Novel measurement system for respiratory aerosols and droplets in indoor environments

The SARS-CoV-2 pandemic has created a great demand for a better understanding of the spread of viruses in indoor environments. A novel measurement system consisting of one portable aerosol-emitting mannequin (emitter) and a number of portable aerosol-absorbing mannequins (recipients) was developed that can measure the spread of aerosols and droplets that potentially contain infectious viruses. The emission of the virus from a human is simulated by using tracer particles solved in water. The recipients inhale the aerosols and droplets and quantify the level of solved tracer particles in their artificial lungs simultaneously over time. The mobile system can be arranged in a large variety of spreading scenarios in indoor environments and allows for quantification of the infection probability due to airborne virus spreading. This study shows the accuracy of the new measurement system and its ability to compare aerosol reduction measures such as regular ventilation or the use of a room air purifier.     

Neural architecture for robotic vision sensor that discounts uneven illumination in a manufacturing environment

Computer vision algorithms for inspection or pick-and-place operations often depend on spatially uniform illumination of a workplace. This necessitates expensive lighting fixtures. To discount effects of uneven illumination we designed and tested a neural network that can adaptively control light sensitivity at the photosensor level. Our neural network architecture consists of multiple layers with hexagonally arranged nodes. All nodes have partially overlapping receptive fields of different spatial frequencies. Feedforward connections are excitatory while feedback pathways subserve lateral inhibition. The outputs of these nodes are combined so as to maximize the signal-to-noise ratio while constantly resetting thresholds to maintain high sensitivity. Our connectionist architecture can account for many characteristics attributed to the lightness constancy phenomenon observed in biological systems. The results suggest that our module maintains high sensitivity over the whole domain of intensities without interfering with transmission of visual information embedded in spatial discontinuities of intensity.     

On maximum norm contractivity of second order damped single step methods

In this paper we consider A(θ)-stable finite difference methods for numerical solutions of dissipative partial differential equations of parabolic type. Combining two rational approximation methods with different orders of accuracy, where the lower order method is applied n ₀ times (n ₀ fixed) at each time step, we prove the existence of a second order method which is contractive for all time steps. Moreover, we shed light on the conditions on the lower order method which are sufficient (and sometimes necessary) to obtain the optimal order of accuracy. For the one-dimensional heat equation we construct a family of numerical methods which are contractive in the maximum norm for all values of the discretization parameters. We also present numerical examples to illustrate our results. Received: May 2002 / Accepted: January 2003     

Working Memory Capacity and the Antisaccade Task: Individual Differences in Voluntary Saccade Control.

Performance on antisaccade trials requires the inhibition of a prepotent response (i.e., don't look at the flashing cue) and the generation and execution of a correct saccade in the opposite direction. The authors attempted to further specify the role of working memory (WM) span differences in the antisaccade task. They tested high- and low-span individuals on variants of prosaccade and antisaccade trials in which an eye movement is the sole requirement. In 3 experiments, they demonstrated the importance of WM span differences in both suppression of a reflexive saccade and generation of a volitional eye movement. The results support the contention that individual differences in WM span are not exclusively due to differences in inhibition but also reflect differences in directing the focus of attention. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A sorter-based architecture for a parallel implementation of communication intensive algorithms

This paper deals with the parallel execution of algorithms with global and/or irregular data dependencies on a regularly and locally connected processor array. The associated communication problems are solved by the use of a two-dimensional sorting algorithm. The proposed architecture, which is based on a two-dimensional sorting network, offers a high degree of flexibility and allows an efficient mapping of many irregularly structured algorithms. In this architecture a one-dimensional processor array performs all required control and arithmetic operations, whereas the sorter solves complex data transfer problems. The storage capability of the sorting network is also used as memory for data elements. The algorithms for sparse matrix computations, fast Fourier transformation and for the convex hull problem, which are mapped onto this architecture, as well as the simulation of a shared-memory computer show that the utilization of the most complex components, the processors, is O(1).     

A confocal microscopic evaluation of the effects of insulin imprinting on the binding of Concanavalin A by Tetrahymena Pyriformis

With confocal microscopy it is possible to study the Concanavalin A (Con A) binding characteristics of the surface and interior of a single cell by viewing optical sections. It was observed in Tetrahymena pyriformis that Con A bound both to the plasma membrane and to intracellular structures. Incubation of cells with a competing sugar a-methylmannopyranoside, decreased binding. Hormonal imprinting with insulin resulted in an increase in binding of Con A to the cell surface and a decrease in intracellular binding. It is possible that the intracellular binding sites may migrate to the plasma membrane.