Evaluation of the Mechanisms Acting on the Atlantic Meridional Overturning Circulation in CESM2 for the 1pctCO_(2) Experiment

The Atlantic Meridional Overturning Circulation(AMOC)is a crucial component of the Earth’s climate system due to its fundamental role in heat distribution,carbon and oxygen transport,and the weather.Other climate components,such as the atmosphere and sea ice,influence the AMOC.Evaluating the physical mechanisms of those interactions is paramount to increasing knowledge about AMOC’s functioning.In this study,the authors used outputs from the Community Earth System Model version 2 and observational data to investigate changes in theAMOC and the associated physical processes.Two DECK experiments were evaluated:piControl and 1pctCO_(2),with an annual increase of 1%of atmospheric CO_(2).The analysis revealed a significant decrease in the AMOC,associated with changes in mixed layer depth and buoyancy in high latitudes of the North Atlantic,resulting in the shutdown of deep convection and potentially affecting the formation of North Atlantic Deep Water and Antarctic Bottom Water.A vital aspect observed in this study is the association between increased runoff and reduced water evaporation,giving rise to a positive feedback process.Consequently,the rates of freshwater spreading have intensified during this period,which could lead to an accelerated disruption of the AMOC beyond the projections of existing models.

Output-only identification of the modal and physical properties of structures using free vibration response

The viability of a complete structural characterization of civil structures is explored and discussed. In particular, the identification of modal （i.e. natural frequencies, damping ratios and modal shapes） and physical properties （i.e. mass and stiffness） using only the structure＇s free decay response is studied. To accomplish this, modal analysis from flee vibration response only （MAFVRO） and mass modification （MM） methodologies are engaged along with Wavelet based techniques for optimal signal processing and modal reconstruction. The methodologies are evaluated using simulated and experimental data. The simulated data are extracted from a simple elastic model of a 5 story shear building and from a more realistic nonlinear model of a RC frame structure. The experimental data are gathered from shake table test of a 2-story scaled shear building. Guidelines for the reconstruction procedure from the data are proposed as the quality of the identified properties is shown to be governed by adequate selection of the frequency bands and optimal modal shape reconstruction. Moreover, in cases where the structure has undergone damage, the proposed identification scheme can also be applied for preliminary assessment of structural health.

A KNN Undersampling Approach for Data Balancing

In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve this problem, the KNN algorithm provides a basis to other balancing methods. These balancing methods are revisited in this work, and a new and simple approach of KNN undersampling is proposed. The experiments demonstrated that the KNN undersampling method outperformed other sampling methods. The proposed method also outperformed the results of other studies, and indicates that the simplicity of KNN can be used as a base for efficient algorithms in machine learning and knowledge discovery.

GIS as a Decision Support Tool in the Area of Influence of the Nuclear Complex Angra dos Reis, Brazil

The outlook concerning the occurrence of industrial accidents has led to the implementation of response systems based on geoprocessing tools, which are widely adopted in emergency for such ventures, since they have helped and served as a support for decision making, as well as for the preparation of guidelines aimed at managing emergencies. Nuclear power plants, because they constitute types of industrial activities that present dangerous conditions and attention regarding security are characterized as hazardous, especially due to consequences that occurred from large accidents— such as Chernobyl (1986) and Fukushima (2011)—highlighting the importance to its negative impacts, since the occurrence of accidents at nuclear power plants may affect surrounding areas, thus exposing a set of elements that are part of the environmental dynamics that integrates the catchment area where this type of plant is situated. In this way, through an integrated view of the region where the nuclear complex is located in Angra dos Reis City (Rio de Janeiro State) and, also, by aggregating information that portray the geobiophysical reality of its surroundings, several elements were incorporated into a database developed in a virtual environment, in which was produced a geographic information system (GIS) that presents a complex of variables that, once considered, can enhance various analysis in order to support emergency situations and planning, as well as guidelines that help define actions from the occurrence of accidental events at the nuclear plant.

A Finite Element Model for the Instability Analysis of Flexible Pipes Tensile Armor Wires

The instability of the tensile armor wire of flexible pipes is a failure mode associated with deep and ultra-deep water applications. Real compressive forces acting on the pipe are necessary to trigger this process. The loss of stability may be divided into two distinct processes, according to the main direction of the wire＇s displacement： radial or lateral instability. This study aims at proposing a numerical tool for predicting lateral and radial critical buckling loads for the tensile armor wires of flexible pipes. A simple finite element model, based on springs and beams elements, was developed in ABAQUS~ to deal with this problem in an efficient and reliable manner. A parametric study was conducted concerning the behavior of the critical load when the laying angle, the initial curvature and the total pipe length are varied. The results were consistent with previously published literature data and analytical expressions, proving its applicability to pipe engineering projects. It also has the advantage of approaching the problem three-dimensionally, which allows further modelling modifications, such as including friction effects.

Genetic Optimization of Artificial Neural Networks to Forecast Virioplankton Abundance from Cytometric Data

Since viruses are able to influence the trophic status and community structure they should be accessed and accounted in ecosystem functioning and management models. So, this work met a set of biological, chemical and physical time series in order to explore the correlations with marine virioplankton community across different trophic gradients. The case studied is the Arraial do Cabo upwelling system, northeast of Rio de Janeiro State in Southeast coast of Brazil. The main goal is to evolve three type of artificial neural network (ANN) by genetic algorithm (GA) optimization to predict virioplankton abundance and dynamic. The input variables range from the abundance of phytoplankton, bacterioplankton and its ratios acquired by one in situ and another ex situ flow cytometers. These data were collected with weekly frequency from August 2006 to June 2007. Our results show viruses being highly correlated to their host, and that GA provided an efficient method of optimizing ANN architectures to predict the virioplankton abundance. The RBF-NN model presented the best performance to an accuracy of 97% for any period in the year. A discussion and ecological interpretations about the system behavior is also provided.

Effects of Sea Level Variation on Biological and Chemical Concentrations in a Coastal Upwelling Ecosystem

Oscillations in sea level due to meteorological forces related to wind and pressure affect the regular tides and modify the sea level conditions, mainly in restricted waters such as bays. Investigations surrounding these variations and the biological and chemical response are important for monitoring coastal regions mainly where upwelling shelf systems occur. A spatial and temporal database from Quick Scatterometer satellite vector wind, surface stations from the Southeast coast of Brazil and surface seawater data collected in Anjos Bay, Arraial do Cabo city, northeast of Rio de Janeiro State were used to investigate the meteorological influences in the variability of the dissolved oxygen, nutrients, meroplankton larvae and chlorophyll-a concentrations. Multivariate statistical approaches such as Principal Component Analysis (PCA) and Clustering Analysis (CA) were applied to verify spatial and temporal variances. A correlation matrix was also verified for different water masses in order to identify the relationship between the above parameters. A seasonal variability of the meteorological residual presents a well-defined pattern with maximum peaks in autumn/winter and minimum during spring/summer with negative values, period of occurrence of upwelling in this region. This lowering of the sea level is in accordance with the increasing of nutrients and meroplankton larvae for the same period. CA showed six groups and an importance of the zonal and meridional wind variability, including these variables in a single cluster. PCA retained eight components, explaining 64.10% of the total variance of data set. Some clusters and loadings have the same variables, showing the importance of the sea-air interaction.

Study of a Photodegradant Polymeric Composite Containing TiO_(2) and Glass Residue

Photodegradation or photocatalysis is a chemical degradation process that occurs when an inorganic semiconductor is exposed to ultraviolet (UV) light. UV light (wavelength 320 - 400 nm) has enough energy to detach an electron from the last layer of the semiconductor, leading to the conduction band, leaving a hole in the valence band. In these bands, chemical reduction and oxidation reactions occur, respectively. These reactions degrade diverse surface dirt, dissociating them into simpler and less offensive substances such as CO2 and H2O. In this work, we studied the potential of photocatalysis of a composite based on a semiconductor encapsulated in epoxy resin, in the degradation of Staphylococcus aureus, pathogen with a high degree of hospital contamination, in order to apply it to the construction in hospital facilities. The experiments were carried out with a fabrication of only epoxy resin tablets and tablets with the composite, at various concentrations of the semiconductor and glass powder. Through contamination of these tablets and their exposure to sunlight and the ambient light, contamination on their surfaces was verified. The results indicated potential photodegradation capacity of the composite.