High-Tc bolometers with silicon-nitride spiderwebsuspension for far-infrared detection

High-Tc GdBa2Cu3O7-δ (GBCO) superconducting transition edge bolometers with operating temperatures near 90 K have been made with both closed silicon-nitride membranes and patterned silicon-nitride (SiN) spiderweb-like suspension structures. As a substrate silicon-on-nitride (SON) wafers are used which are made by fusion bonding of a silicon wafer to a silicon wafer with a silicon-nitride top layer. The resulting monocrystalline silicon top layer on the silicon-nitride membranes enables the epitaxial growth of GBCO. By patterning the silicon-nitride the thermal conductance G is reduced from about 20 to 3 μW/K. The noise of both types of bolometers is dominated by the intrinsic noise from phonon fluctuations in the thermal conductance G. The optical efficiency in the far infrared is about 75% due to a goldblack absorption layer. The noise equivalent power NEP for FIR detection is 1.8 pW/√Hz, and the detectivity D* is 5.4×1010 cm √Hz/W. Time constants are 0.1 and 0.6 s, for the closed membrane and the spiderweb like bolometers respectively. The effective time constant can be reduced with about a factor 3 by using voltage bias. Further reduction necessarily results in an increase of the NEP due to the 1/f noise of the superconductor

Effects of environmental enrichment on behavioral responses to novelty, learning, and memory, and the circadian rhythm in cortisol in growing pigs

Previously we showed that pigs reared in an enriched environment had higher baseline salivary cortisol concentrations during the light period than pigs reared under barren conditions. In the present experiment, it was investigated whether these higher baseline salivary cortisol concentrations were a real difference in cortisol concentration or merely represented a phase difference in circadian rhythm. The effects of different cortisol concentrations on the behavioral responses to novelty and learning and long-term memory in a maze test were also studied in enriched and barren housed pigs. At 9 weeks of age enriched and barren housed pigs did not differ in baseline salivary cortisol concentrations nor in circadian rhythm, but at 22 weeks of age barren housed pigs had a blunted circadian rhythm in salivary cortisol as compared to enriched housed pigs. The differences in baseline salivary cortisol concentrations between enriched- and barren-housed pigs are age-dependent, and become visible after 15 weeks of age. Enriched- and barren-housed piglets did not differ in time spent on exploration in the novel environment test. Barren-housed pigs had an impaired long-term memory in the maze test compared to enriched-housed pigs; however, no differences in learning abilities between enriched- and barren-housed pigs were found. Because blunted circadian cortisol rhythms are often recorded during states of chronic stress in pigs and rats or during depression in humans, it is suggested that the blunted circadian rhythm in cortisol in barren-housed pigs similarily may reflect decreased welfare.

Analysing the effects of travel information on public transport traveller’s decision making and learning

This thesis examines the effect of travel information on a public transport traveller’s decision making over time. It investigates whether the effect of information is sustained over time and is affected by its type and reliability. It is postulated that the traveller will attain better decision outcomes over time, and this process is reinforced when given information. It is postulated that dynamic information would produce the best outcomes, followed by static information and no information. A series of computer-based experiments, in which the participants made hypothetical trips by public bus under various travel information and operating conditions, were conducted. At the aggregate level, the hypothesised relationships are not observed at a statistically significant level. At the disaggregate level, day-to-day decisions are shown to relate significantly to the outcome of the previous day, with the participant more likely to seek a more rewarding but riskier choice if the previous day sees no adverse outcome, and vice-versa. When the information is static, decision changes are few and incremental. When it is dynamic, these changes are more frequent and pronounced, with choices ‘anchored’ around values provided by the information. Nonetheless, a significant proportion of participants made no or few changes, regardless of information or operating conditions. The findings suggest a higher propensity for some travellers to use dynamic information over static information over time, regardless of reliability. On the other hand, those who acquire information do not necessarily maximise their utility, implying that they do so for other less quantifiable factors. The benefits of information provision could also be further circumscribed by the heterogeneity of responses. This set of findings suggests that assuming travellers respond to information in a utility-maximising and homogeneous manner may over-estimate the effect of information

Low noise far-infrared detection at 90 K using high-T(c) superconducting bolometers with silicon-nitride beam suspension

High-T(c) GdBa2Cu3O7-d (GBCO) superconducting transition edge bolometers with operating temperatures near 90 K and receiving area of 1 mm2 have been made with both closed silicon-nitride membranes and patterned silicon-nitride (Si(x)N(y)) spiderweb-like suspension structures. To enable epitaxial growth of the GBCO layer, a thin monocrystalline Si layer is prepared on the silicon-nitride base, using fusion bonding techniques. By pattering the silicon-nitride supporting membrane the thermal conductance G is reduced from 20 to 3.5 μW/K. The noise of both types of bolometers is fully dominated by the intrinsic noise from phonon fluctuations in the thermal conductance G. The optical efficiency in the far infrared is about 75% due to a gold black absorption layer. The optical noise equivalent power (NEP) is 1.8 pW/√Hz, and the detectivity D* is 5.4x1010 cm√Hz/W. Time constants are 0.1 and 0.6 s, for the closed membrane and the spiderweb like bolometers respectively. We have observed an empirical limit for the NEP for this type of bolometers. The effective timeconstant can be reduced with a factor of 3 by using an electronic feedback system or by using voltage bias. A further reduction necessarily results in an increase of the NEP due to the 1/f noise of the superconductor

Natural variation in stomata size contributes to the local adaptation of water-use efficiency in Arabidopsis thaliana

Stomata control gas exchanges between the plant and the atmosphere. How natural variation in stomata size and density contributes to resolve trade-offs between carbon uptake and water loss in response to local climatic variation is not yet understood. We developed an automated confocal microscopy approach to characterize natural genetic variation in stomatal patterning in 330 fully sequenced Arabidopsis thaliana accessions collected throughout the European range of the species. We compared this to variation in water-use efficiency, measured as carbon isotope discrimination (C-13). We detect substantial genetic variation for stomata size and density segregating within Arabidopsis thaliana. A positive correlation between stomata size and C-13 further suggests that this variation has consequences on water-use efficiency. Genome wide association analyses indicate a complex genetic architecture underlying not only variation in stomatal patterning but also to its covariation with carbon uptake parameters. Yet, we report two novel QTL affecting C-13 independently of stomatal patterning. This suggests that, in A. thaliana, both morphological and physiological variants contribute to genetic variance in water-use efficiency. Patterns of regional differentiation and covariation with climatic parameters indicate that natural selection has contributed to shape some of this variation, especially in Southern Sweden, where water availability is more limited in spring relative to summer. These conditions are expected to favour the evolution of drought avoidance mechanisms over drought escape strategies

Single plane-wave imaging using physics-based deep learning

In plane-wave imaging, multiple unfocused ultrasound waves are transmitted into a medium of interest from different angles and an image is formed from the recorded reflections. The number of plane waves used leads to a tradeoff between frame-rate and image quality, with single-plane-wave (SPW) imaging being the fastest possible modality with the worst image quality. Recently, deep learning methods have been proposed to improve ultrasound imaging. One approach is to use image-to-image networks that work on the formed image and another is to directly learn a mapping from data to an image. Both approaches utilize purely data-driven models and require deep, expressive network architectures, combined with large numbers of training samples to obtain good results. Here, we propose a data-to-image architecture that incorporates a wave-physics-based image formation algorithm in-between deep convolutional neural networks. To achieve this, we implement the Fourier (FK) migration method as network layers and train the whole network end-to-end. We compare our proposed data-to-image network with an image-to-image network in simulated data experiments, mimicking a medical ultrasound application. Experiments show that it is possible to obtain high-quality SPW images, almost similar to an image formed using 75 plane waves over an angular range of ±16°. This illustrates the great potential of combining deep neural networks with physics-based image formation algorithms for SPW imaging