A fuzzy optimization model for planning integrated terrestrial carbon management networks

Clean Technologies and Environmental Policy - Biochar application and enhanced weathering are negative emission technologies (NETs) with the potential for large-scale deployment for the removal of...     

A review of adaptive online learning for artificial neural networks

In real applications learning algorithms have to address several issues such as, huge amount of data, samples which arrive continuously and underlying data generation processes that evolve over time. Classical learning is not always appropriate to work in these environments since independent and indentically distributed data are assumed. Taking into account the requirements of the learning process, systems should be able to modify both their structures and their parameters. In this survey, our aim is to review the developed methodologies for adaptive learning with artificial neural networks, analyzing the strategies that have been traditionally applied over the years. We focus on sequential learning, the handling of the concept drift problem and the determination of the network structure. Despite the research in this field, there are currently no standard methods to deal with these environments and diverse issues remain an open problem.     

Brazil’s new national policy on solid waste: challenges and opportunities

Brazil, one of the world’s largest developing countries, has recently introduced a new solid waste management regulatory policy. This new regulatory policy will have implications for a wide variety of stakeholders and sets the stage for opportunities and lessons to be learned. These issues are discussed in this article.     

Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction

The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density (MD) in a more objective and accurate way than via visual-based methods and for labeling the mammograms that are later employed to train the fully automated tool. Although most automated methods rely on supervised approaches based on a global labeling of the mammogram, the proposed method relies on pixel-level labeling, allowing better tissue classification and density measurement on a continuous scale. The fully automated method presented combines a classification scheme based on local features and thresholding operations that improve the performance of the classifier. A dataset of 655 mammograms was used to test the concordance of both approaches in measuring MD. Three expert radiologists measured MD in each of the mammograms using the semi-automated tool (DM-Scan). It was then measured by the fully automated system and the correlation between both methods was computed. The relation between MD and breast cancer was then analyzed using a case–control dataset consisting of 230 mammograms. The Intraclass Correlation Coefficient (ICC) was used to compute reliability among raters and between techniques. The results obtained showed an average ICC = 0.922 among raters when using the semi-automated tool, whilst the average correlation between the semi-automated and automated measures was ICC = 0.838. In the case–control study, the results obtained showed Odds Ratios (OR) of 1.38 and 1.50 per 10% increase in MD when using the semi-automated and fully automated approaches respectively. It can therefore be concluded that the automated and semi-automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available.     

Multifunctional Silver‐Exchanged Zeolite Micromotors for Catalytic Detoxification of Chemical and Biological Threats

Multifunctional reactive‐zeolite‐based micromotors have been developed and characterized toward effective and rapid elimination of chemical and biological threats. The incorporation of silver ions (Ag⁺) into aluminosilicate zeolite framework imparts several attractive functions, including strong binding to chemical warfare agents (CWA) followed by effective degradation, and enhanced antibacterial activity. The new zeolite‐micromotors protocol thus combines the remarkable adsorption capacity of zeolites and the efficient catalytic properties of the reactive Ag⁺ ions with the autonomous movement of the zeolite micromotors for an accelerated detoxification of CWA. Furthermore, the high antibacterial activity of Ag⁺ along with the rapid micromotor movement enhances the contact between bacteria and reactive Ag⁺, leading to a powerful “on‐the‐fly” bacteria killing capacity. These attractive adsorptive/catalytic features of the self‐propelled zeolite micromotors eliminate secondary environmental contamination compared to adsorptive micromotors. The distinct cubic geometry of the zeolite micromotors leads to enhanced bubble generation and faster movement, in unique movement trajectories, which increases the fluid convection and highly efficient detoxification of CWA and killing of bacteria. The attractive capabilities of these zeolite micromotors will pave the way for their diverse applications in defense, environmental and biomedical applications in more economical and sustainable manner.     

Analysing green supply chain management practices in Brazil’s electrical/electronics industry using interpretive structural modelling

Industries need to adopt the environmental management concepts in the traditional supply chain management. The green supply chain management (GSCM) is an established concept to ensure environment-friendly activities in industry. This paper identifies the relationship of driving and dependence that exists between GSCM practices with regard to their adoption within Brazilian electrical/electronic industry with the help of interpretive structural modelling (ISM). From the results, we infer that cooperation with customers for eco-design practice is driving other practices, and this practice acts as a vital role among other practices. Commitment to GSCM from senior managers and cooperation with customers for cleaner production occupy the highest level.     

Multimode equivalent network representation for junctions between coaxial and circular waveguides

In this article we present two contributions to the study of coaxial waveguide structures. First, we present an efficient and accurate technique to evaluate the modes in the coaxial waveguides; second, we analyze junctions involving coaxial and circular waveguides using the multimode equivalent network representation. Numerical and experimental results are presented, showing good agreement. © 1997 John Wiley & Sons, Inc. Int J Microwave Millimeter-Wave CAE 7: 180–194, 1997.     

Chlorophyll and Carotenoid Composition in Virgin Olive Oils from Various Spanish Olive Varieties

A study of chlorophyll and carotenoid composition of nine single-variety virgin olive oils from the main Spanish producing regions has shown differences depending on variety and ripening degree of the fruits. Pheophytin a was the major pigment in all the oils studied (44–58% total pigments), followed by lutein (18–38%) and β-carotene (6–17%). The chlorophyll pigments group also included pheophytin b and in some cases chlorophylls a and b . The carotenoid fraction also included the xanthophylls neoxanthin, violaxanthin, luteoxanthin, antheraxanthin, mutatoxanthin and β-cryptoxanthin. The mean provitamin A activity of the oils was 260 μg kg⁻¹ expressed as retinol equivalent. cis -α-Carotene (tentative), mono- and di-esterified xanthophylls and pheophorbide a were pigments exclusive to Arbequina variety, a fact that could be used as a chemo-taxonomic differentiator of the oils of this variety. The ratio between the chlorophyll fraction and the carotenoid fraction was maintained in most cases around 1, demonstrating that the green and yellow fractions were in balance, notwithstanding their greater or lesser total pigment content. The considerable range in the lutein/β-carotene ratio (between 1·3 and 5·1 depending on variety) makes this ratio a differentiator of single-variety oils. Despite the different sources of the oils, some general trends have been shown which suggest what chlorophyll and carotenoid pigments should be expected in an olive oil so as to include it within the denomination ‘virgin’.     

Analysis of the Content of Fatty Acid Methyl Esters in Biodiesel by Fourier-Transform Infrared Spectroscopy: Method and Comparison with Gas Chromatography

The increasing importance of sustainability in energy production has led to a global commitment to the use of fuels derived from renewable biological sources, such as biodiesel produced from plant crops or biomass residues, that do not compete with human food for their production. For a biofuel to be considered biodiesel, it must satisfy the specifications described in the UNE 14214, with the UNE-EN 14103 referring to the determination of fatty acid methyl ester content. This standard applies gas chromatography as an analytical technique. Gas chromatography is a widely used technique in the analysis of methyl ester although it has a number of drawbacks such as: long analysis times, a high consumption of high-quality gases and internal standards, does not allow the analysis of different compounds with the same column, etc. From an industrial production point of view, is necessary to know the fatty acid methyl ester content in biodiesel samples quickly. This paper studies the development of an analytical method using Fourier transform infrared spectroscopy (FTIR) as alternative to gas chromatography (GC), since it is a simple, rapid, and precise analytical technique to quantify fatty acid methyl ester content in biofuel samples.     

Fetal Undernutrition Modifies Vascular RAS Balance Enhancing Oxidative Damage and Contributing to Remodeling

Fetal stress is known to increase susceptibility to cardiometabolic diseases and hypertension in adult age in a process known as fetal programming. This study investigated the relationship between vascular RAS, oxidative damage and remodeling in fetal programming. Six-month old Sprague-Dawley offspring from mothers that were fed ad libitum (CONTROL) or with 50% intake during the second half of gestation (maternal undernutrition, MUN) were used. qPCR or immunohistochemistry were used to obtain the expression of receptors and enzymes. Plasma levels of carbonyls were measured by spectrophotometry. In mesenteric arteries from MUN rats we detected an upregulation of ACE, ACE2, AT₁ receptors and NADPH oxidase, and lower expression of AT₂, Mas and MrgD receptors compared to CONTROL. Systolic and diastolic blood pressure and plasma levels of carbonyls were higher in MUN than in CONTROL. Vascular morphology evidenced an increased media/lumen ratio and adventitia/lumen ratio, and more connective tissue in MUN compared to CONTROL. In conclusion, fetal undernutrition indices RAS alterations and oxidative damage which may contribute to the remodeling of mesenteric arteries, and increase the risk of adverse cardiovascular events and hypertension.