dataesr/scientific-paragraphs-categorization huggingface dataset:
The tests were performed according the EN 14034 series and the operating instructions of the 20 L-sphere  [44]. In order to assess the course of explosion behaviour of metal powders and in addition to the previous experimental data, available literature data for microsized and nanosized metal powders were gathered in a comprehensive database. Results are illustrated graphically for 5 metallic powders, namely aluminium (Figures  1  and 2 ), magnesium (Figures  3  and 4 ), titanium (Figures  5  and 6 ), iron (Figures  7  and 8 ) and zinc (Figures  9  and 10 ). It should be stressed that the solid (or dotted) lines have been added to illustrate a tendency and do not correspond to a model or a curve fit. In some figures, an important dispersion of the experimental data is noticed, both for low and high specific surface areas.
It should be kept in mind that this parameter has been determined either by BET measurements or by calculations based on mass median diameter and on the assumption of unimodal particle size distribution. Moreover, the specific surface area is not the only relevant parameter to consider when determining the explosion severity of a dust. Finally, the data collected were obtained under the same experimental conditions, following the same procedure. As well known, variations of the ignition energy, the ignition delay time (turbulence) or the explosion vessel shape can significantly impact the explosion severity. A specific pattern related to the evolution of explosivity (i. e. maximum explosion rate, maximum rate of pressure rise) is observed for the studied metallic materials. These figures show that the explosion severity of nanopowders is not systematically higher than that of microsized dusts and, notably due to agglomeration, tends to decrease with decreasing the particle size below a specific diameter.
Application of Huang's model To go beyond the simplistic model of Cassel and get a confirmation of our assumptions, i. e. a flame propagation driven by combustion in the 20 L explosion sphere, the model developed by Huang et al. [88]  has been considered by implementing all the available physico-chemical data on aluminium. This model consists in solving an algebraic equation depending on the physico-chemical properties of the particles as well as on the laminar flame velocity. As before, the physico-chemical properties are calculated at an average combustion temperature and the combustion time at ignition temperature Tign. The modelling results were compared to experimental available ones, i. e. data gained from direct measurements of flame velocity performed either with a "Bunsen" apparatus  [67, 71, 85] , a propagation tube  [89]  or the standard explosion sphere, as it was the case in this current work  [6, 8].
Acknowledgements This work was supported financially by the  French Ministry of Environment, Ecology and Durable Development , the  German Federal Ministry of Economic Affairs and Energy  ( TNS-Project  contract  N°03FS13035 ), the  European Commission   Seventh Framework Program  Project  FP7-MARINA  (Grant  N°263215  -www. marina. eu),and the  European Commission  Mandate  M461  for standardization.
All analyses were performed using the full-analysis set (FAS, all randomized transplanted patients who received ³1 dose of study drug). Statistical analyses were carried out using Statistical Analytical System (SAS ® , SAS Institute Inc. ) Version 9. 1. 3 or higher. Patients with missing baseline data for stratification factors were omitted from the analyses. Although the initial study design was not powered for these post-hoc subgroup analyses, a P value <0. 05 was considered significant for all comparisons.
Study Subjects The EUROCONDOR [NCT01726075] was a European multicenter, 96-week prospective, interventional, phase II to III, randomized controlled clinical trial that aimed to evaluate the effect of topical neuroprotection to arrest or prevent early retinal neurodegeneration in DR. 11  In a study including 11 European centers, a total of 449 patients were recruited and randomized 1:1:1 to topical treatment twice daily (BID) with placebo, brimonidine tartrate 0. 2%, or somatostatin 0. 1%. Criteria of inclusion were: type 2 diabetes with no, minimal, or mild DR (Early Treatment Diabetic Retinopathy Study [ETDRS] levels 10, 20, or 35, respectively),  17  duration of type 2 diabetes for at least 5 years, and age between 45 and 75 years. Exclusion criteria included previous retinal photocoagulation, retinal degenerative diseases (i.
e. , glaucoma), and refractive error or 65 diopters or more, hazy ocular media, inadequate pupil dilation, renal failure (creatinine >124 lm/L) or HbA1c >10% (86 mmol/mol) in the previous 6 months. For each patient, one eye was identified as the study eye by a central reading center (Coimbra Ophthalmology Reading Centre, Coimbra, Portugal), which also provided grading of the level of DR at baseline and follow-up. The study was approved and funded by the European Commission Seventh Framework Program (Grant Agreement No. FP7-278040). At all centers, the study was conducted in accordance with the tenets of the Declaration of Helsinki with approvals of the local scientific ethnical committees and written informed consent from all patients.
Retinal Vascular Caliber Analysis Mydriatic cameras (TRC-50IA, -50IX, -50EX, -50DX, -50DX Type IA, or NW6S; Topcon Corp. , Tokyo, Japan) or a fundus camera (FF450 PLUS IR; Carl Zeiss Meditec, Jena, Germany) were used to capture 308 to 358 modified ETDRS-field 1 images including the optic disc of the study eye. These were subsequently used for retinal vascular caliber measurements. 18 Images were analyzed by IVAN (Department of Ophthalmology and Visual Science, University of Wisconsin, Madison, WI, USA), which is a semiautomatic software program that has previously been validated. 19 he optic disc is automatically detected by the software, and vessel calibers are traced in a zone of 0. 5 to 1. 0 discdiameters from the optic disc margin. After manual adjustment by the grader, retinal vascular calibers are summarized into the central retinal arteriolar and venular equivalent (CRAE and CRVE) according to the ''Big 6-formula'' that includes the six largest arterioles and venules.
Acknowledgments Supported by the  European Union 's  Seventh Framework Programme  for research, technological development and demonstration under Grant Agreement No. 278040. U. Frydkjaer-Olsen  was supported by  Fight for Sight Denmark, The Region of Southern Denmark , and  University of Southern Denmark. Disclosure:  J. Grauslund , None;  U. Frydkjaer-Olsen , None;  T. Peto , None;  J. Fernández-Carneado ,  BCN Peptides (E) ;  B. Ponsati ,  BCN Peptides (E) ;  C. Hernández , None;  J. Cunha-Vaz , None;  R. Sim  ó, None.
This study investigates combining the property of human vision system and a 2-phase data hiding strategy to improve the visual quality of data-embedded compressed images. The visual Internet of Things (IoT) is indispensable in smart cities, where different sources of visual data are collected for more efficient management. With the transmission through the public network, security issue becomes critical. Moreover, for the sake of increasing transmission efficiency, image compression is widely used. In order to respond to both needs, we present a novel data hiding scheme for image compression with Absolute Moment Block Truncation Coding (AMBTC). Embedding secure data in digital images has broad security uses, e. g. , image authentication, prevention of forgery attacks, and intellectual property protection.
The proposed method embeds data into an AMBTC block by two phases. In the intra-block embedding phase, a hidden function is proposed, where the five AMBTC parameters are extracted and manipulated to embed the secret data. In the inter-block embedding phase, the relevance of high mean and low mean values between adjacent blocks are exploited to embed additional secret data in a reversible way. Between these two embedding phases, a halftoning scheme called direct binary search is integrated to efficiently improve the image quality without changing the fixed parameters. The modulo operator is used for data extraction. The advantages of this study contain two aspects. First, data hiding is an essential area of research for increasing the IoT security. Second, hiding in compressed images instead of original images can improve the network transmission efficiency.
Image data hiding is typically based on some specific image compression format  [12] [13] [14] [15] [16]. When the image is compressed, it requires less memory for storage and is more efficient for transmission via the Internet. Image compression formats can be divided into lossy image compression and lossless image compression. Although lossy compression cannot recover the original image, it significantly reduces the image size, i. e. , the compression rate performance of lossy compression is better than that of lossless compression. In this study, we use a lossy image compression method called absolute moment block truncation coding (AMBTC), to effectively compress the image. Using the image data hiding techniques, we can embed secret data into an image to protect the owner's intellectual property and prevent abuse or tampering.
Image data hiding is typically based on some specific image compression format  [12] [13] [14] [15] [16]. When the image is compressed, it requires less memory for storage and is more efficient for transmission via the Internet. Image compression formats can be divided into lossy image compression and lossless image compression. Although lossy compression cannot recover the original image, it significantly reduces the image size, i. e. , the compression rate performance of lossy compression is better than that of lossless compression. In this study, we use a lossy image compression method called absolute moment block truncation coding (AMBTC), to effectively compress the image. The advantage of the AMBTC compression technique is that it requires quite low computation power and can still achieve an acceptable image quality.
Therefore, it is suitable for low-energy devices. Recently, several researchers have investigated the AMBTC-based data hiding methods. Ou and Sun  [17]  proposed a steganography method that classifies the AMBTC blocks into smooth or complex blocks. In  [17] , two embedding schemes are designed according to the block type, which helps the authors to exploit the different block properties more efficiently. Tang et al. [18]  proposed an adaptive image steganography method that uses the interpolation technique to improve the hiding performance. Lin et al. [19]  proposed an image authentication method that also divides the AMBTC blocks into smooth or complex blocks. In smooth blocks, the authentication code is embedded into the bitmap, whereas in complex blocks, the authentication code is embedded to adjust the quantization levels using a reference table.
Huang et al. [20]  proposed a hybrid secret hiding scheme for data hiding in AMBTC images, in which, similar to  [17]  and  [19] , two types of blocks are classified. Then, data embedding in the complex blocks exploits the difference between high and low mean values of a block; therefore, it achieves a higher embedding capacity than the previous methods. Al-Salhi and Lu  [21]  presented an image concealment scheme that uses PVD techniques. Furthermore, the human visual system and adaptive neural networks are integrated to improve the image quality. Hong et al. [22]  proposed an AMBTC-based data hiding method that uses a suppress threshold mechanism and a perturbation technique to minimize the block distortion in the stego image. However, image quality image is inevitably degraded or a few image details are lost after compression by AMBTC and the data hiding procedure.
Intra-Block Embedding Phase This study presents a 2-phase (intra-block and inter-block) data hiding strategy by manipulating AMBTC parameters. In the intra-block embedding phase, the hidden data are embedded into an AMBTC block by proper modification of the set containing five AMBTC parameters:   , , , , HM LM NH NL BS   , (4) where HM, LM, NH, NL, and BS indicate, respectively, high mean, low mean, number of high-mean bits, number of low-mean bits, and AMBTC block size. The hidden function is defined as: ( ) ( 1) ( 2) ( 3) ( 4) ( 5) H HM LM NH NL BS           . (5) The secret bits to be embedded are converted to their decimal representation S. For example,.
Intra-Block Embedding Phase This study presents a 2-phase (intra-block and inter-block) data hiding strategy by manipulating AMBTC parameters. In the intra-block embedding phase, the hidden data are embedded into an AMBTC block by proper modification of the set containing five AMBTC parameters: θ = {HM, LM, NH, NL, BS}, (4) where HM, LM, NH, NL, and BS indicate, respectively, high mean, low mean, number of high-mean bits, number of low-mean bits, and AMBTC block size. The hidden function is defined as: H(θ) = (HM × 1) + (LM × 2) + (NH × 3) + (NL × 4) + (BS × 5). (5) The secret bits to be embedded are converted to their decimal representation S. For example, S = (11010) 2 = 26 in the case of 5-bit secret data. The goal of intra-block embedding is to adjust the parameters in θ so that S is equal to the result obtained from the modulo operation: S = mod(H, 2 n ) ( 6 ) where n is the size of the secret bits embedded in a hidden function.
Experimental Results and Discussions For evaluation, the performance of the proposed method is compared with the recently published methods in  [17]  (2015),  [20]  (2017), and  [22]  (2017). Because medical images are essential sources of visual data in smart cities (for example, a smart home-based health care system which needs to transmit mass medical images for telemedicine), eight 400 × 400 test images are collected from the public database  [25]  (Figure  6 ). sources of visual data in smart cities (for example, a smart home-based health care system which needs to transmit mass medical images for telemedicine), eight 400 × 400 test images are collected from the public database  [25]  (Figure  6 ). Moreover, for the methods in  [17] ,  [20] , and  [22] , blocks are classified as smooth and complex blocks.
The MSSIM value can be expressed as: 1 MSSIM SSIM( , ) M j j j g h   . ( 22 ) where M is the number of SSIM local windows (set as 3 in this paper); j g and j h represent the image block within the j-th window, from the input grayscale image and the resulting stego AMBTC image, respectively. Table  3  shows the overall comparison of the four methods as the threshold value (for distinguishing smooth and complex blocks) is equal to 2. As shown in Table  3 , because Moreover, for the methods in  [17, 20, 22] , blocks are classified as smooth and complex blocks. Similarly, in our comparison, the concept in  [17]  is adopted to embed data into smooth blocks, and the proposed method is used to embed data into complex blocks. In addition to comparing the payload (i. e. , data capacity in units of bits), this work adopts two image quality measures to fairly evaluate the performance of each method.
Successive up-regulation of HIF-1a at different stages of carcinogenesis To investigate what role HIF-1a plays at different stages of skin carcinogenesis, data mining analyses were performed on the two following independent transcriptomic databases: GSE2503  (Nindl et al. , 2006) , in which human skin specimens were analyzed and compared, including six healthy, four AK, and five SCC samples, and GSE45216  (Lambert et al. , 2014) , in which 30 SCC and 16 AK human samples were compared. Using gene ontology annotation, we found that the most significantly up-regulated biological pathway in SCC was the response to hypoxia (Figure  5a ). We then performed gene set enrichment analysis, which considers groups of genes linked together in functional pathways rather than single transcripts. We used the Winter_Hypoxia_Up (M5466)  (Winter et al.
, 2007)  enrichment data set, which includes 126 genes differentially regulated under hypoxia, and superimposed it on the GSE2503 and GSE45216 data sets (Figure  5b ). In other  words, we tested whether the set of genes whose activities are linked to hypoxia are enriched in SCC relative to either AK or healthy skin. When using GSE2503, we found that genes involved in the response to hypoxia were significantly enriched in both AK and SCC samples compared with healthy skin, and there was still a stronger enrichment in SCC than in AK (P < 0. 001). Likewise, gene set enrichment analysis of GSE45216 showed greater enrichment of genes involved in hypoxia in SCC than in AK (P < 0. 01). In the Nindl cohort, Hif-1a mRNA expression levels were markedly elevated in SCC versus either AK or healthy skin (Figure  5c ).
Duplicate experiments were normalized with NormalizeIt software  (Millau et al. , 2008)  and corrected with the fluorescence intensity of unmodified control plasmids. Finally, the total fluorescence obtained for the repair of CPDs was calculated by averaging the values of the different dilutions. Cellular O 2 /CO 2 exchange A Seahorse XF24 Extracellular Flux Analyzer (Seahorse Bioscience, North Billerica, MA) was used to analyze the bioenergetic function of skin samples, as already explained  (Hosseini et al. , 2018). Results were normalized with weight of skin samples for potential differences in skin size. Briefly, slices were put on nylon inserts and then placed individually face down into 20 wells of 24-well XF Islet Capture Microplates (Seahorse Bioscience) that contained 500 ml of assay medium.
Measurement of intracellular ROS The intracellular production of ROS was assessed using a CellROX Deep Red Reagent according to the manufacturer's instructions (Invitrogen/Life Technologies). Briefly, 5 mmol/L CellROX Deep Red Reagent were added to cells isolated from mice and incubated for 15 minutes at 37 C in the dark. After two washes with phosphate-buffered saline, the cells were immediately analyzed by flow cytometry. Ten thousand individual data points were collected for each sample.
Figure5. Increase in HIF-1a expression during skin carcinogenesis. (a) Enrichment analyses were done on GSE2503 (Nindl et al. , 2006)  and GSE45216 (Lambert et al. , 2014)  transcriptomic databases to evaluate the up-regulation of biological processes in SCC versus healthy skin and/or AK. (b) Winter_Hypoxia_Up (Winter et al. , 2007)  gene set taken from the Gene Ontology database (gene set enrichment analysis M5466) was used to test enrichment of the genes involved in response to hypoxia in SCC versus AK and/or healthy skin by using the GSE2503 and GSE45216 transcriptomic databases. (c, d) HIF-1a mRNA expression in healthy skin, AK, and SCC was evaluated by (c) Nindl et al. (2006)  and (d) Lambert et al. (2014) transcriptomic data bases (GSE2503 and GSE45216). (e) HIF-1a expression was assessed in human skin specimens at different stages of tumorigenesis.
ACKNOWLEDGMENTS The authors acknowledge the patient support group " Les Enfants de La Lune. "They wish to thank  P. Costet  ( University of Bordeaux ) for his valuable expertise and  Vanessa Bergeron  and  Doriane Bortolotto  for technical assistance. HRR gratefully acknowledges support from the  Institut National du Cancer, INCa-Canceropole GSO  (grant no. INCA_6654 ),  SocieteFrancaise de Dermatologie , and  Societede Recherche Dermatologique.
Lymphoid hyperplasia with signs of typhlitis was observed in the caeca mucosa. These lesions varied greatly depending on the section examined and were not more frequent in one group than in another. Characterization of intestinal morphometry of duodenum, jejunum, and ileum revealed no significant differences in the size of the villus and crypts in the duodenum and ileum among groups whereas a small increase in crypt depth of the jejunum was observed in broilers fed the diet containing FUS (Table  3 ). Moreover, no significant difference in the surface area and the villus to crypt ratio of the duodenum and ileum was found among groups (data not shown). By contrast, in the jejunum, the surface area of the crypt increased in broilers fed FUS whereas the villus to crypt ratio decreased and the surface area of the villus was not affected (Table  3 ).
1  and Fig. S2 , Supplemental Digital Content 1, http://links. lww. com/HS/A25). ] [12]  We next investigated which genes were differentially expressed between KMT2A-PTD AML and all other AMLs, in particular, AML with t(11q23), using our previously published gene expression profile (GEP) dataset (n = 513 AML). 13 Interestingly, multiple homeobox-related gene family members were consistently overexpressed in KMT2A-PTD AML. The top-35 differentially expressed genes included HOX-and TALE-related genes, such as HOXB5, HOXB6, HOXB7, HOXB8, HOXB9, and NKX2. 3, whereas KMT2A itself appeared to be the most consistently overexpressed gene (Table  S2 , Supplemental Digital Content 3, http://links. lww. com/HS/A27). Since mutations in NPM1 are also associated with dysregulation of HOX gene expression, we next used an association model to see if those differentially expressed HOX genes were also dysregulated in NPM1 mutant AML.
Acknowledgments We thank all the participating centers of the  Dutch-Belgian Cooperative Trial Group for Hematology-Oncology (HOVON)  and  Swiss Group for Clinical Cancer Research (SAKK) , where the clinical trials that formed the basis for this study were conducted;  H. Berna Beverloo  for performing cytogenetic analyses,  Eric Bindels  for performing next-generation sequencing,  Remco Hoogenboezem  for assisting with bioinformatics.
14, 15 This behavior results in a comparatively flat learning curve and may well contribute to the occurrence of some of the often devastating periprocedural complications. 16 It is, therefore, desirable to facilitate and optimize device sizing and device positioning through preimplantation simulation. Computer-based-simulation modeling tools such as the Sim&Size software (Sim&Cure; Grabels, France) provide the opportunity to simulate and, hence, to anticipate PED behavior of variable dimensions easily and within seconds. In short, this novel technology aims to standardize the PED-sizing process and ultimately promises to increase the neurointerventionalists' ability to confidently select optimal PED dimensions before implantation. In this multicenter cohort study of 74 patients who underwent aneurysm treatment with PEDs, we compared the dimensions of devices selected by neurointerventionalists with considerable PED experience based on conventional, manual 2D measurements obtained from rotational angiography with the computed optimal PED dimensions determined by Sim&Size experts, who were blinded to the neurointerventionalists' choice.
Study Design The Sim&Size software became available in France and Switzerland for use in routine clinical practice at the end of 2016. For cases performed before the software had become available (all patients from center A), the presumed optimal device dimensions were manually determined on the basis of 2D measurements made on rotational angiography acquired before PED implantation by 1 of 2 local neurointerventionalists with considerable PED experience. The manually determined presumed optimal device was then implanted. In these cases, the computed optimal PED dimensions were retrospectively determined by virtual simulation by a team of Sim&Size experts, which included software engineers and at least 1 local neurointerventionalist with considerable PED experience, all blinded to the operating neurointerventionalists' manual choice.
For cases performed after Sim&Size software had become available (all patients from center B), preimplantation virtual device simulation was routinely performed before implantation by a team of Sim&Size experts that included software engineers and at least 1 local neurointerventionalist with considerable PED experience. In these cases, the manually determined presumed optimal device dimensions were retrospectively determined on the basis of 2D measurements made on rotational angiography acquired before PED implantation by 1 of 2 local neurointerventionalists with considerable PED experience who was blinded to the results of virtual simulation.