Multi-level Protocol for Mechanistic Reaction Studies Using Semi-local Fitted Potential Energy Surfaces

In this work, we propose a multi-scale protocol for routine theoretical studies of chemical reaction mechanisms. The initial reaction paths of our investigated systems are sampled using the Nudged-Elastic Band (NEB) method driven by a cheap electronic structure method. Forces recalculated at the more accurate electronic structure theory for a set of points on the path are fitted with a machine-learning technique (in our case symmetric gradient domain machine learning or sGDML) to produce a semi-local reactive Potential Energy Surface (PES), embracing reactants, products and transition state (TS) regions. This approach has been successfully applied to a unimolecular (Bergman cyclization of enediyne) and a bimolecular (S$_\text{N}$2 substitution) reaction. In particular, we demonstrate that with only 50 to 150 energy-force evaluations with the accurate reference methods (here CASSCF and CCSD) it is possible to construct a semi-local PES giving qualitative agreement for stationary-point geometries, intrinsic reaction-coordinates and barriers. Furthermore, we find a qualitative agreement in vibrational frequencies and reaction rate coefficients. The key aspect of the method's performance is its multi-scale nature, which not only saves computational effort but also allows extracting meaningful information along the reaction path, characterized by zero gradients in all but one direction. Agnostic to the nature of the TS and computationally economic, the protocol can be readily automated and routinely used for mechanistic reaction studies

EEG Microstate Dynamics Associated with Dream-Like Experiences During the Transition to Sleep.

Consciousness always requires some representational content; that is, one can only be conscious about something. However, the presence of conscious experience (awareness) alone does not determine whether its content is in line with the external and physical world. Dreams, apart from certain forms of hallucinations, typically consist of non-veridical percepts, which are not recognized as false, but rather considered real. This type of experiences have been described as a state of dissociation between phenomenal and reflective awareness. Interestingly, during the transition to sleep, reflective awareness seems to break down before phenomenal awareness as conscious experience does not immediately fade with reduced wakefulness but is rather characterized by the occurrence of uncontrolled thinking and perceptual images, together with a reduced ability to recognize the internal origin of the experience. Relative deactivation of the frontoparietal and preserved activity in parieto-occipital networks has been suggested to account for dream-like experiences during the transition to sleep. We tested this hypothesis by investigating subjective reports of conscious experience and large-scale brain networks using EEG microstates in 45 healthy young subjects during the transition to sleep. We observed an inverse relationship between cognitive effects and physiological activation; dream-like experiences were associated with an increased presence of a microstate with sources in the superior and middle frontal gyrus and precuneus. Additionally, the presence of a microstate associated with higher-order visual areas was decreased. The observed inverse relationship might therefore indicate a disengagement of cognitive control systems that is mediated by specific, inhibitory EEG microstates

Aplicación y mejoras al método MPM para el análisis de deslizamientos y movimientos de tierra

En este artículo se presentan dos extensiones al Método de Puntos Materiales (MPM) que mejoran la aptitud del método en la simulación de deslizamientos y movimientos de tierra. La primera consiste en el uso de una formulación de multi-fase que permite el análisis de mezclas sólido-fluido y su interacción a varias escalas. La segunda provee una técnica apropiada para mitigar el problema de "locking" que surge de usar, en el MPM estándar, funciones de interpolación lineales en una grilla Euleriana. Para este caso se propone una estrategia de relajación basada en el principio de Hu-Washizu y se demuestra su aplicabilidad en la modelación de flujos granulares

Soft dentin results in unique flexible teeth in scraping catfishes

Teeth are generally used for actions in which they experience mainly compressive forces acting toward the base. The ordered tooth enamel(oid) and dentin structures contribute to the high compressive strength but also to the minor shear and tensile strengths. Some vertebrates, however, use their teeth for scraping, with teeth experiencing forces directed mostly normal to their long axis. Some scraping suckermouth catfishes (Loricariidae) even appear to have flexible teeth, which have not been found in any other vertebrate taxon. Considering the mineralized nature of tooth tissues, the notion of flexible teeth seems paradoxical. We studied teeth of five species, testing and measuring tooth flexibility, and investigating tooth (micro) structure using transmission electron microscopy, staining, computed tomography scanning, and scanning electron microscopy-energy-dispersive spectrometry. We quantified the extreme bending capacity of single teeth (up to 180 degrees) and show that reorganizations of the tooth (micro) structure and extreme hypomineralization of the dentin are adaptations preventing breaking by allowing flexibility. Tooth shape and internal structure appear to be optimized for bending in one direction, which is expected to occur frequently when feeding (scraping) under natural conditions. Not all loricariid catfishes possess flexible teeth, with the trait potentially having evolved more than once. Flexible teeth surely rank among the most extreme evolutionary novelties in known mineralized biological materials and might yield a better understanding of the processes of dentin formation and (hypo) mineralization in vertebrates, including humans

The EDGE-CALIFA Survey: Interferometric Observations of 126 Galaxies with CARMA

We present interferometric CO observations, made with the Combined Array for Millimeter-wave Astronomy (CARMA) interferometer, of galaxies from the Extragalactic Database for Galaxy Evolution survey (EDGE). These galaxies are selected from the Calar Alto Legacy Integral Field Area (CALIFA) sample, mapped with optical integral field spectroscopy. EDGE provides good-quality CO data (3σ sensitivity before inclination correction, resolution ∼1.4 kpc) for 126 galaxies, constituting the largest interferometric CO survey of galaxies in the nearby universe. We describe the survey and data characteristics and products, then present initial science results. We find that the exponential scale lengths of the molecular, stellar, and star-forming disks are approximately equal, and galaxies that are more compact in molecular gas than in stars tend to show signs of interaction. We characterize the molecular-to-stellar ratio as a function of Hubble type and stellar mass and present preliminary results on the resolved relations between the molecular gas, stars, and star-formation rate. We then discuss the dependence of the resolved molecular depletion time on stellar surface density, nebular extinction, and gas metallicity. EDGE provides a key data set to address outstanding topics regarding gas and its role in star formation and galaxy evolution, which will be publicly available on completion of the quality assessment.Fil: Bolatto, Alberto. University of Maryland; Estados UnidosFil: Wong, Tony. University of Illinois at Urbana; Estados UnidosFil: Utomo, Dyas. University of California at Berkeley; Estados UnidosFil: Blitz, Leo. University of California at Berkeley; Estados UnidosFil: Vogel, Stuart N.. University of Maryland; Estados UnidosFil: Sánchez, Sebastián F.. Universidad Nacional Autónoma de México; MéxicoFil: Barrera-Ballesteros, Jorge. University Johns Hopkins; Estados UnidosFil: Cao, Yixian. University of Illinois; Estados UnidosFil: Colombo, Dario. Max Planck Institut Fur Radioastronomie; AlemaniaFil: Dannerbauer, Helmut. Universidad de La Laguna; EspañaFil: García-Benito, Rubén. Instituto de Astrofísica de Andalucía; EspañaFil: Herrera-Camus, Rodrigo. Max Planck Institute für Extraterrestrische Physik; AlemaniaFil: Husemann, Bernd. Max-Planck-Institut für Astronomie; AlemaniaFil: Kalinova, Veselina. Max Planck Institut für Radioastronomie; AlemaniaFil: Leroy, Adam K.. Ohio State University; Estados UnidosFil: Leung, Gigi. Max-Planck-Institut für Astronomie; AlemaniaFil: Levy, Rebecca C.. University of Maryland; Estados UnidosFil: Mast, Damian. Observatorio Astronomico de la Universidad Nacional de Cordoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Ostriker, Eve. University of Princeton; Estados UnidosFil: Rosolowsky, Erik. University of Alberta; CanadáFil: Sandstrom, Karin M.. University of California at San Diego; Estados UnidosFil: Teuben, Peter. University of Maryland; Estados UnidosFil: Van De Ven, Glenn. Max-Planck-Institut für Astronomie; AlemaniaFil: Walter, Fabian. Max-Planck-Institut für Astronomie; Alemani

Is aggregated synthetic amorphous silica toxicologically relevant?

The regulatory definition(s) of nanomaterials (NMs) frequently uses the term 'agglomerates and aggregates' (AA) despite the paucity of evidence that AA are significantly relevant from a nanotoxicological perspective. This knowledge gap greatly affects the safety assessment and regulation of NMs, such as synthetic amorphous silica (SAS). SAS is used in a large panel of industrial applications. They are primarily produced as nano-sized particles (1-100 nm in diameter) and considered safe as they form large aggregates (> 100 nm) during the production process. So far, it is indeed believed that large aggregates represent a weaker hazard compared to their nano counterpart. Thus, we assessed the impact of SAS aggregation on in vitro cytotoxicity/biological activity to address the toxicological relevance of aggregates of different sizes

A double blind, fixed blood-level study comparing mirtazapine with imipramine in depressed in-patients

Antidepressant effects of mirtazapine and imipramine were compared in a randomized, double blind, fixed blood-level study with in-patients in a single centre. Patients with a DSM-III-R diagnosis of major depression and a Hamilton (17-item) score of ≤ 18 were selected. After a drug-free and a placebo-washout period of 7 days in total, 107 patients still fulfilling the HRSD criterion of ≤ 18, started on active treatment. The dose was adjusted to a predefined fixed blood level to avoid suboptimal dosing of imipramine. Concomitant psychotropic medication was administered only in a few cases because of intolerable anxiety or intolerable psychotic symptoms. Eight patients dropped out and two were excluded from analyses because of non-compliance; 97 completed the study. According to the main response criterion (50% or more reduction on the HRSD score) 11/51 (21.6%) patients responded on mirtazapine and 23/46 (50%) on imipramine after 4 weeks' treatment on the predefined blood level. Such a dramatic difference in efficacy between antidepressants has not often been reported before. The selection of (severely ill) in-patients, including those with suicidal or psychotic features, may have significance in this respect. Optimization of treatment with the reference drug imipramine through blood level control, exclusion of non-compliance for both drugs, exclusion of most concomitant medication and a low drop-out rate may also have contributed. It is concluded that imipramine is superior to mirtazapine in the patient population studied

Plasma Surrogate Modelling using Fourier Neural Operators

Predicting plasma evolution within a Tokamak reactor is crucial to realizing the goal of sustainable fusion. Capabilities in forecasting the spatio-temporal evolution of plasma rapidly and accurately allow us to quickly iterate over design and control strategies on current Tokamak devices and future reactors. Modelling plasma evolution using numerical solvers is often expensive, consuming many hours on supercomputers, and hence, we need alternative inexpensive surrogate models. We demonstrate accurate predictions of plasma evolution both in simulation and experimental domains using deep learning-based surrogate modelling tools, viz., Fourier Neural Operators (FNO). We show that FNO has a speedup of six orders of magnitude over traditional solvers in predicting the plasma dynamics simulated from magnetohydrodynamic models, while maintaining a high accuracy (MSE $\approx$ $10^{-5}$). Our modified version of the FNO is capable of solving multi-variable Partial Differential Equations (PDE), and can capture the dependence among the different variables in a single model. FNOs can also predict plasma evolution on real-world experimental data observed by the cameras positioned within the MAST Tokamak, i.e., cameras looking across the central solenoid and the divertor in the Tokamak. We show that FNOs are able to accurately forecast the evolution of plasma and have the potential to be deployed for real-time monitoring. We also illustrate their capability in forecasting the plasma shape, the locations of interactions of the plasma with the central solenoid and the divertor for the full duration of the plasma shot within MAST. The FNO offers a viable alternative for surrogate modelling as it is quick to train and infer, and requires fewer data points, while being able to do zero-shot super-resolution and getting high-fidelity solutions