Advanced quantum based neural network classifier and its application for objectionable web content filtering

© 2013 IEEE. In this paper, an Advanced Quantum-based Neural Network Classifier (AQNN) is proposed. The proposed AQNN is used to form an objectionable Web content filtering system (OWF). The aim is to design a neural network with a few numbers of hidden layer neurons with the optimal connection weights and the threshold of neurons. The proposed algorithm uses the concept of quantum computing and genetic concept to evolve connection weights and the threshold of neurons. Quantum computing uses qubit as a probabilistic representation which is the smallest unit of information in the quantum computing concept. In this algorithm, a threshold boundary parameter is also introduced to find the optimal value of the threshold of neurons. The proposed algorithm forms neural network architecture which is used to form an objectionable Web content filtering system which detects objectionable Web request by the user. To judge the performance of the proposed AQNN, a total of 2000 (1000 objectionable + 1000 non-objectionable) Website's contents have been used. The results of AQNN are also compared with QNN-F and well-known classifiers as backpropagation, support vector machine (SVM), multilayer perceptron, decision tree algorithm, and artificial neural network. The results show that the AQNN as classifier performs better than existing classifiers. The performance of the proposed objectionable Web content filtering system (OWF) is also compared with well-known objectionable Web filtering software and existing models. It is found that the proposed OWF performs better than existing solutions in terms of filtering objectionable content

A Generalized Enhanced Quantum Fuzzy Approach for Efficient Data Clustering

© 2013 IEEE. Data clustering is a challenging task to gain insights into data in various fields. In this paper, an Enhanced Quantum-Inspired Evolutionary Fuzzy C-Means (EQIE-FCM) algorithm is proposed for data clustering. In the EQIE-FCM, quantum computing concept is utilized in combination with the FCM algorithm to improve the clustering process by evolving the clustering parameters. The improvement in the clustering process leads to improvement in the quality of clustering results. To validate the quality of clustering results achieved by the proposed EQIE-FCM approach, its performance is compared with the other quantum-based fuzzy clustering approaches and also with other evolutionary clustering approaches. To evaluate the performance of these approaches, extensive experiments are being carried out on various benchmark datasets and on the protein database that comprises of four superfamilies. The results indicate that the proposed EQIE-FCM approach finds the optimal value of fitness function and the fuzzifier parameter for the reported datasets. In addition to this, the proposed EQIE-FCM approach also finds the optimal number of clusters and more accurate location of initial cluster centers for these benchmark datasets. Thus, it can be regarded as a more efficient approach for data clustering

A review of clustering techniques and developments

© 2017 Elsevier B.V. This paper presents a comprehensive study on clustering: exiting methods and developments made at various times. Clustering is defined as an unsupervised learning where the objects are grouped on the basis of some similarity inherent among them. There are different methods for clustering the objects such as hierarchical, partitional, grid, density based and model based. The approaches used in these methods are discussed with their respective states of art and applicability. The measures of similarity as well as the evaluation criteria, which are the central components of clustering, are also presented in the paper. The applications of clustering in some fields like image segmentation, object and character recognition and data mining are highlighted

A new mechanism of voltage-dependent gating exposed by KV10.1 channels interrupted between voltage sensor and pore

Voltage-gated ion channels couple transmembrane potential changes to ion flow. Conformational changes in the voltage-sensing domain (VSD) of the channel are thought to be transmitted to the pore domain (PD) through an α-helical linker between them (S4-S5 linker). However, our recent work on channels disrupted in the S4-S5 linker has challenged this interpretation for the KCNH family. Furthermore, a recent single-particle cryo-electron microscopy structure of KV10.1 revealed that the S4-S5 linker is a short loop in this KCNH family member, confirming the need for an alternative gating model. Here we use "split" channels made by expression of VSD and PD as separate fragments to investigate the mechanism of gating in KV10.1. We find that disruption of the covalent connection within the S4 helix compromises the ability of channels to close at negative voltage, whereas disconnecting the S4-S5 linker from S5 slows down activation and deactivation kinetics. Surprisingly, voltage-clamp fluorometry and MTS accessibility assays show that the motion of the S4 voltage sensor is virtually unaffected when VSD and PD are not covalently bound. Finally, experiments using constitutively open PD mutants suggest that the presence of the VSD is structurally important for the conducting conformation of the pore. Collectively, our observations offer partial support to the gating model that assumes that an inward motion of the C-terminal S4 helix, rather than the S4-S5 linker, closes the channel gate, while also suggesting that control of the pore by the voltage sensor involves more than one mechanism

APP Homodimers Transduce an Amyloid-β-Mediated Increase in Release Probability at Excitatory Synapses

SummaryAccumulation of amyloid-β peptides (Aβ), the proteolytic products of the amyloid precursor protein (APP), induces a variety of synaptic dysfunctions ranging from hyperactivity to depression that are thought to cause cognitive decline in Alzheimer’s disease. While depression of synaptic transmission has been extensively studied, the mechanisms underlying synaptic hyperactivity remain unknown. Here, we show that Aβ40 monomers and dimers augment release probability through local fine-tuning of APP-APP interactions at excitatory hippocampal boutons. Aβ40 binds to the APP, increases the APP homodimer fraction at the plasma membrane, and promotes APP-APP interactions. The APP activation induces structural rearrangements in the APP/Gi/o-protein complex, boosting presynaptic calcium flux and vesicle release. The APP growth-factor-like domain (GFLD) mediates APP-APP conformational changes and presynaptic enhancement. Thus, the APP homodimer constitutes a presynaptic receptor that transduces signal from Aβ40 to glutamate release. Excessive APP activation may initiate a positive feedback loop, contributing to hippocampal hyperactivity in Alzheimer’s disease

Positive Feedback between Transcriptional and Kinase Suppression in Nematodes with Extraordinary Longevity and Stress Resistance

Insulin/IGF-1 signaling (IIS) regulates development and metabolism, and modulates aging, of Caenorhabditis elegans. In nematodes, as in mammals, IIS is understood to operate through a kinase-phosphorylation cascade that inactivates the DAF-16/FOXO transcription factor. Situated at the center of this pathway, phosphatidylinositol 3-kinase (PI3K) phosphorylates PIP2 to form PIP3, a phospholipid required for membrane tethering and activation of many signaling molecules. Nonsense mutants of age-1, the nematode gene encoding the class-I catalytic subunit of PI3K, produce only a truncated protein lacking the kinase domain, and yet confer 10-fold greater longevity on second-generation (F2) homozygotes, and comparable gains in stress resistance. Their F1 parents, like weaker age-1 mutants, are far less robust—implying that maternally contributed trace amounts of PI3K activity or of PIP3 block the extreme age-1 phenotypes. We find that F2-mutant adults have <10% of wild-type kinase activity in vitro and <60% of normal phosphoprotein levels in vivo. Inactivation of PI3K not only disrupts PIP3-dependent kinase signaling, but surprisingly also attenuates transcripts of numerous IIS components, even upstream of PI3K, and those of signaling molecules that cross-talk with IIS. The age-1(mg44) nonsense mutation results, in F2 adults, in changes to kinase profiles and to expression levels of multiple transcripts that distinguish this mutant from F1 age-1 homozygotes, a weaker age-1 mutant, or wild-type adults. Most but not all of those changes are reversed by a second mutation to daf-16, implicating both DAF-16/ FOXO–dependent and –independent mechanisms. RNAi, silencing genes that are downregulated in long-lived worms, improves oxidative-stress resistance of wild-type adults. It is therefore plausible that attenuation of those genes in age-1(mg44)-F2 adults contributes to their exceptional survival. IIS in nematodes (and presumably in other species) thus involves transcriptional as well as kinase regulation in a positive-feedback circuit, favoring either survival or reproduction. Hyperlongevity of strong age-1(mg44) mutants may result from their inability to reset this molecular switch to the reproductive mode