dataesr/scientific-paragraphs-categorization huggingface dataset:
The ChEBI ontology contains is-a relations, but also other types of relations such as has part, has role, and chemistry specific relations such as is conjugate base of and is tautomer of. Figure  1b  shows the closest is-a ascendants of the ChEBI concept "biliverdin (2-)". Entity linking is a challenging task for biomedical literature when compared to other domains. For example, while there is no exact match for "iron chloride" in ChEBI, a database of chemical entities with biological interest  [13] , there are 157 abstracts on PubMed that match that exact string at the time we were writing this manuscript. These cases are problematic to automatic approaches because the entity string itself is ambiguous, requiring more advanced approaches to resolve this ambiguity. According to the Human Phenotype Ontology (HPO), dyschromatopsia and color-blindness refer to the same phenotype.
Bunesco et al. presented a method based on Support Vector Machines, using a dictionary generated from 1 https://github. com/lasigeBioTM/PPRSSM Wikipedia to detect and link entities  [21]. Other authors aimed at maximizing the global coherence between the linked entities  [22] [23] [24]. Pershina et al. presented a graphbased method based on the Personalized PageRank (PPR) algorithm to this task, incorporating both local and global coherence  [25]. They assumed that the probability of each node is related to how likely it is to fit with the other highest scoring nodes. More recently, Radhakrishnan et al. presented a method that improved entity similarity by training embedding vectors on a densified KB  [20]. Since the majority of entity linking gold standards are based on Wikipedia, these systems are developed for general KBs, and rarely focus on domain-specific KBs.
Graph-based approaches Several graph-based approaches have been proposed for entity linking. [26]  developed a graph-based framework to rank the entries of a database according to their relevance to a query. [27]  proposed a method to rank the concepts and relations of an ontology according to their importance to the domain. Although this method is helpful to better understand a domain using ontologies, the authors did not explore its utility for other text mining tasks. [28]  explored Markov networks for entity linking, applied to citation databases. These types of approaches require training data, which is not always available, particularly in some biomedical domains. Unlike other authors that explored graph-based methods for entity linking, we propose a method that takes advantage of the semantic relations described in the KB.
Data We evaluated our method on three gold standards, consisting of biomedical documents manually annotated with ontology concepts. Table  1  presents a comparison between the gold standards. The ChEBI-patents corpus consists of 40 patent documents annotated with chemical entities, using the ChEBI ontology as reference. This gold standard was developed by a team of curators from ChEBI and the European Patent Office. The documents were selected to be representative of the universe of chemical patent documents. Whenever possible, the curators added the ChEBI concept identifier to the entity annotations. Since we were interested only in linking entity mentions to concept identifiers, we discarded entity mentions that were not assigned an identifier. There were 8407 textual entity mentions annotated with ChEBI identifiers in this corpus, corresponding to 2081 unique entity mentions.
Evaluation setup We evaluated each model considering the entities that were manually mapped to an ontology concept and for which the correct solution was in the set of candidates. Using the matching methods presented in the Methods section, we obtain a list of candidates for each entity. Table  1  shows that on the datasets used, most entities had its solution in the respective candidate list. Figure  3  shows an example of how we applied our method to the ChEBI-patents corpus. We found that many concepts were not directly linked to each other in the ontology, meaning that the graph of each document would not have enough edges to apply PPR. For this reason, we studied the effect of considering the transitivity of subsumption relations, with a maximum distance threshold between 1 and 8. For example, if 5 is the maximum distance allowed, we would consider that there is an Fig.
The code used to implement the method is publicly available  2. As future work, we could take advantage of the similarities between ontologies to develop a joint approach, as suggested by  [38]. The authors of this paper have shown that considering multiple ontologies together is beneficial to biomedical EL. Other improvements would be to improve the candidate generation process, so that more entities have the correct candidate in their candidate list. One possible approach would be to use word embeddings to find the most similar concepts, instead of matching the characters of the string. Furthermore, the document graph could be improved using relation extracted from the document between entities. This way, if a relation between two entities is stated in the document, but not in the ontology, we could still use that information.
Simulation Parameters To analyse the connection effects on the cutoff frequency, the finite element method (Comsol) was used and the numerical model was divided in two parts because of the big difference between electrode connection dimensions, as follows: the channel innerelectrode connection tracks with micrometric-order dimensions and the channel outerelectrode connection tracks with millimetre-order dimensions. In this way, one obtains a parasitic capacitance (Cplar) with the finite element model at the millimetre order and the values of Cm, Rm, and Cp with a finite element model at the micrometric order. Once the values Cplar, Cp, Cm, and Rm have been obtained, MatLab (Mathworks, Natick, MA, USA) was used to plot the frequency domain curves. Basically, cells are composed of a cytoplasm and a membrane.
Simulation Parameters To analyse the connection effects on the cutoff frequency, the finite element method (Comsol) was used and the numerical model was divided in two parts because of the big difference between electrode connection dimensions, as follows: the channel innerelectrode connection tracks with micrometric-order dimensions and the channel outerelectrode connection tracks with millimetre-order dimensions. In this way, one obtains a parasitic capacitance (C plar ) with the finite element model at the millimetre order and the values of C m , R m , and C p with a finite element model at the micrometric order. Once the values C plar , C p , C m , and R m have been obtained, MatLab (Mathworks, Natick, MA, USA) was used to plot the frequency domain curves. Basically, cells are composed of a cytoplasm and a membrane.
Nutrients In the context of marine systems, key nutrients of interest are nitrate, nitrite, ammonium, phosphate, silicate, and a number of trace metals (e. g. , iron). Nutrients have historically been more difficult to measure in situ than physical or bulk chemical parameters, due both to cross-sensitivities with other constituents and to challenges with miniaturization of lab instrumentation for field deployment. While there are a number of commercially available multi-parameter instruments for nutrient measurements in the marine environment (comprehensive list in the ACT Technologies Database 14  ), many of these are now mature technologies that are still relatively costly, unlikely to see further decreases in cost and likely to see only incremental improvements in accuracy. A number of emerging technologies, however, build on insights gained from these instruments and may have the potential to meet decreased size, cost, and/or power demands.
Underwater Bio-Acoustics Passive and active acoustic sensing are capable of delivering datasets of relevance to several EOVs, including fish abundance and distribution  (Simmonds and MacLennan, 2005) , marine mammal distributions  (Brehmer et al. , 2012) , diving seabird behaviors  (Benoit-Bird et al. , 2011; Williamson et al. , 2017) , habitat type and fine-scale topography  (Roberts et al. , 2005; Smith and McConnaughey, 2016)  and ocean sound  (Hildebrand, 2009). Although the absolute price tag may not be comparable with available low-cost biogeochemical sensors, the multi-purposes and high data output per unit cost of bio-acoustic sensors allow them become a cost-effective way of studying a wide range of biological processes and marine organisms, along with their living habitats in the last decade.
g. ,  Briggs et al. , 2013). For the prototype network deployed at He'eia Fishpond, three styles of low-cost mini-Nodes have been developed: (1) Arduino-controlled telemetry dongles that parse and relay any serial data from industry-standard instruments such as Seabird SBE19+ (node-025), (2) BeagleBone Black-controlled multiparameter packages that log data from Aanderaa oxygen optodes,  Aanderaa conductivity sensors, low-cost MEMS barometric pressure-temperature-humidity sensors, and submersible MEMS piezo-resistive pressure sensors (node-003), and (3) Arduino controlled temperature-compensated ultrasonic sensors mounted on bridges over sluice gates (mâkâhâs) in the Fishpond wall to monitor water level (tidal exchange with Kaneohe Bay). For each configuration, data are telemetered back to a shore-side base station where data are logged into an SQL database, stored, and transferred to a server at UH Mānoa (UHM).
At UHM, an x86 Linux server (NUC5i7RYH) performs automatic, first-pass QA/QC data filtering and flags data that is out of expected range or mini-Nodes that have not reported as scheduled. Data are then served on the web via an open-architecture RESTful API (Figure  7 ). Three specific advances in low-cost electrical components and software tools are making these new deployments possible and timely: (1) the availability of low-cost powerful single-board microcomputers and microcontrollers (e. g. , BeagleBone Black, Texas Instruments, $55; ATMEGA32U4, Arduino-compatible, $5), (2) robust low-power radio frequency (RF) wireless mesh network transceivers (XBee Pro 900HP, Digi. , $39), and (3) growing popularity and capability of crowd-sourced opensource software tools (i. e. , Linux-operating system, Python embedded systems control and visualization libraries, and GitHub coordinated version control development).
, 2018)  and phosphate. These deployments show the ability of the sensor and AUV to capture simultaneous, high spatiotemporal variability of physical parameters and nutrients, revealing previously obscured processes and features. While often cited as a likely problem for LOC, fouling has not been a significant issue that degraded LOC's performance. The so-far longest data set obtained without reagent resupply or intervention was >1 year from a nitrate/nitrite sensor deployed on the FixO3 mooring in the Fram Strait. Although the cold and dark conditions in this annually ice covered region (less biofouling) assisted long-term preservation of reagents, other fouling and challenges in low-temperature environments did not degrade sensors' performance during the deployment period.
, 2015). Sometimes the sensors also require recovery for recalibration (as in the case of some oxygen sensors), otherwise assumptions of sensor drift and expected conditions have to be applied, limiting some data resolution or applications. The second general data conveyance method is to relay information through a network  (Dragon et al. , 2010; Blain et al. , 2013). This has long been through the aging ARGOS satellite network. These can be relatively small transmitter-tags but the data is limited by the network thus measurements are often lower-resolution. Iridium hardware is still usually too big for most animals to handle. Cell networks are increasingly being used in areas where service is available (near shore). These methods can be combined, relaying low-resolution data through ARGOS and acquiring high resolution data if/when the AnBS is recovered.
However, evidence to date is that developers are keen to reveal their development plans to aid uptake and that the international observing governance bodies are ready and willing to support and sustain this activity beyond the life of short term individual projects (see footnote 18). There is also evidence that inclusion in the roadmap is aiding developers of instrumentation through promoting links to platform and observing systems (see footnote 18). Once new instruments are made available, information databases, such as the one maintained by the Alliance for Coastal Technologies, 19  will be critical in linking global customers to an increasing array of options for studying marine systems.
ACKNOWLEDGMENTS The authors would like to acknowledge the contributions to the LOC elements of this manuscript from the wider OTEG team at the NOC but particularly Socratis Loucaides,  Alexander Beaton ,  Geraldine Clinton-Bailey ,  Chris Cardwell , and  Greg Slavik. The authors would also like to express their gratitude to the development teams of the CHANOS and iTag, particularly  Sophie Chu ,  Mallory Ringham ,  Kate Morkeski ,  Alex Shorter ,  David Mann ,  Kakani Katija ,  Fritz Sonnichesen ,  Steve Lerner , and  Glenn McDonald , as well as the IRD and the  Ifremer acoustics teams, particularly Lemar, Marbec, Imago , and  François Gerlotto ,  Erwan Josse ,  Anne Lebourges-Dhaussy ,  Yannick Perrot ,  Jeremie Habasque , and  Gildas Roudaut.
Cell Outlines and Switches Cell outlines were extracted manually from phase-contrast micrographs in ImageJ and exported in MatLab. Each outline was digitized as a polygon with 600 vertices. The switches from protrusion to retraction are defined as in  [16]. Briefly, a protrusion-retraction switch is a region of the plane that is inside the cell at frame n but neither at frame n-1, nor n + 1.
The profiles were taken on the line connecting the outline point at the onset of retraction (first time point with negative speed) to the center of the cell. A sequence of stress profiles on this line was then taken from t = t s -60s to t = t s + 60s, t = t s being the time of onset of retraction. Local curvature was measured on portions of the cell edge representing 1 30 to 1 60 of the total perimeter. In stress-curvature measurements, the center of the edge portion matched the center of the rectangle where stress was averaged. To define the centers of the force clusters, clustering of traction force microscopy data was carried out with the mean shift clustering algorithm implementation from python scikit-learn library (http://scikit-learn. org). The mean distance to the closest cluster was then measured for each point on the cell outline and each PR switching point.
Numerical Model The model consists of a hexagonal lattice of bendable elastic bonds, local attractive dipoles and fixed anchors that represent actin filaments, molecular motors and cell-substrate adhesions, respectively. It was derived from models described in  [23]  and  [27]. Each bond can be stretched, or be compressed and bend. To simplify the calculation of the bending energy, it is assumed that bending of each bond occurs at the midpoint between two lattice points. There are thus two types of vertices, lattice point and mid-point. Only lattice points can form dipoles and be fixed points. The model was implemented in a C++ program and the data was analysed with C++ and python programs. The elongation and compression part of the energy is E s ( ) = µ ( -0 ) 2 2. (2) In this equation is the segment length and µ is a spring constant, a parameter of the model and 0 the segments rest length.
We then develop an algorithm, or more specifically a set of parameters to be used in an algorithm, optimized for the CCE that can potentially be used to estimate particle flux using both the UVP and fully autonomous instruments such as the Zooglider  (Ohman et al. , 2018). We present evidence that as our dataset encompasses a decade's worth of data in the CCE, including various frontal regimes, mesoscale, and submesoscale phenomena, these parameterizations are far more accurate to the region than values previously published. We caution, however, that more accurate quantification of flux from optical measurements likely requires additional information beyond particle size spectra, including characteristics related to the composition and identification of the particle or aggregate.
55-mm inner diameter (i. e. , slightly larger than the trap tube above it), because on previous cruises we found that material often clustered near the edge of the gel. Immediately after the cruise, a series of images covering the entire gel was taken under both bright field and dark field at 7. 5X magnification (effective resolution 11. 6 µm/pixel) with a Zeiss Discovery V20 stereomicroscope. 7. 5X magnification bright field images were manually stitched together using Photoshop software. Particles were then manually circled and length, width, and area were extracted using Image J processing software (dark field images were simultaneously viewed to aid in particle and aggregate identification). A random set of locations on the gel was also imaged at 20X and 40X magnification. These higher magnification images were used only for qualitative analysis of smaller particles, because non-uniform loading of particles across the gel traps limited our ability to compute abundances from these images.
UVP Measurements and Data Processing The UVP was attached downward facing on the CTD Niskinrosette, allowing for contemporaneous particle imaging and water column characterization, typically on 10 casts per cycle. For P0810, P1208, P1408, and P1604 the UVP5 standard definition model was used while for P1106 and P1706 a zooming version and HD model were deployed respectively. Each instrument was cross-calibrated in the lab prior to deployment. The UVP images a volume of ∼1 L with each image and takes 6 images per second. It was typically deployed to a depth of 500 m. Post-cruise, data were processed using published Matlab scripts and uploaded to the Ecotaxa website  1. Particle data were obtained from the Particle Module of the Ecotaxa website. While the UVP reliably images organisms with a size > 600-µm by converting the pixel border length to metric dimensions, it can also be used to quantify particle size and abundance down to the calibrated pixel size of the sensor, though for such small particles this is not as straight-forward a task.
From these spectra the point at which the particle abundance relationship no longer followed a power law function was determined. However, because the camera and calibrations varied between cruises, there was no consistent size range at which the slope of the power law function changed, yet it was necessary to apply a uniform cutoff in order to determine a single parameter set representative of the entire dataset. Two hundred µm was chosen as the minimum particle size as it represented a reasonable compromise when comparing the particle spectra and considering the importance of ∼200 µm fecal pellets in sediment trap derived export (discussed further in Section "Sinking Particle Size Spectrum"). However, we note that, particularly for the 2008 cruise, the UVP is likely underestimating the abundance of 200-400 µm particles as the smallest particles detected were of 240 µm ESD.
e. , the concentration of particles in bin i, divided by the bin width of bin i), d i [mm] is the mid-point diameter of bin i, and A and B are constants related to the power law relationships that relate particle size to mass and settling velocity. In each instance, we averaged the flux estimates from the ∼10 casts per Lagrangian cycle and compared this flux estimate to the sediment trap-derived POC flux measurements (a total of 69 independent sediment trap-derived flux POC were made on cycles with associated UVP profiles). We also compared the UVP flux measurements to our blended flux profiles (separated into 5-m vertical bins from 50 to 200 m depth), which yielded 780 matchups between cycle average UVP flux and measured POC flux. In order to improve the model's predictive capability for the CCE we calculated values of A and B specific to our dataset using a grid search method (to avoid the possibility of finding local, rather than global, minima).
They were identified as fish (likely anchovy) fecal pellets. In three samples (P1706-2, 50 m; P1706-3, 60 m; and  P1706-4, 50 m) marine snow aggregates were also noted in the samples. However, they appeared to be less dense than the acrylamide gel and hence were not in the same focal plane as the rest of the particles. Therefore they were not included in the data assembled in Figure  6 , but their impact will be further considered in the Section "Discussion. " For P1706-2, three marine snow aggregates (equating to flux of 218 aggregates m -2 d -1 ) were noted with an average ESD of 2. 3 mm. For P1706-3, 24 marine snow aggregates (1958 m -2 d -1 ) were noted with ESD ranging from 1. 6 to 7. 1 mm. For P1706-4, an estimated 57 marine snow aggregates (6550 m -2 d -1 ) with typical ESD of 2. 5 mm were noted.
DATA AVAILABILITY STATEMENT Data used in this manuscript can be found on the CCE LTER DataZoo website: https://oceaninformatics. ucsd. edu/ datazoo/catalogs/ccelter/datasets and on the EcoTaxa website: https://ecotaxa. obs-vlfr. fr/. The R code used to compile and analyze the data is available open-source on GitHub: https://github. com/tbrycekelly/CCE-UVP.
FUNDING This work was funded by  NSF  grants to the  CCE LTER Program :  OCE-0417616 ,  OCE-1026607 ,  OCE-1637632 , and  OCE-1614359. A portion of this work was performed at the  National High Magnetic Field Laboratory , which is supported by the  National Science Foundation  Cooperative Agreement No. DMR-1644779  and the  State of Florida.
Other applications in hematooncology involving V(D)J-NGS include clonal evolution of lymphoid malignancies  [20, 21] , biomarker tracing employing liquid biopsies  [22, 23] , and monitoring of minimal residual disease (MRD)  [24] [25] [26] [27]. The large majority of these studies have been focused on obtaining full sequence coverage of complete IG heavy chain IGHV-IGHD-IGHJ gene rearrangements. In addition, several bioinformatics tools have been developed for V (D)J germline assignment and detection of IGH and IG κ light chain (IGK) rearrangements within reads obtained from NGS datasets  [28] [29] [30] [31] [32]. In recent years, the EuroClonality-NGS Working Group has developed IG/TR assays, which have been validated across expert European centres to allow for quality-controlled, streamlined, and comprehensive detection of clonal IG/TR rearrangements  [33, 34].
Acknowledgements We acknowledge the sequencing facilities in the various centres of the EuroClonality-NGS Working Group members. Supported by  Ministry of Health of the Czech Republic , grant no. 16-34272A ; Computational resources were provided by the  CESNET LM2015042  and the  CERIT Scientific Cloud LM2015085 , provided under the program "Projects of  Large Research, Development, and Innovations Infrastructures". Design of IGK  assays and analyses in Nijmegen and Rotterdam laboratories were supported by an  Innovation  project granted by the  Zorgverzekeraars Nederland  (number  2017-3442 ).
However, a packet switching network, in general, does not guarantee very low jitter communication. Considering our needs for sparse inference, we decided to introduce a new neuron model which is somewhere in between "synchronous ANN nodes" and "leaky integrate and fire (LIF) spiking neurons". Our goal was to optimize the number of operations for spatio-temporal sparsity while performing asynchronous inference. This paper is a continuation of our previous brief paper  [36]. In the present paper, in addition to more detailed explanations, we extend our algorithm to use "valued spikes" which results in a smaller number of required events. Additionally, since our previous paper only reported results from the MNIST dataset, we have added two more experiments to strengthen the paper. In the second experiment, we process a framedbased video for an autonomous steering application.