Fatigue crack behaviour : comparing three-point bend test and wedge splitting test data on vibrated concrete using Paris' law

The fatigue behaviour of concrete has become more important for the design of constructions due to the desire to build slimmer structures, which are more sensitive to fatigue loading. This article aims to evaluate and compare the fatigue crack propagation rate in vibrated concrete for four different stress ratios using the Paris-Erdogan law. The data evaluation in this article is based on crack mouth opening displacement (CMOD) measurements from cyclic three-point bending tests on single edge notched beams and from wedge splitting tests on notched cubes, obtained from experiments at Ghent University. For this study, finite element analysis is used to obtain a mathematical relationship between the CMOD and the relative crack length a/W, as well as a relationship between the stress intensity ratio ∆K and a/W. The obtained mathematical relationships were then combined with the measured CMOD values to correlate the test data to the Paris-Erdogan law. Herein, the crack propagation rate da/dN is plotted against the corresponding stress intensity range ∆K in a log-log graph. In a final step, the Paris-Erdogan law parameters C and m were obtained through linear curve fitting on the data points from the obtained graphs. The parameters C and m are then used to compare and evaluate the fatigue crack behavior in vibrated concrete, and the differences between the results from the three-point bend tests and wedge splitting tests

Additional load bearing capacity of prestressed hollow core slabs due to membrane action

Due to their efficient design, economic production process and quick installation, prestressed concrete hollow core slabs are frequently used in all kinds of constructions. These prefabricated units are typically installed as single span elements, which are at the joints tied to the neighbouring elements with additional rebars. In a final step, the joints at the edges and between the elements are filled with grout, or a second layer of cast in-situ concrete is added on top of the elements. Although the execution of the joints and the stiffness of the surrounding structure provide a certain level of rigidity, hollow core slabs are typically designed as simply supported single span elements. However, the stiffness of the surrounding structure might facilitate compressive membrane action, which can increase the bearing capacity of the elements. This additional load bearing capacity, which is usually not taken into account, can be beneficial in accidental loading situations. This paper evaluates the additional load bearing capacity of prestressed concrete hollow core slabs due to compressive membrane action using two detailed 3D non-linear finite element models in Abaqus. The influence of the longitudinal restraint forces on the load bearing capacity of a single hollow core element is evaluated and compared to a simply supported configuration. The influence of the element geometry and span to height ratio on the additional load bearing capacity is investigated for both reinforced and prestressed hollow sections

A monopartite nuclear localization sequence regulates nuclear targeting of the actin binding protein myopodin

Myopodin is an actin bundling protein that shuttles between nucleus and cytoplasm in response to cell stress or during differentiation. Here, we show that the myopodin sequence (58)KKRRRRARK(66), when tagged to either enhanced green fluorescent protein (EGFP) or to enhanced cyan fluorescent protein-CapG (ECFPCapG), is able to target these proteins to the nucleolus in HeLa or H-EK293T cells. By contrast, (KKRR61)-K-58 ECFP-CapG accumulates in the nucleus. Mutation of (58)KKRRRRARK(66) into alanine residues blocks myopodin nuclear import and promotes formation of cytoplasmic actin filaments. A second putative nuclear localization sequence, (612)KTSKKKGKK(620), displays much weaker activity in a heterologous context, and appears not to be functional in the full length protein. Thus myopodin nuclear translocation is dependent on a monopartite nuclear localization sequence

Comparison of fire resistance and burnout resistance of simply supported reinforced concrete slabs exposed to parametric fires

Traditionally the fire resistance of concrete elements is determined through prescriptive methods, often with the use of tabulated data. Herein, the structural behaviour during or after the cooling phase of the fire is not considered. This is a major shortcoming considering the potential of delayed collapse during the cooling phase exists. To take into account the structural behavior after the heating phase, the concept of burnout resistance was introduced in recent literature, which indicates the performance of concrete elements or structures until complete burnout. In this paper the bending moment resistance until burnout is determined for simply supported reinforced concrete slabs exposed to the Eurocode parametric fire curve, for a wide range of parameters. The fire resistance and burnout resistance are compared and an equation for describing the relationship between both is presented. A calculation method is provided which allows to apply these results to a parametric fire in any given compartment, through the use of a reference compartment and equivalence equations. Through the use of this simple method, the maximal allowable fire load density for which the concrete slab maintains stability during the entire fire exposure, including the cooling phase, can directly be obtained for any given rectangular compartment

Structural reliability of hollow core slabs considering compressive membrane action

Compressive membrane action can considerably improve the load bearing capacity of concrete slabs and beams in case of excessive loaded due to an accidental event. Currently, only limited research has been focusing on compressive membrane action in prestressed concrete elements, or on concrete elements with large cavities, such as precast concrete hollow core slabs. Therefore, a novel real-scale test setup has been developed in order to assess this effect in precast hollow core slabs, and how it can enhance the load-carrying capacity in accidental events. In parallel with these tests, a numerical finite element model has been developed in order to perform a more detailed structural analysis of this phenomenon, and to study the influence of various input parameters. The details of this test setup are briefly explained, and some relevant experimental test results are provided. Considering the experimental findings and validated numerical model, this contribution aims to quantify the influence of compressive membrane action on the structural reliability of precast concrete hollow core slabs. To this end, probabilistic models for the most important material and geometric variables are gathered, and the structural reliability is assessed using Latin Hypercube sampling. Overall, the results indicate that considering the formation of compressive membrane action strongly influences the variability of the ultimate load-carrying capacity of precast concrete hollow core slabs

Global Resistance Factor for the burnout resistance of concrete slabs exposed to parametric fires

Although traditionally the fire resistance rating of concrete elements is determined through standardized tests or tabulated data, there is a growing trend towards the use of performance-based approaches to evaluate structural behaviour during or after a fire. The safety format to be applied with these advanced numerical evaluations is however unclear. In this paper, the applicability of the concept of a global resistance factor (GRF) safety format is explored for simply supported concrete slabs exposed to the Eurocode parametric fire curve for a wide range of parameters. The safety of the slab is evaluated in relation to its ability to withstand a complete burnout scenario, i.e. its ability to resist the applied loads throughout the entire duration of a fire including the cooling phase. Using a full-probabilistic model, the required GRF is numerically derived for a specified target safety level in case of fire. Additionally, a calculation method is provided which allows to determine the GRF of fire exposed slabs for any given compartment through the use of a reference compartment and equivalency equations

Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients

Background: Beta-lactam antimicrobial concentrations are frequently suboptimal in critically ill patients. Population pharmacokinetic (PopPK) modeling is the golden standard to predict drug concentrations. However, currently available PopPK models often lack predictive accuracy, making them less suited to guide dosing regimen adaptations. Furthermore, many currently developed models for clinical applications often lack uncertainty quantification. We, therefore, aimed to develop machine learning (ML) models for the prediction of piperacillin plasma concentrations while also providing uncertainty quantification with the aim of clinical practice. Methods: Blood samples for piperacillin analysis were prospectively collected from critically ill patients receiving continuous infusion of piperacillin/tazobactam. Interpretable ML models for the prediction of piperacillin concentrations were designed using CatBoost and Gaussian processes. Distribution-based Uncertainty Quantification was added to the CatBoost model using a proposed Quantile Ensemble method, useable for any model optimizing a quantile function. These models are subsequently evaluated using the distribution coverage error, a proposed interpretable uncertainty quantification calibration metric. Development and internal evaluation of the ML models were performed on the Ghent University Hospital database (752 piperacillin concentrations from 282 patients). Ensuing, ML models were compared with a published PopPK model on a database from the University Medical Centre of Groningen where a different dosing regimen is used (46 piperacillin concentrations from 15 patients.). Results: The best performing model was the Catboost model with an RMSE and R-2 of 31.94-0.64 and 33.53-0.60 for internal evaluation with and without previous concentration. Furthermore, the results prove the added value of the proposed Quantile Ensemble model in providing clinically useful individualized uncertainty predictions and show the limits of homoscedastic methods like Gaussian Processes in clinical applications. Conclusions: Our results show that ML models can consistently estimate piperacillin concentrations with acceptable and high predictive accuracy when identical dosing regimens as in the training data are used while providing highly relevant uncertainty predictions. However, generalization capabilities to other dosing schemes are limited. Notwithstanding, incorporating ML models in therapeutic drug monitoring programs seems definitely promising and the current work provides a basis for validating the model in clinical practice

Allocation and modeling of biomass of Dendrocalamus asper

O objetivo deste trabalho foi quantificar a biomassa seca total individual de plantas de bambu da espécie Dendrocalamus asper (Schult. & Schult. f.) Backer ex K. Heyne, visando conhecer a sua distribuição nos diferentes compartimentos, bem como avaliar modelos de biomassa em função de variáveis biométricas das plantas. Foram avaliados 20 indivíduos, coletados em Bauru, SP. As plantas amostradas foram medidas, abatidas e pesadas. A maior fração da biomassa foi observada na parte aérea, com 86%, sendo 64% para o compartimento colmo, 16% para os galhos e 6% para as folhas. Os rizomas representaram 14% da biomassa total. As variáveis biométricas (diâmetro à altura do peito – DAP, altura total – ht e diâmetro de colo – Dcolo) correlacionaram-se significativamente com as biomassas total e do colmo. O modelo que apresentou o melhor desempenho para a biomassa total teve como variável independente apenas o DAP, enquanto que para a biomassa dos colmos foi a variável combinada dap0,5*lndap. Os ajustes para os demais compartimentos não geraram resultados satisfatórios, em função da baixa correlação entre as variáveis biométricas e suas biomassas. Concluiu-se que é possível expressar a biomassa seca total e do colmo do bambu por meio de modelos alométricos, porém o mesmo não se aplica aos demais compartimentos.Palavras-chave: Bambu; fitomassa; modelos alométricos. AbstractAllocation and modeling of biomass of Dendrocalamus asper. The aim of this research was to quantify the total individual biomass of bamboo plants of the species Dendrocalamus asper (Schult. & Schult. f.) Backer ex K. Heyne, in order to understand its distribution along different compartments, as well as evaluat biomass models according to biometric variables. Twenty individuals collected in Bauru, SP were evaluated. The plants were measured, cut and weighed. The aboveground biomass accounted for the major fraction, representing 86%. The stem compartment represented 64% of total biomass, followed by the branches, with 16% and leaves, with 6%. Rhizomes accounted for 14% of the total biomass. The biometric variables (diameter at breast height - dbh, total height – ht, and collar diameter - dcollar) were significantly correlated with total and stem biomass. The model that revealed best performance for total biomass had only dap as independent variable, for the stems biomass the combined variable was dap0,5*lndap. The adjustments for other compartments were not satisfactory due to low correlation between the biometric variables and their biomass. As conclusion, it is possible to express the total  dry stem biomass and culm mass of bamboo using allometric models, however, the same does not apply to other compartments.Keywords: Bamboo; phytomass; allometric models.AbstractThe aim of this research was to quantify the total individual biomass of bamboo plants of the species Dendrocalamus asper (Schult. & Schult. f.) Backer ex K. Heyne, in order to understand its distribution along different compartments, as well as evaluat biomass models according to biometric variables. Twenty individuals collected in Bauru, SP were evaluated. The plants were measured, cut and weighed. The aboveground biomass accounted for the major fraction, representing 86%. The stem compartment represented 64% of total biomass, followed by the branches, with 16% and leaves, with 6%. Rhizomes accounted for 14% of the total biomass. The biometric variables (diameter at breast height - dbh, total height – ht, and collar diameter - dcollar) were significantly correlated with total and stem biomass. The model that revealed best performance for total biomass had only dap as independent variable, for the stems biomass the combined variable was dap0,5*lndap. The adjustments for other compartments were not satisfactory due to low correlation between the biometric variables and their biomass. As conclusion, it is possible to express the total  dry stem biomass and culm mass of bamboo using allometric models, however, the same does not apply to other compartments.Keywords: Bamboo; phytomass; allometric models

Early mobilisation in critically ill COVID-19 patients:a subanalysis of the ESICM-initiated UNITE-COVID observational study

Background Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. Methods This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. Results Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p <= 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI - 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI - 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. Conclusions Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility