Soil-cement mixtures reinforced with fibers: a data-driven approach for mechanical properties prediction

The reinforcement of stabilized soils with fibers arises as an interesting technique to overcome the two main limitations of the stabilized soils: the weak tensile/flexural strength and the higher brittleness of the behavior. These types of mixtures require extensive laboratory characterization since they entail the study of a great number of parameters, which consumes time and resources. Thus, this work presents an alternative approach to predict the unconfined compressive strength (UCS) and the tensile strength of soil-binder-water mixtures reinforced with short fibers, following a Machine Learning (ML) approach. Four ML algorithms (Artificial Neural Networks, Support Vector Machines, Random Forest and Multiple Regression) are explored for mechanical prediction of reinforced soil-binder-water mixtures with fibers. The proposed models are supported on representative databases with approximately 100 records for each type of test (UCS and splitting tensile strength tests) and on the consideration of sixteen properties of the composite material (soil, fibers and binder). The predictive models provide an accurate estimation (R2 higher than 0.95 for Artificial Neuronal Networks algorithm) of the compressive and the tensile strength of the soil-water-binder-fiber mixtures. Additionally, the results of the proposed models are in line with the main experimental findings, i.e., the great effect of the binder content in compressive and tensile strength, and the significant effect of the type and the fiber properties in the assessment of the tensile strength.This research was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Engineering Structures (ISISE), under reference UIDB/04029/2020, the R&D Unit Chemical Process Engineering and Forest Products Research Centre (CIEPQPF) under reference UIDB/00102/2020, and under the project PTDC/ECICON/28382/2017

Data mining approach for unconfined compression strength prediction of laboratory soil cement mixtures

A previsão da resistência à compressão uniaxial (qu) de misturas solo-cimento é de elevada importância durante a fase de projeto. Para a sua quantificação são realizados ensaios laboratoriais, os quais consomem muito tempo e recursos. Neste artigo é apresentada uma nova abordagem para avaliação da qu ao longo do tempo tirando proveito das elevadas capacidades de aprendizagem das técnicas de Inteligência Artificial (IA). Três algoritmos de IA, nomeadamente as Redes Neuronais Artificiais (RNAs), as Máquinas de Vetores de Suporte (MVSs) e Regressões Múltiplas (RMs), foram treinados utilizando uma base de dados composta por 444 registos contemplando solos não coesivos, coesivos e orgânicos, assim como diferentes ligantes, condições de mistura e tempos de cura. Os resultados obtidos evidenciam um desempenho promissor na previsão da qu de misturas laboratoriais de solo-cimento, sendo o melhor desempenho conseguido através da média das previsões obtidas pelas MVSs e RNAs (R2=0.95). Estes modelos reproduzem eficazmente os principais efeitos das variáveis de entrada, nomeadamente da razão água/cimento, teor em cimento, teor em matéria orgânica e tempo de cura, as quais são conhecidas como preponderantes no comportamento de misturas solo-cimento.info:eu-repo/semantics/publishedVersio

Decreased renal function in overweight and obese prepubertal children

BACKGROUND: Obesity is a potentially modifiable risk factor for the development and progression of kidney disease, both in adults and children. We aim to study the association of obesity and renal function in children, by comparing estimated glomerular filtration rate (eGFR) in nonoverweight and overweight/obese children. Secondarily, we aim to evaluate the accuracy of equations on eGFR estimation when compared to 24-h urinary creatinine clearance (CrCl). METHODS: Cross-sectional study of 313 children aged 8-9 y, followed in the birth cohort Generation XXI (Portugal). Creatinine and cystatin C, GFR estimated by several formulas and CrCl were compared in 163 nonoverweight and 150 overweight/obese, according to World Health Organization growth reference. RESULTS: Overweight/obese children had significantly lower eGFR, estimated by all methods, except for CrCl and revised Schwartz formula. Despite all children having renal function in the normal range, eGFR decreased significantly with BMI z-score (differences ranging from -4.3 to -1.1 ml/min/1.73 m(2) per standard deviation of BMI). The Zappitelli combined formula presented the closest performance to CrCl, with higher correlation coefficients and higher accuracy values. CONCLUSION: Young prepubertal children with overweight/obesity already present significantly lower GFR estimations that likely represent some degree of renal impairment associated with the complex deleterious effects of adiposity

Sex-Specific Mediating Role of Insulin Resistance and Inflammation in the Effect of Adiposity on Blood Pressure of Prepubertal Children

Objective: To evaluate the association between obesity indices and blood pressure (BP) at 4 years of age, in each sex, and to quantify to which extent this association is mediated by inflammation and insulin resistance (IR). Materials and Methods: We studied 1250 4-year-old children selected from the population-based birth cohort Generation XXI. Associations between body mass index (BMI) z-score and waist-to-height ratio (WHtR), office BP, inflammation (high sensitivity C-reactive protein) and IR (HOMA-IR index) were assessed. Path Analysis, a modified multivariate regression approach, was applied to test causal models and quantify direct and indirect effects of predictors of systolic (SBP) and diastolic BP (DBP). Results: SBP and DBP increased significantly with BMI and WHtR in both sexes. There was a strong direct association (explaining 74.1-93.2% of the total association) of both measures of adiposity with SBP, in both sexes. This association was additionally indirectly mediated by IR, particularly regarding WHtR (20.5% in girls and 9.4% in boys). Mediation by inflammation did not reach statistical significance in either sex. Regarding DBP, the direct effect of adiposity was strong (>95% for BMI and WHtR in boys) and the mediation by IR was much smaller in boys than in girls. Discussion: The direct association between adiposity and BP in healthy 4-year-old children is strong and IR plays an important mediating role. The strength of effects of IR and inflammation suggests sex differences in the complex interplay between BP, adiposity and inflammation

Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life