dataesr/scientific-paragraphs-categorization huggingface dataset:
Procedure. The participants sat alone in an experimental room in front of a computer and were asked to wait for the experimenter to contact them via a text (written) chat conversation using Skype. The experimenter initiated the chat conversation and provided the following initial brief to the subject: "design a process that allows by which a hen's egg that is dropped from a height of ten meters does not break". Each subject was then instructed by the experimenter to write down, in the chat conversation, the maximum number of original ideas they could generate to solve this problem. The task duration was set to 10 minutes per participant. Using an existing database of solutions that was collected over the last five years  [8] , two experimenters were trained before the experiment to identify whether a generated idea belonged to the fixation paths (which included damping the shock, slowing the fall, and protecting the egg) or were outside of those paths (for instance, interventions implemented before or after the fall, the use of a living device, the use of the intrinsic properties of the environment, etc.
). Table  1  lists the categories of solutions to the hen's egg task according to the database. The participants in the control group received neutral feedback that simply acknowledged the reception of an idea generated by the subordinate and awaited the next idea. For the participants in the congruent executive feedback group, if the generated idea was in the fixation path, the feedback provided was "search for another path"; in contrast, if the generated idea was in the expansion path, the provided feedback was "continue in this path". In contrast to the congruent executive feedback group, for the participants in the incongruent executive feedback group, if the generated idea was in the expansion path, the provided feedback was "search for another path"; in contrast, if the generated idea was in the fixation path, the provided feedback was "continue in this path".
Model Setup. Simulations were performed with the finite element software "Code Aster" (Code of Structural Analysis and Thermomechanics For Studies and Research, EDF, France). This code is a general code for thermomechanical calculations and includes a series of analytical methods and nonlinear multiphysical modelling. The finite element method (FEM) was implemented for discretization. The "THM" module of "Code Aster" was used to treat the continuum mechanics equations using the theory of unsaturated porous media and assuming completely coupled mechanical, thermal, and hydraulic phenomena. In our study, the "AXIS HH2D" model was selected from the "THM" module. "AXIS" indicates axisymmetry, "HH2" indicates hydraulic modelling with two unknown pressures and two   components, and "D" indicates that the points of integration are taken at the tops of the elements.
In a previous work  [5] , both PNES and VVS events were examined in an attempt to extend the non-epileptic class. In order to automatically classify epileptic and non-epileptic (PNES and VVS) EEG epochs, a large set of temporal and spectral features was examined using an EI scheme for the combination of information across EEG channels using a dataset of 11 patients. Although such a spatiotemporal analysis captures holistically the change of the EEG signal, the limited number of the available samples was not enough to fully capture the spatiotemporal variation. This is a common problem in biomedical applications where the high dimensionality of the data hinders data modeling and representation  [18]. Building upon our previous work  [5]  in which an EI scheme was implemented, we now investigate two LI schemes performing per channel classification.
Data In this paper, we use EEG recordings acquired by the Department of Clinical Neurophysiology and Epilepsies in St Thomas' Hospital, London, UK from 11 patients for the needs of the ARMOR project  [19]. For investigation purposes the epileptic and non-epileptic events were manually annotated and isolated from the recordings. The epileptic events were derived from patients diagnosed with Idiopathic Generalized Epilepsy (IGE) with absence seizures. The isolated epileptic events consist of Generalized Spike Waves (GSW) derived from the epileptic group. The non-epileptic events were derived from 2 patients with VVS and 5 patients with PNES. For all the examined subjects, at least one typical epileptic or non-epileptic event appear during the recording. The recordings were performed using conventional AgCl EEG electrodes positioned according to the extended international 10-20 system.
We previously evaluated  [5]  the ability of the extracted features to differentiate epileptic from non-epileptic epochs by examining several classification algorithms implemented by the WEKA machine learning toolkit software  [24]  including the BayesNet  [24, 26] , RandomCommittee, RandomForest  [27] , IBk  [28]  and SMO  [29, 30]  with RBF kernel. Since the overall highest accuracy was achieved by the BayesNet classifier, we now evaluate the examined fusion schemes with respect to the BayesNet. In BayesNet algorithm, a bayesian belief network structure, which is a directed acyclic graph, is built  [25, 26]. In such a graph, features are represented by nodes and dependencies among features are represented by edges between nodes. If there is no direct probabilistic dependency between the features the corresponding edge is absent.
As can be seen in Table  4 , the overall highest accuracy for classification between epileptic and non-epileptic EEG events is 90% for the LI with global training model fusion scheme. The LI with local models and EI schemes follow with 89% and 86% accuracy, respectively. For the LI with global model scheme with the highest accuracy, the sensitivity (or recall), i. e. the proportion of epileptic events which are correctly classified as such, is 94% and the specificity, i. e. the fraction of nonepileptic events (either PNES or VVS) which are correctly identified as such, is 84%. Although a LI scheme with either channel dependent models or one channel independent model, does not exploit the spatial information of the EEG, it improves the classification performance. It seems that the high dimensionality of the training samples at the EI fusion scheme of  [5]  is not appropriate for rather limited datasets.
The characteristics of the LI with global model fusion scheme (smaller dimensionality, more training samples), make it the most appropriate for our dataset. In a further step, we applied feature ranking using t-test and the leave-one-out strategy as described in Section 2. 4  The performance of the classification, in terms of accuracy, for each fusion scheme separately and for different number of N-best features, N=10,20, 30,. 1150 when EI scheme is evaluated and N =1, 2, 3,. 55 when LI schemes are evaluated are shown in Figure  4  and Figure  5  respectively. As can be seen in the above figures for all fusion schemes the highest classification accuracy is achieved when a small subset of discriminative features is used. Specifically, when LI fusion schemes are used the highest accuracy is achieved for a subset of 2 best features (number of local minima and number of local maxima) with a percentage of 91,71% for both of them, which is sufficiently high in comparison to the accuracy achieved when all features are used (88,78% for the LI with local models and 90,24% for the LI with global model).
In general, the experimental evaluation of the fusion schemes under examination indicates that in datasets with rather limited number of samples, LI schemes with global models give better classification performance compared to EI schemes even after feature selection. Finally, for each fusion scheme we performed PCA on the corresponding feature matrix. The feature matrices are formulated as described in Section 2. The feature matrix in the EI scheme is of dimensionality 205 × 1155. The dimensionality of each feature matrix in LI scheme with local models is 205 × 55 whereas in LI scheme with global model it is 4305 × 55. After sorting the eigenvectors in descending order we compute the proportion of retained variance for different number of retained eigenvectors by 𝑉𝑎𝑟𝑖𝑎𝑛𝑐𝑒 = ∑ 𝜆 𝑖 𝑟 𝑖=1 ∑ 𝜆 𝑗 𝑚 𝑗=1 where λ i is the eigenvalue for the i-th principal component, r is the number of retained eigenvectors and m is the total number of components.
Once again the LI scheme with a global training model outperforms the other two schemes and achieves the overall highest accuracy (96,59%) and sensitivity (100%) of our work with the burden of lower specificity (91,46%). However, the fact that PCA assists the LI scheme with global model in classifying more accurately the epileptic events but fails to improve the classification of the non-epileptic ones should not be considered as a general conclusion since it is possibly owed to our unbalanced dataset. The number of the epileptic epochs in our dataset (123 epochs) is slightly higher than the one of the nonepileptic (82). As a result, the few retained eigenvectors describe better the epileptic class resulting to high sensitivity. For the two other schemes, the classification accuracy when using PCA drops in comparison to both classifications with fully-dimensional or reduced by the t-test feature vectors.
For both LI schemes the classification accuracy increases with the growth of retained variance reaching its maximum when 3 and 2 components are retained for the LI with local and global models respectively. For the EI scheme the maximum accuracy is achieved when 198 components are retained (100% retained variance) and such a steady increase of accuracy cannot be observed. Although it is difficult to directly compare our results with other studies due to the different characteristics of each dataset (e. g. , different seizure types, lack of PNES or VVS examples or single channel data), the achieved epileptic recognition accuracy of the LI fusion schemes outperforms the performance reported in the literature. In particular, the achieved accuracy in  [16]  is 86%, lower to the accuracy of both late-integration fusion schemes in our methodology.
The classification performance was further improved by feature selection using a subset of 2-best features resulting to 92% accuracy for the best scheme (LI with global model). In a further step, we performed dimensionality reduction through PCA. Classification using only a few eigenvectors so as a high percentage of variance is retained (99,99%) was performed for each scheme. PCA helped the proposed LI scheme with global model reach the overall highest accuracy of our work (97% accuracy for a 100% sensitivity and 91% specificity). Although the dimensionality of the feature vector was examined in this study, the size of the dataset is still being one more parameter that should be considered when comparing the three fusion schemes. Under this scope we aim to evaluate our framework on datasets with different sizes and study the behavior of each scheme as function of the number of samples available in the training set.
Mporas from Multidimensional Data Analysis and Knowledge Management Laboratory, Dept. of Computer Engineering and Informatics, University of Patras for his help with data preprocessing, Dr Vasiliki Tsirka from, Division of Neuroscience at the Institute of Psychiatry, Psychology & Neuroscience, King's College London for contributing to the data annotation, Prof Mark Richardson from, Division of Neuroscience at the Institute of Psychiatry, Psychology & Neuroscience, King's College London and Konstantinos Deltouzos from Multidimensional Data Analysis and Knowledge Management Laboratory for valuable discussions. This study was partially funded by the EC under the FP7/2007-2013 with grant ARMOR, Agreement Number 287720. This research has been also co-financed by the European Union (European Social Fund -ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the NSRF -Research Funding Program: Thales.
Conclusion: Vitamin K deficiency, as assessed by high dp-ucMGP levels, is profound in hemodialysis patients from the Eastern Mediterranean region and it is significantly correlated with vascular calcifications. Daily 360 μg of menaquinone-7, given for 4 weeks, effectively reduces dp-ucMGP in this population. Future studies are needed to assess the changes in vascular calcifications in hemodialysis patients treated with vitamin K 2 over a longer follow-up period. Trial registration: The clinical trial was registered on clinicaltrials. gov (Identification number NCT02876354, on August 11, 2016).
Trial design, participants and data collection This is a prospective, pre-post intervention clinical trial. All patients in our center older than 18 years on chronic hemodialysis for more than 1 month were included. Patients who refused to sign the consent form and those who were on vitamin K antagonists (VKA) and could not stop it (those with heart valve replacements) were excluded. The total trial duration was 4 weeks. Demographics, comorbidities, medications and laboratory data were collected from the patients' medical records.
Acknowledgements We want to thank  Dr. Leon Schurgers  for his valuable scientific advices and support. We would like to thank also  Omicron, Lebanon  for providing the treatment and all the nursing team of the dialysis unit at  Saint-Georges Hospital  and  Dr. Ziad Maalouf  the head of the  BMP laboratory department  where the dp-ucMGP levels were measured. We are grateful to all patients who participated in this study.
Once purified from the original colony, the strain was identified based on its 16S rRNA gene sequence (GenBank accession number DQ512786). Pseudomonas graminis PDD-13b-3 has the ability to develop at low temperature, degrade some organic compounds present in clouds  (6) , and produce siderophores to satisfy their iron requirements  (7) ; it thus potentially interferes with cloud chemical reactivity. This strain was found to be ice-nucleation negative  (8) , but it produces biosurfactants known for facilitating spread on surfaces, and perhaps also participating in cell aerosolization and cloud formation  (9). Pseudomonas graminis PDD-13b-3 appears thus to be a model of cloud water microorganisms. To further understand the specificities of Pseudomonas graminis PDD-13b-3, its ability to survive in cloud water, and the implications of its presence in clouds, its whole genome was sequenced and is reported here.
nmpdr. org). It contains 61 RNAs and 5,177 proteincoding genes, of which 52% were assigned to a total of 527 SEED subsystems. Among these SEED subsystems, 98 were affiliated with oxidative stress response (encoding NADPH:quinone oxidoreductase, glutathione synthetase, peroxidase, etc. ) and 85 with DNA repair processes. Eleven protein-coding genes were related to iron acquisition and metabolism, encoding iron siderophore (pyoverdine) and related sensor and receptor systems. Interestingly, 8 protein-coding genes were associated with carbon starvation. All these could have contributed to Pseudomonas graminis PDD-13b-3 survival in clouds. Accession number(s). This whole-genome shotgun project has been deposited in the GenBank database under the accession number MTSB00000000.
Challenge 5: Maintain the aesthetic appeal of the icons Besides communicating the meaning of the commands involved in a software, toolbar icons contribute to the overall aesthetic of the interface, which is a critical factor of user experience  [23]. Aesthetic appeal is related to many criteria and is dependent on users personal perception: two users might have different opinions on how to improve the design of an icon  [23]. The familiarity and the complexity of the icon can easily impact the aesthetic appeal of the icon  [28]. While the aesthetics decisions related to the visual aspect of the pictorial representation of the command are left to the designer, IconHK sets out to be as undestructive as possible so as to preserve as high aesthetic appeal as the original visuals.
Results All three designers felt more comfortable using a vector graphics software or paper+pencil over animation software or programming. Designers interrupted the session (after 3h, 2h, and 4h respectively for D1, D2, and D3) before completing all three iconsets, albeit no time constraint was imposed. We discuss here the key insights of our study: Design process. It was interesting to observe how designers spontaneously made radical decisions regarding good icon and shortcut design practices. All of them primarily focused on consistency between icons, as they generally feel that a consistent iconset is more "user friendly than an iconset that better communicate the information to the user," a mindset that contradicts IconHK's essence. How they valued consistency had an impact on the choice of the strategies: they believed that mixing the embedding strategies in the same iconset could be confusing to the user because the icons would not have the "same identity.
1% formic acid) to 35% B (100% acetonitrile, 0. 1% formic acid) in 98 min. Peptides were analyzed in the orbitrap in full ion scan mode at a resolution of 60000 (at m/z 400) and with a mass range of m/z 350-1550. Fragments were obtained with a Higher-energy Collisional Dissociation (HCD) activation with a collisional energy of 30%, and a quadrupole isolation width of 1. 6 Da. MS/MS data were acquired in the linear ion trap in top-speed mode, with a dynamic exclusion of 50 s and a repeat duration of 60 s. The maximum ion accumulation times were set to 250 ms for MS acquisition and 60 ms for MS/MS acquisition in parallelization mode. MS/MS data were processed with Proteome Discoverer 1. 4 software (Thermo Fisher scientific, San Jose, CA) coupled to an in house Mascot search server (Matrix Science, Boston, MA; version 2.
5. 1). The mass tolerance was set to 7 ppm for precursor ions and 0. 5 Dalton for fragments. The following modifications were used in variable modifications: oxidation (M), phosphorylations (STY), acetylations (K, N-term), deamidations (N, Q), methylations (K), ubiquitinylation (GG and LRGG motifs on K amino acids). The maximum number of missed cleavages by trypsin was limited to 2. MS/MS data were searched against SwissProt databases with the Schizosaccharomyces pombe taxonomy. False Discovery Rate (FDR) for peptides was calculated using the Percolator algorithm and peptides were considered identified under the 1% FDR threshold.
7 (Sigma, #P1944) and precipitated with ethanol. RNA samples were treated with DNase (Ambion, #AM1906) prior to RT-qPCR analyses as mentioned above. Measurements were statistically compared using two-tailed t-tests with the following p-value cut-offs for significance: 5E-2>*>1E-2; 1E-2>**>1E-5; ***<1E-5. Transcriptome analyses by RNA-sequencing cDNA libraries were generated according to standard Illumina protocols. The RNA sequences reported in this paper have been deposited in the NCBI Gene Expression Omnibus with the accession number GSE72327. Reads were trimmed with cutadapt and mapped to the ASM294v2. 23 S. pombe genome using bowtie2. Read counts for every annotated transcript were calculated using HT-seq count and the ASM294v2. 23 genome annotation. Differential expression was computed using the R bioconductor package DESeq2.
Microscopy Exponentially growing cells cultured in minimal medium (EMM0. 5X) were imaged at room temperature with a motorized Olympus BX-61 fluorescence microscope equipped with an Olympus PlanApo 100 Â oil immersion objective (1. 40 NA), Nomarski optics, a QiClick cooled monochrome camera (QImaging, Surrey, BC, Canada) and the MetaVue acquisition software (Molecular Devices; Sunnyvale, CA, USA). GFP-tagged proteins were visualized using a GFP filter set (41020 from Chroma Technology, Bellows Falls, VT; excitation HQ480/20x, dichroic Q505LP, emission HQ535/50 m). Images were processed in ImageJ (NIH). (UniversiteParis-Saclay). This work was supported by the Fondation  Bettencourt-Schueller (prix Coup d'Elan 2009)  to DL and by the Fondation ARC pour la recherche sur le cancer (Projet Fondation ARC 1782) and the Agence Nationale de la Recherche (ANR-16-CE12-0031-01) to MR.
Acknowledgements We are grateful to  Sigurd Braun ,  Marc Bu ¨hler ,  Tim Humphrey ,  Hiten Madhani ,  Danesh Moazed  and AndreVerdel for generous gift of strains and plasmids. We thank  Antonin Morillon ,  Benoit Palancade  and  Tommaso Villa  for critical reading of the manuscript. This work has benefited from the facilities and expertise of the high-throughput sequencing platform of  IMAGIF (Centre de Recherche de Gif  -www. imagif. cnrs. fr)and the structural and functional proteomic/mass spectrometry facility from the  Institut Jacques Monod. FS was supported by PhD fellowships from the  French Ministry of Research (UniversiteParis-Saclay)  and the  Fondation ARC pour la recherche sur le cancer  ( DOC20160603784 ). TC was supported by a PhD fellowship from the  French Ministry of Research.
I. INTRODUCTION Geographical scaling has been at the core of a wealth of studies of human mobility. On one hand, physical distances between connected individuals or between related places have repeatedly been shown to hardly obey any distinctive scale, let alone exhibit distinct phases. Distance frequencies observed in large geotagged datasets of human behaviour usually follow strongly heterogeneous distributions spanning several orders of magnitude, be it for links based on cell phone movements  14, 17  and calls  9, 18, 31  , social media "checkins"  10, 22  or postings  4  , commutes  20, 29  or taxi rides  21  , or circulation of artifacts  8. On the other hand, this type of data has more recently been used to uncover geographically consistent areas based on clusters of places, movements or interactions  3, 7, 11, 13, 19, 22, 27, 31, 34, 35  where, in essence, the relevant literature generally proceeds on the assumption that all empirical measurements, irrespective of their diverse spatial scales, should be taken into account to form a single global picture.
II. EMPIRICAL APPROACH We obtained datasets of human movement in a variety of geographical regions from public data extracted from Instagram over a period of 16 months (See Materials and Methods section for a complete and formal description of the techniques and algorithms discussed here). Modern smartphones contain geolocation technology that can be employed to geotag photos, and many users accept this setting. Instagram associates photos with the identifier of the users who took them, and it also timestamps them. The global adoption of Instagram in the last few years make it a considerable trove of geosocial data for a nascent literature. Regarding mobility in particular, several recent works demonstrated that reliable mobility data could be extracted from photo-posting and check-in platforms  4, 10, 11, 22  , while Instagram appears to be both.
The Benelux map enriches the previous insight on Belgium by providing a broader picture on potential cross-national interfaces -an achievement not possible with country-specific datasets traditionally used in the literature -here, the highest scale exhibits a mix of expected international borders (for instance between Belgium and the Netherlands) and fuzzy cross-national spaces (such as the wide commuting area surrounding Luxembourg, or the narrow strips adjacent to the French-Belgian border, e. g. around Lille), while leaving room for cross-border low-scale patterns. Paris features both the traditional east-west sociological partition of the city, while exhibiting more specific activity neighbourhoods at the lower level (Quartier Latin, Belleville, the governmental area).