Efeitos da Globalização na Inflação Brasileira

In this paper we present a dynamic stochastic general equilibrium (DSGE) model, which aims at evaluating the effects of trade globalization over inflation. The period of the inflation targeting regime (1999-2008) is employed to estimate the parameters for the Brazilian economy. The results show that trade globalization appreciates the terms of trade and reduces the inflation rate. Meanwhile to implement barriers to trade - for example, by increasing import and/or export taxes - affects positively the inflation rate. Under a secondary purpose of disseminating technical information, we derive in the appendix the model developed in the paper and we describe in the introduction the recent evolution of the Brazilian international trade.

Incidental potable water reuse in a Catalonian basin: living downstream

A preliminary assessment of incidental potable water reuse (IPR) in the Llobregat River basin has been conducted by estimating the dilution factor of treated effluent discharges upstream of six river flow measurement sections. IPR in the Llobregat River basin is an everyday occurrence, because of the systematic discharge of treated effluents upstream of river sections used as drinking water sources. Average river flows at the Sant Joan Despí measurement section increased from 400,000 m3/d (2007) to 864,000 m3/d (2008) and to 931,000 m3/d (2013), while treated effluent discharges upstream of that section ranged from 109,000 m3/d to 114,000 m3/d in those years. The highest degree of IPR occurs downstream of the Abrera and Sant Joan Despí flow measurement sections, from where about half of the drinking water supplied to the Barcelona Metropolitan Area is abstracted. Based on average annual flows, the likelihood that drinking water produced from that river stretch contained treated effluent varied from 25% (2007) to 13% (2008) and to 12% (2013). Water agencies and drinking water production utilities have strived for decades to ensure that drinking water production satisfies applicable quality requirements and provides the required public health protection.Peer ReviewedPostprint (published version

First-order methods for the convex hull membership problem

The convex hull membership problem (CHMP) consists in deciding whether a certain point belongs to the convex hull of a finite set of points, a decision problem with important applications in computational geometry and in foundations of linear programming. In this study, we review, compare and analyze first-order methods for CHMP, namely, Frank-Wolfe type methods, Projected Gradient methods and a recently introduced geometric algorithm, called Triangle Algorithm (TA). We discuss the connections between this algorithm and Frank-Wolfe, showing that TA can be interpreted as an inexact Frank-Wolfe. Despite this similarity, TA is strongly based on a theorem of alternatives known as distance duality. By using this theorem, we propose suitable stopping criteria for CHMP to be integrated into Frank-Wolfe type and Projected Gradient, specializing these methods to the membership decision problem. Interestingly, Frank-Wolfe integrated with such stopping criteria coincides with a greedy version of the Triangle Algorithm which is, in its turn, equivalent to an algorithm due to von Neumann. We report numerical experiments on random instances of CHMP, carefully designed to cover different scenarios, that indicate which algorithm is preferable according to the geometry of the convex hull and the relative position of the query point. Concerning potential applications, we present two illustrative examples, one related to linear programming feasibility problems and another related to image classification problems.Comment: 29 pages, 11 figure

Quantitative supply chain segmentation model for dynamic alignment

[EN] Companies deal with different customer groups, requirements differ among them, which makes it important to define the service level precisely and improve customer service through different supply chain strategies for each group. An alternative to deal with imprecision related to the segmentation processes suggested by either the Leagile or the Dynamic Alignment Schools is the application of fuzzy set theory. The objective of this work is to develop a quantitative model that uses the fuzzy set theory and, based on sales data, assess the company s supply chain(s). The model's aim is to facilitate managers' decision-making processes to achieve the dynamic alignment. It was possible to identify the supply chains that serve the client groups evaluated, providing answers faster than the analysis proposed by the models found in the literature. The application in two real situations validated the model since the results obtained were consistent with the reality pointed out by the experts of the companies assessed. The model indicates possible actions for the realignment of the supply chain by their managers. Results obtained should improve practice, preparing managers to cope with the organizations` multiple supply chains. This study is the first one that aims to segment quantitatively supply chains on a company applying fuzzy set theory, providing a novel approach to align operations and supply chain strategy dynamically.Alves Ferreira, R.; A. S. Santos, L.; Espôsto, KF. (2022). Quantitative supply chain segmentation model for dynamic alignment. International Journal of Production Management and Engineering. 10(2):99-113. https://doi.org/10.4995/ijpme.2022.16494OJS9911310

On the predictability of postoperative complications for cancer patients: a Portuguese cohort study

Funding Information: This work was supported by the FCT, through IDMEC, under LAETA project (UIDB/50022/2020), IPOscore project with reference DSAIPA/DS/0042/2018, and Data2Help (DSAIPA/DS/0044/2018). This work was further supported by the Associate Laboratory for Green Chemistry – LAQV which is financed by national funds from FCT/MCTES (UIDB/50006/2020, UIDP/50006/2020), INESC-ID pluriannual (UIDB/50021/2020), and the contract CEECIND/01399/2017. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.Postoperative complications are still hard to predict despite the efforts towards the creation of clinical risk scores. The published scores contribute for the creation of specialized tools, but with limited predictive performance and reusability for implementation in the oncological context. This work aims to predict postoperative complications risk for cancer patients, offering two major contributions. First, to develop and evaluate a machine learning-based risk score, specific for the Portuguese population using a retrospective cohort of 847 cancer patients undergoing surgery between 2016 and 2018, for 4 outcomes of interest: (1) existence of postoperative complications, (2) severity level of complications, (3) number of days in the Intermediate Care Unit (ICU), and (4) postoperative mortality within 1 year. An additional cohort of 137 cancer patients from the same center was used for validation. Second, to improve the interpretability of the predictive models. In order to achieve these objectives, we propose an approach for the learning of risk predictors, offering new perspectives and insights into the clinical decision process. For postoperative complications the Receiver Operating Characteristic Curve (AUC) was 0.69, for complications’ severity AUC was 0.65, for the days in the ICU the mean absolute error was 1.07 days, and for 1-year postoperative mortality the AUC was 0.74, calculated on the development cohort. In this study, predictive models which could help to guide physicians at organizational and clinical decision making were developed. Additionally, a web-based decision support tool is further provided to this end.publishersversionpublishe

Image Denoising using Attention-Residual Convolutional Neural Networks

During the image acquisition process, noise is usually added to the data mainly due to physical limitations of the acquisition sensor, and also regarding imprecisions during the data transmission and manipulation. In that sense, the resultant image needs to be processed to attenuate its noise without losing details. Non-learning-based strategies such as filter-based and noise prior modeling have been adopted to solve the image denoising problem. Nowadays, learning-based denoising techniques showed to be much more effective and flexible approaches, such as Residual Convolutional Neural Networks. Here, we propose a new learning-based non-blind denoising technique named Attention Residual Convolutional Neural Network (ARCNN), and its extension to blind denoising named Flexible Attention Residual Convolutional Neural Network (FARCNN). The proposed methods try to learn the underlying noise expectation using an Attention-Residual mechanism. Experiments on public datasets corrupted by different levels of Gaussian and Poisson noise support the effectiveness of the proposed approaches against some state-of-the-art image denoising methods. ARCNN achieved an overall average PSNR results of around 0.44dB and 0.96dB for Gaussian and Poisson denoising, respectively FARCNN presented very consistent results, even with slightly worsen performance compared to ARCNN.Comment: Published in: 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI

Line-Strength Indices in Bright Spheroidals: Evidence for a Stellar Population Dichotomy between Spheroidal and Elliptical Galaxies

We present new measurements of central line-strength indices (namely Mg2, , and Hbeta and gradients for a sample of 6 bright spheroidal galaxies (Sph's) in the Virgo cluster. Comparison with similar measurements for elliptical galaxies (E's), galactic globular clusters (GGC's), and stellar population models yield the following results: (1) In contrast with bright E's, bright Sph's are consistent with solar abundance [Mg/Fe] ratios; (2) Bright Sph's exhibit metallicities ranging from values typical for metal-rich GGC's to those for E's; (3) Although absolute mean ages are quite model dependent, we find evidence that the stellar populations of some (if not all) Sph's look significantly younger than GGC's; and (4) Mg2 gradients of bright Sph's are significantly shallower than those of E galaxies. We conclude that the dichotomy found in the structural properties of Sph and E galaxies is also observed in their stellar populations. A tentative interpretation in terms of differences in star formation histories is suggested.Comment: 14 pages, LaTeX file + 2 PostScript figures, aasms4.sty require

Non-essential elements and their role in sustainable agriculture

Agricultural systems are constantly under environmental pressure, and the continuous rise of the global population requires an increasingly intensification of agronomical productivity. To meet the current global food demand, particularly in depleted ecosystems under adverse climate conditions, the development of novel agronomical practices, which ensure crop productivity while safeguarding minimal impact to the environment, must be encouraged. Since aluminium (Al), cobalt (Co), selenium (Se), silicon (Si) and sodium (Na) are not essential to plant metabolism, their benefits are often neglected or underestimated in agriculture; however, several studies support their advantages in sustainable agriculture when properly employed. The agronomical uses of these elements have been studied in the last decades, delivering important cues for the improvement of food and feed production worldwide due to beneficial effects in plant growth and productivity, nutrient balance, pest and pathogen resistance, water stress management, heavy-metal toxicity alleviation, and postharvest performance. However, their application has not been addressed as part of a holistic conservation strategy that supports the sustainability of agroecosystems. Here, we discuss the potential use of these elements in sustainable agriculture, and the knowledge gaps that hinder their effective integration into agronomical practices, which result in equally profitable applications while supporting environmental sustainability.info:eu-repo/semantics/publishedVersio