Classification of valence changes of trivalent rare earth ions in alkaline earth borates using artificial neural networks

The investigations of classification on the valence changes from RE3+ to RE2+ (RE = Eu, Sm, Yb, Tm) in host compounds of alkaline earth berate were performed using artificial neural networks (ANNs). For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods. (C) 1999 Elsevier Science B.V. All rights reserved.

Aiding classification of gene expression data with feature selection: a comparative study

C. Shang and Q. Shen. Aiding classification of gene expression data with feature selection: a comparative study. Computational Intelligence Research, 1(1):68-76.

AN IMPEDANCE TUBE FOR THE IN-SITU CLASSIFICATION OF BUBBLY LIQUIDS

It is well documented that the presence of even a few air bubbles in water can signifi- cantly alter the propagation and scattering of sound. Air bubbles are both naturally and artificially generated in all marine environments, especially near the sea surface. The abil- ity to measure the acoustic propagation parameters of bubbly liquids in situ has long been a goal of the underwater acoustics community. One promising solution is a submersible, thick-walled, liquid-filled impedance tube. Recent water-filled impedance tube work was successful at characterizing low void fraction bubbly liquids in the laboratory [1]. This work details the modifications made to the existing impedance tube design to allow for submersed deployment in a controlled environment, such as a large tank or a test pond. As well as being submersible, the useable frequency range of the device is increased from 5 - 9 kHz to 1 - 16 kHz and it does not require any form of calibration. The opening of the new impedance tube is fitted with a large stainless steel flange to better define the boundary condition on the plane of the tube opening. The new device was validated against the classic theoretical result for the complex reflection coefficient of a tube opening fitted with an infinite flange. The complex reflection coefficient was then measured with a bubbly liquid (order 250 micron radius and 0.1 - 0.5 % void fraction) outside the tube opening. Results from the bubbly liquid experiments were inconsistent with flanged tube theory using current bubbly liquid models. The results were more closely matched to unflanged tube theory, suggesting that the high attenuation and phase speeds in the bubbly liquid made the tube opening appear as if it were radiating into free space.

Multi-sensor classification of tennis strokes

In this work, we investigate tennis stroke recognition using a single inertial measuring unit attached to a player’s forearm during a competitive match. This paper evaluates the best approach for stroke detection using either accelerometers, gyroscopes or magnetometers, which are embedded into the inertial measuring unit. This work concludes what is the optimal training data set for stroke classification and proves that classifiers can perform well when tested on players who were not used to train the classifier. This work provides a significant step forward for our overall goal, which is to develop next generation sports coaching tools using both inertial and visual sensors in an instrumented indoor sporting environment.

Genome- and transcriptome-assisted development of nuclear insertion/deletion markers for Calanus species (Copepoda: Calanoida) identification

Copepods of the genus Calanus are key zooplankton species in temperate to arctic marine ecosystems. Despite their ecological importance, species identification remains challenging. Furthermore, the recent report of hybrids among Calanus species highlights the need for diagnostic nuclear markers to efficiently identify parental species and hybrids. Using next-generation sequencing analysis of both the genome and transcriptome from two sibling species, Calanus finmarchicus and Calanus glacialis, we developed a panel of 12 nuclear insertion/deletion markers. All the markers showed species-specific amplicon length. Furthermore, most of the markers were successfully amplified in other Calanus species, allowing the molecular identification of Calanus helgolandicus, Calanus hyperboreus and Calanus marshallae.

Chemotherapy-Induced CXC-Chemokine/CXC-Chemokine Receptor Signaling in Metastatic Prostate Cancer Cells Confers Resistance to Oxaliplatin through Potentiation of Nuclear Factor-κB Transcription and Evasion of Apoptosis

Constitutive activation of nuclear factor (NF)-kappa B is linked with the intrinsic resistance of androgen-independent prostate cancer (AIPC) to cytotoxic chemotherapy. Interleukin-8 (CXCL8) is a transcriptional target of NF-kappa B whose expression is elevated in AIPC. This study sought to determine the significance of CXCL8 signaling in regulating the response of AIPC cells to oxaliplatin, a drug whose activity is reportedly sensitive to NF-kappa B activity. Administration of oxaliplatin to PC3 and DU145 cells increased NF-kappa B activity, promoting antiapoptotic gene transcription. In addition, oxaliplatin increased the transcription and secretion of CXCL8 and the related CXC-chemokine CXCL1 and increased the transcription and expression of CXC-chemokine receptors, especially CXC-chemokine receptor (CXCR) 2, which transduces the biological effects of CXCL8 and CXCL1. Stimulation of AIPC cells with CXCL8 potentiated NF-kappa B activation in AIPC cells, increasing the transcription and expression of NF-kappa B-regulated antiapoptotic genes of the Bcl-2 and IAP families. Coadministration of a CXCR2-selective antagonist, AZ10397767 (Bioorg Med Chem Lett 18:798-803, 2008), attenuated oxaliplatin-induced NF-kappa B activation, increased oxaliplatin cytotoxicity, and potentiated oxaliplatin-induced apoptosis in AIPC cells. Pharmacological inhibition of NF-kappa B or RNA interference-mediated suppression of Bcl-2 and survivin was also shown to sensitize AIPC cells to oxaliplatin. Our results further support NF-kappa B activity as an important determinant of cancer cell sensitivity to oxaliplatin and identify the induction of autocrine CXCR2 signaling as a novel mode of resistance to this drug.

Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78-0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1-6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI. © Springer-Verlag London Limited 2008.