Label-free detection of human prostate-specific antigen (hPSA) using film bulk acoustic resonators (FBARs)

Label-free detection of cancer biomarkers using low cost biosensors has promising applications in clinical diagnostics. In this work, ZnO-based thin film bulk acoustic wave resonators (FBARs) with resonant frequency of ∼1.5 GHz and mass sensitivity of 0.015 mg/m2 (1.5 ng/cm2) have been fabricated for their deployment as biosensors. Mouse monoclonal antibody, anti-human prostate-specific antigen (Anti-hPSA) has been used to bind human prostate-specific antigen (hPSA), a model cancer used in this study. Ellipsometry was used to characterize and optimise the antibody adsorption and antigen binding on gold surface. It was found that the best amount of antibody at the gold surface for effective antigen binding is around 1 mg/m2, above or below which resulted in the reduced antigen binding due to either the limited binding sites (below 1 mg/m2) or increased steric effect (above 1 mg/m2). The FBAR data were in good agreement with the data obtained from ellipsometry. Antigen binding experiments using FBAR sensors demonstrated that FBARs have the capability to precisely detect antigen binding, thereby making FBARs an attractive low cost alternative to existing cancer diagnostic sensors. © 2013 Elsevier B.V.

Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation.

The human cervix is an important mechanical barrier in pregnancy which must withstand the compressive and tensile forces generated from the growing fetus. Premature cervical shortening resulting from premature cervical remodeling and alterations of cervical material properties are known to increase a woman׳s risk of preterm birth (PTB). To understand the mechanical role of the cervix during pregnancy and to potentially develop indentation techniques for in vivo diagnostics to identify women who are at risk for premature cervical remodeling and thus preterm birth, we developed a spherical indentation technique to measure the time-dependent material properties of human cervical tissue taken from patients undergoing hysterectomy. In this study we present an inverse finite element analysis (IFEA) that optimizes material parameters of a viscoelastic material model to fit the stress-relaxation response of excised tissue slices to spherical indentation. Here we detail our IFEA methodology, report compressive viscoelastic material parameters for cervical tissue slices from nonpregnant (NP) and pregnant (PG) hysterectomy patients, and report slice-by-slice data for whole cervical tissue specimens. The material parameters reported here for human cervical tissue can be used to model the compressive time-dependent behavior of the tissue within a small strain regime of 25%.

Effect of dry oxidation on the energy gap and chemical composition of CVD graphene on nickel

The findings presented herein show that the electronic properties of CVD graphene on nickel can be altered from metallic to semiconducting by introducing oxygen adsorbates via UV/ozone or oxygen plasma treatment. These properties can be partially recovered by removing the oxygen adsorbates via vacuum annealing treatment. The effect of oxidation is studied by scanning tunneling microscopy/spectroscopy (STM/STS) and X-ray photoelectron spectroscopy (XPS). As probed by STM/STS, an energy gap opening of 0.11-0.15 eV is obtainable as the oxygen/carbon atomic ratio reaches 13-16%. The corresponding XPS spectra show a significant monotonic increase in the concentration of oxygenated functional groups due to the oxidation treatments. This study demonstrates that the opening of energy gap in CVD graphene can be reasonably controlled by a combination of UV/ozone or oxygen plasma treatment and vacuum annealing treatment. © 2013 Elsevier B.V.

Behavior learning of a face robot based on the characteristics of human instruction

Computer simulation experiments were performed to examine the effectiveness of OR- and comparative-reinforcement learning algorithms. In the simulation, human rewards were given as +1 and -1. Two models of human instruction that determine which reward is to be given in every step of a human instruction were used. Results show that human instruction may have a possibility of including both model-A and model-B characteristics, and it can be expected that the comparative-reinforcement learning algorithm is more effective for learning by human instructions.