Learning to Recognize Actions from Limited Training Examples Using a Recurrent Spiking Neural Model

A fundamental challenge in machine learning today is to build a model that can learn from few examples. Here, we describe a reservoir based spiking neural model for learning to recognize actions with a limited number of labeled videos. First, we propose a novel encoding, inspired by how microsaccades influence visual perception, to extract spike information from raw video data while preserving the temporal correlation across different frames. Using this encoding, we show that the reservoir generalizes its rich dynamical activity toward signature action/movements enabling it to learn from few training examples. We evaluate our approach on the UCF-101 dataset. Our experiments demonstrate that our proposed reservoir achieves 81.3%/87% Top-1/Top-5 accuracy, respectively, on the 101-class data while requiring just 8 video examples per class for training. Our results establish a new benchmark for action recognition from limited video examples for spiking neural models while yielding competetive accuracy with respect to state-of-the-art non-spiking neural models.Comment: 13 figures (includes supplementary information

Spatiotemporal Chaos in Coupled Map Lattice.

"sensitive dependence on initial condition", which is the essential feature of chaos is demonstrated through simple Lorenz model. Period doubling route to chaos is shown by analysis of Logistic map and other different route to chaos is discussed. Coupled map lattices are investigated as a model for spatio-temporal chaos. Diffusively coupled logistic lattice is studied which shows different pattern in accordance with the coupling constant and the non-linear parameter i.e. frozen random pattern, pattern selection with suppression of chaos , Brownian motion of the space defect, intermittent collapse, soliton turbulence and travelling waves

Role Of DNA Methyltransferase 1, “DNMT 1” In Human Cancer

Changes in methylation of promoter or first exon may mimic the effect of mutations of various tumor suppressor genes (TSGs) or proto- oncogene. Repression of various genes during malignant transformation is due to CpG island hypermethylation and chromatin remodeling. Transcriptional-silencing is due to the Hypermethylation of promoter of various TSGs. However, hypomethylation of regulatory DNA sequences activates transcription of proto-oncogene, retrotransposons, as well as genes encoding proteins involved in genomic instability and malignant cell metastasis. The methylation of genomic DNA in malignant cells is catalyzed by DNA methyltransferases DNMT1. DNA methylation can be induced by the tobacco-specific carcinogen NNK. The role of DNMT1-mediated methylation in tobacco carcinogenesis remains unclear. In a human lung cell line, glycogen synthase kinase 3β (GSK3β) phosphorylatedDNMT1 to recruit β-transducin repeat–containing protein (βTrCP), resulting in DNMT1 degradation, and that NNK activated AKT, inhibiting GSK3β function and thereby attenuating DNMT1 degradation. Chemotherapy using DNA intercalators is one of the most successful approaches to cancer treatment. Induction of apoptosis in tumor cells is due t DNA intercalators that are believed to inhibit DNA polymerases and topo-isomerases, . The inhibition of DNMT1 the primary DNA methyltransferase in mammalian cells ,enzymatic activity is done by the DNA intercalators, such as doxorubicin. Expression levels of DNMT1 in tumor cells may affect the effectiveness of doxorubicin in chemotherapy. Global hypomethylation in the absence of DNMT1down-regulation is apparent in non-primate placentas and invitro derived human cyto-trophoblast stem cells, suggesting that DNMT1down-regulation is not an absolute requirement for genomic hypomethylation in all instances. Here, we worked with the lymph node cancer tissue and found that the suppression of the activity along with other effects caused by other genes is responsible for the cancer development in the lymph node tissue

Synthesis and characterization of Thiol functionalized Mesoporous Zirconia and its utilizisation for the removal of methyl blue from waste water

In this work, functionalized mesoporous zirconia have been synthesized by a simple chemical process, in the presence of pluronic F127, MPTMS and toluene. The microscopic assembly of the thiol functionalized material and the crystallinity of the pore walls were studied by using small X-ray powder diffractions. Batch adsorption study was conducted to investigate the removal of methyl blue from waste water by using thiol functionalized mesoporous zirconia. Adsorption experiments were conducted as a function of adsorbent dose, equilibrium pH, contact time, initial concentration, adsorption kinetics and adsorption isotherms. The characterization and mechanisms involved in adsorption of methyl blue on the material were studied by using instrumental technique like XRD, FTIR, SEM, BET and chemical methods. The adsorption kinetic studies indicated that the overall adsorption process was best described by pseudo-second-order kinetics. The adsorption data were fitted linearly transformed Langmuir isotherm with R2 (correlation coefficient) > 0.97. The results indicate that thiol functionalized mesoporous zirconia can be used as an effective and low cost adsorbent for the treatment of wastewater

Synthesis and Characterization of Porous Metal Oxides in Imidazolium Ionic Liquids

Metal oxide microspheres have potential applications in many fields. Porous hollow metal oxides play a crucial role in the properties of microspheres. ZnO nanoparticle, tin dioxide microsphere and zinc oxide microspheres were prepared by solvothermal and simple solid-state reaction. The porous hollow metal oxides were characterized by XRD, SEM, Photolumenescence, FTIR