dataesr/scientific-paragraphs-categorization huggingface dataset:
Retrieval of b-Lactamase Sequences Protein sequences of b-lactamase enzymes were obtained from Antibiotic Resistance Gene-ANNOTation (ARG-ANNOT) database  (Gupta et al. 2014). A total of 1,155 sequences (bacterial sequences) were retrieved, which were then classified into four Ambler molecular classes using available literature and resources in the public domain. These sequences were categorized as 620 in Class A, 174 in Class B, 151 in Class C, and 210 in Class D.
Homologous Sequence Detection from Biological Databases In order to identify of homologous sequences from sequence databases, we used two methods; a BLAST search analysis with the reconstructed ancestral sequences and an HMM profile search. Ancestral sequences and HMM profiles were generated for each class of b-lactamases (A-D) separately. We used ancestral sequences and HMM profiles as a probe/query for homologous sequence similarity searches in biological sequence databases. In supplementary file S1, Supplementary Material online, we show that ancestral sequences are more efficient than extant enzymes, and the BLAST search analysis of extant enzymes retrieved significant hits which were completely covered by BLAST hits of the ancestral sequence. We selected potential homologous sequences under the following BLAST settings: 30% sequence identity, 50% query length coverage, and an e-value cut-off of 1e-10.
HMM profiles of extant b-lactamases were generated using HMMER3  (Eddy et al. 2011)  software. A profile is a description of the consensus of a multiple sequence alignment and uses a position-specific scoring system to capture information about the degree of conservation at different position in the alignment. The maximum-likelihood multiple sequence alignment of each class of b-lactamases were subjected to HMMER3 using the "hmmbuild" command. The HMM profiles of four classes of b-lactamases were then queried against biological sequence databases (for a homologous sequence search) using the "hmmsearch" command. An e-value of 1e-10 was adopted during the HMM profile search. To identify novel b-lactamases, four biological databases, environmental protein sequence database (env_nr), the human microbiome project reference genome (HMP-HMRGD), the human microbiome project metagenomic database (HMP-HMASM), and the NCBI nonredundant (nr) database were considered.
At the time of analysis (September 2015), there were 6,891,928 protein sequences in the env_nr database, 78,625,685 protein sequences in the NCBI nr database, 2,537,354 protein sequences in the HMP reference genome database, and 75,199,622 (predicted ORF) protein sequences in the HMP metagenome database. To detect homologous sequences in the human microbiome database, 50 million assembled metagenomic scaffolds were downloaded. These sequences were associated with 16 body sites (anterior nares, attached keratinized gingiva, buccal mucosa, hard palate, left retroauricular crease, midvagina, palatine tonsils, posterior fornix, right retroauricular crease, saliva, stool, subgingival plaque, supragingival plaque, throat, tongue dorsum, and vaginal introitus). Potential protein coding regions (ORFs) were predicted using the getorf command in EMBOSS  (Rice et al.
Identifying the Domain Composition of Putative b-Lactamases All the candidate sequences identified through the HMM profile search and ancestral sequences were queried against the Pfam release 30. 0 web interface  (Bateman et al. 1999 ) and the NCBI's Conserved Domain Database  (Marchler-Bauer 2011; Marchler-Bauer et al. 2015). The Pfam and CDD were executed with the default setting on their respective websites.
BLAST Search Analysis against PATRIC Database All the selected putative b-lactamases were queried in a protein BLAST search analysis against the PATRIC (Pathosystems Resource Integration Center) database  (Wattam et al. 2014 ) to detect of antibiotic resistance genes. A total of 90,597 sequences were obtained from the PATRIC database. We selected potential sequences under the following BLAST settings: 30% sequence identity, 50% query length coverage, and an e-value cut-off of 1e-10. The protein BLAST search analysis of all identified putative sequences against the PATRIC database indicates that all these sequences are antibiotic resistance genes (supplementary table  S1 , Supplementary Material online).
Multiple sequence alignment trimming was performed using the trimAL, which removes poorly aligned regions  (Capella et al. 2009). Approximate maximum-likelihood phylogenetic trees were constructed using the WAG substitution model in FastTree  (Price et al. 2010 ) and visualized with FigTree-v1. 4. 2 (http://tree. bio. ed. ac. uk/software/figtree/; last accessed July 5, 2017).
Homologous Sequence Identification and Phylogenetic Tree Construction For the comprehensive identification of homologous sequences, we executed three types of analysis: a BLAST search analysis with the extant b-lactamases, a BLAST search analysis with the reconstructed ancestral sequences, and an HMM profile search in four biological databases (details can be found in Materials and Methods). In the present study, we found numerous putative b-lactamases through the HMM profile search, as compared with the extant and ancestral sequence-based BLAST search analyses. Moreover, we noticed that most (>95%) of the significant putative homologues (detected by the ancestral and extant BLAST) were also identified by the HMM profile search. Therefore, in this study, we mainly discuss the results obtained from the HMM profile search, and present ancestral sequence-based results when novel hits were obtained.
Class A The HMM profile search of class A b-lactamases in four biological databases retrieved a total of 13,720 (env_nr: 298, HMP metagenome: 2812, HMP reference genome: 261, NCBI nr: 10349) significant putative b-lactamase-like sequences, which contain b-lactamase functional characteristics (functional b-lactamase domain, and characteristic amino acid motifs) (supplementary table S1, Supplementary Material online). The presence of the b-lactamase domain suggests that these are possibly functional b-lactamases. In contrast, the BLAST search analysis of reconstructed ancestral sequences was able to identify a total of 10,182 (env_nr: 160, HMP metagenome: 1886, HMP reference   S1 , Supplementary Material online). Of these sequences, 97% (9,889) were detected through the HMM profile search and only 3% (293) from the NCBI nr database were found to be unique and not detected by the HMM profile search.
2 ). Since these clades are clustered separately without any extant enzymes, they were considered as "novel clades". The bacterial b-lactamase sequences were considered for the construction of ancestral and HMM profiles. In this report, the HMM profile search analysis detected remote homologous sequences from archaea domains (such as Haladaptatus paucihalophilus, Halobacteriaceae archaeon SB9, Halococcus agarilyticus, Halococcus sediminicola, Halostagnicola larsenii, and Halostagnicola larsenii JCM 1346). This finding indicates that the HMM profile search analysis detected homologues which were distantly related to archaea. Other than archaea, all sequences are related to bacterial domain and metagenomic. The metagenomic sequences are not annotated in public databases, therefore, their source of organisms are unknown.
3 ). The multiples sequence alignment shows H 131,133,222,291 conserved amino acid residues (supplementary file S3, Supplementary Material online). souniana). This finding suggested that the HMM profile of bacterial sequences was able to detect homologous sequences which were remote from the archaea domain. Other than archaea, all sequences are related to bacteria and metagenomes. The metagenomic sequences are not annotated in public databases, therefore, their source of organisms are unknown. A number of other proteins contain the metallo-b-lactamase domain. These proteins include glyoxalase IIs, A-type flavoproteins, and ribonucleases  (Alderson et al. 2014). Therefore, in the present phylogenetic diversity analysis (fig. 3 ), we selected some sequences from this diverse set of enzymes, along with extant and newly identified putative blactamase-like sequences.
We then combined all sequences from the above analysis for clustering, followed by a multiple sequence alignment and phylogenetic tree analysis. The multiple sequence alignment of these sequences shows conserved S 111 XXK and Y 209 XN amino acid motifs (supplementary file S4, Supplementary Material online). Here, "X" represents sequences that can accommodate multiple substitutions. The phylogenetic tree presents eight novel clades; C-1 to C-8 (fig. 4 ), which contain archaea, bacterial, and metagenomic sequences. S1 , Supplementary Material online). This finding indicates that the HMM profile of bacterial sequences was able to detect homologues which are remote from Archaea. Other than archaea, all sequences are related to bacteria and metagenomes. The metagenomic sequences are not annotated in public databases and, therefore, their sources of organisms are unknown.
Discussion The objective of this study was to identify putative b-lactamases from biological databases (the HMP reference genome database, the HMP metagenome database, the environmental metagenome database, and NCBI's nr database), and to describe their phylogenetic diversity. With this in mind, we built HMM profiles and most probable ancestral sequences of extant enzymes, which were considered to be more efficient in recognizing remotely homologous sequences. We then predicted b-lactamase domains and conserved amino acid residues/motifs in putative sequences, which suggested their probable functional involvement in the catalytic mechanism. We constructed the putative ancestral sequences and HMM profile of four classes (class A-D) of extant b-lactamases to identify homologous sequences from distinct databases.
Moreover, it was previously suggested that protein-protein alignment with evalues < 0. 001 can reliably be used to infer homology  (Stormo 2009). The HMM profile search also produced numerous unnamed and hypothetical sequences, but the results were filtered on the basis of e-value (identity and coverage criteria were not applicable to the HMM profile search). The PATRIC database contains genomes with AMR (antimicrobial resistance) data, which offers BLAST matches to antimicrobial resistance (AMR) related proteins (curated at ARDB, the Antibiotic Resistance Genes Database and CARD, the Comprehensive Antibiotic Resistance Database). Therefore, in order to verify the presence of homologous sequences of putative b-lactamases, in this study, we performed local BLAST matches (putative b-lactamases and PATRIC AMR-related protein data as a query and database, respectively).
Based on selected threshold criteria (mentioned in Materials and Methods) we selected homologous sequences. When putative b-lactamases have homologous sequences in the PATRIC database, this indicates that these are antimicrobial resistance sequences. A total of 32,032 putative b-lactamase sequences (identified through BLAST matches of ancestral sequences and an HMM profile search) shows homologues in the PATRIC database. Supplementary table S1, Supplementary Material online, presents the list of putative b-lactamase sequences and their homologues which are present (abbreviated as "Y" in supplementary table S1, Supplementary Material online) or absent (abbreviated as "N" in supplementary table S1, Supplementary Material online) in the PATRIC database. The occurrence of the putative b-lactamase sequence in the metagenomic database was considered as dark-matter.
The term "dark-matter" indicates unannotated, unclassified metagenomic sequences where sufficient information is lacking about their sources and functions. The metagenomic databases help to discover novel protein families and are a valuable resource for identifying and annotating remote homologous sequences  (Lobb et al. 2015). Previously, several novel antibiotic resistance genes, including genes responsible for b-lactam resistance were identified in remote Alaskan soil  (Allen et al. 2009). To this end, our current study suggested a vast repository of unannotated b-lactamases in the human microbiome and environmental metagenomic databases, which illustrates the need for further experimentation with a view to their proper characterization. Apart from metagenomics, in this study, we found evidence that the human microbiome reference genome and NCBI's nr databases, along with the respective organism, are also potential reservoirs of putative b-lactamases.
In this study, we found a greater number of putative b-lactamases from the nr data sets than from other selected databases. We predicted functional sites in the detected homologous sequences and our results provided evidence to support the hypothesis that the identified putative sequences would probably be functional b-lactamases. Our results revealed signature motif characteristics of each group of b-lactamases (S 69 XXK, S 131 DN, and K 235 XG in Class A, H 131,133,222,291 in class B, S 111 XXK and Y 209 XN in class C, and S 58 XXK, K 194 XG in class D, where "X" represents any amino acid). This result is consistent with previous studies summarized by  Bush (Bush 2013). These class-specific motifs indicate that these regions are either structurally or functionally important for b-lactamase activity.
These regions can, therefore, be used to develop diagnostic probes. The functional domain that we recognized can be used as a fingerprint for recognizing new relatives and predicting their likely functional properties. The identified putative novel sequences are uncharacterized and unnamed, thus, in future, experiments should be conducted on these novel sequences to provide more detailed information. Phylogenetic trees of different classes of b-lactamases (A-D) strongly support the existence of new clades. The topology of these trees suggests that the novel clades are distantly related to the extant b-lactamase enzymes. Overall, the findings from this study suggest that the human microbiome, environmental metagenomic, and NCBI's nr databases offer a new and broadened reservoir of previously unseen b-lactamases, which are highly diverse from extant enzymes.
Conclusions The principal conclusions of this study can be summarized as follows: 1. The results of this study indicate that the putative ancestral sequences provide an intuitive way of inspecting homologous sequences in microbial communities, and the HMMbased profile search is far better in detecting remote homologs. 2. b-lactamases are more diverse than currently understood, and unannotated putative b-lactamase-like sequences are found in the metagenomic database.
Web Audio is a recent W3C API that brings the world of computer music applications to the browser. Although developers have been actively using it since the first beta implementations in 2012, the number of web apps built using Web Audio API cannot yet compare to the number of commercial and open source audio software tools available on native platforms. Many of the sites using this new technology are of an experimental nature or are very limited in their scope. While JavaScript and Web standards are increasingly flexible and powerful, C and C++ are the languages most often used for real-time audio applications and domain specific languages such as FAUST facilitate rapid development with high performance. Our work aims to create a continuum between native and browser based audio app development and to appeal to programmers from both worlds.
INTRODUCTION This paper will introduce work that was originally being done separately by three groups of researchers who had different initial interests. Due to the clear similarities in the work, the authors decided to join forces to develop interoperable Web Audio plugins and plug-in hosts, and to synchronize their efforts towards the beginnings of an open standard. One group has been developing the FAUST domain specific language (DSL) since 2002 [7]. FAUST is a DSL for digital signal processing with a focus on audio applications. Hundreds of musical instruments and audio effects are available written using the FAUST language, and the toolchain can compile them to different targets, including Web Audio. Another group has been developing the Web Audio Module (WAM) API since 2014 [4]. WAMs are high level audio plug-ins for the Web browser and have a C++ API, like native plug-in formats.
This has become one of the primary means of musicians obtaining new sounds and there are many companies that focus on the development of the software instruments and effects, as well as a lively hobbyist community  4. Several other manufacturers of DAWs and operating systems developed their own APIs in order to have a better influence on the user experience of their platform (Apple's AudioUnits, Avid's AAX etc. ). In addition, the open source community created their own formats  5. These APIs all share common functionality, namely processing blocks of audio samples, handling parameter changes, handling MIDI and handling state. For this reason, many third-party developers opt to use an intermediate C++ framework such as JUCE  6  or iPlug  7  , which allow a single code base to target multiple APIs, saving the developer a lot of time.
What makes the Web platform different? Although we aim to introduce the functionality offered by native audio plug-ins to the Web, the differences of the environment require a different approach to API design, and since this is an entirely new platform it provides an opportunity to improve upon some aspects of existing APIs. The web platform also brings with it some new possibilities and unique challenges, when developing real-time audio software: Advantages: The Web facilitates ease of distribution (no installation required), easy maintenance (resources at URLs can be silently updated), new kinds of collaboration (using technologies such as WebSockets and WebRTC for example), platform/architecture independence, security (the browser has sandboxing that can prevent misbehaving plug-ins from affecting the host or file system).
In the WASABI pedal board  9  , you can drag and drop pedals (or the amp simulator), connect them, change the settings using knobs or sliders, and control the parameters using a MIDI controller device if your browser supports Web MIDI. In our architecture, each plug-in is a Web Component (Web Components is a suite of different technologies allowing you to create reusable custom user interface components -with their functionality encapsulated away from the rest of your code -and utilize them in your web apps 10  ). This file embeds the "audio processor" JavaScript and may also define a GUI in its HTML <template> section. The audio processor code inherits an "EffectTemplate" JavaScript class that conforms to an "audio processor" API we defined, that is similar to the interface 11  implemented by all standard Web Audio nodes.
). The parent class that defines this "host dependent behavior" is named PBplug-in for "Pedal Board plug-in". For each plug-in, we write a subclass of PBplug-in in which we import the HTML file that defines the "redistributable plug-in" (and this can be a remote URL), and uses the HTML custom element that corresponds to the imported plug-in to generate its GUI and add some JS code to initialize it. The code of PBplug-in and of its subclass is "host dependent" and is not candidate for a standard. However, the way we defined "redistributable plug-ins": as Web Components (for distribution, solving encapsulation problems and reusability), and separated the "audio processor part" from the "GUI/controller" part, is close to the other approaches presented in the next sections.
; all this, in a standard user interface, or any kind of control using a remote protocol like OSC or HTTP. The FAUST compiler is organized in successive stages, from the DSP block diagram to signals, and finally to the FIR (FAUST Imperative Representation) which is then translated to several target languages. The FIR language describes the computation performed on the samples in a generic manner. It contains primitives to read and write variables and arrays, do arithmetic operations, and it defines the necessary control structures (for and while loops, if statements for branching etc. ). Several backends have been developed to translate the FIR to C, C++, Java, asm. js, WebAssembly (WASM) and LLVM IR. Two FAUST backends have been developed to generate WebAssembly formats [8]. The WAST backend generates humanreadable text based code, which is easier to test and debug.
The WASM backend generates the equivalent binary format to be directly loaded and executed in browsers. JavaScript code is used to load the WASM file into a typed array, compile it to a module with WebAssembly. compile, then instantiate it using WebAssembly. Instance function, and finally get the callable exported functions. Monophonic DSPs (generators, processor, analyzers. ) are created by wrapping a single DSP Faust object. Polyphonic MIDI controllable instruments can be defined using wrapper code that takes the Faust DSP code to be used as the description of a single voice. Several voices are then automatically created, and a MIDI API to handle incoming events, and to do voices allocation and handling is added. The DSP memory is either allocated inside the WASM module (for monophonic DSPs), or externally in the wrapping JavaScript code (to allocate several voices in the polyphonic instrument case), and is given as parameter when creating the module.
The DSP code is finally wrapped to be usable as a regular AudioNode. Two models have been successfully developed: a specialized ScriptProcessorNode and more recently a specialized AudioWorkletNode. In both cases their standard AudioNode API is extended with some additional methods: getNumInputs/getNumOutputs: returns the number of audio inputs/outputs. getParamValue(path,value)/setParamValue(path ,value) to read and write control parameters, and getParams retails an array containing all their paths (as OSC like hierarchical paths). getJSON returns a full JSON description of the DSP control hierarchy, to be used by a GUI manager to create a GUI with buttons, sliders etc. Additional MIDI control entry points (keyOn/keyOff, ctrlChange, pitchWheel…) are also added for polyphonic instruments. Starting from a given FAUST DSP source file, a set of scripts (faust2wasm, faust2webaudiowasm…) allow to chain successive operations: calling the FAUST compiler to produce the compiled WASM file, to generate the glue JavaScript code starting from the generic architecture file, and even possibly to create a fullyfunctional self-contained HTML page with a complete GUI to control the DSP processor or instrument.
How can our projects co-operate? WAMs describe the audio processor as a single Web Audio node and propose a controller/host to load it and configure its GUI, ports, etc. In the FAUST generated files, when targeting Web Audio, the audio processor is also considered as a single AudioWorklet node, and the JS generated code acts as the 12 https://webaudiomodules. org/wamsynths/ 13 https://github. com/webaudiomodules controller / host part like the approach used in WAMs. Both FAUST and WAMs have a rather complete API for the audio processor and/or controller part that is similar to that of the Web Audio interface (shared by all Web Audio nodes), with important additions described in previous sections (metadata, MIDI, audio buffer size can be set, etc. ) The pedal board from the WASABI project is mainly a host -an interactive web app for manipulating Web Audio plug-ins, arranging them on the screen, connecting them etc.