dataesr/scientific-paragraphs-categorization huggingface dataset:
WpsI contains a DUF2142 (PF09913) domain with no known function but that belongs to the GT-C clan containing glycosyltransferases with 8 -13 predicted TMHs and that are dependent on polyprenyl phosphate-linked sugars  (8, 25). In particular, WpsI contains the typical modified catalytic DXD motif ( 63 EPD 65 ) located in the first predicted large extracellular loop located after the first TMH segment (Fig. S5 ). HHpred analysis also predicts structural similarity to several membrane-associated glycosyltransferases known to possess a GT-C fold, including 4-amino-4-deoxy-Larabinose (L-Ara4N) transferase (ArnT) (probability, 99. 1%; E-value, 1. 4e Ϫ9 ; PDB structure 5EZM_A) and the archaeal oligosaccharyltransferase AglB (probability, 98. 55%; E-value, 8. 3e Ϫ7 ; PDB structure 3WAJ_A), which catalyzes the transfer of oligosaccharide chains from lipid-oligosaccharide precursors to Asn residues in proteins.
Attachment of PSP to rhamnan From our previous results (15), we gathered evidence that rhamnan is anchored to peptidoglycan, whereas PSP may be attached to rhamnan, thereby constituting a large heteropolysaccharide in the cell wall. In the more conserved part of the cwps gene cluster, the wpsJ gene encoding a putative integral membrane protein (463 AA) with nine TMHs is conserved among L. lactis genomes but exhibits sequence variability. WpsJ does not exhibit significant sequence identity with any protein with known function but contains a DUF2142 (PF09913, IPR018674) domain that belongs to the GT-C clan containing glycosyltransferases with 8 -13 predicted TMH segments and that are dependent on polyprenyl phosphate-linked sugars. Notably, it contains a modified catalytic DXD motif ( 43 EPD 45 ) located in the first predicted extracellular loop of the protein (Fig.
CWPS analysis of the mutant derivatives CWPS of the obtained mutants was extracted and analyzed. For this purpose, cell walls were prepared from the mutant strains, and CWPS was extracted by hydrofluoric acid (HF) treatment. Regarding the control WT L. lactis NZ9000, HF extract contains rhamnan and oligosaccharides derived from PSP by cleavage of the phosphodiester bonds inside the PSP chain, which can be separated as two major peaks when subjected to SEC-HPLC analysis as described previously (15) (Fig. 1B ). The SEC-HPLC profile of the CWPS extracted from the nine mutants revealed first that all mutants are able to synthesize rhamnan (Fig. 1D  and data not shown). Notably, inactivation of wpsJ, located in the more conserved part of the cwps gene cluster, did not prevent the synthesis of rhamnan (data not shown).
21 and 593. 10 (Fig. 3 ), consistent with structures corresponding to single PSP subunit (as represented in Fig. 1C ) cleaved by HF at the level of the phosphodiester bond. Notably, the peaks corresponding to polymeric chains found in the WT spectrum were not detected, thus supporting impairment of PSP polymerization in these two mutants. These data are in agreement with the proposed role of WpsH and WpsI in PSP polymerization. Regarding the NZ9000-wpsJ mutant, CWPS analysis by SEC-HPLC showed the presence of the rhamnan peak but the absence of the PSP peak (profile similar to NZ9000-wpsA) (data not shown). In addition, no signal could be detected by MS analysis of the fractions eluting at the same retention time as the WT PSP peak (Fig. 3 ). These results indicate that wpsJ, located in the more conserved part of the cwps cluster, is essential for PSP assembly in the cell wall.
Edited by Chris Whitfield The work of the M. -P. C. -C. team was supported by  INRA. This article contains Figs. S1-S5 and Tables  S1-S4. 1  Recipient of Starting Investigator Research Grant  ( SIRG) 15/SIRG/3430 funded by  Science Foundation Ireland (SFI). 2 Both authors contributed equally to this work. 3Supported by Principal Investigator Award  450 13/IA/1953 ) through SFI.
We argue that gluon saturation effects may be visible in Large Hadron Collider (LHC) data. We look at the centrality dependence of the away-side peak of two-particle correlations measured in p-Pb collisions, using both ALICE data at midrapidity, and LHCb data at forward rapidity. Once the collective flow-like signal measured at the near-side peak is removed from the correlation function, the centrality dependence of the away-side peak turns out to be much stronger in the forward region than at midrapidity. We argue that this is a very specific prediction of the saturation framework, and we compare LHCb data to a state-of-the-art calculation within the Color Glass Condensate theory.
( 1 ) At the LHC, then, if particles are correlated at large rapidity, y ∼ 4, one obtains x 1 ∼ 1 and x 2 ∼ 10 -4. The projectile is thus dilute, i. e. , probed at large values of Bjorken x, whereas saturation is maximized in the target, which is probed in the dense small-x region, and is amenable to a CGC description. In this work, we argue that the suppression of the away-side peak observed in current LHC p-Pb data provides strong and unique evidence in support of the CGC picture.
2. Subtracting the near-side contribution from each peak on the away side, we obtain the curves shown in the right panel of Fig. 1. The difference between flow-subtracted ALICE and LHCb data is striking: An evident hierarchy with centrality emerges in forward LHCb data, which is much less visible at midarpidity in the ALICE measurement. We conclude that the two crucial features predicted by the CGC formalism are both visible in the experimental data: The away-side peak is suppressed in central collisions, and this suppression fades away as we correlate particles away from the forward region. This is our main result, and is, arguably, the clearest signature of gluon saturation at play in experimental data so far observed at the LHC. Right panel: Same but for LHCb data measured at forward rapidity  [6].
Electronic monitoring systems generally consist of various activity sensors, GPS, computer hardware and cameras (Figure  1 ) which allow for video monitoring and documentation of catches and detailed fishing effort estimation without requiring additional on-board personnel, unless additional biological data, for example otoliths, are needed (e. g. Needle et al. , 2015; Ulrich et al. , 2015). The data recorded can be reviewed at a later stage to obtain catch information, for example species composition, numbers, volume and lengths. In North America, the first EM trial was implemented in the Area "A" crab fishery in 1999 in British Columbia, Canada, to monitor vessel trap limits and to control catch and gear theft. As a result, the fisheries authorities implemented a full EM programme involving 50 vessels with a 36,000 fleet-wide trap limit.
| North America The majority of fully implemented comprehensive EM programmes, 9 out of 12 (75%) worldwide, run in both Canada and the United States (Table  2 ). All these programmes are management-driven monitoring schemes, where EM is officially used for compliance monitoring purposes. Vessels under these regulations are required to have some form of monitoring and may choose to use EM. The number of vessels  demonstrated that EM is a promising tool for at-sea monitoring applications. It was repeatedly reported that EM differs from the more traditional observer programmes in terms of data collection capabilities and programme design issues  (Kindt-Larsen et al. , 2011; McElderry et al. , 2014; Needle et al. , 2015; Pierre, 2018; Plet-Hansen, Bergsson, & Ulrich, 2019). In comparison with observer programmes, EM has a number of advantages including its suitability across a broad range of vessels, the ability to review video for data verification, its presumed lower cost and higher scalability, and its ability to engage the industry in self-reporting processes.
| South and Central America In total, three EM studies were conducted in South and Central America (Table  1 ). The results of the Peruvian trial indicate that EM was an effective alternative to human observers in monitoring catches of Peru's small-scale elasmobranch gill net fishery  (Bartholomew et al. , 2018). The Mexican trial, comparing the efficacy of video monitoring systems versus on-board observers, used the "Flywire Camera System," a low budget EM system developed for small-scale and artisanal fisheries using high-quality video linked to a GPS. The same system was used in a Hawaiian EM project for catch and by-catch monitoring (NOAA, 2017d). To enhance data collection on small-scale fisheries in developing countries, the World Wildlife Fund for Nature (WWF) supports the development of "affordable" EM systems for this region (www.
| EM set-ups and data flow In all trials, the EM system set-up consisted of (a) a GPS recorder supplying information on vessel location, (b) cameras supplying visual information on fishing activities and catches, and (c) hydraulic and drum-rotation sensors to mark deployment and retraction of gears. All data are conveyed into a computer, which saves the information (Figure  1 ). Vessels in all trials were initially equipped with the technology developed by the Canadian company Archipelago Marine Research (www. archi pelago. ca). This system uses hard discs to store sensor data, geographical location and video recording. These hard discs were replaced manually before reaching data storage limits. The Danish and German trials switched to another provider that allowed the transmission of data using 4G cellular networks (www.
Digital cameras process and store all imagery in compressed data files. Higher resolution and increased frame rates are, therefore, less of a problem. In earlier EM systems, imagery of analog cameras was processed by the central computer, limiting resolution and frame rate by the processing capacity of the computer. In the standard EM set-up, vessels were fitted with hydraulic pressure and drum-rotation sensors. Data from these sensors allow interpretation on gear use. This contributes to data review because it directly marks events of interest in the analysis software. The deployment and retrieval times are registered in the data flow, enabling accurate estimates of haul duration. Another purpose of sensors is to automatically start and stop camera recording outside of the active fishing operations, which could save storage capacity of the system or to respect the privacy of crew members.
| Supplementary information Supplementary catch information, for example logbook, haul-byhaul catch and observer data, was collected in all trials, with the purpose to evaluate and compare the efficacy of EM in a variety of management and scientific objectives. In the case of catch quota management trials for cod, all catches, including undersize individuals, were recorded. During trials in Germany and Denmark, extra information on discards was provided in official electronic logbooks  (Götz et al. , 2015; Ulrich et al. , 2015). In several trials, data from on-board observer programmes were used in comparison with EM data (Marine Management Organisation, 2013b;  Mortensen et al. , 2017; Needle et al. , 2015). In the Netherlands and England, fishers were requested to record catches by species or size category on a haul-by-haul basis  (Course et al.
), so that all can be visualized together. When inspecting EM data sets, users can fast forward, rewind or pause with synchronous views of all active cameras, along with normal video viewing tools such as zoom. The review time depends on the quality of the data set, the quality of the review software, the monitoring objective and the type of operation observed. When monitoring for rare and highly visible events, such as the catch of cetaceans, all footage was reviewed when played at a higher rate (10-12 times faster than real time) (Kindt-Larsen,  Dalskov, Stage, & Larsen, 2012). Monitoring catches of commercial species aboard demersal trawlers is generally time-consuming and in response to the large quantity of data most trials developed strategies where a random 10%-20% of the camera footage was validated against (self-) recorded catch data in logbooks  (Course et al.
| EM performance Most trials studied the performance of EM as a reliable source of catch information (Table  3 ). This performance depends on the technical reliability of the EM systems and the ability to correctly estimate catches. Technical EM failures and loss of data due to poor video quality were reported in 11 (out of 15) trials. However, not all technical errors were reported in similar detail. During the review, reported errors were classified in three different categories: system failure, storage failure and obstructed view. Where possible, errors were quantified as a percentage of data loss (Table  5 ). System failures were recorded in seven trials, with the main reason being broken cameras and non-functional drum-rotation sensors. Two studies (#12 and #22) mentioned system failure caused by power supply issues.
Storage failure was recorded in three trials, caused by corrupted EM data, mainly video data, on the exchangeable hard drives. During the German trial, a hard drive began to burn during the copy process in the Institute and data were lost  (Götz et al. , 2015). Another form of storage failure occurred in the Dutch CQM trial; storage failure occurred because full hard drives were not replaced in time. This was not related to a technical failure of the EM system itself, but due to insufficient management of exchanging hard drives when vessels entered ports. A similar situation was described in the German trial where logistical and technical problems were encountered in relation to the exchange of hard drives, when vessels entered distant ports  (Götz et al. , 2015). Nevertheless, no data losses were reported in this trial because of these situations.
Obstructed view was reported in six trials. In these situations, the EM system worked properly; however, the footage recorded could not be used for further analysis because the view was blocked or unclear. The primary reported reason for EM data loss was unclear views because of dirty lenses, in some cases responsible for significant amounts of data loss, up to 48% (Table  5 ). The principal problem was the positioning of the cameras. To get a sufficient view of the catch and to be able to identify species, and count and measure individuals, the cameras were directed at the catch sorting areas. However, the working space in fishing vessels is generally extremely limited with low ceilings, and it can be difficult to position a camera in a way that can enable a wide, clear and undistorted view of the sorting area without the risk of water and fish waste splashing up onto the camera casing  (Bergsson et al.
This loss stopped after 2014 when manual data transmission was replaced by transmission via the Internet (Danish FDF trial for CQM) "…hauls with defected or dirty cam-eras were not analysed…" (Danish MINIDISC project) a Percentages are calculated on different premises, for example total number of hauls, fishing days or fishing hours. trials have been sufficiently reliable to fulfil the goals of the studies, provided there was ongoing attention to maintenance. All European trials had the objective to evaluate the ability of EM to estimate catches in commercial fisheries (Table  3 ). Different methods were used to estimate catch from video footage (Table  4 ). To test the efficiency of EM, catch estimates based on video review were compared with recordings of fishers and/ or on-board observers.
, 2018). Such benefits could include improved data quality through EM, allowing for more efficient management measures and, eventually, improved financial performance for industry, and increased flexibility in regulations as a result of improved accountability from EM. The Danish trial on free gear selection  (Mortensen et al. , 2017)  is a good example of this, alternative uses for EM data, for example, improved business analytics, such as identifying and avoiding by-catch hotspots, support of (eco-) certifications by increasing traceability in seafood supply chains.
As part of the English Marine Management Organization CQM scheme, a participating skipper voluntarily altered the selectivity of his trawl. Comparative catch weight data from the skipper using different net designs were corroborated using EM (Marine Management Organisation, 2015a). These data were used to optimize the modi- In two of the reviewed trials, the Dutch CQM and the Danish MINIDISC trials (studies #4 and #20, Table  3 ), changes in fishing activity and behaviour were analysed when vessels were under different management regimes  (van Helmond et al. , 2016; Mortensen et al. , 2017). The wider monitoring coverage of the fleet, in essence a 100% coverage  (Kindt-Larsen et al. , 2011) , created a unique opportunity to investigate fishers' gear choices, mesh sizes and fishing locations at broader (macro) and finer (micro) geographical scale.
| Summary of European trials, operational benefits of EM The three major benefits of EM perceived in the European trials With the potential to enhance data collection programmes, EM has the ability to improve the scientific stock assessment and risk assessment processes. In particular, the assessments of data-limited stocks (DLS) would benefit from a system like EM, the wider coverage of the fleet enabling data collection from less abundant species or specific fisheries, for example long-distance or smallscale fisheries, which are notably difficult to cover with a traditional observer programme. However, age and maturity data can only be collected through direct physical sampling. Observers can also collect sex data for some species by external observation (e. g. plaice, Elasmobranchs and Nephrops) which is not possible with existing EM systems.
, 2018). This is especially true in fisheries with strong restrictions on discards and by-catches, like fisheries under the landing obligation in the EU, where fishers have become dependent on discarding the most limiting quota that would lead to early closures of the fishery, the "choke" species. Not surprisingly, EM has faced significant opposition from parts of the fishing industry in this region  (Michelin et al. , 2018; Plet-Hansen et al. , 2017). 2. Costs of EM adoption are clear for the fishing industry, but the long-term benefits are not. While implementation costs are often covered through government funds, running costs and data analysis costs are generally at the expense of the industry (NOAA, 2017a). Meanwhile, potential benefits for individual fishers, for example market access, sustainability claims, improved traceability and data licensing, are not well documented and not always of direct interest to them.
3. Most pilot studies were not designed to initiate broad implementation. Commitment on what successful trials would trigger was lacking, and there was no plan for further development into full EM programmes  (Michelin et al. , 2018). 4. Most fisheries government agencies lack capacity and expertise, for example people capable of programme design and video review, to run fully implemented fleet-wide EM programmes. The implementation of such programmes requires large IT infrastructures to deal with the amount of data that EM generates in, for example, data transmission, data storage and data review. Many fisheries management agencies have no experience in setting up these infrastructures and are hesitant to commit to this effort. In the absence of support, individual fishery managers or regulators can be reluctant to implement EM schemes at scale  (ICES, 2019; Michelin et al.
| Enhancing the implementation of EM Electronic monitoring as a monitoring tool contains a range of solid strengths that are not diminished by its weaknesses and EM has the opportunity to be a powerful tool in the future monitoring of a wide range of different types of fisheries. Electronic monitoring can be used to fully document a fishery or be integrated with existing data collection programmes, for management and compliance purposes or scientific data collection. Nevertheless, the viability of EM depends largely on how a range of threats are dealt with. Changes in the political landscape make the future of EM unpredictable; the end of the Fully Documented Fisheries programme in Denmark was the result of governmental change with a different view on fisheries management. Another important liability is its very low acceptance by the fishing industry.
O RCI D Aloysius T. M. van  Helmond https://orcid. org/0000-0002-5508-3814 Thomas Catchpole https://orcid. org/0000-0001-7708-0967 Stephen Mangi https://orcid. org/0000-0001-8233-2612 DATA AVA I L A B I L I T Y S TAT E M E N T The data, summarized information subtracted through literature review, that support the findings of this study are available from the corresponding author upon reasonable request. | 187 van HELMOnD Et aL. Marine Management Organisation (2013b). Under 10 metre remote electronic monitoring technical trial (p. 19). Newcastle, UK. Marine Management Organisation (2014a). Catch quota trials: Western haddock final report 2013 (p. 24). Newcastle, UK. Marine Management Organisation (2014b). Grade composition and selectivity of ICES VII b-k haddock in the southwest Otter-Trawl fishery (p.
z Represents either m or h, and time constant (τ), factor (A), slope (S) and reversal potential (E) are constant parameters, specific to m or h. For interneurons, these parameters are set to 0, and there are no dynamic sodium currents. The parameters g syn , E lo , and E hi are constants representing the synapse's maximum synaptic conductance, its lower threshold, and its upper threshold, respectively. V pre here is the presynaptic neuron voltage. Details of neuronal and synaptic parameter can be found in Appendix A (Tables  A1  and A2 ). All the modeling and simulation was performed in Animatlab  [28]. The biomechanical model reconstruction is limited to motion in the sagittal plane for the rat hindlimbs, resulting in six actuated degrees of freedom, three for each hindlimb (hip, knee, and ankle), and three unactuated degrees of freedom (the forward and vertical translation, and pitch angle of the pelvis).
All the modeling and simulation was performed in Animatlab  [28]. The biomechanical model reconstruction is limited to motion in the sagittal plane for the rat hindlimbs, resulting in six actuated degrees of freedom, three for each hindlimb (hip, knee, and ankle), and three unactuated degrees of freedom (the forward and vertical translation, and pitch angle of the pelvis). To improve simulation and calculation speed, the biomechanical model was simplified by reducing the complexity of segment shapes (Figure  3 ). Instead of loading rat bone files scanned from X-ray images as previously described  [8, 26] , the pelvis (red), femur (green), tibia (yellow), and foot (purple) were constructed with simple box models. This resulted in the simulation running four times faster. The length, weight, and density of the bones, and the insertion points and properties of muscle are the same as in our previous biomechanical model.
5 s. When negative electrical current is applied to both rhythm generator neurons (blue area in Figure  6 ), the cycle period is prolonged to 0. 65 s per period. The cycle period is calculated using MATLAB (MATLAB 2017b, The MathWorks, Inc. , Natick, MA, USA). Each new period begins when the extensor pattern formation neuron voltage, V PFext , crosses a threshold (i. e. , V PFext = -60 mV and dV PFext dt > 0). The result of external stimulus to the rhythm generators demonstrates that rhythmic periods can be modulated with minimal influence on the motoneuron activation amplitudes. When a positive electrical current is applied to both rhythm generator neurons (orange area in Figure  5 ), the period of one stride is shortened from 0. 5 to 0. 35 s. After the excitatory stimulus is removed, the period immediately returns to 0.