Weakening processes in thrust faults: insights from the Monte Perdido thrust fault (southern Pyrenees, Spain)

The Monte Perdido thrust fault (southern Pyrenees) consists of a 6-m-thick interval of intensely deformed clay-bearing rocks. The fault zone is affected by a pervasive pressure solution seam and numerous shear surfaces. Calcite extensional-shear veins are present along the shear surfaces. The angular relationships between the two structures indicate that shear surfaces developed at a high angle (70°) to the local principal maximum stress axis r1. Two main stages of deformation are present. The first stage corresponds to the development of calcite shear veins by a combination of shear surface reactivation and extensional mode I rupture. The second stage of deformation corresponds to chlorite precipitation along the previously reactivated shear surfaces. The pore fluid factor k computed for the two deformation episodes indicates high fluid pressures during the Monte Perdido thrust activity. During the first stage of deformation, the reactivation of the shear surface was facilitated by a suprahydrostatic fluid pressure with a pore fluid factor kv equal to 0.89. For the second stage, the fluid pressure remained still high (with a k value ranging between 0.77 and 0.84) even with the presence of weak chlorite along the shear surfaces. Furthermore, evidence of hydrostatic fluid pressure during calcite cement precipitation supports that incremental shear surface reactivations are correlated with cyclic fluid pressure fluctuations consis- tent with a fault-valve model.

Integrated Ladinian bio-chronostratigraphy and geochrononology of Monte San Giorgio (Southern Alps, Switzerland)

New biostratigraphic data significantly improve the age assignment of the Ladinian succession of Monte San Giorgio (UNESCO World Heritage List site, Southern Alps, Switzerland), whose world-famous fossil marine vertebrate faunas are now dated to the substage and zone levels. High-resolution single-zircon U-Pb dating was performed using ID-TIMS and chemical abrasion (CA) pre-treatment technique on volcanic ash layers intercalated in the biostratigraphically-defined intervals of the Meride Limestone. It yielded ages of 241.07 +/- 0.13 Ma (Cava superiore beds, P. gredleri Zone), 240.63 +/- 0.13 Ma (Cassina beds, P gredleri/P. archelaus transition Zone) and 239.51 +/- 0.15 Ma (Lower Kalkschieferzone, P. archelaus Zone). Our results suggest that the time interval including the vertebrate-bearing Middle Triassic section spans around 4 Myr and is thus significantly shorter than so far assumed. The San Giorgio Dolomite and the Meride Limestone correlate with intervals of the Buchenstein Formation and the Wengen Formation in the reference section at Bagolino, where the Global boundary Stratotype Section and Point (GSSP) for the base of the Ladinian was defined. The new radio-isotopic ages of the Meride Limestone are up to 2 Myr older than those published for the biostratigraphically-equivalent intervals at Bagolino but they are consistent with the recent re-dating of the underlying Besano Formation, also performed using the CA technique. Average sedimentation rates at Monte San Giorgio are by more than an order of magnitude higher compared to those assumed for the Buchenstein Formation, which formed under sediment-starved pelagic conditions, and reflect prevailing high subsidence and high carbonate mud supply from the adjoining Salvatore/Esino platforms. Finally, the high-resolution U-Pb ages allow a correlation of the vertebrate faunas of the Cava superiore/Cava inferiore beds with the marine vertebrate record of the Prosanto Formation (Upper Austroalpine), so far precluded by the poor biostratigraphic control of the latter.

[Frascati. Eremiti Camaldolesi di Monte Corona]

Référence bibliographique : Weigert, 167, 168, 169

Photopolymerizable hydrogels for implants: Monte-Carlo modeling and experimental in vitro validation.

Photopolymerization is commonly used in a broad range of bioapplications, such as drug delivery, tissue engineering, and surgical implants, where liquid materials are injected and then hardened by means of illumination to create a solid polymer network. However, photopolymerization using a probe, e.g., needle guiding both the liquid and the curing illumination, has not been thoroughly investigated. We present a Monte Carlo model that takes into account the dynamic absorption and scattering parameters as well as solid-liquid boundaries of the photopolymer to yield the shape and volume of minimally invasively injected, photopolymerized hydrogels. In the first part of the article, our model is validated using a set of well-known poly(ethylene glycol) dimethacrylate hydrogels showing an excellent agreement between simulated and experimental volume-growth-rates. In the second part, in situ experimental results and simulations for photopolymerization in tissue cavities are presented. It was found that a cavity with a volume of 152  mm3 can be photopolymerized from the output of a 0.28-mm2 fiber by adding scattering lipid particles while only a volume of 38  mm3 (25%) was achieved without particles. The proposed model provides a simple and robust method to solve complex photopolymerization problems, where the dimension of the light source is much smaller than the volume of the photopolymerizable hydrogel.

A Monte Carlo-based procedure for independent monitor unit calculation in IMRT treatment plans.

Intensity-modulated radiotherapy (IMRT) treatment plan verification by comparison with measured data requires having access to the linear accelerator and is time consuming. In this paper, we propose a method for monitor unit (MU) calculation and plan comparison for step and shoot IMRT based on the Monte Carlo code EGSnrc/BEAMnrc. The beamlets of an IMRT treatment plan are individually simulated using Monte Carlo and converted into absorbed dose to water per MU. The dose of the whole treatment can be expressed through a linear matrix equation of the MU and dose per MU of every beamlet. Due to the positivity of the absorbed dose and MU values, this equation is solved for the MU values using a non-negative least-squares fit optimization algorithm (NNLS). The Monte Carlo plan is formed by multiplying the Monte Carlo absorbed dose to water per MU with the Monte Carlo/NNLS MU. Several treatment plan localizations calculated with a commercial treatment planning system (TPS) are compared with the proposed method for validation. The Monte Carlo/NNLS MUs are close to the ones calculated by the TPS and lead to a treatment dose distribution which is clinically equivalent to the one calculated by the TPS. This procedure can be used as an IMRT QA and further development could allow this technique to be used for other radiotherapy techniques like tomotherapy or volumetric modulated arc therapy.

Frutificação precoce de laranjeiras 'Monte Parnaso' com anelagem e pulverizações de ácido giberélico e óleo mineral

Com o objetivo de diminuir a floração muito intensa e aumentar a produção de frutos, laranjeiras de umbigo 'Monte Parnaso' (Citrus sinensis Osb.), com dois anos de idade, foram submetidas à anelagem de casca do tronco, pulverizações foliares com doses de 0, 10, 20 e 30 ppm de ácido giberélico (AG3), combinadas com 0 e 1% de óleo mineral emulsionável. Foram realizados dois experimentos: um com pulverizações repetidas em 22 e 29/07/93, e outro com pulverização em plena floração em 15/09/93. Em ambos os experimentos, 50% das plantas foram submetidas à anelagem da casca do tronco, feita por uma incisão anelar, 5 cm abaixo da formação da copa. A produção diminuiu linearmente com o aumento das dosagens de AG3 pulverizado no final de julho; não houve efeito significativo sobre a frutificação quando o AG3 foi aplicado em plena floração. As pulverizações com 1% de óleo mineral diminuíram o número de frutos produzidos, em até 42%, principalmente nos tratamentos feitos no final de julho. A anelagem da casca do tronco aumentou o número de frutos em aproximadamente 25%, mas diminuiu o peso médio dos frutos.

A semi-grand canonical Monte Carlo simulation model for ion binding to ionizable surfaces: proton binding of carboxylated latex particles as a case study

In this paper, we present a computer simulation study of the ion binding process at an ionizable surface using a semi-grand canonical Monte Carlo method that models the surface as a discrete distribution of charged and neutral functional groups in equilibrium with explicit ions modelled in the context of the primitive model. The parameters of the simulation model were tuned and checked by comparison with experimental titrations of carboxylated latex particles in the presence of different ionic strengths of monovalent ions. The titration of these particles was analysed by calculating the degree of dissociation of the latex functional groups vs. pH curves at different background salt concentrations. As the charge of the titrated surface changes during the simulation, a procedure to keep the electroneutrality of the system is required. Here, two approaches are used with the choice depending on the ion selected to maintain electroneutrality: counterion or coion procedures. We compare and discuss the difference between the procedures. The simulations also provided a microscopic description of the electrostatic double layer (EDL) structure as a function of p H and ionic strength. The results allow us to quantify the effect of the size of the background salt ions and of the surface functional groups on the degree of dissociation. The non-homogeneous structure of the EDL was revealed by plotting the counterion density profiles around charged and neutral surface functional groups.

Quantitative integration of high-resolution hydrogeophysical data through Monte-Carlo-type conditional simulations

Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

A critical evaluation of secondary cancer risk models applied to Monte Carlo dose distributions of 2-dimensional, 3-dimensional conformal and hybrid intensity-modulated radiation therapy for breast cancer.

The comparison of radiotherapy techniques regarding secondary cancer risk has yielded contradictory results possibly stemming from the many different approaches used to estimate risk. The purpose of this study was to make a comprehensive evaluation of different available risk models applied to detailed whole-body dose distributions computed by Monte Carlo for various breast radiotherapy techniques including conventional open tangents, 3D conformal wedged tangents and hybrid intensity modulated radiation therapy (IMRT). First, organ-specific linear risk models developed by the International Commission on Radiological Protection (ICRP) and the Biological Effects of Ionizing Radiation (BEIR) VII committee were applied to mean doses for remote organs only and all solid organs. Then, different general non-linear risk models were applied to the whole body dose distribution. Finally, organ-specific non-linear risk models for the lung and breast were used to assess the secondary cancer risk for these two specific organs. A total of 32 different calculated absolute risks resulted in a broad range of values (between 0.1% and 48.5%) underlying the large uncertainties in absolute risk calculation. The ratio of risk between two techniques has often been proposed as a more robust assessment of risk than the absolute risk. We found that the ratio of risk between two techniques could also vary substantially considering the different approaches to risk estimation. Sometimes the ratio of risk between two techniques would range between values smaller and larger than one, which then translates into inconsistent results on the potential higher risk of one technique compared to another. We found however that the hybrid IMRT technique resulted in a systematic reduction of risk compared to the other techniques investigated even though the magnitude of this reduction varied substantially with the different approaches investigated. Based on the epidemiological data available, a reasonable approach to risk estimation would be to use organ-specific non-linear risk models applied to the dose distributions of organs within or near the treatment fields (lungs and contralateral breast in the case of breast radiotherapy) as the majority of radiation-induced secondary cancers are found in the beam-bordering regions.

Monte Carlo simulation of a clearance box monitor used for nuclear power plant decommissioning.

When decommissioning a nuclear facility it is important to be able to estimate activity levels of potentially radioactive samples and compare with clearance values defined by regulatory authorities. This paper presents a method of calibrating a clearance box monitor based on practical experimental measurements and Monte Carlo simulations. Adjusting the simulation for experimental data obtained using a simple point source permits the computation of absolute calibration factors for more complex geometries with an accuracy of a bit more than 20%. The uncertainty of the calibration factor can be improved to about 10% when the simulation is used relatively, in direct comparison with a measurement performed in the same geometry but with another nuclide. The simulation can also be used to validate the experimental calibration procedure when the sample is supposed to be homogeneous but the calibration factor is derived from a plate phantom. For more realistic geometries, like a small gravel dumpster, Monte Carlo simulation shows that the calibration factor obtained with a larger homogeneous phantom is correct within about 20%, if sample density is taken as the influencing parameter. Finally, simulation can be used to estimate the effect of a contamination hotspot. The research supporting this paper shows that activity could be largely underestimated in the event of a centrally-located hotspot and overestimated for a peripherally-located hotspot if the sample is assumed to be homogeneously contaminated. This demonstrates the usefulness of being able to complement experimental methods with Monte Carlo simulations in order to estimate calibration factors that cannot be directly measured because of a lack of available material or specific geometries.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.