1,346 research outputs found
Size effects on dynamics of nanodroplets in binary head-on collisions
Head-on collision dynamics of 10, 50 and 100 nm droplets are investigated in vacuum by molecular dynamics, involving 35,858, 4,506,410 and 36,051,466 molecules, respectively. A variety of droplet collision dynamics are observed, such as coalescence, hole formation and shattering, as a function of the Weber number. It is found for the first time that the collision and reflexive separation can occur in the nanodroplet regime when the droplet diameter reaches 100 nm but not for 10 or 50 nm droplets. The size effect in droplet collisions is studied based on the analysis of stretching factors, energy dissipation and collision outcomes for droplets of different diameters. The kinetic energy dissipation due to the atomic interactions at nanoscales is identified to significantly influence the occurrence or otherwise of reflexive separation. Through quantitative analysis of the evolution of the internal structure of the 100 nm nanodroplets collision at the Weber number of 277, it is revealed for the first time that molecules from both parent nanodroplets have penetrated the full length of the merged nanodroplet in the direction of collision, due to a combination of molecular mixing and internal currents. Consequently, all three child nanodroplets have molecules from both parent nanodroplets, contrary to the perception gained from common imaging techniques. The results show that the dynamics, outcomes and mechanisms of nanodroplet collisions have both similarities and differences compared with their micro- and macro-counterparts
Multimodal Fake News Detection with Textual, Visual and Semantic Information
[EN] Recent years have seen a rapid growth in the number of fake
news that are posted online. Fake news detection is very challenging since they are usually created to contain a mixture of false and real information and images that have been manipulated that confuses the readers. In this paper, we propose a multimodal system with the aim to di erentiate between fake and real posts. Our system is based on a neural network and combines textual, visual and semantic information. The textual information is extracted from the content of the post, the visual one from the image that is associated with the post and the semantic refers to the similarity between the image and the text of the post. We conduct our experiments on three standard real world collections and we show the importance of those features on detecting fake news.Anastasia Giachanou is supported by the SNSF Early Postdoc Mobility grant under the project Early Fake News Detection on Social Media, Switzerland (P2TIP2 181441). Guobiao Zhang is funded by China Scholarship Council (CSC) from the Ministry of Education of P.R. China. The work of Paolo Rosso is partially funded by the Spanish MICINN under the research project MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE speech (PGC2018-096212-B-C31)Giachanou, A.; Zhang, G.; Rosso, P. (2020). Multimodal Fake News Detection with Textual, Visual and Semantic Information. Springer. 30-38. https://doi.org/10.1007/978-3-030-58323-1_3S3038Boididou, C., et al.: Verifying multimedia use at MediaEval 2015. In: MediaEval 2015 Workshop, pp. 235–237 (2015)Castillo, C., Mendoza, M., Poblete, B.: Information credibility on Twitter. In: WWW 2011, pp. 675–684 (2011)Chollet, F.: Xception: deep learning with depthwise separable convolutions. In: CVPR 2017, pp. 1251–1258 (2017)Davidson, T., Warmsley, D., Macy, M., Weber, I.: Automated hate speech detection and the problem of offensive language. In: ICWSM 2017 (2017)Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: CVPR 2009, pp. 248–255 (2009)Ghanem, B., Rosso, P., Rangel, F.: An emotional analysis of false information in social media and news articles. ACM Trans. Internet Technol. (TOIT) 20(2), 1–18 (2020)Giachanou, A., Gonzalo, J., Mele, I., Crestani, F.: Sentiment propagation for predicting reputation polarity. In: Jose, J.M., et al. (eds.) ECIR 2017. LNCS, vol. 10193, pp. 226–238. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-56608-5_18Giachanou, A., RÃssola, E.A., Ghanem, B., Crestani, F., Rosso, P.: The role of personality and linguistic patterns in discriminating between fake news spreaders and fact checkers. In: Métais, E., Meziane, F., Horacek, H., Cimiano, P. (eds.) NLDB 2020. LNCS, vol. 12089, pp. 181–192. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-51310-8_17Giachanou, A., Rosso, P., Crestani, F.: Leveraging emotional signals for credibility detection. In: SIGIR 2019, pp. 877–880 (2019)He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR 2016, pp. 770–778 (2016)Huang, D., Shan, C., Ardabilian, M., Wang, Y., Chen, L.: Local binary patterns and its application to facial image analysis: a survey. IEEE Trans. Syst. Man Cybern. Part C 41(6), 765–781 (2011)Khattar, D., Goud, J.S., Gupta, M., Varma, V.: MVAE: multimodal variational autoencoder for fake news detection. In: WWW 2019, pp. 2915–2921 (2019)Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002)Popat, K., Mukherjee, S., Yates, A., Weikum, G.: DeClarE: debunking fake news and false claims using evidence-aware deep learning. In: EMNLP 2018, pp. 22–32 (2018)Rashkin, H., Choi, E., Jang, J.Y., Volkova, S., Choi, Y.: Truth of varying shades: analyzing language in fake news and political fact-checking. In: EMNLP 2017, pp. 2931–2937 (2017)Shu, K., Wang, S., Liu, H.: Understanding user profiles on social media for fake news detection. In: MIPR 2018, pp. 430–435 (2018)Shu, K., Mahudeswaran, D., Wang, S., Lee, D., Liu, H.: FakeNewsNet: a data repository with news content, social context and spatialtemporal information for studying fake news on social media. arXiv:1809.01286 (2018)Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556 (2014)Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: CVPR 2016, pp. 2818–2826 (2016)Tausczik, Y.R., Pennebaker, J.W.: The psychological meaning of words: LIWC and computerized text analysis methods. J. Lang. Soc. Psychol. 29(1), 24–54 (2010)Vosoughi, S., Roy, D., Aral, S.: The spread of true and false news online. Science 359(6380), 1146–1151 (2018)Wang, Y., et al.: EANN: event adversarial neural networks for multi-modal fake news detection. In: KDD 2018, pp. 849–857 (2018)Zhao, Z., et al.: An image-text consistency driven multimodal sentiment analysis approach for social media. Inf. Process. Manag. 56(6), 102097 (2019)Zlatkova, D., Nakov, P., Koychev, I.: Fact-checking meets fauxtography: verifying claims about images. In: EMNLP-IJCNLP 2019, pp. 2099–2108 (2019
Repeatability of Corneal Elevation Maps in Keratoconus Patients Using the Tomography Matching Method
To assess repeatability of corneal tomography in successive measurements by Pentacam in keratoconus (KC) and normal eyes based on the Iterative Closest Point (ICP) algorithm. The study involved 143 keratoconic and 143 matched normal eyes. ICP algorithm was used to estimate six single and combined misalignment (CM) parameters, the root mean square (RMS) of the difference in elevation data pre (PreICP-RMS) and post (PosICP-RMS) tomography matching. Corneal keratometry, expressed in the form of M, J0 and J45 (power vector analysis parameters), was used to evaluate the effect of misalignment on corneal curvature measurements. The PreICP-RMS and PosICP-RMS were statistically higher (P < 0.01) in KC than normal eyes. CM increased significantly (p = 0.00), more in KC (16.76 ± 20.88 μm) than in normal eyes (5.43 ± 4.08 μm). PreICP-RMS, PosICP-RMS and CM were correlated with keratoconus grade (p < 0.05). Corneal astigmatism J0 was different (p = 0.01) for the second tomography measurements with misalignment consideration (−1.11 ± 2.35 D) or not (−1.18 ± 2.35 D), while M and J45 kept similar. KC corneas consistently show higher misalignments between successive tomography measurements and lower repeatability compared with healthy eyes. The influence of misalignment is evidently clearer in the estimation of astigmatism than spherical curvature. These higher errors appear correlated with KC progression
NRF2-driven miR-125B1 and miR-29B1 transcriptional regulation controls a novel anti-apoptotic miRNA regulatory network for AML survival
Transcription factor NRF2 is an important regulator of oxidative stress. It is involved in cancer progression, and has abnormal constitutive expression in acute myeloid leukaemia (AML). Posttranscriptional regulation by microRNAs (miRNAs) can affect the malignant phenotype of AML cells. In this study, we identified and characterised NRF2-regulated miRNAs in AML. An miRNA array identified miRNA expression level changes in response to NRF2 knockdown in AML cells. Further analysis of miRNAs concomitantly regulated by knockdown of the NRF2 inhibitor KEAP1 revealed the major candidate NRF2-mediated miRNAs in AML. We identified miR-125B to be upregulated and miR-29B to be downregulated by NRF2 in AML. Subsequent bioinformatic analysis identified putative NRF2 binding sites upstream of the miR-125B1 coding region and downstream of the mir-29B1 coding region. Chromatin immunoprecipitation analyses showed that NRF2 binds to these antioxidant response elements (AREs) located in the 5′ untranslated regions of miR-125B and miR-29B. Finally, primary AML samples transfected with anti-miR-125B antagomiR or miR-29B mimic showed increased cell death responsiveness either alone or co-treated with standard AML chemotherapy. In summary, we find that NRF2 regulation of miR-125B and miR-29B acts to promote leukaemic cell survival, and their manipulation enhances AML responsiveness towards cytotoxic chemotherapeutics
Origin Identification and Quantitative Analysis of Honeys by Nuclear Magnetic Resonance and Chemometric Techniques
The combination of H-1 NMR spectroscopy and multivariate statistical analysis has become a promising method for the discrimination of food origins. In this paper, this method has been successfully employed to analyze 70 Chinese honey samples from eight botanic origins, three geographical origins, and five production dates. Thirty-three components in honey samples were detected and identified from their H-1 NMR spectra, and 20 of them were accurately quantified by comparing their integral area with that of internal standards with relaxation time correction. Nontargeted principal component analysis (PCA) has been applied to distinguish the honeys from different botanical and geographical origins. The variations of components in the honeys, including saccharides and all kind of amino and organic carboxylic acids, confirmed their clustering according to their origins in PCA scores plots. Orthogonal partial least squares discriminant analysis (OPLS-DA) based on the NMR data for the different pairwise honey samples allows to identify the compositional variations contributed to geographical discrimination and storage time. Hence, NMR spectroscopy coupled with chemometric techniques offers an efficient tool for quality control of honey, and it could further serve to the classification, qualitative and quantitative control of other foods
Selective area epitaxy of ultra-high density InGaN quantum dots by diblock copolymer lithography
Highly uniform InGaN-based quantum dots (QDs) grown on a nanopatterned dielectric layer defined by self-assembled diblock copolymer were performed by metal-organic chemical vapor deposition. The cylindrical-shaped nanopatterns were created on SiNx layers deposited on a GaN template, which provided the nanopatterning for the epitaxy of ultra-high density QD with uniform size and distribution. Scanning electron microscopy and atomic force microscopy measurements were conducted to investigate the QDs morphology. The InGaN/GaN QDs with density up to 8 × 1010 cm-2 are realized, which represents ultra-high dot density for highly uniform and well-controlled, nitride-based QDs, with QD diameter of approximately 22-25 nm. The photoluminescence (PL) studies indicated the importance of NH3 annealing and GaN spacer layer growth for improving the PL intensity of the SiNx-treated GaN surface, to achieve high optical-quality QDs applicable for photonics devices
Emissions from mechanically-biologically treated waste landfills at field scale
Modern waste management tends towards greater sustainability in landfilling, with the implementation of strategies such as the pretreatment of solid waste. This work assesses the behaviour of rejects from a refining stage of mechanically-biologically treated municipal solid waste at the landfill. The main results of 18 months' monitoring of an experimental pilot cell with waste from a full-scale plant are presented. This first stages are expected to be the most problematic period for this type of waste. The evolution of the temperature and the composition of leachate and gas at various points within the cell are included. During the first weeks, pollutant concentrations in the leachate exceeded the reference ranges in the literature, coinciding with a rapid onset of methanogenic conditions. However, there was a quick wash, reducing concentrations to below one third of the initial values before the first year. pH values influenced concentrations of some pollutants such as copper. These results indicate that, right from the beginning of disposal, such facilities should be prepared to treat a high pollution load in the leachate and install the gas emissions control elements due to the rapid onset of methanogenesis.This work is funded by the Spanish Ministry of Economics and Competitiveness through the CTM2012-35055 project. The project is financed jointly by the European Regional Development Fund, FEDER (operational period 2007-2013). The authors wish to thank the Government of Cantabria, through the public company MARE, and TirCantabria, the landfill operator company, for their collaboration
Evaluation of Physicochemical and Antioxidant Properties of Peanut Protein Hydrolysate
Peanut protein and its hydrolysate were compared with a view to their use as food additives. The effects of pH, temperature and protein concentration on some of their key physicochemical properties were investigated. Compared with peanut protein, peanut peptides exhibited a significantly higher solubility and significantly lower turbidity at pH values 2–12 and temperature between 30 and 80°C. Peanut peptide showed better emulsifying capacity, foam capacity and foam stability, but had lower water holding and fat adsorption capacities over a wide range of protein concentrations (2–5 g/100 ml) than peanut protein isolate. In addition, peanut peptide exhibited in vitro antioxidant properties measured in terms of reducing power, scavenging of hydroxyl radical, and scavenging of DPPH radical. These results suggest that peanut peptide appeared to have better functional and antioxidant properties and hence has a good potential as a food additive
Expression and biological-clinical significance of hTR, hTERT and CKS2 in washing fluids of patients with bladder cancer
<p>Abstract</p> <p>Background</p> <p>at present, pathogenesis of bladder cancer (BC) has not been fully elucidated. Aim of this study is to investigate the role of human telomerase RNA (<it>hTR</it>), human telomerase reverse transcriptase (<it>hTERT</it>) and CDC28 protein kinase regulatory subunit 2 (<it>CKS2</it>) in bladder carcinogenesis and their possible clinical significance;</p> <p>Methods</p> <p>the transcript levels of <it>hTR</it>, <it>hTERT </it>and <it>CKS2 </it>were quantified by Real time reverse transcriptase chain reaction in exfoliated cells from bladder washings of 36 patients with BC and 58 controls. The statistical significance of differences between BC bearing patients and control groups, in the general as well as in the stratified analysis (superficial or invasive BC), was assessed by Student's t test. Non parametric Receiver Operating Characteristics analysis (ROC) was performed to ascertain the accuracy of study variables to discriminate between BC and controls. The clinical value of concomitant examination of <it>hTR</it>, <it>hTERT </it>and <it>CKS2 </it>was evaluated by logistic regression analysis;</p> <p>Results</p> <p>a significant decrease in <it>hTR </it>and a significant increase in <it>hTERT </it>or <it>CKS2 </it>gene expression were found between BC bearing patients and controls, as well as in the subgroups analysis. The area under the curve (AUC) indicated an average discrimination power for the three genes, both in the general and subgroups analysis, when singularly considered. The ability to significantly discriminate between superficial and invasive BC was observed only for <it>hTR </it>transcript levels. A combined model including <it>hTR </it>and <it>CKS2 </it>was the best one in BC diagnosis;</p> <p>Conclusions</p> <p>our results, obtained from a sample set particularly rich of exfoliated cells, provide further molecular evidence on the involvement of <it>hTR, hTERT </it>and <it>CKS2 </it>gene expression in BC carcinogenesis. In particular, while <it>hTERT </it>and <it>CKS2 </it>gene expression seems to have a major involvement in the early stages of the disease, <it>hTR </it>gene expression, seems to be more involved in progression. In addition, our findings suggest that the studied genes have a clinical role in discriminating between BC and controls in the general as well as in the stratified analysis, when singularly considered. A combined model improved over the single marker BC diagnosis.</p
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