Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.     

Acoustic scattering solver based on single level FMM for multi-GPU systems

In this paper, we present a heterogeneous parallel solver of a high frequency single level Fast Multipole Method (FMM) for the Helmholtz equation applied to acoustic scattering. The developed solution uses multiple GPUs to tackle the compute bound steps of the FMM (aggregation, disaggregation, and near interactions) while the CPU handles a memory bound step (translation) using OpenMP. The proposed solver performance is measured on a workstation with two GPUs (NVIDIA GTX 480) and is compared with that of a distributed memory solver run on a cluster of 32 nodes (HP BL465c) with an Infiniband network. Some energy efficiency results are also presented in this work.     

mfERG_LAB: Software for processing multifocal electroretinography signals

The multifocal electroretinography technique consists of performing sectorized light excitation of the retina and capturing the resulting evoked potential. This provides functional localized information about the state of the retinal neurons. Analysis of multifocal electroretinography signals can be used for diagnosing different types of optic neuropathies (glaucomatous, demyelinating and ischemic ethiology). In order to obtain a reliable diagnosis, it is necessary to apply advanced processing algorithms (morphological, frequency and time-frequency analysis, etc.) to the multifocal electroretinography signal. This paper presents a software application developed in MATLAB(?) (MathWorks Inc., MA) designed to perform advanced multifocal electroretinography signal analysis and classification. This intuitive application, mfERG_LAB, is used to plot the signals, apply various algorithms to them and present the data in an appropriate format. The application's computational power and modular structure make it suitable for use in clinical settings as a powerful and innovative diagnostic tool, as well as in research and teaching settings as a means of assessing new algorithms.     

Local structural characterization of Zn:Cd:Se ternary semiconductors

We have studied the local atomic structure around Zn and Cd, in CdSe, ZnSe, and ordered and disordered Zn_0.5Cd_0.5Se thin films, grown by molecular beam epitaxy (MBE) and atomic layer epitaxy (ALE) using X-ray absorption spectroscopy (XAS). Zn K-shell X-ray absorption fine structure (XAFS) shows that the Zn–Se pair nearest neighbor distance is the same in both ordered and disordered ternary samples. This result shows that the ordered (or disordered growth) does not have a significant effect in the nearest neighbor Zn environment. However, results from K-shell Cd XAFS show that the Cd–Se pair nearest neighbor distance in the Zn_0.5Cd_0.5Se ordered film exhibits a contraction compared to the same pair distance in the disordered Zn_0.5Cd_0.5Se sample and the binary CdSe compound. This suggests that the shortest Zn–Se nearest neighbor distance regulates the Cd–Se nearest neighbor distance in the ternary compounds, when these are grown in an ordered, layer by layer, fashion.     

Modelling and solving English Peg Solitaire

Peg Solitaire is a well known puzzle, which can prove difficult despite its simple rules. Pegs are arranged on a board such that at least one ‘hole’ remains. By making draughts/checkers-like moves, pegs are gradually removed until no further moves are possible or some goal configuration is achieved. This paper considers the English variant, consisting of a board in a cross shape with 33 holes. Modelling Peg Solitaire via constraint or integer programming techniques presents a considerable challenge and is examined in detail. The merits of the resulting models are discussed and they are compared empirically. The sequential nature of the puzzle naturally conforms to a planning problem, hence we also present an experimental comparison with several leading AI planning systems. Other variants of the puzzle, such as ‘Fool's Solitaire’ and ‘Long-hop’ Solitaire are also considered.     

Perinatal Obesity Induces Hepatic Growth Restriction with Increased DNA Damage Response,Senescence, and Dysregulated Igf-1-Akt-Foxo1 Signaling in Male Offspring of Obese Mice

Maternal obesity predisposes for hepato-metabolic disorders early in life. However, the underlying mechanisms causing early onset dysfunction of the liver and metabolism remain elusive. Since obesity is associated with subacute chronic inflammation and accelerated aging, we test the hypothesis whether maternal obesity induces aging processes in the developing liver and determines thereby hepatic growth. To this end, maternal obesity was induced with high-fat diet (HFD) in C57BL/6N mice and male offspring were studied at the end of the lactation [postnatal day 21 (P21)]. Maternal obesity induced an obese body composition with metabolic inflammation and a marked hepatic growth restriction in the male offspring at P21. Proteomic and molecular analyses revealed three interrelated mechanisms that might account for the impaired hepatic growth pattern, indicating prematurely induced aging processes: (1) Increased DNA damage response (γH2AX), (2) significant upregulation of hepatocellular senescence markers (Cdnk1a, Cdkn2a); and (3) inhibition of hepatic insulin/insulin-like growth factor (IGF)-1-AKT-p38-FoxO1 signaling with an insufficient proliferative growth response. In conclusion, our murine data demonstrate that perinatal obesity induces an obese body composition in male offspring with hepatic growth restriction through a possible premature hepatic aging that is indicated by a pathologic sequence of inflammation, DNA damage, senescence, and signs of a possibly insufficient regenerative capacity.     

Differential Expression of Proteins in an Atypical Presentation of Autoimmune Lymphoproliferative Syndrome

Autoimmune lymphoproliferative syndrome (ALPS) is a rare disease defined as a defect in the lymphocyte apoptotic pathway. Currently, the diagnosis of ALPS is based on clinical aspects, defective lymphocyte apoptosis and mutations in Fas, FasL and Casp 10 genes. Despite this, ALPS has been misdiagnosed. The aim of this work was to go one step further in the knowledge of the disease, through a molecular and proteomic analysis of peripheral blood mononuclear cells (PBMCs) from two children, a 13-year-old girl and a 6-year-old boy, called patient 1 and patient 2, respectively, with clinical data supporting the diagnosis of ALPS. Fas, FasL and Casp10 genes from both patients were sequenced, and a sample of the total proteins from patient 1 was analyzed by label-free proteomics. Pathway analysis of deregulated proteins from PBMCs was performed on the STRING and PANTHER bioinformatics databases. A mutation resulting in an in-frame premature stop codon and protein truncation was detected in the Fas gene from patient 2. From patient 1, the proteomic analysis showed differences in the level of expression of proteins involved in, among other processes, cell cycle, regulation of cell cycle arrest and immune response. Noticeably, the most down-regulated protein is an important regulator of the cell cycle process. This could be an explanation of the disease in patient 1.     

An approach to accidents modeling based on compounds road environments

The most common approach to study the influence of certain road features on accidents has been the consideration of uniform road segments characterized by a unique feature. However, when an accident is related to the road infrastructure, its cause is usually not a single characteristic but rather a complex combination of several characteristics. The main objective of this paper is to describe a methodology developed in order to consider the road as a complete environment by using compound road environments, overcoming the limitations inherented in considering only uniform road segments. The methodology consists of: dividing a sample of roads into segments; grouping them into quite homogeneous road environments using cluster analysis; and identifying the influence of skid resistance and texture depth on road accidents in each environment by using generalized linear models. The application of this methodology is demonstrated for eight roads. Based on real data from accidents and road characteristics, three compound road environments were established where the pavement surface properties significantly influence the occurrence of accidents. Results have showed clearly that road environments where braking maneuvers are more common or those with small radii of curvature and high speeds require higher skid resistance and texture depth as an important contribution to the accident prevention.     

Elevation of Tear MMP-9 Concentration as a Biomarker of Inflammation in Ocular Pathology by Antibody Microarray Immunodetection Assays

Matrix metalloproteinases are a family of enzymes fundamental in inflammatory processes. Between them, MMP-9 is up-regulated during inflammation; thus, its quantification in non-invasive fluids is a promising approach for inflammation identification. To this goal, a biomarker quantification test was developed for ocular inflammation detection using anti-MMP-9 antibody microarrays (AbMAs). After validation with eight healthy control tear samples characterized by ELISA, 20 samples were tested from individuals diagnosed with ocular inflammation due to: cataracts, glaucoma, meibomian gland dysfunction, allergy, or dry eye. Concentration values of tear MMP-9 were obtained for each sample, and 12 patients surpassed the pathological threshold (30 ng/mL). A significant elevation of MMP-9 concentration in the tears of glaucoma patients compared with healthy controls was observed. In order to evaluate the diagnostic ability, an ROC curve analysis was performed using our data, determining the optimal threshold for the test at 33.6 ng/mL of tear MMP-9. In addition, a confusion matrix was applied, estimating sensitivity at 60%, specificity at 88%, and accuracy at 68%. In conclusion, we demonstrated that the AbMAs system allows the quantification of MMP-9 in pathologies that involve inflammation of the ocular surface.     

Synthesis and Biological Evaluation of Small Molecules as Potential Anticancer Multitarget Agents

Twenty-six triazole-based derivatives were designed for targeting both PD-L1 (programmed death receptor ligand 1) and VEGFR-2 (vascular endothelial growth factor receptor 2). These compounds were synthetized and biologically evaluated as multitarget inhibitors of VEGFR-2, PD-L1 and c-Myc proteins. The antiproliferative activity of these molecules on several tumor cell lines (HT-29, A-549, and MCF-7) and on the non-tumor cell line HEK-293 was determined. The effects on the abovementioned biological targets were evaluated for some selected compounds. Compound 23, bearing a p-chlorophenyl group, showed better results than sorafenib in regard to the downregulation of VEGFR-2 and a similar effect to BMS-8 on both PD-L1 and c-Myc proteins. The antiangiogenic and antivascular activities of chloro derivatives were also established by endothelial microtube formation assay on Matrigel^®.