dataesr/scientific-paragraphs-categorization huggingface dataset:
Digested peptides were analyzed using a capillary liquid chromatography system Ultima3000 (Dionex, USA) connected online to a mass spectrometer (LTQ-XL; Thermo Scientific, USA). Raw spectral data were processed using SEQUEST software to extract peak lists. Peak lists were analyzed using MASCOT against the Ciona protein database  63. As control experiments, we conducted the same analyses with mucus cords isolated from the dorsal lamina. We accepted results for envelope membranes when they are concentrated more than five time than in controls. Full-length transcripts that encode the most frequently identified three components Ci-MACPF1, VCBP-C, and Ci-GFM1 were isolated by RT-PCR and RACE, as described above. Primers for RT-PCR were designed from transcripts KH. C1. 45. v1. A. ND1-1, KH. C4.
16S rRNA gene analysis of tilapia gut microbes. O. mossambicus was fed with a chitin-free diet for a week, and the whole intestine was isolated as described above. The hepatic loop and the distal major coil were longitudinally cut open. Mucus that covers envelope membranes was removed with sterile filter papers and washed away with PBS. Envelope membranes were cut open, and luminal digesta was collected by suction and stored at -80 °C. There was no envelope membrane in the stomachs of O. mossambicus. Stomach digesta, aquarium water and the chitin-free food were also collected. Aliquots (20 μL) of thawed specimens were treated with NaOH, PCR-amplified, subcloned and sequenced, as for axenic PCR. Obtained sequences were used as queries for blastn searches in 16S ribosomal RNA sequence database at NCBI.
57 chitinase product. Purified envelope membranes of C. intestinalis Type A, B. floridae, E. atami and O. mossambicus were separately treated with recombinant hyperthermophilic chitinase PF-ChiA from Pyrococcus furiosus (Thermostable Enzyme Laboratory, Japan) following manufacturer's instructions. Molecular cloning of chordate chitin synthases. Total RNA was isolated from young adult specimens (1 month) of C. intestinalis Type A, reverse-transcribed and used for RT-PCR56. Primers were designed from a transcript KH. L22. 57. v1. B. ND1-1 (1481 bp) identified by tblastn searches in the ghost database57using invertebrate chitin synthases as queries. It was necessary to conduct rounds of rapid amplification of cDNA ends (RACE) (Marathon cDNA amplification kit, Clontech, USA) to obtain full-length transcripts (5487 bp) encoding Ci-CHS.
Data availability. DNA sequences of Ci-CHS, Ci-MACPF1, Ci-GFM1, and Om-CHS1 were deposited in DNA Data Bank of Japan with accession codes LC072663, LC072664, LC072665, and LC072666, respectively. DNA sequences of 16S rRNA gene amplicons were deposited with accession codes LC409535-LC410039 and LC410204-LC411764. Proteome data set, including raw data files, processed peak lists, and database search results, are deposited at jPOST with the Proteo-meXchange code, PXD010503. The data that support the finding of this study are available from the corresponding author upon reasonable request.
Primer sequences used in this study are provided in Supplementary Table3. B. floridae EST clones bfad030d07 and bflv038m04 were obtained from the cDNA database An aliquot (5 μL) was collected from each reaction at 0, 1, 2, 3 and 4 h after the onset of reaction and subjected to LC-MS analyses. For LC, we used an ACQUITY UPLC-I-class (Waters, USA) equipped with an ACQUITY UPLC BEH amide column and performed with a 5-min gradient from 80/20 to 25/75 MeCN/H 2 O with 0. 1% NH 4 OH at a flow rate of 0. 17 mL/min. For MS, we used a SYNAPT G2-S (Waters, USA) in ES+ ionization mode with capillary voltage at 2. 0 kV, cone voltage at 25 V, source temperature at 120 °C desolvation temperatures at 350 °C, a desolvation gas flow of 500 L/h, cone gas flows of 50 L/h, scan time of 0. 2 ms at a high resolution mode (35,000 full-width at half maximum) and a lock mass of Leu- enkephalin (556.
Background: Recent reports highlight malaria as a frequent diagnosis in migrants who originate from Eritrea. A descriptive analysis of GeoSentinel cases of malaria in Eritrean migrants was done together with a literature review to elucidate key attributes of malaria in this group with a focus on possible areas of acquisition of malaria and treatment challenges. Results: A total of 146 cases were identified from the GeoSentinel database from 1999 through September 2017, with a marked increase in 2014 and 2015. All patients originated from Eritrea and the main reporting GeoSentinel sites were in Norway, Switzerland, Sweden, Israel and Germany. The majority of patients (young adult males) were diagnosed with malaria following arrival in the host country. All patients had a possible exposure in Eritrea, but may have been exposed in documented transit countries including Ethiopia, Sudan and possibly Libya in detention centres.
Countries are responsible for determining whether an asylum-seeker is a refugee or not. Eritrea is considered to be one of the world's "fastest emptying nations" mainly due to forced army conscription that may last a lifetime. Eritrea ranks 5th in the top ten origins of persons applying for asylum in the European Union  [5]. The United Nations High Commissioner for Refugees (UNHCR) reported 474,296 Eritreans globally to be refugees and asylum-seekers  [5]. This constitutes approximately 12% of Eritrea's official 3. 6 million population estimate as of 2015. Using the dual approach of a GeoSentinel global database descriptive analysis and an in-depth literature review, this analysis describes malaria in Eritreans presenting at GeoSentinel sites and evaluates the complexity of presentation and treatment in this distinct group of migrants.
Methods GeoSentinel (http://www. geose ntine l. org) sites are clinics specializing in travel, migration and/or tropical medicine, that contribute clinician-based data on ill migrants and travellers to a global database. To be eligible for inclusion in the database, the patient must have crossed an international border in the 10 years prior to presentation and the diagnosis must be considered "travel-related" by the reporting GeoSentinel clinician  [6]. GeoSentinel's data collection protocol has been reviewed by the institutional review board officer at CDC's National Center for Emerging and Zoonotic Infectious Diseases and is classified as public health surveillance and not human subject research. When indicated by national regulations at individual GeoSentinel sites, additional ethical clearance has been obtained.
Only symptomatic Eritrean migrants with confirmed malaria diagnoses were included in this analysis. Clinical data captured included the presenting symptoms, malaria species identification, severity of infection and in-patient/out-patient status. 'Severe malaria' was defined according to World Health Organization (WHO) criteria  [7]. Demographic data were also collated: age, sex, country of birth, and country of residence/asylum, travel history (arrival date and transit routes when available). GeoSentinel sites use the best reference diagnostic tests available and screen for glucose-6-phosphate dehydrogenase (G6PD) deficiency; the malaria cases in this study were based on presence of malaria symptoms and confirmation by microscopy or PCR or RDT. In addition to the descriptive analysis of the GeoSentinel database, a literature review was done.
The databases PubMed, Embase and Scopus were searched using the word combinations "malaria", "migrant", "Eritrea". Articles in English, German, Italian and French were included. Relevant reports from public health agencies, ministries and malaria surveillance statistics were also screened. The time period for the database searches was January 1st 2010 to July 31st 2018. GeoSentinel Sites that contributed cases to this analysis, were queried regarding the availability of primaquine and G6PDH deficiency testing at their sites.
Results There were 146 cases identified from the GeoSentinel database from 1999 through September 15, 2017 (Fig. 1 ), with a marked increase in 2014 and 2015. There was a 66% hospitalization rate and 9 cases of severe malaria. No death was recorded. All patients originated from Eritrea and were diagnosed with malaria following their initial migration trip with the main reporting sites in Norway, Switzerland, Sweden, Israel and Germany (Table  1 ) in descending order of contribution. The majority of the patients were young adult males. The migration route was not documented for all patients (Table  2 ), but most of them were possibly also exposed in other transit countries, including notably Sudan 76% (41/54) and Ethiopia 57% (31/54). Additionally, 34 patients 63% (34/54) declared having transited Libya during their migration trip, 7 transit routes led through Egypt, one through Syria, one through Turkey and one through Uganda.
Since 2013, Eritrean asylum seekers have changed the profile of imported malaria cases in Europe with a shift towards P. vivax. In Germany, prior to 2013, 80% of all imported malaria cases, numbering 500-600 total cases annually were falciparum malaria cases, and vivax malaria was a minor contributor (approximately 7%)  [3]   [10]. In Sweden, a significant number of P. vivax cases in asylum-seekers from Eritrea led to the largest surge in imported malaria cases since computerized recording of malaria cases began in 1986  [4]. Because Sweden has accurate denominator data on asylum-seekers, the incidence rate of P. vivax in Eritreans was estimated at 19. 5 per 1000 asylum seekers. In those aged less than 18 years, the incidence rate was considerably higher and estimated at 38. 2 per 1000  [4].
Strengths and limitations This is a large descriptive analysis of malaria cases in Eritrean asylum-seekers. A major strength of the Geo-Sentinel database is the global linkage of clinician verified malaria clinical data with accurate demographics and detailed travel history including transit routes. The improved GeoSentinel data collection form for migrants captures data elements on the status of the migrant (refugee, asylum-seeker) and screening results. GeoSentinel analyses constitute a valuable approach to documenting epidemiological patterns in mobile populations such as migrants. This GeoSentinel study has the limitation that denominator data are unavailable and that only a subset of all malaria cases in Eritrean migrants were captured. Because GeoSentinel sites in Europe are often important reference hospitals, this may have led to a bias selecting the more severe malaria cases and cases treated elsewhere are missed.
Our corpus includes newspapers which employed several modalities of image production, including wood engraving as well as photo-process techniques, all of which present unique challenges to the interpreter. In this article, we describe the progress of our experiments and the methodological reflections they generate. Our article, like our early research, pursues exploratory data analysis rather than a set of hypotheses, as we attempted to determine just how computer vision and image processing techniques might be adapted for large-scale interpretation of historical materials. Ultimately, we propose an approach related to Lev Manovich's methods of sorting a digital image collection at various scales using low-level image features, as opposed to machine-learned attempts to identify image content.
16 r three titles result primarily from what data we could access-data that has also been shaped by the history of how British Library newspapers were digitized. 17 Newspaper pages were scanned from microfilm, most of it newly shot for the digitization process (including the Graphic and IPN). However, the Penny Illustrated Magazine was among the few titles scanned from legacy microfilm made in the 1950s, which resulted in low-quality digital images unsuited for our computational processes. Even with the higher quality scans of the Graphic and IPN, some pages are unevenly lit or poorly exposed, appearing far lighter or darker than the clarity of their printed versions. Seeking additional illustrated newspapers and potentially better quality images, we contacted the HathiTrust Research Center about access to their collections.
Unfortunately, their online PDFs introduce image noise, or aliasing due to under-sampling which makes them far less suitable for analysis. Access to the original scanned image files, many of them made by Google, is complicated by licensing and large file sizes. Our own collection is similarly restricted by the terms of Gale's license with NCSU Libraries, in that we cannot freely share the source data. In many ways, our project exemplifies the problems of access to historical content ostensibly in the public domain. But as our initial goals were methodological, simply figuring out what approach might even yield interesting results, we chose to make do with what we had in hopes these experiments suggest ways of approaching other collections. Our first task was to identify and extract distinct illustrations from the data set.
Gale's data for the collection comprise XML files with OCR text and metadata for each newspaper issue, along with high-resolution page facsimile images in JPG and TIFF formats. Page counts for each newspaper in our collection range into the tens of thousands; each page may contain several illustrations, a full page picture, or none at all. Gale's product does offer page zoning for articles and illustrations by pixel location, which it uses to segment and highlight different items browsed or found through the database's web interface. But we chose to identify and extract illustrations from page facsimile images using open-source code developed for OpenCV (https://github. com/acdha/image-mining/). The scanned newspaper page is first converted into a black and white image using a threshold. The Canny edge detector was applied to find a set of contours.
23 Johanna Drucker, "Humanities Approaches to Graphical Display, " Digital Humanities Quarterly suggest alternative ways of defining the study of illustrations. What does an image mean? As Maidment persuasively argues, historical illustrations cannot simply serve as evidence of things seen. Even though many illustrated newspapers insisted on the accuracy and fidelity of their images, these illustrations were thoroughly mediated from sketches to reworking on the block. Their content was often fabricated, sometimes based upon other prints or illustrations, sometimes envisioned from verbal testimonies or textual reports. 24 What we "see" in a newspaper illustration is less a historical record than a record of historical ways of seeing. As Maidment claims, the Victorian illustration "must be understood both as a naturalistic representational medium … and as a shorthand non-naturalistic visual code built out of long traditions.
"  25  In Graphesis, Johanna Drucker emphasizes how the very concept of the visual has its own histories. Visual epistemologies change with cultural circumstance, or the "conventions, habits of reading and thought, and graphical expressions whose properties translate into semantic value. " 26 It is not simply that we see with different eyes, but that we differently understand the very possibility of visual knowledge. Add to these complications the technological layer of the image's remediation into microfilm and then digital forms, rendered through a variety of compression and display processes, and approached in a new context of its computational tractability as data. What are we seeing at all? What exactly is our data evidence of? While the extent of these biases seem enormous, they can also effect a powerful shift in researchers' points of view, a "productive unease" that may reveal other interpretive angles.
" 31  These scholars propose several hypotheses which might be computationally testable, or at least provide launching points for further experiments. For instance, should facial recognition succeed, even its errors would be instructive, used to consider representational patterns in era in which phrenology and facial physiognomies were both explicitly and tacitly accepted as signs. To make learning-based face detection algorithms work on our dataset, or even to measure the performance of such algorithms, we would need a training set of illustrations with each face labeled by a bounding box. A similarly labeled data set would be needed for object detection in these images, which we also hoped to try. But labeled datasets with these levels of granularity do not currently exist, and we despaired at the magnitude of labor required to create, test, and refine them, given the limits of funding and our interests in exploring multiple approaches.
Seeking a workaround, we approached researchers involved with the Database of Mid-Victorian Illustration and the Illustration Archive, each of which "tags" images by hand according to a typology. Because of "the lack of a fixed bibliographic convention for describing illustration, " as Julia Thomas explains, these projects created their own vocabularies and, with the Illustration Archive, relied on crowdsourced tagging to describe visual content. 32 Those tags may not be consistently applied, nor do they label specific locations within the images, which limits their utility for identifying image features. These projects were designed for human users to apply categories and sort by them, rather than for machine analysis. We also considered trying some unsupervised approaches such as image segmentation and machine learning.
" Of course, deep learning algorithms must be trained on a tagged data set, "taught" to identify positive and negative examples. Again, we decided to pursue other approaches. Yet there are some promising developments in the field which suggest pathways for content-based image analysis using historical materials. For example, Giles Bergel and colleagues at the University of Oxford and the Bodleain Libraries developed an image recognition tool and semantic tagging for early modern broadsides and ballads. 33 Thomas Smits and Melvin Wevers working at the Dutch National Library have used a convolutional neural network to classify images from Dutch newspapers 1860-1940. 34 Neural Neighbors, a project of the Yale Digital Humanities Lab, also uses this technique to find pictorial tropes in the Beinecke Library's digital collection of historical photographs.
From Content to Image Features In spring 2016, we presented our initial work to our funder in a room full of computer scientists and data analysts. One person came up afterwards, fascinated and flummoxed by how these seemingly self-evident illustrations defied the power of image processing algorithms to reckon with them. As he asked, "Why can humans recognize this stuff and computers cannot?" The question gets to the very heart of computer vision research. But it also formulates the problem in a way which makes it impossible to answer. The question assumes that our visual processes can transpose onto computational processes, which, were that even possi- , where is the number of pixels with intensity below the threshold and is the total number of pixels in the image. While many programming languages might suffice for this work, Qian Ge used MATLAB to process all of the extracted images and generate sorted lists of images as well as distribution charts.
"  46  Photographic histories have a tendency to celebrate firsts in this manner, but halftone detection can also be used to identify larger batches and longer trends. For instance, we measured the relative numbers of illustrations the Graphic published using different reprographic techniques. Standard narratives in the history of print illustration suggest that wood engraving effectively dies out by the end of the nineteenth century. Our results show an increasing presence of halftone images in the Graphic starting in the 1880s and achieving equal levels with wood engravings by 1900 (figure  9 ). At least by 1900-when our data set ends-the Graphic continues to produce wood engravings and halftones in equal measure, though the trajectories are clear. The graph also lets us focus on the outliers like "firsts" and the peaks which turn out to be special issues, as well as confirm or add nuance to larger historical trends.
These portraits were collected by computing GIST features or overall vectors for our image collections and sorting by similarity. Figure  13. sample portrait images from The Graphic. The computer sees the shape, but when visualized this way, we see much more. By sorting and showing illustrations by computational means, we can also reveal the ordinary, what goes unseen for being always seen, sometimes arriving with the shock of its homogeneity. We can also notice what is missing, many women's and black and native faces for instance, because they are absent from the data or from the collections we study. The absence of evidence significantly affects the research horizon for computational cultural history. As Ben Fagan argues in "Chronicling White America, " analytics projects on digital newspaper collections may perpetuate the biases of the collection's own history.
We began our experiments by trying image processing and recognition methods we were already familiar with, attempting to test what techniques might succeed (or not) on historical illustrations. We started with face recognition, image segmentation, and object recognition, using "out-ofthe-box" and open software, such as the OpenCV face detection using Haar Cascades as well as Adam Geitgey's face recognition based on dlib (https://github. com/ageitgey/face_recognition). Initial results were poor: out of a sample of 229 images with faces we selected from the Graphic, the face recognition software returned rates of true positives at 0. 3144, false positives at 0. 0131, and false negatives at 0. 6856. The IPN scored even worse: out of a sample 328 images of faces, we got true positives at 0. 2927, false positives at 0.
ACKNOWLEDGEMENTS This work is supported by the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No  640891  ( DREAM  project). Experiments presented in this paper were carried out using the Grid'5000 experimental testbed, being developed under the  INRIA   ALADDIN development action  with support from  CNRS ,  RENATER  and several universities as well as other funding bodies (see https://www. grid5000. fr).
FSPCre-Pparb/d -/-mice exhibit a pro-fibrotic gene expression profile The above observations suggest that FSPCre-Pparb/d -/- mice exhibited certain localized SSc-like hallmarks, including excessive collagen deposition leading to thickening of the dermis and greater number of myofibroblasts. Previous studies also concluded that localized SSc involves autoimmune abnormalities with elevated levels of anti-nucleosome antibodies  31, 32. We detected higher levels of anti-nucleosome antibodies in 69% of our FSPCre-Pparb/d -/-mice, with a higher frequency in female mice than male mice (Fig. S2e ). To further strengthen our findings, we performed comparative microarray gene expression analysis of skin biopsies from SSc patients, other mouse models of SSc and FSPCre-Pparb/d -/-mice. An intrinsic SSc gene set comprising 995 genes was previously identified by Milano et al (GSE9285)  33.
We examined the expression of these genes in the tight skin (Tsk) 1 or 2 heterozygous mutant mouse model (GSE71999), the bleomycin-induced fibrosis mouse model (GSE71999), the sclerodermatous graft versus host disease (SGVHD) mouse model (GSE24410), and our FSPCre-Pparb/d -/-mice (Fig. S3 ). Unguided hierarchical clustering of samples revealed that the mouse models of SSc mainly represented the fibroproliferative subtypes of human SSc. Both fibroproliferative 1 and 2 subtypes of human SSc share a common biological program of proliferation  [33] [34] [35]. FSPCre-Pparb/d -/-mice samples branched off from the same node as fibroproliferative 2 subtype of human SSc samples, indicating that the gene expression profiles of the two sample groups are highly similar (Fig. S3 ). A subset of 113 genes involved in cell:cell signaling and interaction, connective tissue development and function, and inflammation was downregulated in fibroproliferative human SSc compared with normal human skin (Fig.