No abstract

No abstract

No abstract

Floods in urban environments often result in loss of life and destruction of property, with many negative socio-economic effects. However, the application of most flood prediction models still remains challenging due to data scarcity. This creates a need to develop novel hybridized models based on historical urban flood events, using, e.g., metaheuristic optimization algorithms and wavelet analysis. The hybridized models examined in this study (Wavelet-SVR-Bat and Wavelet-SVR-GWO), designed as intelligent systems, consist of a support vector regression (SVR), integrated with a combination of wavelet transform and metaheuristic optimization algorithms, including the grey wolf optimizer (GWO), and the bat optimizer (Bat). The efficiency of the novel hybridized and standalone SVR models for spatial modeling of urban flood inundation was evaluated using different cutoff-dependent and cutoff-independent evaluation criteria, including area under the receiver operating characteristic curve (AUC), Accuracy (A), Matthews Correlation Coefficient (MCC), Misclassification Rate (MR), and F-score. The results demonstrated that both hybridized models had very high performance (Wavelet-SVR-GWO: AUC = 0.981, A = 0.92, MCC = 0.86, MR = 0.07; Wavelet-SVR-Bat: AUC = 0.972, A = 0.88, MCC = 0.76, MR = 0.11) compared with the standalone SVR (AUC = 0.917, A = 0.85, MCC = 0.7, MR = 0.15). Therefore, these hybridized models are a promising, cost-effective method for spatial modeling of urban flood susceptibility and for providing in-depth insights to guide flood preparedness and emergency response services.

Human-induced urban growth and sprawl have implications for greenhouse gas (GHG) emissions that may not be included in conventional GHG accounting methods. Improved understanding of this issue requires use of interactive, spatial-explicit social-ecological systems modeling. This paper develops a comprehensive approach to modeling GHG emissions from urban developments, considering Stockholm County, Sweden as a case study. GHG projections to 2040 with a social-ecological system model yield overall greater emissions than simple extrapolations in official climate action planning. The most pronounced difference in emissions (39% higher) from energy use single-residence buildings resulting from urban sprawl. And this difference is not accounted for in the simple extrapolations. Scenario results indicate that a zoning policy, restricting urban development in certain areas, can mitigate 72% of the total emission effects of the model-projected urban sprawl. The study outcomes include a decision support interface for communicating results and policy implications with policymakers. Keywords Climate change Á Greenhouse gas emissions Á Land-use change Á Planning support system Á Social-ecological system Á Stockholm Electronic supplementary material The online version of this article (

No abstract

No abstract

Aging is a social and economic challenge of the highest importance and a multidisciplinary intervention seems to be a promising approach for improving the quality of life of elderly individuals. This project was designed aimed at promoting an active and healthy aging through the implementation of an intervention program based on the comprehensive geriatric assessment model (AGA@4life), focused on promoting health and wellbeing, independence and autonomy, mobility, and social inclusion. A non-randomized interventional study was designed to evaluate the effect of only a dietetic and nutritional approach (control group (CG)) and the combination of a tailored exercise program and a dietetic and nutritional approach (intervention group (IG)) in the biochemical and hematological profile of older adults in the framework of AGA@4life. The 34 participants enrolled, aged 65 years or over, were subject to a thorough baseline (T0) multidisciplinary diagnostic evaluation, including the gathering of clinical information and a battery of biochemical and hematological determinations, and reevaluated after eight weeks of intervention (T1). Between T0 and T1, an increase in albumin and total proteins serum levels were observed in both groups (p < 0.01); the hematological profile in CG and IG showed an increase in red cell count and hemoglobin (p < 0.05). In IG, an increase of HDL cholesterol (p < 0.001) and a decrease of triglycerides (p = 0.001) were still observed. The AGA@4life multidisciplinary intervention improved the hematological and biochemical profile of old adults, potentially contributing to delay the development of several aging comorbidities and increase the quality of life of participants.