Plane Formation by Synchronous Mobile Robots in the Three Dimensional Euclidean Space

Creating a swarm of mobile computing entities frequently called robots, agents or sensor nodes, with self-organization ability is a contemporary challenge in distributed computing. Motivated by this, we investigate the plane formation problem that requires a swarm of robots moving in the three dimensional Euclidean space to land on a common plane. The robots are fully synchronous and endowed with visual perception. But they do not have identifiers, nor access to the global coordinate system, nor any means of explicit communication with each other. Though there are plenty of results on the agreement problem for robots in the two dimensional plane, for example, the point formation problem, the pattern formation problem, and so on, this is the first result for robots in the three dimensional space. This paper presents a necessary and sufficient condition for fully-synchronous robots to solve the plane formation problem that does not depend on obliviousness i.e., the availability of local memory at robots. An implication of the result is somewhat counter-intuitive: The robots cannot form a plane from most of the semi-regular polyhedra, while they can form a plane from every regular polyhedron (except a regular icosahedron), whose symmetry is usually considered to be higher than any semi-regular polyhedrdon

Deep Neural Networks for Document Processing of Music Score Images

[EN] There is an increasing interest in the automatic digitization of medieval music documents. Despite efforts in this field, the detection of the different layers of information on these documents still poses difficulties. The use of Deep Neural Networks techniques has reported outstanding results in many areas related to computer vision. Consequently, in this paper, we study the so-called Convolutional Neural Networks (CNN) for performing the automatic document processing of music score images. This process is focused on layering the image into its constituent parts (namely, background, staff lines, music notes, and text) by training a classifier with examples of these parts. A comprehensive experimentation in terms of the configuration of the networks was carried out, which illustrates interesting results as regards to both the efficiency and effectiveness of these models. In addition, a cross-manuscript adaptation experiment was presented in which the networks are evaluated on a different manuscript from the one they were trained. The results suggest that the CNN is capable of adapting its knowledge, and so starting from a pre-trained CNN reduces (or eliminates) the need for new labeled data.This work was supported by the Social Sciences and Humanities Research Council of Canada, and Universidad de Alicante through grant GRE-16-04.Calvo-Zaragoza, J.; Castellanos, F.; Vigliensoni, G.; Fujinaga, I. (2018). Deep Neural Networks for Document Processing of Music Score Images. Applied Sciences. 8(5). https://doi.org/10.3390/app8050654S85Bainbridge, D., & Bell, T. (2001). Computers and the Humanities, 35(2), 95-121. doi:10.1023/a:1002485918032Byrd, D., & Simonsen, J. G. (2015). Towards a Standard Testbed for Optical Music Recognition: Definitions, Metrics, and Page Images. Journal of New Music Research, 44(3), 169-195. doi:10.1080/09298215.2015.1045424LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444. doi:10.1038/nature14539Rebelo, A., Fujinaga, I., Paszkiewicz, F., Marcal, A. R. S., Guedes, C., & Cardoso, J. S. (2012). Optical music recognition: state-of-the-art and open issues. International Journal of Multimedia Information Retrieval, 1(3), 173-190. doi:10.1007/s13735-012-0004-6Louloudis, G., Gatos, B., Pratikakis, I., & Halatsis, C. (2008). Text line detection in handwritten documents. Pattern Recognition, 41(12), 3758-3772. doi:10.1016/j.patcog.2008.05.011Montagner, I. S., Hirata, N. S. T., & Hirata, R. (2017). Staff removal using image operator learning. Pattern Recognition, 63, 310-320. doi:10.1016/j.patcog.2016.10.002Calvo-Zaragoza, J., Micó, L., & Oncina, J. (2016). Music staff removal with supervised pixel classification. International Journal on Document Analysis and Recognition (IJDAR), 19(3), 211-219. doi:10.1007/s10032-016-0266-2Calvo-Zaragoza, J., Pertusa, A., & Oncina, J. (2017). Staff-line detection and removal using a convolutional neural network. Machine Vision and Applications, 28(5-6), 665-674. doi:10.1007/s00138-017-0844-4Shelhamer, E., Long, J., & Darrell, T. (2017). Fully Convolutional Networks for Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(4), 640-651. doi:10.1109/tpami.2016.2572683Kato, Z. (2011). Markov Random Fields in Image Segmentation. Foundations and Trends® in Signal Processing, 5(1-2), 1-155. doi:10.1561/2000000035Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278-2324. doi:10.1109/5.72679

Exploration of Finite 2D Square Grid by a Metamorphic Robotic System

We consider exploration of finite 2D square grid by a metamorphic robotic system consisting of anonymous oblivious modules. The number of possible shapes of a metamorphic robotic system grows as the number of modules increases. The shape of the system serves as its memory and shows its functionality. We consider the effect of global compass on the minimum number of modules necessary to explore a finite 2D square grid. We show that if the modules agree on the directions (north, south, east, and west), three modules are necessary and sufficient for exploration from an arbitrary initial configuration, otherwise five modules are necessary and sufficient for restricted initial configurations

Pattern formation

The Pattern Formation problem is one of the most important coordination problem for robotic systems. Initially the entities are in arbitrary positions; within finite time they must arrange themselves in the space so to form a pattern given in input. In this chapter, we will mainly deal with the problem in the OBLOT model

RNA polymerase II stalling promotes nucleosome occlusion and pTEFb recruitment to drive immortalization by Epstein-Barr virus

Epstein-Barr virus (EBV) immortalizes resting B-cells and is a key etiologic agent in the development of numerous cancers. The essential EBV-encoded protein EBNA 2 activates the viral C promoter (Cp) producing a message of ~120 kb that is differentially spliced to encode all EBNAs required for immortalization. We have previously shown that EBNA 2-activated transcription is dependent on the activity of the RNA polymerase II (pol II) C-terminal domain (CTD) kinase pTEFb (CDK9/cyclin T1). We now demonstrate that Cp, in contrast to two shorter EBNA 2-activated viral genes (LMP 1 and 2A), displays high levels of promoter-proximally stalled pol II despite being constitutively active. Consistent with pol II stalling, we detect considerable pausing complex (NELF/DSIF) association with Cp. Significantly, we observe substantial Cp-specific pTEFb recruitment that stimulates high-level pol II CTD serine 2 phosphorylation at distal regions (up to +75 kb), promoting elongation. We reveal that Cp-specific pol II accumulation is directed by DNA sequences unfavourable for nucleosome assembly that increase TBP access and pol II recruitment. Stalled pol II then maintains Cp nucleosome depletion. Our data indicate that pTEFb is recruited to Cp by the bromodomain protein Brd4, with polymerase stalling facilitating stable association of pTEFb. The Brd4 inhibitor JQ1 and the pTEFb inhibitors DRB and Flavopiridol significantly reduce Cp, but not LMP1 transcript production indicating that Brd4 and pTEFb are required for Cp transcription. Taken together our data indicate that pol II stalling at Cp promotes transcription of essential immortalizing genes during EBV infection by (i) preventing promoter-proximal nucleosome assembly and ii) necessitating the recruitment of pTEFb thereby maintaining serine 2 CTD phosphorylation at distal regions

Preferential Entry of Botulinum Neurotoxin A Hc Domain through Intestinal Crypt Cells and Targeting to Cholinergic Neurons of the Mouse Intestine

Botulism, characterized by flaccid paralysis, commonly results from botulinum neurotoxin (BoNT) absorption across the epithelial barrier from the digestive tract and then dissemination through the blood circulation to target autonomic and motor nerve terminals. The trafficking pathway of BoNT/A passage through the intestinal barrier is not yet fully understood. We report that intralumenal administration of purified BoNT/A into mouse ileum segment impaired spontaneous muscle contractions and abolished the smooth muscle contractions evoked by electric field stimulation. Entry of BoNT/A into the mouse upper small intestine was monitored with fluorescent HcA (half C-terminal domain of heavy chain) which interacts with cell surface receptor(s). We show that HcA preferentially recognizes a subset of neuroendocrine intestinal crypt cells, which probably represent the entry site of the toxin through the intestinal barrier, then targets specific neurons in the submucosa and later (90–120 min) in the musculosa. HcA mainly binds to certain cholinergic neurons of both submucosal and myenteric plexuses, but also recognizes, although to a lower extent, other neuronal cells including glutamatergic and serotoninergic neurons in the submucosa. Intestinal cholinergic neuron targeting by HcA could account for the inhibition of intestinal peristaltism and secretion observed in botulism, but the consequences of the targeting to non-cholinergic neurons remains to be determined

Stress from Nucleotide Depletion Activates the Transcriptional Regulator HEXIM1 to Suppress Melanoma

Studying cancer metabolism gives insight into tumorigenic survival mechanisms and susceptibilities. In melanoma, we identify HEXIM1, a transcription elongation regulator, as a melanoma tumor suppressor that responds to nucleotide stress. HEXIM1 expression is low in melanoma. Its overexpression in a zebrafish melanoma model suppresses cancer formation, while its inactivation accelerates tumor onset in vivo. Knockdown of HEXIM1 rescues zebrafish neural crest defects and human melanoma proliferation defects that arise from nucleotide depletion. Under nucleotide stress, HEXIM1 is induced to form an inhibitory complex with P-TEFb, the kinase that initiates transcription elongation, to inhibit elongation at tumorigenic genes. The resulting alteration in gene expression also causes anti-tumorigenic RNAs to bind to and be stabilized by HEXIM1. HEXIM1 plays an important role in inhibiting cancer cell-specific gene transcription while also facilitating anti-cancer gene expression. Our study reveals an important role for HEXIM1 in coupling nucleotide metabolism with transcriptional regulation in melanoma

Mycophenolate mofetil versus cyclosporine for remission maintenance in nephrotic syndrome

We performed a multi-centre randomized controlled trial to compare the efficacy of mycophenolate mofetil (MMF) to that of cyclosporine A (CsA) in treating children with frequently relapsing nephrotic syndrome and biopsy-proven minimal change disease. Of the 31 randomized initially selected patients, seven were excluded. The remaining 24 children received either MMF 1200 mg/m2per day (n = 12) or CsA 4-5 mg/kg per day (n = 12) during a 12-month period. Of the 12 patients in the MMF group, two discontinued the study medication. Evaluation of the changes from the baseline glomerular filtration rate showed an overall significant difference in favour of MMF over the treatment period (p = 0.03). Seven of the 12 patients in the MMF group and 11 of the 12 patients in the CsA group remained in complete remission during the entire study period. Relapse rate in the MMF group was 0.83/year compared to 0.08/year in the CsA group (p = 0.08). None of the patients reported diarrhea. Pharmacokinetic profiles of mycophenolic acid were performed in seven patients. The patient with the lowest area under the curve had three relapses within 6 months. In children with frequently relapsing minimal change nephrotic syndrome, MMF has a favourable side effect profile compared to CsA; however, there is a tendency towards a higher relapse risk in patients treated with MMF