The Conditional Lucas & Kanade Algorithm

The Lucas & Kanade (LK) algorithm is the method of choice for efficient dense image and object alignment. The approach is efficient as it attempts to model the connection between appearance and geometric displacement through a linear relationship that assumes independence across pixel coordinates. A drawback of the approach, however, is its generative nature. Specifically, its performance is tightly coupled with how well the linear model can synthesize appearance from geometric displacement, even though the alignment task itself is associated with the inverse problem. In this paper, we present a new approach, referred to as the Conditional LK algorithm, which: (i) directly learns linear models that predict geometric displacement as a function of appearance, and (ii) employs a novel strategy for ensuring that the generative pixel independence assumption can still be taken advantage of. We demonstrate that our approach exhibits superior performance to classical generative forms of the LK algorithm. Furthermore, we demonstrate its comparable performance to state-of-the-art methods such as the Supervised Descent Method with substantially less training examples, as well as the unique ability to "swap" geometric warp functions without having to retrain from scratch. Finally, from a theoretical perspective, our approach hints at possible redundancies that exist in current state-of-the-art methods for alignment that could be leveraged in vision systems of the future.Comment: 17 pages, 11 figure

A study of 15N14N isotopic exchange over cobalt molybdenum nitrides

The 14N/15N isotopic exchange pathways over Co3Mo3N, a material of interest as an ammonia synthesis catalyst and for the development of nitrogen transfer reactions, have been investigated. Both the homomolecular and heterolytic exchange processes have been studied, and it has been shown that lattice nitrogen species are exchangeable. The exchange behavior was found to be a strong function of pretreatment with ca. 25% of lattice N atoms being exchanged after 40 min at 600 °C after N2 pretreatment at 700 °C compared to only 6% following similar Ar pretreatment. This observation, for which the potential contribution of adsorbed N species can be discounted, is significant in terms of the application of this material. In the case of the Co6Mo6N phase, regeneration to Co3Mo3N under 15N2 at 600 °C occurs concurrently with 14N15N formation. These observations demonstrate the reactivity of nitrogen in the Co–Mo–N system to be a strong function of pretreatment and worthy of further consideration

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., Ríssola, 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

In Search of a Cure: The Development of Therapeutics to Alter the Progression of Spinal Muscular Atrophy

Until the recent development of disease-modifying therapeutics, spinal muscular atrophy (SMA) was considered a devastating neuromuscular disease with a poor prognosis for most affected individuals. Symptoms generally present during early childhood and manifest as muscle weakness and progressive paralysis, severely compromising the affected individual’s quality of life, independence, and lifespan. SMA is most commonly caused by the inheritance of homozygously deleted SMN1 alleles with retention of one or more copies of a paralog gene, SMN2, which inversely correlates with disease severity. The recent advent and use of genetically targeted therapies have transformed SMA into a prototype for monogenic disease treatment in the era of genetic medicine. Many SMA-affected individuals receiving these therapies achieve traditionally unobtainable motor milestones and survival rates as medicines drastically alter the natural progression of this disease. This review discusses historical SMA progression and underlying disease mechanisms, highlights advances made in therapeutic research, clinical trials, and FDA-approved medicines, and discusses possible second-generation and complementary medicines as well as optimal temporal intervention windows in order to optimize motor function and improve quality of life for all SMA-affected individuals

How to stop disproportionation of a hydrochloride salt of a very weakly basic compound in a non-clinical suspension formulation

Our objectives were to stabilize a non-clinical suspension for use in toxicological studies and to develop methods to investigate the stability of the formulation in terms of salt disproportionation. The compound under research was a hydrochloride salt of a practically insoluble discovery compound ODM-203. The first of the three formulation approaches was a suspension prepared and stored at room temperature. The second formulation was stabilized by pH adjustment. In the third approach cooling was used to prevent salt disproportionation. 5 mg/mL aqueous suspension consisting of 20 mg/mL PVP/VA and 5 mg/mL Tween 80 was prepared for each of the approaches. The polymer was used as precipitation inhibitor to provide prolonged supersaturation while Tween 80 was used to enhance dissolution and homogeneity of the suspension. The consequences of salt disproportionation were studied by a small-scale in vitro dissolution method and by an in vivo pharmacokinetic study in rats. Our results show that disproportionation was successfully suppressed by applying cooling of the suspension in an ice bath at 2-8 degrees C. This procedure enabled us to proceed to the toxicological studies in rats. The in vivo study results obtained for the practically insoluble compound showed adequate exposures with acceptable variation at each dose level.Peer reviewe

Spatial structure of the 8200 cal yr BP event in northern Europe

International audienceA synthesis of well-dated high-resolution pollen records suggests a spatial structure in the 8200 cal yr BP event in northern Europe. The temperate, thermophilous tree taxa, especially Corylus, Ulmus, and Alnus, decline abruptly between 8300 and 8000 cal yr BP at most sites located south of 61° N, whereas there is no clear change in pollen values at the sites located in the North-European tree-line region. Pollen-based quantitative temperature reconstructions and several other, independent palaeoclimate proxies, such as lacustrine oxygen-isotope records, reflect the same pattern, with no detectable cooling in the sub-arctic region. The observed patterns challenges the general view of the wide-spread occurrence of the 8200 cal yr BP event in the North Atlantic region. An alternative explanation is that the cooling during the 8200 cal yr BP event took place mostly during the winter and spring, and the ecosystems in the south responded sensitively to the cooling during the onset of the growing season. In contrast, in the sub-arctic area, where the vegetation was still dormant and lakes ice-covered, the cold event is not reflected in pollen-based or lake-sediment-based records

Recognising facial expressions in video sequences

We introduce a system that processes a sequence of images of a front-facing human face and recognises a set of facial expressions. We use an efficient appearance-based face tracker to locate the face in the image sequence and estimate the deformation of its non-rigid components. The tracker works in real-time. It is robust to strong illumination changes and factors out changes in appearance caused by illumination from changes due to face deformation. We adopt a model-based approach for facial expression recognition. In our model, an image of a face is represented by a point in a deformation space. The variability of the classes of images associated to facial expressions are represented by a set of samples which model a low-dimensional manifold in the space of deformations. We introduce a probabilistic procedure based on a nearest-neighbour approach to combine the information provided by the incoming image sequence with the prior information stored in the expression manifold in order to compute a posterior probability associated to a facial expression. In the experiments conducted we show that this system is able to work in an unconstrained environment with strong changes in illumination and face location. It achieves an 89\% recognition rate in a set of 333 sequences from the Cohn-Kanade data base

Comparative Analysis of Whole-Genome Sequences of Influenza A(H1N1)pdm09 Viruses Isolated from Hospitalized and Nonhospitalized Patients Identifies Missense Mutations That Might Be Associated with Patient Hospital Admissions in Finland during 2009 to 2014

Peer reviewe

Comparison of Local Analysis Strategies for Exudate Detection in Fundus Images

Diabetic Retinopathy (DR) is a severe and widely spread eye disease. Exudates are one of the most prevalent signs during the early stage of DR and an early detection of these lesions is vital to prevent the patient’s blindness. Hence, detection of exudates is an important diagnostic task of DR, in which computer assistance may play a major role. In this paper, a system based on local feature extraction and Support Vector Machine (SVM) classification is used to develop and compare different strategies for automated detection of exudates. The main novelty of this work is allowing the detection of exudates using non-regular regions to perform the local feature extraction. To accomplish this objective, different methods for generating superpixels are applied to the fundus images of E-OPHTA database and texture and morphological features are extracted for each of the resulting regions. An exhaustive comparison among the proposed methods is also carried out.This paper was supported by the European Union’s Horizon 2020 research and innovation programme under the Project GALAHAD [H2020-ICT2016-2017, 732613]. The work of Adri´an Colomer has been supported by the Spanish Government under a FPI Grant [BES-2014-067889]. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.Pereira, J.; Colomer, A.; Naranjo Ornedo, V. (2018). Comparison of Local Analysis Strategies for Exudate Detection in Fundus Images. En Intelligent Data Engineering and Automated Learning – IDEAL 2018. Springer. 174-183. https://doi.org/10.1007/978-3-030-03493-1_19S174183Sidibé, D., Sadek, I., Mériaudeau, F.: Discrimination of retinal images containing bright lesions using sparse coded features and SVM. Comput. Biol. Med. 62, 175–184 (2015)Zhou, W., Wu, C., Yi, Y., Du, W.: Automatic detection of exudates in digital color fundus images using superpixel multi-feature classification. IEEE Access 5, 17077–17088 (2017)Sinthanayothin, C., et al.: Automated detection of diabetic retinopathy on digital fundus images. Diabet. Med. 19(2), 105–112 (2002)Walter, T., Klein, J.C., et al.: A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina. IEEE Trans. Med. Imaging 21(10), 1236–1243 (2002)Ali, S., et al.: Statistical atlas based exudate segmentation. Comput. Med. Imaging Graph. 37(5–6), 358–368 (2013)Zhang, X., Thibault, G., Decencière, E., Marcotegui, B., et al.: Exudate detection in color retinal images for mass screening of diabetic retinopathy. Med. Image Anal. 18(7), 1026–1043 (2014)Li, H., Chutatape, O.: Automated feature extraction in color retinal images by a model based approach. IEEE Trans. Biomed. Eng. 51(2), 246–254 (2004)Welfer, D., Scharcanski, J., Marinho, D.R.: A coarse-to-fine strategy for automatically detecting exudates in color eye fundus images. Comput. Med. Imaging Graph. 34(3), 228–235 (2010)Giancardo, L., et al.: Exudate-based diabetic macular edema detection in fundus images using publicly available datasets. Med. Image Anal. 16(1), 216–226 (2012)Amel, F., Mohammed, M., Abdelhafid, B.: Improvement of the hard exudates detection method used for computer-aided diagnosis of diabetic retinopathy. Int. J. Image Graph. Signal Process. 4(4), 19 (2012)Akram, M.U., Khalid, S., Tariq, A., Khan, S.A., Azam, F.: Detection and classification of retinal lesions for grading of diabetic retinopathy. Comput. Biol. Med. 45, 161–171 (2014)Akram, M.U., Tariq, A., Khan, S.A., Javed, M.Y.: Automated detection of exudates and macula for grading of diabetic macular edema. Comput. Methods Programs Biomed. 114(2), 141–152 (2014)Machairas, V.: Waterpixels and their application to image segmentation learning. Ph.D. thesis, Université de recherche Paris Sciences et Lettres (2016)Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 888–905 (2000)Veksler, O., Boykov, Y., Mehrani, P.: Superpixels and supervoxels in an energy optimization framework. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6315, pp. 211–224. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15555-0_16Comaniciu, D., Meer, P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Mach. Intell. 24(5), 603–619 (2002)Levinshtein, A., Stere, A., Kutulakos, K.N., Fleet, D.J., Dickinson, S.J., Siddiqi, K.: TurboPixels: fast superpixels using geometric flows. IEEE Trans. Pattern Anal. Mach. Intell. 31(12), 2290–2297 (2009)Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Süsstrunk, S.: SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274–2282 (2012)Machairas, V., Faessel, M., Cárdenas-Peña, D., Chabardes, T., Walter, T., Decencière, E.: Waterpixels. IEEE Trans. Image Process. 24(11), 3707–3716 (2015)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)Guo, Z., Zhang, L., Zhang, D.: Rotation invariant texture classification using LBP variance (LBPV) with global matching. Pattern Recognit. 43(3), 706–719 (2010)Morales, S., Naranjo, V., Angulo, J., Alcañiz, M.: Automatic detection of optic disc based on PCA and mathematical morphology. IEEE Trans. Med. Imaging 32(4), 786–796 (2013)Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. (TIST) 2(3), 27 (2011)Decencière, E., Cazuguel, G., Zhang, X., Thibault, G., Klein, J.C., Meyer, F., et al.: TeleOphta: machine learning and image processing methods for teleophthalmology. IRBM 34(2), 196–203 (2013)DErrico, J.: inpaint\_nans, matlab central file exchange (2004). http://kr.mathworks.com/matlabcentral/fileexchange/4551-inpaint-nans . Accessed 13 Aug 201

A high affinity, partial antagonist effect of 3,4-diaminopyridine mediates action potential broadening and enhancement of transmitter release at NMJs

3,4-Diaminopyridine (3,4-DAP) increases transmitter release from neuromuscular junctions (NMJs), and low doses of 3,4-DAP (estimated to reach ∼1 μM in serum) are the Food and Drug Administration (FDA)-Approved treatment for neuro muscular weakness caused by Lambert-Eaton myasthenic syn drome. Canonically, 3,4-DAP is thought to block voltage-gated potassium (Kv) channels, resulting in prolongation of the pre synaptic action potential (AP). However, recent reports have shown that low millimolar concentrations of 3,4-DAP have an off-Target agonist effect on the Cav1 subtype ( L-Type ) of voltage-gated calcium (Cav) channels and have speculated that this agonist effect might contribute to 3,4-DAP effects on transmitter release at the NMJ. To address 3,4-DAPs mecha nism(s) of action, we first used the patch-clamp electrophysi ology to characterize the concentration-dependent block of 3,4-DAP on the predominant presynaptic Kv channel subtypes found at the mammalian NMJ (Kv3.3 and Kv3.4). We identified a previously unreported high-Affinity (1-10 μM) partial antag onist effect of 3,4-DAP in addition to the well-known low-Af finity (0.1-1 mM) antagonist activity. We also showed that 1.5-μM DAP had no effects on Cav1.2 or Cav2.1 current. Next, we used voltage imaging to show that 1.5-or 100-μM 3,4-DAP broadened the AP waveform in a dose-dependent manner, in dependent of Cav1 calcium channels. Finally, we demonstrated that 1.5-or 100-μM 3,4-DAP augmented transmitter release in a dose-dependent manner and this effect was also independent of Cav1 channels. From these results, we conclude that low micromolar concentrations of 3,4-DAP act solely on Kv chan nels to mediate AP broadening and enhance transmitter release at the NMJ