Nanoscale Zr-containing precipitates; a solution for significant improvement of high-temperature strength in Al-Si-Cu-Mg alloys

Jaguar Range Rove

Effect of family-based cognitive behavioral therapy in modification of self-image associated with obesity among children

Background and purpose: The purpose of this study was to investigate the effect of family-based cognitive behavioral therapy in modification of self-image associated with obesity in children. Materials and methods: A randomized controlled trial was performed in children with obesity (BMI � 95th percentile(aged 8-15 years old. Using convenience sampling, the participants were recruited from Children Hospital and Morsali clinic in Arak, Iran. They were randomly assigned to either the experimental group (n= 15) or control group (n= 15). The children in experimental group received family-based cognitive behavioral therapy (6 group sessions) and their parents attended 5 group sessions. All participants completed Body Parts Satisfaction Scale-Revised (BPSS-R) and Standard Figural Stimuli Scale (SFSS) in pretest, posttest and follow-up. BMI was calculated in all three stages. Results: Family-based cognitive-behavioral therapy was found effective in improving the body parts satisfaction (P=0.023) and body image satisfaction (P=0.0001). The improvement maintained only in body image at follow-up (P=0.0001). Conclusion: According to these results, family-based cognitive behavioral therapy is effective in modification of self-image in children. © 2016, Mazandaran University of Medical Sciences. All rights reserved

Integration of VR with BIM to facilitate real-time creation of bill of quantities during the design phase:a proof of concept study

As time goes on and building practices change, procedures that at one point seemed indispensable can fall by the wayside. One such example is the bill of quantities (B/Q). Research into the extant literature attributes declining use of B/Qs to a multitude of reasons, such as its complexity and potentially drawn-out time to produce, non-traditional procurement systems growing in popularity and the challenge of using its information in a construction schedule. With these issues in mind, a combined process of Building Information Modelling (BIM), Virtual Reality (VR) and including the client in the design process has been proposed as a potential solution. Following a literature review and precedent study, an experiment was carried out using this new process to simulate a client’s design decisions on window and interior furnishings, specifically. Their choices made using VR automatically updated a B/Q Revit Schedule and allowed the client to have a firm grasp on the project costs. Not only did this process give the client more confidence in a pleasing final outcome, but the technology ensured an up-to-date, accurate and easily understood B/Q. Here lies great potential savings in cost, time and gives the B/Q a newfound importance in future construction processes. The research case presented in this paper was a stepping stone in exploring new opportunities offered by VR and BIM and how they could improve the reliability and accuracy of traditional procurement within construction, specifically within the B/Q document

Design and Synthesis of Heterocyclic Cations for Specific DNA Recognition: From AT-Rich to Mixed-Base-Pair DNA Sequences

The compounds synthesized in this research were designed with the goal of establishing a new paradigm for mixed-base-pair DNA sequence-specific recognition. The design scheme starts with a cell-permeable heterocyclic cation that binds to AT base pair sites in the DNA minor groove. Modifications were introduced in the original compound to include an Hbond accepting group to specifically recognize the G-NH that projects into the minor groove. Therefore, a series of heterocyclic cations substituted with an azabenzimidazole ring has been designed and synthesized for mixed-base-pair DNA recognition. The most successful compound, 12a, had an azabenzimidazole to recognize G and additional modifications for general minor groove interactions. It binds to the DNA site −AAAGTTT− more strongly than the −AAATTT− site without GC and indicates the design success. Structural modifications of 12a generally weakened binding. The interactions of the new compound with a variety of DNA sequences with and without GC base pairs were evaluated by thermal melting analysis, circular dichroism, fluorescence emission spectroscopy, surface plasmon resonance, and molecular modeling

The NAMPT inhibitor FK866 reverts the damage in spinal cord injury

<p>Abstract</p> <p>Background</p> <p>Emerging data implicate nicotinamide phosphoribosyl transferase (NAMPT) in the pathogenesis of cancer and inflammation. NAMPT inhibitors have proven beneficial in inflammatory animal models of arthritis and endotoxic shock as well as in autoimmune encephalitis. Given the role of inflammatory responses in spinal cord injury (SCI), the effect of NAMPT inhibitors was examined in this setting.</p> <p>Methods</p> <p>We investigated the effects of the NAMPT inhibitor FK866 in an experimental compression model of SCI.</p> <p>Results</p> <p>Twenty-four hr following induction of SCI, a significant functional deficit accompanied widespread edema, demyelination, neuron loss and a substantial increase in TNF-α, IL-1β, PAR, NAMPT, Bax, MPO activity, NF-κB activation, astrogliosis and microglial activation was observed. Meanwhile, the expression of neurotrophins BDNF, GDNF, NT3 and anti-apoptotic Bcl-2 decreased significantly. Treatment with FK866 (10 mg/kg), the best known and characterized NAMPT inhibitor, at 1 h and 6 h after SCI rescued motor function, preserved perilesional gray and white matter, restored anti-apoptotic and neurotrophic factors, prevented the activation of neutrophils, microglia and astrocytes and inhibited the elevation of NAMPT, PAR, TNF-α, IL-1β, Bax expression and NF-κB activity.</p> <p>We show for the first time that FK866, a specific inhibitor of NAMPT, administered after SCI, is capable of reducing the secondary inflammatory injury and partly reduce permanent damage. We also show that NAMPT protein levels are increased upon SCI in the perilesional area which can be corrected by administration of FK866.</p> <p>Conclusions</p> <p>Our findings suggest that the inflammatory component associated to SCI is the primary target of these inhibitors.</p

Adenosine A2A receptors: localization and function

Adenosine is an endogenous purine nucleoside present in all mammalian tissues, that originates from the breakdown of ATP. By binding to its four receptor subtypes (A1, A2A, A2B, and A3), adenosine regulates several important physiological functions at both the central and peripheral levels. Therefore, ligands for the different adenosine receptors are attracting increasing attention as new potential drugs to be used in the treatment of several diseases. This chapter is aimed at providing an overview of adenosine metabolism, adenosine receptors localization and their signal transduction pathways. Particular attention will be paid to the biochemistry and pharmacology of A2A receptors, since antagonists of these receptors have emerged as promising new drugs for the treatment of Parkinson's disease. The interactions of A2A receptors with other nonadenosinergic receptors, and the effects of the pharmacological manipulation of A2A receptors on different body organs will be discussed, together with the usefulness of A2A receptor antagonists for the treatment of Parkinson's disease and the potential adverse effects of these drugs

Machine learning for estimation of building energy consumption and performance:a review

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance