End of life management of industrial robots

End of life management (EOL) is currently a hot topic in the electronics industry. Currently, mostly IT equipment and goods of consumer electronics are considered. In the nearest future automation equipment has also to be taken into account. There are three possibilities depending on the age and kind of the device: resell–reuse–recycle, called the “3Rs”. For recycling fully or semi-automated disassembly will gain in importance in the nearest future also for robots. Producers of robots have to take into account EoL because of regulations and laws as well as according to ethical codes contributing to protection of the environment. Based on previous works a real example will be presented and discussed.     

Synthesis and Evaluation of Water‐Soluble Prodrugs of Ursodeoxycholic Acid (UDCA), an Anti‐apoptotic Bile Acid

Ursodeoxycholic acid (UDCA) is a bile acid with demonstrated anti‐apoptotic activity in both in vitro and in vivo models. However, its utility is hampered by limited aqueous solubility. As such, water‐soluble prodrugs of UDCA could have an advantage over the parent bile acid in indications where intravenous administration might be preferable, such as decreasing damage from stroke or acute kidney injury. Five phosphate prodrugs were synthesized, including one incorporating a novel phosphoryloxymethyl carboxylate (POMC) moiety. These prodrugs were highly water‐soluble, but showed significant differences in chemical stability, with oxymethylphosphate prodrugs being the most unstable. In a series of NMR experiments, the POMC prodrug was bioactivated to UDCA by alkaline phosphatase (AP) faster than a prodrug containing a phosphate directly attached to the alcohol at the 3‐position of UDCA. Both of these prodrugs showed significant anti‐apoptotic activity in a series of in vitro assays, although the POMC prodrug required the addition of AP for activity, while the other compound was active without exogenous AP.     

Effect of precipitation on the geological development of badlands in arid regions

The main objective of this paper was to study the effect of precipitation on the geological development of badlands in arid regions. Field observations and laboratory investigations were carried out to characterize the surface soils of the Avonlea badlands in southern Saskatchewan, Canada, which is currently experiencing a rapid development in infrastructure. Three distinct surface sediments were identified: an upper slope of cemented sandstone, a mid-slope on weathered mudrock and a relatively flat basal pediment. Each of these soils reacts differently to rainfall events. Precipitation results in grain size reduction which, together with the consistency limits, explains the water sensitivity of the soils; the fines increased by 16% in the cemented sandstone, 78% in the weathered mudrock and 33% in the basal pediment. Erosion susceptibility was highest in the basal pediment (2% clays) followed by cemented sandstone (cementation by 6% active clays) and then by weathered mudrock (cohesion due to the 40% clay).     

Acoustic emissions simulation of tumbling mills using charge dynamics

Knowledge of the internal variables of a mill is of importance in design and performance optimization of the mill, notwithstanding the difficulty in measuring these variables within the harsh mill environment. To overcome this problem, the research has focused on measuring the internal parameters through non-invasive measurement methods such as the use of the vibration/acoustic signal obtained from the mill. Alternatively, virtual instruments, such as discrete element methods (DEM), are employed. Here, a methodology is developed to simulate on-the-shell acoustic signal emitted from tumbling mills using the information extracted from a DEM simulator. The transfer function which links the forces exerted on the internal surface of the mill and the acoustic signal measured on the outer surface is measured experimentally. Given this transfer function and the force distribution obtained from the DEM simulation, and assuming a linear time-invariant response, the on-the-shell acoustic of a laboratory scale ball mill has been simulated. Comparison of this simulated signal with the signal measured experimentally can be used as a criterion to judge the validity of the DEM simulations, and as a tool for enhancing our understanding of both DEM simulations and the use of acoustics within the context of mineral processing. The results derived from preliminary experiments on a laboratory scale mill shows satisfactory agreement between the actual measurement and the simulated acoustic signal.     

Supervised inductive learning with Lotka–Volterra derived models

We present a classification algorithm built on our adaptation of the Generalized Lotka–Volterra model, well-known in mathematical ecology. The training algorithm itself consists only of computing several scalars, per each training vector, using a single global user parameter and then solving a linear system of equations. Construction of the system matrix is driven by our model and based on kernel functions. The model allows an interesting point of view of kernels’ role in the inductive learning process. We describe the model through axiomatic postulates. Finally, we present the results of the preliminary validation experiments.     

Analyzing developmental processes on an individual level using nonstationary time series modeling.

Individuals change over time, often in complex ways. Generally, studies of change over time have combined individuals into groups for analysis, which is inappropriate in most, if not all, studies of development. The authors explain how to identify appropriate levels of analysis (individual vs. group) and demonstrate how to estimate changes in developmental processes over time using a multivariate nonstationary time series model. They apply this model to describe the changing relationships between a biological son and father and a stepson and stepfather at the individual level. The authors also explain how to use an extended Kalman filter with iteration and smoothing estimator to capture how dynamics change over time. Finally, they suggest further applications of the multivariate nonstationary time series model and detail the next steps in the development of statistical models used to analyze individual-level data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)