Studies that investigated an association between asymmetric dimethylarginine (ADMA) and glycated haemoglobin (HbA1c) in type 2 diabetes mellitus (T2DM) have given discordant results. The aim of this study was to determine and compare serum ADMA concentration in patients with T2DM and healthy controls, and to assess correlation between ADMA and HbA1c in patients with T2DM. Serum ADMA concentration was determined by ELISA method with the use of ADMA ® - ELISA kit (DLD Diagnostics, Hamburg, Germany) and HbA1c levels were determined by an immunoturbidimetric method in 60 patients with T2DM and 60 healthy individuals matched for age and sex. Results have shown that mean serum ADMA concentration was significantly higher in T2DM patients (1.54±0.06 μmol/L) compared to mean serum ADMA concentration (0.62±0.02 μmol/L; p<0.0001) in healthy subjects. A significant, positive, correlation between serum ADMA concentration and HbA1c levels was observed (r=0.494; p<0.01) in T2DM patients. Our results suggest that there is an association between endothelial dysfunction and glycaemic control in type 2 diabetes mellitus. Possible explanation for obtained results may be oxidative stress that is increased in conditions of hyperglycaemia and it also promotes endothelial dysfunction. Larger, longitudinal studies are required that will evaluate relation between metabolic abnormalities and increased ADMA levels in patients with type 2 diabetes mellitus.

This paper seeks to address emerging concerns related to co-robotic technologies by exploring conceptual and practical approaches for explicitly including “the social” as the basis for developing and evaluating robots. In this talk, four recent projects performed within the scope of the R-House human-robot interaction lab ((http://rhouse.soic.indiana.edu)) is described. Three of the studies took place outside the laboratory - in users' homes, a local nursing institution, and an office - and involve culturally and socially situated studies of user perceptions of and interactions with robots to inform robot development. The fourth example describes the development of socially aware robotic agents using long time series of low resolution data (e.g. mechanical vibration, temperature, lighting, collisions) and bio-inspired computational methods to identify human presence and activities.

Conventionally, magnetic resonance imaging (MRI) is performed by pulsing gradient coils, which invariably leads to strong acoustic noise, patient safety concerns due to induced currents, and costly power/space requirements. This modeling study investigates a new silent, gradient coil-free MR imaging method, in which a radiofrequency (RF) coil and its nonuniform field (B 1 +) are mechanically rotated about the patient. The advantage of the rotating B 1 + field is that, for the first time, it provides a large number of degrees of freedom to aid a successful B 1 + image encoding process. The mathematical modeling was performed using flip angle modulation as part of a finite-difference-based Bloch equation solver. Preliminary results suggest that representative MR images with intensity deviations of <5% from the original image can be obtained using rotating RF field approach. This method may open up new avenues towards anatomical and functional imaging in medicine.

This paper describes fast analytical model for computation of the switched reluctance machine's (SRM) nonlinear magnetization characteristic and torque lookup table. The flux-tube and the gage-curve methods are used to develop this fast analytical model. Presented model is used for computation of the magnetization characteristic and torque lookup table of three and four-phase SRMs. The simulation results obtained using proposed analytical model are compared to the results of magnetostatic finite-element analysis (FEA) for a three-phase 12/8 SRM. Experimental verification of the analytical model is also presented for the same 12/8 SRM prototype.