3,178 research outputs found

    Functional testing of ASICs designed with hardware description languages

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    Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 99).by Richard Davis.M.Eng

    Effects of rapid decompression and exposure to bright light on visual function in black rockfish (Sebastes melanops) and Pacific halibut (Hippoglossus stenolepis)

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    Demersal fishes hauled up from depth experience rapid decompression. In physoclists, this can cause overexpansion of the swim bladder and resultant injuries to multiple organs (barotrauma), including severe exophthalmia (“pop-eye”). Before release, fishes can also be subjected to asphyxia and exposure to direct sunlight. Little is known, however, about possible sensory deficits resulting from the events accompanying capture. To address this issue, electroretinography was used to measure the changes in retinal light sensitivity, flicker fusion frequency, and spectral sensitivity in black rockfish (Sebastes melanops) subjected to rapid decompression (from 4 atmospheres absolute [ATA] to 1 ATA) and Pacific halibut (Hippoglossus stenolepis) exposed to 15 minutes of simulated sunlight. Rapid decompression had no measurable influence on retinal function in black rockfish. In contrast, exposure to bright light significantly reduced retinal light sensitivity of Pacific halibut, predominately by affecting the photopigment which absorbs the green wavelengths of light (≈520–580 nm) most strongly. This detriment is likely to have severe consequences for postrelease foraging success in green-wavelength-dominated coastal waters. The visual system of Pacific halibut has characteristics typical of species adapted to low light environments, and these characteristics may underlie their vulnerability to injury from exposure to bright light

    A multi-wavelength study of the microwave emission in the Perseus molecular cloud

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    Cosmic Microwave Background (CMB) anisotropy measurements have provided a great insight to the cosmological parameters that define our Universe. Obtaining these measurements to ever higher sensitivity is complicated by the presence of contaminating foregrounds, whose physical understanding is, therefore, critical. The discovery of a dust-correlated emission mechanism in the frequency range 10-100 GHz, known an anomalous microwave emission, has reignited the study of Galactic foregrounds as interstellar medium (ISM) emission mechanisms. This thesis describes the investigation of this anomalous microwave emission, with the aim of improving our understanding of the physical processes causing this emission. Understanding the precise nature and spectral behaviour of this anomalous microwave emission is of critical importance for modelling Galactic foregrounds for current and future sensitive CMB anisotropy experiments (e.g. Planck).Very Small Array (VSA) observations of the dust feature, G159.6-18.5, in the Perseus molecular complex are presented. These observations were reduced and calibrated resulting in the production of a 33 GHz map of the region with ≈7 arcmin angular resolution and an r.m.s. noise level of 88 %) appears to be originating from a large-scale, diffuse component, and is not concentrated in the five compact components.Having detected this anomalous emission, which is consistent with the spinning dust hypothesis, photometric Spitzer data were completely reprocessed and used in conjunction with the dust emission model, DUSTEM, to characterise the dust within the region. The results of this dust characterisation are presented and were found to tentatively agree with the spinning dust hypothesis.Finally, this work provides evidence illustrating that anomalous emission is a very complex process, and that further work still needs to be performed.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Combination CD200R/PD-1 blockade in a humanised mouse model

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    There is an increasing number of immune-checkpoint inhibitors being developed and approved for cancer immunotherapy. Most of the new therapies aim to reactivate tumour-infiltrating T cells, which are responsible for tumour killing. However, in many tumours, the most abundant infiltrating immune cells are macrophages and myeloid cells, which can be tumour-promoting as well as tumouricidal. CD200R was initially identified as a myeloid-restricted, inhibitory immune receptor, but was subsequently also found to be expressed within the lymphoid lineage. Using a mouse model humanised for CD200R and PD-1, we investigated the potential of a combination therapy comprising nivolumab, a clinically approved PD-1 blocking antibody, and OX108, a CD200R antagonist. We produced nivolumab as a murine IgG1 antibody and validated its binding activity in vitro as well as ex vivo. We then tested the combination therapy in the immunogenic colorectal cancer model MC38 as well as the PD-1 blockade-resistant lung cancer model LLC1, which is characterised by a large number of infiltrating myeloid cells, making it an attractive target for CD200R blockade. No significant improvement of overall survival was found in either model, compared to nivolumab mIgG1 monotherapy. There was a trend for more complete responses in the MC38 model, but investigation of the infiltrating immune cells failed to account for this. Importantly, MC38 cells expressed low levels of CD200, whereas LLC1 cells were CD200-negative. Further investigation of CD200R-blocking antibodies in tumours expressing high levels of CD200 could be warranted

    CLIMB: Curriculum Learning for Infant-inspired Model Building

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    We describe our team's contribution to the STRICT-SMALL track of the BabyLM Challenge. The challenge requires training a language model from scratch using only a relatively small training dataset of ten million words. We experiment with three variants of cognitively-motivated curriculum learning and analyze their effect on the performance of the model on linguistic evaluation tasks. In the vocabulary curriculum, we analyze methods for constraining the vocabulary in the early stages of training to simulate cognitively more plausible learning curves. In the data curriculum experiments, we vary the order of the training instances based on i) infant-inspired expectations and ii) the learning behavior of the model. In the objective curriculum, we explore different variations of combining the conventional masked language modeling task with a more coarse-grained word class prediction task to reinforce linguistic generalization capabilities. Our results did not yield consistent improvements over our own non-curriculum learning baseline across a range of linguistic benchmarks; however, we do find marginal gains on select tasks. Our analysis highlights key takeaways for specific combinations of tasks and settings which benefit from our proposed curricula. We moreover determine that careful selection of model architecture, and training hyper-parameters yield substantial improvements over the default baselines provided by the BabyLM challenge

    CLIMB: Curriculum Learning for Infant-inspired Model Building

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    We describe our team's contribution to the STRICT-SMALL track of the BabyLM Challenge. The challenge requires training a language model from scratch using only a relatively small training dataset of ten million words. We experiment with three variants of cognitively-motivated curriculum learning and analyze their effect on the performance of the model on linguistic evaluation tasks. In the vocabulary curriculum, we analyze methods for constraining the vocabulary in the early stages of training to simulate cognitively more plausible learning curves. In the data curriculum experiments, we vary the order of the training instances based on i) infant-inspired expectations and ii) the learning behavior of the model. In the objective curriculum, we explore different variations of combining the conventional masked language modeling task with a more coarse-grained word class prediction task to reinforce linguistic generalization capabilities. Our results did not yield consistent improvements over our own non-curriculum learning baseline across a range of linguistic benchmarks; however, we do find marginal gains on select tasks. Our analysis highlights key takeaways for specific combinations of tasks and settings which benefit from our proposed curricula. We moreover determine that careful selection of model architecture, and training hyper-parameters yield substantial improvements over the default baselines provided by the BabyLM challenge

    Immune Checkpoints as Therapeutic Targets in Autoimmunity

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    Antibodies that block the immune checkpoint receptors PD1 and CTLA4 have revolutionized the treatment of melanoma and several other cancers, but in the process, a new class of drug side effect has emerged—immune related adverse events. The observation that therapeutic blockade of these inhibitory receptors is sufficient to break self-tolerance, highlights their crucial role in the physiological modulation of immune responses. Here, we discuss the rationale for targeting immune checkpoint receptors with agonistic agents in autoimmunity, to restore tolerance when it is lost. We review progress that has been made to date, using Fc-fusion proteins, monoclonal antibodies or other novel constructs to induce immunosuppressive signaling through these pathways. Finally, we explore potential mechanisms by which these receptors trigger and modulate immune cell function, and how understanding these processes might shape the design of more effective therapeutic agents in future
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