High temperature field effect hydrogen and hydrocarbon gas sensors based on SiC MOS devices

The growing need for reliable, efficient, high temperature hydrogen and hydrocarbon monitoring has fueled research into novel structures for gas sensing. Metal oxide semiconductor (MOS) devices employing a catalytic metal layer have emerged as one of the leading sensing platforms for such applications, owing to their high sensitivity and inherent capability for signal amplification. The limited operating temperature of such devices employing silicon as the semiconductor has led research efforts to focus on replacing them with devices based on silicon carbide (SiC). More recently, MOS devices having different oxide layers exhibiting improved sensing performance have emerged. Considering the amount of research that has been carried out in this area in recent times, it is important to elucidate the new findings and the gas interaction mechanisms that have been ascribed to such devices, and bring together several theories proposed by different research groups. In this paper we first highlight the needs which have driven research into SiC based field effect hydrogen and hydrocarbon sensors, illustrate the various structures being investigated, and describe the device evolution and current status. We provide several sensing examples of devices that make use of different oxide layers and demonstrate how their electrical properties change in the presence of the gases, as well as presenting the hydrogen gas interaction mechanisms of these sensors.     

Uncertainty quantification and apportionment in air quality models using the polynomial chaos method

Current air quality models generate deterministic forecasts by assuming perfect model, perfectly known parameters, and exact input data. However, our knowledge of the physics is imperfect. It is of interest to extend the deterministic simulation results with “error bars” that quantify the degree of uncertainty, and analyze the impact of the uncertainty input on the simulation results. This added information provides a confidence level for the forecast results. Monte Carlo (MC) method is a popular approach for air quality model uncertainty analysis, but it converges slowly. This work discusses the polynomial chaos (PC) method that is more suitable for uncertainty quantification (UQ) in large-scale models. We propose a new approach for uncertainty apportionment (UA), i.e., we develop a PC approach to attribute the uncertainties in model results to different uncertainty inputs. The UQ and UA techniques are implemented in the Sulfur Transport Eulerian Model (STEM-III). A typical scenario of air pollution in the northeast region of the USA is considered. The UQ and UA results allow us to assess the combined effects of different input uncertainties on the forecast uncertainty. They also enable to quantify the contribution of input uncertainties to the uncertainty in the predicted ozone and PAN concentrations.     

Accuracy improvement method for flank milling surface design

In this paper, a variation of the method of designing surfaces for flank milling proposed by Li et al. 2006 (Surface design for flank milling. Submitted to CAD, July) is presented. Li’s method is based on the premise that the surface flank milled by a cylindrical tool can be represented by a NURBS surface and can be used by designers to build efficient impellers, blades and other engineering parts. In the proposed method, a four control point curve is used to approximate the grazing curves and for subsequent generation of a polynomial surface. This eliminates the need of weights for the interior control points and still results in a good surface. The accuracy of the surface can be controlled by adding control points. Examples are given to demonstrate the proposed surface design method.     

Islet amyloid polypeptide in patients with pancreatic cancer and diabetes

Population-based psychiatric admission rates vary across geographic areas, but reasons for this variation are unknown. Insofar as Community Mental Health Centers (CMHCs) provide outpatient services that may deter the need for hospitalization, the presence and structural characteristics of CMHCs may have an impact on a population's psychiatric admission rates. This study uses small area analysis to examine how general hospital psychiatric admission rates are associated with CMHC characteristics. Based on a survey of all CMHCs in Iowa and corresponding small area variation data, it was found that population admission rates were higher in areas closer to the CMHC and lower in outlying catchment areas, adjusting for age, sex, and urban/rural differences in populations. There was little evidence that differences in staffing and service variables influenced admission rates, although greater CMHC staff coverage by social workers and psychiatric residents was associated with lower admission rates. The results suggest that CMHCs do not lower an area's hospitalization rate, and in fact, the presence of CMHCs may promote a "supplier-induced demand" phenomenon of higher admissions.     

Novel Lyapunov-based rapid and ripple-free MPPT using a robust model reference adaptive controller for solar PV system

The technological, economic, and environmental benefits of photovoltaic (PV) systems have led to their widespread adoption in recent years as a source of electricity generation. However, precisely identifying a PV system''s maximum power point (MPP) under normal and shaded weather conditions is crucial to conserving the maximum generated power. One of the biggest concerns with a PV system is the existence of partial shading, which produces multiple peaks in the P–V characteristic curve. In these circumstances, classical maximum power point tracking (MPPT) approaches are prone to getting stuck on local peaks and failing to follow the global maximum power point (GMPP). To overcome such obstacles, a new Lyapunov-based Robust Model Reference Adaptive Controller (LRMRAC) is designed and implemented to reach GMPP rapidly and ripple-free. The proposed controller also achieves MPP accurately under slow, abrupt and rapid changes in radiation, temperature and load profile. Simulation and OPAL-RT real-time simulators in various scenarios are performed to verify the superiority of the proposed approach over the other state-of-the-art methods, i.e., ANFIS, INC, VSPO, and P&O. MPP and GMPP are accomplished in less than 3.8 ms and 10 ms, respectively. Based on the results presented, the LRMRAC controller appears to be a promising technique for MPPT in a PV system.     

A framework for implementing robotic process automation projects

Robotic process automation is a disruptive technology to automate already digital yet manual tasks and subprocesses as well as whole business processes rapidly. In contrast to other process automation technologies, robotic process automation is lightweight and only accesses the presentation layer of IT systems to mimic human behavior. Due to the novelty of robotic process automation and the varying approaches when implementing the technology, there are reports that up to 50% of robotic process automation projects fail. To tackle this issue, we use a design science research approach to develop a framework for the implementation of robotic process automation projects. We analyzed 35 reports on real-life projects to derive a preliminary sequential model. Then, we performed multiple expert interviews and workshops to validate and refine our model. The result is a framework with variable stages that offers guidelines with enough flexibility to be applicable in complex and heterogeneous corporate environments as well as for small and medium-sized companies. It is structured by the three phases of initialization, implementation, and scaling. They comprise eleven stages relevant during a project and as a continuous cycle spanning individual projects. Together they structure how to manage knowledge and support processes for the execution of robotic process automation implementation projects.

     

Antireflection coatings for UV radiation obtained by molecular-beam deposition

We have developed fluoride antireflection (AR) coatings on MgF(2) substrates for a wavelength of 248 nm by molecular-beam deposition. Transmission and laser-induced damage threshold of the samples were measured and atomic force microscope (AFM) investigations were carried out. We compare a 14-layer design for AR coatings with sublayer thicknesses of 12 nm with a conventional two-layer design with quarter-wavelength thicknesses. The laser-induced damage threshold of the 14-layer coating is slightly higher than that of the two-layer coating. The AFM surface images show that the 14-layer coating has a smoother surface than the two-layer coating.