Solutions of the general equations for the radiation dose dependence of the molecular weights of irradiated polymers with an initial Schulz-Zimm distribution

Summary The general equations for the radiation dose dependence of irradiated polymer molecular weights have been solved exactly. For an initial most probable molecular weight distribution (=1), the solutions are analytical and exact. For the general case (1) the solutions are numerical and exact. The present approach has resulted in the solutions for both =1 and 1 being incorporated into a group of FORTRAN computer programs which will solve experimental data for scission and crosslinking yields by both minimization and exact treatments. Simulated data treated using these FORTRAN programs are give. The FORTRAN programs are available from the authors.     

Solvent interactions with n ring systems in proteins

The interaction of water molecules with apolar amino acids isan important aspect of the hydrophobic effect and hence of proteinfolding. Our distributed multipole electrostatic model for waterinteracting with phenylalanine dipeptides shows that minimumenergy sites exist above the aromatic ring such that a solventmolecule can interact with the electrons, but only when thissite is not blocked by mainchain atoms or disturbed by main-chainpolar atoms. This is consistent with the experimental evidenceof others that water can hydrogen bond to aromatic n electrons.In contrast, our analysis of solvent interactions with phenylalanineresidues based on 48 high-resolution, well-refined protein structuresshows that the dominant interaction of solvent molecules iswith the edge of the ring and not with the 7i electrons. Asthe faces of phenylalanine rings tend to be buried, and solventinteractions with neighbouring polar atoms are more favourable,the interaction of water molecules with the faces of aromatic rings appears not to occur frequently in proteins     

High Figure of Merit (FOM) of Bragg Modes in Au‐Coated Nanodisk Arrays for Plasmonic Sensing

Gold‐coated nanodisk arrays of nearly micron periodicity are reported that have high figure of merit (FOM) and sensitivity necessary for plasmonic refractometric sensing, with the added benefit of suitability for surface‐enhanced Raman scattering (SERS), large‐scale microfabrication using standard photolithographic techniques and a simple instrumental setup. Gold nanodisk arrays are covered with a gold layer to excite the Bragg modes (BM), which are the propagative surface plasmons localized by the diffraction from the disk array. This generates surface‐guided modes, localized as standing waves, leading to highly confined fields confirmed by a mapping of the SERS intensity and numerical simulations with 3D finite element method. The optimal gold‐coated nanodisk arrays are applied for refractometric sensing in transmission spectroscopy with better performance than nanohole arrays and they are integrated to a 96‐well plate reader for detection of IgY proteins in the nanometer range in PBS. The potential for sensing in biofluids is assessed with IgG detection in 1:1 diluted urine. The structure exhibits a high FOM of up to 46, exceeding the FOM of structures supporting surface plasmon polaritons and comparable to more complex nanostructures, demonstrating that subwavelength features are not necessary for high‐performance plasmonic sensing.     

Shifting role for human factors in an ‘unmanned’ era

Human factors practitioners (HFPs) play many different roles in the design, creation, operation and maintenance of engineered systems. Less well known are the methods which are aimed at helping with the early stages of design, which are more systems-oriented and often involve questions of the concept of operation in which the engineered system will be fielded. Emerging from the field of cognitive engineering, these methods, including simulation, cognitive work analysis, cognitive task analyses and hierarchical task analysis, will be important as autonomous systems become increasingly capable. Even the most capable systems will continue to interact with humans, and it is at these interfaces between humans and engineered systems that HFP will continue to be needed. This paper describes recent work to leverage these methods to inform concepts of operation in aviation and space, machine learning algorithms and goal-oriented human–machine collaboration.     

Desired concentration-dependent ion exchange for micro-optic lenses

The required concentration-dependent diffusion coefficients for both ideal one-dimensional and ideal radial gradient-index profiles are determined. The modified quasi-chemical diffusion model is used to relate the diffusion coefficient to optimum glass composition. Adding aluminum to sodium silicate glasses facilitates the approach to the desired concentration dependence of the diffusion coefficient for silver-sodium ion exchange. A parabolic one-dimensional index profile is fabricated in one of the glasses. It deviates from ideal values by less than 2%.     

Formal testing for separation assurance

In order to address the rapidly increasing load of air traffic operations, innovative algorithms and software systems must be developed for the next generation air traffic control. Extensive verification of such novel algorithms is key for their adoption by industry. Separation assurance algorithms aim at predicting if two aircraft will get closer to each other than a minimum safe distance; if loss of separation is predicted, they also propose a change of course for the aircraft to resolve this potential conflict. In this paper, we report on our work towards developing an advanced testing framework for separation assurance. Our framework supports automated test case generation and testing, and defines test oracles that capture algorithm requirements. We discuss three different approaches to test-case generation, their application to a separation assurance prototype, and their respective strengths and weaknesses. We also present an approach for statistical analysis of the large numbers of test results obtained from our framework.     

Synthesis of Responsive Motion Using a Dynamic Model

Synthesizing the movements of a responsive virtual character in the event of unexpected perturbations has proven a difficult challenge. To solve this problem, we devise a fully automatic method that learns a nonlinear probabilistic model of dynamic responses from very few perturbed walking sequences. This model is able to synthesize responses and recovery motions under new perturbations different from those in the training examples. When perturbations occur, we propose a physics‐based method that initiates motion transitions to the most probable response example based on the dynamic states of the character. Our algorithm can be applied to any motion sequences without the need for preprocessing such as segmentation or alignment. The results show that three perturbed motion clips can sufficiently generate a variety of realistic responses, and 14 clips can create a responsive virtual character that reacts realistically to external forces in different directions applied on different body parts at different moments in time.     

Estimating the uncertainty of modeled carbon sequestration: The GreenCert™ system

The GreenCert? system was developed to help farm and ranch owners to quantify, standardize, pool and market CO₂ emissions offset (sequestration) credits derived from improved rangeland or cropland management. It combines a user-friendly interface with the CENTURY biogeochemical model, a GIS database of soil and climate parameters, and a Monte Carlo-based uncertainty estimation methodology. This paper focuses on uncertainty treatment, discussing sources of error, parameter distributions, and the Monte Carlo randomization approach, culminating in a sensitivity analysis of model parameters.Idealized crop and grazing scenarios were used to evaluate the uncertainty of modeled soil organic carbon stocks and stock changes stemming from variability in site and management parameters. Normalized sensitivity coefficients and an integrated index for relative sensitivity of the model to the ensemble of the tested variables indicate that environmental factors are the most important in determining the actual size of the soil carbon stock, but that management is a much more important determinant of short- to medium-term carbon fluxes. GreenCert? uses the patented C-LOCK^® approach to efficiently limit uncertainty in the most critical phase of the modelling process by maximizing the use of available management information, and quantifies the remaining uncertainty in an unbiased fashion using Monte Carlo parameter randomization.