A Comparison Between Pulse Pressure Variation and Right End Diastolic Volume Index as Guides to Resuscitation in a Model of Hemorrhagic Shock in Pigs

Background: Different hemodynamic parameters including static indicators of cardiac preload as right ventricular end-diastolic volume index (RVEDVI) and dynamic parameters as pulse pressure variation (PPV) have been used in the decision-making process regarding volume expansion in critically ill patients. The objective of this study was to compare fluid resuscitation guided by either PPV or RVEDVI after experimentally induced hemorrhagic shock. Methods: Twenty-six anesthetized and mechanically ventilated pigs were allocated into control (group I), PPV (group II), or RVEDVI (group III) group. Hemorrhagic shock was induced by blood withdrawal to target mean arterial pressure of 40 mm Hg, maintained for 60 minutes. Parameters were measured at baseline, time of shock, 60 minutes after shock, immediately after resuscitation with hydroxyethyl starch 6% (130/0.4), 1 hour and 2 hours thereafter. The endpoint of fluid resuscitation was determined as the baseline values of PPV and RVEDVI. Statistical analysis of data was based on analysis of variance for repeated measures followed by the Bonferroni test (p < 0.05). Results: Volume and time to resuscitation were higher in group III than in group II (group III = 1,305 +/- 331 mL and group II = 965 +/- 245 mL, p < 0.05; and group III = 24.8 +/- 4.7 minutes and group II = 8.8 +/- 1.3 minutes, p < 0.05, respectively). All static and dynamic parameters and biomarkers of tissue oxygenation were affected by hemorrhagic shock and nearly all parameters were restored after resuscitation in both groups. Conclusion: In the proposed model of hemorrhagic shock, resuscitation to the established endpoints was achieved within a smaller amount of time and with less volume when guided by PPV than when guided by pulmonary artery catheter-derived RVEDVI.

A fuzzy Reed-Frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

POLYETHYLENE GLYCOL ADDITION DOES NOT IMPROVE EXOGENOUS SURFACTANT FUNCTION IN AN EXPERIMENTAL MODEL OF MECONIUM ASPIRATION SYNDROME

Meconium (MEC) is a potent inactivator of pulmonary surfactant. The authors studied the effects of polyethylene glycol addition to the exogenous surfactant over the lung mechanics and volumes. Human meconium was administrated to newborn rabbits. Animals were ventilated for 20 minutes and dynamic compliance, ventilatory pressure, and tidal volume were recorded. Animals were randomized into 3 study groups: MEC group (without surfactant therapy); S100 group (100 mg/kg surfactant); and PEG group (100 mg/kg porcine surfactant plus 5% PEG). After ventilation, a pulmonary pressure-volume curve was built. Histological analysis was carried out to calculate the mean alveolar size (Lm) and the distortion index (DI). Both groups treated with surfactant showed higher values of dynamic pulmonary compliance and lower ventilatory pressure, compared with the MEC group (P .05). S100 group had a larger maximum lung volume, V30, compared with the MEC group (P .05). Lm and DI values were smaller in the groups treated with surfactant than in the MEC group (P .05). No differences were observed between the S100 and PEG groups. Animals treated with surfactant showed significant improvement in pulmonary function as compared to nontreated animals. PEG added to exogenous surfactant did not improve lung mechanics or volumes.

Comparative study of pressure- and volume-controlled ventilation on pulse pressure variation in a model of hypovolaemia in rabbits

Background and objective: Dynamic indices represented by systolic pressure variation and pulse pressure variation have been demonstrated to be more accurate than filling pressures in predicting fluid responsiveness. However, the literature is scarce concerning the impact of different ventilatory modes on these indices. We hypothesized that systolic pressure variation or pulse pressure variation could be affected differently by volume-controlled ventilation and pressure-controlled ventilation in an experimental model, during normovolaemia and hypovolaemia. Method: Thirty-two anaesthetized rabbits were randomly allocated into four groups according to ventilatory modality and volaemic status where G1-ConPCV was the pressure-controlled ventilation control group, G2-HemPCV was associated with haemorrhage, G3-ConVCV was the volume-controlled ventilation control group and G4-HemVCV was associated with haemorrhage. In the haemorrhage groups, blood was removed in two stages: 15% of the estimated blood volume withdrawal at M1, and, 30 min later, an additional 15% at M2. Data were submitted to analysis of variance for repeated measures; a value of P < 0.05 was considered to be statistically significant. Results: At MO (baseline), no significant differences were observed among groups. At M1, dynamic parameters differed significantly among the control and hypovolaemic groups (P < 0.05) but not between ventilation modes. However, when 30% of the estimated blood volume was removed (M2), dynamic parameters became significantly higher in animals under volume-controlled ventilation when compared with those under pressure-controlled ventilation. Conclusions: Under normovolaemia and moderate haemorrhage, dynamic parameters were not influenced by either ventilatory modalities. However, in the second stage of haemorrhage (30%), animals in volume-controlled ventilation presented higher values of systolic pressure variation and pulse pressure variation when compared with those submitted to pressure-controlled ventilation.

Combining two potential causes of metalloproteinase secretion causes abdominal aortic aneurysms in rats: a new experimental model

P>Progress in understanding the pathophysiology of abdominal aortic aneurysms (AAA) is dependent in part on the development and application of effective animal models that recapitulate key aspects of the disease. The objective was to produce an experimental model of AAA in rats by combining two potential causes of metalloproteinase (MMP) secretion: inflammation and turbulent blood flow. Male Wistar rats were randomly divided in four groups: Injury, Stenosis, Aneurysm and Control (40/group). The Injury group received a traumatic injury to the external aortic wall. The Stenosis group received an extrinsic stenosis at a corresponding location. The Aneurysm group received both the injury and stenosis simultaneously, and the Control group received a sham operation. Animals were euthanized at days 1, 3, 7 and 15. Aorta and/or aneurysms were collected and the fragments were fixed for morphologic, immunohistochemistry and morphometric analyses or frozen for MMP assays. AAAs had developed by day 3 in 60-70% of the animals, reaching an aortic dilatation ratio of more than 300%, exhibiting intense wall remodelling initiated at the adventitia and characterized by an obvious inflammatory infiltrate, mesenchymal proliferation, neoangiogenesis, elastin degradation and collagen deposition. Immunohistochemistry and zymography studies displayed significantly increased expressions of MMP-2 and MMP-9 in aneurysm walls compared to other groups. The haemo-dynamic alterations caused by the stenosis may have provided additional contribution to the MMPs liberation. This new model illustrated that AAA can be multifactorial and confirmed the key roles of MMP-2 and MMP-9 in this dynamic remodelling process.

Izergin-Korepin model with a boundary

The Izergin-Korepin model on a semi-infinite lattice is diagonalized by using the level-one vertex operators of the twisted quantum affine algebra U-q[((2))(2)]. We give the bosonization of the vacuum state with zero particle content. Excitation states are given by the action of the vertex operators on the vacuum state. We derive the boundary S-matrix. We give an integral expression of the correlation functions of the boundary model, and derive the difference equations which they satisfy. (C) 2001 Elsevier Science B.V. All rights reserved.

The acquisition of movement skills: Practice enhances the dynamic stability of bimanual coordination

During bimanual movements, two relatively stable inherent patterns of coordination (in-phase and anti-phase) are displayed (e.g., Kelso, Am. J. Physiol. 246 (1984) R1000). Recent research has shown that new patterns of coordination can be learned. For example, following practice a 90 degrees out-of-phase pattern can emerge as an additional, relatively stable, state (e.g., Zanone & Kelso, J. Exp. Psychol.: Human Performance and Perception 18 (1992) 403). On this basis, it has been concluded that practice leads to the evolution and stabilisation of the newly learned pattern and that this process of learning changes the entire attractor layout of the dynamic system. A general feature of such research has been to observe the changes of the targeted pattern's stability characteristics during training at a single movement frequency. The present study was designed to examine how practice affects the maintenance of a coordinated pattern as the movement frequency is scaled. Eleven volunteers were asked to perform a bimanual forearm pronation-supination task. Time to transition onset was used as an index of the subjects' ability to maintain two symmetrically opposite coordinated patterns (target task - 90 degrees out-of-phase - transfer task - 270 degrees out-of-phase). Their ability to maintain the target task and the transfer task were examined again after five practice sessions each consisting of 15 trials of only the 90 degrees out-of-phase pattern. Concurrent performance feedback (a Lissajous figure) was available to the participants during each practice trial. A comparison of the time to transition onset showed that the target task was more stable after practice (p = 0.025). These changes were still observed one week (p = 0.05) and two months (p = 0.075) after the practice period. Changes in the stability of the transfer task were not observed until two months after practice (p = 0.025). Notably, following practice, transitions from the 90 degrees pattern were generally to the anti-phase (180 degrees) pattern, whereas, transitions from the 270 degrees pattern were to the 90 degrees pattern. These results suggest that practice does improve the stability of a 90 degrees pattern, and that such improvements are transferable to the performance of the unpractised 270 degrees pattern. In addition, the anti-phase pattern remained more stable than the practised 90 degrees pattern throughout. (C) 2001 Elsevier Science B.V. All rights reserved.

The IWA Anaerobic Digestion Model No 1 (ADM1)

The IWA Anaerobic Digestion Modelling Task Group was established in 1997 at the 8th World Congress on,Anaerobic Digestion (Sendai, Japan) with the goal of developing a generalised anaerobic digestion model. The structured model includes multiple steps describing biochemical as well as physicochemical processes. The biochemical steps include disintegration from homogeneous particulates to carbohydrates, proteins and lipids; extracellular hydrolysis of these particulate substrates to sugars, amino acids, and long chain fatty acids (LCFA), respectively; acidogenesis from sugars and amino acids to volatile fatty acids (VFAs) and hydrogen; acetogenesis of LCFA and VFAs to acetate; and separate methanogenesis steps from acetate and hydrogen/CO2. The physico-chemical equations describe ion association and dissociation, and gas-liquid transfer. Implemented as a differential and algebraic equation (DAE) set, there are 26 dynamic state concentration variables, and 8 implicit algebraic variables per reactor vessel or element. Implemented as differential equations (DE) only, there are 32 dynamic concentration state variables.

Benchmarking nitrogen removal suspended-carrier biofilm systems using dynamic simulation

We are witnessing an enormous growth in biological nitrogen removal from wastewater. It presents specific challenges beyond traditional COD (carbon) removal. A possibility for optimised process design is the use of biomass-supporting media. In this paper, attached growth processes (AGP) are evaluated using dynamic simulations. The advantages of these systems that were qualitatively described elsewhere, are validated quantitatively based on a simulation benchmark for activated sludge treatment systems. This simulation benchmark is extended with a biofilm model that allows for fast and accurate simulation of the conversion of different substrates in a biofilm. The economic feasibility of this system is evaluated using the data generated with the benchmark simulations. Capital savings due to volume reduction and reduced sludge production are weighed out against increased aeration costs. In this evaluation, effluent quality is integrated as well.

Dynamic Behavior of the Jahn-Teller distorted Cu(H2O)(6)(2+) ion in Cu2+ doped Cs-2[Zn(H2O)(6)](ZrF6)(2) and the crystal structure of the host lattice

The temperature dependence of the X- and Q-band EPR spectra of Cs-2[Zn(H2O)(6)](ZrF6)(2) containing similar to1% Cu2+ is reported. All three molecular g-values vary with temperature, and their behavior is interpreted using a model in which the potential surface of the Jahn-Teller distorted Cu(H2O)(6)(2+) ion is perturbed by an orthorhombic strain induced by interactions with the surrounding lattice. The strain parameters are significantly smaller than those reported previously for the Cu(H2O)(6)(2+) ion in similar lattices. The temperature dependence of the two higher g-values suggests that in the present compound the lattice interactions change slightly with temperature. The crystal structure of the Cs-2[Zn(H2O)(6)](ZrF6)(2) host is reported, and the geometry of the Zn(H2O)(6)(2+) ion is correlated with lattice strain parameters derived from the EPR spectrum of the guest Cu2+ complex.

Enriched behavioral prediction equation and its impact on structured learning and the dynamic calculus

This theoretical note describes an expansion of the behavioral prediction equation, in line with the greater complexity encountered in models of structured learning theory (R. B. Cattell, 1996a). This presents learning theory with a vector substitute for the simpler scalar quantities by which traditional Pavlovian-Skinnerian models have hitherto been represented. Structured learning can be demonstrated by vector changes across a range of intrapersonal psychological variables (ability, personality, motivation, and state constructs). Its use with motivational dynamic trait measures (R. B. Cattell, 1985) should reveal new theoretical possibilities for scientifically monitoring change processes (dynamic calculus model; R. B. Cattell, 1996b), such as encountered within psycho therapeutic settings (R. B. Cattell, 1987). The enhanced behavioral prediction equation suggests that static conceptualizations of personality structure such as the Big Five model are less than optimal.

Stress correlation function evolution in lattice solid elasto-dynamic models of shear and fracture zones and earthquake prediction

It has been argued that power-law time-to-failure fits for cumulative Benioff strain and an evolution in size-frequency statistics in the lead-up to large earthquakes are evidence that the crust behaves as a Critical Point (CP) system. If so, intermediate-term earthquake prediction is possible. However, this hypothesis has not been proven. If the crust does behave as a CP system, stress correlation lengths should grow in the lead-up to large events through the action of small to moderate ruptures and drop sharply once a large event occurs. However this evolution in stress correlation lengths cannot be observed directly. Here we show, using the lattice solid model to describe discontinuous elasto-dynamic systems subjected to shear and compression, that it is for possible correlation lengths to exhibit CP-type evolution. In the case of a granular system subjected to shear, this evolution occurs in the lead-up to the largest event and is accompanied by an increasing rate of moderate-sized events and power-law acceleration of Benioff strain release. In the case of an intact sample system subjected to compression, the evolution occurs only after a mature fracture system has developed. The results support the existence of a physical mechanism for intermediate-term earthquake forecasting and suggest this mechanism is fault-system dependent. This offers an explanation of why accelerating Benioff strain release is not observed prior to all large earthquakes. The results prove the existence of an underlying evolution in discontinuous elasto-dynamic, systems which is capable of providing a basis for forecasting catastrophic failure and earthquakes.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

An energy-based model for swing hammer mills

An energy-based swing hammer mill model has been developed for coke oven feed preparation. it comprises a mechanistic power model to determine the dynamic internal recirculation and a perfect mixing mill model with a dual-classification function to mimic the operations of crusher and screen. The model parameters were calibrated using a pilot-scale swing hammer mill at various operating conditions. The effects of the underscreen configurations and the feed sizes on hammer mill operations were demonstrated through the fitted model parameters. Relationships between the model parameters and the machine configurations were established. The model was validated using the independent experimental data of single lithotype coal tests with the same BJD pilot-scale hammer mill and full operation audit data of an industrial hammer mill. The outcome of the energy-based swing hammer mill model is the capability to simulate the impact of changing blends of coal or mill configurations and operating conditions on product size distribution. Alternatively, the model can be used to select the machine settings required to achieve a desired product. (C) 2003 Elsevier Science B.V. All rights reserved.

Predictive Optimal Matrix Converter Control for a Dynamic Voltage Restorer with Flywheel Energy Storage

This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters.