Previsão da procura na indústria do vestuário

Dissertação de mestrado integrado em Engenharia e Gestão IndustrialTradicionalmente, produtos de moda, designadamente na indústria do vestuário, incorrem em grandes perdas devido a quebras de stock e a stocks obsoletos, devido a dois fatores muito caraterísticos deste mercado, longos tempos de processamento dos produtos, combinado com a concentração das vendas em períodos muito curtos. Assim sendo, as previsões de vendas tem tido um papel cada vez maior na cadeia de abastecimento, e cada vez mais relevantes para a manutenção da competitividade num mercado cada vez mais globalizado e concorrencial. Nesse sentido, surge o projeto de investigação apresentado nesta dissertação, que consiste no desenvolvimento de um modelo de previsão da procura para a empresa Cruz&Areal, detentora da marca BusUrban Wear. O atual processo de previsão da procura (indutivo, sem qualquer base matemática), tem conduzido a elevados custos provenientes de excesso ou quebras de stocks. Neste sentido, o projeto de desenvolvimento de um modelo de previsão tem como objetivo atingir um valor de erro reduzido (erro percentual absoluto médio próximo de 10%), que permita a racionalização dos recursos envolvidos e a maximização da faturação proveniente da redução de stocks conjugada com a minimização das quebras. Na fase inicial do projeto, foi efetuada a revisão da literatura que incidiu na análise dos conceitos, técnicas e abordagens no processo de previsão. Esta revisão bibliográfica foi importante para uma melhor compreensão das dificuldades e desafios associados aos métodos de previsão de novos produtos e a analisar possíveis abordagens para ultrapassar estas dificuldades. A fase seguinte consistiu na aplicação das abordagens referidas na literatura no sentido de verificar a adaptabilidade das mesmas à tipologia do problema, sendo necessário recorrer a uma série de métodos para a obtenção de resultados enquadrados com o objetivo. A última fase consistiu num estudo originado pelo tratamento dos dados, que indicava uma grande oportunidade de optimizar o mostruário (grupo de peças de coleção propostas aos clientes), podendo levar a poupanças muito significativas e a um eficiente aproveitamento dos recursos.Traditionally, fashion products, particularly in the garment industry have incurred high losses due to stock outs and inventory obsolete caused by two factors very characteristic of this market, long lead times, combined with the concentration of sales in very short periods. Therefore, sales forecasts have had a growing role in the supply chain, and more and more relevant to maintaining competitiveness in an increasingly globalized and competitive market. In this regard, arises the research project presented in this dissertation, which is to develop a model for forecasting demand to the company Cruz&Areal, owner of the brand Bus Urban Wear. The current process of forecasting demand (inductive, without any mathematical foundation), has led to high costs from excess stocks or breaks. In this sense, the project of developing a forecasting model aims to achieve a low error value (mean absolute percentage error around 10%), allowing the rationalization of resources involved and the maximization of billing from the lower inventories combined with minimization of stock outs. In the initial phase of the project was made a literature review that focused on the analysis of concepts, techniques and approaches in the forecasting process. This literature review was important for a better understanding of the difficulties and challenges associated with forecasting methods of new products and analyze possible approaches to overcome these difficulties. The next step was the application of these approaches referred in the literature in order to verify the adaptability of them to the typology of the problem, being necessary use a number of methods for obtaining results framed with the objective. The final stage consisted of a study caused by the processing of data, which indicated a great opportunity to optimize the showcase (group of collection pieces offered to customers), that can lead to very significant savings and an efficient use of resources

Beyond new neurons in the adult hippocampus: imipramine acts as a pro-astrogliogenic factor and rescues cognitive impairments induced by stress exposure

Depression is a prevalent, socially burdensome disease. Different studies have demonstrated the important role of astrocytes in the pathophysiology of depression as modulators of neurotransmission and neurovascular coupling. This is evidenced by astrocyte impairments observed in brains of depressed patients and the appearance of depressive-like behaviors upon astrocytic dysfunctions in animal models. However, little is known about the importance of de novo generated astrocytes in the mammalian brain and in particular its possible involvement in the precipitation of depression and in the therapeutic actions of current antidepressants (ADs). Therefore, we studied the modulation of astrocytes and adult astrogliogenesis in the hippocampal dentate gyrus (DG) of rats exposed to an unpredictable chronic mild stress (uCMS) protocol, untreated and treated for two weeks with antidepressants—fluoxetine and imipramine. Our results show that adult astrogliogenesis in the DG is modulated by stress and imipramine. This study reveals that distinct classes of ADs impact differently in the astrogliogenic process, showing different cellular mechanisms relevant to the recovery from behavioral deficits induced by chronic stress exposure. As such, in addition to those resident, the newborn astrocytes in the hippocampal DG might also be promising therapeutic targets for future therapies in the neuropsychiatric field.ARMS: ELC, NDA, PP, AMP, JSC, MM, AJR, JFO, and L.P. received fellowships from the Portuguese Foundation for Science and Technology (FCT) (IF/00328/2015 to J.F.O.; 2020.02855.CEECIND to LP). This work was funded by FCT (IF/01079/2014, PTDC/MED-NEU/31417/2017 Grant to JFO), BIAL Foundation Grants (037/18 to J.F.O. and 427/14 to L.P.), “la Caixa” Foundation Health Research Grant (LCF/PR/HR21/52410024) and Nature Research Award for Driving Global Impact—2019 Brain Sciences (to L.P.). This was also co-funded by the Life and Health Sciences Research Institute (ICVS), and by FEDER, through the Competitiveness Internationalization Operational Program (POCI), and by National funds, through the Foundation for Science and Technology (FCT)—project UIDB/50026/2020 and UIDP/50026/2020. Moreover, this work has been funded by ICVS Scientific Microscopy Platform, member of the national infrastructure PPBI—Portuguese Platform of Bioimaging (PPBI-POCI-01-0145-FEDER-022122; by National funds, through the Foundation for Science and Technology (FCT)—project UIDB/50026/2020 and UIDP/50026/2020; “la Caixa” Foundation (ID 100010434 to A.J.R.), under the agreement LCF/PR/HR20/52400020; and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 101003187 to A.J.R.)

Comparative complete scheme and booster effectiveness of COVID‐19 vaccines in preventing SARS‐CoV‐2 infections with SARS‐CoV‐2 Omicron (BA.1) and Delta (B.1.617.2) variants: A case–case study based on electronic health records

Background: Information on vaccine effectiveness in a context of novel variants of concern (VOC) emergence is of key importance to inform public health policies. This study aimed to estimate a measure of comparative vaccine effectiveness between Omicron (BA.1) and Delta (B.1.617.2 and sub-lineages) VOC according to vaccination exposure (primary or booster). Methods: We developed a case–case study using data on RT-PCR SARS-CoV2-positive cases notified in Portugal during Weeks 49–51, 2021. To obtain measure of comparative vaccine effectiveness, we compared the odds of vaccination in Omicron cases versus Delta using logistic regression adjusted for age group, sex, region, week of diagnosis, and laboratory of origin. Results: Higher odds of vaccination were observed in cases infected by Omicron VOC compared with Delta VOC cases for both complete primary vaccination (odds ratio [OR] = 2.1; 95% confidence interval [CI]: 1.8 to 2.4) and booster dose (OR = 5.2; 95% CI: 3.1 to 8.8), equivalent to reduction of vaccine effectiveness from 44.7% and 92.8%, observed against infection with Delta, to 6.0% (95% CI: 29.2% to 12.7%) and 62.7% (95% CI: 35.7% to 77.9%), observed against infection with Omicron, for complete primary vaccination and booster dose, respectively. Conclusion: Consistent reduction in vaccine-induced protection against infection with Omicron was observed. Complete primary vaccination may not be protective against SARS-CoV-2 infection in regions where Omicron variant is dominant.Grant no. 2021/PHF/23776; POCI-01-0145-FEDER-022184; Project ALG-D2-2021-06info:eu-repo/semantics/publishedVersio

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -- corrected for geometrical effects -- is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO

Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy

We measure the energy emitted by extensive air showers in the form of radio emission in the frequency range from 30 to 80 MHz. Exploiting the accurate energy scale of the Pierre Auger Observatory, we obtain a radiation energy of 15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV arriving perpendicularly to a geomagnetic field of 0.24 G, scaling quadratically with the cosmic-ray energy. A comparison with predictions from state-of-the-art first-principle calculations shows agreement with our measurement. The radiation energy provides direct access to the calorimetric energy in the electromagnetic cascade of extensive air showers. Comparison with our result thus allows the direct calibration of any cosmic-ray radio detector against the well-established energy scale of the Pierre Auger Observatory.Comment: Replaced with published version. Added journal reference and DOI. Supplemental material in the ancillary file

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution