Mix Design Effects on the Durability of Alkali-Activated Slag Concrete in a Hydrochloric Acid Environment

Because of its high strength, energy reduction, and low environmental impact, researchers have encouraged considering alkali-activated slag concrete (AASC) as a potential alternative to conventional concrete. In this study, the impact of mix design parameters on the durability of AASC, made with ground granulated blast furnace slag and activated with different alkaline solutions (NaOH, KOH, and Na2SiO3 ) immersed up to six months in a hydrochloric acid bath with pH = 3, has been investigated. A total of 13 mix designs were made in a way that, in addition to the type of alkaline solution, considered three other parameters, namely the molarity of alkaline solutions, the weight ratio of alkaline solutions to slag, and the weight ratio of alkaline solutions to sodium silicate. Visual inspections displayed that the AASC samples almost remained intact after exposure to an HCl acid solution with pH = 3 for up to 6 months, while the OPC sample experienced deleterious deterioration. The results clearly show that AASC outperformed OPC concrete when it comes to durability in an HCl acid solution. The strength reduction and weight loss of AASC compared with OPC concrete were approximately one-tenth and one-fifth, respectively. The AASC samples containing potassium hydroxide showed a higher strength reduction and weight loss in the HCl acid solution than the samples made with sodium hydroxide

Retro MTA and tricalcium phosphate/retro MTA for guided tissue regeneration of periodontal dehiscence defects in a dog model: a pilot study

Objectives: Retro MTA is a fast setting Calcium silicate cement used in endodontic regeneration procedures in recent years. Beta-tricalcium phosphate (β-TCP) is another common biomaterial used for bone augmentation procedures. The present pilot study was undertaken to evaluate and compare the efficacy of Retro MTA and a mixture of Retro MTA / β-TCP for periodontal tissue regeneration. Materials and methods: In 4 beagle dogs, periodontal dehiscence type defects were created. In each side, one dehiscence defect was left empty as a control site and three treatment modalities were randomly applied for the others: Retro MTA covered with a collagen membrane, Retro MTA + β-TCP covered with a membrane and covering the defect with a membrane without any bone augmentation. After 8 weeks Animals were sacrificed and Histomorphometric and histologic analysis were conducted. Results: Histologic analysis showed more cementum formation for both Retro MTA+ β-TCP (3.74 ± 0.34 mm) and Retro MTA group (3.24 ± 0.56 mm) compared to control group 1 (1. 15 ± 0.45 mm) and control group 2 (0.78 ± 0.65 mm). Formation of newly formed bone and cementum in the experimental groups were significantly higher as compared to the control groups (P < 0.0001). Conclusions: Retro MTA or Retro MTA+ β-TCP covered with a collagen membrane resulted in regeneration of periodontal tissues. However, Retro MTA+ β-TCP showed tendency towards better results than the use of Retro MTA alone. KEYWORDS: Bone regeneration; Calcium silicate cement; Guided tissue regeneration; MT

The Use of Machine Learning Models in Estimating the Compressive Strength of Recycled Brick Aggregate Concrete

The focus of this study is to investigate the applicability of Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), and Multiple Linear Regression (MLR) in modeling the compressive strength of Recycled Brick Aggregate Concrete (RBAC). A comparative study on the application of the aforementioned models is developed based on statistical tools such as coefficient of determination, mean absolute error, root mean squared error, and some others, and the application potential of each of these models is investigated. To study the effects of RBAC factors on the performance of representative data-driven models, the Sensitivity Analysis (SA) method is used. The findings revealed that ANN with R2 value of 0.9102 has a great application potential in predicting the compressive strength of concrete. In the absence of ANN, ANFIS with R2 value of 0.8538 is also an excellent substitute for predictions. MLR was shown to be less effective than the preceding models and is only recommended for preliminary estimations. In addition, Subsequent sensitivity analysis on the database indicates the reliability of the prediction models have a strong correlation to the number of input parameters. The application of ANN and ANFIS as a precursor to traditional methods can eliminate the need for old-style tests, thus, constituting a significant reduction in time and expense needed for design and/or repairs

An Efficient Routing Tree Algorithm for Combined Uplink and Downlink Subframes on Centralized Scheduling in IEEE 802.16 Based Wireless Mesh Networks

IEEE 802.16 mesh mode defines routing tree for transmitting data in centralized scheduling but it does not define any explicit proposal for combining uplink and downlink subframes. Deploying combined uplink and downlink subframes on the centralized scheduling scheme can be more flexible and utilization is improved. However, existing interferences among the transmission of neighboring nodes lead to performance reduction of the network. In this paper, an efficient routing tree algorithm is proposed with combined uplink and downlink slot allocation on the centralized scheduling scheme which can abate interferences in the network. This algorithm allows more subscriber stations to transmit concurrently and so improves spatial reuse in the network. Also, the algorithm uses multi-channel and single channel systems and considers relay model, smoothing switching frequently between transmitting and receiving in successive time slots and fairness in the network. Extensive simulation results demonstrate the effectiveness of the proposed method in terms of scheduling length, link concurrency ratio, network throughput and Channel Utilization Ratio (CUR)