A cloud platform for automating and sharing analysis of raw simulation data from high throughput polymer molecular dynamics simulations

Open material databases storing hundreds of thousands of material structures and their corresponding properties have become the cornerstone of modern computational materials science. Yet, the raw outputs of the simulations, such as the trajectories from molecular dynamics simulations and charge densities from density functional theory calculations, are generally not shared due to their huge size. In this work, we describe a cloud-based platform to facilitate the sharing of raw data and enable the fast post-processing in the cloud to extract new properties defined by the user. As an initial demonstration, our database currently includes 6286 molecular dynamics trajectories for amorphous polymer electrolytes and 5.7 terabytes of data. We create a public analysis library at https://github.com/TRI-AMDD/htp_md to extract multiple properties from the raw data, using both expert designed functions and machine learning models. The analysis is run automatically with computation in the cloud, and results then populate a database that can be accessed publicly. Our platform encourages users to contribute both new trajectory data and analysis functions via public interfaces. Newly analyzed properties will be incorporated into the database. Finally, we create a front-end user interface at https://www.htpmd.matr.io for browsing and visualization of our data. We envision the platform to be a new way of sharing raw data and new insights for the computational materials science community.Comment: 21 pages, 7 figure

Genomics and transcriptomics yields a system-level view of the biology of the pathogen Naegleria fowleri

Background The opportunistic pathogen Naegleria fowleri establishes infection in the human brain, killing almost invariably within 2 weeks. The amoeba performs piece-meal ingestion, or trogocytosis, of brain material causing direct tissue damage and massive inflammation. The cellular basis distinguishing N. fowleri from other Naegleria species, which are all non-pathogenic, is not known. Yet, with the geographic range of N. fowleri advancing, potentially due to climate change, understanding how this pathogen invades and kills is both important and timely. Results Here, we report an -omics approach to understanding N. fowleri biology and infection at the system level. We sequenced two new strains of N. fowleri and performed a transcriptomic analysis of low- versus high-pathogenicity N. fowleri cultured in a mouse infection model. Comparative analysis provides an in-depth assessment of encoded protein complement between strains, finding high conservation. Molecular evolutionary analyses of multiple diverse cellular systems demonstrate that the N. fowleri genome encodes a similarly complete cellular repertoire to that found in free-living N. gruberi. From transcriptomics, neither stress responses nor traits conferred from lateral gene transfer are suggested as critical for pathogenicity. By contrast, cellular systems such as proteases, lysosomal machinery, and motility, together with metabolic reprogramming and novel N. fowleri proteins, are all implicated in facilitating pathogenicity within the host. Upregulation in mouse-passaged N. fowleri of genes associated with glutamate metabolism and ammonia transport suggests adaptation to available carbon sources in the central nervous system. Conclusions In-depth analysis of Naegleria genomes and transcriptomes provides a model of cellular systems involved in opportunistic pathogenicity, uncovering new angles to understanding the biology of a rare but highly fatal pathogen.publishedVersio

Two legged robot

This research is focused on developing a two legged robot that employs walking and balancing algorithms. The robot utilizes two main microcontrollers which performs most of the information manipulation and control of the servo motors. It consists of 8 DC servo motors forming a pair of legs, each composed of 4 servo motors adjoined together to carry out walking function. The system utilizers two types of sensors, a tilt sensor that will determine the inclination of the robot, and two pairs of pressure sensors that will determine the robot\u27s weight distribution. Additional features such as walking backwards, turning both in the left and right directions, and kicking were also implemented

An Electrochemical Series for Materials

The electrochemical series is a useful tool in electrochemistry, but its effectiveness in materials chemistry is limited by the fact that the standard electrochemical series is based on a relatively small set of reactions, many of which are measured in aqueous solutions. To address this problem, we have used machine learning to create an electrochemical series for inorganic materials from tens of thousands of entries in the Inorganic Crystal Structure Database. We demonstrate that this series is generally more consistent with oxidation states in solid-state materials than the series based on aqueous ions. The electrochemical series was constructed by developing and parameterizing a physical, human-interpretable model of oxidation states in materials. We show that this model enables the prediction of oxidation states from composition in a way that is more accurate than a state-of-the-art transformer-based neural network model. We present applications of our approach to structure prediction, materials discovery, and materials electrochemistry, and we discuss possible additional applications and areas for improvement. To facilitate the use of our approach, we introduce a freely available web site and API

A cloud platform for sharing and automated analysis of raw data from high throughput polymer MD simulations

Open material databases storing thousands of material structures and their properties have become the cornerstone of modern computational materials science. Yet, the raw simulation outputs are generally not shared due to their huge size. In this work, we describe a cloud-based platform to enable fast post-processing of the trajectories and to facilitate sharing of the raw data. As an initial demonstration, our database includes 6286 molecular dynamics trajectories for amorphous polymer electrolytes (5.7 terabytes of data). We create a public analysis library at https://github.com/TRI-AMDD/htp_md to extract ion transport properties from the raw data using expert-designed functions and machine learning models. The analysis is run automatically on the cloud, and the results are uploaded onto an open database. Our platform encourages users to contribute both new trajectory data and analysis functions via public interfaces. Finally, we create a front-end user interface at https://www.htpmd.matr.io/ for browsing and visualization of our data. We envision the platform to be a new way of sharing raw data and new insights for the materials science community

Od pamięci biodziedzicznej do postpamięci

Na tom niniejszy składają się teksty powstałe w oparciu o trojakie spotkania: pierwszy rodzaj stanowiły wykłady prowadzone przez zaproszonych gości, reprezentujących różne dziedziny czy pola badawcze, które w pewnym niezbędnym uproszczeniu podzielić można na historiografię (Ewa Domańska), filozofię (Agata Bielik-Robson), literaturoznawstwo i studia nad pamięcią (Michael Rothberg), filozofię literatury (Michał Paweł Markowski). Wykładom towarzyszyły warsztaty, których prowadzący przedstawiają swoje teksty w części drugiej, a na część trzecią składają się zapisy wystąpień panelowych. Tego typu sesje zajęciowe siłą rzeczy odznaczają się zarówno sporą intensywnością (różnego rodzaju spotkania od rana do wieczora), jak i nieuniknioną rozmaitością spojrzenia, co zresztą stanowi jeden z ogromnych plusów podobnych przedsięwzięć. Kolejnym jest nieco bardziej „personalistyczne” zetknięcie się nie tyle z tekstem, co z postacią autora, a zatem i z osobowością badacza. Klamrą spinającą wszystkie wydarzenia stała się pamięć, bardzo różnie pojmowana i traktowana, a owa różnorodność punktów wyjścia i spojrzeń na formy oraz miejsca funkcjonowania pamięci przerodziła się w bogactwo doświadczeń „nadawców” oraz obfitość doznań (także tych odciskających się w pamięci) „odbiorców”.This volume comprises texts created on the basis of three-fold meetings: the first kind were constituted by lectures led by invited guests, representing various fields and areas of research, which, in some necessary simplification, can be divided into historiography (Ewa Domańska), philosophy (Agata Bielik-Robson), literary and memory studies (Michael Rothberg), and philosophy of literature (Michał Paweł Markowski). The lectures were accompanied by workshops, whose leaders present their texts in the second part of the work, and the third part is made up of notes from panel talks. As per the nature of these types of sessions, they present themselves as highly intense (various meetings from morning until evening), as well as showing the unavoidable variety in outlooks, which is one of the major advantages of such events. Another advantage is a slightly more ‘personalist’ encounter, not so much with text, but with the figure of an author, and thus also with the personality of a researcher. What became the idea bringing all these activities together was memory, understood and treated in very different ways. The variety of starting points and views on the forms and places of the functioning of memory then transformed itself into an abundance of experiences of the ‘originators’ and the richness of feelings (also of those imprinting themselves in memory) of the ‘receivers’

Genomics and transcriptomics yields a system-level view of the biology of the pathogen Naegleria fowleri

Background The opportunistic pathogen Naegleria fowleri establishes infection in the human brain, killing almost invariably within 2 weeks. The amoeba performs piece-meal ingestion, or trogocytosis, of brain material causing direct tissue damage and massive inflammation. The cellular basis distinguishing N. fowleri from other Naegleria species, which are all non-pathogenic, is not known. Yet, with the geographic range of N. fowleri advancing, potentially due to climate change, understanding how this pathogen invades and kills is both important and timely. Results Here, we report an -omics approach to understanding N. fowleri biology and infection at the system level. We sequenced two new strains of N. fowleri and performed a transcriptomic analysis of low- versus high-pathogenicity N. fowleri cultured in a mouse infection model. Comparative analysis provides an in-depth assessment of encoded protein complement between strains, finding high conservation. Molecular evolutionary analyses of multiple diverse cellular systems demonstrate that the N. fowleri genome encodes a similarly complete cellular repertoire to that found in free-living N. gruberi. From transcriptomics, neither stress responses nor traits conferred from lateral gene transfer are suggested as critical for pathogenicity. By contrast, cellular systems such as proteases, lysosomal machinery, and motility, together with metabolic reprogramming and novel N. fowleri proteins, are all implicated in facilitating pathogenicity within the host. Upregulation in mouse-passaged N. fowleri of genes associated with glutamate metabolism and ammonia transport suggests adaptation to available carbon sources in the central nervous system. Conclusions In-depth analysis of Naegleria genomes and transcriptomes provides a model of cellular systems involved in opportunistic pathogenicity, uncovering new angles to understanding the biology of a rare but highly fatal pathogen