Face recognition with lattice independent component analysis and extreme learning machines

We focus on two aspects of the face recognition, feature extraction and classification. We propose a two component system, introducing Lattice Independent Component Analysis (LICA) for feature extraction and Extreme Learning Machines (ELM) for classification. In previous works we have proposed LICA for a variety of image processing tasks. The first step of LICA is to identify strong lattice independent components from the data. In the second step, the set of strong lattice independent vector are used for linear unmixing of the data, obtaining a vector of abundance coefficients. The resulting abundance values are used as features for classification, specifically for face recognition. Extreme Learning Machines are accurate and fast-learning innovative classification methods based on the random generation of the input-to-hidden-units weights followed by the resolution of the linear equations to obtain the hidden-to-output weights. The LICA-ELM system has been tested against state-of-the-art feature extraction methods and classifiers, outperforming them when performing cross-validation on four large unbalanced face databases.     

Fuzzy ontologies-based user profiles applied to enhance e-learning activities

Nowadays, the impact of technological developments on improving human activities is becoming more evident. In e-learning, this situation is no different. There are common to use systems that assist the daily activities of students and teachers. Typically, e-learning recommender systems are focused on students; however, teachers can also benefit from these type of tools. A recommender system can propose actions and resources that facilitate teaching activities like structuring learning strategies. In any case, a complete user’s representation is required. This paper shows how a fuzzy ontology can be used to represent user profiles into a recommender engine and enhances the user’s activities into e-learning environments. A fuzzy ontology is an extension of domain ontologies for solving the problems of uncertainty in sharing and reusing knowledge on the Semantic Web. The user profile is built from learning objects published by the user himself into a learning object repository. The initial experiment confirms that the automatically obtained fuzzy ontology is a good representation of the user’s preferences. The experiment results also indicate that the presented approach is useful and warrants further research in recommending and retrieval information.     

Optimal configuration of Energy-Efficient Ethernet

The IEEE 802.3az standard provides a new low power mode that Ethernet network interfaces can use to save energy when there is no traffic to transmit. Simultaneously with the final standard approval, several algorithms were proposed to govern the physical interface state transition between the normal active mode and the new low power mode. In fact, the standard leaves this sleeping algorithm unspecified to spur competition among different vendors and achieve the greatest energy savings. In this paper, we try to bring some light to the most well known sleeping algorithms, providing mathematical models for the expected energy savings and the average packet delay inflicted on outgoing traffic. We will then use the models to derive optimum configuration parameters for them under given efficiency constraints.     

A multi-objective approach for the motion planning of redundant manipulators

Kinematic redundancy occurs when a manipulator possesses more degrees of freedom than those required to execute a given task. Several kinematic techniques for redundant manipulators control the gripper through the pseudo-inverse of the Jacobian, but lead to a kind of chaotic inner motion with unpredictable arm configurations. Such algorithms are not easy to adapt to optimization schemes and, moreover, often there are multiple optimization objectives that can conflict between them. Unlike single optimization, where one attempts to find the best solution, in multi-objective optimization there is no single solution that is optimum with respect to all indices. Therefore, trajectory planning of redundant robots remains an important area of research and more efficient optimization algorithms are needed. This paper presents a new technique to solve the inverse kinematics of redundant manipulators, using a multi-objective genetic algorithm. This scheme combines the closed-loop pseudo-inverse method with a multi-objective genetic algorithm to control the joint positions. Simulations for manipulators with three or four rotational joints, considering the optimization of two objectives in a workspace without and with obstacles are developed. The results reveal that it is possible to choose several solutions from the Pareto optimal front according to the importance of each individual objective.     

An XPS and reduction study of PrCoO3

The perovskite-type oxide PrCoO₃ has been studied by means of X-ray photoelectron spectroscopy (XPS), reduction in H₂ and X-ray diffraction. Two types of oxygen were detected: lattice oxygen (binding energy = 528.4 eV) and adsorbed oxygen (binding energy = 530.9 eV). The increase in relative intensity of the peak corresponding to the latter species after reduction of PrCo0₃ to 3e^– per molecule is assigned to the formation of hydroxyl groups. Temperature-programmed reduction (TPR) results showed two reduction steps: to 1 e^– per molecule (Co^3.1 Co²⁺) at 475 to 635 K, and to 3e^– per molecule (Co²¹ Co⁰) at 725 to 815 K. Reduction in the first and second steps occurs according to the contracting sphere model and the nucleation mechanism, respectively. Reduction of Co³⁺ to Co²⁺ causes minimal structural changes in the perovskite. Reduction to 3e^– per molecule yielded Pr₂O₃ and metallic cobalt. After this reduction and reoxidation at 973 K, the perovskite structure was regained. By XPS and TPR it was shown that PrCo0₃ is more easily reducible than LaCo0₃. It is concluded that the cation in the A position of the structure plays a significant role in the bulk and surface properties of LnCo0₃ (Ln, lanthanide elements) oxides.     

Effect of breed-type on the relationships between intramuscular and total body fat in steers

The partitioning of total dissectible body fat and the amounts of intramuscular fat in Psoas major, Semitendinosus and Biceps brachii muscles were determined in two groups of A. Angus and AA × Nelore steers with similar averages of total dissectible fat (27·7 kg). In addition, the fatty acid composition of total fat and the triglyceride fraction from dissectible and intramuscular fats were determined.

The AA × Nelore steers have higher levels of subcutaneous fat and lower levels of intermuscular fat than the A. Angus but contain lower levels of intramuscular fat in the three muscles. The allometric regressions varied according to the muscle and breed type. The fatty acid composition of subcutaneous and kidney fats were similar but differences in the percentages of 14:0, 18:0, 18:2 and 20:4 fatty acids in intramuscular fats between the two genetic groups were detected.     

A study of behavioural groupings of polyphenolic species in "fino" sherry wine. Evolution during vinification and mechanical treatment of the grape

The different groups and/or classes among phenolic acids and aldehydes identified during the elaboration process of "fino" sherry wine have been studied. The study was carried out using different processes during the elaboration of the wine and we have attempted to establish whether the different treatments of the grape affect these groupings. The study was undertaken by means of cluster and multifactorial analysis on the data obtained by the quantitative determination of phenolic acids and aldehydes during vinification and in experiments carried out on the grape under different mechanical treatments. The analysis of phenolic acids and aldehydes was done with HPLC, using a C-18 mu-Bondapak and a stepwise composite gradient. The samples were previously extracted with ethylic ether.     

Structure, hyperfine interactions and magnetization studies of mechanically alloyed Fe50Ge50 and Fe62Ge38

X-ray diffraction, Mössbauer spectroscopy and magnetization measurements were used to study the structure and some magnetic properties of Fe₅₀Ge₅₀ and Fe₆₂Ge₃₈ prepared by mechanical alloying from the elemental powders. In both cases in the early stages of milling the intermediate paramagnetic FeGe₂ phase was formed. The mechanical alloying process of Fe₅₀Ge₅₀ resulted in the formation of the paramagnetic FeGe (B20) phase with an average crystallite size of about 15 nm. In the case of the Fe₆₂Ge₃₈, the ferromagnetic Fe₅Ge₃ (β) phase with a Curie temperature of about 430 K was obtained. The average crystallite size was about 9 nm. The average hyperfine magnetic field of about 16 T allowed it to determine that more than four germanium atoms exist in the nearest environment of the ⁵⁷Fe isotopes in the Fe₅Ge₃ phase.     

MMP1 and MMP11 Expression in Peripheral Blood Mononuclear Cells upon Their Interaction with Breast Cancer Cells and Fibroblasts

Tumor-infiltrating immune cells phenotype is associated with tumor progression. However, little is known about the phenotype of the peripheral blood mononuclear cells (PBMC) from breast cancer patients. We investigated MMP1 and MMP11 expression in PBMC from breast cancer patients and we analyzed gene expression changes upon their interaction with cancer cells and cancer-associated fibroblasts (CAF). We measured the impact of PBMC on proinflammatory gene expression in breast cancer cells, normal fibroblast (NF), and CAF and the impact on proliferation and invasiveness capacity of breast cancer cells. Gene expression of MMP1 and MMP11 in PBMC from breast cancer patients (n = 54) and control (n = 28); expression of IL1A, IL6, IL17, IFNβ, and NFĸB in breast cancer cell lines (MCF-7 and MDA-MB-231); and, additionally, IL10 and MMP11 in CAF and NF were analyzed by qRT-PCR before and after co-culture. Our results show the existence of a subpopulation of breast cancer patients (25.9%) with very high levels of MMP11 gene expression in PBMC. Also, gene expression of MMP1 and MMP11 increases in PBMC after co-culture with breast cancer cell lines, NF or CAF. PBMC from healthy or breast cancer patients induce an increased proliferation rate on MCF-7 and an increased invasiveness capacity of MDA-MB-231. Finally, we show a differential expression profile of inflammatory genes in NF and CAF when co-cultured with control or breast cancer PBMC. We have observed that MMPs’ expression in PBMC is regulated by the microenvironment, while the expression of inflammatory genes in NF or CAF is differentially regulated by PBMC. These findings confirm the importance of the crosstalk between stromal cells and suggest that PBMC would play a role in promoting aggressive tumor behavior.