Impact loads due to ship collision on irrigation structures is significantly decreasing their durability. Loss of material and degradation are quite common problems facing lock walls and piers. In the current research, rubberized self-compacting concrete (SCC) was used to investigate problems associated with impact. SCC with cement kiln dust cement replacement was used for that purpose. Concrete specimens were prepared with different crumb rubber ratios of 10% (RSCC-10), 20% (RSCC-20), 30% (RSCC-30), and 40% (RSCC-40) sand replacement by volume. Standard compressive, flexure, and splitting strength tests were conducted to monitor the effect of the added rubber on concrete behavior. Moreover, impact testing program was applied to specific specimens, cylinder of diameter 200 mm and thickness 50 mm, according to ACI committee 544 procedures. The number of blows to first and ultimate cracks was determined. The relationship between the mechanical properties and impact resilience is also presented. With the increase in rubber percentage the resistance to impact increased, but there was a decrease in specimen strength and modulus of elasticity. The variation in results was discussed and mix RSCC-30 exhibited the best impact resistance, 3 times over control mix with 40% reduction of compressive strength.

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Background Functional mapping of eloquent brain areas is crucial for preoperative planning in patients with brain tumors. Resting state functional MRI (rs-fMRI) allows the localization of functional brain areas without the need for task performance, making it well-suited for the pediatric population. In this study the independent component analysis (ICA) rs-fMRI functional mapping results are reported in a group of 22 pediatric patients with supratentorial brain tumors. Additionally, the functional connectivity (FC) maps of the sensori-motor network (SMN) obtained using ICA and seed-based analysis (SBA) are compared. Results Different resting state networks (RSNs) were extracted using ICA with varying levels of sensitivity, notably, the SMN was identified in 100% of patients, followed by the Default mode network (DMN) (91%) and Language networks (80%). Additionally, FC maps of the SMN extracted by SBA were more extensive (mean volume = 25,288.36 mm3, standard deviation = 13,364.36 mm3) than those found on ICA (mean volume = 13,403.27 mm3, standard deviation = 9755.661 mm3). This was confirmed by statistical analysis using a Wilcoxon signed rank t test at p < 0.01. Conclusions Results clearly demonstrate the successful applicability of rs-fMRI for localizing different functional brain networks in the preoperative assessment of brain areas, and thus represent a further step in the integration of computational radiology research in a clinical setting.

In the framework of structural health monitoring, continuous dynamic records are essential for good judgment of structures. Overall degradation of structures can be obtained with reasonable accuracy using various system identification techniques. It is however, challenging to obtain precisely the position and size of local damages. The current research focuses on Damage Index Method (DIM) as a tool for determining local damages occurred in flexural structural elements. The DIM technique depends on comparing modal strain energies of structures at different degradation stages. Self-made computer module was developed to encounter DIM for damage detection. First, the method was verified experimentally. Simply supported steel beam of 1500 mm (length), 50 mm (width) and 6 mm (thickness), in addition to steel plate of area 930 · 910 mm and 3 mm (thickness) was implemented in the experimental program. Both the beam and plate were subjected to different damage configurations. Collected acceleration time history was processed and used to verify the adequacy of DIM in identifying damages in the used physical models. Numerical parametric study was also conducted on a variety of beams and plates with various damage degrees and locations. It was noticed that both the experimental and numerical results showed good agreement in identifying damages in flexural structural elements. ª 2015 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).