A knowledge-intensive methodology for explainable sales prediction

Sales prediction in food market is a complex issue that has been addressed in the recent past with machine learning techniques. Although some promising results, an experimental work that we describe in this paper shows some drawbacks of the above mentioned data-driven method and habilitates the definition of a novel methodology, strongly involving a piori knowledg

Protecting the environment: A multi-agent approach to environmental monitoring

In this paper we discuss a transition model from commonly adopted models of data gathering, transfer and management for environmental monitoring towards more sophisticated ones based on Artificial Intelligence and IoT. The transition model is based on the paradigm of multiple agent systems. The adoption of this transition model is motivated by the need to improve effectiveness, efficiency and interoperability of environmental monitoring by simultaneously guaranteeing its sustainability in economic term

A machine learning and chemometrics assisted interpretation of spectroscopic data: a NMR-based metabolomics platform for the assessment of Brazilian propolis

In this work, a metabolomics dataset from 1H nuclear magnetic resonance spectroscopy of Brazilian propolis was analyzed using machine learning algorithms, including feature selection and classification methods. Partial least square-discriminant analysis (PLS-DA), random forest (RF), and wrapper methods combining decision trees and rules with evolutionary algorithms (EA) showed to be complementary approaches, allowing to obtain relevant information as to the importance of a given set of features, mostly related to the structural fingerprint of aliphatic and aromatic compounds typically found in propolis, e.g., fatty acids and phenolic compounds. The feature selection and decision tree-based algorithms used appear to be suitable tools for building classification models for the Brazilian propolis metabolomics regarding its geographic origin, with consistency, high accuracy, and avoiding redundant information as to the metabolic signature of relevant compounds.The work is partially funded by ERDF -European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects ref. COMPETE FCOMP-01-0124-FEDER-015079 and PEstOE/ EEI/UI0752/2011. RC's work is funded by a PhD grant from the Portuguese FCT ( ref. SFRH/BD/66201/2009)

A 1H-NMR-based metabolomic analysis of propolis from Santa Catarina state

16th IUFoST World Congress of Food Science and Technology: Addressing Global Food Security and Wellness through Food Science and TechnologyPropolis is a resinous biomass produced by honeybees from exudates of local flora. It has been used since ancient times in folk medicine and in recent years has been added to foods and beverages to improve health and prevent diseases. The chemical composition of propolis is highly variable and depends on the climate, season, specie of bee, and mainly the local flora visited by bees to collect resin. In order to identify groups of chemical similarity among samples (n=20 autumn, n=16 winter, n=19 spring, n=17 summer) of propolis produced in Santa Catarina (SC) state (southern Brazil - 2010), lyophilized ethanolic extracts (200 mg/ml, EtOH 70%, v/v) were solubilized in MeOD3 (700l) and analyzed by NMR spectroscopy. One-dimensional 1HNMR spectra were acquired at a magnetic field strength of 500,13/125,03 MHz using a Varian Inova 500 MHz equipment and standard conditions of data acquisition. The 1H-NMR peak list data set was processed under MetaboAnalyst 2.0. suite, computing the resonances at 0.80- 12ppm spectral window. Principal Components Analysis (PCA) score scatter plots (PC1 88.2% x PC2 2.2%) clearly demonstrated samples discriminated mainly according to the season of production. These results suggest that not only geographical origin is important for the classification of propolis, but the seasonal effects as well. Since seasons directly influence the flora available from where bees collect resin, the propolis chemical profile can be significantly modified over the seasons even from a same geographical origin.info:eu-repo/semantics/publishedVersio

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.Financial support for this investigation by National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Brazilian Biosciences National Laboratory (LNBioCNPEM/MCTI), Foundation for Support of Scientific and Technological Research in the State of Santa Catarina (FAPESC), and Portuguese Foundation for Science and Technology (FCT) is acknowledged. The research fellowship granted by CNPq to the first author is also acknowledged. The work was partially funded by a CNPq and FCT agreement through the PropMine grant

UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)

In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.FAPESC (Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina) and CNPq (Conselho Nacional de Desenvolvimento Cientıfico e Tecnologico) for financial support. The research fellowship from CNPq on behalf of the last author is acknowledged. The work is partially funded by Project PropMine, funded by the agreement between Portuguese FCT and Brazilian CNPq. The authors also thank the FCT Strategic Project of UID/BIO/04469/2013 uni

A five-year retrospective study of the epidemiological characteristics and visual outcomes of patients hospitalized for ocular trauma in a Mediterranean area

<p>Abstract</p> <p>Background</p> <p>To determine the epidemiological characteristics and visual outcome of ocular trauma in southern Italy.</p> <p>Methods</p> <p>All cases of ocular trauma admitted to Department of Ophthalmology of Palermo University, Italy, from January 2001–December 2005 were retrospectively reviewed for open- or closed-globe injury (OGI or CGI). Data extracted included age, sex, residence, initial and final visual acuity (VA), cause and treatment of injury, hospitalization. The injuries were classified by Ocular Trauma Classification System (OTCS) and Birmingham Eye Trauma Terminology (BETT). We also referred to the Ocular Trauma Score (OTS) in evaluating the final visual outcome.</p> <p>Results</p> <p>Of the 298 eyes, there were 146 OGI and 152 CGI. Fifty eyes (16.8%) had an intraocular foreign body (IOFB). The annual incidence of eye injuries was 4.9 per 100,000. Most injuries occurred in men (84.6%, p < 0.0005), with an average age of 33.0 vs. 49.9 for women (p = 0.005). Cause of injury differed significantly by gender (p = 0.001) and urban vs. rural location (p = 0.009). The most frequent causes in men were outdoor activities related injuries (30.9%), work-related (25.4%), and sport-related (17.5%), and in women were home-related (52.2%) and outdoor activities related injuries (30.4%). In urban areas, road accidents were more frequent; in rural areas, work-related injuries were more frequent with a greater rate of IOFBs than in urban areas (p = 0.002).</p> <p>The incidence of OGI and CGI differed in work-related injuries (p < 0.0005), sport-related injuries (p < 0.0005), and assaults (p = 0.033). The final visual acuity was 20/40 (6/12) or better in 144 eyes (48.3%), 20/40–20/200 (6/12–6/60) in 90 eyes (30.2%), and <20/200 (6/60) or less in 46 eyes (15.5%). Eighteen eyes (6%) had a final acuity of no light perception. Of those eyes that presented with hand motion vision or better, 220 (86.6%) had a final vision of better than 20/200 (6/60). Initial visual acuity was found to be correlated with final visual acuity (Spearman's correlation coefficient = 0.658; p < 0.001). The likelihood of the final visual acuities in the OTS categories was correlated to that of the OTS study group in 12 of 14 cases (85.7%).</p> <p>Conclusion</p> <p>This analysis provides insight into the epidemiology of patients hospitalized for ocular trauma. The findings indicate that ocular trauma is a significant cause of visual loss in this population.</p

Factors associated with serum 25-hydroxyvitamin D concentrations in older people in Europe: the EUREYE study.

BACKGROUND/OBJECTIVES: We aimed to describe serum 25-hydroxyvitamin D (25OHD) concentrations in older Europeans and to investigate associations between 25OHD and lifestyle factors, including dietary intake and supplement use. SUBJECTS/METHODS: Men and women aged ≥ 65 years were recruited from seven centres across north to south Europe. Serum 25OHD2 and 25OHD3 concentrations were measured by liquid chromatography tandem mass spectrometry (LC-MS/MS) in 4495 samples and total 25OHD (25OHD2 + 25OHD3) was adjusted for season of blood collection. RESULTS: The mean (25th, 75th quartile) of seasonally adjusted 25OHD was 46 (34, 65) nmol/L, with the highest concentration of 25OHD in Bergen [61 (49, 79) nmol/L], and the lowest in Paris [36 (24, 57) nmol/L)]. Vitamin D deficiency (25-50 nmol/L) and vitamin D insufficiency (50-75 nmol/L) were found in 41 and 33% of the population, respectively. In multivariable analysis controlled for confounders, seasonally adjusted 25OHD concentrations were significantly (p < 0.05) lower in smokers and participants with self-reported diabetes and higher with increasing dietary vitamin D, and supplement use with fish liver oil, omega-3, and vitamin D. Additionally, in further analysis excluding Bergen, 25OHD was associated with higher intakes of oily fish and increasing UVB exposure. We observed low concentrations of 25OHD in older people in Europe. CONCLUSIONS: Our findings of the higher 25OHD concentrations in supplement users (omega-3 fish oil, fish liver oil, vitamin D) add to current recommendations to reduce vitamin D deficiency. We were unable to fully assess the role of dietary vitamin D as we lacked information on vitamin D-fortified foods