Multi-level diffusion model for manufactured sand mortar considering particle shape and limestone powder effects

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Functional and structural connectivity of the amygdala underpins locus of control in mild cognitive impairment

Locus of control (LOC) is an important personality trait. LOC over cognitive competency reflects an individual's perceived control of desired cognitive outcomes, which is critical for maintaining successful cognitive aging. It is important to understand the neural substrates of LOC over cognitive competency in older adults, especially for individuals at high risk of dementia. Here, we characterized a cohesive functional and structural connectivity profile underlying LOC among 55 older adults with amnestic mild cognitive impairment (aMCI), combining resting-state functional magnetic resonance imaging and diffusion tensor imaging. The results showed that both functional and structural connectivity between the medial prefrontal cortex and amygdala were significantly correlated with external LOC. The functional connectivity mediated the correlation between structural connectivity and external LOC. In addition, aging-associated neurodegeneration moderated the relationship between structural connectivity and external LOC, showing that the structural connectivity was positively correlated with external LOC in low, but not high neurodegeneration. Our results suggest a critical role of the functional amygdala-frontal network, which may serve as a bridge between its white matter tract and LOC over cognitive competency in groups at high risk for dementia. Keywords: Locus of control, Alzheimer's disease signature cortical thickness, Amnestic mild cognitive impairment, Amygdala, Resting-state fMRI, Diffusion tensor imagin

Prediction of compressive strength of concrete with manufactured sand by ensemble classification and regression tree method

Manufactured sand (MS) has been increasingly used as fine aggregate for concrete. This paper proposes a prediction of the compressive strength of concrete with manufactured sand (MS-concrete) based on an ensemble classification and regression tree (En_CART) method. A data set containing 1,350 original measured strengths of 328 concrete mixtures from actual engineering projects were used for training and testing. The cross-validation and experimental data from the literature were also used for validation, both indicating that the En_CART model provides an accurate and robust prediction. The comparison of En_CART with various machine learning methods, including artificial neural network, linear regression, Gaussian process regression, random forest, and support vector machine regressions, indicates that the En_CART model indicates superiority in predicting the compressive strength of MS-concrete. Based on the proposed model, the evolution of compressive strength is analyzed. The importance analysis indicates that age is the most significant factor influencing the compressive strength of MS-concrete, and stone powder content presents approximately 25% of the age contribution. The compressive strength of MS-concrete was found to first increase and then decrease with increasing content of MS. The optimal content of MS slightly increases with an increase in the strength level of MS-concrete. Stone powder, at certain MS content, is also found to indicate remarkable improvement in the compressive strength of MS-concrete. The optimum content of stone powder in MS is higher for MS-concrete with lower strength and lower for MS-concrete with higher strength

Rheological properties of concrete with manufactured sand : a multi-level prediction

Conventional rheological predictions of concrete were mostly developed based on spherical aggregate assumptions whereas the particle shape of irregular aggregate significantly influences the rheological properties of concrete. In this study, rheological properties of concrete with manufactured sand (MS) are predicted concerning the particle shape of aggregate based on a multi-level biphase assumption. The relative plastic viscosity and relative yield stress at each level are demonstrated to present power-law relationships with the relative thickness of the corresponding suspending media. The proposed models are proved with high accuracy and robustness for predicting the rheological properties of mixtures with MS and coarse aggregate that have various particle shapes and particle size distributions. Based on the proposed predictions, the influences of particle shapes of MS and coarse aggregate on the rheological properties of mixtures can be represented by their effects on the relative paste film thickness (R_PFT) and relative mortar film thickness (R_MFT), respectively. The proposed multi-level prediction lays the foundation of mix proportioning of concrete with irregular aggregate according to the specified rheological requirements

A hierarchical C-S-H/organic superstructure with high stiffness, super-low porosity, and low mass density

International audienceHerein, a hierarchical cementitious calcium silicate hydrate (C-S-H) superstructure with high Young's modulus, super-low porosity, and low mass density is reported. It has a very high Young's modulus at 47.5 GPa, three times higher than our reference synthetic C-S-H. Its specific surface area is merely 0.4509 m2/g, two orders of magnitude smaller than our reference synthetic C-S-H and the most common construction materials. In addition, the skeletal density of this composite is 1.96 g/cm3, much lower than C-S-H and hardened cement paste. In a density-Young's modulus diagram, this composite is located at the intersection of metals, ceramics, and polymers, approaching the carbon fiber region, implying lightweight and stiff characteristics. The cryogenic stability is also evaluated. It shows a satisfying applicability potential for cryogenic engineering with stable pore structure and nanoscopic mechanical properties. We confirm that the assembly of hierarchical C-S-H superstructure requires both hydrophilic amide and anionic carboxylic groups

Plastic viscosity of cement mortar with manufactured sand as influenced by geometric features and particle size

This paper investigates the plastic viscosity of cement mortar with manufactured sand (MS) concerning the influences of geometric features and particle size of MS. The geometric features, including overall shape, angularity and roughness, of MS with various particle sizes were evaluated by aspect ratio, convexity area ratio, convexity perimeter ratio and circularity. The plastic viscosity of cement mortar was calculated based on the Bingham model. Results show that the combined effects of overall shape, angularity and roughness provide coarser MS particles with lower circularity. In terms of relative plastic viscosity, Robinson model shows optimal fittings for all mixtures and is thus used to determine the packing fraction of MS under shearing. From the particle packing viewpoint, shear-induced orientation increases the packing fraction of non-spherical MS particles from the random loose packing fraction and the influence is increasingly prominent with the decrease of circularity. The relative volume fraction is an important parameter influencing the relative plastic viscosity of mixtures with MS while the relative paste film thickness (R_PFT), calculated from the real packing fraction and specific surface area (SSA), is found as the dominating factor. The dependence of plastic viscosity of cement mortar on geometric features and particle size of MS can be attributed to their influences on the packing fraction and SSA of particles

Design and Preparation of White High-Strength Concrete with Ground Limestone Powder by Means of Response Surface Methodology

This paper investigates the properties of white high-strength concrete (WHSC) prepared with ground limestone powder (GLP). Response surface methodology (RSM) was used to design the proportions of mixes and evaluate the influence of the water–binder ratio (w/b), slurry volume fraction (Vs), and the content of GLP in a binder (Cg) on the slump, whiteness and compressive strength of WHSC via Box–Behnken equations. Results indicate that quadratic polynomial regression equations can be used to predict the performance of WHSC as influenced by combined factors. Both slump and compressive strength of WHSC are found highly influenced by w/b while GLP significantly improves the whiteness of WHSC. An optimal mix proportion of WHSC is provided by the multi-objective optimization with high-accuracy predictions. This paper demonstrates the feasibility of preparing WHSC with GLP and presents the potential of using RSM in the mix proportioning of concrete

Nature of aluminates in C-A-S-H: A cryogenic stability insight, an extension of DNA-code rule, and a general structural-chemical formula

International audienceHerein, we report a cryogenic attack study on C-A-S-H with bulk Ca/(Al+Si) = 0.84~1.75, Al/(Al+Si) = 0.1, 0.2. The C-A-S-H nanostructure variations are quantitively analyzed using thermogravimetric analysis, single-pulse 29Si, and 27Al MAS NMR. Observing the conversion of tetrahedral aluminates to octahedral ones in the absence of depolymerization, we confirm the presence of bridging octahedral aluminates in C-A-S-H chains. The consistency between the slight polymerization and the decrease of pentahedral aluminate fraction in low-Al C-A-S-H reveals the existence of interlayer pentahedral aluminate. The depolymerization in high-Al C-A-S-H is accompanied by conversion of pentahedral aluminate to octahedral aluminate, which confirms the presence of bridging pentahedral and interlayer octahedral aluminates. We further identify the complexes for each structural unit. Then, a DNA-code rule is proposed to describe C-A-S-H atomistic structure considering both bridging and interlayer aluminates. Finally, we propose a general structural-chemical formula for C-A-S-H