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"Hamilton, Scott A"
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Analysis of Limiting Factors Across the Life Cycle of Delta Smelt (Hypomesus transpacificus)
AbstractWe developed a mechanistic life-cycle model derived from the elicitation of multiple factors influencing the success of individual life-stages of the imperiled delta smelt (Hypomesus transpacificus). We discuss the relevance of limiting factors in population ecology and problems with additive models in detecting them. We identify limiting factors and assess their significance using a non-linear optimization routine, combined with traditional metrics to assess the value of covariates and model performance. After reviewing previous conceptual models and multivariate analyses, we identified a set of factors that were consistent with conceptual models and useful in explaining the erratic fluctuations in a common abundance index: food at certain times in certain locations, predation by introduced species primarily in the spring, and entrainment. The analytical approach provides a transparent and intuitive framework in which to consider the contribution of covariates and consequences for population trends, and has the potential to assist with the evaluation of proposed recovery measures.
Journal Article
MRI profile and response to endovascular reperfusion after stroke (DEFUSE 2): a prospective cohort study
Whether endovascular stroke treatment improves clinical outcomes is unclear because of the paucity of data from randomised placebo-controlled trials. We aimed to establish whether MRI can be used to identify patients who are most likely to benefit from endovascular reperfusion.
In this prospective cohort study we consecutively enrolled patients scheduled to have endovascular treatment within 12 h of onset of stroke at eight centres in the USA and one in Austria. Aided by an automated image analysis computer program, investigators interpreted a baseline MRI scan taken before treatment to establish whether the patient had an MRI profile (target mismatch) that suggested salvageable tissue was present. Reperfusion was assessed on an early follow-up MRI scan (within 12 h of the revascularisation procedure) and defined as a more than 50% reduction in the volume of the lesion from baseline on perfusion-weighted MRI. The primary outcome was favourable clinical response, defined as an improvement of 8 or more on the National Institutes of Health Stroke Scale between baseline and day 30 or a score of 0–1 at day 30. The secondary clinical endpoint was good functional outcome, defined as a modified Rankin scale score of 2 or less at day 90. Analyses were adjusted for imbalances in baseline predictors of outcome. Investigators assessing outcomes were masked to baseline data.
138 patients were enrolled. 110 patients had catheter angiography and of these 104 had an MRI profile and 99 could be assessed for reperfusion. 46 of 78 (59%) patients with target mismatch and 12 of 21 (57%) patients without target mismatch had reperfusion after endovascular treatment. The adjusted odds ratio (OR) for favourable clinical response associated with reperfusion was 8·8 (95% CI 2·7–29·0) in the target mismatch group and 0·2 (0·0–1·6) in the no target mismatch group (p=0·003 for difference between ORs). Reperfusion was associated with increased good functional outcome at 90 days (OR 4·0, 95% CI 1·3–12·2) in the target mismatch group, but not in the no target mismatch group (1·9, 0·2–18·7).
Target mismatch patients who had early reperfusion after endovascular stroke treatment had more favourable clinical outcomes. No association between reperfusion and favourable outcomes was present in patients without target mismatch. Our data suggest that a randomised controlled trial of endovascular treatment for patients with the target mismatch profile is warranted.
National Institute for Neurological Disorders and Stroke.
Journal Article
Time to treatment with intravenous alteplase and outcome in stroke: an updated pooled analysis of ECASS, ATLANTIS, NINDS, and EPITHET trials
Early administration of intravenous recombinant tissue plasminogen activator (rt-PA) after ischaemic stroke improves outcome. Previous analysis of combined data from individual patients suggested potential benefit beyond 3 h from stroke onset. We re-examined the effect of time to treatment with intravenous rt-PA (alteplase) on therapeutic benefit and clinical risk by adding recent trial data to the analysis.
We added data from ECASS III (821 patients) and EPITHET (100 patients) to a pool of common data elements from six other trials of alteplase for acute stroke (2775 patients). We used multivariate logistic regression to assess the relation of stroke onset to start of treatment (OTT) with treatment on favourable 3-month outcome (defined as modified Rankin score 0–1), mortality, and occurrence and outcome of clinically relevant parenchymal haemorrhage. The presence of an arterial occlusion was inferred from the patient's symptoms and absence of haemorrhage or other causes of ischaemic stroke. Vascular imaging was not a requirement in the trials. All patients with confirmed OTT within 360 min were included in the analysis.
Treatment was started within 360 min of stroke onset in 3670 patients randomly allocated to alteplase (n=1850) or to placebo (n=1820). Odds of a favourable 3-month outcome increased as OTT decreased (p=0·0269) and no benefit of alteplase treatment was seen after around 270 min. Adjusted odds of a favourable 3-month outcome were 2·55 (95% CI 1·44–4·52) for 0–90 min, 1·64 (1·12–2·40) for 91–180 min, 1·34 (1·06–1·68) for 181–270 min, and 1·22 (0·92–1·61) for 271–360 min in favour of the alteplase group. Large parenchymal haemorrhage was seen in 96 (5·2%) of 1850 patients assigned to alteplase and 18 (1·0%) of 1820 controls, with no clear relation to OTT (p=0·4140). Adjusted odds of mortality increased with OTT (p=0·0444) and were 0·78 (0·41–1·48) for 0–90 min, 1·13 (0·70–1·82) for 91–180 min, 1·22 (0·87–1·71) for 181–270 min, and 1·49 (1·00–2·21) for 271–360 min.
Patients with ischaemic stroke selected by clinical symptoms and CT benefit from intravenous alteplase when treated up to 4·5 h. To increase benefit to a maximum, every effort should be taken to shorten delay in initiation of treatment. Beyond 4·5 h, risk might outweigh benefit.
None.
Journal Article
Delocalized Photonic Deep Learning on the Internet's Edge
Advances in deep neural networks (DNNs) are transforming science and technology. However, the increasing computational demands of the most powerful DNNs limit deployment on low-power devices, such as smartphones and sensors -- and this trend is accelerated by the simultaneous move towards Internet-of-Things (IoT) devices. Numerous efforts are underway to lower power consumption, but a fundamental bottleneck remains due to energy consumption in matrix algebra, even for analog approaches including neuromorphic, analog memory and photonic meshes. Here we introduce and demonstrate a new approach that sharply reduces energy required for matrix algebra by doing away with weight memory access on edge devices, enabling orders of magnitude energy and latency reduction. At the core of our approach is a new concept that decentralizes the DNN for delocalized, optically accelerated matrix algebra on edge devices. Using a silicon photonic smart transceiver, we demonstrate experimentally that this scheme, termed Netcast, dramatically reduces energy consumption. We demonstrate operation in a photon-starved environment with 40 aJ/multiply of optical energy for 98.8% accurate image recognition and <1 photon/multiply using single photon detectors. Furthermore, we show realistic deployment of our system, classifying images with 3 THz of bandwidth over 86 km of deployed optical fiber in a Boston-area fiber network. Our approach enables computing on a new generation of edge devices with speeds comparable to modern digital electronics and power consumption that is orders of magnitude lower.
Paper
The effect of aggregate response assumptions on environmental impact analyses
Extract: This paper reports on an investigation of the implications of alternative response assumptions on the estimates of changes in welfare, prices, and production due to environmental alterations. A variety of aggregate response assumptions are examined within a mathematical programming framework using a case example assessment involving the economic effects of air quality changes on agriculture. This type of empirical research is used by the U.S. Environmental Protection Agency (EPA) to evaluate the efficiency of alternative national ambient air quality standards, including acid deposition precursors. Benefits to agriculture are an important category in setting such standards
Journal Article
High-rate field demonstration of large-alphabet quantum key distribution
Quantum key distribution (QKD) exploits the quantum nature of light to share provably secure keys, allowing secure communication in the presence of an eavesdropper. The first QKD schemes used photons encoded in two states, such as polarization. Recently, much effort has turned to large-alphabet QKD schemes, which encode photons in high-dimensional basis states. Compared to binary-encoded QKD, large-alphabet schemes can encode more secure information per detected photon, boosting secure communication rates, and also provide increased resilience to noise and loss. High-dimensional encoding may also improve the efficiency of other quantum information processing tasks, such as performing Bell tests and implementing quantum gates. Here, we demonstrate a large-alphabet QKD protocol based on high-dimensional temporal encoding. We achieve record secret-key rates and perform the first field demonstration of large-alphabet QKD. This demonstrates a new, practical way to optimize secret-key rates and marks an important step towards transmission of high-dimensional quantum states in deployed networks.
Paper