2,621 research outputs found
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data
We propose a matrix factorization technique that decomposes the resting state
fMRI (rs-fMRI) correlation matrices for a patient population into a sparse set
of representative subnetworks, as modeled by rank one outer products. The
subnetworks are combined using patient specific non-negative coefficients;
these coefficients are also used to model, and subsequently predict the
clinical severity of a given patient via a linear regression. Our
generative-discriminative framework is able to exploit the structure of rs-fMRI
correlation matrices to capture group level effects, while simultaneously
accounting for patient variability. We employ ten fold cross validation to
demonstrate the predictive power of our model on a cohort of fifty eight
patients diagnosed with Autism Spectrum Disorder. Our method outperforms
classical semi-supervised frameworks, which perform dimensionality reduction on
the correlation features followed by non-linear regression to predict the
clinical scores
Multilevel Delayed Acceptance MCMC with an Adaptive Error Model in PyMC3
This is the final version. Available from NeurIPS 2020 via the DOI in this recordUncertainty Quantification through Markov Chain Monte Carlo (MCMC) can be prohibitively expensive for target probability densities with expensive likelihood functions, for instance when the evaluation it involves solving a Partial Differential Equation (PDE), as is the case in a wide range of engineering applications. Multilevel Delayed Acceptance (MLDA) with an Adaptive Error Model (AEM) is a novel approach, which alleviates this problem by exploiting a hierarchy of models, with increasing complexity and cost, and correcting the inexpensive models on-the-fly. The method has been integrated within the open-source probabilistic programming package PyMC3 and is available in the latest development version. In this paper, the algorithm is presented along with an illustrative example.Turing AI fellowshipEngineering and Physical Sciences Research Council (EPSRC
Higgs friends and counterfeits at hadron colliders
We consider the possibility of "Higgs counterfeits" - scalars that can be
produced with cross sections comparable to the SM Higgs, and which decay with
identical relative observable branching ratios, but which are nonetheless not
responsible for electroweak symmetry breaking. We also consider a related
scenario involving "Higgs friends," fields similarly produced through gg fusion
processes, which would be discovered through diboson channels WW, ZZ, gamma
gamma, or even gamma Z, potentially with larger cross sections times branching
ratios than for the Higgs. The discovery of either a Higgs friend or a Higgs
counterfeit, rather than directly pointing towards the origin of the weak
scale, would indicate the presence of new colored fields necessary for the
sizable production cross section (and possibly new colorless but electroweakly
charged states as well, in the case of the diboson decays of a Higgs friend).
These particles could easily be confused for an ordinary Higgs, perhaps with an
additional generation to explain the different cross section, and we emphasize
the importance of vector boson fusion as a channel to distinguish a Higgs
counterfeit from a true Higgs. Such fields would naturally be expected in
scenarios with "effective Z's," where heavy states charged under the SM produce
effective charges for SM fields under a new gauge force. We discuss the
prospects for discovery of Higgs counterfeits, Higgs friends, and associated
charged fields at the LHC.Comment: 27 pages, 5 figures. References added and typos fixe
A comprehensive evaluation of colonic mucosal isolates of Sutterella wadsworthensis from inflammatory bowel disease
Peer reviewedPublisher PD
Evaluating Acquisition Time of rfMRI in the Human Connectome Project for Early Psychosis. How Much Is Enough?
Resting-state functional MRI (rfMRI) correlates activity across brain regions to identify functional connectivity networks. The Human Connectome Project (HCP) for Early Psychosis has adopted the protocol of the HCP Lifespan Project, which collects 20 min of rfMRI data. However, because it is difficult for psychotic patients to remain in the scanner for long durations, we investigate here the reliability of collecting less than 20 min of rfMRI data. Varying durations of data were taken from the full datasets of 11 subjects. Correlation matrices derived from varying amounts of data were compared using the Bhattacharyya distance, and the reliability of functional network ranks was assessed using the Friedman test. We found that correlation matrix reliability improves steeply with longer windows of data up to 11–12 min, and ≥14 min of data produces correlation matrices within the variability of those produced by 18 min of data. The reliability of network connectivity rank increases with increasing durations of data, and qualitatively similar connectivity ranks for ≥10 min of data indicates that 10 min of data can still capture robust information about network connectivities
A primary current distribution model of a novel micro-electroporation channel configuration
Traditional macro and micro-electroporation devices utilize facing electrodes, which generate electric fields inversely proportional to their separation distance. Although the separation distances in micro-electroporation devices are significantly smaller than those in macro-electroporation devices, they are limited by cell size. Because of this, significant potential differences are required to induce electroporation. These potential differences are often large enough to cause water electrolysis, resulting in electrode depletion and bubble formation, both of which adversely affect the electroporation process. Here, we present a theoretical study of a novel micro-electroporation channel composed of an electrolyte flowing over a series of adjacent electrodes separated by infinitesimally small insulators. Application of a small, non-electrolysis inducing potential difference between the adjacent electrodes results in radially-varying electric fields that emanate from these insulators, causing cells flowing through the channel to experience a pulsed electric field. This eliminates the need for a pulse generator, making a minimal power source (such as a battery) the only electrical equipment that is needed. A non-dimensional primary current distribution model of the novel micro-electroporation channel shows that decreasing the channel height results in an exponential increase in the electric field magnitude, and that cells experience exponentially greater electric field magnitudes the closer they are to the channel walls. Finally, dimensional primary current distribution models of two potential applications, water sterilization and cell transfection, demonstrate the practical feasibility of the novel micro-electroporation channel
Acaricidal and oviposition deterring effects of santalol identified in sandalwood oil against two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae)
Thirty-four plant essential oils were screened for their acaricidal and oviposition deterrent activities against two-spotted spider mite (TSSM), Tetranychus urticae Koch (Acari: Tetranychidae), in the laboratory using a leaf-dip bioassay. From initial trials, sandalwood and common thyme oils were observed to be the most effective against TSSM adult females. Subsequent trials confirmed that only sandalwood oil was significantly active (87.2 ± 2.9% mortality) against TSSM adult females. Sandalwood oil also demonstrated oviposition deterring effects based on a 89.3% reduction of the total number of eggs on leaf disks treated with the oil. GC–MS analysis revealed that the main components of the sandalwood oil were α-santalol (45.8%), β-santalol (20.6%), β-sinensal (9.4%), and epi-β-santalol (3.3%). A mixture of α- and β-santalol (51.0:22.9, respectively) produced significantly higher mortality (85.5 ± 2.9%) and oviposition deterrent effects (94.7% reduction in the number of eggs) than the control. Phytotoxicity was not shown on rose shoots to which a 0.1% solution of sandalwood oil was applied
Neural correlates of enhanced visual short-term memory for angry faces: An fMRI study
Copyright: © 2008 Jackson et al.Background: Fluid and effective social communication requires that both face identity and emotional expression information are encoded and maintained in visual short-term memory (VSTM) to enable a coherent, ongoing picture of the world and its players. This appears to be of particular evolutionary importance when confronted with potentially threatening displays of emotion - previous research has shown better VSTM for angry versus happy or neutral face identities.Methodology/Principal Findings: Using functional magnetic resonance imaging, here we investigated the neural correlates of this angry face benefit in VSTM. Participants were shown between one and four to-be-remembered angry, happy, or neutral faces, and after a short retention delay they stated whether a single probe face had been present or not in the previous display. All faces in any one display expressed the same emotion, and the task required memory for face identity. We find enhanced VSTM for angry face identities and describe the right hemisphere brain network underpinning this effect, which involves the globus pallidus, superior temporal sulcus, and frontal lobe. Increased activity in the globus pallidus was significantly correlated with the angry benefit in VSTM. Areas modulated by emotion were distinct from those modulated by memory load.Conclusions/Significance: Our results provide evidence for a key role of the basal ganglia as an interface between emotion and cognition, supported by a frontal, temporal, and occipital network.The authors were supported by a Wellcome Trust grant (grant number 077185/Z/05/Z) and by BBSRC (UK) grant BBS/B/16178
Potential health impacts of heavy metals on HIV-infected population in USA.
Noninfectious comorbidities such as cardiovascular diseases have become increasingly prevalent and occur earlier in life in persons with HIV infection. Despite the emerging body of literature linking environmental exposures to chronic disease outcomes in the general population, the impacts of environmental exposures have received little attention in HIV-infected population. The aim of this study is to investigate whether individuals living with HIV have elevated prevalence of heavy metals compared to non-HIV infected individuals in United States. We used the National Health and Nutrition Examination Survey (NHANES) 2003-2010 to compare exposures to heavy metals including cadmium, lead, and total mercury in HIV infected and non-HIV infected subjects. In this cross-sectional study, we found that HIV-infected individuals had higher concentrations of all heavy metals than the non-HIV infected group. In a multivariate linear regression model, HIV status was significantly associated with increased blood cadmium (p=0.03) after adjusting for age, sex, race, education, poverty income ratio, and smoking. However, HIV status was not statistically associated with lead or mercury levels after adjusting for the same covariates. Our findings suggest that HIV-infected patients might be significantly more exposed to cadmium compared to non-HIV infected individuals which could contribute to higher prevalence of chronic diseases among HIV-infected subjects. Further research is warranted to identify sources of exposure and to understand more about specific health outcomes
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