Using knowledge to control tree searching

PARADISE (PAttern Recognition Applied to DIrecting SEarch) uses a knowledge-based analysis and little searching to find the correct move in chess middle game positions. PARADISE's search does not have a depth limit or any other artificial effort limit. This paper describes the methods used to constrain the search. The ideas of using different strategies to show that one move is best and using ranges to express the values of moves (first developed in Berliner's B1 search), are extended and clarified. PARADISE combines these ideas with the use of plans, a threshold, and various measures of possibility. Examples are presented, including one in which PARADISE uses an indirect strategy to prove that one move is best without finding the winning line (a first for a chess program).     

A robust return‐map algorithm for general multisurface plasticity

Three new contributions to the field of multisurface plasticity are presented for general situations with an arbitrary number of nonlinear yield surfaces with hardening or softening. A method for handling linearly dependent flow directions is described. A residual that can be used in a line search is defined. An algorithm that has been implemented and comprehensively tested is discussed in detail. Examples are presented to illustrate the computational cost of various components of the algorithm. The overall result is that a single Newton‐Raphson iteration of the algorithm costs between 1.5 and 2 times that of an elastic calculation. Examples also illustrate the successful convergence of the algorithm in complicated situations. For example, without using the new contributions presented here, the algorithm fails to converge for approximately 50% of the trial stresses for a common geomechanical model of sedementary rocks, while the current algorithm results in complete success. Because it involves no approximations, the algorithm is used to quantify the accuracy of an efficient, pragmatic, but approximate, algorithm used for sedimentary‐rock plasticity in a commercial software package. The main weakness of the algorithm is identified as the difficulty of correctly choosing the set of initially active constraints in the general setting. Copyright © 2016 John Wiley & Sons, Ltd.     

Impurities block the alpha to omega martensitic transformation in titanium

Impurities control phase stability and phase transformations in natural and man-made materials, from shape-memory alloys to steel to planetary cores. Experiments and empirical databases are still central to tuning the impurity effects. What is missing is a broad theoretical underpinning. Consider, for example, the titanium martensitic transformations: diffusionless structural transformations proceeding near the speed of sound. Pure titanium transforms from ductile alpha to brittle omega at 9 GPa, creating serious technological problems for beta-stabilized titanium alloys. Impurities in the titanium alloys A-70 and Ti-6Al-4V (wt%) suppress the transformation up to at least 35 GPa, increasing their technological utility as lightweight materials in aerospace applications. These and other empirical discoveries in technological materials call for broad theoretical understanding. Impurities pose two theoretical challenges: the effect on the relative phase stability, and the energy barrier of the transformation. Ab initio methods calculate both changes due to impurities. We show that interstitial oxygen, nitrogen and carbon retard the transformation whereas substitutional aluminium and vanadium influence the transformation by changing the d-electron concentration. The resulting microscopic picture explains the suppression of the transformation in commercial A-70 and Ti-6Al-4V alloys. In general, the effect of impurities on relative energies and energy barriers is central to understanding structural phase transformations.     

A Spectral Finite Element Approach to Modeling Soft Solids Excited with High-Frequency Harmonic Loads

An approach for efficient and accurate finite element analysis of harmonically excited soft solids using high-order spectral finite elements is presented and evaluated. The Helmholtz-type equations used to model such systems suffer from additional numerical error known as pollution when excitation frequency becomes high relative to stiffness (i.e. high wave number), which is the case, for example, for soft tissues subject to ultrasound excitations. The use of high-order polynomial elements allows for a reduction in this pollution error, but requires additional consideration to counteract Runge's phenomenon and/or poor linear system conditioning, which has led to the use of spectral element approaches. This work examines in detail the computational benefits and practical applicability of high-order spectral elements for such problems. The spectral elements examined are tensor product elements (i.e. quad or brick elements) of high-order Lagrangian polynomials with non-uniformly distributed Gauss-Lobatto-Legendre nodal points. A shear plane wave example is presented to show the dependence of the accuracy and computational expense of high-order elements on wave number. Then, a convergence study for a viscoelastic acoustic-structure interaction finite element model of an actual ultrasound driven vibroacoustic experiment is shown. The number of degrees of freedom required for a given accuracy level was found to consistently decrease with increasing element order. However, the computationally optimal element order was found to strongly depend on the wave number.     

Integration of LEFM and Strength Criteria for the Prediction of Notched Strength of Polymeric Composites

The prediction of the notched strength of polymeric composites has been the object of much interest in recent years. Theories based on both linear elastic fracture mechanics (LEFM) and strength criteria have been proposed by numerous investigators. In the present paper a model that integrates the concepts of a general strength criterion with the energy concept of LEFM is presented. This enables the transition between the extremes of both theories. Predictions made by the model are shown to compare well with experimental data for center-slit specimens of a variety of material systems. The use of the proposed model in ranking materials on the basis of notch sensitivity is also shown.     

Metal catalyst residues in carbon nanotubes decrease the thermal stability of carbon nanotube/silicone composites

An anomalous decrease in the thermal stability of silicone was observed when carbon nanotubes (CNTs) were added as fillers. The decreased thermal stability is found to result from the residues of cobalt nanoparticles in CNTs, whereas CNTs synthesized with other metal catalysts do not show such a phenomenon. The analysis of thermal degradation products indicates that CNT fillers do not change the mechanism of the thermal degradation of silicone but cobalt nanoparticles within CNTs may accelerate the degradation through free radical generation. Radical scavengers such as hindered amines and impurity-free CNTs, or removal of cobalt nanoparticles by acid treatment, can mitigate the accelerated thermal degradation.     

Lipid and Phospholipid Profiling of Biological Samples Using MALDI Fourier Transform Mass Spectrometry

Here we describe a study of the feasibility of lipid and phospholipid (PL) profiling using matrix assisted laser desorption/ionization (MALDI) Fourier transform mass spectrometry (FTMS) for two different applications. In this work PL profiles of different mammalian tissues as well as those of whole cell organisms were examined. In particular, comparative analysis of lipid and PL profiles of tissues from mice fed different diets was done and, in another application, MALDI FTMS was used to analyze PL profiles of genetically modified Saccharomyces cerevisiae. Computational sorting of the observed ions was done in order to group the lipid and PL ions from complex MALDI spectra. The PL profiles of liver tissues from mice fed different diets showed a cross correlation coefficient of 0.2580, indicating significant dissimilarity, and revealed more than 30 significantly different peaks at the 99.9% confidence level. Histogram plots derived from the spectra of wild type and genetically modified yeast resulted in a cross correlation coefficient 0.8941 showing greater similarity, but still revealing a number of significantly different peaks. Based on these results, it appears possible to use MALDI FTMS to identify PLs as potential biomarkers for metabolic processes in whole cells and tissues.     

Annexin 1 Is a Component of eATP-Induced Cytosolic Calcium Elevation in Arabidopsis thaliana Roots

Extracellular ATP (eATP) has long been established in animals as an important signalling molecule but this is less understood in plants. The identification of Arabidopsis thaliana DORN1 (Does Not Respond to Nucleotides) as the first plant eATP receptor has shown that it is fundamental to the elevation of cytosolic free Ca²⁺ ([Ca²⁺]_cyt) as a possible second messenger. eATP causes other downstream responses such as increase in reactive oxygen species (ROS) and nitric oxide, plus changes in gene expression. The plasma membrane Ca²⁺ influx channels involved in eATP-induced [Ca²⁺]_cyt increase remain unknown at the genetic level. Arabidopsis thaliana Annexin 1 has been found to mediate ROS-activated Ca²⁺ influx in root epidermis, consistent with its operating as a transport pathway. In this study, the loss of function Annexin 1 mutant was found to have impaired [Ca²⁺]_cyt elevation in roots in response to eATP or eADP. Additionally, this annexin was implicated in modulating eATP-induced intracellular ROS accumulation in roots as well as expression of eATP-responsive genes.     

Differences in seasonal distribution of wild and stocked juvenile lake trout by depth and temperature in Lake Champlain

Lake trout (Salvelinus namaycush) reared in hatcheries are exposed to an environment and feeding regime that is different from wild lake trout, and are stocked at substantially larger sizes with higher lipid reserves. In addition to differences in diet and growth, this early experience may alter habitat use compared to the wild cohort. We used seasonal data on the depth and temperature distribution of wild and stocked juvenile lake trout to test for differences in habitat use and inform sampling strategies to evaluate annual recruitment. Bottom trawling was conducted from 2015 to 2019 in the central basin of Lake Champlain every two to four weeks during the ice-free season. Differences in distribution of wild and stocked lake trout were most pronounced during thermal stratification, when wild juveniles were more abundant than stocked juveniles at shallower depths and warmer temperatures and stocked juveniles were more abundant at deeper depths and colder temperatures. Temperature preferences may be a consequence of different early rearing environments; wild lake trout are acclimated to lake temperatures and forage, whereas stocked fish entered the lake with high lipid content and little foraging experience. Unbiased assessment of the proportion of wild lake trout and growth and survival of the entire juvenile lake trout population using bottom trawl sampling should either take place in the pre- and post-stratification seasons when wild and stocked fish are at the same depths, or include the full range of depths and temperatures that wild and stocked fish occupy during the stratified period.