Bounded rationality in decision making: Biases in managers of the Portuguese port sector

Decision-making is a multidisciplinary and ubiquitous phenomenon in organizations, and it can be observed at the individual, group, and organizational levels. Decision making plays, however, an increasingly important role for the manager, whose cognitive competence is reflected in his ability to identify potential opportunities, to immediately detect and solve the problems he faces, and to predict and prevent future threats. Nevertheless, to what extent do managers of the most diverse sectors continue to rely on false knowledge when they have better strategies at their disposal? The present article proposes the diagnosis of three prominent biases – overconfidence, optimism, and anchoring effect – in managers of the Portuguese port sector, as well as a comparative analysis with the conclusions already documented in relation to the Brazilian civil construction sector. In addition, this paper also provides a set of measures capable of contributing to the mitigation of the effects of these and other biases.info:eu-repo/semantics/publishedVersio

Padrões de inativação microbiana em hortelã-pimenta por radiação gama

As plantas podem ter várias aplicações, especialmente como aditivos alimentares e na promoção da saúde, como ingredientes em formulações de alimentos funcionais e nutracêuticos. Contudo, um dos maiores problemas associados ao seu consumo e comercialização é a sua contaminação microbiana. Esta contaminação pode ocorrer ao longo da colheita, processamento e distribuição. Deste modo, torna-se necessário encontrar uma solução viável para a conservação de plantas comestíveis ou medicinais e que cumpra as normas de segurança alimentar e farmacêutica. Atualmente, o processamento de ervas e especiarias por radiação ionizante é aceite como uma tecnologia segura e eficaz na descontaminação e desinfeção microbiana. Porém, a maioria dos estudos em irradiação de plantas incide nos efeitos da tecnologia nas propriedades químicas das plantas. O objetivo específico deste trabalho foi estudar os padrões de inativação por radiação gama da microbiota de Mentha x piperita (hortelã-pimenta). A metodologia seguida baseouse na determinação da carga microbiana (bactérias mesófilas e fungos filamentosos) de amostras secas de hortelãpimenta antes e após irradiação a várias doses de radiação gama (1,5 kGy e 10 kGy), recorrendo a métodos convencionais de cultura. As irradiações foram efetuadas num equipamento de Co-60 a um débito de dose de 1,2 kGy/h. Os resultados obtidos indicaram uma cinética de inativação não-linear (côncava) para a população bacteriana das plantas, e uma curva de sobrevivência linear para a população de fungos filamentosos. A análise da contaminação diferencial das amostras indicou após irradiação a 10 kGy, um decréscimo de 3 log em relação à carga bacteriana inicial de 5 log UFC/g, e uma redução de 2 log para a população fúngica inicial de 4 UFC/g. De referir, que não foi detetada a presença de coliformes totais nas amostras irradiadas a partir dos 1,5 kGy. Resumidamente, as eficiências máximas de inativação para as condições do estudo foram de 99,9% para a população bacteriana e de 99% para a população fúngica. Assim, este estudo sugere a tecnologia de irradiação, como um tratamento promissor e mais amigo do ambiente, pretendendo-se validar a sua aplicação na descontaminação/desinfeção microbiana de plantas secas com interesse alimentar e medicinal, sobre as quais este tipo de processamento e seus efeitos não se encontra documentado

Padrões de inactivação microbiana em hortelã-pimenta por radiação gama

As plantas podem ser utilizadas como aditivos alimentares e em benefício da saúde, como ingredientes em formulações de alimentos funcionais e nutracêuticos. Um dos principais problemas associado ao seu consumo e comercialização é a sua contaminação microbiana, que pode ocorrer ao longo da colheita, no processamento e na distribuição. Deste modo, torna-se necessário encontrar uma solução viável para a conservação de plantas comestíveis ou medicinais e que cumpra as normas de segurança alimentar e farmacêutica. Actualmente, o processamento de ervas e especiarias por radiação ionizante é reconhecido como uma tecnologia segura e eficaz na descontaminação e desinfecção microbiana. Porém, a maioria dos estudos em irradiação de plantas incide nos efeitos da tecnologia nas propriedades químicas das plantas. O objectivo específico deste trabalho foi estudar os padrões de inactivação por radiação gama da microbiota de Mentha x piperita (hortelã-pimenta). A metodologia seguida baseou-se na determinação da carga microbiana (bactérias mesófilas e fungos filamentosos) de amostras secas de hortelã-pimenta antes e após irradiação a várias doses de radiação gama (1,5 kGy a 10 kGy), recorrendo a métodos convencionais de cultura. As irradiações foram efectuadas num equipamento de 60Co a um débito de dose de 1,2 kGy/h. Os resultados obtidos indicaram uma cinética de inactivação não-linear (côncava) para a população bacteriana das plantas, e uma curva de sobrevivência linear para a população de fungos filamentosos. A análise da contaminação diferencial das amostras indicou após irradiação a 10 kGy, um decréscimo de 3 log em relação à carga bacteriana inicial de 5 log UFC/g, e uma redução de 2 log para a população fúngica inicial de 4 UFC/g. De referir, que não foi detectada a presença de coliformes totais nas amostras irradiadas a partir dos 1,5 kGy. As eficiências máximas de inactivação observadas nas condições do estudo foram de 99,9% para a população bacteriana e de 99% para a população fúngica. Assim, este estudo sugere a tecnologia de irradiação, como um tratamento promissor e mais amigo do ambiente, pretendendo-se validar a sua aplicação na descontaminação/desinfecção microbiana de plantas secas com interesse alimentar e medicinal, sobre as quais este tipo de processamento e seus efeitos não se encontra documentado.PRODER - Projecto AROMAP e FCT (Portugal) RECI/AAG-TEC/0400/2012 pelo apoio financeiro à execução do trabalho e à empresa “MaisErvas - Aromáticas e Medicinais” (Portugal), pela disponibilização das amostras

Assessment of gamma radiation effects on antioxidant activity of cork wastewater

Cork cooking wastewater results from the process of boiling cork planks. It is an aqueous and complex dark liquor with high concentration of phenolic compounds such as phenolic acids and tannins [1, 2], which are known for their high antioxidant activity. The aim of this work is to perform a compreensive assessment of the effects of gamma radiation on the antioxidant activity of cork cooking water. The irradiation experiments were carried out at room temperature in a Co-60 experimental equipment (Prescisa 22, Graviner, Lda, UK), with an activity of 140 Tbq (3.77 kCi) and at a dose rate of 1.5 kGy/h, located at the Centro de Ciências e Tecnologias Nucleares (Portugal). Samples of wastewater were irradiated at. three distinct. doses (10, 20 and 50 KGy) and the antioxidant activity was evaluated by in vitro assays based on different mechanisms of action: DPPH radical scavenging activity, reducing power and inhibition of β-carotene bleaching. Antioxidant capacity was compared with the physico-chemical characterization [3) of cork wastewater - Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Total Suspended Solids (TSS) and Total Phenolic Content. (TP) - when exposed to gamma radiation. The obtained results point out that gamma radiation induces changes in complex compounds leading to an increase in the antioxidant capacity. These results demonstrate the potential of this technology in order to increase the added value of cork wastewaters.We are grateful to FCT (Portugal) by the supporting of RECI/AAG-TEC/0400/2012 "Application of lonizing Radiation for a Sustainable Environment" project and to lnternational Atomic Energy Agency (Austria) by the supporting of CRP 1539 - F23029 "Radiation Treatment of Wastewater for Reuse with Particular Focus on Wastewaters Containing Organic Pollutants"' project.info:eu-repo/semantics/publishedVersio

Enzyme classification with peptide programs: a comparative study

<p>Abstract</p> <p>Background</p> <p>Efficient and accurate prediction of protein function from sequence is one of the standing problems in Biology. The generalised use of sequence alignments for inferring function promotes the propagation of errors, and there are limits to its applicability. Several machine learning methods have been applied to predict protein function, but they lose much of the information encoded by protein sequences because they need to transform them to obtain data of fixed length.</p> <p>Results</p> <p>We have developed a machine learning methodology, called peptide programs (PPs), to deal directly with protein sequences and compared its performance with that of Support Vector Machines (SVMs) and BLAST in detailed enzyme classification tasks. Overall, the PPs and SVMs had a similar performance in terms of Matthews Correlation Coefficient, but the PPs had generally a higher precision. BLAST performed globally better than both methodologies, but the PPs had better results than BLAST and SVMs for the smaller datasets.</p> <p>Conclusion</p> <p>The higher precision of the PPs in comparison to the SVMs suggests that dealing with sequences is advantageous for detailed protein classification, as precision is essential to avoid annotation errors. The fact that the PPs performed better than BLAST for the smaller datasets demonstrates the potential of the methodology, but the drop in performance observed for the larger datasets indicates that further development is required.</p> <p>Possible strategies to address this issue include partitioning the datasets into smaller subsets and training individual PPs for each subset, or training several PPs for each dataset and combining them using a bagging strategy.</p

Degradation of compounds present in cork boiling water by gamma radiation

Cork boiling water is an aqueous and complex dark liquor with high concentration of phenolic compounds such as phenolic acids and tannins [1, 2], which are considered biorecalcitrants [2]. Ionizing radiation has been widely studied as an alternative technology for the degradation of organic contaminants without the addition of any other (e.g.: Fenton technologies). The aim of this work was to identify the compounds present in cork boiling water and further evaluate the resulting stable degradation products after gamma irradiation. The irradiation experiments of standard solutions were carried out at room temperature using a Co-60 experimental equipment. The applied absorbed doses were 20 and 50 kGy at a dose rate of 1.5 kGy/h, determined by routine dosimeters [3]. The identification of radiolytic products was carried out by HPLC-DAD-ESI/MS. The phenolic compounds were identified by comparing their retention times and UV–vis and mass spectra with those obtained from standard compounds, when available, as well as by comparing the obtained information with available data reported in the literature. Concerning the obtained results and the literature review, the main cork wastewater components are: quinic, gallic, protocatechuic, vanillic, syringic and ellagic acids. Based on this, we used protocatechuic, vanillic and syringic acids as model compounds to study their degradation by gamma radiation in order to identify the corresponding radiolytic products. Standard aqueous solutions were irradiated and the derivatives of each model compound are represented in figure 1. The obtained results seem to demonstrate that the derivatives of the parent compounds could also be phenolic acids, since it was observed the loss of 44 u (CO2) from the [M-H]- ions. Gallic and protocatechuic acids are identified as derivatives of vanillic and syringic acids, and gallic acid as a protocatechuic acid derivative. Compound 5 ([M-H]- at m/z 169) was tentatively identified as 2,4,6-trihydroxybenzoic acid, since its fragmentation pattern (m/z 151, 125 and 107) is similar to that previously reported in literature [4]. The structure of compound 7 was proposed based on the molecular ion and its fragmentation and compound 6 remains unknown

Land Cover Classification from Multispectral Data Using Computational Intelligence Tools: A Comparative Study

This article discusses how computational intelligence techniques are applied to fuse spectral images into a higher level image of land cover distribution for remote sensing, specifically for satellite image classification. We compare a fuzzy-inference method with two other computational intelligence methods, decision trees and neural networks, using a case study of land cover classification from satellite images. Further, an unsupervised approach based on k-means clustering has been also taken into consideration for comparison. The fuzzy-inference method includes training the classifier with a fuzzy-fusion technique and then performing land cover classification using reinforcement aggregation operators. To assess the robustness of the four methods, a comparative study including three years of land cover maps for the district of Mandimba, Niassa province, Mozambique, was undertaken. Our results show that the fuzzy-fusion method performs similarly to decision trees, achieving reliable classifications; neural networks suffer from overfitting; while k-means clustering constitutes a promising technique to identify land cover types from unknown areas

Salmonella typhimurium inactivation in Mentha x piperita L. by gamma irradiation

Salmonella is an importante foodborne pathogen and one of the most significant causes of bacterial gastroenteritis around the world (1). Its transmission occurs through the ingestion of contaminated fruits, vegetables or aromatic plants. Many studies have described a relation between Salmonela transmission and the consumption of aromatic herbs, like Mentha x piperita L. (2].info:eu-repo/semantics/publishedVersio

Mining GO Annotations for Improving Annotation Consistency

<div><p>Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the quality of electronically inferred annotations. In this work, we analyze the full GO molecular function annotation of UniProtKB proteins, and discuss some of the issues that affect their quality, focusing particularly on the lack of annotation consistency. Based on our analysis, we estimate that 64% of the UniProtKB proteins are incompletely annotated, and that inconsistent annotations affect 83% of the protein functions and at least 23% of the proteins. Additionally, we present and evaluate a data mining algorithm, based on the association rule learning methodology, for identifying implicit relationships between molecular function terms. The goal of this algorithm is to assist GO curators in updating GO and correcting and preventing inconsistent annotations. Our algorithm predicted 501 relationships with an estimated precision of 94%, whereas the basic association rule learning methodology predicted 12,352 relationships with a precision below 9%.</p> </div