Formal probabilistic analysis of a surgical robot control algorithm with different virtual fixtures

Surgical robots are increasingly being used in operation theaters involving normal or laparoscopic surgeries. The working of these surgical robots is highly dependent on their control algorithms, which require very rigorous analysis to ensure their correct functionality due to the safety-critical nature of surgeries. Traditionally, safety of control algorithms is ensured by simulations, but they provide incomplete and approximate analysis results due to their inherent sampling-based nature. We propose to use probabilistic model checking, which is a formal verification method, for quantitative analysis, to verify the control algorithms of surgical robots in this paper. As an illustrative example, the paper provides a formal analysis of a virtual fixture control algorithm, implemented in a neuro-surgical robot, using the PRISM model checker. In particular, we provide a formal discrete-time Markov chain-based model of the given control algorithm and its environment. This formal model is then analyzed for multiple virtual fixtures, like cubic, hexagonal and irregular shapes. This verification allowed us to discover new insights about the considered algorithm that allow us to design safer control algorithms.     

Toxicity and Metabolism of Layered Double Hydroxide Intercalated with Levodopa in a Parkinson’s Disease Model

Layered hydroxide nanoparticles are generally biocompatible, and less toxic than most inorganic nanoparticles, making them an acceptable alternative drug delivery system. Due to growing concern over animal welfare and the expense of in vivo experiments both the public and the government are interested to find alternatives to animal testing. The toxicity potential of zinc aluminum layered hydroxide (ZAL) nanocomposite containing anti-Parkinsonian agent may be determined using a PC 12 cell model. ZAL nanocomposite demonstrated a decreased cytotoxic effect when compared to levodopa on PC12 cells with more than 80% cell viability at 100 μg/mL compared to less than 20% cell viability in a direct levodopa exposure. Neither levodopa-loaded nanocomposite nor the un-intercalated nanocomposite disturbed the cytoskeletal structure of the neurogenic cells at their IC₅₀ concentration. Levodopa metabolite (HVA) released from the nanocomposite demonstrated the slow sustained and controlled release character of layered hydroxide nanoparticles unlike the burst uptake and release system shown with pure levodopa treatment.     

Non-uniform illumination in concentrating solar cells

After a gap of more than two decades, Concentrator Photovoltaics (CPV) technology is once again under spotlight for making use of the best available solar cell technologies and improving the overall performance. CPV finds its use in a number of applications ranging from building integration to huge power generation units. Although the principles of solar concentration are well understood, many practical design, operation, control issues require further understanding and research. A particular issue for CPV technology is the non-uniformity of the incident flux which tends to cause hot spots, current mismatch and reduce the overall efficiency of the system. Understanding of this effect requires further research, and shall help to employ the most successful means of using solar concentrators. This study reviews the causes and effects of the non-uniformity in the CPV systems. It highlights the importance of this issue in solar cell design and reviews the methods for the solar cell characterization under non-uniform flux conditions. Finally, it puts forward a few methods of improving the CPV performance by reducing the non-uniformity effect on the concentrator solar cells.