dataesr/scientific-paragraphs-categorization huggingface dataset:
significantly better than random models (p-values from twosided paired Student's t-test obtained by class-permutation test equal 4. 57•× 10 -6 and 2. 86•× 10 -4 , respectively; see Figure  1  and Table  1 ). For each case, the best model is defined as that obtaining the highest MCC in 10 standard LOOCVs of the full dataset (i. e. all data instances and all available features). Figure  S6  shows that the performance of these models is robust to different sizes of both training set and test set. As observed in Figure  2  CART models strongly reduce the number of features involved in the predictions. The miRNA expression-based model found that 4 out of 337 mature miRNAs were the most informative features (MIMAT0004985 or miR-942-5p, MIMAT0000084 or miR-27a-3p, MIMAT0000274 or miR-217, and MIMAT0004657 or miR-200c-5p), while the CpGsite methylation model identified 2 out of 22,941 CpG sites as the most informative features (cg09691574, which is related to the protein coding genes MRGPRX4 and SAA2-SAA4, and to the lincRNA RP11-113D6.
Moreover, these models allow going further in the interpretation of response to paclitaxel (Figure  2 ). For example, the CpG-methylation DT unveils two rules employing only two features to predict which are the paclitaxel-sensitive BC tumors (Figure  2 ). The other example is the miRNA DT, which carries out these predictions using four induced rules based on only four features (Figure  2 ). Thus, the application of these rules to forthcoming tumors should improve paclitaxel treatment for BC patients. To facilitate such application, we are providing two python scripts in the supplementary materials, each implementing the rules for one of these predictive profiles. Our best classifier obtained a median MCC of 0. 54 in 10 LOOCV runs (an average MCC of 0. 62, with MCC ranging from The predictive performance of CART models was presented in Figure  1.
MATERIAls And METHOds Cohorts We used a sample of 2938 individuals of European ancestry for whom complete clinical and GWAS data were available. This sample comprised individuals from a pre-existing international collaboration formed to study the genetics of response to TNFi agents  12  and individuals recruited to the Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate (BRAGGSS) after 2013. 4  Table  1  shows sample sizes, phenotypes and clinical variables for each of the data collections used in this study. All participants provided informed consent, and institutional review board/ ethics approvals were in place as described in Cui et al  12  and Massey et al. 4.
Genotypic risk scores We used the GENOSCORES platform (https:// pm2. phs. ed. ac. uk/ genoscores/) to compute genotypic risk scores for the intermediate traits. GENOSCORES is a database of published SNP to trait associations from a large number of well-powered GWAS, including GWAS of disease traits, biomarkers, gene expression and methylation. The database is accompanied by a software package implemented in R that can be used to compute genotypic risk scores and run downstream statistical analyses in cohorts with SNP data. We queried the GENOSCORES database for genetic associations with RA risk, 9 149 heritable immune cell traits reported by Roederer et al, 10 and whole-blood expression and methylation for 93 genes reported in a recent meta-analysis  11  as differentially expressed before treatment between responder and non-responder patients with RA treated with TNFi.
Evaluation of prediction We used two measures to quantify improvement in prediction: the difference in log-likelihood between a model with clinical covariates and genotypic scores and a model with clinical covariates only (measured in natural log units (nats)); and the per cent of residual variance explained by the genotypic scores. Both measures were computed on the testing data from 10-fold cross-validation on the full data set. For readers who prefer a frequentist interpretation, the asymptotic equivalence of model choice by cross-validation and Akaike's information criterion (AIC)  22  implies that a p value of 0. 01 for comparison of nested models is equivalent to a difference in test log-likelihood of 2. 3 nats (likelihood ratio of 10) for models differing by one extra parameter. The large sample size of this study means that small robust increments in predictive performance can be detected.
Acknowledgements We thank all the patients who have contributed to this research and clinical staff who supported patient recruitment. We thank the  Medical research council and arthritis research UK (arUK)  for their joint funding of the Maximising Therapeutic Utility in rheumatoid arthritis (MaTUra) study. We thank  MaTUra consortium members  for their input and feedback during the design of this project, and we would like to give particular mention to Felix agakov,  Jennifer H Barrett  and  Heather J cordell. The list of MaTUra collaborators and affiliations is available in the online supplementary information (table s12). We thank  Peter K Gregersen  for providing access to clinical and genetic data from the aBcon cohort. We thank stephanie ling for collating acPa data from the BraGGss cohort into a usable format.
Simulator As a standalone simulator, AFF3CT proposes to simulate various communication chains with a broad range of codes. The simulator is a command line program; Fig. 2  depicts its main arguments: -m and -M set the minimum and the maximum Signal Noise Ratio (SNR, E b /N 0 ) to simulate, -s specifies the iteration step inbetween. Parameter -C selects the channel code type, -K sets the length in bits of the initial information message and -N sets the codeword size, which is the encoder output size. 3 The command line interface is designed to be easily used from scripts. Fig. 3  shows simulations ran with AFF3CT on various code types (BPSK modulation and AWGN channel).
Software functionalities The AFF3CT software functionalities can be decomposed in three main parts: the codecs, the modems and the channels. The codecs are the main part of the toolbox. There is a broad range of supported codes listed in Table  2. The codecs naturally encompass the encoders and decoders, but they can also include puncturing patterns to shorten frames length according to some communication standards. Most of the codec algorithms come from the literature, while the others have been designed under AFF3CT  [2] [3] [4] [5]. In channel coding, the decoder is the most time-consuming process, compared to the puncturing and the encoding processes. This is why a specific effort is put on ensuring the high computing performance of the decoders. Most of the decoding algorithms have thus been optimized to satisfy high throughput and low latency constraints  [6] [7] [8] [9].
Those optimizations generally involve a vectorized implementation, a tailored data quantization and the use of fixed-point arithmetic. In typical communication chains, it is necessary to adapt the digital signal to the physical support. This operation is performed by the modulator and conversely by the demodulator. AFF3CT comes with a rich set of modems to this purpose. Table  3  lists all the supported modems. AFF3CT supports several coded modulation/demodulation schemes like the Continuous Phase Modulation (CPM)  [10, 11]  and the Sparse Code Multiple Access (SCMA) modulation  [12] [13] [14]  (many codebooks are supported  [15] [16] [17] [18] [19] [20] [21] ). It allows to easily combine and evaluate the channel codes with several types of modulations. In the case of the CPM, analogical wave shapes are also simulated.
For all the CPU targets, the code has been compiled with the C++ GNU compiler version 8. 2. 0 on Linux, with the following optimization flags: -O3 -funroll-loops -march = native. Note that AFF3CT also works on Windows and macOS at the same level of performance. The simulation scales rather well on the tested architectures. The data remains in the CPU caches because of the moderate frame size (N = 2048). Scaling on the Xeon Gold 6142 is not as good as the other targets, because the Intel Turbo Boost technology is enabled on this platform: the CPU runs at higher frequencies when the number of active cores is low. AFF3CT effectively leverages the simultaneous multi-threading (SMT) technology. This is especially true for the ThunderX2 CN9975 and Xeon Gold 6140 targets. The SMT technology helps to improve the usage of the available instruction-level parallelism.
Using AFF3CT as a library Listing 2: Modules allocation. 1 # include <aff3ct. hpp > 2 using namespace aff3ct ; In this section the communication chain proposed in Fig. 4  is implemented with the AFF3CT library. The first step is to allocate the modules. In Listing 2 we chose to allocate modules on the stack, but it is also possible to do the same on the heap. K is the number of information bits, N is the frame size and E is the number of erroneous frames to simulate. One can notice that there is a module for the encoder and for the decoder, this differs from Fig. 4  where encode and decode are tasks of the codec module. In fact the codec module exists in AFF3CT and it is an aggregation of the encoder and decoder modules. For simplicity, we chose not to use the codec module here. In this basic example, a repetition code is selected, it simply repeats the information bits N/K times.
Impact AFF3CT is currently used in several industrial contexts for simulation purposes (Turbo concept, Airbus, Thales, Huawei) and for specific developments (CNES, Schlumberger, Airbus, Thales, Orange), as well as in academic projects (NAND French National Agency project, IdEx CPU). The MIT license used in the project is very permissive and gives confidence to industrial and academic partners, who can then invest themselves and reuse parts of AFF3CT in their own projects without any restrictions. An important aspect of channel coding is the ability to reproduce state-of-the-art results, because there are many possible configurations and it is time-consuming to rediscover those configurations. This is why AFF3CT comes with a large database of pre-simulated performance curves with all the required parameters.
Conclusion and future works In this paper we presented AFF3CT, a forward error correction toolbox that enables high throughput simulations thanks to multi-node, multi-threaded and vectorization paradigms. AFF3CT makes reproducible and replicable science possible with a large database of reference simulations available, and tools to reproduce them quickly on commonly used systems. Both the AFF3CT library and standalone simulator ship with a wide range of heterogeneous algorithms, and can easily be enriched by the community, for instance with additional families of codes, or to fit new application contexts such as software defined radio. In the near future, a wrapper is scheduled to directly use the AFF3CT library from MATLAB and Python. It will give the opportunity to non-experts in C++ community to easily take 4 BER/FER comparator: http://aff3ct.
Through the "Know your city" program ,the SDI network assumes that residents are more able to resist eviction policies once they have been able to document their existence themselves. The objective of the Map & Jerry project was not initially to describe the neighbourhood using the grid used by SDI. But, knowing this network and how it works, we were inspired by this community-driven data collection and participatory mapping method, produced in a bottom up manner, i. e. by the inhabitants themselves who are best placed to remind the world of their existence. A few months after the start of our project in Ladji, we learned, without much surprise, that a delegation of SDI, from Nigeria, was preparing to train people in the neighbourhood, to " empower" them to face the announced evictions 8. It is therefore inspired by all these examples of participatory mapping, their successes and failures, and with the expertise and skills of our two partners, BloLab and the OpenStreetMap community, very active in Benin, that we launched the Map & Jerry project in January 2018.
This first workshop for the manufacture of jerrys lasted 8 days, gathering 40 people, from 18 to 55 years old, and with various profiles: fishermen, students, unemployed people, traders. Women accounted for a quarter of the participants. At the end of the workshop, 17 jerrys were assembled. 10 2. Mapping phase: it is then a question of using computers equipped with free software to map the neighbourhood with the inhabitants, using the OpenStreetMap methodology. Now initiated in NICTs 10 and equipped with computer equipment, the 36 participants of this second workshop discovered the reading of a geo-referenced map and were trained in the knowledge and mastery of cartographic editing tools (JOSM) or free mobile applications (OSMand, OSMTracker, Mapillary) used to create cartographic content (lines, points, photographs.
However, even if a period of training in the JOSM editing software was provided, this did not give them the ability to create and edit map data autonomously on the OpenStreetMap database. The digitization of buildings and streets, the cleaning of information acquired during the field phase, and their integration into the database were thus carried out by OSM Benin staff, before and after the training. Due to a lack of required skills, participants remained confined to the role of contributors, unlike OSM mappers who have the ability to edit information, change colors or even create new symbology on the database. This high level of expertise required was impossible to achieve within the time frame of the project. This would have required more training and participation time, which would have been difficult for people (mothers of families, businesswomen, unemployed young people or students), whose resources depend on daily activities.
This caused significant variations in electrical current intensities: a computer and several power sockets were fried under their effect. In addition, of the 36 participants in the second phase, only five had a smartphone, which is an essential tool for data collection. We therefore provided them with 10 devices for the duration of the training to allow everyone to participate in the collection of GPS points in the field. But without a personal smartphone, how can we continue to feed the neighbourhood map on a daily basis after the project? For residents of a precarious neighbourhood, without financial resources, how can we ensure the maintenance of computers afterwards, or rent a space to make jerrys available to all, and pay for Internet access at a prohibitive cost? If frugal innovation is to be the way to do better with less  (Radjou, Prabhu, 2015) , it is difficult to "do better with nothing".
Finally, a reflection must be made on the categories and graphic choices made by OpenStreetMap. A certain semiology is used, relatively codified on a global scale and not very modifiable. It is a "Western" and standardized graphic language, which leaves little room for the expression of local culture, as G. Rambaldi (2005)  pointed out in his article "Who owns the map legend?" This semiology may have appeared to be a limitation because it did not correspond to the realities of the district. This was particularly the case for locating places of worship and in particular those related to voodoo. How do you represent convents and identify the different Vodoun deities (fetishes in particular) present in space? The OSM community chose to use the figurative "place of worship" which represents a kneeling individual.
Georges, local authority, when he discovered the map. This testimony says a lot about the symbolic and political significance of the map. Neighbouring neighbourhood leaders regularly ask us to benefit from the Map & Jerry project and in turn obtain a map, a sign of its political importance. At the end of the project in August 2018, Ladji presents itself as one of the most detailed districts in Cotonou on the OpenStreetMap map. In free access, the work carried out by OSM and the inhabitants was subsequently transferred to Google Map for its own database. This precarious neighbourhood is therefore temporarily put in the spotlight on Google and OSM, even though a few months earlier, there was no official map. We designed the project against the backdrop of the principles of the "right to the city", as defined by Henri  Lefebvre (1968).
New information and communication technologies 11. This application is the free and open source equivalent of the Google Street View platform. The images are accessible on the Mapillary database. 12. The results will be the subject of another article. For more information, see the website of the Observatory of Coastal Urban Dynamics in West Africa (URBACOT) project: https:// urbacot. hypotheses. org. See also the media coverage of the project: participation in two radio programmes, a report by RFI, two press articles in national newspapers, as well as the video report of the project (Map & Jerry on youtube). 13. In Benin, the average monthly income is 38,000 FCFA, or 58 € according to the national statistics institute in 2016. The cost of an unlimited internet connection is at least 15 000 FCFA / month (23 €).
Blolab is the first FabLab in Benin. 3. The OpenStreetMap (OSM) project is a mapping project that aims to build a free geographic database of the world. It relies on volunteers organized in groups around the world, as here in Benin (see WikiProjet Benin). See in particular the electronic forum on participatory technologies and information systems. For more information, see the valuable bibliographies prepared byMcCall (2015)and Rambaldi.
Blolab is the first FabLab in Benin. 3. The OpenStreetMap (OSM) project is a mapping project that aims to build a free geographic database of the world. It relies on volunteers organized in groups around the world, as here in Benin (see WikiProjet Benin). See in particular the electronic forum on participatory technologies and information systems. For more information, see the valuable bibliographies prepared byMcCall (2015)and Rambaldi Amelot X. , 2013, "Cartographie participative pour le développement local et la gestion de l'environnement à Madagascar : empowerment, impérialisme numérique ou illusion participative ?", L'Information géographique, Vol. 77, No. 4, 47-67. Antoni J. -P. , Klein O. , Moisy S. , 2004, "Cartographie interactive et multimédia : vers une aide à la réflexion géographique"4.
Materials and methods 12Ab oligomer complexes preparations The structure of 12Ab 11-40 oligomer was taken from the protein data base (PDB ID: 2LMN) based on numerous constraints from solid state NMR and electron microscopy. 70 Available inhibitors for Ab 40 peptide were searched referring the binding database. 71 he 3D structures of 30 inhibitors were downloaded from PubChem database (see Table  S1  in the ESI † for the list of inhibitors). The geometrics of these compounds was optimized using chemical quantum calculation with B3LYP functional at 6-31G(d) level. The molecular docking protocol using Autodock Vina 72 was then applied to obtain the Ab bril complexes as starting structures for MD simulations. The binding poses of these inhibitors to the 12Ab 11-40 oligomer are depicted in Fig.
Moreover, we exploit the sparse polynomial structure to improve the performance. More generally, our implementation uses the Intel vector instructions to obtain interesting speed-ups. Our library also supports DualModeMS  [25] , which is a candidate in the NIST PQC standardization process. It is a modified HFE-based signature scheme which permits to decrease the size of the public-key, but by increasing the size of the signature. The parameters are chosen to minimize the sum of both sizes. By improving the implementation of HFE-based schemes, we automatically improve the implementation of DualModeMS. Evaluation of multivariate quadratic systems. Many multivariate cryptosystems require to evaluate a multivariate quadratic system (MQS) to encrypt data or verify a signature (e. g. [17, 15, 19] ).
Encryption uses secret data and should be performed in constanttime, whereas verification is a public process and does not have this constraint. In HFEv-signature schemes, the evaluation step is the main part of verification. Efficient implementations of evaluation have been studied in  [7, 16, 19, 20]. The authors of  [7]  propose different strategies for the evaluations in F 2 , F 2 4 and F 2 8. In  [16] , the evaluation is vectorized with ssse3 instructions in F 31 , F 16 and F 256. In  [19] , the authors propose to optimize the evaluation in F 31 and F 2 256 by evaluating the public-key equations one-by-one. Their implementation is vectorized with the avx2 instructions set. In  [20] , the authors present a faster evaluation with the same instructions set. To do so, they use a "monomial representation" of the public-key: for each monomial, the corresponding coefficients in each equation are stored together.
Choice of parameters. Table To find a root of F (X, v) -D. During the signature generation, F (X, v) -D cannot have solution. In GeMSS, r and v are changed while F (X, v) -D does not have roots (cf. Algorithm 2). Then, when there are roots, one is deterministically chosen for fixed D , by using the SHA-3 of D as a randombytes generator. In Gui, v is changed while F (X, v) -D does not have a unique root. In practice, d is generated from the hash of a document. To do it, GeMSS uses SHA-3, whereas Gui uses SHA-2. The output size of the hash functions is the double of the level of security. In MQsoft, we have chosen the SHA-3 function from the Keccak Code Package  [26]  and the SHA-2 function from OpenSSL.
• VPERMQ: this instruction from avx2 permutes the 64-bit parts of a 256-bit register. In particular, it can duplicate one 64-bit part four times. • VPMASKMOVQ: this instruction from avx2 loads four contiguous 64-bit integers from a buffer, then applies a mask which permits to set to zero 64-bit parts. • POPCNT: this instruction counts the number of bits set to 1 in 64-bit integers. It is used to speed-up the dot product of vectors in F 2. We benchmarked our software toolkit against the following softwares or libraries. • Magma (  [12] , version 2. 23-6). Magma is a computer algebra software, well-known to be very efficient over finite fields. • NTL (  [43] , version 10. 5. 0), installed with GMP ([28], version 6. 1. 2). NTL is one of the best library for number theory. It is implemented in C++.
• gf2x ([14],version 1. 2). gf2x is a C implementation of the state-of-the-art multiplica- tions in F 2 [X]. The multiplication algorithm depends on the degree of the operands and the vector instructions set available. When PCLMULQDQ is not available, MQsoft uses the gf2x multiplication. Magma is running with magma. avx64. dyn. exe to take advantage of vector instructions. In our tests, the avx64 version optimizes mainly the performance of multiplication in binary fields. The measurements used one core of the CPU, and the C code was compiled with gcc -O4 -mavx2 -mpclmul -mpopcnt -funroll-loops. We use the version 6. 4. 0 of gcc. Turbo Boost and Enhanced Intel Speedstep Technology are disabled to have more accurate measurements, excepted when we use DesktopH and DesktopS. In practice, Turbo Boost generates a speed-up of 1.
The field multiplication with modular reduction using sse2 is the fastest, because the PCLMULQDQ instruction requires to use 128-bit registers. When sse2 is used with avx2, the implementation pays a penalty. However, this problem will be solved with the VPCLMULQDQ instruction on the future Ice Lake processors [1]. In Table  9 , the modular reduction is measured when it is used with squaring in F 2 [X]. As for the multiplication in F 2 n , the performance of squaring depends on the context. For this reason, we measure it in two ways: • Left value: we measure the cost of one field squaring on average during the raising of an element of F 2 n at the power 2 i (x 2 i is computed as (x 2 i-1 ) 2 ). Each result depends on the previous result, and the data are already loaded. • Right value: we measure the cost of one field squaring on average to compute the squaring of elements of one buffer.