Spatial inverse query processing

Traditional spatial queries return, for a given query object q, all database objects that satisfy a given predicate, such as epsilon range and k-nearest neighbors. This paper defines and studies inverse spatial queries, which, given a subset of database objects Q and a query predicate, return all objects which, if used as query objects with the predicate, contain Q in their result. We first show a straightforward solution for answering inverse spatial queries for any query predicate. Then, we propose a filter-and-refinement framework that can be used to improve efficiency. We show how to apply this framework on a variety of inverse queries, using appropriate space pruning strategies. In particular, we propose solutions for inverse epsilon range queries, inverse k-nearest neighbor queries, and inverse skyline queries. Furthermore, we show how to relax the definition of inverse queries in order to ensure non-empty result sets. Our experiments show that our framework is significantly more efficient than naive approaches.     

Generalized modal satisfiability

It is well known that modal satisfiability is PSPACE-complete (Ladner (1977) [21]). However, the complexity may decrease if we restrict the set of propositional operators used. Note that there exist an infinite number of propositional operators, since a propositional operator is simply a Boolean function. We completely classify the complexity of modal satisfiability for every finite set of propositional operators, i.e., in contrast to previous work, we classify an infinite number of problems. We show that, depending on the set of propositional operators, modal satisfiability is PSPACE-complete, coNP-complete, or in P. We obtain this trichotomy not only for modal formulas, but also for their more succinct representation using modal circuits. We consider both the uni-modal and the multi-modal cases, and study the dual problem of validity as well.     

Oxygen permeation of various archetypes of oxygen membranes based on BSCF

Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3‐δ tubes, capillaries, capillary modules, and asymmetric membranes were prepared and tested for oxygen permeation in a dead‐end vacuum operation mode at temperatures up to 850^°C. The capillary module was built up by reactive air brazing using seven capillaries and a supply tube. Two machined discs were used as an end cap and as a connector plate. The oxygen permeation behaves according to Wagner at small driving forces, but significant negative deviations were observed for asymmetric membranes and single capillaries at higher ones. This is caused by pressure drops at the vacuum side for single capillaries. The highest oxygen flux was revealed for the capillary module with 175.5 mL(STP)/min at a low‐vacuum pressure of 0.042 bar at 850^°C, but the asymmetric membrane showing a little bit higher flux at moderate vacuum pressures above 0.07 bar. © 2012 American Institute of Chemical Engineers AIChE J, 58: 3195–3202, 2012     

Pre-adolescent children exhibit lower aerosol particle volume emissions than adults for breathing,speaking, singing and shouting

Speaking and singing are activities linked to increased aerosol particle emissions from the respiratory system, dependent on the utilized vocal intensity. As a result, these activities have experienced considerable restrictions in enclosed spaces since the onset of the COVID-19 pandemic due to the risk of infection from the SARS-CoV-2 virus, transmitted by virus-carrying aerosols. These constraints have affected public education and extracurricular activities for children as well, from in-person music instruction to children’s choirs. However, existing risk assessments for children have been based on emission measurements of adults. To address this, we measured the particle emission rates of 15 pre-adolescent children, all eight to ten years old, with a laser particle counter for the test conditions: breathing at rest, speaking, singing and shouting. Compared with values taken from 15 adults, emission rates for breathing, speaking and singing were significantly lower for children. Particle emission rates were reduced by a factor of 4.3 across all conditions, whereas emitted particle volume rates were reduced by a factor of 4.8. These data can supplement SARS-CoV-2 risk management scenarios for various school and extracurricular settings.     

Hierarchically Structured Poly(alkyl‐p‐xylylene) Nonwovens with Superhydrophobic Properties

Hierarchically structured poly(alkyl‐p‐xylylene) (alkyl‐PPX) nonwovens are prepared by specific parameter variation during the electrospinning process. The investigated parameters are changes in solutions properties and ambient humidity level, which lead to the formation of different fiber architectures and surface morphologies. The characterization of the nonwovens by scanning electron microscopy confirms the formation of hierarchically structured fibers, comprising bead‐on‐string architecture if spun from tetra­hydrofuran (THF) solutions, and porous surfaces at relative humidity (RH) levels > 30% for both chloroform and THF solutions. The wetting properties of nonwovens spun from THF and chloroform solutions are analyzed by water contact angle (CA) measurements, roll‐angle determination, and high speed imaging. PPX‐heptyl and PPX‐butyl fiber mats spun from 2.5 wt% THF and PPX‐heptyl spun from 3 wt% chloroform solutions at RH > 75% show superhydrophobic and self‐cleaning properties with CA > 153° and roll‐off angles of 10–15°. The nonwovens maintain their fiber morphology and water‐repellent properties after thermal and mechanical stress.

     

Optimal sensor placement for joint parameter and state estimation problems in large-scale dynamical systems with applications to thermo-mechanics

We consider large-scale dynamical systems in which both the initial state and some parameters are unknown. These unknown quantities must be estimated from partial state observations over a time window. A data assimilation framework is applied for this purpose. Specifically, we focus on large-scale linear systems with multiplicative parameter-state coupling as they arise in the discretization of parametric linear time-dependent partial differential equations. Another feature of our work is the presence of a quantity of interest different from the unknown parameters, which is to be estimated based on the available data. In this setting, we employ a simplicial decomposition algorithm for an optimal sensor placement and set forth formulae for the efficient evaluation of all required quantities. As a guiding example, we consider a thermo-mechanical PDE system with the temperature constituting the system state and the induced displacement at a certain reference point as the quantity of interest.