A Novel Family of Adaptive Filtering Algorithms Based on The Logarithmic Cost

We introduce a novel family of adaptive filtering algorithms based on a relative logarithmic cost. The new family intrinsically combines the higher and lower order measures of the error into a single continuous update based on the error amount. We introduce important members of this family of algorithms such as the least mean logarithmic square (LMLS) and least logarithmic absolute difference (LLAD) algorithms that improve the convergence performance of the conventional algorithms. However, our approach and analysis are generic such that they cover other well-known cost functions as described in the paper. The LMLS algorithm achieves comparable convergence performance with the least mean fourth (LMF) algorithm and extends the stability bound on the step size. The LLAD and least mean square (LMS) algorithms demonstrate similar convergence performance in impulse-free noise environments while the LLAD algorithm is robust against impulsive interferences and outperforms the sign algorithm (SA). We analyze the transient, steady state and tracking performance of the introduced algorithms and demonstrate the match of the theoretical analyzes and simulation results. We show the extended stability bound of the LMLS algorithm and analyze the robustness of the LLAD algorithm against impulsive interferences. Finally, we demonstrate the performance of our algorithms in different scenarios through numerical examples.Comment: Submitted to IEEE Transactions on Signal Processin

Stochastic Subgradient Algorithms for Strongly Convex Optimization over Distributed Networks

We study diffusion and consensus based optimization of a sum of unknown convex objective functions over distributed networks. The only access to these functions is through stochastic gradient oracles, each of which is only available at a different node, and a limited number of gradient oracle calls is allowed at each node. In this framework, we introduce a convex optimization algorithm based on the stochastic gradient descent (SGD) updates. Particularly, we use a carefully designed time-dependent weighted averaging of the SGD iterates, which yields a convergence rate of $O\left(\frac{N\sqrt{N}}{T}\right)$ after $T$ gradient updates for each node on a network of $N$ nodes. We then show that after $T$ gradient oracle calls, the average SGD iterate achieves a mean square deviation (MSD) of $O\left(\frac{\sqrt{N}}{T}\right)$. This rate of convergence is optimal as it matches the performance lower bound up to constant terms. Similar to the SGD algorithm, the computational complexity of the proposed algorithm also scales linearly with the dimensionality of the data. Furthermore, the communication load of the proposed method is the same as the communication load of the SGD algorithm. Thus, the proposed algorithm is highly efficient in terms of complexity and communication load. We illustrate the merits of the algorithm with respect to the state-of-art methods over benchmark real life data sets and widely studied network topologies

Ocular complications of diabetes mellitus

Diabetes mellitus (DM) is a important health problem that induces ernestful complications and it causes significant morbidity owing to specific microvascular complications such as, retinopathy, nephropathy and neuropathy, and macrovascular complications such as, ischaemic heart disease, and peripheral vasculopathy. It can affect children, young people and adults and is becoming more common. Ocular complications associated with DM are progressive and rapidly becoming the world's most significant cause of morbidity and are preventable with early detection and timely treatment. This review provides an overview of five main ocular complications associated with DM, diabetic retinopathy and papillopathy, cataract, glaucoma, and ocular surface diseases

Acute brucella melitensis M16 infection model in mice treated with tumor necrosis factor-alpha inhibitors

Introduction: There is limited data in the literature about brucellosis related to an intracellular pathogen and anti-tumor necrosis factor alpha (anti-TNFα) medication. The aim of this study was to evaluate acute Brucella infections in mice receiving anti-TNFα drug treatment. Methodology: Anti-TNFα drugs were injected in mice on the first and fifth days of the study, after which the mice were infected with B. melitensis M16 strain. Mice were sacrificed on the fourteenth day after infection. Bacterial loads in the liver and spleen were defined, and histopathological changes were evaluated. Results: Neither the liver nor the spleen showed an increased bacterial load in all anti-TNFα drug groups when compared to a non-treated, infected group. The most significant histopathological findings were neutrophil infiltrations in the red pulp of the spleen and apoptotic cells with hepatocellular pleomorphism in the liver. There was no significant difference among the groups in terms of previously reported histopathological findings, such as extramedullary hematopoiesis and granuloma formation. Conclusions: There were no differences in hepatic and splenic bacterial load and granuloma formation, which indicate worsening of the acute Brucella infection in mice; in other words, anti-TNFα treatment did not exacerbate the acute Brucella spp. infection in mice. © 2015 Kutlu et al

Synthesis, crystal structures, hydrogen bonding graph-sets and theoretical studies of nickel (+II) co-ordinations with pyridine-2,6-dicarboxamide oxime

The pyridine-2,6-dicarboxamide oxime, C7H9N5O2, was Synthesis and  characterises with 1H NMR and FTIR spectroscopy . The reaction of this ligand with nickel (II) perchlorate yielded green crystals of formula  [Ni(C<sub>7</sub>H<sub>9</sub>N<sub>5</sub>O<sub>2</sub>)<sub>2</sub>]<sup>2+</sup>,2[ClO<sub>4</sub>]-, which crystallized in the monoclinic space group C2/c with a = 14.915(2), b = 0.895(2), c = 8.205(1) Å, β = 114.69(1), and Z = 4. The complex consists of discrete cations (+II) and one perchlorate anion, the  cations existing in a slightly distorted octahedral  complex with bonding through the heterocyclic and oxime nitrogen atoms. The structure is held together through N-H…O, O-H…O and C-H...O hydrogen bonds occurring  between the coordinated oxime  molecules and the perchlorate counter-ion. Computational investigations of nickel(II) complex are done by using M062X method with 6-31+G(d)(LANL2DZ) basis set in vacuo.Keywords: Oxime complexe; Crystal structure; Hydrogen-bonding graph-set; DFT; M062X method; 6-31+G(d)(LANL2DZ) basis

Synthesis, quantum chemical computations and x-ray crystallographic studies of a new complex based of manganese (+II)

The ligand oxime, C7H9N5O2, was Synthesis and characterises with different characterization methods such as 1H NMR and FTIR spectroscopy. The complexation of this ligand with manganese (II) perchlorate yielded pink crystals of formula [Mn (C7H9N5O2)2]2+, 2[ClO4]-, which crystallized in the monoclinic space group P21/n with a = 12.824(3), b=13.799(2), c=15.441(4)Å, β = 100.17(2), and Z = 4. The complex consists of cations (+II) and two perchlorate anions, the cations part existing in a slightly distorted octahedral complex. Computational investigations of manganese (II) complex are done by using the DFTmethod with B3LYP functional in conjunction with the 6-31G(d,p) and lanl2dz basis sets in the gas phase imposing the C1 and C2v symmetries.Keywords: Manganese complex; Crystal structure; DFT method; B3LYP functional; 6-31G(d,p) and (LANL2DZ) basi

Improved convergence performance of adaptive algorithms through logarithmic cost

We present a novel family of adaptive filtering algorithms based on a relative logarithmic cost. The new family intrinsically combines the higher and lower order measures of the error into a single continuous update based on the error amount. We introduce the least mean logarithmic square (LMLS) algorithm that achieves comparable convergence performance with the least mean fourth (LMF) algorithm and overcomes the stability issues of the LMF algorithm. In addition, we introduce the least logarithmic absolute difference (LLAD) algorithm. The LLAD and least mean square (LMS) algorithms demonstrate similar convergence performance in impulse-free noise environments while the LLAD algorithm is robust against impulsive interference and outperforms the sign algorithm (SA). © 2014 IEEE

Logarithmic regret bound over diffusion based distributed estimation

We provide a logarithmic upper-bound on the regret function of the diffusion implementation for the distributed estimation. For certain learning rates, the bound shows guaranteed performance convergence of the distributed least mean square (DLMS) algorithms to the performance of the best estimation generated with hindsight of spatial and temporal data. We use a new cost definition for distributed estimation based on the widely-used statistical performance measures and the corresponding global regret function. Then, for certain learning rates, we provide an upper-bound on the global regret function without any statistical assumptions. © 2014 IEEE

A Neural Circuit Arbitrates between Persistence and Withdrawal in Hungry Drosophila

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive