1H-NMR and mass spectrometric characterization of the metabolic response of juvenile Atlantic salmon (Salmo salar) to long-term handling stress

Stressors of various kinds constantly affect fish both in the wild and in culture, examples being acute water temperature and quality changes, predation, handling, and confinement. Known physiological responses of fish to stress such as increases in plasma cortisol and glucose levels, are considered to be adaptive, allowing the animal to cope in the short term. Prolonged exposure to stressors however, has the potential to affect growth, immune function, and survival. Nonetheless, little is known about the mechanisms underlying the long-term stress response. We have investigated the metabolic response of juvenile Atlantic salmon (Salmo salar) to long-term handling stress by analyzing fish plasma via ¹H nuclear magnetic resonance spectroscopy and ultra high performance liquid chromatography–mass spectrometry (UPLC–MS), and comparing results with controls. Analysis of NMR data indicated a difference in the metabolic profiles of control and stressed fish after 1 week of stress with a maximum difference observed after 2 weeks. These differences were associated with stress-induced increases in phosphatidyl choline, lactate, carbohydrates, alanine, valine and trimethylamine-N-oxide, and decreases in low density lipoprotein, very low density lipoprotein, and lipid. UPLC-MS data showed differences at week 2, associated with another set of compounds, tentatively identified on the basis of their mass/charge. Overall the results provided a multi-faceted view of the response of fish to long-term handling stress, indicating that the metabolic disparity between the control and stress groups increased to week 2, but declined by weeks 3 and 4, and revealed several new molecular indicators of long-term stress.

An effective heuristic for stockyard planning and machinery scheduling at a coal handling facility

Coal handling is a complex process involving different correlated and highly dependent operations such as selecting appropriate product types, planning stockpiles, scheduling stacking and reclaiming activities and managing train loads. Planning these operations manually is time consuming and can result in non-optimized schedules as future impact of decisions may not be appropriately considered. This paper addresses the operational scheduling of the continuous coal handling problem with multiple conflicting objectives. As the problem is NP-hard in nature, an effective heuristic is presented for planning stockpiles and scheduling resources to minimize delays in production and the coal age in the stockyard. A model of stockyard operations within a coal mine is described and the problem is formulated as a Bi- Objective Optimization Problem (BOOP). The algorithm efficacy is demonstrated on different real-life data scenarios. Computational results show that the solution algorithm is effective and the coal throughput is substantially impacted by the conflicting objectives. Together, the model and the proposed heuristic, can act as a decision support system for the stockyard planner to explore the effects of alternative decisions, such as balancing age and volume of stockpiles, and minimizing conflicts due to stacker and reclaimer movements.

Evolutionary optimization: a big data perspective

Stochastic search techniques such as evolutionary algorithms (EA) are known to be better explorer of search space as compared to conventional techniques including deterministic methods. However, in the era of big data like most other search methods and learning algorithms, suitability of evolutionary algorithms is naturally questioned. Big data pose new computational challenges including very high dimensionality and sparseness of data. Evolutionary algorithms' superior exploration skills should make them promising candidates for handling optimization problems involving big data. High dimensional problems introduce added complexity to the search space. However, EAs need to be enhanced to ensure that majority of the potential winner solutions gets the chance to survive and mature. In this paper we present an evolutionary algorithm with enhanced ability to deal with the problems of high dimensionality and sparseness of data. In addition to an informed exploration of the solution space, this technique balances exploration and exploitation using a hierarchical multi-population approach. The proposed model uses informed genetic operators to introduce diversity by expanding the scope of search process at the expense of redundant less promising members of the population. Next phase of the algorithm attempts to deal with the problem of high dimensionality by ensuring broader and more exhaustive search and preventing premature death of potential solutions. To achieve this, in addition to the above exploration controlling mechanism, a multi-tier hierarchical architecture is employed, where, in separate layers, the less fit isolated individuals evolve in dynamic sub-populations that coexist alongside the original or main population. Evaluation of the proposed technique on well known benchmark problems ascertains its superior performance. The algorithm has also been successfully applied to a real world problem of financial portfolio management. Although the proposed method cannot be considered big data-ready, it is certainly a move in the right direction.

A new interval-based method for handling non-monotonic information

The focus of this paper is on handling non-monotone information in the modelling process of a single-input target monotone system. On one hand, the monotonicity property is a piece of useful prior (or additional) information which can be exploited for modelling of a monotone target system. On the other hand, it is difficult to model a monotone system if the available information is not monotonically-ordered. In this paper, an interval-based method for analysing non-monotonically ordered information is proposed. The applicability of the proposed method to handling a non-monotone function, a non-monotone data set, and an incomplete and/or non-monotone fuzzy rule base is presented. The upper and lower bounds of the interval are firstly defined. The region governed by the interval is explained as a coverage measure. The coverage size represents uncertainty pertaining to the available information. The proposed approach constitutes a new method to transform non-monotonic information to interval-valued monotone system. The proposed interval-based method to handle an incomplete and/or non-monotone fuzzy rule base constitutes a new fuzzy reasoning approach.

An online transfer learning RBF neural network for cross domain data classification

In this paper, a Radial Basis Function Network (RBFN) trained with the Dynamic Decay Adjustment (DDA) algorithm (i.e., RBFNDDA) is deployed as an incremental learning model for tackling transfer learning problems. An online learning strategy is exploited to allow the RBFNDDA model to transfer knowledge from one domain and applied to classification tasks in a different yet related domain. An experimental study is carried out to evaluate the effectiveness of the online RBFNDDA model using a benchmark data set obtained from a public domain. The results are analyzed and compared with those from other methods. The outcomes positively reveal the potentials of the online RBFNDDA model in handling transfer learning tasks. © 2014 The authors and IOS Press. All rights reserved.

The effects of military body armour on trunk and hip kinematics during performance of manual handling tasks

Musculoskeletal injuries are reported as burdening the military. An identified risk factor for injury is carrying heavy loads; however, soldiers are also required to wear their load as body armour. To investigate the effects of body armour on trunk and hip kinematics during military-specific manual handling tasks, 16 males completed 3 tasks while wearing each of 4 body armour conditions plus a control. Three-dimensional motion analysis captured and quantified all kinematic data. Average trunk flexion for the weightiest armour type was higher compared with control during the carry component of the ammunition box lift (p < 0.001) and sandbag lift tasks (p < 0.001). Trunk rotation ROM was lower for all armour types compared with control during the ammunition box place component (p < 0.001). The altered kinematics with body armour occurred independent of armour design. In order to optimise armour design, manufacturers need to work with end-users to explore how armour configurations interact with range of personal and situational factors in operationally relevant environments. Practitioner Summary: Musculoskeletal injuries are reported as burdening the military and may relate to body armour wear. Body armour increased trunk flexion and reduced trunk rotation during military-specific lifting and carrying tasks. The altered kinematics may contribute to injury risk, but more research is required.

Leakage Detection And Localization Method Based On A Hybrid Inverse/Direct Modelling Approach Suitable For Handling Multiple-Leak Scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

Employing 2D Projections for Fast Visual Exploration of Large Fiber Tracking Data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Methodology proposal for acquisition of biotelemetric data in a real time

This work presents a methodological proposal for acquisition of biometric data through telemetry basing its development on a research-action and a case study. Nowadays, the qualified professionals of physical evaluation have to use specific devices to obtain biometric signals and data. These devices in the most of the time are high cost and difficult to use and handling. Therefore, the methodological proposal was elaborate in order to develop, conceptually, a bio telemetric device which could acquire the desirable biometric signals: oxymetry, biometrics, corporal temperature and pedometry which are essential for the area of physical evaluation. It was researched the existent biometrics sensors, the possible ways for the remote transmission of signals and the computer systems available so that the acquisition of data could be possible. This methodological proposal of remote acquisition of biometrical signals is structured in four modules: Acquisitor of biometrics data; Converser and transmitter of biometric signals; Receiver and Processor of biometrics signals and Generator of Interpretative Graphs. The modules aim the obtention of interpretative graphics of human biometric signals. In order to validate this proposal a functional prototype was developed and it is presented in the development of this work.

30° inclination in handles of plastic boxes can reduce postural and muscular workload during handling

CONTEXTUALIZAÇÃO:O manuseio de materiais está ainda presente nos setores industriais e é associado a lesões na coluna lombar e membros superiores. A inserção de alças em caixas industriais é uma forma de reduzir os riscos relacionados à tarefa, porém a posição e a angulação das alças, que são fatores importantes para o conforto e segurança durante o manuseio, são ainda pouco investigadas objetivamente.OBJETIVOS:Comparar o manuseio de uma caixa comercial e de protótipos com alças e avaliar seus efeitos na postura de membros superiores, atividade elétrica muscular e percepção de agradabilidade em diferentes empunhaduras durante manuseio entre diferentes alturas.MÉTODO:Trinta e sete voluntários saudáveis avaliaram as alças dos protótipos que possibilitavam mudança nas posições (superior e inferior) e angulações (0°, 15° e 30º). Os movimentos dos punhos, cotovelos e ombros foram avaliados por meio da eletrogoniometria e inclinometria. A atividade elétrica muscular dos extensores do punho, bíceps braquial e porção superior do trapézio foi avaliada por um eletromiógrafo portátil. Os registros de movimento e atividade elétrica muscular foram sincronizados. Aspectos subjetivos de agradabilidade foram avaliados por meio de uma escala visual analógica.RESULTADOS E CONCLUSÕES:Os protótipos com alças inclinadas em 30° apresentaram as melhores avaliações de agradabilidade, posturas mais neutras de punho, menores níveis de atividade eletromiográfica do trapézio superior e menores ângulos de elevação dos braços. Os diferentes métodos de medida se mostraram complementares para a avaliação dos membros superiores durante as tarefas de manuseio.

Long-term obesity promotes alterations in diastolic function induced by reduction of phospholamban phosphorylation at serine-16 without affecting calcium handling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

MR-Radix: a multi-relational data mining algorithm

Background: Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods: Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results: This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion: The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.

The evolution of phylogeographic data sets

Empirical phylogeographic studies have progressively sampled greater numbers of loci over time, in part motivated by theoretical papers showing that estimates of key demographic parameters improve as the number of loci increases. Recently, next-generation sequencing has been applied to questions about organismal history, with the promise of revolutionizing the field. However, no systematic assessment of how phylogeographic data sets have changed over time with respect to overall size and information content has been performed. Here, we quantify the changing nature of these genetic data sets over the past 20years, focusing on papers published in Molecular Ecology. We found that the number of independent loci, the total number of alleles sampled and the total number of single nucleotide polymorphisms (SNPs) per data set has improved over time, with particularly dramatic increases within the past 5years. Interestingly, uniparentally inherited organellar markers (e.g. animal mitochondrial and plant chloroplast DNA) continue to represent an important component of phylogeographic data. Single-species studies (cf. comparative studies) that focus on vertebrates (particularly fish and to some extent, birds) represent the gold standard of phylogeographic data collection. Based on the current trajectory seen in our survey data, forecast modelling indicates that the median number of SNPs per data set for studies published by the end of the year 2016 may approach similar to 20000. This survey provides baseline information for understanding the evolution of phylogeographic data sets and underscores the fact that development of analytical methods for handling very large genetic data sets will be critical for facilitating growth of the field.

Gestational protein malnutrition impairs c-myc and p63 protein expression, increases prostatic intraepithelial neoplasia incidence and prostatitis aggressiveness in adult male offspring subjected to hormonal handling

Background: Prostate cancer is the second most common cancer diagnosed in men; however its etiology remains unknown. Previous studies have shown that environmental adverse factors, such as maternal nutritional status during pregnancy, can influence fetal development and predispose people to diseases in adult life. The feeding of low-protein diets to pregnant rats result in fetal growth disturbance, androgen/estrogen unbalance and changes in the expression and sensibility of hormone receptors in male offspring. These alterations can promote permanent changes in androgen dependent organs, such as in the prostate. In this sense, we hypothesized that the hormonal unbalance that occurs during aging can lead to an increase in the susceptibility to prostatic disorders. Aim: To evaluate our hypothesis, malnourished male rat offspring were submitted to simultaneous estrogen and testosterone exposure in adulthood, to drive lesions in the rat ventral prostate gland (VP). Methods: 17 week-old Wistar rats (n=48) that received in utero normal protein diet (NP group, AIN93G=17% protein) or low protein diet (RP group, AIN93G modified=6% protein) were given implants with 17β-estradiol plus testosterone administration (NPH and RPH groups) for 17 weeks. The animals were killed at the age of 34 weeks and the VP were excised, weighted and processed for histopathological, immunohistochemical (Ki67, AR, p63, e-caderin, laminin, c-myc and GSTP), biochemical and ultrastructural analysis. Results: Both absolute and relative VP weight from NPH animals were about 30% higher than RPH. Serological data showed that estradiol levels were similar in both groups, but testosterone levels were lower in the RPH male offspring. The steroid hormone exposure in adult life promoted prostate lesions in both RPH and NPH offspring associated with reactive stroma. VP from RPH group exhibited heightened susceptibility to prostatic intraepithelial neoplasia (mainly cribriform and signet ring-cell patterns) and increased the incidence and aggressiveness of prostatitis. In this group, a higher proportion of basal cells, increased proliferation index, lower expression ofthe androgen receptor and increased focus of collagenous micronodules closely associated to epithelial neoplasias were also observed. Conclusion:These observations suggest that maternal protein restriction alters adult prostate response to androgen/estrogen handling and increases susceptibility to prostate diseases. Ethical protocol:CEEA,476/2013 IBB-UNESP; Funding Support: 2009/50204-6 and 2013/09649-0.

A Model-Based Approach for Making Ecological Inference from Distance Sampling Data

We consider a fully model-based approach for the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study area. There is, however, no readily available method of making statistical inference on the relationships between abundance and environmental covariates. Spatial Poisson process likelihoods can be used to simultaneously estimate detection and intensity parameters by modeling distance sampling data as a thinned spatial point process. A model-based spatial approach to distance sampling data has three main benefits: it allows complex and opportunistic transect designs to be employed, it allows estimation of abundance in small subregions, and it provides a framework to assess the effects of habitat or experimental manipulation on density. We demonstrate the model-based methodology with a small simulation study and analysis of the Dubbo weed data set. In addition, a simple ad hoc method for handling overdispersion is also proposed. The simulation study showed that the model-based approach compared favorably to conventional distance sampling methods for abundance estimation. In addition, the overdispersion correction performed adequately when the number of transects was high. Analysis of the Dubbo data set indicated a transect effect on abundance via Akaike’s information criterion model selection. Further goodness-of-fit analysis, however, indicated some potential confounding of intensity with the detection function.