Structural behavior of mortarless interlocking load bearing hollow block wall panel under out-of-plane loading.

Experimental and numerical investigation of interlocking mortarless wall panels with 1.0 m height, 1.2 m width and 150 mm thickness are conducted. Behaviour of both hollow and partially grouted masonry wall panels is studied. The panels were tested under constant pre-compressive vertical load and out-of-plane lateral load. Lateral load carrying capacity, deflection at mid height, dry joint opening between block layers and mode of failure are investigated. Strain characteristics throughout the loading process are also monitored. A finite element analysis is presented for the system and a good agreement between the experimental and modelling results is achieved. Parametric study using the finite element model is also presented and the effect of different parameters; amount of pre-compressive load and slenderness ratio is studied. The study reveals that pre-compressive vertical load and reinforcement significantly affect the structural behaviour of mortarless walls under out-of-plane loading. Useful expressions for the capacity are obtained from the analysis

Computational Drug Repurposing: Current Trends

Biomedical discovery has been reshaped upon the exploding digitization of data which can be retrieved from a number of sources, ranging from clinical pharmacology to cheminformatics-driven databases. Now, supercomputing platforms and publicly available resources such as biological, physicochemical, and clinical data, can all be integrated to construct a detailed map of signaling pathways and drug mechanisms of action in relation to drug candidates. Recent advancements in computer-aided data mining have facilitated analyses of 'big data' approaches and the discovery of new indications for pre-existing drugs has been accelerated. Linking gene-phenotype associations to predict novel drug-disease signatures or incorporating molecular structure information of drugs and protein targets with other kinds of data derived from systems biology provide great potential to accelerate drug discovery and improve the success of drug repurposing attempts. In this review, we highlight commonly used computational drug repurposing strategies, including bioinformatics and cheminformatics tools, to integrate large-scale data emerging from the systems biology, and consider both the challenges and opportunities of using this approach. Moreover, we provide successful examples and case studies that combined various in silico drug-repurposing strategies to predict potential novel uses for known therapeutics