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.     

Precise selective deposition of microparticles on electrodes of microelectronic chips

We examined the high precision deposition of toner and polymer microparticles with a typical size of approximately 10 microm on electrode arrays with electrodes of 100 microm and below using custom-made microelectronic chips. Selective desorption of redundant particles was employed to obtain a given particle pattern from preadsorbed particle layers. Microparticle desorption was regulated by dielectrophoretic attracting forces generated by individual pixel electrodes, tangential detaching forces of an air flow, and adhesion forces on the microchip surface. A theoretical consideration of the acting forces showed that without pixel voltage, the tangential force applied for particle detachment exceeded the particle adhesion force. When the pixel voltage was switched on, however, the sum of attracting forces was larger than the tangential detaching force, which was crucial for desorption efficiency. In our experiments, appropriately large dielectrophoretic forces were achieved by applying high voltages of up to 100 V on the pixel electrodes. In addition, electrode geometries on the chip's surface as well as particle size influenced the desorption quality. We further demonstrated the compatibility of this procedure to complementary metal oxide semiconductor chip technology, which should allow for an easy technical implementation with respect to high-resolution microparticle deposition.     

Microstructure and properties of K2O doped superconducting YBa2Cu3O7−x

K doped YBa₂Cu₂O _x powders have been obtained by incorporating K₂CO₃ to previously coprecipitated amorphous hydroxide mixtures. Synthesis was performed at 900C and an orthorhombic 1 2 3 phase was the final product. Sintering of isopressed bars was carried out from 920 to 940C. K doping up to 5 at % led to the development of dense bodies with good superconducting behaviour. Oxygen pick-up during the cooling step following sintering was well accomplished despite the high density of the samples. Transition temperatures 90 K were measured. Doping above that percentage led to samples with lower density values. The presence of non-superconducting phases, such as CuO and a green phase, was very significant, and suppressed the superconducting transition.     

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.     

Deterministic Polymorphic Engineering of MoTe2 for Photonic and Optoelectronic Applications

Developing selective and coherent polymorphic crystals at the nanoscale offers a novel strategy for designing integrated architectures for photonic and optoelectronic applications such as metasurfaces, optical gratings, photodetectors, and image sensors. Here, a direct optical writing approach is demonstrated to deterministically create polymorphic 2D materials by locally inducing metallic 1T′-MoTe₂ on the semiconducting 2H-MoTe₂ host layer. In the polymorphic-engineered MoTe₂, 2H- and 1T′- crystalline phases exhibit strong optical contrast from near-infrared to telecom-band ranges (1–1.5 µm), due to the change in the band structure and increase in surface roughness. Sevenfold enhancement of third harmonic generation intensity is realized with conversion efficiency (susceptibility) of ≈1.7 × 10⁻⁷ (1.1 × 10⁻¹⁹ m² V⁻²) and ≈1.7 × 10⁻⁸ (0.3 × 10⁻¹⁹ m² V⁻²) for 1T′ and 2H-MoTe₂, respectively at telecom-band ultrafast pump laser. Lastly, based on polymorphic engineering on MoTe₂, a Schottky photodiode with a high photoresponsivity of 90 AW⁻¹ is demonstrated. This study proposes facile polymorphic engineered structures that will greatly benefit realizing integrated photonics and optoelectronic circuits.     

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.

     

Conditional-sampling spectrograph detection system for fluorescence measurements of individual airborne biological particles

We report the design and operation of a prototype conditional-sampling spectrograph detection system that can record the fluorescence spectra of individual, micrometer-sized aerosols as they traverse an intense 488-nm intracavity laser beam. The instrument's image-intensified CCD detector is gated by elastic scattering or by undispersed fluorescence from particles that enter the spectrograph's field of view. It records spectra only from particles with preselected scattering-fluorescence levels (a fiber-optic-photomultiplier subsystem provides the gating signal). This conditional-sampling procedure reduces data-handling rates and increases the signal-to-noise ratio by restricting the system's exposures to brief periods when aerosols traverse the beam. We demonstrate these advantages by reliably capturing spectra from individual fluorescent microspheres dispersed in an airstream. The conditional-sampling procedure also permits some discrimination among different types of particles, so that spectra may be recorded from the few interesting particles present in a cloud of background aerosol. We demonstrate such discrimination by measuring spectra from selected fluorescent microspheres in a mixture of two types of microspheres, and from bacterial spores in a mixture of spores and nonfluorescent kaolin particles.     

Beyond loop bounds: comparing annotation languages for worst-case execution time analysis

Worst-case execution time (WCET) analysis is concerned with computing a precise-as-possible bound for the maximum time the execution of a program can take. This information is indispensable for developing safety-critical real-time systems, e. g., in the avionics and automotive fields. Starting with the initial works of Chen, Mok, Puschner, Shaw, and others in the mid and late 1980s, WCET analysis turned into a well-established and vibrant field of research and development in academia and industry. The increasing number and diversity of hardware and software platforms and the ongoing rapid technological advancement became drivers for the development of a wide array of distinct methods and tools for WCET analysis. The precision, generality, and efficiency of these methods and tools depend much on the expressiveness and usability of the annotation languages that are used to describe feasible and infeasible program paths. In this article we survey the annotation languages which we consider formative for the field. By investigating and comparing their individual strengths and limitations with respect to a set of pivotal criteria, we provide a coherent overview of the state of the art. Identifying open issues, we encourage further research. This way, our approach is orthogonal and complementary to a recent approach of Wilhelm et al. who provide a thorough survey of WCET analysis methods and tools that have been developed and used in academia and industry.