A preliminary study of a new multi-objective optimization algorithm

This paper presents a preliminary study which describes and evaluates a multi-objective (MO) version of a recently created single objective (SO) optimization algorithm called the "Alliance Algorithm" (AA). The algorithm is based on the metaphorical idea that several tribes, with certain skills and resource needs, try to conquer an environment for their survival and to ally together to improve the likelihood of conquest. The AA has given promising results in several fields to which has been applied, thus the development of a MO variant (MOAA) is a natural extension. Here the MOAA's performance is compared with two well-known MO algorithms: NSGA-II and SPEA-2. The performance measures chosen for this study are the convergence and diversity metrics. The benchmark functions chosen for the comparison are from the ZDT and OKA families and the main classical MO problems. The results show that the three algorithms have similar overall performance. Thus, it is not possible to identify a best algorithm for all the problems; the three algorithms show a certain complementarity because they offer superior performance for different classes of problems. © 2012 IEEE.

The multi-weight neuron with geometry algorithm and its application

A novel approach for multi-dimension signals processing, that is multi-weight neural network based on high dimensional geometry theory, is proposed. With this theory, the geometry algorithm for building the multi-weight neuron is mentioned. To illustrate the advantage of the novel approach, a Chinese speech emotion recognition experiment has been done. From this experiment, the human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. And the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. Compared with traditional GSVM model, the new method has its superiority. It is noted that this method has significant values for researches and applications henceforth.

Application of multi-weighted neuron for iris recognition

In this paper, from the cognition science point of view, we constructed a neuron of multi-weighted neural network, and proposed a new method for iris recognition based on multi-weighted neuron. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the correct rejection rate is 98.9%, the correct cognition rate and the error recognition rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the correct rejection rate of the test samples excluded in the classes of training samples is very high. It proves the proposed method for iris recognition is effective.

Genetic mechanisms of multi-antimicrobial resistance in a pathogenic Edwardsiella tarda strain

TX01, a pathogenic Edwardsiella tarda strain isolated from diseased fish at an epidemic-inflicted fish farm in China, exhibits resistance to multiple classes of antimicrobial agents. The genes (kn(R). catA3, and tet(A), respectively) encoding resistance to kanamycin, chloramphenicol, and tetracycline were cloned and found to be 99-100% identical to the corresponding genes carried by known plasmids and transposons of human, animal, and environmental isolates. Further study demonstrated that TX01 harbors a plasmid, pETX, which proved to be (i) the carrier of the tet and cut operons; (ii) a mobile genetic element that is capable of transferring between bacteria of different genera. These results, which, to our knowledge, documented for the first time the co-existence of chloramphenicol and tetracycline resistance determinants on a conjugative plasmid in a pathogenic E tarda strain, indicated that gene acquisition via horizontal transferring of pETX-like mobile genetic entities may have played an important part in the dissemination of antimicrobial resistance and that there have existed for some time widespread genetic exchanges between bacteria of human, animal/fish, and environmental origins. (C) 2008 Elsevier B.V. All rights reserved.

Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics

Struyf, J., Dzeroski, S. Blockeel, H. and Clare, A. (2005) Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. In proceedings of the EPIA 2005 CMB Workshop

Early biomarkers to predict grade of encephalopathy following hypoxic ischaemic injury

The standard early markers for identifying and grading HIE severity, are not sufficient to ensure all children who would benefit from treatment are identified in a timely fashion. The aim of this thesis was to explore potential early biomarkers of HIE. Methods: To achieve this a cohort of infants with perinatal depression was prospectively recruited. All infants had cord blood samples drawn and biobanked, and were assessed with standardised neurological examination, and early continuous multi-channel EEG. Cord samples from a control cohort of healthy infants were used for comparison. Biomarkers studied included; multiple inflammatory proteins using multiplex assay; the metabolomics profile using LC/MS; and the miRNA profile using microarray. Results: Eighty five infants with perinatal depression were recruited. Analysis of inflammatory proteins consisted of exploratory analysis of 37 analytes conducted in a sub-population, followed by validation of all significantly altered analytes in the remaining population. IL-6 and IL-6 differed significantly in infants with a moderate/severely abnormal vs. a normal-mildly abnormal EEG in both cohorts (Exploratory: p=0.016, p=0.005: Validation: p=0.024, p=0.039; respectively). Metabolomic analysis demonstrated a perturbation in 29 metabolites. A Cross- validated Partial Least Square Discriminant Analysis model was developed, which accurately predicted HIE with an AUC of 0.92 (95% CI: 0.84-0.97). Analysis of the miRNA profile found 70 miRNA significantly altered between moderate/severely encephalopathic infants and controls. miRNA target prediction databases identified potential targets for the altered miRNA in pathways involved in cellular metabolism, cell cycle and apoptosis, cell signaling, and the inflammatory cascade. Conclusion: This thesis has demonstrated that the recruitment of a large cohortof asphyxiated infants, with cord blood carefully biobanked, and detailed early neurophysiological and clinical assessment recorded, is feasible. Additionally the results described, provide potential alternate and novel blood based biomarkers for the identification and assessment of HIE.

Multi-program benchmark definition

© 2015 IEEE.Although definition of single-program benchmarks is relatively straight-forward-a benchmark is a program plus a specific input-definition of multi-program benchmarks is more complex. Each program may have a different runtime and they may have different interactions depending on how they align with each other. While prior work has focused on sampling multiprogram benchmarks, little attention has been paid to defining the benchmarks in their entirety. In this work, we propose a four-tuple that formally defines multi-program benchmarks in a well-defined way. We then examine how four different classes of benchmarks created by varying the elements of this tuple align with real-world use-cases. We evaluate the impact of these variations on real hardware, and see drastic variations in results between different benchmarks constructed from the same programs. Notable differences include significant speedups versus slowdowns (e.g., +57% vs -5% or +26% vs -18%), and large differences in magnitude even when the results are in the same direction (e.g., 67% versus 11%).

The prognosis of incurable cachectic cancer patients on home parenteral nutrition: A multi-centre observational study with prospective follow-up of 414 patients

Background: The role of home parenteral nutrition (HPN) in incurable cachectic cancer patients unable to eat is extremely controversial. The aim of this study is to analyse which factors can influence the outcome. Patients and methods: We studied prospectively 414 incurable cachectic (sub)obstructed cancer patients receiving HPN and analysed the association between patient or clinical characteristics and surviving status. Results: Median weight loss, versus pre-disease and last 6-month period, was 24% and 16%, respectively. Median body mass index was 19.5, median KPS was 60, median life expectancy was 3 months. Mean/median survival was 4.7/3.0 months; 50.0% and 22.9% of patients survived 3 and 6 months, respectively. At the multivariable analysis, the variables significantly associated with 3- and 6-month survival were Glasgow Prognostic Score (GPS) and KPS, and GPS, KPS and tumour spread, respectively. By the aggregation of the significant variables, it was possible to dissect several classes of patients with different survival probabilities. Conclusions: The outcome of cachectic incurable cancer patients on HPN is not homogeneous. It is possible to identify groups of patients with a ≥6-month survival (possibly longer than that allowed in starvation). The indications for HPN can be modulated on these clinical/biochemical indices. © The Author 2013. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved.

Multi-physics-multi-scale simulation and optimisation: the next generation

FEA and CFD analysis is becoming ever more complex with an emerging demand for simulation software technologies that can address ranges of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and length scales. Computation modelling of such problems requires software technologies that enable the representation of these complex suites of 'physical' interactions. This functionality requires the structuring of simulation modules for specific physical phemonmena so that the coupling can be effectiely represented. These 'multi-physics' and 'multi-scale' computations are very compute intensive and so the simulation software must operate effectively in parallel if it is to be used in this context. Of course the objective of 'multi-physics' and 'multi-scale' simulation is the optimal design of engineered systems so optimistation is an important feature of such classes of simulation. In this presentation, a multi-disciplinary approach to simulation based optimisation is described with some key examples of application to challenging engineering problems.

Computational modelling of multi-physics and multi-scale processes in parallel

This paper provides an overview of the developing needs for simulation software technologies for the computational modelling of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and space scales. Computational modelling of such problems requires software tech1nologies that enable the mathematical description of the interacting physical phenomena together with the solution of the resulting suites of equations in a numerically consistent and compatible manner. This functionality requires the structuring of simulation modules for specific physical phenomena so that the coupling can be effectively represented. These multi-physics and multi-scale computations are very compute intensive and the simulation software must operate effectively in parallel if it is to be used in this context. An approach to these classes of multi-disciplinary simulation in parallel is described, with some key examples of application to2 challenging engineering problems.

Development of a rapid, multi-class method for the confirmatory analysis of anti-inflammatory drugs in bovine milk using liquid chromatography tandem mass spectrometry

A rapid liquid chromatography tandem mass spectrometry (LC-MS/MS) method has been developed and validated for the simultaneous identification, confirmation and quantitation of seven licensed anti-inflammatory drugs (AIDS) in bovine milk. The method was validated in accordance with the criteria defined in Commission Decision 2002/657/EC. Two classes of AIDS were investigated, corticosteroids and non-steroidal anti-inflammatory drugs (NSAIDs). The developed method is capable of detecting and confirming dexamethasone (DXM), betamethasone (BTM), prednisolone (FRED), tolfenamic acid (TV), 5-hydroxy flunixin (5-OH-FLU). meloxicam (MLX) and 4-methyl amino antipyrine (4-MAA) at their associated maximum residue limits (MRLs). These compounds represent all the corticosteroids and NSAIDs licensed for use in bovine animals producing milk for human consumption. These compounds have never been analysed before in the same method and also 4-methyl amino antipyrine has never been analysed with the other licensed NSAIDs. The method can be considered rapid as permits the analysis of up to 30 samples in one day. Milk samples are extracted with acetonitrile; sodium chloride is added to aid partition of the milk and acetonitrile mixture. The acetonitrile extract is then subjected to liquid-liquid purification by the addition of hexane. The purified extract is finally evaporated to dryness and reconstituted in a water/acetonitrile mixture and determination is carried out by LC-MS/MS. Decision limit (CC alpha) values and detection capability (CC beta) values have been established for each compound. (C) 2009 Elsevier B.V. All rights reserved.

Parallel patterns + Macro Data Flow for multi-core programming

Data flow techniques have been around since the early '70s when they were used in compilers for sequential languages. Shortly after their introduction they were also consideredas a possible model for parallel computing, although the impact here was limited. Recently, however, data flow has been identified as a candidate for efficient implementation of various programming models on multi-core architectures. In most cases, however, the burden of determining data flow "macro" instructions is left to the programmer, while the compiler/run time system manages only the efficient scheduling of these instructions. We discuss a structured parallel programming approach supporting automatic compilation of programs to macro data flow and we show experimental results demonstrating the feasibility of the approach and the efficiency of the resulting "object" code on different classes of state-of-the-art multi-core architectures. The experimental results use different base mechanisms to implement the macro data flow run time support, from plain pthreads with condition variables to more modern and effective lock- and fence-free parallel frameworks. Experimental results comparing efficiency of the proposed approach with those achieved using other, more classical, parallel frameworks are also presented. © 2012 IEEE.

Multi-detection of Paralytic, Diarrheic and Amnesic Shellfish Toxins by an Inhibition Immunoassay Using a Microsphere-Flow Cytometry System

The presence of paralytic shellfish poisoning (PSP), diarrheic shellfish poisoning (DSP) and amnesic shellfish poisoning (ASP) toxins in seafood is a severe and growing threat to human health. In order to minimize the risks of human exposure, the maximum content of these toxins in seafood has been limited by legal regulations worldwide. The regulated limits are established in equivalents of the main representatives of the groups: saxitoxin (STX), okadaic acid (OA) and domoic acid (DA), for PSP, DSP and ASP, respectively. In this study a multi-detection method to screen shellfish samples for the presence of these toxins simultaneously was developed. Multiplexing was achieved using a solid-phase microsphere assay coupled to flow-fluorimetry detection, based on the Luminex xMap technology. The multi-detection method consists of three simultaneous competition immunoassays. Free toxins in solution compete with STX, OA or DA immobilized on the surface of three different classes of microspheres for binding to specific monoclonal antibodies. The IC50 obtained in buffer was similar in single- and multi-detection: 5.6 ± 1.1 ng/mL for STX, 1.1 ± 0.03 ng/mL for OA and 1.9 ± 0.1 ng/mL for DA. The sample preparation protocol was optimized for the simultaneous extraction of STX, OA and DA with a mixture of methanol and acetate buffer. The three immunoassays performed well with mussel and scallop matrixes displaying adequate dynamic ranges and recovery rates (around 90 % for STX, 80 % for OA and 100 % for DA). This microsphere-based multi-detection immunoassay provides an easy and rapid screening method capable of detecting simultaneously in the same sample three regulated groups of marine toxins.

Type Synthesis of 3-DOF Multi-Mode Translational/Spherical Parallel Mechanisms with Lockable Joints

A 3-DOF (degrees-of-freedom) multi-mode translational/spherical PM (parallel mechanism) with lockable joints is a novel reconfigurable PM. It has both 3-DOF spatial translational operation mode and 3-DOF spherical operation mode. This paper presents an approach to the type synthesis of translational/spherical PMs with lockable joints. Using the proposed approach, several 3-DOF translational/spherical PMs are obtained. It is found that these translational/spherical PMs do not encounter constraint singular configurations and self-motion of sub-chain of a leg during reconfiguration. The approach can also be used for synthesizing other classes of multi-mode PMs with lockable joints, multi-mode PMs with variable kinematic joints, partially decoupled PMs, and reconfigurable PMs with a reconfigurable platform.

Multi-detection method for five common microalgal toxins based on the use of microspheres coupled to a flow-cytometry system

Freshwater and brackish microalgal toxins, such as microcystins, cylindrospermopsins, paralytic toxins, anatoxins or other neurotoxins are produced during the overgrowth of certain phytoplankton and benthic cyanobacteria, which includes either prokaryotic or eukaryotic microalgae. Although, further studies are necessary to define the biological role of these toxins, at least some of them are known to be poisonous to humans and wildlife due to their occurrence in these aquatic systems. The World Health Organization (WHO) has established as provisional recommended limit 1 μg of microcystin-LR per liter of drinking water. In this work we present a microsphere-based multi-detection method for five classes of freshwater and brackish toxins: microcystin-LR (MC-LR), cylindrospermopsin (CYN), anatoxin-a (ANA-a), saxitoxin (STX) and domoic acid (DA). Five inhibition assays were developed using different binding proteins and microsphere classes coupled to a flow-cytometry Luminex system. Then, assays were combined in one method for the simultaneous detection of the toxins. The IC₅₀'s using this method were 1.9 ± 0.1 μg L⁻¹ MC-LR, 1.3 ± 0.1 μg L⁻¹ CYN, 61 ± 4 μg L⁻¹ ANA-a, 5.4 ± 0.4 μg L⁻¹ STX and 4.9 ± 0.9 μg L⁻¹ DA. Lyophilized cyanobacterial culture samples were extracted using a simple procedure and analyzed by the Luminex method and by UPLC–IT-TOF-MS. Similar quantification was obtained by both methods for all toxins except for ANA-a, whereby the estimated content was lower when using UPLC–IT-TOF-MS. Therefore, this newly developed multiplexed detection method provides a rapid, simple, semi-quantitative screening tool for the simultaneous detection of five environmentally important freshwater and brackish toxins, in buffer and cyanobacterial extracts.