Gene subset selection in microarray data using entropic filtering for cancer classification

Abstract: In this work an entropic filtering algorithm (EFA) for feature selection is described, as a workable method to generate a relevant subset of genes. This is a fast feature selection method based on finding feature subsets that jointly maximize the normalized multivariate conditional entropy with respect to the classification ability of tumours. The EFA is tested in combination with several machine learning algorithms on five public domain microarray data sets. It is found that this combination offers subsets yielding similar or much better accuracies than using the full set of genes. The solutions obtained are of comparable quality to previous results, but they are obtained in a maximum of half an hour computing time and use a very low number of genes.     

The impact of false warnings on partial and full lane departure warnings effectiveness and acceptance in car driving

In the past, lane departure warnings (LDWs) were demonstrated to improve driving behaviours during lane departures but little is known about the effects of unreliable warnings. This experiment focused on the influence of false warnings alone or in combination with missed warnings and warning onset on assistance effectiveness and acceptance. Two assistance unreliability levels (33 and 17%) and two warning onsets (partial and full lane departure) were manipulated in order to investigate interaction. Results showed that assistance, regardless unreliability levels and warning onsets, improved driving behaviours during lane departure episodes and outside of these episodes by favouring better lane-keeping performances. Full lane departure and highly unreliable warnings, however, reduced assistance efficiency. Drivers’ assistance acceptance was better for the most reliable warnings and for the subsequent warnings. The data indicate that imperfect LDWs (false warnings or false and missed warnings) further improve driving behaviours compared to no assistance.

Practitioner Summary: This study revealed that imperfect lane departure warnings are able to significantly improve driving performances and that warning onset is a key element for assistance effectiveness and acceptance. The conclusion may be of particular interest for lane departure warning designers.     

Ordinal regression by a gravitational model in the field of educational data mining

Educational data mining (EDM) is a research area where the goal is to develop data mining methods to examine data critically from educational environments. Traditionally, EDM has addressed the following problems: clustering, classification, regression, anomaly detection and association rule mining. In this paper, the ordinal regression (OR) paradigm, is introduced in the field of EDM. The goal of OR problems is the classification of items in an ordinal scale. For instance, the prediction of students' performance in categories (where the different grades could be ordered according to A ? B ? C ? D) is a classical example of an OR problem. The EDM community has not yet explored this paradigm (despite the importance of these problems in the field of EDM). Furthermore, an amenable and interpretable OR model based on the concept of gravitation is proposed. The model is an extension of a recently proposed gravitational model that tackles imbalanced nominal classification problems. The model is carefully adapted to the ordinal scenario and validated with four EDM datasets. The results obtained were compared with state‐of‐the‐art OR algorithms and nominal classification ones. The proposed models can be used to better understand the learning–teaching process in higher education environments.     

Stronger Lempel-Ziv Based Compressed Text Indexing

Given a text T[1..u] over an alphabet of size σ, the full-text search problem consists in finding the occ occurrences of a given pattern P[1..m] in T. In indexed text searching we build an index on T to improve the search time, yet increasing the space requirement. The current trend in indexed text searching is that of compressed full-text self-indices, which replace the text with a more space-efficient representation of it, at the same time providing indexed access to the text. Thus, we can provide efficient access within compressed space. The Lempel-Ziv index (LZ-index) of Navarro is a compressed full-text self-index able to represent T using 4uH _k (T)+o(ulog?σ) bits of space, where H _k (T) denotes the k-th order empirical entropy of T, for any k=o(log? _σ u). This space is about four times the compressed text size. The index can locate all the occ occurrences of a pattern P in T in O(m ³log?σ+(m+occ)log?u) worst-case time. Although this index has proven very competitive in practice, the O(m ³log?σ) term can be excessive for long patterns. Also, the factor 4 in its space complexity makes it larger than other state-of-the-art alternatives. In this paper we present stronger Lempel-Ziv based indices (LZ-indices), improving the overall performance of the original LZ-index. We achieve indices requiring (2+ε)uH _k (T)+o(ulog?σ) bits of space, for any constant ε>0, which makes them the smallest existing LZ-indices. We simultaneously improve the search time to O(m ²+(m+occ)log?u), which makes our indices very competitive with state-of-the-art alternatives. Our indices support displaying any text substring of length ? in optimal O(?/log? _σ u) time. In addition, we show how the space can be squeezed to (1+ε)uH _k (T)+o(ulog?σ) to obtain a structure with O(m ²) average search time for m≥2log? _σ u. Alternatively, the search time of LZ-indices can be improved to O((m+occ)log?u) with (3+ε)uH _k (T)+o(ulog?σ) bits of space, which is much less than the space needed by other Lempel-Ziv-based indices achieving the same search time. Overall our indices stand out as a very attractive alternative for space-efficient indexed text searching.     

Crystal chemistry of calcium silicates: Germinate and chromate analogues of KF·2[Ca6(SO4)(SiO4)2O]

The germanate KF·2[Ca₆(SO₄) (GeO₄)₂O] was synthesized by solid state reactions; comparison of the observed and calculated powder pattern, assuming an isostructural relationship with the silicate phase, gives good agreement. Sulphate groups may also be substituted by CrO₄²⁻ to give the isostructural KF·2[Ca₆(CrO₄)(SiO₄)₂O].     

Probabilistic proximity search: Fighting the curse of dimensionality in metric spaces

Proximity searches become very difficult on “high dimensional” metric spaces, that is, those whose histogram of distances has a large mean and/or a small variance. This so-called “curse of dimensionality”, well known in vector spaces, is also observed in metric spaces. The search complexity grows sharply with the dimension and with the search radius. We present a general probabilistic framework applicable to any search algorithm and whose net effect is to reduce the search radius. The higher the dimension, the more effective the technique. We illustrate empirically its practical performance on a particular class of algorithms, where large improvements in the search time are obtained at the cost of a very small error probability.     

Heavy metal precipitation by polycation-polyanion complex of PEI and its phosphonomethylated derivative

The removal of various heavy metal ions such as Cu2+, Co2+, Zn2+, Ni2+ and Pb2+ from aqueous solutions by precipitation with polyelectrolyte complex of PPEI and PEI was conducted. Heavy metal binding with PPEI was initially allowed to occur and then upon equilibration, PEI was added to initiate precipitation of the polyelectrolyte complex together with the heavy metal ion. The PPEI-PEI system was found effective for heavy metal scavenging purposes even in the presence of high concentrations of non-transition metal ions like Na+. Heavy metal concentration may be reduced beyond emission standards for industrial wastewaters. The PPEI-PEI polyelectrolyte complex was found to be more effective than traditional precipitation methods for the treatment of a representative electroless Ni plating waste solution.     

Approximate Matching of Run-Length Compressed Strings

We focus on the problem of approximate matching of strings that have been compressed using run-length encoding. Previous studies have concentrated on the problem of computing the longest common subsequence (LCS) between two strings of length m and n , compressed to m' and n' runs. We extend an existing algorithm for the LCS to the Levenshtein distance achieving O(m'n+n'm) complexity. Furthermore, we extend this algorithm to a weighted edit distance model, where the weights of the three basic edit operations can be chosen arbitrarily. This approach also gives an algorithm for approximate searching of a pattern of m letters (m' runs) in a text of n letters (n' runs) in O(mm'n') time. Then we propose improvements for a greedy algorithm for the LCS, and conjecture that the improved algorithm has O(m'n') expected case complexity. Experimental results are provided to support the conjecture.     

Highly Stable Colloidal “Giant” Quantum Dots Sensitized Solar Cells

Colloidal quantum dots (QDs) are widely studied due to their promising optoelectronic properties. This study explores the application of specially designed and synthesized “giant” core/shell CdSe/(CdS)_x QDs with variable CdS shell thickness, while keeping the core size at 1.65 nm, as a highly efficient and stable light harvester for QD sensitized solar cells (QDSCs). The comparative study demonstrates that the photovoltaic performance of QDSCs can be significantly enhanced by optimizing the CdS shell thickness. The highest photoconversion efficiency (PCE) of 3.01% is obtained at optimum CdS shell thickness ≈1.96 nm. To further improve the PCE and fully highlight the effect of core/shell QDs interface engineering, a CdSe_x S_1?x interfacial alloyed layer is introduced between CdSe core and CdS shell. The resulting alloyed CdSe/(CdSe_x S_1?x )₅/(CdS)₁ core/shell QD‐based QDSCs yield a maximum PCE of 6.86%, thanks to favorable stepwise electronic band alignment and improved electron transfer rate with the incorporation of CdSe_x S_1?x interfacial layer with respect to CdSe/(CdS)₆ core/shell. In addition, QDSCs based on “giant” core/CdS‐shell or alloyed core/shell QDs exhibit excellent long‐term stability with respect to bare CdSe‐based QDSCs. The giant core/shell QDs interface engineering methodology offers a new path to improve PCE and the long‐term stability of liquid junction QDSCs.     

Active inverted stripline circular patch antennas for spatial powercombining

An active antenna configuration is proposed for spatial-power-combining applications. The active patch antenna uses an inverted stripline topology to take advantage of several features. These features include avoiding drilling through the circuit substrate to insert the diode and the use of air within the resonant cavity to reduce loss. The inverted substrate serves as a radome for hermetic sealing. The active antenna and housing can be fabricated in modular form for reduced cost and easy replaceability of devices. The active inverted stripline patch antenna exhibits a much cleaner spectrum and greater stability than previously reported active antennas. The fixture serves as a ground plane, heat sink, and support in an active planar array or as a mirror in a quasi-optical power-combining resonator. A single active antenna operating at 9.23 GHz exhibited a 16-MHz locking bandwidth at 30-dB locking gain. Power-combining efficiencies of over 89% have been demonstrated for a four-element square array that maintained injection-locking and power-combining over a 60-MHz bias tuned bandwidth. Similarly, a four-element diamond array showed over 86% combining efficiency and 50-MHz bias tuned bandwidth. Beam steering was demonstrated by varying bias voltage to the individual antenna elements of the square array