37 research outputs found
Illustration of OASIS for an AR(1) process (see S2 Video).
<p>Red lines depict true spike times. The shaded background shows how the time points are gathered in pools. The pool currently under consideration is indicated by the blue crosses. A constraint violation is encountered for the second time step <b>(A)</b> leading to backtracking and merging <b>(B)</b>. The algorithm proceeds moving forward <b>(C-E)</b> until the next violation occurs <b>(E)</b> and triggers backtracking and merging <b>(F-G)</b> as long as constraints are violated. When the most recent spike time has been reached <b>(G)</b> the algorithm proceeds forward again <b>(H)</b>. The process continues until the end of the series has been reached <b>(I)</b>. The solution is obtained and pools span the inter-spike-intervals.</p
OASIS produces the same high quality results as convex solvers at least an order of magnitude faster.
<p><b>(A)</b> Raw and inferred traces for simulated AR(1) data, <b>(B)</b> simulated AR(2) and <b>(C)</b> real data from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005423#pcbi.1005423.ref036" target="_blank">36</a>] fitted with an AR(2) model. OASIS solves <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005423#pcbi.1005423.e005" target="_blank">Eq (3)</a> exactly for AR(1) and just approximately for AR(2) processes, nevertheless well extracting spikes. <b>(D)</b> Computation time for simulated AR(1) data with given λ (blue circles, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005423#pcbi.1005423.e005" target="_blank">Eq 3</a>) or inference with hard noise constraint (green x, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005423#pcbi.1005423.e077" target="_blank">Eq 15</a>). GUROBI failed on the noise constrained problem. The inset shows the same data in logarithmic scale. <b>(E)</b> Computation time for simulated AR(2) data. <b>(F)</b> Normalized computation time of OASIS for simulated AR(1) data with given λ (blue circles, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005423#pcbi.1005423.e005" target="_blank">Eq 3</a>) and inference with hard noise constraint on full data (green x, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005423#pcbi.1005423.e077" target="_blank">Eq 15</a>) or small initial batch followed by processing in online mode (orange crosses).</p
Generative autoregessive model for calcium dynamics.
<p>Spike train <b><i>s</i></b> gets filtered to produce calcium trace <b><i>c</i></b>; here we used <i>p</i> = 2 as order of the AR process. Added noise yields the observed fluorescence <b><i>y</i></b>.</p
Thresholding can improve the accuracy of spike inference.
<p><b>(A)</b> Inferred trace using L1 penalty (L1, blue) and the thresholded OASIS (Thresh., green). The data (gray) are simulated with AR(1) model. <b>(B)</b> Inferred spiking activity. <b>(C)</b> The detected events using thresholded OASIS depend on the selection of <i>s</i><sub>min</sub>. The ground truth is shown in red. <b>(D,E,F)</b>, same as <b>(A,B,C)</b>, but the data are simulated with AR(2).</p
Optimizing sparsity parameter λ and AR coefficient .
<p><b>(A)</b> Running the active set method, with conservatively small estimate , yields an initial <i>denoised</i> estimate (blue) of the data (gray) roughly capturing the truth (red). We also report the correlation between the <i>deconvolved</i> estimate and true spike train as a direct measure for the accuracy of spike train inference. <b>(B)</b> Updating sparsity parameter λ according to <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005423#pcbi.1005423.e082" target="_blank">Eq (18)</a> such that RSS = <i>σ</i><sup>2</sup> <i>T</i> (left) shifts the current estimate downward (right, blue). <b>(C)</b> Running the active set method enforces the constraints again and is fast due to warm-starting. <b>(D)</b> Updating by minimizing the polynomial function RSS() and <b>(E)</b> running the warm-started active set method completes one iteration, which yields already a decent fit. <b>(F)</b> A few more iterations improve the solution further. The obtained estimate (blue) is hardly distinguishable from the one obtained with known true <i>γ</i> (yellow dashed trace, plotted in addition to the traces in A-E, is on top of blue solid line). Note that determining based on the autocovariance (additionally plotted purple trace) yields a crude solution that even misses spikes (at 24.6 s and 46.5 s).</p
Varied lag in the online estimator.
<p><b>(A,B)</b> Performance of spike inference as function of lag for various noise levels (i.e., inverse SNR) without (A) and with positive threshold <i>s</i><sub>min</sub> (B). We used correlation of the inferred spike train as similarity measure and compared to ground truth as well as to the optimally recoverable activity when the lag is unlimited as in offline processing. <b>(C)</b> Inferred trace with positive threshold <i>s</i><sub>min</sub> for increasing lag using the data depicted in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005423#pcbi.1005423.g004" target="_blank">Fig 4A</a> with high noise level (<i>σ</i> = 0.3). The gray lines indicate the true spike times.</p
Captured video of augmented scene, when the camera changes focus
Captured video of augmented scene, when the camera changes focu
Thiophene-Fused Benzothiadiazole: A Strong Electron-Acceptor Unit to Build D–A Copolymer for Highly Efficient Polymer Solar Cells
A novel strong electron-acceptor,
thienoÂ[2,3-<i>f</i>]-2,1,3-benzothiadiazole-6-carboxylate
(BTT), was first designed
and synthesized. By introducing two thienyl groups into BTT and then
copolymerizing with thienyl group substituted benzoÂ[1,2-b:4,5-b′]Âdithiophene
(BDTT) unit, a low band gap D–A copolymer (PBTT-TBDTT) was
obtained. Compared with its polymer analogue (PBT-TBDTT) with benzothiadiazole
(BT) as an acceptor, PBTT-TBDTT exhibits stronger intramolecular charge
transfer. Thus, it shows much broader absorption covering almost the
whole visible light region (in the range of 300–850 nm) and
narrower optical band gap around 1.45 eV with a large IP (ionization
potential) at 5.35 eV. The maximum efficiency of PBTT-TBDTT based
device reaches 6.07% which is much higher than that of PBT-TBDTT (3.24%),
indicating that BTT unit is a promising electron-acceptor moiety to
construct low band gap D–A copolymers for PSCs with high photovoltaic
performances
Acetate Salts as Nonhalogen Additives To Improve Perovskite Film Morphology for High-Efficiency Solar Cells
A two-step
method has been popularly adopted to fabricate a perovskite film of
planar heterojunction organo-lead halide perovskite solar cells (PSCs).
However, this method often generates uncontrollable film morphology
with poor coverage. Herein, we report a facile method to improve perovskite
film morphology by incorporating a small amount of acetate (CH<sub>3</sub>COO<sup>–</sup>, Ac<sup>–</sup>) salts (NH<sub>4</sub>Ac, NaAc) as nonhalogen additives in CH<sub>3</sub>NH<sub>3</sub>I solution used for immersing PbI<sub>2</sub> film, resulting
in improved CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> film morphology.
Under the optimized NH<sub>4</sub>Ac additive concentration of 10
wt %, the best power conversion efficiency (PCE) reaches 17.02%, which
is enhanced by ∼23.2% relative to that of the pristine device
without additive, whereas the NaAc additive does not lead to an efficiency
enhancement despite the improvement of the CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> film morphology. SEM study reveals that NH<sub>4</sub>Ac and NaAc additives can both effectively improve perovskite film
morphology by increasing the surface coverage via diminishing pinholes.
The improvement on CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> film
morphology is beneficial for increasing the optical absorption of
perovskite film and improving the interfacial contact at the perovskite/spiro-OMeTAD
interface, leading to the increase of short-circuit current and consequently
efficiency enhancement of the PSC device for NH<sub>4</sub>Ac additive
only
New Kind of Hyperbranched Conjugated Polymers Containing Alkyl-Modified 2,4,6-Tris(thiophen-2-yl)-1,3,5-triazine Unit for Enhancing Two-Photon Absorption
Two series of hyperbranched polymers
based on alkyl-modified 2,4,6-trisÂ(thiophen-2-yl)-1,3,5-triazine
central units linked through fluorene bridges of different lengths
have been synthesized via Suzuki coupling. The two series of polymers
differ in the position of alkyl substitution within the thienyl group,
which can be either closer to the triazine core (<b>P0</b>–<b>P10</b>) or to the fluorene bridge (<b>P0</b>′–<b>P10</b>′). Introduction of a hexyl group at one of the
β-positions of the thienyl group improves the solubility of
the polymers. A good control over the ratio of triazine and fluorene
units allows for the systematic study of the polymer composition effects
on the electrochemical, linear, and nonlinear photophysical properties.
The nonlinear absorption has been shown to have a noticeable promotion
with increasing molar ratio of the triazine core, while the emission
quantum yield decreases. The position of alkyl substitution within
the thienyl group has a significant effect on the two-photon absorption
cross section. Substitution at the β-position of the thienyl
group closer to the triazine unit favors nonlinear absorption in the <b>P0</b>–<b>P10</b> series when compared to the <b>P0</b>′–<b>P10</b>′ series. These polymers
perform considerably better as nonlinear absorbers than their unsubstituted
analogues