14,486 research outputs found
Study of the structural and dynamical properties of a biomimetic compound of diiron proteins via ab initio and hybrid (QM/MM) molecular dynamics simulations.
No full textA recipe for the computation of the free energy barrier and the lowest free energy path of concerted reactions
No full textThe recently introduced hills method (Proc. Natt. Acad. Sci. U.S.A. 2002, 99, 12562) is a powerful tool to compute the multidimensional free energy surface of intrinsically concerted reactions. We have extended this method by focusing our attention on localizing the lowest free energy path that connects the stable reactant and product states. This path represents the most probable reaction mechanism, similar to the zero temperature intrinsic reaction coordinate, but also includes finite temperature effects. The transformation of the multidimensional problem to a one-dimensional reaction coordinate allows for accurate convergence of the free energy profile along the lowest free energy path using standard free energy methods. Here we apply the hills method, our lowest free energy path search algorithm, and umbrella sampling to the prototype S(N)2 reaction. The hills method replaces the in many cases difficult problem of finding a good reaction coordinate with choosing relatively simple collective variables, such as the bond lengths of the broken and formed chemical bonds. The second part of the paper presents a guide to using the hills method, in which we test and fine-tune the method for optimal accuracy and efficiency using the umbrella sampling results as a reference
Metadata Representations for Queryable ML Model Zoos
No full textMachine learning (ML) practitioners and organizations are building model zoos of pre-trained models, containing metadata describing properties of the ML models and datasets that are useful for reporting, auditing, reproducibility, and interpretability purposes. The metatada is currently not standardised; its expressivity is limited; and there is no interoperable way to store and query it. Consequently, model search, reuse, comparison, and composition are hindered. In this paper, we advocate for standardized ML model metadata representation and management, proposing a toolkit supported to help practitioners manage and query that metadata.Web Information SystemsHuman-Centred Artificial Intelligenc
A Manifesto of Nodalism
No full textThis paper proposes the notion of Nodalism as a means describing contemporary culture and of understanding my own creative practice in electronic music composition. It draws on theories and ideas from Kirby, Bauman, Bourriaud, Deleuze, Guatarri, and Gochenour, to demonstrate how networks of ideas or connectionist neural models of cognitive behaviour can be used to contextualize, understand and become a creative tool for the creation of contemporary electronic music
Andreas G. Klein - The Quasi-ML approach for modeling nonlinear SEM
No full textContent:
Nonlinear SEM, Model Types and Estimation; Approaches to Nonlinear SEM; Quasi-ML Techniques; Quasi-ML Matrix Commands; Heterogeneity of Growt
Optimizing ML Inference Queries Under Constraints
No full textThe proliferation of pre-trained ML models in public Web-based model zoos facilitates the engineering of ML pipelines to address complex inference queries over datasets and streams of unstructured content. Constructing optimal plan for a query is hard, especially when constraints (e.g. accuracy or execution time) must be taken into consideration, and the complexity of the inference query increases. To address this issue, we propose a method for optimizing ML inference queries that selects the most suitable ML models to use, as well as the order in which those models are executed. We formally define the constraint-based ML inference query optimization problem, formulate it as a Mixed Integer Programming (MIP) problem, and develop an optimizer that maximizes accuracy given constraints. This optimizer is capable of navigating a large search space to identify optimal query plans on various model zoos.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Web Information SystemsHuman-Centred Artificial Intelligenc
Low ML Decoding Complexity STBCs via Codes Over the Klein Group
No full textIn this paper, we give a new framework for constructing low ML decoding complexity space-time block codes (STBCs) using codes over the Klein group K. Almost all known low ML decoding complexity STBCs can be obtained via this approach. New full-diversity STBCs with low ML decoding complexity and cubic shaping property are constructed, via codes over K, for number of transmit antennas N=2m, m ≥ 1, and rates R >; 1 complex symbols per channel use. When R=N , the new STBCs are information-lossless as well. The new class of STBCs have the least known ML decoding complexity among all the codes available in the literature for a large set of (N,R) pairs
Low ML Decoding Complexity STBCs via Codes Over the Klein Group
No full textIn this paper, we give a new framework for constructing low ML decoding complexity space-time block codes (STBCs) using codes over the Klein group K. Almost all known low ML decoding complexity STBCs can be obtained via this approach. New full- diversity STBCs with low ML decoding complexity and cubic shaping property are constructed, via codes over K, for number of transmit antennas N = 2(m), m >= 1, and rates R > 1 complex symbols per channel use. When R = N, the new STBCs are information- lossless as well. The new class of STBCs have the least knownML decoding complexity among all the codes available in the literature for a large set of (N, R) pairs
Building a generalisable ML pipeline at ING
No full textAdvances in data science have caused an increase in the use of Artificial Intelligence (AI), specifically Machine Learning (ML), throughout various fields. Not only in research but in the industry as well, has ML been receiving increasing amounts of interest. Many companies rely on ML models to increase the efficiency of existing processes or offer new services and products. The industry, however, is facing several additional challenges compared to the academic context. One of those challenges is applying the Development Operations (DevOps) model to an ML application, also referred to as MLOps. This thesis sets out to find the specific challenges that practitioners encounter while operationalising ML models. To do so, we perform a single-case case study on an ML pipeline built by the Trade & Communication Surveillance team at the ING bank. This case study consists of conducting a set of interviews and performing a manual code inspection of the pipeline. The team faces challenges ranging from having insufficient time for operationalising each ML project individually to operating in the highlyregulated fintech context. Their pipeline is able to deploy a single ML model but it does not generalise well to other projects. We present the first version of an application that mitigates these challenges. The application is able to deploy ML models to the development environment at ING and can be operated by data scientists to reduce the effort of operationalising an ML model. Computer Science | Software Technolog
Catalytic metal ions and enzymatic processing of DNA and RNA.
No full textTwo-metal-ion-dependent nucleases cleave the phosphodiester bonds of nucleic acids via the two-metal-ion (2M) mechanism. Several high-resolution X-ray structures portraying the two-metal-aided catalytic site, together with mutagenesis and kinetics studies, have demonstrated a functional role of the ions for catalysis in numerous metallonucleases. Overall, the experimental data confirm the general mechanistic hypothesis for 2M-aided phosphoryl transfer originally reported by Steitz and Steitz ( Proc. Natl. Acad. Sci. U.S.A. 1993 , 90 ( 14 ), 6498 - 6502 ). This seminal paper proposed that one metal ion favors the formation of the nucleophile, while the nearby second metal ion facilitates leaving group departure during RNA hydrolysis. Both metals were suggested to stabilize the enzymatic transition state. Nevertheless, static X-ray structures alone cannot exhaustively unravel how the two ions execute their functional role along the enzymatic reaction during processing of DNA or RNA strands when moving from reactants to products, passing through metastable intermediates and high-energy transition states. In this Account, we discuss the role of multiscale molecular simulations in further disclosing mechanistic insights of 2M-aided catalysis for two prototypical enzymatic targets for drug discovery, namely, ribonuclease H (RNase H) and type II topoisomerase (topoII). In both examples, first-principles molecular simulations, integrated with structural data, emphasize a cooperative motion of the bimetal motif during catalysis. The coordinated motion of both ions is crucial for maintaining a flexible metal-centered structural architecture exquisitely tailored to accommodate the DNA or RNA sugar-phosphate backbone during phosphodiester bond cleavage. Furthermore, our analysis of RNase H and the N-terminal domain (PAN) of influenza polymerase shows that classical molecular dynamics simulations coupled with enhanced sampling techniques have contributed to describe the modulatory effect of metal ion concentration and metal uptake on the 2M mechanism and efficiency. These aspects all point to the emerging and intriguing role of additional adjacent ions potentially involved in the modulation of phosphoryl transfer reactions and enzymatic turnover in 2M-catalysis, as recently observed experimentally in polymerase η and homing endonuclease I-DmoI. These computational results, integrated with experimental findings, describe and reinforce the nascent concept of a functional and cooperative dynamics of the catalytic metal ions during the 2M-dependent enzymatic processing of DNA and RNA. Encouraged by the insights provided by computational approaches, we foresee further experiments that will feature the functional and joint dynamics of the catalytic metal ions for nucleic acid processing. This could impact the de novo design of artificial metallonucleases and the rational design of potent metal-chelating inhibitors of pharmaceutically relevant enzymes
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