ChAmElEoN: A Customizable Language for Teaching Programming Languages

ChAmElEoN is a programming language for teaching students the concepts and implementation of computer languages. We describe its syntax and semantics, the educational aspects involved in the implementation of a variety of interpreters for it, its malleability, and student feedback to inspire its use for teaching languages

Thermodynamic properties of extremely diluted symmetric Q-Ising neural networks

Using the replica-symmetric mean-field theory approach the thermodynamic and retrieval properties of extremely diluted {\it symmetric} $Q$-Ising neural networks are studied. In particular, capacity-gain parameter and capacity-temperature phase diagrams are derived for $Q=3, 4$ and $Q=\infty$. The zero-temperature results are compared with those obtained from a study of the dynamics of the model. Furthermore, the de Almeida-Thouless line is determined. Where appropriate, the difference with other $Q$-Ising architectures is outlined.Comment: 16 pages Latex including 6 eps-figures. Corrections, also in most of the figures have been mad

Bioprospecting for and the applications of halophilic acidophiles in bioleaching operations

The economic recovery of metals from sulfide ores has become a topic of increasing interest due to the escalating demand for critical minerals and the reducing grade of available ores. Bioleaching is the use of acidophilic iron and sulfur-oxidising microorganisms to facilitate the extraction of base metals from primary sulfide ores and tailings. One significant issue limiting the use of bioleaching is the availability of freshwater due to the sensitivity of these microbes to chloride. The use of saline tolerant acidophilic iron- and-sulfur oxidising microorganisms will go a long way to addressing this issue. There are three possible means of sourcing suitable microorganisms; adaptation, genetic engineering and bioprospecting, with bioprospecting showing the greatest possibilities. Bioprospecting in search of native organisms for bioleaching operations has led researchers to numerous locations around the world and the isolation of iron- and sulfur-oxidising acidophiles that are capable of tolerating high levels of salinity has been of particular interest in these investigations

The Little-Hopfield model on a Random Graph

We study the Hopfield model on a random graph in scaling regimes where the average number of connections per neuron is a finite number and where the spin dynamics is governed by a synchronous execution of the microscopic update rule (Little-Hopfield model).We solve this model within replica symmetry and by using bifurcation analysis we prove that the spin-glass/paramagnetic and the retrieval/paramagnetictransition lines of our phase diagram are identical to those of sequential dynamics.The first-order retrieval/spin-glass transition line follows by direct evaluation of our observables using population dynamics. Within the accuracy of numerical precision and for sufficiently small values of the connectivity parameter we find that this line coincides with the corresponding sequential one. Comparison with simulation experiments shows excellent agreement.Comment: 14 pages, 4 figure

An Introduction to Declarative Programming in CLIPS and PROLOG

We provide a brief introduction to CLIPS—a declarative/logic programming language for implementing expert systems—and PROLOG—a declarative/logic programming language based on first-order, predicate calculus. Unlike imperative languages in which the programmer specifies how to compute a solution to a problem, in a declarative language, the programmer specifies what they what to find, and the system uses a search strategy built into the language. We also briefly discuss applications of CLIPS and PROLOG

Neotypification and redescription of Amanita preissii (Basidiomycota), and reconsideration of the status of A. griseibrunnea

Amanita preissii (Fr.) Sacc. is redescribed. Re-examination of collections of A. griseibrunnea O.K.Mill. show that they do not differ significantly from A. preissii and the two species are combined. This species is common in the Perth IBRA subregion. Sequence data from the nuclear ribosomal internal transcribed spacer (ITS) region, 28S nuclear ribosomal large subunit rRNA (28S) region, RNA polymerase II (RPB2) region, β-tubulin region and translation elongation factor 1-α (EF1-α) region have been deposited in GenBank

Fixed Points of Hopfield Type Neural Networks

The set of the fixed points of the Hopfield type network is under investigation. The connection matrix of the network is constructed according to the Hebb rule from the set of memorized patterns which are treated as distorted copies of the standard-vector. It is found that the dependence of the set of the fixed points on the value of the distortion parameter can be described analytically. The obtained results are interpreted in the terms of neural networks and the Ising model.Comment: RevTEX, 19 pages, 2 Postscript figures, the full version of the earler brief report (cond-mat/9901251

Analysis of element yield, bacterial community structure and the impact of carbon sources for bioleaching rare earth elements from high grade monazite

Rare earth element (REE) recovery from waste streams, mine tailings or recyclable components using bioleaching is gaining traction due to the shortage and security of REE supply as well as the environmental problems that occur from processing and refining. Four heterotrophic microbial species with known phosphate solubilizing capabilities were evaluated for their ability to leach REE from a high-grade monazite when provided with either galactose, fructose or maltose. Supplying fructose resulted in the greatest amount of REE leached from the ore due to the largest amount of organic acid produced. Gluconic acid was the dominant organic acid identified produced by the cultures, followed by acetic acid. The monazite proved difficult to leach with the different carbon sources, with preferential release of Ce over La, Nd and Pr

Statistical Mechanics of Learning in the Presence of Outliers

Using methods of statistical mechanics, we analyse the effect of outliers on the supervised learning of a classification problem. The learning strategy aims at selecting informative examples and discarding outliers. We compare two algorithms which perform the selection either in a soft or a hard way. When the fraction of outliers grows large, the estimation errors undergo a first order phase transition.Comment: 24 pages, 7 figures (minor extensions added