Diagnosis of gastric carcinoma by classification on feature projections

Cataloged from PDF version of article.A new classification algorithm, called benefit maximizing classifier on feature projections (BCFP), is developed and applied to the problem of diagnosis of gastric carcinoma. The domain contains records of patients with known diagnosis through gastroscopy results. Given a training set of such records, the BCFP classifier learns how to differentiate a new case in the domain. BCFP represents a concept in the form of feature projections on each feature dimension separately. Classification in the BCFP algorithm is based on a voting among the individual predictions made on each feature. In the gastric carcinoma domain, a lesion can be an indicator of one of nine different Levels of gastric carcinoma, from early to late stages. The benefit of correct classification of early levels is much more than that of late cases. Also, the costs of wrong classifications are not symmetric. In the training phase, the BCFP algorithm learns classification rules that maximize the benefit of classification. In the querying phase, using these rules, the BCFP algorithm tries to make a prediction maximizing the benefit. A genetic algorithm is applied to select the relevant features. The performance of the BCFP algorithm is evaluated in terms of accuracy and running time. The rules induced are verified by experts of the domain. (C) 2004 Elsevier B.V. All rights reserved

Magnetic and structural transitions in layered FeAs systems: AFe2As2 versus RFeAsO compounds

Resistivity, specific heat and magnetic susceptibility measurements performed on SrFe2As2 samples evidence a behavior very similar to that observed in LaFeAsO and BaFe2As2 with the difference that the formation of the SDW and the lattice deformation occur in a pronounced first order transition at T_0=205K. Comparing further data evidences that the Fe-magnetism is stronger in SrFe2As2 and in EuFe2As2 than in the other layered FeAs systems investigated up to now. Full potential LDA band structure calculations confirm the large similarity between the compounds, especially for the relevant low energy Fe 3d states. The relation between structural details and magnetic order is analyzed.Comment: 4 pages, 3 figure

Strong coupling between magnetic and structural order parameters in SrFe2As2

X-ray and Neutron diffraction as well as muon spin relaxation and M\"ossbauer experiments performed on SrFe$_2$As$_2$ polycrystalls confirm a sharp first order transition at $T_0 = 205$,K corresponding to an orthorhombic phase distortion and to a columnar antiferromagnetic Fe ordering with a propagation vector (1,0,1), and a larger distortion and larger size of the ordered moment than reported for BaFe$_2$As$_2$. The structural and the magnetic order parameters present an remarkable similarity in their temperature dependence from $T_0$ down to low temperatures, showing that both phenomena are intimately connected. Accordingly, the size of the ordered Fe moments scale with the lattice distortion when going from SrFe$_2$As$_2$ to BaFe$_2$As$_2$. Full-potential band structure calculations confirm that the columnar magnetic order and the orthorhombic lattice distortion are intrinsically tied to each other.Comment: 10 pages, 4 figure

AFe2As2 (A = Ca, Sr, Ba, Eu) and SrFe_(2-x)TM_(x)As2 (TM = Mn, Co, Ni): crystal structure, charge doping, magnetism and superconductivity

The electronic structure and physical properties of the pnictide compound families $RE$OFeAs ($RE$ = La, Ce, Pr, Nd, Sm), $A$Fe$_{2}$As$_{2}$ ($A$ = Ca, Sr, Ba, Eu), LiFeAs and FeSe are quite similar. Here, we focus on the members of the $A$Fe$_{2}$As$_{2}$ family whose sample composition, quality and single crystal growth are better controllable compared to the other systems. Using first principles band structure calculations we focus on understanding the relationship between the crystal structure, charge doping and magnetism in $A$Fe$_{2}$As$_{2}$ systems. We will elaborate on the tetragonal to orthorhombic structural distortion along with the associated magnetic order and anisotropy, influence of doping on the $A$ site as well as on the Fe site, and the changes in the electronic structure as a function of pressure. Experimentally, we investigate the substitution of Fe in SrFe$_{2-x}TM_{x}$As$_{2}$ by other 3$d$ transition metals, $TM$ = Mn, Co, Ni. In contrast to a partial substitution of Fe by Co or Ni (electron doping) a corresponding Mn partial substitution does not lead to the supression of the antiferromagnetic order or the appearance of superconductivity. Most calculated properties agree well with the measured properties, but several of them are sensitive to the As $z$ position. For a microscopic understanding of the electronic structure of this new family of superconductors this structural feature related to the Fe-As interplay is crucial, but its correct ab initio treatment still remains an open question.Comment: 27 pages, single colum

Quantifying unpredictability: A multiple-model approach based on satellite imagery data from Mediterranean ponds.

Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1) gathering long-term data and (2) handling the hard-won data. This paper takes advantage of the free access to long-term recordings of remote sensing data (27 years, Landsat TM/ETM+) to assess a set of environmental models for estimating environmental predictability. The case study included 20 Mediterranean saline ponds and lakes, and the focal variable was the water-surface area. This study first aimed to produce a method for accurately estimating the water-surface area from satellite images. Saline ponds can develop salt-crusted areas that make it difficult to distinguish between soil and water. This challenge was addressed using a novel pipeline that combines band ratio water indices and the short near-infrared band as a salt filter. The study then extracted the predictable and unpredictable components of variation in the water-surface area. Two different approaches, each showing variations in the parameters, were used to obtain the stochastic variation around a regular pattern with the objective of dissecting the effect of assumptions on predictability estimations. The first approach, which is based on Colwell's predictability metrics, transforms the focal variable into a nominal one. The resulting discrete categories define the relevant variations in the water-surface area. In the second approach, we introduced General Additive Model (GAM) fitting as a new metric for quantifying predictability. Both approaches produced a wide range of predictability for the studied ponds. Some model assumptions-which are considered very different a priori-had minor effects, whereas others produced predictability estimations that showed some degree of divergence. We hypothesize that these diverging estimations of predictability reflect the effect of fluctuations on different types of organisms. The fluctuation analysis described in this manuscript is applicable to a wide variety of systems, including both aquatic and nonaquatic systems, and will be valuable for quantifying and characterizing predictability, which is essential within the expected global increase in the unpredictability of environmental fluctuations. We advocate that a priori information for organisms of interest should be used to select the most suitable metrics estimating predictability, and we provide some guidelines for this approach

Feshbach resonances and mesoscopic phase separation near a quantum critical point in multiband FeAs-based superconductors

High Tc superconductivity in FeAs-based multilayers (pnictides), evading temperature decoherence effects in a quantum condensate, is assigned to a Feshbach resonance (called also shape resonance) in the exchange-like interband pairing. The resonance is switched on by tuning the chemical potential at an electronic topological transition (ETT) near a band edge, where the Fermi surface topology of one of the subbands changes from 1D to 2D topology. We show that the tuning is realized by changing i) the misfit strain between the superconducting planes and the spacers ii) the charge density and iii) the disorder. The system is at the verge of a catastrophe i.e. near a structural and magnetic phase transition associated with the stripes (analogous to the 1/8 stripe phase in cuprates) order to disorder phase transition. Fine tuning of both the chemical potential and the disorder pushes the critical temperature Ts of this phase transition to zero giving a quantum critical point. Here the quantum lattice and magnetic fluctuations promote the Feshbach resonance of the exchange-like anisotropic pairing. This superconducting phase that resists to the attacks of temperature is shown to be controlled by the interplay of the hopping energy between stripes and the quantum fluctuations. The superconducting gaps in the multiple Fermi surface spots reported by the recent ARPES experiment of D. V. Evtushinsky et al. arXiv:0809.4455 are shown to support the Feshbach scenario.Comment: 31 pages, 7 figure

High temperature thermoelectric properties of the type-I clathrate Ba_8Ni_xGe_(46−x−y□y)

Polycrystalline samples of the type-I clathrate Ba_8Ni_xGe_(46−x−y□y) were synthesized for 0.2 ≤ x ≤ 3.5 by melt quenching and for 3.5<x ≤ 6.0 by melting with subsequent annealing at 700 °C. The maximum Ni content in the clathrate framework at this temperature was found to be x ≈ 4.2 atoms per unit cell. Thermoelectric and thermodynamic properties of the type-I clathrate were investigated from 300 to 700 K by means of electrical resistivity, thermopower, thermal conductivity and specific heat measurements. As the Ni content increases, the electronic properties gradually evolve from a metallic character (x < 3.5) towards a highly doped semiconducting state (x ≥ 3.5). Below x ≈ 4.0 transport is dominated by electrons, while further addition of Ni (x ≈ 4.2) switches the electrical conduction to p-type. Maximum value of the dimensionless thermoelectric figure of merit ZT ≈ 0.2 was achieved at 500 K and 650 K for x ≈ 2.0 and x ≈ 3.8, respectively