170 research outputs found

    The Democratic Idiom: Languages of Democracy in the Chartist Movement

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    On the impact of transport model errors for the estimation of CO2 surface fluxes from GOSAT observations

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    A series of observing system simulation experiments is presented in which column averaged dry air mole fractions of CO2 (XCO2) from the Greenhouse gases Observing SATellite (GOSAT) are made consistent or not with the transport model embedded in a flux inversion system. The GOSAT observations improve the random errors of the surface carbon budget despite the inconsistency. However, we find biases in the inferred surface CO2 budget of a few hundred MtC/a at the subcontinental scale, that are caused by differences of only a few tenths of a ppm between the simulations of the individual XCO2 soundings. The accuracy and precision of the inverted fluxes are little sensitive to an 8-fold reduction in the data density. This issue is critical for any future satellite constellation to monitor XCO2 and should be pragmatically addressed by explicitly accounting for transport errors in flux inversion systems

    Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients

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    Purpose{\bf Purpose}: Earlier work showed that IVIM-NETorig_{orig}, an unsupervised physics-informed deep neural network, was more accurate than other state-of-the-art intravoxel-incoherent motion (IVIM) fitting approaches to DWI. This study presents an improved version: IVIM-NEToptim_{optim}, and characterizes its superior performance in pancreatic ductal adenocarcinoma (PDAC) patients. Method{\bf Method}: In simulations (SNR=20), the accuracy, independence and consistency of IVIM-NET were evaluated for combinations of hyperparameters (fit S0, constraints, network architecture, # hidden layers, dropout, batch normalization, learning rate), by calculating the NRMSE, Spearman's Ļ\rho, and the coefficient of variation (CVNET_{NET}), respectively. The best performing network, IVIM-NEToptim_{optim} was compared to least squares (LS) and a Bayesian approach at different SNRs. IVIM-NEToptim_{optim}'s performance was evaluated in 23 PDAC patients. 14 of the patients received no treatment between scan sessions and 9 received chemoradiotherapy between sessions. Intersession within-subject standard deviations (wSD) and treatment-induced changes were assessed. Results{\bf Results}: In simulations, IVIM-NEToptim_{optim} outperformed IVIM-NETorig_{orig} in accuracy (NRMSE(D)=0.18 vs 0.20; NMRSE(f)=0.22 vs 0.27; NMRSE(D*)=0.39 vs 0.39), independence (Ļ\rho(D*,f)=0.22 vs 0.74) and consistency (CVNET_{NET} (D)=0.01 vs 0.10; CVNET_{NET} (f)=0.02 vs 0.05; CVNET_{NET} (D*)=0.04 vs 0.11). IVIM-NEToptim_{optim} showed superior performance to the LS and Bayesian approaches at SNRs<50. In vivo, IVIM-NEToptim_{optim} sshowed significantly less noisy parameter maps with lower wSD for D and f than the alternatives. In the treated cohort, IVIM-NEToptim_{optim} detected the most individual patients with significant parameter changes compared to day-to-day variations. Conclusion{\bf Conclusion}: IVIM-NEToptim_{optim} is recommended for IVIM fitting to DWI data

    Author disambiguation using multi-aspect similarity indicators

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    Key to accurate bibliometric analyses is the ability to correctly link individuals to their corpus of work, with an optimal balance between precision and recall. We have developed an algorithm that does this disambiguation task with a very high recall and precision. The method addresses the issues of discarded records due to null data fields and their resultant effect on recall, precision and F-measure results. We have implemented a dynamic approach to similarity calculations based on all available data fields. We have also included differences in author contribution and age difference between publications, both of which have meaningful effects on overall similarity measurements, resulting in significantly higher recall and precision of returned records. The results are presented from a test dataset of heterogeneous catalysis publications. Results demonstrate significantly high average F-measure scores and substantial improvements on previous and stand-alone techniques

    Pulmonary histoplasmosis presenting as chronic productive cough, fever, and massive unilateral consolidation in a 15-year-old immune-competent boy: a case report

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    Severe histoplasmosis is known to be among the AIDS-defining opportunistic infections affecting patients with very low CD4 cell counts in histoplasmosis-endemic areas. Histoplasma capsulatum var. duboisii is common in West and Central Africa, where it occurs in both HIV/AIDS and non-HIV patients. Few cases of life-threatening histoplasmosis in immune-competent individuals have been reported worldwide. We describe a case of pulmonary histoplasmosis diagnosed on the basis of autopsy and histological investigations. A 15-year old East African immune-competent boy with a history of smear-positive tuberculosis and a two-year history of rock cutting presented to our hospital with chronic productive cough, fever, and massive unilateral consolidation. At the time of presentation to our hospital, this patient was empirically treated for recurrent tuberculosis without success, and he died on the seventh day after admission. The autopsy revealed a huge granulomatous lesion with caseation, but no acid-fast bacilli were detected on several Ziehl-Neelsen stains. However, periodic acid-Schiff staining was positive, and the histological examination revealed features suggestive of Histoplasma yeast cells. Severe pulmonary histoplasmosis should be considered in evaluating immune-competent patients with risk factors for the disease who present with pulmonary symptoms mimicking tuberculosis

    Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

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    Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (nā€‰=ā€‰187) and serum (nā€‰=ā€‰405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (nā€‰=ā€‰196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-Ī² deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker

    Layered control architectures in robots and vertebrates

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    We revieiv recent research in robotics, neuroscience, evolutionary neurobiology, and ethology with the aim of highlighting some points of agreement and convergence. Specifically, we com pare Brooks' (1986) subsumption architecture for robot control with research in neuroscience demonstrating layered control systems in vertebrate brains, and with research in ethology that emphasizes the decomposition of control into multiple, intertwined behavior systems. From this perspective we then describe interesting parallels between the subsumption architecture and the natural layered behavior system that determines defense reactions in the rat. We then consider the action selection problem for robots and vertebrates and argue that, in addition to subsumption- like conflict resolution mechanisms, the vertebrate nervous system employs specialized selection mechanisms located in a group of central brain structures termed the basal ganglia. We suggest that similar specialized switching mechanisms might be employed in layered robot control archi tectures to provide effective and flexible action selection
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