(Table S1) Boron isotope and trace element data and reconstructed carbonate system parameters, ODP Holes 122-761B and 154-926A

The middle Miocene Climatic Optimum (17-15 Ma; MCO) is a period of global warmth and relatively high CO2 and is thought to be associated with a significant retreat of the Antarctic Ice Sheet (AIS). We present here a new planktic foraminiferal d11B record from 16.6 to 11.8 Ma from two deep ocean sites currently in equilibrium with the atmosphere with respect to CO2. These new data demonstrate that the evolution of global climate during the middle Miocene (as reflected by changes in the cyrosphere) was well correlated to variations in the concentration of atmospheric CO2. What is more, within our sampling resolution (~1 sample per 300 kyr) there is no evidence of hysteresis in the response of ice volume to CO2 forcing during the middle Miocene, contrary to what is understood about the Antarctic Ice Sheet from ice sheet modelling studies. In agreement with previous data, we show that absolute levels of CO2 during the MCO were relatively modest (350-400 ppm) and levels either side of the MCO are similar or lower than the pre-industrial (200-260 ppm). These new data imply the presence of either a very dynamic AIS at relatively low CO2 during the middle Miocene or the advance and retreat of significant northern hemisphere ice. Recent drilling on the Antarctic margin and shore based studies indicate significant retreat and advance beyond the modern limits of the AIS did occur during the middle Miocene, but the complete loss of the AIS was unlikely. Consequently, it seems that ice volume and climate variations during the middle Miocene probably involved a more dynamic AIS than the modern but also some component of land-based ice in the northern hemisphere.

Water chemistry, carbonate system parameters, and macro-organism biomass of vent and off-vent sites in the Columbretes Islands Marine Reserve

Ocean acidification is receiving increasing attention because of its potential to affect marine ecosystems. Rare CO2 vents offer a unique opportunity to investigate the response of benthic ecosystems to acidification. However, the benthic habitats investigated so far are mainly found at very shallow water (less than or equal to 5 m depth) and therefore are not representative of the broad range of continental shelf habitats. Here, we show that a decrease from pH 8.1 to 7.9 observed in a CO2 vent system at 40 m depth leads to a dramatic shift in highly diverse and structurally complex habitats. Forests of the kelp Laminaria rodriguezii usually found at larger depths (greater than 65 m) replace the otherwise dominant habitats (i.e. coralligenous outcrops and rhodolith beds), which are mainly characterized by calcifying organisms. Only the aragonite-calcifying algae are able to survive in acidified waters, while high-magnesium-calcite organisms are almost completely absent. Although a long-term survey of the venting area would be necessary to fully understand the effects of the variability of pH and other carbonate parameters over the structure and functioning of the investigated mesophotic habitats, our results suggest that in addition of significant changes at species level, moderate ocean acidification may entail major shifts in the distribution and dominance of key benthic ecosystems at regional scale, which could have broad ecological and socio-economic implications.

Analysis of the Variability of Carbonate System Parameters in the North-East Atlantic.

The purpose of this thesis is to analyse the spatial and temporal variability of the aragonite saturation state (ΩAR), commonly used as an indicator of ocean acidification, in the North-East Atlantic. When the aragonite saturation state decreases below a certain threshold, ΩAR <1, calcifying organisms (i.e. molluscs, pteropods, foraminifera, crabs, etc.) are subject to dissolution of shells and aragonite structures. This objective agrees with the challenge 'Ocean, climate change and acidification' of the EU COST Ocean Governance for Sustainability project, which aims to combine the information collected on the state of health of the oceans. Two open-sources data products, EMODnet and GLODAPv2, have been integrated and analysed for the first time in the North-East Atlantic region. The integrated dataset contains 1038 ΩAR vertical profiles whose time distribution spans from 1970 to 2014. The ΩAR has been computed from CO2SYS software considering different combinations of input parameters, pH, Total Alkalinity (TAlk) and Dissolved Inorganic Carbon (DIC), associated with Temperature, Salinity and Pressure at in situ conditions. A sensitivity analysis has been performed to better understand the data consistency of ΩAR computed from the different combinations of pH, Talk and DIC and to verify the difference among observed TAlk and DIC parameters and their output values from the CO2SYS tool. Maps of ΩAR have been computed with the best data coverage obtained from the two datasets, at different levels of depth in the area of investigation and they have been compared to the work of Jiang et al. (2015). The results are consistent and show similar horizontal and vertical patterns. The study highlights some aragonite undersaturated values (ΩAR <1) below 500 meters depth, suggesting a potential effect of acidification in the considered time period. This thesis aims to be a preliminary work for future studies that will be able to design the ΩAR variability on a decadal distribution based on the extended time-series acquired in this work.

Monitoramento de parâmetros imunológicos em atletas adolescentes de basquetebol durante e após a temporada esportiva= : Monitoring of immunological parameters in adolescent basketball athletes during and after a sports season

Universidade Estadual de Campinas . Faculdade de Educação Física

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

Mean motion resonances and the stability of a circumbinary disk in a triple stellar system

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identification of structural parameters for active vibration control

The study of algorithms for active vibration control in flexible structures became an area of enormous interest for some researchers due to the innumerable requirements for better performance in mechanical systems, as for instance, aircrafts and aerospace structures. Intelligent systems, constituted for a base structure with sensors and actuators connected, are capable to guarantee the demanded conditions, through the application of diverse types of controllers. For the project of active controllers it is necessary, in general, to know a mathematical model that enable the representation in the space of states, preferential in modal coordinates to permit the truncation of the system and reduction in the order of the controllers. For practical applications of engineering, some mathematical models based in discrete-time systems cannot represent the physical problem, therefore, techniques of identification of system parameters must be used. The techniques of identification of parameters determine the unknown values through the manipulation of the input (disturbance) and output (response) signals of the system. Recently, some methods have been proposed to solve identification problems although, none of them can be considered as being universally appropriate to all the situations. This paper is addressed to an application of linear quadratic regulator controller in a structure where the damping, stiffness and mass matrices were identified through Chebyshev's polynomial functions.

On the dynamic behaviour of a nonlinear system weakly connected to a linear single degree-of-freedom system

This paper discusses the dynamic behaviour of a nonlinear two degree-of-freedom system consisting of a harmonically excited linear oscillator weakly connected to a nonlinear attachment that behaves as a hardening Duffing oscillator. A system which behaves in this way could be a shaker (linear system) driving a nonlinear isolator. The mass of the nonlinear system is taken to be much less than that in the linear system and thus the nonlinear system has little effect on the dynamics of the linear system. Of particular interest is the situation when the linear natural frequency of the nonlinear system is less than the natural frequency of the linear system such that the frequency response curve of the nonlinear system bends to higher frequencies and thus interacts with the resonance frequency of the linear system. It is shown that for some values of the system parameters a complicated frequency response curve for the nonlinear system can occur; closed detached curves can appear as a part of the overall amplitude-frequency response. The reason why these detached curves appear is presented and approximate analytical expressions for the jump-up and jump-down frequencies of the system under investigation are given.

Effects of macrocyclic lactones on the reproductive parameters of engorged Rhipicephalus (Boophilus) microplus females detached from experimentally infested cattle

The present study therefore assessed the deleterious effects of MLs (ivermectin, abamectin, doramectin and moxidectin) on the reproductive parameters of engorged Rhipicephalus (Boophilus) microplus females that naturally detached from experimentally infested cattle in two experiments. The following reproductive parameters of engorged female ticks were analyzed: female weight, egg mass weight, percentage of hatchability, percentage of reduction in oviposition, percentage of reduction in hatchability, reproductive efficiency and percent control/efficacy of formulations with respect to reproductive parameters. In the experiment I, statistical analysis of the data grouped into 5-days intervals revealed that pour-on application of abamectin (500. mcg/kg) had significantly (p≤. 0.05) reduced engorged female weight, egg mass weight and percent hatchability on days 6-15, 6-20 and 11-20 post-treatment (p. t.) compared to the respective data for detached and pre-selected engorged females in the control group. The abamectin, demonstrated 33.41% of reduction in oviposition, 6.77% in hatchability and abamectin efficacy was of 13.99%. In the experiment II, statistically significant reductions (p≥. 0.05) were observed in animals treated subcutaneous with ivermectin (630. mcg/kg), doramectin (700. mcg/kg) and moxidectin (1000. mcg/kg) relative to the control for days 6-40, 6-48 and 6-40 p. t., respectively. Ivermectin reduced hatchability only on days 16-20 p. t., whereas doramectin significantly reduced (p≤. 0.05) hatchability on days 6-10 and 16-35 p. t. For moxidectin, deleterious effects on hatchability were observed on days 16-35 p. t. The percent reductions in oviposition of engorged female ticks were 46.31%, 62.17% and 61.02% with ivermectin, doramectin and moxidectin treatments, respectively. The percent efficacy of the formulations on the reproductive parameters of engorged female ticks was 21.22% for ivermectin, 36.03% for doramectin and 35.45% for moxidectin. Among the MLs assessed, doramectin and moxidectin had the highest acaricidal efficacies and the most deleterious effects on the reproductive parameters of engorged R. (B.) microplus females. However, future studies will be necessary to assess the extent to which these effects, along with acaricidal activity, can be used to control the ectoparasite in cattle. © 2013 Elsevier Inc..