Susceptibility and Vulnerability to Landslides—Case Study: Basin of River Bengalas—City of Nova Friburgo—Brazil

Landslides have frequently occurred in last years, due to the disorderly grownth of the cities and the occupation of risk areas by the poor population, causing social, environmental and economic impacts. Urban areas in expansion move to geologically unstable areas and topographically inclined, such as the Basin of River Bengalas, located in the city of Nova Friburgo, mountainous region of the State of Rio de Janeiro, Brazil. This article aims to present the model developed and used to evaluate the susceptibility and vulnerability of the Basin of River Bengalas to landslides, which in January 2011, with the occurrence of heavy rains, caused landslides that impacted in the death of 429 people in city of Nova Friburgo. For the case study, several investigations have been made related to the areas of the basin, such as slope, soil conditions, lithology, land use and cover, vertical curvature, horizontal curvature, and precipitation data. With this study it was possible to understand how the natural and anthropics elements of the basin are related to the local dynamics of the disasters regarding to their interferences in the induction of landslides; evaluate the effectiveness of the guidelines of the Plano Diretor Participativo do Município de Nova Friburgo regarding the landslides; identify the susceptible and vulnerable basin areas to landslides and calculate the rates of susceptibility and vulnerability to landslides from new calculation model proposed

Suscetibilidade da Bacia do Rio Bengalas a deslizamentos de terra

Landslides have frequently occurred in last years, due to the disorderly grownth of the cities and the occupation of risk areas by the poor population, causing social, environmental and economic impacts. Urban areas in expansion move to geologically unstable areas and topographically inclined, such as the Basin of River Bengalas, located in the city of Nova Friburgo, mountainous region of the State of Rio de Janeiro, Brazil. This article aims to present the model survey to assess the susceptibility of the Basin of River Bengalas to landslides, which in january 2011, with the occurrence of heavy rains, caused landslides that impacted in the death of 429 people in city of Nova Friburgo. For the case study, several investigations have been made related to the areas of the basin, such as slope, soil conditions, lithology, land use and cover, vertical and horizontal curvatures. With this study it was possible to understand how the natural and anthropics elements of the basin are related to the local dynamics of the disasters regarding to their interferences in the induction of landslides, thus enabling improved public management of the Municipality regarding the use and division of land, from the identification of areas Basin of River Bengalas susceptible to landslides

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Erosión y desertificación.-Contribution to the edaphic component definition in the desertification susceptibility index

ABSTRACT Many of the biophysical processes involved in the scope of desertification depend on the hydric characteristics of the soils that impact on vegetation cover. To protect soils against desertification, it is necessary to understand how some of these characteristics (such as water storage) interact in a complex and integrated chain of degradation processes. Several works have been developed to contribute to the definition of a Index of Desertification Susceptibility (DSI) expressed as a function of several components, climatic, edaphic, vegetative and slope. However, the various built-in edaphic components already defined, leave aside the water retention in soil. Furthermore, these components only focus on the characteristics of the uppermost surface soil layer (A-layer). In fact, desertification is simultaneously cause and consequence of the depleted soil water retention with a positive feedback on the plant life and on the hydrological cycle. This work intends to respond to the question of assessing if the B-layer exerts a significant influence in the definition of the edaphic component of the DSI. This may reflect the influence of the B-layer on the soil resilience to external factors. An experimental study has been performed on several profiles (n = 50) of representative soil units at Mértola, Southern Portugal (a region classified as having high DSI). Soil columns, have been delimited having at the upper and lower boundaries respectively the soil surface and the C-layer. The total volume (VT) of the Soil Available Water Content (AWC) was calculated as the sum of the elementary volumes (in the case, VA and VB) stored in each layer of the prospected soil column. Furthermore, volumetric ratios VA/VT and VB/VT have been determined. A possible existing empirical relationship between the ratios VA/VT and VB/VT, was investigated aiming to establish the relative importance of each term to the total volume VT. The results reveal a clear linear trend between VA/VT and VB/VT suggesting that the B-layer assumes the greater importance in terms of the holding water capacity of soil. It was found that except for soils constituted only by the A-layer, or when this layer is deeper than 45 cm, the relative weight of the B-layer is preponderant. For the most representative soil units of the study area, the referred relationship is persistent and is dependent on the layer thickness. To conclude, the foregoing relationship allowed identifying the soil units with greater desertification susceptibility through their inability to store sufficient water to maintain vegetation. It also allowed one to identify soil units whose B-layer assumes the greater importance in this soil function, and therefore should be take into account in defining the edaphic component of DSI. Thus, it is understood that the results of the present exercise have contributed to a better understanding of desertification processes, allowing to outlining strategies of action and implementing technologies for soil and water conservation, more appropriate to each situation. A more extended and detailed study will have to be done in order to more effectively contribute to upscale the results to the regional level

Statistical–dynamical modeling of the cloud-to-ground lightning activity in Portugal

The present study employs a dataset of cloud-to-ground discharges over Portugal, collected by the Portuguese lightning detection network in the period of 2003–2009, to identify dynamically coherent lightning regimes in Portugal and to implement a statistical–dynamical modeling of the daily discharges over the country. For this purpose, the high-resolution MERRA reanalysis is used. Three lightning regimes are then identified for Portugal: WREG, WREM and SREG. WREG is a typical cold-core cut-off low. WREM is connected to strong frontal systems driven by remote low pressure systems at higher latitudes over the North Atlantic. SREG is a combination of an inverted trough and a mid-tropospheric cold-core nearby Portugal. The statistical–dynamical modeling is based on logistic regressions (statistical component) developed for each regime separately (dynamical component). It is shown that the strength of the lightning activity (either strong or weak) for each regime is consistently modeled by a set of suitable dynamical predictors (65–70% of efficiency). The difference of the equivalent potential temperature in the 700–500 hPa layer is the best predictor for the three regimes, while the best 4-layer lifted index is still important for all regimes, but with much weaker significance. Six other predictors are more suitable for a specific regime. For the purpose of validating the modeling approach, a regional-scale climate model simulation is carried out under a very intense lightning episode.info:eu-repo/semantics/publishedVersio

Predictors for anastomotic leak, postoperative complications, and mortality after right colectomy for cancer: Results from an international snapshot audit

Background: A right hemicolectomy is among the most commonly performed operations for colon cancer, but modern high-quality, multination data addressing the morbidity and mortality rates are lacking. Objective: This study reports the morbidity and mortality rates for right-sided colon cancer and identifies predictors for unfavorable short-term outcome after right hemicolectomy. Design: This was a snapshot observational prospective study. Setting: The study was conducted as a multicenter international study. Patients: The 2015 European Society of Coloproctology snapshot study was a prospective multicenter international series that included all patients undergoing elective or emergency right hemicolectomy or ileocecal resection over a 2-month period in early 2015. This is a subanalysis of the colon cancer cohort of patients. Main Outcome Measures: Predictors for anastomotic leak and 30-day postoperative morbidity and mortality were assessed using multivariable mixed-effect logistic regression models after variables selection with the Lasso method. Results: Of the 2515 included patients, an anastomosis was performed in 97.2% (n = 2444), handsewn in 38.5% (n = 940) and stapled in 61.5% (n = 1504) cases. The overall anastomotic leak rate was 7.4% (180/2444), 30-day morbidity was 38.0% (n = 956), and mortality was 2.6% (n = 66). Patients with anastomotic leak had a significantly increased mortality rate (10.6% vs 1.6% no-leak patients; p 65 0.001). At multivariable analysis the following variables were associated with anastomotic leak: longer duration of surgery (OR = 1.007 per min; p = 0.0037), open approach (OR = 1.9; p = 0.0037), and stapled anastomosis (OR = 1.5; p = 0.041). Limitations: This is an observational study, and therefore selection bias could be present. For this reason, a multivariable logistic regression model was performed, trying to correct possible confounding factors. Conclusions: Anastomotic leak after oncologic right hemicolectomy is a frequent complication, and it is associated with increased mortality. The key contributing surgical factors for anastomotic leak were anastomotic technique, surgical approach, and duration of surgery