Coal-oil mixture from a synthetic oil obtained by hydroliquefaction of a South African coal

A coal-oil mixture (COM) was prepared from a South African coal and a synthetic oil derived from the same coal by hydroliquefaction. The settling and rheological properties of this mixture were compared with those of a mixture of the same coal with fuel oil. The synthetic oil mixture showed greater settling stability, comparable with that of a commercial COM containing additives. The increased stability may be related to polar compounds present in the oil and on the coal surface.     

Modification of oxidizing activity of Thiobacillus ferroxidans by some particulate solids

Different particulate solids such as glass powder, various types of activated carbon and bentonite suspended in Thiobacillus ferrooxidans cultures produce very different effects on the oxidizing activity of the microorganism. The atmospheric oxygen uptake by Thiobacillus ferrooxidans in Warburg respirometer flasks containing 9K medium with ferrous sulfate as energy source and suspended bentonite is 2.8 times that in the absence of solids. The dissolution rate of pure pyrite in 250 cm³ shake flasks containing 9K medium and bentonite is considerably enhanced over that where the only solid phase is pyrite. Conversely, the oxidizing ability of the microorganism seems to be inhibited by all the activated carbons tested. The effect of ground glass seems to be related to its particle size distribution. Implications for the bioleaching of sulfide ores and coal pyrite are discussed in the light of current knowledge on the adsorption of Thiobacillus ferrooxidans cells on solid surfaces.     

Enlarging the Margins in Perceptron Decision Trees

Capacity control in perceptron decision trees is typically performed by controlling their size. We prove that other quantities can be as relevant to reduce their flexibility and combat overfitting. In particular, we provide an upper bound on the generalization error which depends both on the size of the tree and on the margin of the decision nodes. So enlarging the margin in perceptron decision trees will reduce the upper bound on generalization error. Based on this analysis, we introduce three new algorithms, which can induce large margin perceptron decision trees. To assess the effect of the large margin bias, OC1 (Journal of Artificial Intelligence Research, 1994, 2, 1–32.) of Murthy, Kasif and Salzberg, a well-known system for inducing perceptron decision trees, is used as the baseline algorithm. An extensive experimental study on real world data showed that all three new algorithms perform better or at least not significantly worse than OC1 on almost every dataset with only one exception. OC1 performed worse than the best margin-based method on every dataset.     

Latent Semantic Kernels

Kernel methods like support vector machines have successfully been used for text categorization. A standard choice of kernel function has been the inner product between the vector-space representation of two documents, in analogy with classical information retrieval (IR) approaches.Latent semantic indexing (LSI) has been successfully used for IR purposes as a technique for capturing semantic relations between terms and inserting them into the similarity measure between two documents. One of its main drawbacks, in IR, is its computational cost.In this paper we describe how the LSI approach can be implemented in a kernel-defined feature space.We provide experimental results demonstrating that the approach can significantly improve performance, and that it does not impair it.     

Layer‐by‐Layer All‐Inorganic Quantum‐Dot‐Based LEDs: A Simple Procedure with Robust Performance

A novel all‐inorganic electroluminescent device is demonstrated based on highly luminescent CdTe nanocrystals intercalated within a laminar hydrotalcite‐like structure. The laminar scaffold acts to both support and distribute the CdTe nanocrystals. The device is synthesized using simple wet chemical processes at room temperature in ambient conditions. It has high thermal stability, operating continuously up to 90 °C, and a maximum efficiency at J = 0.12 A cm^?2. The device is targeted at the automotive industry.     

An Analysis of the Interaction Between Intelligent Software Agents and Human Users

Interactions between an intelligent software agent (ISA) and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality (and deploying concepts from artificial intelligence, behavioural economics, control theory, and game theory), we frame these interactions as instances of an ISA whose reward depends on actions performed by the user. Such agents benefit by steering the user’s behaviour towards outcomes that maximise the ISA’s utility, which may or may not be aligned with that of the user. Video games, news recommendation aggregation engines, and fitness trackers can all be instances of this general case. Our analysis facilitates distinguishing various subcases of interaction (i.e. deception, coercion, trading, and nudging), as well as second-order effects that might include the possibility for adaptive interfaces to induce behavioural addiction, and/or change in user belief. We present these types of interaction within a conceptual framework, and review current examples of persuasive technologies and the issues that arise from their use. We argue that the nature of the feedback commonly used by learning agents to update their models and subsequent decisions could steer the behaviour of human users away from what benefits them, and in a direction that can undermine autonomy and cause further disparity between actions and goals as exemplified by addictive and compulsive behaviour. We discuss some of the ethical, social and legal implications of this technology and argue that it can sometimes exploit and reinforce weaknesses in human beings.