Less Than 2 °C Warming by 2100 Unlikely.

The recently published Intergovernmental Panel on Climate Change (IPCC) projections to 2100 give likely ranges of global temperature increase in four scenarios for population, economic growth and carbon use1. However these projections are not based on a fully statistical approach. Here we use a country-specific version of Kaya's identity to develop a statistically-based probabilistic forecast of CO2 emissions and temperature change to 2100. Using data for 1960-2010, including the UN's probabilistic population projections for all countries2-4, we develop a joint Bayesian hierarchical model for GDP per capita and carbon intensity. We find that the 90% interval for cumulative CO2 emissions includes the IPCC's two middle scenarios but not the extreme ones. The likely range of global temperature increase is 2.0-4.9°C, with median 3.2°C and a 5% (1%) chance that it will be less than 2°C (1.5°C). Population growth is not a major contributing factor. Our model is not a "business as usual" scenario, but rather is based on data which already show the effect of emission mitigation policies. Achieving the goal of less than 1.5°C warming will require carbon intensity to decline much faster than in the recent past

Clinical Knowledge Graph Embedding Representation Bridging the Gap between Electronic Health Records and Prediction Models

Learning knowledge embedding representation is an increasingly important technology. However, the choice of hyperparameters is seldom justified and usually relies on exhaustive search. Understanding the effect of hyperparameter combinations on embedding quality is crucial to avoid the inefficient process and enhance practicality of embedding representation along subsequent machine learning applications. This work focuses on translational embedding models for multi-relational categorized data in the clinical domain. We trained and evaluated models with different combinations of hyperparameters on two clinical datasets. We contrasted the results by comparing metric distributions and fitting a random forest regression model. Classifiers were trained to assess embedding representation quality. Finally, clustering was tested as a validation protocol. We observed consistent patterns of hyperparameter preference and identified those that achieved better results respectively. However, results show different patterns regarding link prediction, which is taken as strong evidence that traditional evaluation protocol used for open-domain data does not necessarily lead to the best embedding representation for categorized data

Design optimization of hot stamping tooling produced by additive manufacturing

The design flexibility of Additive Manufacturing (AM) can be utilized to develop innovative and sustainable hot stamping tools with enhanced quenching capability compared to tools manufactured by conventional manufacturing processes. This study proposes a concept for hot stamping tools with integrated lattice structures that selectively substitute a die's solid areas. A lattice structure demonstrates reduced thermal mass and can affect the ability of the tool to absorb heat from the blank and the rate at which the tool is cooled between two consecutive stamping cycles. This study explores the design space of a hot stamping tool with integrated lattice structures. It presents the optimized design for an effective compromise between cooling performance, structural integrity, and several other design parameters shown in the study. The proposed method utilizes a 2D thermo-mechanical finite element analysis model of a single cooling channel combined with Design of Experiments (DoE) to reduce the computational cost. The results show that the integration of lattice structure cannot only deliver improved cooling performance with minimum change in the dimensions of the cooling system but also achieves a faster AM build time since less material is required to be printed

A parabolic approach to the control of opinion spreading

We analyze the problem of controlling to consensus a nonlinear system modeling opinion spreading. We derive explicit exponential estimates on the cost of approximately controlling these systems to consensus, as a function of the number of agents N and the control time-horizon T. Our strategy makes use of known results on the controllability of spatially discretized semilinear parabolic equations. Both systems can be linked through time-rescalin

Evidence for Superfluidity of Ultracold Fermions in an Optical Lattice

The study of superfluid fermion pairs in a periodic potential has important ramifications for understanding superconductivity in crystalline materials. Using cold atomic gases, various condensed matter models can be studied in a highly controllable environment. Weakly repulsive fermions in an optical lattice could undergo d-wave pairing at low temperatures, a possible mechanism for high temperature superconductivity in the cuprates. The lattice potential could also strongly increase the critical temperature for s-wave superfluidity. Recent experimental advances in the bulk include the observation of fermion pair condensates and high-temperature superfluidity. Experiments with fermions and bosonic bound pairs in optical lattices have been reported, but have not yet addressed superfluid behavior. Here we show that when a condensate of fermionic atom pairs was released from an optical lattice, distinct interference peaks appear, implying long range order, a property of a superfluid. Conceptually, this implies that strong s-wave pairing and superfluidity have now been established in a lattice potential, where the transport of atoms occurs by quantum mechanical tunneling and not by simple propagation. These observations were made for unitarity limited interactions on both sides of a Feshbach resonance. For larger lattice depths, the coherence was lost in a reversible manner, possibly due to a superfluid to insulator transition. Such strongly interacting fermions in an optical lattice can be used to study a new class of Hamiltonians with interband and atom-molecule couplings.Comment: accepted for publication in Natur

Finite temperature phase diagram of a polarised Fermi condensate

The two-component Fermi gas is the simplest fermion system displaying superfluidity, and as such finds applications ranging from the theory of superconductivity to QCD. Ultracold atomic gases provide an exceptionally clean realization of this system, where the interatomic interaction and the atom species population are both independent, tuneable parameters. This allows one to investigate the Fermi gas with imbalanced spin populations, which had previously been experimentally elusive, and this prospect has stimulated much theoretical activity. Here we show that the finite temperature phase diagram contains a region of phase separation between the superfluid and normal states that touches the boundary of second-order superfluid transitions at a tricritical point, reminiscent of the phase diagram of $^3$He-$^4$He mixtures. A variation of interaction strength then results in a line of tricritical points that terminates at zero temperature on the molecular Bose-Einstein condensate (BEC) side. On this basis, we argue that tricritical points will play an important role in the recent experiments on polarised atomic Fermi gases.Comment: 6 pages, 4 figures. Manuscript extended and figures modified. For final version, see Nature Physic

Collisions of low-energy antiprotons with molecular hydrogen: ionization, excitation and stopping power

A time-dependent coupled-channel approach was used to calculate ionization, excitation, and energy-loss cross sections as well as energy spectra for antiproton and proton collisions with molecular hydrogen for impact energies 8 keV < E < 4000 keV.Comment: 4 pages, 4 figures, conference LEAP0

Generation and quality control of lipidomics data for the alzheimers disease neuroimaging initiative cohort.

Alzheimers disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/

Electromagnetic wave diffraction by periodic planar metamaterials with nonlinear constituents

We present a theory which explains how to achieve an enhancement of nonlinear effects in a thin layer of nonlinear medium by involving a planar periodic structure specially designed to bear a trapped-mode resonant regime. In particular, the possibility of a nonlinear thin metamaterial to produce the bistable response at a relatively low input intensity due to a large quality factor of the trapped-mode resonance is shown. Also a simple design of an all-dielectric low-loss silicon-based planar metamaterial which can provide an extremely sharp resonant reflection and transmission is proposed. The designed metamaterial is envisioned for aggregating with a pumped active medium to achieve an enhancement of quantum dots luminescence and to produce an all-dielectric analog of a 'lasing spaser'.Comment: 18 pages, 13 figure

Allitridi Inhibits Multiple Cardiac Potassium Channels Expressed in HEK 293 Cells

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