dataesr/scientific-paragraphs-categorization huggingface dataset:
However, some BTB proteins have previously been reported to form heterodimers, which could result in a nonlinear response of this assay system and potentially misleading data  [3]. Therefore, we first employed our previously reported KEAP1 dimerization assay to address this question and test the capacity of KLHL11 to form heterodimers with KEAP1 (Fig. S3 )  [44]. As shown in Fig. 7A , we did not observe KEAP1-KLHL11 heterodimerization, rendering our approach viable for the direct profiling of KEAP1--CUL3 NTD interaction with this assay platform. Next, we performed dose-response experiments with the respective KEAP1 constructs in the KLHL11-CUL3 NTD protein displacement assay. We determined K D values of 720 nM (95% CI 650-797 nM) and 798 nM (95% CI 730-882 nM) for KEAP1 BTB-3-box and KEAP1 BTB-BACK-Kelch , respectively, suggesting that the complete BTB-BACK domain does not meaningfully contribute to the binding affinity of the KEAP1-CUL3 NTD interaction compared to BTB-3-box alone (Fig.
However, our structure provides no evidence to support this prediction. Nonetheless, in agreement with Cleasby et al. , we observe a potential steric clash with CUL3 when modelling its binding to the 3-box groove. To gain insights into the contributions of different domains and the impact of CDDO on KEAP1-CUL3 binding, we determined the equilibrium binding constants and binding kinetics of the various constructs. Unfortunately, we were unable to establish functional biolayer interferometry assays for several protein combinations. However, we successfully developed a robust and versatile biochemical TR-FRET assay platform based on our CoraFluor technology that facilitated the comprehensive, quantitative measurement of the CUL3 interactions. Importantly, when available, the data obtained by TR-FRET were in good agreement with the results determined by BLI.
One aspect of this has been the desire to trace personal histories through family trees and family history, often as retirement projects for an ageing population. However, this interest in local history illustrates where biography and geography intersect. Local historical societies bring together diverse interests including professional historians, amateur historians, locals and incomers. The increasing resources available online through the Internet, through public databases and even through commercial organisations offering to help trace family histories have made this view of the past all much more accessible. Social media, including the sharing of photographs on Facebook pages and Facebook groups have helped generate shared interests in revisiting the past. The burgeoning of local museums collecting objects, photos and histories has helped to strengthen these trends.
Embracing digital opportunities In 2011 a team of us at the dot. rural digital hub at the University of Aberdeen was invited to help the nascent digital platform 'Hebridean Connections' to develop a new online platform. This initiative to link the different CEs across the islands by providing a common, searchable database had run aground by being dependent on commercial software, which had in itself become obsolete. Therefore, a research team at the University of Aberdeen helped to set up a new database using free open-source software. Using semantic web technology, it was able to link to other archives and databases as well as conjoining the material across the islands. In this way, it was able to link residents, crofts, fishing boats and other information  (Tait et al. , 2013). However, this required that volunteers at the local CEs were trained to provide and validate data on the database.
Those coming in can further develop their sense of connectedness within the community. It also represents how the CE movement is not just indigenous islanders remembering their past but a vibrant series of communities attracting incomers who bring skills as well as bridging social capital to institutions outside the island. Third, digitalisation also fostered another kind of social linking -to the Scottish diaspora communities. The keen interest in Scottish heritage and in tracing 'one's roots' that is found among Scottish descendants elsewhere provides a new set of users and contributors to the digital platform. These more geographically scattered people could link in to cultural heritage information through the use of Hebridean Connections websites and databases which provided information about former residents, their fishing boats, marriages and crofts and places where they were born and died.
Additional and contested narratives could arrive from outside the community (for example from diaspora communities) and materials become submerged in the great global ocean of communications and subsequently remashed in unknown ways. This was why some CEs refused to participate in the online platforms created by Hebridean Connections. The project enabled the creation of a database of records, which could be cross-referenced and accessed openly based upon individuals, crofts, fishing boats or other reference points  (Tait et al. , 2013)  enabling online searches and constructing new information and narratives around local sources as they were connected in new ways both internally and externally. This therefore represents what  Rose (2016)  terms as the movement of cultural 'artefacts' into digital form and this chapter seeks to consider the changing geographies created by such a transition to collective way of knowing  (Elwood & Mitchell, 2015).
The Comainn Eachdraidh -six years on A set of follow-up interviews in 2019 illustrated some of the successes as well as the pitfalls of the digitalisation of cultural heritage. The database, which had been running from 2015 to 2019, generated 'hits' from an astonishing 151,096 people from 153 countries. Hence, while the database helped make local records more manageable and sustainable for local communities, it also helped link those communities with a wider world. So the 'local' became 'global'. In doing so, it was evident that the wider diaspora was also invested in a sense of local community with which they identified through their sense of history. In the words of one respondent: 'It starts with the local and it makes it international if you like … People from all over the world have connections with the place.
However, its popularity generated its own problems as this small number of workers were inundated with requests for information, not all of which could be followed up. Local authority spending cuts had cut the service to the bone and even the 1. 5 people employed also had to spread their time with other projects. The Facebook page in particular had generated a lot of interest and through the Facebook page people were redirected to the database and eventually to the relevant local CE branch. However, the database still relied on volunteers to upload and validate information, which was a painstaking and time-consuming piece of work that only trained volunteers could take up. There were not enough of them and therefore there was a backlog of materials that were on the database and not yet validated.
This is where the Facebook pages took on a life of their own, because it was relatively easy to upload and discuss photographs or other data. The Facebook page provided a very fast turnaround of information, was more easily accessed and enabled strong participation -in contrast to the Hebridean Connections database where all entries have to be laboriously and manually validated. This led the Hebridean Connections management to develop a revamped and easier database whereby materials could be uploaded for public information and only later validated. However, due to lack of funding, the launch had been delayed at the time of our interviews in 2019. A further complication was that since our initial contact in 2011, European Union GDPR legislation came into force, limiting what personal information could be held digitally.
This meant that all living persons had to be expunged from the database and only information about deceased persons could be uploaded. This was sometimes a problem for those trying to find information about living relatives. It became clear that the value of this database was a product of it constantly being updated and validated. Yet this activity was under threat due to the lack of trained volunteers (the training had taken place in 2015 and some of those trained had dropped out, died or moved away, so more training was needed). The whole project was under threat due to lack of funds and the uneven nature of project funding, which tended to be time Civil society, cultural heritage and digitalisation 2 9 3 limited. We had already discovered that the timing of project funding did not always coincide with what was needed, which was why there had been a two-year delay between initially setting up the Hebridean Connections project and actually implementing it, which was only possible when a grant had allowed two project officers to be employed for a year to go round and train volunteers in the CE branches.
The local museum becomes a community focal point. This also helps to generate economic benefits for the community, even if that was not the first principle, even in fairly remote islands: 'And the idea has always been that with that information (from the database) they'll then come and visit Bernera itself and spend money and provide a bit of income that way. ' Digitalisation helps to preserve cultural heritage and to make it available to a wider world. However, it is also dependent upon affordable and accessible technology -the reason we became involved in the project in the first place was that the previous database could only be maintained by a professional service -something which was unsustainable in the longer term. Therefore, the Hebridean Connections project was in some ways a victim of its own success as it created a demand that could not always be fulfilled.
7 he goal of asthma treatment is to achieve good control of symptoms, reduce exacerbations, and improve quality of life. This goal is still far from being achieved for severe non-eosinophilic asthma. A better knowledge of severe noneosinophilic asthma and its difference with eosinophilic asthma could favor the development of new therapeutic agents. Therefore, a secondary analysis of the data from the FASE-CPHG study which included adult patients with severe asthma was performed focusing on patients with non-eosinophilic asthma and comparing their characteristics and their management to those of patients with eosinophilic asthma.
Materials and Methods This study was a secondary data analysis of the existing FASE-CPHG database. FASE-CPHG was an observational, cross-sectional, prospective, multicentric study conducted in France by respiratory physicians working in non-academic hospitals on a large population of adult patients with severe asthma. Its primary objective was to assess the characteristics of patients with severe non-eosinophilic asthma and the burden of severe non-eosinophilic asthma. ] [15]  Data from 1502 adult (>18 years) patients with severe asthma were collected from May 2016 to June 2017 in France by 104 respiratory physicians in non-academic hospitals. All patients received information about the study and gave their informed consent before being included in the FASE-CPHG study. Patients were informed during a regular visit by their physicians.
4] [15]  Current analyses were performed using data that were deidentified. Only data from patients with severe asthma as diagnosed by the physicians and with reported data for blood eosinophil (EOS) counts were included in the present study. For data analysis, two groups of patients (EOS+ and EOS-) were constituted based on blood EOS counts. The threshold value for EOS+ asthma was primarily set at 300 giga (G)/l, and secondarily at 150 G/l. EOS-asthma was defined by blood EOS count below the threshold. For total serum IgE level, the threshold was set at 150 international unit per milliliter (IU/mL). Skin allergy or allergen-specific IgE assays (when performed) allowed to differentiate patients with (ALL+) from without (ALL-) allergic asthma. Statistical analyses were carried out using SAS software (SAS institute, 9.
4 version, North Carolina, USA). No hypothesis was tested for the study which was descriptive. Missing data were not replaced, and analysis was based on available data, considering missing data as non-indicative. Briefly, descriptive analyses included mean with standard deviation (SD), median with interquartile range (IQR) for quantitative variables and sample size (N) and frequency (%) per category for qualitative and ordinal variables. Tests (Student's t-test or Wilcoxon-Mann-Whitney nonparametric test) were performed to compare independent groups. Homogeneity of variances was tested by Levene's test. The normal distribution was based on the overall shape of the histogram and the result of the Shapiro-Wilk test if required. Association between blood eosinophil counts and total serum IgE levels was assessed with Pearson's Chi-square or Fisher's exact test.
Results Of the 1502 included patients in the database, 1075 patients with severe asthma according to GINA treatment criteria and a blood EOS count were recorded and included in the present analysis. Of these 1075 patients, 234 had an EOS count <150 G/l (21. 8%), 266 an EOS count between 150 and 300 G/l (24. 7%), and 575 an EOS count ≥300 G/l (53. 5%). When the sociodemographic and clinical characteristics of the patients considering either the 150 G/l or the 300 G/l thresholds were compared, they were very similar overall (data available in Supplementary Table  1  and Supplementary Table  2 ). The selected threshold was 300 G/l, and the EOS-and EOS+ groups therefore included 500 (46. 5%) and 575 (53. 5%) patients, respectively (Figure  1 ). Sensitization to allergens, treatment with OCS, and nasal polyposis were reported for 616 (57.
Discussion The present secondary analysis of the FASE CPHG database which was dedicated to severe asthma patients offered the possibility to improve knowledge about EOS-asthma, such as the characteristics of patients with EOS-asthma and level of control and management of their asthma. This analysis showed that EOS-asthma (<300 G/l of blood eosinophil) was approximately as frequent as EOS+ asthma (47% vs 53%). This result was in line with the literature until recently. 9, 16 A recent article published by Heaney et al concluded that the occurrence of a severe EOS-asthma was rare; 83. 8% of the patients of their study were identified as most likely to have severe EOS+ asthma. In their study, EOS+ asthma was defined using a multicomponent "eosinophil gradient algorithm". This composite criterion considered blood EOS count, OCS use, elevated fractional exhaled nitric oxide, nasal polyps, and adult-onset asthma.
Acknowledgments The authors would like to thank the  Collège des Pneumologues des Hôpitaux Généraux (CPHG, France)  which initiated the  FASE-CPHG study, Kappa Santé company (Paris, France)  for the management of collected data, and  Abelia Science (Saint-Georges-sur-Baulche, France)  for providing medical writing support. The authors also thank the FASE-CPHG participants and investigators for making this study possible:  Dr Parrat  ( CH Papeete );  Dr Nocent  ( CH Bayonne );  Dr Mangiapan  ( CHI Créteil );  Dr Prud 'homme and  Dr Courdeau-Labourie  and  Dr Demaegdt  ( CH Tarbes );  Dr Oster  and  Dr Moreau  and  Dr Allibe  ( CH Colmar );  Dr Portel  and  Dr Roy  ( CH Libourne );  Dr Appere De Vecchi  ( CH Argenteuil );  Dr Maurer  ( CH Montfermeil );  Dr Lepoulain Doubliez  ( CH Charleville Mezières );  Dr Iamandi  ( CH Mulhouse );  Dr Gourcerol  ( CH Pau );  Dr Didi ,  Dr Decroisette  and  Dr Bertocchi  ( CH Pringy );  Dr Barbare  and  Dr Moncelly  ( CH Meaux );  Dr Tannous  ( CH Forbach );  Dr Kelkel  ( CH Chambéry );  Dr Rolland  ( CH Cannes );  Dr Jouveshomme  ( Hôpital St-Joseph, Paris );  Dr Bernier  ( CH Dinan );  Dr Hauss ,  Dr Ould ,  Dr Vincent ,  Dr Van Mossevelde  and  Dr Gallego  ( CH Elbeuf );  Dr Merzoug  ( CH Fougères );  Dr Haddad  ( CH Lourdes );  Dr Guerrero ,  Dr Jarjour ,  Dr Haouachi  and  Dr Goutorbe  ( CH Béziers );  Dr Morel ,  Dr Lemaire  and  Dr Russier  ( CH Orléans );  Dr Roge  ( CH Morlaix );  Dr Dumont  ( CH Chauny );  Dr Cavestri  and  Dr Just  ( CH Roubaix );  Dr Colin  ( CH Versailles );  Dr Goupil ,  Dr Mansour  and  Dr Paris  ( CH Le Mans );  Dr Philippe  and  Dr Boitiaux  ( CH Cergy-Pontoise );  Dr Simon  ( CH Compiègne );  Dr Marcq ,  Dr Bizieux ,  Dr Guibert  and  Dr Caby  ( CH La Roche sur Yon );  Dr Lecuyer  ( CH Saint-Quentin );  Dr Merlusca  ( CH Sedan );  Dr Blanc  ( CH Aix en Provence );  Dr Langelot  ( CH Les Sables d'Olonne) ;  Dr Tagu  ( CH Bar le Duc );  Dr Leveiller ,  Dr Duriel-Niel  and  Dr Coëtmeur  ( CH Saint-Brieuc );  Dr Ilie  ( CH Dunkerque );  Dr Raspopa  ( CH Toulon );  Dr Lerousseau  and  Dr Rotomondo  ( CH Antibes );  Dr Gramada  ( CH Sarreguemines );  Dr Cornu  and  Dr Petit  ( CH Verdun );  Dr Kraemer  ( CH Fréjus );  Dr Guy  ( CH Vannes );  Dr Gentil ,  Dr Luciani  and  Dr Lucena  ( CH Bourgoin Jallieu );  Dr Michaux  ( CH Macon );  Dr Maitre  ( CH Vesoul );  Dr De Faverges  ( CH Nevers );  Dr Fouret  ( CH Villeneuve Saint-Georges );  Dr Goarant  ( CH Saint-Malo );  Dr Bara  and  Dr Hamoudi  ( CH Angoulême );  Dr Maetz  ( CH Douai );  Dr Yousef  and  Dr Lungoci  ( CH Le Puy en Velay );  Dr Al Freijat  ( CH Belfort );  Dr Assemi  ( CH Saverne );  Dr Beysens  ( CH Saintes );  Dr Clarissou  ( CH Beaumont sur Oise );  Dr Karimo  ( CH Saint-Omer );  Dr Saadi  ( CH Barbezieux Saint Hilaire );  Dr Barre  and  Dr Farny  ( CH Cahors );  Dr Romand  ( CH Contamine sur Arve );  Dr Leleu  ( CH Abbeville );  Dr Bernard  ( CH Quimper );  Dr Marangoni  ( CH Saint-Dié );  Dr Fevrier  ( CH Saumur );  Dr Paillot  ( CH Metz );  Dr Bonnefoy  ( CH Jonzac );  Dr Manoila  ( CH Evreux );  Dr Abraham  ( CH Dax );  Dr Lacroix  ( CH Périgueux );  Dr Virally  ( CH Aulnay sous Bois ).
Data and simulation samples The data used in this search correspond to an integrated luminosity of 139 fb -1 of pp collision data collected by the ATLAS detector between 2015 and 2018 at a centre-of-mass energy √ s = 13 TeV. The uncertainty in the combined 2015-2018 integrated luminosity is 1. 7%  [34] , obtained using the LUCID-2 detector  [35]  for the primary luminosity measurements. The presence of additional interactions in the same or neighbouring bunch crossing, referred to as pile-up, is characterised by the average number of such interactions, μ , which was 33. 7 for the combined data sample. Only events recorded under stable beam conditions and for which all relevant detector subsystems were known to be in a good operating condition are used. Dedicated Monte Carlo (MC) simulated samples are used to model SM processes and estimate the expected signal yields.
Z + HF background The normalisation of the Z + HF background, which is a relatively small contribution in the SRs, is observed to be in disagreement with the NLO cross-section in Sherpa (e. g. Ref. [116]). It is therefore determined from data using a Z +HF CR that targets events containing a Z boson decaying into a light-lepton pair and produced in association with two heavy-flavour jets. The composition of this control region is approximately 60% Z + HF events and 40% t t events, with less than 1% arising from backgrounds with misidentified τ had-vis. Since the contribution from backgrounds with misidentified τ had-vis is negligible, only the RF for the t t shape is included in this CR. Data for the CR was recorded using a combination of the single-lepton triggers described above and additional dilepton triggers requiring pairs of same-flavour leptons.
Uncertainties are considered from changing the matrix element, parton shower, and impacts of diagram interference. In addition, variations of initial-and final-state radiation and PDFs are considered. The matrix element uncertainty is determined by comparing the Powheg+Pythia 8 sample with an aMC@NLO+Pythia 8 sample. The parton shower uncertainty is determined by comparing the Powheg+Pythia 8 sample with a Powheg+Herwig 7 sample. The diagram interference uncertainty is evaluated by comparing the nominal single top samples, which use a diagram removal scheme, with alternative samples that utilise a diagram subtraction scheme  [119]. The other modelling uncertainties are evaluated using internal weights in the nominal single-top samples. All t t and single-top modelling uncertainties are also propagated through the top reweighting procedure, such that there Table  4  Post-fit yields for background events, determined from a background-only fit, compared with the observed number of data events in the τ lep τ had and τ had τ had SRs.
ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TENMAK, Türkiye; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain;.
Study region: Data-scarce basins located in West Africa and northern Central Africa. Study focus: Multiple studies have shown that global gridded precipitation datasets could provide an alternative to the lack of observed data in Sub-Saharan Africa. This work evaluated 15 precipitation datasets based on satellite rainfall (ARC v. 2, CHIRP v. 2, CHIRPS v. 2, PERSIANN-CDR, MSWEP v2. 2 and TAMSAT v3), reanalysis (ERA5, JRA-55 Adj, MERRA-2 PRECTOT, MERRA-2 PRECTOTCORR, WFDEI-CRU and WFDEI-GPCC) and ground measurements (CPC v. 1, CRU TS v. 4. 00 and GPCC v. 7), as well as a regional estimation method, based on spatial proximity, for the parameters of a simple monthly water balance model, GR2M. The regional simulations of the GR2M model were evaluated based on a Kling-Gupta Efficiency score in a split-sample spatiotemporal validation scheme.
Indeed, infrared recordings make it possible to deduce the temperature of the clouds and to estimate the quantity of precipitated water. On the other side, satellite microwave sensors allow precipitation estimation through measuring the microwave radiation emitted or reflected by the atmosphere and Earth's surface. In addition to the analysis of cloud dynamics, there are satellite estimates, again using the infrared and microwaves, of soil surface temperature and even soil humidity  (Martens et al. , 2017). Machine learning methods such as neural networks make it possible to take better advantage of this mass of data  (Hsu et al. , 1999 (Hsu et al. , , 1997;; Sun et al. , 2018). Furthermore, the ground-based GPEs and bias correction procedures based on physiographic indices ensure the design of more robust composite GPEs that take into account satellite estimates  (Ashouri et al.