809 research outputs found
The clustering conditions for managing creative tourism destinations: the Alqueva region case, Portugal
This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this recordThe paper discusses conditions and format of a cluster model to support the management of a potential creative tourism destination in a setting where regional cross-sectoral collaboration is lacking. Creative tourism development requires a flexible framework and a healthy collaboration environment, more so when associated with resources shared by several stakeholders. This article focuses on the tourism potential of archaeological knowledge discovered during the environmental impact assessment of the Alqueva dam (Alentejo, Portugal). Interviews were conducted with 38 regional actors in the tourism and heritage sectors, as well as the dam developers and the companies responsible for archaeological interventions. Findings indicate that the lack of specific local policy addressing archaeological heritage hampers its potential use for tourism development, which is further aggravated by the absence of stakeholder communication and cooperation. A conceptual cluster model for the management of creative tourism destinations based on heritage resources and other local resources is proposed.Portuguese national funding agency for Science, Research and Technology (FCT
Short-term water demand forecasting using machine learning techniques
Nowadays, a large number of water utilities still manage their operation on the instant water demand of
the network, meaning that the use of the equipment is conditioned by the immediate water necessity.
The water reservoirs of the networks are filled using pumps that start working when the water level
reaches a specified minimum, stopping when it reaches a maximum level. Shifting the focus to water
management based on future demand allows use of the equipment when energy is cheaper, taking
advantage of the electricity tariff in action, thus bringing significant financial savings over time. Shortterm water demand forecasting is a crucial step to support decision making regarding the equipment
operation management. For this purpose, forecasting methodologies are analyzed and implemented.
Several machine learning methods, such as neural networks, random forests, support vector machines
and k-nearest neighbors, are evaluated using real data from two Portuguese water utilities. Moreover,
the influence of factors such as weather, seasonality, amount of data used in training and forecast
window is also analysed. A weighted parallel strategy that gathers the advantages of the different
machine learning techniques is suggested. The results are validated and compared with those achieved
by autoregressive integrated moving average (ARIMA) also using benchmarks.publishe
Increased performance in the short-term water demand forecasting through the use of a parallel adaptive weighting strategy
Recent research on water demand short-term forecasting has shown that models using univariate time
series based on historical data are useful and can be combined with other prediction methods to reduce
errors. The behavior of water demands in drinking water distribution networks focuses on their repetitive
nature and, under meteorological conditions and similar consumers, allows the development of a heuristic forecast model that, in turn, combined with other autoregressive models, can provide reliable forecasts. In this study, a parallel adaptive weighting strategy of water consumption forecast for the next 24–48 h, using univariate time series of potable water consumption, is proposed. Two Portuguese potable water distribution networks are used as case studies where the only input data are the consumption of water and the national calendar. For the development of the strategy, the Autoregressive Integrated Moving Average (ARIMA) method and a short-term forecast heuristic algorithm are used. Simulations with the model showed that, when using a parallel adaptive weighting strategy, the prediction error can be reduced by 15.96% and the average error by 9.20%. This reduction is important in the control and management of water supply systems. The proposed methodology can be extended to other forecast
methods, especially when it comes to the availability of multiple forecast models.by UE/FEDER through the program COMPETE 2020 and UID/EMS/00481/2013-FCT under CENTRO-01-0145-FEDER- 022083publishe
Cross-sectional and prospective associations between moderate to vigorous physical activity and sedentary time with adiposity in children.
BACKGROUND: Physical activity (PA) and sedentary time (SED) have both been suggested as potential risk factors for adiposity in children. However, there is paucity of data examining the temporal associations between these variables. OBJECTIVE: This study aimed to analyze the cross-sectional and prospective associations between PA, SED and body composition in children. METHODS: A total of 510 children (age at baseline 10.1±0.8, age at follow-up 11.8±0.9) from six Portuguese schools from the Oeiras Municipality participated in this study. PA and SED were measured by accelerometry and trunk fat mass (TFM) and body fat mass (BFM) were measured by dual energy X-ray absorptiometry. Fat mass index (FMI) was calculated as BFM divided by height squared. Several regression models adjusted for age, sex, maturity status, follow-up duration, baseline levels of the outcome variable and SED or moderate to vigorous PA (MVPA) were performed. RESULTS: MVPA (min per day) was cross-sectionally inversely associated with adiposity indexes (FMI, TFM and BFM). Adiposity indexes were inversely associated with time in MVPA. In prospective analyses, MVPA was associated with a lower levels of FMI (β=-0.37, 95% confidence interval (CI): -0.49 to -0.26, P<0.001), TFM (β=-0.20, 95% CI: -0.29 to -0.10, P<0.001) and BFM (β=-0.37, 95% CI: -0.49 to -0.26, P<0.001). When the model was adjusted for age, sex, maturity status and for baseline levels of the outcome variables MVPA remained a significant predictor of lower adiposity indexes (FMI: β=-0.09, 95% CI: -0.16 to -0.01, P<0.05; TFM: β=-0.08, 95% CI: -0.15 to -0.01, P<0.05; BFM: β=-0.07, 95% CI: -0.15 to 0.00, P<0.05). Adiposity was not associated with MVPA when modeled as the exposure in prospective analyses. SED was not related with adiposity indexes, except for the relationship with FMI. CONCLUSIONS: In cross-sectional and prospective analyses, MVPA is associated with lower adiposity independent of covariates and SED. Results suggest that promoting MVPA is important for preventing gain in adiposity in healthy children.The study was supported by the Portuguese Foundation of Science and Technology. Support/grant: PTDC/DES/108372/2008.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ijo.2015.16
Report Card on Physical Activity for Children and Youth
Background: This article describes the procedures and development of the rst Portuguese Report Card on Physical Activity in Children and Adolescents. Methods: Comprehensive searches for data related to indicators of physical activity (PA) were completed by a committee of physical activity and sports specialists. Grades were assigned to each indicator consistent with the process and methodology outlined by the Active Healthy Kids Canada Report Card model. Results: Nine indicators of PA were graded. The following grades were assigned: Overall Physical Activity Levels, D; Organized Sport Participation, B; Active Play, D; Active Transportation, C; Sedentary Behaviors, D; Family and Peers, C; Schools, B; Community and the Built Environment, D; and Government, C. Conclusions: Portuguese children and adolescents do not reach suf cient physical activity levels and spend larger amounts of time spent in sedentary behaviors compared with recommendations. Effective policies of PA promotion and implementation are needed in different domains of young people’s daily lives
Abdominal obesity in adolescents: Development of age-specific waist circumference cut-offs linked to adult IDF criteria
Objectives: The purpose of this study was to develop age- and sex-specific waist cir-cumference (WC) cut-off points, linked to older adolescent and adult criteria forabdominal obesity, to be applied to children in the clinical setting.Methods: A total of 16,788 adolescents aged 10 to 16 years were assessed for WC.Smoothed age and sex-specific WC curves were obtained using Cole’s LMS method.Results: Percentiles that corresponded to the International Diabetes Federation (IDF)recommendations used for older adolescents and adults (161 years old) were the97thpercentile for boys and the 87thpercentile for girls. Using these cutoffs, a total of368 boys and 1138 girls were categorized as abdominally obese, in contrast to 1654boys and 987 girls that were identified using the current IDF pediatric criteria (90thpercentile).Conclusions: We provide age- and sex-specific cut-off points that can be used toidentify abdominal obesity in adolescents. The present findings provide a tool thatcan be used in the clinical setting for the early detection and prevention of adult obe-sity. Population-specific cutoffs may be required for pediatric ages to diagnosechildren at risk
Cartografia e caraterização composicional cerâmica de argilas comuns da região de Torres Vedras - Bombarral
Magnetron sputtering thin films as tool to detect triclosan in infant formula powder: Electronic tongue approach
This work was supported by the Project "Development of Nanostructures for Detection of Triclosan Traces on Aquatic Environments" (PTDC/FIS-NAN/0909/2014). The Center for Environmental and Sustainability Research (CENSE) and Centre of Physics and Technological Research (CEFITEC), which is financed by national funds from FCT/MEC (UID/AMB/04085/2019 and UID/FIS/00068/2019). The authors also acknowledge and appreciate the support given to Center for Environmental and Sustainability Research (CENSE) and Centre of Physics and Technological Research (CEFITEC) by the Portuguese Foundation for Science and Technology (FCT) through the strategic project UIDB/04085/2020 and UID/FIS/00068/2020.Triclosan (TCS) is being detected in breast milk and in infants of puerperal women. The harmful effects caused by this compound on living beings are now critical and thus it is pivotal find new tools to TCS monitoring. In the present study, an electronic tongue (e‐tongue) device comprising an array of sputtered thin films based on Multi‐Walled Carbon Nanotubes and titanium dioxide was developed to identify TCS concentrations, from 10−15 to 10−5 M, in both water and milkbased solutions. Impedance spectroscopy was used for device signal transducing and data was analyzed by principal component analysis (PCA). The e‐tongue revealed to be able to distinguish water from milk‐based matrices through the two Principal Components (PC1 and PC2), which represented 67.3% of the total variance. The PC1 values of infant formula milk powder prepared with tap water (MT) or mineral water (MMW) follows a similar exponential decay curve when plotted with the logarithm of concentration. Therefore, considering the TCS concentration range between 1015 and 10−9 M, the PC1 values are fitted by a straight line and values of −1.9 ± 0.2 and of 7.6 × 10−16 M were calculated for the sensor sensitivity and sensor resolution, respectively. Additionally, a strong correlation (R = 0.96) between MT and MMW PC1 data was found. These results have shown that the proposed device corresponds to a promisor method for the detection of TCS in milk‐based solutions.publishersversionpublishe
NEW EQUATIONS TO DETERMINE EXERCISE INTENSITY USING DIFFERENT EXERCISE MODES
The purpose of this study was to determine new equations from the relationship of %·VO2max versus %HRmax, based on direct measures of oxygen uptake, in four exercise modes (leg cycling, rowing, stepping and running), in young adult females and males with low risk for cardiovascular disease. Ten adult males and ten females volunteered for the study. The participants performed an incremental test for each exercise mode until exhaustion. Regression analyses were carried out for each participant at a target % of VO2max and %HRmax was computed. At 40-90%·VO2max, the regression equations predicted similar values of %HRmax for males and females in the four exercise modes. In contrast, estimated %HRmax for cycling was higher at 40-70%·VO2max, when compared with stepping and running. The results support the notion that a single equation to predict target heart rate values for both males and females can be applied. Furthermore, at light and moderate intensities, leg cycling produces different %·VO2max-%HRmax regression equations than stepping and running
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