TMM-Fast: A Transfer Matrix Computation Package for Multilayer Thin-Film Optimization

Achieving the desired optical response from a multilayer thin-film structure over a broad range of wavelengths and angles of incidence can be challenging. An advanced thin-film structure can consist of multiple materials with different thicknesses and numerous layers. Design and optimization of complex thin-film structures with multiple variables is a computationally heavy problem that is still under active research. To enable fast and easy experimentation with new optimization techniques, we propose the Python package TMM-Fast which enables parallelized computation of reflection and transmission of light at different angles of incidence and wavelengths through the multilayer thin-film. By decreasing computational time, generating datasets for machine learning becomes feasible and evolutionary optimization can be used effectively. Additionally, the sub-package TMM-Torch allows to directly compute analytical gradients for local optimization by using PyTorch Autograd functionality. Finally, an OpenAi Gym environment is presented which allows the user to train reinforcement learning agents on the problem of finding multilayer thin-film configurations.Comment: Technical note, 8 pages, introduction to Python package TMM-Fast, Repository: https://github.com/MLResearchAtOSRAM/tmm_fast

Rhythmic temporal structure at encoding enhances recognition memory

Presenting events in a rhythm has been shown to enhance perception and facilitate responses for stimuli that appear in synchrony with the rhythm, but little is known about how rhythm during encoding influences later recognition. In this study, participants were presented with images of everyday objects in an encoding phase prior to a recognition task in which they judged whether or not objects were previously presented. Blockwise, object presentation during encoding followed either a rhythmic (constant, predictable) or arrhythmic (random, unpredictable) temporal structure, of which participants were unaware. Recognition was greater for items presented in a rhythmic relative to an arrhythmic manner. During encoding, there was a Dm effect with larger positivity for rhythmic over arrhythmic stimuli. At recognition, memory specific ERP components were differentially affected by temporal structure: the FN400 old/new effect was unaffected by rhythmic structure, whilst the late positive component (LPC) old/new effect was observed only for rhythmically encoded items. Taken together, this study provides new evidence that memory specific processing at recognition is affected by temporal structure at encoding

LPMLE3 : a novel 1-D approach to study water flow in streambeds using heat as a tracer

We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods

Reactivity of neodymium carriers in deep sea sediments: Implications for boundary exchange and paleoceanography

The dissolved neodymium (Nd) isotopic distribution in the deep oceans is determined by continental weathering inputs, water mass advection, and boundary exchange between particulate and dissolved fractions. Reconstructions of past Nd isotopic variability may therefore provide evidence on temporal changes in continental weathering inputs and/or ocean circulation patterns over a range of timescales. However, such an approach is limited by uncertainty in the mechanisms and importance of the boundary exchange process, and the challenge in reliably recovering past seawater Nd isotopic composition (εNd) from deep sea sediments. This study addresses these questions by investigating the processes involved in particulate–solution interactions and their impact on Nd isotopes. A better understanding of boundary exchange also has wider implications for the oceanic cycling and budgets of other particle-reactive elements. Sequential acid-reductive leaching experiments at pH ∼2–5 on deep sea sediments from the western Indian Ocean enable us to investigate natural boundary exchange processes over a timescale appropriate to laboratory experiments. We provide evidence that both the dissolution of solid phases and exchange processes influence the εNd of leachates, which suggests that both processes may contribute to boundary exchange. We use major element and rare earth element (REE) data to investigate the pools of Nd that are accessed and demonstrate that sediment leachate εNd values cannot always be explained by admixture between an authigenic component and the bulk detrital component. For example, in core WIND 24B, acid-reductive leaching generates εNd values between −11 and −6 as a function of solution/solid ratios and leaching times, whereas the authigenic components have εNd ≈ −11 and the bulk detrital component has εNd ≈ −15. We infer that leaching in the Mascarene Basin accesses authigenic components and a minor radiogenic volcanic component that is more reactive than Madagascan-derived clays. The preferential mobilisation of such a minor component demonstrates that the Nd released by boundary exchange could often have a significantly different εNd composition than the bulk detrital sediment. These experiments further demonstrate certain limitations on the use of acid-reductive leaching to extract the εNd composition of the authigenic fraction of bulk deep sea sediments. For example, the detrital component may contain a reactive fraction which is also acid-extractible, while the incongruent nature of this dissolution suggests that it is often inappropriate to use the bulk detrital sediment elemental chemistry and/or εNd composition when assessing possible detrital contamination of leachates. Based on the highly systematic controls observed, and evidence from REE patterns on the phases extracted, we suggest two approaches that lead to the most reliable extraction of the authigenic εNd component and good agreement with foraminiferal-based approaches; either (i) leaching of sediments without a prior decarbonation step, or (ii) the use of short leaching times and low solution/solid ratios throughout

Directional emission of white light via selective amplification of photon recycling and Bayesian optimization of multi-layer thin films

Over the last decades, light-emitting diodes (LED) have replaced common light bulbs in almost every application, from flashlights in smartphones to automotive headlights. Illuminating nightly streets requires LEDs to emit a light spectrum that is perceived as pure white by the human eye. The power associated with such a white light spectrum is not only distributed over the contributing wavelengths but also over the angles of vision. For many applications, the usable light rays are required to exit the LED in forward direction, namely under small angles to the perpendicular. In this work, we demonstrate that a specifically designed multi-layer thin film on top of a white LED increases the power of pure white light emitted in forward direction. Therefore, the deduced multi-objective optimization problem is reformulated via a real-valued physics-guided objective function that represents the hierarchical structure of our engineering problem. Variants of Bayesian optimization are employed to maximize this non-deterministic objective function based on ray tracing simulations. Eventually, the investigation of optical properties of suitable multi-layer thin films allowed to identify the mechanism behind the increased directionality of white light: angle and wavelength selective filtering causes the multi-layer thin film to play ping pong with rays of light

Ready ... Go: Amplitude of the fMRI Signal Encodes Expectation of Cue Arrival Time

What happens when the brain awaits a signal of uncertain arrival time, as when a sprinter waits for the starting pistol? And what happens just after the starting pistol fires? Using functional magnetic resonance imaging (fMRI), we have discovered a novel correlate of temporal expectations in several brain regions, most prominently in the supplementary motor area (SMA). Contrary to expectations, we found little fMRI activity during the waiting period; however, a large signal appears after the “go” signal, the amplitude of which reflects learned expectations about the distribution of possible waiting times. Specifically, the amplitude of the fMRI signal appears to encode a cumulative conditional probability, also known as the cumulative hazard function. The fMRI signal loses its dependence on waiting time in a “countdown” condition in which the arrival time of the go cue is known in advance, suggesting that the signal encodes temporal probabilities rather than simply elapsed time. The dependence of the signal on temporal expectation is present in “no-go” conditions, demonstrating that the effect is not a consequence of motor output. Finally, the encoding is not dependent on modality, operating in the same manner with auditory or visual signals. This finding extends our understanding of the relationship between temporal expectancy and measurable neural signals

Surprisingly correct: Unexpectedness of observed actions activates the medial prefrontal cortex

Not only committing errors, but also observing errors has been shown to activate the dorsal medial prefrontal cortex, particularly BA 8 and adjacent rostral cingulate zone (RCZ). Currently, there is a debate on whether this activity reflects a response to the incorrectness of the committed action or to its unexpectedness. This article reports two studies investigating whether activity in BA 8/RCZ is due to the unexpectedness of observed errors or the incorrectness of the specific observed action. Both studies employed an action observation paradigm reliant on the observation of an actor tying sailing knots. The reported behavioral experiment delivered evidence that the paradigm successfully induced the expectation of incorrect actions as well as the expectation of correct actions. The functional magnetic resonance imaging study revealed that unexpectedly correct as well as unexpectedly incorrect actions activate the BA 8/RCZ. The same result was confirmed for a coordinate in the vicinity that has been previously reported to be activated in separate studies either by the error observation or by the unexpectedness of committed errors, and has been associated with the error-related negativity. The present results suggest that unexpectedness has an impact on the medial prefrontal correlate of observed errors

Independent effects of bottom-up temporal expectancy and top-down spatial attention. An audiovisual study using rhythmic cueing

Selective attention to a spatial location has shown enhanced perception and facilitate behavior for events at attended locations. However, selection relies not only on where but also when an event occurs. Recently, interest has turned to how intrinsic neural oscillations in the brain entrain to rhythms in our environment, and, stimuli appearing in or out of sync with a rhythm have shown to modulate perception and performance. Temporal expectations created by rhythms and spatial attention are two processes which have independently shown to affect stimulus processing but it remains largely unknown how, and if, they interact. In four separate tasks, this study investigated the effects of voluntary spatial attention and bottom-up temporal expectations created by rhythms in both unimodal and crossmodal conditions. In each task the participant used an informative cue, either color or pitch, to direct their covert spatial attention to the left or right, and respond as quickly as possible to a target. The lateralized target (visual or auditory) was then presented at the attended or unattended side. Importantly, although not task relevant, the cue was a rhythm of either flashes or beeps. The target was presented in or out of sync (early or late) with the rhythmic cue. Results showed participants were faster responding to spatially attended compared to unattended targets in all tasks. Moreover, there was an effect of rhythmic cueing upon response times in both unimodal and crossmodal conditions. Responses were faster to targets presented in sync with the rhythm compared to when they appeared too early in both crossmodal tasks. That is, rhythmic stimuli in one modality influenced the temporal expectancy in the other modality, suggesting temporal expectancies created by rhythms are crossmodal. Interestingly, there was no interaction between top-down spatial attention and rhythmic cueing in any task suggesting these two processes largely influenced behavior independently

Comparative Effectiveness Research: An Empirical Study of Trials Registered in ClinicalTrials.gov

Background The $1.1 billion investment in comparative effectiveness research will reshape the evidence-base supporting decisions about treatment effectiveness, safety, and cost. Defining the current prevalence and characteristics of comparative effectiveness (CE) research will enable future assessments of the impact of this program. Methods We conducted an observational study of clinical trials addressing priority research topics defined by the Institute of Medicine and conducted in the US between 2007 and 2010. Trials were identified in ClinicalTrials.gov. Main outcome measures were the prevalence of comparative effectiveness research, nature of comparators selected, funding sources, and impact of these factors on results. Results 231 (22.3%; 95% CI 19.8%–24.9%) studies were CE studies and 804 (77.7%; 95% CI, 75.1%–80.2%) were non-CE studies, with 379 (36.6%; 95% CI, 33.7%–39.6%) employing a placebo control and 425 (41.1%; 95% CI, 38.1%–44.1%) no control. The most common treatments examined in CE studies were drug interventions (37.2%), behavioral interventions (28.6%), and procedures (15.6%). Study findings were favorable for the experimental treatment in 34.8% of CE studies and greater than twice as many (78.6%) non-CE studies (P<0.001). CE studies were more likely to receive government funding (P = 0.003) and less likely to receive industry funding (P = 0.01), with 71.8% of CE studies primarily funded by a noncommercial source. The types of interventions studied differed based on funding source, with 95.4% of industry trials studying a drug or device. In addition, industry-funded CE studies were associated with the fewest pediatric subjects (P<0.001), the largest anticipated sample size (P<0.001), and the shortest study duration (P<0.001). Conclusions In this sample of studies examining high priority areas for CE research, less than a quarter are CE studies and the majority is supported by government and nonprofits. The low prevalence of CE research exists across CE studies with a broad array of interventions and characteristics.National Library of Medicine (U.S.) (5G08LM009778)National Institutes of Health (U.S.