Automata Tutor v3

Computer science class enrollments have rapidly risen in the past decade. With current class sizes, standard approaches to grading and providing personalized feedback are no longer possible and new techniques become both feasible and necessary. In this paper, we present the third version of Automata Tutor, a tool for helping teachers and students in large courses on automata and formal languages. The second version of Automata Tutor supported automatic grading and feedback for finite-automata constructions and has already been used by thousands of users in dozens of countries. This new version of Automata Tutor supports automated grading and feedback generation for a greatly extended variety of new problems, including problems that ask students to create regular expressions, context-free grammars, pushdown automata and Turing machines corresponding to a given description, and problems about converting between equivalent models - e.g., from regular expressions to nondeterministic finite automata. Moreover, for several problems, this new version also enables teachers and students to automatically generate new problem instances. We also present the results of a survey run on a class of 950 students, which shows very positive results about the usability and usefulness of the tool

A complete small molecule dataset from the protein data bank

AbstractA complete set of 6300 small molecule ligands was extracted from the protein data bank, and deposited online in PubChem as data source ‘SMID’. This set’s major improvement over prior methods is the inclusion of cyclic polypeptides and branched polysaccharides, including an unambiguous nomenclature, in addition to normal monomeric ligands. Only the best available example of each ligand structure is retained, and an additional dataset is maintained containing co-ordinates for all examples of each structure. Attempts are made to correct ambiguous atomic elements and other common errors, and a perception algorithm was used to determine bond order and aromaticity when no other information was available

If My Grandmother Had Wheels She\u27d Be A Trolley Car: The Accumulation of Objects, Encounters and The Passage of Time

The house is the structure. Within the house are rooms, spaces, hallways and corners. In those live the objects.The objects live on surfaces, surfaces that much like the previous layers, are made up of many things, most certainly not one thing. A static object may hold a series of other objects, spaces and events. A static object may also embody the passage of time.Though one may try to hold the object at a constant, that is to slow or even bring a halt to its motion, this task is near impossible. Bird Box House, Bear Box Dresser, Lamp Hat, Macaroni Light Tears, Dresser, Ginger Ale Bottle, Wine Bottle, Beer Bottle, Medicine Bottle, Bagel These objects are anything but singular. They hold many things at once. They are superpositions of everyday objects. My accumulating marks attempt to take a physical account for this motion, the passage of time. When the object begins to grow hair, fur or feathers, in the moment of the drawing, the painting, the bird box, the object, time stands still…bearly

Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates

Computational drug design based on artificial intelligence is an emerging research area. At the time of writing this paper, the world suffers from an outbreak of the coronavirus SARS-CoV-2. A promising way to stop the virus replication is via protease inhibition. We propose an evolutionary multi-objective algorithm (EMOA) to design potential protease inhibitors for SARS-CoV-2's main protease. Based on the SELFIES representation the EMOA maximizes the binding of candidate ligands to the protein using the docking tool QuickVina 2, while at the same time taking into account further objectives like drug-likeliness or the fulfillment of filter constraints. The experimental part analyzes the evolutionary process and discusses the inhibitor candidates.Comment: 15 pages, 7 figures, submitted to PPSN 202

Margaret Weininger, transcript only

Transcript of an interview with Margaret Weininger, née Kulka, by Lucille Brown of Union College. Margaret went by Greta and was born in 1892 in a section of Moravia that was part of Austria at the time she was born and is now in the Czech Republic.https://digitalworks.union.edu/berkoralhistories/1014/thumbnail.jp

The creation and characterisation of a National Compound Collection: the Royal Society of Chemistry pilot

We present a summary of the National Compound Collection (NCC) pilot; which harvested chemical structure data from 746 publicly-available PhD theses to create an enhanced database of diverse and interesting (largely organic) molecular entities. The database comprised ∼75 000 structure entries, of which 70% were new to ChemSpider at the time of upload. The dataset was evaluated for structural uniqueness by twelve external drug discovery groups from the pharmaceutical, biotech, academic and not-for-profit sectors. These partners generated data reported here comparing the NCC pilot with their in-house compound collections. The proportion of NCC structures considered to be useful for drug discovery ranged from 5–80% depending on the strictness of the filters used; most interestingly from a drug discovery standpoint ∼13k NCC compounds (18% of the NCC) passed the filters and were of good diversity. These compounds are quite different from those that are already present in the screening collections but not so different that they are no longer considered to be drug-like. In general, the drug discovery teams would consider these compounds to be high value molecules for inclusion in their screening collections. This pilot addressed the potential value of unpublished data and explored the practicalities of large-scale data extraction, to inform both retrospective and prospective extraction of chemical data from theses