.
Computational models can be created more efficiently by composing them from smaller, well-defined sub-models that represent specific cellular structures that appear often in different contexts. ...Cellular iron metabolism is a prime example of this as multiple cell types tend to rely on a similar set of components (proteins and regulatory mechanisms) to ensure iron balance. One recurrent component, ferritin, is the primary iron storage protein in mammalian cells and is necessary for cellular iron homeostasis. Its ability to sequester iron protects cells from rising concentrations of ferrous iron limiting oxidative cell damage. The focus of the present work is establishing a model that tractably represents the ferritin iron sequestration kinetics such that it can be incorporated into larger cell models, in addition to contributing to the understanding of general ferritin iron sequestration dynamics within cells. The model's parameter values were determined from published kinetic and binding experiments and the model was validated against independent data not used in its construction. Simulation results indicate that FT concentration is the most impactful on overall sequestration dynamics, while the FT iron saturation (number of iron atoms sequestered per FT cage) fine tunes the initial rates. Finally, because this model has a small number of reactions and species, was built to represent important details of FT kinetics, and has flexibility to include subtle changes in subunit composition, we propose it to be used as a building block in a variety of specific cell type models of iron metabolism.
Abstract
This article explores the patterns of class inequality and capital accumulation in Brazil, showing the drivers and limits of the decline in inequality that occurred during the Workers’ Party ...governments. It proposes that minimum wage hikes and greater social security changed the demand pattern and kick-started a cumulative causation process. Growth and redistribution thus reinforced each other for a period, and then spelled their own limits. As growth accelerated in the 2000s, a Gini decomposition indicates that class inequality decreased, but confined to changes between workers—capitalist income and social stratification were preserved. This also endogenously led to a regressive structural change, as low-productivity, labour-intensive services grew and international trade patterns worsened. This created a medium-term dependence on commodity prices for balance-of-trade solvency, and heightened cost-push inflation, which could not be overcome under the limited policy framework in place. The constrained basis for reducing inequality and the regressive structural change underscore that developmental strategies requires broad, multi-dimensional inequality-reducing measures and an encompassing catching-up project.
In this paper, we propose a novel multiclass classifier for the open-set recognition scenario. This scenario is the one in which there are no a priori training samples for some classes that might ...appear during testing. Usually, many applications are inherently open set. Consequently, successful closed-set solutions in the literature are not always suitable for real-world recognition problems. The proposed open-set classifier extends upon the Nearest-Neighbor (NN) classifier. Nearest neighbors are simple, parameter independent, multiclass, and widely used for closed-set problems. The proposed Open-Set NN (OSNN) method incorporates the ability of recognizing samples belonging to classes that are unknown at training time, being suitable for open-set recognition. In addition, we explore evaluation measures for open-set problems, properly measuring the resilience of methods to unknown classes during testing. For validation, we consider large freely-available benchmarks with different open-set recognition regimes and demonstrate that the proposed OSNN significantly outperforms their counterparts in the literature.
ChEBI is a database and ontology containing information about chemical entities of biological interest. It currently includes over 46,000 entries, each of which is classified within the ontology and ...assigned multiple annotations including (where relevant) a chemical structure, database cross-references, synonyms and literature citations. All content is freely available and can be accessed online at http://www.ebi.ac.uk/chebi. In this update paper, we describe recent improvements and additions to the ChEBI offering. We have substantially extended our collection of endogenous metabolites for several organisms including human, mouse, Escherichia coli and yeast. Our front-end has also been reworked and updated, improving the user experience, removing our dependency on Java applets in favour of embedded JavaScript components and moving from a monthly release update to a 'live' website. Programmatic access has been improved by the introduction of a library, libChEBI, in Java, Python and Matlab. Furthermore, we have added two new tools, namely an analysis tool, BiNChE, and a query tool for the ontology, OntoQuery.
•Hydrogenating activity per total adsorbing sites depends on the zeolite.•Pt acid sites proximity may lead to higher hydrogen spillover efficiency.•Pt zeolite catalysts exhibit increasing TOF with ...increasing accessible Pt.•Activity per total adsorbing sites is proposed as a faithful measure.
Toluene hydrogenation was studied over catalysts based on Pt supported on large pore zeolites (HUSY and HBEA) with different metal/acid ratios. Acidity of zeolites was assessed by pyridine adsorption followed by FTIR showing only small changes before and after Pt introduction. Metal dispersion was determined by H2–O2 titration and verified by a linear correlation with the intensity of Pt0–CO band obtained by in situ FTIR. It was also observed that the electronic properties of Pt0 clusters were similar for the different catalysts. Catalytic tests showed rapid catalyst deactivation with an activity loss of 80–95% after 60min of reaction. The turnover frequency of fresh catalysts depended both on metal dispersion and the support. For the same support, it changed by a 1.7-fold (HBEA) and 4.0-fold (HUSY) showing that toluene hydrogenation is structure-sensitive, i.e. hydrogenating activity is not a unique function of accessible metal. This was proposed to be due to the contribution to the overall activity of the hydrogenation of adsorbed toluene on acid sites via hydrogen spillover. Taking into account the role of zeolite acidity, the catalysts series were compared by the activity per total adsorbing sites which was observed to increase steadily with nPt/(nPt+nA). An increase of the accessible Pt atoms leads to an increase on the amount of spilled over hydrogen available in acid sites therefore increasing the overall activity. Pt/HBEA catalysts were found to be more active per total adsorbing site than Pt/HUSY which is proposed to be due to an augmentation in the efficiency of spilled over hydrogen diffusion related to the proximity between Pt clusters and acid sites. The intervention of Lewis acid sites in a greater extent than that measured by pyridine adsorption may also contribute to this higher activity of Pt/HBEA catalysts. These results reinforce the importance of model reactions as a closer perspective to the relevant catalyst properties in reaction conditions.
Open science and data are yet to make a real breakthrough and research policies will have a critical role in it. The history and general context around open data is hence firstly addressed, including ...how researchers perceive the existing incentives, leading to recommendations on how to foster data sharing. Subsequently, the focus is on catalysis, with a particular emphasis on benchmarking the data sharing practices against other fields and surveying the type of data currently being shared. The current infrastructure, including data repositories, and standards formats is maped. The striking differences among different disciplines are discussed, serving as a basis to propose specific actions to promote data sharing in catalysis. Short‐term initiatives are needed to boost the amount of openly available data, particularly in heterogeneous catalysis, but a high degree of standardization in data formats will be needed to ensure optimal and automated data mining in the long run. Because of its unique, central role in understanding the catalytic action, kinetic catalytic data is of particular interest. As formats and mining tools are dependant on the type of data, kinetic catalytic data is firstly characterized. Guidelines for a standardized sharing format are proposed, taking into account the small, well‐structured nature of this type of data. To maximize the extraction of information, the low volume of kinetic catalytic data will be compensated by incorporating fundamental knowledge into statistics‐based tools. Whencoupled with knowledge generation tools, i. e. kinetic models, new insights at the active site and mechanism levels will be reached in an ever more automated and powerful way.
Catalysis informatics: Sharing data enables scientists to join efforts worldwide to solve key scientific puzzles. For optimal data (re)usage, raw data should be shared in machine readable unified formats via open databases. Specific guidelines for data sharing in catalysis are discussed, together with relevant tools for data‐centric knowledge generation.
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