Scale detection via keypoint density maps in regular or near-regular textures

In this paper we propose a new method to detect the global scale of images with regular, near regular, or homogenous textures. We define texture “scale” as the size of the basic elements (texels or textons) that most frequently occur into the image. We study the distribution of the interest points into the image, at different scale, by using our Keypoint Density Maps (KDMs) tool. A “mode” vector is built computing the most frequent values (modes) of the KDMs, at different scales. We observed that the mode vector is quasi linear with the scale. The mode vector is properly subsampled, depending on the scale of observation, and compared with a linear model. Texture scale is estimated as the one which minimizes an error function between the related subsampled vector and the linear model. Results, compared with a state of the art method, are very encouraging.     

Electrochemical behavior of hydrophobic silane–zeolite coatings for corrosion protection of aluminum substrate

The anticorrosive properties of a silane–zeolite composite coating applied on a 6061 aluminum substrate was investigated. The composite film, deposited by dip-coating technique, was prepared with different contents of SAPO34 powder (60–90 wt%) with the purpose of evaluating the protective action offered by the zeolite-filled silane matrix. Corrosion protection performance, during immersion in 3.5% NaCl solution, was evaluated by means of a potentiodynamic polarization test and electrochemical impedance spectroscopy (EIS). The coating evidenced good barrier properties and high hydrophobicity. The addition of zeolite in the silane matrix induced, as expected, a reduction of cathodic and anodic current. The zeolite improved the barrier properties of the hybrid sol–gel films, enhancing the resistance to localized corrosion attacks. Better results were observed for the sample with 80 wt% of zeolite filler that evidenced still acceptable protective action after 3 days of immersion in the sodium chloride solution.     

In-Pero: Exploiting Deep Learning Embeddings of Protein Sequences to Predict the Localisation of Peroxisomal Proteins

Peroxisomes are ubiquitous membrane-bound organelles, and aberrant localisation of peroxisomal proteins contributes to the pathogenesis of several disorders. Many computational methods focus on assigning protein sequences to subcellular compartments, but there are no specific tools tailored for the sub-localisation (matrix vs. membrane) of peroxisome proteins. We present here In-Pero, a new method for predicting protein sub-peroxisomal cellular localisation. In-Pero combines standard machine learning approaches with recently proposed multi-dimensional deep-learning representations of the protein amino-acid sequence. It showed a classification accuracy above 0.9 in predicting peroxisomal matrix and membrane proteins. The method is trained and tested using a double cross-validation approach on a curated data set comprising 160 peroxisomal proteins with experimental evidence for sub-peroxisomal localisation. We further show that the proposed approach can be easily adapted (In-Mito) to the prediction of mitochondrial protein localisation obtaining performances for certain classes of proteins (matrix and inner-membrane) superior to existing tools.     

Detection of mutagenic potential of some glass–ionomer cements through Ames testing

The mutagenic potential of three commercially available glass–ionomer cements used in dentistry was examined. The cement components were mixed according to the manufacturers indications and set for two defined times: 1 h or, alternatively, 1 wk. Cements B and C set spontaneously; in the case of cement A, the manufacturer suggests the use of a lamp to trigger also a photopolymerization. Photopolymerization, however, was not used. Ames tests were performed on the dimethyl sulphoxide extracts of cements by using Salmonella typhimurium strains TA 98, TA 100, TA 1535, TA 1537, TA 1538 and TA 102. Cement A showed mutagenicity only against TA 1537 strain, either in the presence or absence of metabolic activation with microsomial fraction S9. The other two cements showed no mutagenic potential. We conclude that glass–ionomer cements are, on the whole, safe materials from the viewpoint of genotoxicity, and hypothesize that the mutagenicity observed in cement A could depend on its polymerization performed without light activation. © 1998 Chapman & Hall     

Symbolic compaction with analogue constraints

A tool named SPARCS-A for compaction of integrated circuits with analogue constraints is presented. the approach is structured in two steps. First a robust and efficient constraint graph compaction algorithm produces a compacted layout quickly, where parasitics are controlled so as to guarantee that the performance constraints are met. Next the layout produced by the first step is fed into a linear programming (LP) solver which enforces symmetries and performs global interconnect length minimization. the computational cost of the iterative LP solver is modest, because its initial state is the configuration found by the constraint graph algorithm and only symmetry constraints need to be enforced. With considerable computational efficiency this algorithm produces a compacted layout which satisfies the high-level performance constraints and is feasible for practical use within industrial-strength analogue synthesis systems. the use of such a compactor allows one to relax the requirements on parasitic control during placement and routing, thus improving the efficiency of the entire layout design process.     

Issues About Retinex Theory and Contrast Enhancement

We present an interpretation of Land’s Retinex theory that we show to be consistent with the original formulation. The proposed model relies on the computation of the expectation value of a suitable random variable weighted with a kernel function, thus the name Kernel-Based Retinex (KBR) for the corresponding algorithm. KBR shares the same intrinsic characteristics of the original Retinex: it can reduce the effect of a color cast and enhance details in low-key images but, since it can only increase pixel intensities, it is not able to enhance over-exposed pictures. Comparing the analytical structure of KBR with that of a recent variational model of color image enhancement, we are able to perform an analysis of the action of KBR on contrast, showing the need to anti-symmetrize its equation in order to produce a two-sided contrast modification, able to enhance both under and over-exposed pictures. The anti-symmetrized KBR equations show clear correspondences with other existing color correction models, in particular ACE, whose relationship with Retinex has always been difficult to clarify. Finally, from an image processing point of view, we mention that both KBR and its antisymmetric version are free from the chromatic noise due to the use of paths in the original Retinex implementation and that they can be suitably approximated in order to reduce their computational complexity from to , being N the number of input pixels.