243 research outputs found

    Keys to Profitable Soybean Production.

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    Constraint-based, Single-point Approximate Kinetic Energy Functionals

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    We present a substantial extension of our constraint-based approach for development of orbital-free (OF) kinetic-energy (KE) density functionals intended for the calculation of quantum-mechanical forces in multi-scale molecular dynamics simulations. Suitability for realistic system simulations requires that the OF-KE functional yield accurate forces on the nuclei yet be relatively simple. We therefore require that the functionals be based on DFT constraints, local, dependent upon a small number of parameters fitted to a training set of limited size, and applicable beyond the scope of the training set. Our previous "modified conjoint" generalized-gradient-type functionals were constrained to producing a positive-definite Pauli potential. Though distinctly better than several published GGA-type functionals in that they gave semi-quantitative agreement with Born-Oppenheimer forces from full Kohn-Sham results, those modified conjoint functionals suffer from unphysical singularities at the nuclei. Here we show how to remove such singularities by introducing higher-order density derivatives. We give a simple illustration of such a functional used for the dissociation energy as a function of bond length for selected molecules.Comment: 16 pages, 9 figures, 2 tables, submitted to Phys. Rev.

    What Ukraine Taught NATO about Hybrid Warfare

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    Russia’s invasion of Ukraine in 2022 forced the United States and its NATO partners to be confronted with the impact of hybrid warfare far beyond the battlefield. Targeting Europe’s energy security, Russia’s malign influence campaigns and malicious cyber intrusions are affecting global gas prices, driving up food costs, disrupting supply chains and grids, and testing US and Allied military mobility. This study examines how hybrid warfare is being used by NATO’s adversaries, what vulnerabilities in energy security exist across the Alliance, and what mitigation strategies are available to the member states. Cyberattacks targeting the renewable energy landscape during Europe’s green transition are increasing, making it urgent that new tools are developed to protect these emerging technologies. No less significant are the cyber and information operations targeting energy security in Eastern Europe as it seeks to become independent from Russia. Economic coercion is being used against Western and Central Europe to stop gas from flowing. China’s malign investments in Southern and Mediterranean Europe are enabling Beijing to control several NATO member states’ critical energy infrastructure at a critical moment in the global balance of power. What Ukraine Taught NATO about Hybrid Warfare will be an important reference for NATO officials and US installations operating in the European theater.https://press.armywarcollege.edu/monographs/1952/thumbnail.jp

    Dynamical downscaling of tropical cyclones from CCSM4 simulations of the Last Glacial Maximum

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    Dynamical downscaling of simulations of the Last Glacial Maximum (LGM) and late twentieth century (20C) were conducted using the Weather Research and Forecasting (WRF) model with the aim of (1) understanding how the downscaled kinematic and thermodynamic variables influence simulated tropical cyclone (TC) activity over the western North Pacific during the LGM and the 20C periods and (2) to test the relevance of TC genesis factors for the colder LGM climate. The results show that, despite the lower temperatures during the LGM, the downscaled TC climatology over the western North Pacific in the LGM simulation does not differ significantly from that in the 20C simulation. Among the TC environmental factors, the TC potential intensity, mid‐tropospheric entropy deficit, and vertical wind shear during the LGM were consistent with previous analyses of TC genesis factors in LGM global climate model simulations. Changes in TC genesis density between the LGM and the 20C simulations seem to be well represented by the ventilation index, a nondimensional measure of the combined effects of vertical wind shear, and thermodynamic properties, suggesting the potential applicability of those factors for TC activity evaluation during the LGM and possibly other climates

    Self-labeling techniques for semi-supervised time series classification: an empirical study

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    An increasing amount of unlabeled time series data available render the semi-supervised paradigm a suitable approach to tackle classification problems with a reduced quantity of labeled data. Self-labeled techniques stand out from semi-supervised classification methods due to their simplicity and the lack of strong assumptions about the distribution of the labeled and unlabeled data. This paper addresses the relevance of these techniques in the time series classification context by means of an empirical study that compares successful self-labeled methods in conjunction with various learning schemes and dissimilarity measures. Our experiments involve 35 time series datasets with different ratios of labeled data, aiming to measure the transductive and inductive classification capabilities of the self-labeled methods studied. The results show that the nearest-neighbor rule is a robust choice for the base classifier. In addition, the amending and multi-classifier self-labeled-based approaches reveal a promising attempt to perform semi-supervised classification in the time series context

    A genetically anchored physical framework for Theobroma cacao cv. Matina 1-6

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    <p>Abstract</p> <p>Background</p> <p>The fermented dried seeds of <it>Theobroma cacao </it>(cacao tree) are the main ingredient in chocolate. World cocoa production was estimated to be 3 million tons in 2010 with an annual estimated average growth rate of 2.2%. The cacao bean production industry is currently under threat from a rise in fungal diseases including black pod, frosty pod, and witches' broom. In order to address these issues, genome-sequencing efforts have been initiated recently to facilitate identification of genetic markers and genes that could be utilized to accelerate the release of robust <it>T. cacao </it>cultivars. However, problems inherent with assembly and resolution of distal regions of complex eukaryotic genomes, such as gaps, chimeric joins, and unresolvable repeat-induced compressions, have been unavoidably encountered with the sequencing strategies selected.</p> <p>Results</p> <p>Here, we describe the construction of a BAC-based integrated genetic-physical map of the <it>T. cacao </it>cultivar Matina 1-6 which is designed to augment and enhance these sequencing efforts. Three BAC libraries, each comprised of 10× coverage, were constructed and fingerprinted. 230 genetic markers from a high-resolution genetic recombination map and 96 Arabidopsis-derived conserved ortholog set (COS) II markers were anchored using pooled overgo hybridization. A dense tile path consisting of 29,383 BACs was selected and end-sequenced. The physical map consists of 154 contigs and 4,268 singletons. Forty-nine contigs are genetically anchored and ordered to chromosomes for a total span of 307.2 Mbp. The unanchored contigs (105) span 67.4 Mbp and therefore the estimated genome size of <it>T. cacao </it>is 374.6 Mbp. A comparative analysis with <it>A. thaliana, V. vinifera</it>, and <it>P. trichocarpa </it>suggests that comparisons of the genome assemblies of these distantly related species could provide insights into genome structure, evolutionary history, conservation of functional sites, and improvements in physical map assembly. A comparison between the two <it>T. cacao </it>cultivars Matina 1-6 and Criollo indicates a high degree of collinearity in their genomes, yet rearrangements were also observed.</p> <p>Conclusions</p> <p>The results presented in this study are a stand-alone resource for functional exploitation and enhancement of <it>Theobroma cacao </it>but are also expected to complement and augment ongoing genome-sequencing efforts. This resource will serve as a template for refinement of the <it>T. cacao </it>genome through gap-filling, targeted re-sequencing, and resolution of repetitive DNA arrays.</p

    A global collaboration to study intimate partner violence-related head trauma: The ENIGMA consortium IPV working group

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    Intimate partner violence includes psychological aggression, physical violence, sexual violence, and stalking from a current or former intimate partner. Past research suggests that exposure to intimate partner violence can impact cognitive and psychological functioning, as well as neurological outcomes. These seem to be compounded in those who suffer a brain injury as a result of trauma to the head, neck or body due to physical and/or sexual violence. However, our understanding of the neurobehavioral and neurobiological effects of head trauma in this population is limited due to factors including difficulty in accessing/recruiting participants, heterogeneity of samples, and premorbid and comorbid factors that impact outcomes. Thus, the goal of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium Intimate Partner Violence Working Group is to develop a global collaboration that includes researchers, clinicians, and other key community stakeholders. Participation in the working group can include collecting harmonized data, providing data for meta- and mega-analysis across sites, or stakeholder insight on key clinical research questions, promoting safety, participant recruitment and referral to support services. Further, to facilitate the mega-analysis of data across sites within the working group, we provide suggestions for behavioral surveys, cognitive tests, neuroimaging parameters, and genetics that could be used by investigators in the early stages of study design. We anticipate that the harmonization of measures across sites within the working group prior to data collection could increase the statistical power in characterizing how intimate partner violence-related head trauma impacts long-term physical, cognitive, and psychological health

    Statistical Analysis of Molecular Signal Recording

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    A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed a “molecular ticker tape”, in which an engineered DNA polymerase (DNAP) writes time-varying signals into DNA in the form of nucleotide misincorporation patterns. Here, we define a theoretical framework quantifying the expected capabilities of molecular ticker tapes as a function of experimental parameters. We present a decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters, directly from misincorporation rates as determined by sequencing. We explore the requirements for accurate signal decoding, particularly the constraints on (1) the polymerase biochemical parameters, and (2) the amplitude, temporal resolution, and duration of the time-varying input signals. Our results suggest that molecular recording devices with kinetic properties similar to natural polymerases could be used to perform experiments in which neural activity is compared across several experimental conditions, and that devices engineered by combining favorable biochemical properties from multiple known polymerases could potentially measure faster phenomena such as slow synchronization of neuronal oscillations. Sophisticated engineering of DNAPs is likely required to achieve molecular recording of neuronal activity with single-spike temporal resolution over experimentally relevant timescales.United States. Defense Advanced Research Projects Agency. Living Foundries ProgramGoogle (Firm)New York Stem Cell Foundation. Robertson Neuroscience Investigator AwardNational Institutes of Health (U.S.) (EUREKA Award 1R01NS075421)National Institutes of Health (U.S.) (Transformative R01 1R01GM104948)National Institutes of Health (U.S.) (Single Cell Grant 1 R01 EY023173)National Institutes of Health (U.S.) (Grant 1R01DA029639)National Institutes of Health (U.S.) (Grant 1R01NS067199)National Science Foundation (U.S.) (CAREER Award CBET 1053233)National Science Foundation (U.S.) (Grant EFRI0835878)National Science Foundation (U.S.) (Grant DMS1042134)Paul G. Allen Family Foundation (Distinguished Investigator in Neuroscience Award
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