The accuracy of some density functional (DF) models widely used in material science depends on empirical or free parameters that are commonly tuned using reference physical properties. Grid-search ...methods are the standard numerical approximations used to find the optimal values of the free parameters, making the computational complexity to scale with the number of points in the grid. In this report, we illustrate that Bayesian optimization (BO), a sample-efficient machine learning algorithm, can calibrate different density functional models, e.g., hybrid exchange-correlation and range-separated density functionals. Using the atomization energies and bond lengths from the Gaussian-1 (G1) and Gaussian-2 (G2) databases, we show that BO optimizes the free parameters of the hybrid exchange-correlation functionals with approximately 55 evaluations of the error function. We also show that selecting exchange-correlation functionals for different physical systems can be done with BO. We jointly optimize and select the form of the exchange-correlation functionals and the free parameters by minimizing the root-mean-square error functions for the G1 and G2 data set atomization energies. The calibrated DF model is more accurate on average than standard DF methods, e.g., PBE0 and B3LYP.
The field of spondyloarthritis (SpA) has experienced major progress in the last decade, especially with regard to new treatments, earlier diagnosis, imaging technology and a better definition of ...outcome parameters for clinical trials. In the present work, the Assessment in SpondyloArthritis international Society (ASAS) provides a comprehensive handbook on the most relevant aspects for the assessments of spondyloarthritis, covering classification criteria, MRI and x rays for sacroiliac joints and the spine, a complete set of all measurements relevant for clinical trials and international recommendations for the management of SpA. The handbook focuses at this time on axial SpA, with ankylosing spondylitis (AS) being the prototype disease, for which recent progress has been faster than in peripheral SpA. The target audience includes rheumatologists, trial methodologists and any doctor and/or medical student interested in SpA. The focus of this handbook is on practicality, with many examples of MRI and x ray images, which will help to standardise not only patient care but also the design of clinical studies.
Soil respiration (Rs), the soil‐to‐atmosphere CO2 flux produced by microbes and plant roots, is a critical but uncertain component of the global carbon cycle. Our current understanding of the ...variability and dynamics is limited by the coarse spatial resolution of existing estimates. We predicted annual Rs and associated uncertainty across the world at 1‐km resolution using a quantile regression forest algorithm trained with observations from the global Soil Respiration Database spanning from 1961 to 2011. This model yielded a global annual Rs estimate of 87.9 Pg C/year with an associated global uncertainty of 18.6 (mean absolute error) and 40.4 (root mean square error) Pg C/year. The estimated annual heterotrophic respiration (Rh), derived from empirical relationships with Rs, was 49.7 Pg C/year over the same period. Predicted Rs rates and associated uncertainty varied widely across vegetation types, with the greatest predicted rates of Rs in evergreen broadleaf forests (accounting for 20.9% of global Rs). The greatest prediction uncertainties were in northern latitudes and arid to semiarid ecosystems, suggesting that these areas should be targeted in future measurement campaigns. This study provides predictions of Rs (and associated prediction uncertainty) at unprecedentedly high spatial resolution across the globe that could help constrain local‐to‐global process‐based models. Furthermore, it provides insights into the large variability of Rs and Rh across vegetation classes and identifies regions and vegetation types with poor model performance that should be prioritized for future data collection.
Plain Language Summary
Soils emit large amounts of carbon dioxide to the atmosphere every year via the process of soil respiration, which greatly exceeds emissions from human sources. However, rates of soil respiration are highly variable in space, which limits our ability to balance global carbon budgets and forecast climate change. We used a novel application of a machine learning approach to predict annual rates of soil respiration at high resolution (1 km) across the globe and examined spatial patterns of the associated uncertainty of these predictions. Predictions were made based on how observations of soil respiration were related to climate (annual temperature and annual and seasonal precipitation) and vegetation information. Predicted annual soil respiration and prediction uncertainty varied across ecosystem types and regions. Our predictions suggest that evergreen tropical forests dominate global annual soil respiration emissions. Dryland, wetland, and cold ecosystems had the highest associated prediction uncertainties, suggesting that future soil respiration measurements would be especially useful in these areas. The high spatial resolution of our predictions will help researchers studying the carbon cycle at local to global scales.
Key Points
A high spatial resolution machine learning approach was used for estimating soil respiration across the world
Predictions of soil respiration varied widely across ecosystem classes, and allowed for suitable estimates of heterotrophic respiration
Associated prediction uncertainty was highest in high latitudes and data scarce regions, which should be targets for future measurements
The rewetting of dry soils and the thawing of frozen soils are short-term, transitional phenomena in terms of hydrology and the thermodynamics of soil systems. The impact of these short-term ...phenomena on larger scale ecosystem fluxes is increasingly recognized, and a growing number of studies show that these events affect fluxes of soil gases such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), ammonia (NH3) and nitric oxide (NO). Global climate models predict that future climatic change is likely to alter the frequency and intensity of drying-rewetting events and thawing of frozen soils. These future scenarios highlight the importance of understanding how rewetting and thawing will influence dynamics of these soil gases. This study summarizes findings using a new database containing 338 studies conducted from 1956 to 2011, and highlights open research questions. The database revealed conflicting results following rewetting and thawing in various terrestrial ecosystems and among soil gases, ranging from large increases in fluxes to non-significant changes. Studies reporting lower gas fluxes before rewetting tended to find higher post-rewetting fluxes for CO2, N2O and NO; in addition, increases in N2O flux following thawing were greater in warmer climate regions. We discuss possible mechanisms and controls that regulate flux responses, and recommend that a high temporal resolution of flux measurements is critical to capture rapid changes in gas fluxes after these soil perturbations. Finally, we propose that future studies should investigate the interactions between biological (i.e., microbial community and gas production) and physical (i.e., porosity, diffusivity, dissolution) changes in soil gas fluxes, apply techniques to capture rapid changes (i.e., automated measurements), and explore synergistic experimental and modelling approaches.
Functional delivery of mRNA to tissues in the body is key to implementing fundamentally new and potentially transformative strategies for vaccination, protein replacement therapy, and genome editing, ...collectively affecting approaches for the prevention, detection, and treatment of disease. Broadly applicable tools for the efficient delivery of mRNA into cultured cells would advance many areas of research, and effective and safe in vivo mRNA delivery could fundamentally transform clinical practice. Here we report the step-economical synthesis and evaluation of a tunable and effective class of synthetic biodegradable materials: charge-altering releasable transporters (CARTs) for mRNA delivery into cells. CARTs are structurally unique and operate through an unprecedented mechanism, serving initially as oligo(α-amino ester) cations that complex, protect, and deliver mRNA and then change physical properties through a degradative, charge-neutralizing intramolecular rearrangement, leading to intracellular release of functional mRNA and highly efficient protein translation. With demonstrated utility in both cultured cells and animals, this mRNA delivery technology should be broadly applicable to numerous research and therapeutic applications.
The flat wasp family Bethylidae Haliday lacks global scale literature on their alpha taxonomy. The only world revision for the family was by Kieffer in 1914 and is fully out of date and somewhat ...useless; the only catalog for the family was made by Gordh Móczár in 1990 and does not include hundreds of changes made since then; and the most recent world genera keys were proposed by Terayama in 2003, but do not reflect the current knowledge we have for the family. Given this scenario, we present a global guide of Bethylidae with diagnoses, taxonomic evaluation, keys, and a checklist of all their extant genera and subfamilies. We visited the main collections around the world, analyzed about 2,000 holotypes, and examined at least 400,000 specimens. To eliminate homonymies, we add the prefix "neo" to the original specific epithet when possible. The family is now composed by 2,920 species allocated in 96 genera distributed in eight subfamilies: Bethylinae, Pristocerinae, Epyrinae, Mesitiinae, Scleroderminae, Lancepyrinae, Holopsenellinae and Protopristocerinae. The latter three are extinct. One new family-group synonym is proposed: Fushunochrysidae Hong syn. nov. of Bethylidae. Two incertae sedis genera are allocated into Bethylinae: Cretobethylellus Rasnytsyn and Omaloderus Walker. One new genus-group synonym is revalidated: Pristepyris Kieffer stat. rev. from Acrepyris Kieffer. Sixteen new genus-group synonyms are proposed: Fushunochrysites Hong syn. nov. and Sinibethylus Hong syn. nov. of Eupsenella Westwood; Messoria Meunier syn. nov. of Goniozus Förster; Acrepyris Kieffer syn. nov. of Pristepyris Kieffer; Apristocera Kieffer syn. nov. and Parapristocera Brues syn. nov. of Pristocera Klug; Usakosia Kieffer syn. nov. of Prosapenesia Kieffer; Isobrachium Förster syn. nov., Leptepyris Kieffer syn. nov., Neodisepyris Kurian syn. nov., Rhabdepyris Kieffer syn. nov. of Epyris Westwood; Codorcas Nagy syn. nov., Hamusmus Argaman syn. nov. and Ukayakos Argaman syn. nov. of Heterocoelia Dahlbom; Domonkos Argaman syn. nov. of Incertosulcus Móczár; Ateleopterus Förster syn. nov. of Sclerodermus Latreille. One new genus-group synonym is revalidated: Topcobius Nagy syn. rev. of Sulcomesitius Móczár. One new genus-group revalidation is proposed: Incertosulcus Móczár stat. rev. from Anaylax Móczár. The following species-group nomenclatural acts are established: 153 new or revalidated combinations, 16 new names to avoid secondary homonyms, 11 species with revalidated status, and one synonym. Keys to the subfamilies and genera are provided. The text is supported by 599 illustrations organized onto 92 plates.
This paper presents a detailed description of finite control set model predictive control (FCS-MPC) applied to power converters. Several key aspects related to this methodology are, in depth, ...presented and compared with traditional power converter control techniques, such as linear controllers with pulsewidth-modulation-based methods. The basic concepts, operating principles, control diagrams, and results are used to provide a comparison between the different control strategies. The analysis is performed on a traditional three-phase voltage source inverter, used as a simple and comprehensive reference frame. However, additional topologies and power systems are addressed to highlight differences, potentialities, and challenges of FCS-MPC. Among the conclusions are the feasibility and great potential of FCS-MPC due to present-day signal-processing capabilities, particularly for power systems with a reduced number of switching states and more complex operating principles, such as matrix converters. In addition, the possibility to address different or additional control objectives easily in a single cost function enables a simple, flexible, and improved performance controller for power-conversion systems.
All living systems require biochemical barriers. As a consequence, all drugs, imaging agents, and probes have targets that are either on, in, or inside of these barriers. Fifteen years ago, we ...initiated research directed at more fully understanding these barriers and at developing tools and strategies for breaching them that could be of use in basic research, imaging, diagnostics, and medicine. At the outset of this research and now to a lesser extent, the “rules” for drug design biased the selection of drug candidates mainly to those with an intermediate and narrow log P. At the same time, it was becoming increasingly apparent that Nature had long ago developed clever strategies to circumvent these “rules.” In 1988, for example, independent reports documented the otherwise uncommon passage of a protein (HIV-Tat) across a membrane. A subsequent study implicated a highly basic domain in this protein (Tat49‑57) in its cellular entry. This conspicuously contradictory behavior of a polar, highly charged peptide passing through a nonpolar membrane set the stage for learning how Nature had gotten around the current “rules” of transport. As elaborated in our studies and discussed in this Account, the key strategy used in Nature rests in part on the ability of a molecule to change its properties as a function of microenvironment; such molecules need to be polarity chameleons, polar in a polar milieu and relatively nonpolar in a nonpolar environment. Because this research originated in part with the protein Tat and its basic peptide domain, Tat49‑57, the field focused heavily on peptides, even limiting its nomenclature to names such as “cell-penetrating peptides,” “cell-permeating peptides,” “protein transduction domains,” and “membrane translocating peptides.” Starting in 1997, through a systematic reverse engineering approach, we established that the ability of Tat49‑57 to enter cells is not a function of its peptide backbone, but rather a function of the number and spatial array of its guanidinium groups. These function-oriented studies enabled us and others to design more effective peptidic agents and to think beyond the confines of peptidic systems to new and even more effective nonpeptidic agents. Because the function of passage across a cell membrane is not limited to or even best achieved with the peptide backbone, we referred to these agents by their shared function, “cell-penetrating molecular transporters.” The scope of this molecular approach to breaching biochemical barriers has expanded remarkably in the past 15 years: enabling or enhancing the delivery of a wide range of cargos into cells and across other biochemical barriers, creating new tools for research, imaging, and diagnostics, and introducing new therapies into clinical trials.
The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant ...concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM2.5, PM10, O3, NO2, CO and SO2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM2.5, PM10 and SO2. Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments.
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•Air pollution exposures in Mexico City result in adverse health outcomes.•Land use regression models for six air pollutants were developed.•Hourly meteorology and traffic data facilitated finer timescale simulation.•A new regression method improved model performance.
We propose a machine-learning approach based on Bayesian optimization to build global potential energy surfaces (PES) for reactive molecular systems using feedback from quantum scattering ...calculations. The method is designed to correct for the uncertainties of quantum chemistry calculations and yield potentials that reproduce accurately the reaction probabilities in a wide range of energies. These surfaces are obtained automatically and do not require manual fitting of the ab initio energies with analytical functions. The PES are built from a small number of ab initio points by an iterative process that incrementally samples the most relevant parts of the configuration space. Using the dynamical results of previous authors as targets, we show that such feedback loops produce accurate global PES with 30 ab initio energies for the three-dimensional H + H2 → H2 + H reaction and 290 ab inito energies for the six-dimensional OH + H2 → H2O + H reaction. These surfaces are obtained from 360 scattering calculations for H3 and 600 scattering calculations for OH3. We also introduce a method that quickly converges to an accurate PES without the a priori knowledge of the dynamical results. By construction, our method illustrates the lowest number of potential energy points (i.e. the minimum information) required for the non-parametric construction of global PES for quantum reactive scattering calculations.
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