170 research outputs found
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Shortwave spectral radiative signatures and their physical controls
The spectrum of reflected solar radiation emerging at the top of the atmosphere is rich with Earth system information. To identify spectral signatures in the reflected solar radiation and directly relate them to the underlying physical properties controlling their structure, over 90,000 solar reflectance spectra are computed over West Africa in 2010 using a fast radiation code employing the spectral characteristics of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). Cluster analysis applied to the computed spectra reveals spectral signatures related to distinct surface properties, and cloud regimes distinguished by their spectral short-wave cloud radiative effect (SWCRE). The cloud regimes exhibit a diverse variety of mean broadband SWCREs, and offer an alternative approach to define cloud type for SWCRE applications that does not require any prior assumptions. The direct link between spectral signatures and distinct physical properties extracted from clustering remains robust between spatial scales of 1, 20 and 240 km, and presents an excellent opportunity to understand the underlying properties controlling real spectral reflectance observations. Observed SCIAMACHY spectra are assigned to the calculated spectral clusters, showing that cloud regimes are most frequent during the active West African monsoon season of JuneāOctober in 2010, and all cloud regimes have a higher frequency of occurrence during the active monsoon season of 2003 compared with the inactive monsoon season of 2004. Overall, the distinct underlying physical properties controlling spectral signatures show great promise for monitoring evolution of the Earth system directly from solar spectral reflectance observations
On the impact of transport model errors for the estimation of CO2 surface fluxes from GOSAT observations
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
: Earlier work showed that IVIM-NET, 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-NET, and characterizes
its superior performance in pancreatic ductal adenocarcinoma (PDAC) patients.
: 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 , and
the coefficient of variation (CV), respectively. The best performing
network, IVIM-NET was compared to least squares (LS) and a Bayesian
approach at different SNRs. IVIM-NET'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. : In simulations, IVIM-NET outperformed
IVIM-NET in accuracy (NRMSE(D)=0.18 vs 0.20; NMRSE(f)=0.22 vs 0.27;
NMRSE(D*)=0.39 vs 0.39), independence ((D*,f)=0.22 vs 0.74) and
consistency (CV (D)=0.01 vs 0.10; CV (f)=0.02 vs 0.05;
CV (D*)=0.04 vs 0.11). IVIM-NET showed superior performance
to the LS and Bayesian approaches at SNRs<50. In vivo, IVIM-NET
sshowed significantly less noisy parameter maps with lower wSD for D and f than
the alternatives. In the treated cohort, IVIM-NET detected the most
individual patients with significant parameter changes compared to day-to-day
variations. : IVIM-NET is recommended for IVIM
fitting to DWI data
Author disambiguation using multi-aspect similarity indicators
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
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
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=ā187) and serum (nā=ā405) 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=ā196) 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
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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