Glioblastoma Stem Cells—Useful Tools in the Battle against Cancer

Glioblastoma stem cells (GSCs) are cells with a self-renewal ability and capacity to initiate tumors upon serial transplantation that have been linked to tumor cell heterogeneity. Most standard treatments fail to completely eradicate GSCs, causing the recurrence of the disease. GSCs could represent one reason for the low efficacy of cancer therapy and for the short relapse time. Nonetheless, experimental data suggest that the presence of therapy-resistant GSCs could explain tumor recurrence. Therefore, to effectively target GSCs, a comprehensive understanding of their biology and the survival and developing mechanisms during treatment is mandatory. This review provides an overview of the molecular features, microenvironment, detection, and targeting strategies of GSCs, an essential information required for an efficient therapy. Despite the outstanding results in oncology, researchers are still developing novel strategies, of which one could be targeting the GSCs present in the hypoxic regions and invasive edge of the glioblastoma.     

Genetic algorithm for S-transform optimisation in the analysis and classification of electrical signal perturbations

At present, many analytical methods are used for the analysis, detection and classification of electrical signal perturbations. One of these methods, the S-transform, has proven effective under specific conditions for acquiring information and parameters of interest associated with a signal. However, depending on the nature of the signal and the input parameters, this method offers different results that sometimes negatively impact the quality of information obtained in the time and frequency domains.This paper describes the design of a genetic algorithm that optimises the S-transform for analysis and classification of the perturbations in electrical signals. This algorithm provides the best parameter values for optimising the Gaussian window, maximising the precision obtained with regard to classification and, later, analysis (via other techniques, such as neural networks or rule-based systems).This paper demonstrates the effectiveness of the S-transform (specified herein) with respect to the original S-transform and reports the best values obtained after optimisation via a comparative study that includes both typical cases and perturbations in modern electrical systems.     

Solving the parity problem in one-dimensional cellular automata

The parity problem is a well-known benchmark task in various areas of computer science. Here we consider its version for one-dimensional, binary cellular automata, with periodic boundary conditions: if the initial configuration contains an odd number of 1s, the lattice should converge to all 1s; otherwise, it should converge to all 0s. Since the problem is ill-defined for even-sized lattices (which, by definition, would never be able to converge to 1), it suffices to account for odd-sized lattices only. We are interested in determining the minimal neighbourhood size that allows the problem to be solvable for any arbitrary initial configuration. On the one hand, we show that radius 2 is not sufficient, proving that there exists no radius 2 rule that can solve the parity problem, even in the simpler case of prime-sized lattices. On the other hand, we design a radius 4 rule that converges correctly for any initial configuration and formally prove its correctness. Whether or not there exists a radius 3 rule that solves the parity problem remains an open problem; however, we review recent data against a solution in radius 3, thus providing strong empirical evidence that there may not exist a radius 3 solution even for prime-sized lattices only, contrary to a recent conjecture in the literature.     

Using “human state aware” robots to enhance physical human–robot interaction in a cooperative scenario

Human motor performance, speed and variability are highly susceptible to emotional states. This paper reviews the impact of the emotions on the motor control performance, and studies the possibility of improving the perceived skill/challenge relation on a multimodal neural rehabilitation scenario, by means of a biocybernetic controller that modulates the assistance provided by a haptic controlled robot in reaction to undesirable physical and mental states. Results from psychophysiological, performance and self assessment data for closed loop experiments in contrast with their open loop counterparts, suggest that the proposed method had a positive impact on the overall challenge/skill relation leading to an enhanced physical human–robot interaction experience.     

Point Defects in CdZnTe Crystals Grown by Different Techniques

We studied, by current deep-level transient spectroscopy (I-DLTS), point defects in CdZnTe detectors grown by different techniques. We identified 12 different traps with energy levels from 7 meV to 1.1 eV. Although the levels of most of the identified defects were independent of the crystal growth techniques, nevertheless there were some associated differences in the traps’ energies and densities.     

Specific features of the electrochemical processes in the bath of an ore-smelting furnace

The mechanism of electrolysis in an ore-smelting cell modeling a bath with a conducting solid material in the melt is considered. An analysis suggests that a number of technological parameters of an ore-smelting furnace can be indirectly controlled by a change in the constant component of the phase voltage and the volt-ampere characteristic of the interelectrode gap.     

Formalising the Fisherman's Folly puzzle

This paper investigates the challenging problem of encoding the common sense knowledge involved in the manipulation of spatial objects from a reasoning about actions and change perspective. In particular, we propose a formal solution to a puzzle composed of non-trivial objects (such as holes and strings) assuming a version of the Situation Calculus written over first-order Equilibrium Logic, whose models generalise the stable model semantics.     

Physical and mechanical characterization of phyllites and metagreywackes in central Portugal

This work defines the physical and mechanical characteristics of phyllites and metagreywackes belonging to a schist–greywacke complex in central Portugal. The index properties, point load strength, uniaxial compressive strength, slake durability and Schmidt rebound hardness were determined. In general, the metagreywackes gave a higher strength than phyllites with the same weathering degree. Possible correlations and estimation models were established and compared with the equations obtained by different researchers.