Visual Code: Breaking the Binary

This project seeks to create an accessible programming language that is more visually based. Although some solutions exist, namely MIT’s Scratch, nothing has caught up to the mobile age. This proj- ect aims to reframe creating a game or app into the context of tell- ing a story, putting character creation first. By researching sto- ry-telling and how people learn, and by applying technical and user interface design knowledge, this project intends to deliver a soft- ware solution that opens introductory coding education to more people

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Incidence and phenotypes of childhood-onset genetic epilepsies:a prospective population-based national cohort

Epilepsy is common in early childhood. In this age group it is associated with high rates of therapy-resistance, and with cognitive, motor, and behavioural comorbidity. A large number of genes, with wide ranging functions, are implicated in its aetiology, especially in those with therapy-resistant seizures. Identifying the more common single-gene epilepsies will aid in targeting resources, the prioritization of diagnostic testing and development of precision therapy. Previous studies of genetic testing in epilepsy have not been prospective and population-based. Therefore, the population-incidence of common genetic epilepsies remains unknown. The objective of this study was to describe the incidence and phenotypic spectrum of the most common single-gene epilepsies in young children, and to calculate what proportion are amenable to precision therapy. This was a prospective national epidemiological cohort study. All children presenting with epilepsy before 36 months of age were eligible. Children presenting with recurrent prolonged (>10 min) febrile seizures; febrile or afebrile status epilepticus (>30 min); or with clusters of two or more febrile or afebrile seizures within a 24-h period were also eligible. Participants were recruited from all 20 regional paediatric departments and four tertiary children’s hospitals in Scotland over a 3-year period. DNA samples were tested on a custom-designed 104-gene epilepsy panel. Detailed clinical information was systematically gathered at initial presentation and during follow-up. Clinical and genetic data were reviewed by a multidisciplinary team of clinicians and genetic scientists. The pathogenic significance of the genetic variants was assessed in accordance with the guidelines of UK Association of Clinical Genetic Science (ACGS). Of the 343 patients who met inclusion criteria, 333 completed genetic testing, and 80/333 (24%) had a diagnostic genetic finding. The overall estimated annual incidence of single-gene epilepsies in this well-defined population was 1 per 2120 live births (47.2/100 000; 95% confidence interval 36.9–57.5). PRRT2 was the most common single-gene epilepsy with an incidence of 1 per 9970 live births (10.0/100 000; 95% confidence interval 5.26–14.8) followed by SCN1A: 1 per 12 200 (8.26/100 000; 95% confidence interval 3.93–12.6); KCNQ2: 1 per 17 000 (5.89/100 000; 95% confidence interval 2.24–9.56) and SLC2A1: 1 per 24 300 (4.13/100 000; 95% confidence interval 1.07–7.19). Presentation before the age of 6 months, and presentation with afebrile focal seizures were significantly associated with genetic diagnosis. Single-gene disorders accounted for a quarter of the seizure disorders in this cohort. Genetic testing is recommended to identify children who may benefit from precision treatment and should be mainstream practice in early childhood onset epilepsy

Global Carbon Budget 2018

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018

Neural Network Potentials for Reactive Chemistry: CASPT2 Quality Potential Energy Surfaces for Bond Breaking

Neural Network potentials are developed which accurately make and break bonds for use in molecular simulations. We report a neural network potential that can describe the potential energy surface for carbon-carbon bond dissociation with less than 1 kcal/mol error compared to complete active space second-order perturbation theory (CASPT2), and maintains this accuracy for both the minimum energy path and molecular dynamic calculations up to 2000K. We utilize a transfer learning algorithm to develop neural network potentials to generate potential energy surfaces; this method aims to use the minimum amount of CASPT2 data on small systems to train neural network potentials while maintaining excellent transferability to larger systems. First, we generate homolytic carbon-carbon bond dissociation data of small size alkanes with density functional theory (DFT) energies to train the potentials to accurately predict bond dissociation at the DFT level. Then, using transfer learning, we retrained the neural network potential to CASPT2 level of accuracy. We demonstrate that the neural network potential only requires bond dissociation data of a few small alkanes to accurately predict bond dissociation energy in larger alkanes. We then perform additional training on molecular dynamic simulations to refine our neural network potentials to obtain high accuracy for general use in molecular simulation. This training algorithm is generally applicable to any type of bond or any level of theory and will be useful for the generation of new reactive neural network potentials

Thin film nanoporous electrodes for the selective catalysis of oxygen in abiotically catalysed micro glucose fuel cells

Selective reduction of oxygen is an important property of fuel cells designed to operate in a mixed fuel environment containing both oxidizing and reducing reactants. This would be of particular importance in the design of a long-lasting energy supply unit powering implantable microsystems and running from exogeneous chemicals that is abundant in the body (such as glucose and oxygen). This paper presents the development of a nanoporous electrode for oxygen reduction in the presence of glucose. The electrode was fabricated by e-beam deposition of palladium thin films on porous ceramic aluminium oxide (AAO) substrates with a pore size of 100 and 200 nm, respectively. The porous nature of the electrodes improved the catalytic properties by increasing the real surface area close to 100 times the geometric surface area. At a dissolved physiological oxygen (DO) concentration of 2 ppm, the maximum exchange current density was found to be 2.9 × 10−3 ± 0.5 × 10−3 μA cm−2, whereas the potential reduction due to the addition of 5 mM glucose was about 20.6 ± 16.1 mV. The Tafel slopes were measured to be about 60 mV per decade. After running for 21 h in a physiological saline solution with 2 ppm DO and 3 mM glucose, the reduction in the electrode operational potential was −0.13 mV h−1 under a load current density of 4.4 μA cm−2. These results suggest that nanoporous AAO cathodes coated with palladium offer a reasonable catalytic performance with a good selectivity towards oxygen in the presence of glucose

Genome-Wide Association study of susceptibility to respiratory syncytial virus hospitalization in young children < 5 years of age

Background. Worldwide, respiratory syncytial virus (RSV) infections are among the most common causes of infant hospitalization. Host genetic factors influencing the risk and severity of RSV infection are not well known.Methods. We conducted a genome-wide association study (GWAS) to investigate single-nucleotide polymorphisms (SNPs) associated with severe RSV infections using a nested case-control design based on 2 Danish cohorts. We compared SNPs from 1786 children hospitalized with RSV to 45 060 controls without an RSV-coded hospitalization. We performed gene-based testing, tissue enrichment, gene-set enrichment, and a meta-analysis of the 2 cohorts. Finally, an analysis of potential associations between the severity of RSV infection and genetic markers was performed.Results. We did not detect any significant genome-wide associations between SNPs and RSV infection or the severity of RSV. We did find potential loci associated with RSV infections on chromosome 5 in 1 cohort but failed to replicate any signals in both cohorts.Conclusions. Despite being the largest GWAS of severe RSV infection, we did not detect any genome-wide significant loci. This may be an indication of a lack of power or an absence of signal. Future studies might include mild illness and need to be larger to detect any significant associations