726,967 research outputs found

    Relation of lime and magnesium to plant growth in Missouri soils

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    TypescriptM.A. University of Missouri 1909The relation of lime and magnesium to each other in plant growth is a problem over which the Agronomist and Plant Physiologist have stumbled for some time, and before its solution is finally reached, will likely involve the consideration of several other mineral elements which are not now generally believed to function with them. It has been known ever since the time of Aristotle that lime is beneficial to most soils, and since then it has been used in all its forms as a condiment; sometimes with success; sometimes with medium results and sometimes with apparent failure. SIR JOHN BENNET LAWS and SIR JOSEPH HENRY GILBERT were the first to make accurate observations upon the practice of liming. They found that the white or "fat lime" would produce better yields than the gray or "poor lime" which was sometimes injurious. From observations of this kind there has grown up the practice of applying lime to soils stiff and poor in texture. Magnesium on the other hand is never applied since it has no such beneficial action, and is supposed to exist in sufficient quantities for all necessary needs of plant growth. This in general is true, as most soils in America and Foreign Countries, contain more lime than magnesium. However, there are instances where the magnesium content of some soils is below that of lime, and applications of magnesium to these soils would be found beneficial. It will be the purpose of the following pages of this paper to discuss the Physical, Chemical, Bacteriological and Physiological relations of Calcium and Magnesium to soils and their effects upon plant growth. And while some of these theories are somewhat obsolete, the majority are new and apparently true.Includes bibliographical reference

    THE ARCHITECTURE OF ENABLING TECHNOLOGY IN THE CRITICAL CARE SETTING: THE ROLE OF ARCHITECTURE IN ADDRESSING THE HEALTH CARE - TECHNOLOGY PARADOX

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    Health care architecture, particularly tertiary care settings, which have the sickest people, and most advanced medical care, should accommodate and employ technology in ways that are both therapeutic and enabling. Although technology in the tertiary care setting is generally considered beneficial, it can sometimes have negative impacts, cause stress and result in poor health outcomes. Norman Cousins said in his book Anatomy of an Illness, \u27Many doctors are increasingly aware of the circular paradox [of the intensive care unit]. It provides better electronic aids than ever before for dealing with emergencies that are often intensified because they communicate a sense of imminent disaster to the patient.\u27 These negative side effects are typically the result of disabling technology, which above all restricts a patients\u27 ability to have and to sense comfort and control. This health care - technology paradox is often activated through medical equipment, medical practices and medical settings. When medical practices and medical equipment are disabling and do not sufficiently enabling comfort and control, then the medical setting can play a role in helping to temper the paradox and hence the total impact technologies have on the patient

    Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks

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    The growing energy and performance costs of deep learning have driven the community to reduce the size of neural networks by selectively pruning components. Similarly to their biological counterparts, sparse networks generalize just as well, sometimes even better than, the original dense networks. Sparsity promises to reduce the memory footprint of regular networks to fit mobile devices, as well as shorten training time for ever growing networks. In this paper, we survey prior work on sparsity in deep learning and provide an extensive tutorial of sparsification for both inference and training. We describe approaches to remove and add elements of neural networks, different training strategies to achieve model sparsity, and mechanisms to exploit sparsity in practice. Our work distills ideas from more than 300 research papers and provides guidance to practitioners who wish to utilize sparsity today, as well as to researchers whose goal is to push the frontier forward. We include the necessary background on mathematical methods in sparsification, describe phenomena such as early structure adaptation, the intricate relations between sparsity and the training process, and show techniques for achieving acceleration on real hardware. We also define a metric of pruned parameter efficiency that could serve as a baseline for comparison of different sparse networks. We close by speculating on how sparsity can improve future workloads and outline major open problems in the field

    Full of care : young carers in Wales 2009 = Bywyd llawn gofal : gofalwyr ifanc yng Nghymru 2009

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    Scottish survey of achievement: 2008 Scottish survey of achievement: mathematics and core skills

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