Quadrature frequency resolved spectroscopy of upconversion photoluminescence in GeGaS:Er<Superscript>3+</Superscript>; II. elucidating excitation mechanisms of red emission besides green emission

The paper addresses the quadrature frequency resolved spectroscopy (QFRS) on the red (⁴ F _9/2 → ⁴ I _15/2) upconverted photoluminescence (UCPL) as well as the green (⁴ S _3/2 → ⁴ I _15/2) UCPL of Er³⁺ in GeGaS chalcogenide glasses at the pump wavelength 975 nm. On the basis of the perturbed rate equations for the generally accepted 5-level model of the green and red UCPLs of Er³⁺, we have derived the formulas for the QFRS on the green and red UCPLs of the two differently Er-doped samples. Adopting the respective formulas as model functions for the nonlinear regressions on the QFRS data of both the UCPLs, we have determined the relevant parameters such as relaxation rates at the four excited levels, the excited absorption cross section and energy transfer parameters. Thereby the differences of UCPL dynamics between the green and red UCPLs as well as between the two differently Er-doped Ge₂₅Ga₁₀S₆₅ samples are interpreted in terms of the determined parameters.     

Automated delineation of individual tree crowns in high spatial resolution aerial images by multiple-scale analysis

This paper presents an automatic multiple-scale algorithm for delineation of individual tree crowns in high spatial resolution infrared colour aerial images. The tree crown contours were identified as zero-crossings, with convex grey-level curvature, which were computed on the intensity image for each image scale. A modified centre of curvature was estimated for every edge segment pixel. For each segment, these centre points formed a swarm which was modelled as a primal sketch using an ellipse extended with the mean circle of curvature. The model described the region of the derived tree crown based on the edge segment at the current scale. The sketch was rescaled with a significance value and accumulated for a scale interval. In the accumulated sketch, a tree crown segment was grown, starting at local peaks, under the condition that it was inside the area of healthy vegetation in the aerial image and did not trespass into a neighbouring crown segment. The method was evaluated by comparison with manual delineation and with ground truth on 43 randomly selected sample plots. It was concluded that the performance of the method is almost equivalent to visual interpretation. On the average, seven out of ten tree crowns were the same. Furthermore, ground truth indicated a large number of hidden trees. The proposed technique could be used as a basic tool in forest surveys. Received: 24 June 1997 / Accepted: 28 April 1998     

Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions

In this article, six individual tree crown (ITC) detection/delineation algorithms are evaluated, using an image data set containing six diverse forest types at different geographical locations in three European countries. The algorithms use fundamentally different techniques, including local maxima detection, valley following (VF), region-growing (RG), template matching (TM), scale-space (SS) theory and techniques based on stochastic frameworks. The structurally complexity of the forests in the aerial images used ranges from a homogeneous plantation and an area with isolated tree crowns to an extremely dense deciduous forest type. None of the algorithms alone could successfully analyse all different cases. The study shows that it is important to partition the imagery into homogeneous forest stands prior to the application of individual tree detection algorithms. It furthermore suggests a need for a common, publicly available suite of test images and common test procedures for evaluation of individual tree detection/delineation algorithms. Finally, it highlights that, for complex forest types, monoscopic images are insufficient for consistent tree crown detection, even by human interpreters.     

A highly sensitive NO2-selective optode membrane

A new NO₂-sensitive polymeric optode membrane is introduced. It takes advantage of the reactivity of NO₂ with an aquacyanocobalt(III)-cobyrinate derivative. The detection mechanism leads to a protonation of the Nile Blue derivative ETH 5418, which changes its visible spectrum thereby. The polymer layer also contains the aquacyanocobalt(III)-cobyrinate derivative, which significantly reduces the response time and improves the operational lifetime of the sensor compared to a blank membrane. No cross-sensitivity to NO, CO, CO₂ and only a small interference by SO₂ was observed.

A large variety of polymers and plasticizers were tested in order to achieve resistance to high temperature and to improve the lifetime of the sensor. Until now, the plasticized poly(vinylchloride) membranes still remain the material of choice in view of a good compromise between stability, response time and solubility of components.     

Exploiting Visibility Correlation in Direct Illumination

The visibility function in direct illumination describes the binary visibility over a light source, e.g., an environment map. Intuitively, the visibility is often strongly correlated between nearby locations in time and space, but exploiting this correlation without introducing noticeable errors is a hard problem. In this paper, we first study the statistical characteristics of the visibility function. Then, we propose a robust and unbiased method for using estimated visibility information to improve the quality of Monte Carlo evaluation of direct illumination. Our method is based on the theory of control variates, and it can be used on top of existing state‐of‐the‐art schemes for importance sampling. The visibility estimation is obtained by sparsely sampling and caching the 4D visibility field in a compact bitwise representation. In addition to Monte Carlo rendering, the stored visibility information can be used in a number of other applications, for example, ambient occlusion and lighting design.     

The State of the Art in Mobile Graphics Research

High-quality computer graphics let mobile-device users access more compelling content. Still, the devices' limitations and requirements differ substantially from those of a PC. This survey of mobile graphics research describes current solutions in terms of specialized hardware (including 3D displays), rendering and transmission, visualization, and user interfaces.     

Modeling and estimating the subjects’ diversity of opinions in video quality assessment: a neural network based approach

Subjective experiments are considered the most reliable way to assess the perceived visual quality. However, observers’ opinions are characterized by large diversity: in fact, even the same observer is often not able to exactly repeat his first opinion when rating again a given stimulus. This makes the Mean Opinion Score (MOS) alone, in many cases, not sufficient to get accurate information about the perceived visual quality. To this aim, it is important to have a measure characterizing to what extent the observed or predicted MOS value is reliable and stable. For instance, the Standard deviation of the Opinions of the Subjects (SOS) could be considered as a measure of reliability when evaluating the quality subjectively. However, we are not aware of the existence of models or algorithms that allow to objectively predict how much diversity would be observed in subjects’ opinions in terms of SOS. In this work we observe, on the basis of a statistical analysis made on several subjective experiments, that the disagreement between the quality as measured by means of different objective video quality metrics (VQMs) can provide information on the diversity of the observers’ ratings on a given processed video sequence (PVS). In light of this observation we: i) propose and validate a model for the SOS observed in a subjective experiment; ii) design and train Neural Networks (NNs) that predict the average diversity that would be observed among the subjects’ ratings for a PVS starting from a set of VQMs values computed on such a PVS; iii) give insights into how the same NN based approach can be used to identify potential anomalies in the data collected in subjective experiments.

     

Maternal and stock effects on egg-size variation among walleye Sander vitreus stocks from the Great Lakes region

Fish egg sizes vary intra-specifically among stocks and individuals, and such variation may reflect a combination of maternal and environmental influences. As egg size variation has important implications for individual and population recruitment success, it is useful to quantify egg-size variation and identify potential factors underlying such variation. We evaluated 1) within-stock maternal influences on egg size and 2) the relative elucidatory power of maternal effects versus stock in explaining inter-individual mean egg size based on eggs collected during 2007–2008 from five walleye Sander vitreus stocks in the North American Laurentian Great Lakes region. We used both linear regression models and classification and regression trees (CART) to describe egg-size variation. Egg size tended to increase with female length and for some stocks was greatest for intermediate maternal ages. However, maternal influences on egg size were relatively low and variable between years. In contrast, stock had a stronger effect; walleye egg-size variation was greater among stocks than within stocks. After controlling for the influence of maternal age and length, we found that egg size was relatively small for fish spawning in Maumee and Sandusky Rivers (western Lake Erie), intermediate in Oneida Lake and Tittabawassee River (Saginaw Bay, Lake Huron), and relatively large in Van Buren Bay (eastern Lake Erie) and Little Bay de Noc (northern Green Bay, Lake Michigan). Such inter-stock differences in maternal influence adjusted egg size appeared to be negatively associated with a system's productivity; suggesting a potential adaptive response of egg size to early life habitat conditions.     

High-performance secure multi-party computation for data mining applications

Secure multi-party computation (MPC) is a technique well suited for privacy-preserving data mining. Even with the recent progress in two-party computation techniques such as fully homomorphic encryption, general MPC remains relevant as it has shown promising performance metrics in real-world benchmarks. Sharemind is a secure multi-party computation framework designed with real-life efficiency in mind. It has been applied in several practical scenarios, and from these experiments, new requirements have been identified. Firstly, large datasets require more efficient protocols for standard operations such as multiplication and comparison. Secondly, the confidential processing of financial data requires the use of more complex primitives, including a secure division operation. This paper describes new protocols in the Sharemind model for secure multiplication, share conversion, equality, bit shift, bit extraction, and division. All the protocols are implemented and benchmarked, showing that the current approach provides remarkable speed improvements over the previous work. This is verified using real-world benchmarks for both operations and algorithms.     

Ca2+ Signalling Induced by NGF Identifies a Subset of Capsaicin-Excitable Neurons Displaying Enhanced Chemo-Nociception in Dorsal Root Ganglion Explants from Adult pirt-GCaMP3 Mouse

Nociceptors sense hazards via plasmalemmal cation channels, including transient receptor potential vanilloid 1 (TRPV1). Nerve growth factor (NGF) sensitises TRPV1 to capsaicin (CAPS), modulates nociceptor excitability and induces thermal hyperalgesia, but cellular mechanisms remain unclear. Confocal microscopy was used to image changes in intracellular Ca²⁺ concentration ([Ca²⁺]_i) across neuronal populations in dorsal root ganglia (DRG) explants from pirt-GCaMP3 adult mice, which express a fluorescent reporter in their sensory neurons. Raised [Ca²⁺]_i was detected in 84 neurons of three DRG explants exposed to NGF (100 ng/mL) and most (96%) of these were also excited by 1 μM CAPS. NGF elevated [Ca²⁺]_i in about one-third of the neurons stimulated by 1 μM CAPS, whether applied before or after the latter. In neurons excitable by NGF, CAPS-evoked [Ca²⁺]_i signals appeared significantly sooner (e.g., respective lags of 1.0 ± 0.1 and 1.9 ± 0.1 min), were much (>30%) brighter and lasted longer (6.6 ± 0.4 vs. 3.9 ± 0.2 min) relative to those non-responsive to the neurotrophin. CAPS tachyphylaxis lowered signal intensity by ~60% but was largely prevented by NGF. Increasing CAPS from 1 to 10 μM nearly doubled the number of cells activated but only modestly increased the amount co-activated by NGF. In conclusion, a sub-population of the CAPS-sensitive neurons in adult mouse DRG that can be excited by NGF is more sensitive to CAPS, responds with stronger signals and is further sensitised by transient exposure to the neurotrophin.