Vegetable

Human life under Queen Victoria was built on—or, more accurately, with—vegetables, from sugarcane, tea, and spices to cotton and indigo, tobacco and opium poppies. While the intricate and multiple economies of some of these vegetable staples have been explored in considerable detail, the highly uneven power dynamics of the Victorians’ complex, drawn-out encounters with the vegetable world mostly continue to be glossed over in simplistic terms of human appropriation and control. This essay proposes “vegetable” as a heuristic for critically engaging plants and other nonanimal growy things as sources of action in Victorianist scholarship. Drawing on thinking from the interdisciplinary field of critical plant studies, I argue that human life and ideas cannot be thought apart from vegetable materialities, especially during the Victorian period. The high degree to which human history was entangled in the vegetable world, I suggest, renders a “vegetable” heuristic indispensable to Victorianist scholarship, especially in the struggle to come to terms with its imperial inheritance

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Prompt Generation Networks for Input-based Adaptation of Frozen Vision Transformers

With the introduction of the transformer architecture in computer vision, increasing model scale has been demonstrated as a clear path to achieving performance and robustness gains. However, with model parameter counts reaching the billions, classical finetuning approaches are becoming increasingly limiting and even unfeasible when models become hosted as inference APIs, as in NLP. To this end, visual prompt learning, whereby a model is adapted by learning additional inputs, has emerged as a potential solution for adapting frozen and cloud-hosted models: During inference, this neither requires access to the internals of models' forward pass function, nor requires any post-processing. In this work, we propose the Prompt Generation Network (PGN) that generates high performing, input-dependent prompts by sampling from an end-to-end learned library of tokens. We further introduce the "prompt inversion" trick, with which PGNs can be efficiently trained in a latent space but deployed as strictly input-only prompts for inference. We show the PGN is effective in adapting pre-trained models to various new datasets: It surpasses previous methods by a large margin on 12/12 datasets and even outperforms full-finetuning on 5/12, while requiring 100x less parameters.Comment: Tech report, 12 pages. Code: https://github.com/jochemloedeman/PG

Climate model variability leads to uncertain predictions of the future abundance of stream macroinvertebrates

Climate change has the potential to alter the flow regimes of rivers and consequently affect the taxonomic and functional diversity of freshwater organisms. We modeled future flow regimes for the 2050 and 2090 time horizons and tested how flow regimes impact the abundance of 150 macroinvertebrate species and their functional trait compositions in one lowland river catchment (Treene) and one mountainous river catchment (Kinzig) in Europe. We used all 16 global circulation models (GCMs) and regional climate models (RCMs) of the CORDEX dataset under the RCP 8.5 scenario to calculate future river flows. The high variability in relative change of flow among the 16 climate models cascaded into the ecological models and resulted in substantially different predicted abundance values for single species. This variability also cascades into any subsequent analysis of taxonomic or functional freshwater biodiversity. Our results showed that flow alteration effects are different depending on the catchment and the underlying species pool. Documenting such uncertainties provides a basis for the further assessment of potential climate-change impacts on freshwater taxa distributions

Surface wave control for large arrays of microwave kinetic inductance detectors

Large ultra-sensitive detector arrays are needed for present and future observatories for far infra-red, submillimeter wave (THz), and millimeter wave astronomy. With increasing array size, it is increasingly important to control stray radiation inside the detector chips themselves, the surface wave. We demonstrate this effect with focal plane arrays of 880 lens-antenna coupled Microwave Kinetic Inductance Detectors (MKIDs). Presented here are near field measurements of the MKID optical response versus the position on the array of a reimaged optical source. We demonstrate that the optical response of a detector in these arrays saturates off-pixel at the $\sim-30$ dB level compared to the peak pixel response. The result is that the power detected from a point source at the pixel position is almost identical to the stray response integrated over the chip area. With such a contribution, it would be impossible to measure extended sources, while the point source sensitivity is degraded due to an increase of the stray loading. However, we show that by incorporating an on-chip stray light absorber, the surface wave contribution is reduced by a factor $>$10. With the on-chip stray light absorber the point source response is close to simulations down to the $\sim-35$ dB level, the simulation based on an ideal Gaussian illumination of the optics. In addition, as a crosscheck we show that the extended source response of a single pixel in the array with the absorbing grid is in agreement with the integral of the point source measurements.Comment: accepted for publication in IEEE Transactions on Terahertz Science and Technolog

What influences students' peer-feedback uptake? Relations between error tolerance, feedback tolerance, writing self-efficacy, perceived language skills and peer-feedback processing

This study investigated the extent to which the uptake of peer-feedback of 10th grade students (N = 160, age range = 15–16) related to intrapersonal factors (error tolerance, feedback tolerance, and writing self-efficacy) and interpersonal factors (feedback provider's language skills, as perceived by the feedback recipient). Two groups of students received similar feedback on their writing performance, provided by trained research-assistants. Half the students was led to believe that feedback was provided by a peer perceived to have stronger language skills than their own, whereas the other half was led to believe that feedback was provided by a peer perceived to have weaker language skills than their own. Results showed that (1) error tolerance was related to feedback tolerance, (2) perceived language skills of the feedback provider positively related to the uptake of peer-feedback on writing style, and (3) error tolerance, feedback tolerance, and writing self-efficacy did not relate to peer-feedback uptake. These results emphasize the central role of errors in peer-feedback processing and they imply that the importance of interpersonal factors should not be overlooked when predicting or explaining peer-feedback uptake

Eliminating stray radiation inside large area imaging arrays

With increasing array size, it is increasingly important to control stray radiation inside the detector chips themselves. We demonstrate this effect with focal plane arrays of absorber coupled Lumped Element microwave Kinetic Inductance Detectors (LEKIDs) and lens-antenna coupled distributed quarter wavelength Microwave Kinetic Inductance Detectors (MKIDs). In these arrays the response from a point source at the pixel position is at a similar level to the stray response integrated over the entire chip area. For the antenna coupled arrays, we show that this effect can be suppressed by incorporating an on-chip stray light absorber. A similar method should be possible with the LEKID array, especially when they are lens coupled.Comment: arXiv admin note: substantial text overlap with arXiv:1707.0214