This paper presents a laboratory study of the effect of naturals (hemp fibers) and synthetics fibers (glass fibers) on the mechanical behavior of sandy soil (natural Chlef sand). A series of shear direct tests were carried out on medium dense (RD= 50%) and dense (RD= 80%) Chlef samples sand with different naturals and synthetics content fibers ranging from 0, 0.25, 0.5, 0.75 and 1% and under three normal stress of 50, 100 and 200 kPa. The test results show that the addition of fibers has a significant effect on the shear strength of the sand-fiber mixture, however, this shear strength increases with the increase of the fibers content, the normal stress applied and the relative density until up an optimal fibers content of 0.5% for the glass fibers and 0.75% for the hemp fibres. Beyond these optimal fibres content, the shear strength decreases. The internal friction angle and the cohesion are significantly influenced by the fibres content.
This study investigates urinary levels of aluminum (Al), arsenic (As), cadmium (Cd), copper (Cu), and lead (Pb), along with essential elements (manganese (Mn), selenium (Se) and zinc (Zn)), in Algerian children with severe ASD, and explores associations with environmental risk factors. This case–control study involved 100 children with ASD and 80 neurotypical children. All participants were subjected to measurements of Al, As, Cd, Cu, Pb, Mn, Se and Zn levels in urine, and to an investigation about possible environmental risk factors. The mean levels of Cd, Pb, Cu and Mn in the ASD group were significantly higher than those in the neurotypical group (p = 0.02, 0.01, 0.04 and 0.02, respectively). However, levels of urinary As, Al, Se and Zn were considerably lower in children with ASD group than those in the neurotypical group (p = 0.001, 0.003, 0.03 and 0.002 respectively). The most associated environmental risk factors were nearby gasoline station (AOR = 7.6, 95
The structural integrity of reinforced concrete (RC) members retrofitted with externally bonded composite laminates is primarily governed by complex interfacial stress transfer mechanisms, which are frequently compromised by manufacturing imperfections and aggressive environmental exposure. While conventional fiber-reinforced polymer strengthening is well established, the transition toward bio-inspired helicoidal Bouligand architectures offers a transformative approach to enhancing delamination resistance. However, the interfacial mechanics of these advanced configurations under coupled multi-physical loading remain insufficiently characterized. This study presents a robust computational framework leveraging high-precision artificial neural networks to evaluate interfacial shear and normal stress distributions in RC beams featuring stochastic air-void defects. Utilizing an extensive database of 63,975 data points, a multi-layer perceptron architecture was optimized to capture the high-dimensional nonlinear coupling between constitutive material properties, geometric configurations, and tri-stage loading. The model demonstrates exceptional predictive fidelity, yielding an overall correlation coefficient Rall = 0.99915. Principal results reveal that the bio-inspired helicoidal technique significantly homogenizes interfacial stress distribution, effectively mitigating peak concentrations at the plate ends. Parametric investigations demonstrate that optimizing the reinforcement density (12–32 layers) and fiber architecture facilitates a global reduction in peak interfacial shear and normal stresses by up to 40
Emotion regulation (ER), empathy, and self-efficacy are key components of adolescent development. While these constructs have often been examined separately, their associations have received limited attention, particularly in non-Western contexts. This study examines the relationships among two types of ER (i.e., cognitive reappraisal [CR] and expressive suppression [ES]), empathy, and self-efficacy within the socio-cultural context of Algerian adolescents. A cross-sectional study was conducted involving 459 adolescent students. Participants completed the Self-Efficacy Questionnaire for Children, the Basic Empathy Scale, and the Emotion Regulation Questionnaire for Children and Adolescents. Pearson correlation analyses indicated significant positive associations among CR, empathy, and self-efficacy. Moreover, ES was significantly associated with self-efficacy but not empathy. Mediation analysis indicated that empathy significantly mediated the relationship between CR and self-efficacy, while the direct effect of CR on self-efficacy remained significant. However, empathy was not a significant mediator in the association between ES and self-efficacy. Overall, the results highlight interconnected patterns among two types of ER, empathy, and self-efficacy during adolescence. This study contributes to a clearer understanding of how these psychological constructs relatewithin the specific socio-cultural context of Algerian adolescents and adds to the broader literature on adolescent psychological development.
Perovskite-type hydrides have emerged as promising candidates for next-generation solid-state hydrogen storage owing to their tunable structural, mechanical, and thermal properties. Here, we combine density functional theory (DFT) and machine learning (ML) to investigate cubic XMnH3 perovskites (X = Li, Na, K) and extend predictions to unexplored compositions and pressures. DFT calculations confirm that all compounds stabilize in a ferromagnetic cubic phase with negative formation energies, competitive hydrogen storage capacities (4.66 wt.% for LiMnH3, 3.73 wt.% for NaMnH3, and 3.12 wt.% for KMnH3), and hydrogen desorption temperatures between 517-886 K. Elastic constants establish mechanical stability up to 30 GPa, though with inherent brittleness, while thermal analysis via the quasi-harmonic Debye model highlights pressure-driven stiffening of the lattice. To circumvent the limitations of small DFT datasets, we trained Random Forest, XGBoost, and neural network models on direct and derived DFT descriptors, and we demonstrated that ensemble tree models yield the most accurate predictions. LiMnH3 continuously outperforms heavier analogues, and expected monotonic trends are reproduced when the Debye and melting temperatures are extended to 60 GPa. Moreover, screening of about 46 ABH(3) hydrides was made possible by composition-based descriptors created with Matminer, which showed systematic ionic-radius trends and identified BeMnH3 and MgMnH3 as promising candidates with superior vibrational stability and hardness. This integrated DFT-ML framework establishes a predictive strategy for accelerating the discovery of hydrides with optimized hydrogen storage performance.
