Field and Forage Crop Fertilization in the Lower Rio Grande Valley.

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Large-Scale Demonstration of Liquid Hydrogen Storage with Zero Boiloff for In-Space Applications

Cryocooler and passive insulation technology advances have substantially improved prospects for zero-boiloff cryogenic storage. Therefore, a cooperative effort by NASA s Ames Research Center, Glenn Research Center, and Marshall Space Flight Center (MSFC) was implemented to develop zero-boiloff concepts for in-space cryogenic storage. Described herein is one program element - a large-scale, zero-boiloff demonstration using the MSFC multipurpose hydrogen test bed (MHTB). A commercial cryocooler was interfaced with an existing MHTB spray bar mixer and insulation system in a manner that enabled a balance between incoming and extracted thermal energy

Cerebral blood flow predicts differential neurotransmitter activity

Application of metabolic magnetic resonance imaging measures such as cerebral blood flow in translational medicine is limited by the unknown link of observed alterations to specific neurophysiological processes. In particular, the sensitivity of cerebral blood flow to activity changes in specific neurotransmitter systems remains unclear. We address this question by probing cerebral blood flow in healthy volunteers using seven established drugs with known dopaminergic, serotonergic, glutamatergic and GABAergic mechanisms of action. We use a novel framework aimed at disentangling the observed effects to contribution from underlying neurotransmitter systems. We find for all evaluated compounds a reliable spatial link of respective cerebral blood flow changes with underlying neurotransmitter receptor densities corresponding to their primary mechanisms of action. The strength of these associations with receptor density is mediated by respective drug affinities. These findings suggest that cerebral blood flow is a sensitive brain-wide in-vivo assay of metabolic demands across a variety of neurotransmitter systems in humans

Feasibility Study of the Effects of Water Quality on Soil Properties in the Red River Valley

The suitability of water for irrigation depends upon many factors, of primary concern is the quantity and quality of salts present in the water Ayers and Wescot1. If total dissolved solids in the irrigation water are too high, salts accumulate in the crop root zone to the extent that yields are reduced. Excessive soil salinity means the crops have difficulty extracting water from the soil solution. The other problems with respect to salinity are concerned with the effects of water quality on permeability of soil to water. The effects of specific ions such as Na or lack of salts in the water can reduce permeability to the extent that crops are not adequately supplied with water and yields are reduced. As pointed out by Rhoades and Ingvalson > and Frenkel, Goertzen and Rhoades2 one of the major factors affecting the suitability of water for irrigation is its sodicity hazard usually expressed as SAR. According to these investigators, our greatest limitation in assessing the sodium hazard is our inability to predict how the water will affect soil structure and permeability. This may be because soil structural stability or instability is a function of many factors. The effect of Na on soil structure can be modified by other soil properties such as texture, organic matter, etc. In Texas, Naghshineh-Pour, Kunze and Carson (6) stated that sodium absorption ratio (SAR), exchangeable Na percentage (ESP), electrolyte concentration, clay content, free iron oxides and clay mineral species are important factors involved in permeability of selected soils. Saffaf (9) noted the decrease of unsaturated hydraulic conductivity with decreasing electrolyte concentrations and increasing the SAR (sodium absorption ratio) of the soil solution was especially pronounced for swelling clay soils. Water in the Red River Basin is often high in salinity and in sodium concentrations (high SAR). Studies evaluated the influences of present and "predicted after reclamation" dissolved solids (TDS) and SAR on permeability of different soils in the Red River Basin. These studies should give some insight as to the effect of present levels of SAR on soil structure and permeability. It was also the purpose of this investigation to evaluate the effects of reduced SAR and total dissolved solids(TDS) on soil permeability. The permeability to rainfall (low TDS) of soils leached with different levels of SAR and salinity was simulated and determined in the laboratory. 1 Contributions of Texas AGM Research and Extension Center at Chillicothe-Vernon, Dallas, Munday and Texas A&M Water Resources Institute; College Station and supported in part by the Tulsa District, U.S. Corps of Engineers. 2 Professor, Chillicothe-Vernon; Associate Professor, Dallas; Director, Water Resources Institute, College Station; Research Engineer, Munday; and formerly Professor, Chillicothe-Vernon

Evaluation of database technologies for the CTBT Knowledge Base prototype

This document examines a number of different software technologies in the rapidly changing field of database management systems, evaluates these systems in light of the expected needs of the Comprehensive Test Ban Treaty (CTBT) Knowledge Base, and makes some recommendations for the initial prototypes of the Knowledge Base. The Knowledge Base requirements are examined and then used as criteria for evaluation of the database management options. A mock-up of the data expected in the Knowledge Base is used as a basis for examining how four different database technologies deal with the problems of storing and retrieving the data. Based on these requirement and the results of the evaluation, the recommendation is that the Illustra database be considered for the initial prototype of the Knowledge Base. Illustra offers a unique blend of performance, flexibility, and features that will aid in the implementation of the prototype. At the same time, Illustra provides a high level of compatibility with the hardware and software environments present at the US NDC (National Data Center) and the PIDC (Prototype International Data Center)

Learning Interpretable Rules for Multi-label Classification

Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously. In this chapter, we advocate a rule-based approach to multi-label classification. Rule learning algorithms are often employed when one is not only interested in accurate predictions, but also requires an interpretable theory that can be understood, analyzed, and qualitatively evaluated by domain experts. Ideally, by revealing patterns and regularities contained in the data, a rule-based theory yields new insights in the application domain. Recently, several authors have started to investigate how rule-based models can be used for modeling multi-label data. Discussing this task in detail, we highlight some of the problems that make rule learning considerably more challenging for MLC than for conventional classification. While mainly focusing on our own previous work, we also provide a short overview of related work in this area.Comment: Preprint version. To appear in: Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning. Springer (2018). See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3077 for further informatio

Heisenberg's Uncertainty Relation and Bell Inequalities in High Energy Physics

An effective formalism is developed to handle decaying two-state systems. Herewith, observables of such systems can be described by a single operator in the Heisenberg picture. This allows for using the usual framework in quantum information theory and, hence, to enlighten the quantum feature of such systems compared to non-decaying systems. We apply it to systems in high energy physics, i.e. to oscillating meson-antimeson systems. In particular, we discuss the entropic Heisenberg uncertainty relation for observables measured at different times at accelerator facilities including the effect of CP violation, i.e. the imbalance of matter and antimatter. An operator-form of Bell inequalities for systems in high energy physics is presented, i.e. a Bell-witness operator, which allows for simple analysis of unstable systems.Comment: 17 page

A clinical genetic method to identify mechanisms by which pain causes depression and anxiety

BACKGROUND: Pain patients are often depressed and anxious, and benefit less from psychotropic drugs than pain-free patients. We hypothesize that this partial resistance is due to the unique neurochemical contribution to mood by afferent pain projections through the spino-parabrachial-hypothalamic-amygdalar systems and their projections to other mood-mediating systems. New psychotropic drugs for pain patients might target molecules in such brain systems. We propose a method to prioritize molecular targets by studying polymorphic genes in cohorts of patients undergoing surgical procedures associated with a variable pain relief response. We seek molecules that show a significant statistical interaction between (1) the amount of surgical pain relief, and (2) the alleles of the gene, on depression and anxiety during the first postoperative year. RESULTS: We collected DNA from 280 patients with sciatica due to a lumbar disc herniation, 162 treated surgically and 118 non-surgically, who had been followed for 10 years in the Maine Lumbar Spine Study, a large, prospective, observational study. In patients whose pain was reduced >25% by surgery, symptoms of depression and anxiety, assessed with the SF-36 Mental Health Scale, improved briskly at the first postoperative measurement. In patients with little or no surgical pain reduction, mood scores stayed about the same on average. There was large inter-individual variability at each level of residual pain. Polymorphisms in three pre-specified pain-mood candidate genes, catechol-O-methyl transferase (COMT), serotonin transporter, and brain-derived neurotrophic factor (BDNF) were not associated with late postoperative mood or with a pain-gene interaction on mood. Although the sample size did not provide enough power to persuasively search through a larger number of genes, an exploratory survey of 25 other genes provides illustrations of pain-gene interactions on postoperative mood – the mu opioid receptor for short-term effects of acute sciatica on mood, and the galanin-2 receptor for effects of unrelieved post-discectomy pain on mood one year after surgery. CONCLUSION: Genomic analysis of longitudinal studies of pain, depression, and anxiety in patients undergoing pain-relieving surgery may help to identify molecules through which pain alters mood. Detection of alleles with modest-sized effects will require larger cohorts

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives