Mechanical characterization of the Amazonian Pomacea dolioides (Reeve, 1856) shell

We investigated the mechanical behavior of freshwater mollusk shells, Pomacea dolioides, collected from a floodplain area located in Amazonas, Brazil. With the purpose of characterizing the mechanical properties of the shells, bending, hardness and roughness tests were carried out. To determine the shell flexural strength, a new methodology was proposed for the calculation of it, considering the curved geometry of the specimens taken from the shells. It was also described the mechanical properties as a function of shell position and thickness, variation of the surface hardness along the shell and the low level of superficial irregularity in the inner layer of the shells. Shell presented a mean flexural rupture modulus (MOR) of 128.0 MPa, Rockwell HR15N hardness = 50 ± 8.3 and a low level of irregularities in the inner layer, roughness Ra = 0.160 μm.Investigamos el comportamiento mecánico de las conchas de moluscos de agua dulce, Pomacea dolioides, recolectados en un área de llanuras aluviales en Amazonas, Brasil. Con el fin de caracterizar las propiedades mecánicas de éstas, se utilizaron ensayos de flexión, dureza y rugosidad. Para determinar la resistencia a la flexión del material, se propuso una nueva metodología para el cálculo de la resistencia a la flexión, considerando la geometría curva de los cuerpos de prueba retirados de las conchas. También se describieron las propiedades mecánicas analizados en función de la posición y de la espesura de la concha, la variación de la superficie de la rigidez con el concha y el nivel bajo de irregularidad superficial en la superficie interna de las conchas. La concha presentó el Módulo de Ruptura a la Flexión (MOR) medio de 128.0 MPa, dureza superficial Rockwell HR15N = 50 ± 8.3 y un bajo nivel de irregularidades en la capa interna, con rugosidad Ra = 0.160 μm

A nested loop for simultaneous model topology screening, parameters estimation, and identification of the optimal number of experiments: Application to a Simulated Moving Bed unit

Simulated Moving Bed (SMB) chromatography is a well-known technique for the resolution of several high-value-added compounds. Parameters identification and model topology definition are arduous when one is dealing with complex systems such as a Simulated Moving Bed unit. Moreover, the large number of experiments necessary might be an expansive-long process. Hence, this work proposes a novel methodology for parameter estimation, screening the most suitable topology of the models sink-source (defined by the adsorption isotherm equation) and defining the minimum number of experiments necessary to identify the model. Therefore, a nested loop optimization problem is proposed with three levels considering the three main goals of the work: parameters estimation; topology screening by isotherm definition; minimum number of experiments necessary to yield a precise model. The proposed methodology emulated a real scenario by introducing noise in the data and using a Software-in-the-Loop (SIL) approach. Data reconciliation and uncertainty evaluation add robustness to the parameter estimation adding precision and reliability to the model. The methodology is validated considering experimental data from literature apart from the samples applied for parameter estimation, following a cross-validation. The results corroborate that it is possible to carry out trustworthy parameter estimation directly from an SMB unit with minimal system knowledge

Perspectives for sustainable aviation biofuels in Brazil

The aviation industry has set ambitious goals to reduce carbon emissions in coming decades. The strategy involves the use of sustainable biofuels, aiming to achieve benefits from environmental, social, and economic perspectives. In this context, Brazilian conditions are favorable, with a mature agroindustry that regularly produces automotive biofuel largely adopted by Brazilian road vehicles, while air transportation has been growing at an accelerating pace and a modern aircraft industry is in place. This paper presents the main conclusions and recommendations from a broad assessment of the technological, economic, and sustainability challenges and opportunities associated with the development of drop-in aviation biofuels in Brazil. It was written by a research team that prepared the initial reports and conducted eight workshops with the active participation of more than 30 stakeholders encompassing the private sector, government institutions, NGOs, and academia. The main outcome was a set of guidelines for establishing a new biofuels industry, including recommendations for (a) filling the identified research and development knowledge gaps in the production of sustainable feedstock; (b) overcoming the barriers in conversion technology, including scaling-up issues; (c) promoting greater involvement and interaction between private and government stakeholders; and (d) creating a national strategy to promote the development of aviation biofuels2015FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP2012/50009-

Exploiting ConvNet Diversity for Flooding Identification

Flooding is the world's most costly type of natural disaster in terms of both economic losses and human causalities. A first and essential procedure toward flood monitoring is based on identifying the area most vulnerable to flooding, which gives authorities relevant regions to focus. In this letter, we propose several methods to perform flooding identification in high-resolution remote sensing images using deep learning. Specifically, some proposed techniques are based upon unique networks, such as dilated and deconvolutional ones, whereas others were conceived to exploit diversity of distinct networks in order to extract the maximum performance of each classifier. The evaluation of the proposed methods was conducted in a high-resolution remote sensing data set. Results show that the proposed algorithms outperformed the state-of-the-art baselines, providing improvements ranging from 1% to 4% in terms of the Jaccard Index

Strong Coupling Constant with Flavour Thresholds at Four Loops in the MS-bar Scheme

We present in analytic form the matching conditions for the strong coupling constant alpha_s^(n_f)(mu) at the flavour thresholds to three loops in the modified minimal-subtraction scheme. Taking into account the recently calculated coefficient beta_3 of the Callan-Symanzik beta function of quantum chromodynamics, we thus derive a four-loop formula for alpha_s^(n_f)(mu) together with appropriate relationships between the asymptotic scale parameters Lambda^(n_f) for different numbers of flavours n_f.Comment: 10 pages (Latex), 3 figures (Postscript

Uso de gonadotrofina corionica equina em programas de transferencia de embriões bovinos a tempo fixo

06

Two-loop amplitudes with nested sums: Fermionic contributions to e+ e- --> q qbar g

We present the calculation of the nf-contributions to the two-loop amplitude for e+ e- --> q qbar g and give results for the full one-loop amplitude to order eps^2 in the dimensional regularization parameter. Our results agree with those recently obtained by Garland et al.. The calculation makes extensive use of an efficient method based on nested sums to calculate two-loop integrals with arbitrary powers of the propagators. The use of nested sums leads in a natural way to multiple polylogarithms with simple arguments, which allow a straightforward analytic continuation.Comment: 31 pages, a file "coefficients.h" with the results in FORM format is include

Uso de acetato de medroxiprogesterona associado ou não ao ECG para sincronização e inseminação artificial a tempo fixo de vacas de corte

15

Enhancing Network Slicing Architectures with Machine Learning, Security, Sustainability and Experimental Networks Integration

Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.Comment: 10 pages, 11 figure