548 research outputs found

    Neurological soft signs in persons with amnestic mild cognitive impairment and the relationships to neuropsychological functions

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    BACKGROUND: Neurological abnormalities have been reported in people with amnestic mild cognitive impairment (aMCI). The current study aimed to examine the prevalence of neurological soft signs (NSS) in this clinical group and to examine the relationship of NSS to other neuropsychological performances. METHODS: Twenty-nine people with aMCI and 28 cognitively healthy elderly people were recruited for the present study. The NSS subscales (motor coordination, sensory integration, and disinhibition) of the Cambridge Neurological Inventory and a set of neuropsychological tests were administered to all the participants. RESULTS: People with aMCI exhibited significantly more motor coordination signs, disinhibition signs, and total NSS than normal controls. Correlation analysis showed that the motor coordination subscale score and total score of NSS were significantly inversely correlated with the combined Z-score of neuropsychological tests in aMCI group. CONCLUSIONS: These preliminary findings suggested that people with aMCI demonstrated a higher prevalence of NSS compared to healthy elderly people. Moreover, NSS was found to be inversely correlated with the neuropsychological performances in persons with aMCI. When taken together, these findings suggested that NSS may play a potential important role and serve as a tool to assist in the early detection of aMCI

    Remarks on self-interaction correction to black hole radiation

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    In the work [P. Kraus and F. Wilczek, \textit{Self-interaction correction to black hole radiation, Nucl. Phys.} B433 (1995) 403], it has been pointed out that the self-gravitation interaction would modify the black hole radiation so that it is no longer thermal, where it is, however, corrected in an approximate way and therefore is not established its relationship with the underlying unitary theory in quantum theory. In this paper, we revisit the self-gravitation interaction to Hawking radiation of the general spherically symmetric black hole, and find that the precisely derived spectrum is not only deviated from the purely thermal spectrum, but most importantly, is related to the change of the Bekenstein-Hawking entropy and consistent with an underlying unitary theory.Comment: 14 page

    Statistical Interpretation of Joint Multiplicity Distributions of Neutrons and Charged Particles

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    Experimental joint multiplicity distributions of neutrons and charged particles emitted in complex nuclear reactions provide an important test of theoretical models. The method is applied to test three different theoretical models of nuclear multi-fragmentation, two of which fail the test. The measurement of neutrons is decisive in distinguishing between the Berlin and Copenhagen models of nuclear multi-fragmentation and challenges the interpretation of pseudo- Arrhenius plots. Statistical-model evaporation calculations with GEMINI give a good reproduction first and second moments of the experimental multiplicity correlations.Comment: 12 pages, 3 figures Added GEMINI calculations of multiplicity correlations Added brief discussion of how neutron emission is treated in MMM

    Filtering and Tracking with Trinion-Valued Adaptive Algorithms

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    A new model for three-dimensional processes based on the trinion algebra is introduced for the first time. Compared with the pure quaternion model, the trinion model is more compact and computationally more efficient, while having similar or comparable performance in terms of adaptive linear filtering. Moreover, the trinion model can effectively represent the general relationship of state evolution in Kalman filtering, where the pure quaternion model fails. Simulations on real-world wind recordings and synthetic data sets are provided to demonstrate the potentials of this new modeling method

    Affective design using machine learning : a survey and its prospect of conjoining big data

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    Customer satisfaction in purchasing new products is an important issue that needs to be addressed in today’s competitive markets. Consumers not only need to be solely satisfied with the functional requirements of a product, and they are also concerned with the affective needs and aesthetic appreciation of the product. A product with good affective design excites consumer emotional feelings so as to buy the product. However, affective design often involves complex and multi-dimensional problems for modelling and maximising affective satisfaction of customers. Machine learning is commonly used to model and maximise the affective satisfaction, since it is effective in modelling nonlinear patterns when numerical data relevant to the patterns is available. This article presents a survey of commonly used machine learning approaches for affective design when two data streams namely traditional survey data and modern big data are used. A classification of machine learning technologies is first provided which is developed using traditional survey data for affective design. The limitations and advantages of each machine learning technology are also discussed and we summarize the uses of machine learning technologies for affective design. This review article is useful for those who use machine learning technologies for affective design. The limitations of using traditional survey data are then discussed which is time consuming to collect and cannot fully cover all the affective domains for product development. Nowadays, big data related to affective design can be captured from social media. The prospects and challenges in using big data are discussed so as to enhance affective design, in which very limited research has so far been attempted. This article provides guidelines for researchers who are interested in exploring big data and machine learning technologies for affective design

    Microwave assisted low temperature synthesis of MnZn ferrite nanoparticles

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    MnZnFe2O4ferrite nanoparticles were prepared by co-precipitation method using a microwave heating system at temperature of 100 °C. X-ray diffraction reveals the samples as prepared are pure ferrite nanocrystalline phase, transmission electron microscopy image analysis shows particles are in agglomeration state with an average size of about 10 nm, furthermore, crystal size of samples are increased with longer microwave heating

    Interventions Targeting Child Undernutrition in Developing Countries May Be Undermined by Dietary Exposure to Aflatoxin

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    Child undernutrition, a form of malnutrition, is a major public health burden in developing countries. Supplementation interventions targeting the major micronutrient deficiencies have only reduced the burden of child undernutrition to a certain extent, indicating that there are other underlying determinants that need to be addressed. Aflatoxin exposure, which is also highly prevalent in developing countries, may be considered an aggravating factor for child undernutrition. Increasing evidence suggests that aflatoxin exposure can occur in any stage of life, including in utero through a trans-placental pathway and in early childhood (through contaminated weaning food and family food). Early life exposure to aflatoxin is associated with adverse effects on low birth weight, stunting, immune suppression, and the liver function damage. The mechanisms underlying impaired growth and aflatoxin exposure are still unclear but intestinal function damage, reduced immune function, and alteration in the insulin-like growth factor axis caused by the liver damage are the suggested hypotheses. Given the fact that both aflatoxin and child undernutrition are common in sub-Saharan Africa, effective interventions aimed at reducing undernutrition cannot be satisfactorily achieved until the interactive relationship between aflatoxin and child undernutrition is clearly understood, and an aflatoxin mitigation strategy takes effect in those vulnerable mothers and children

    Recent Advances in Understanding Particle Acceleration Processes in Solar Flares

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    We review basic theoretical concepts in particle acceleration, with particular emphasis on processes likely to occur in regions of magnetic reconnection. Several new developments are discussed, including detailed studies of reconnection in three-dimensional magnetic field configurations (e.g., current sheets, collapsing traps, separatrix regions) and stochastic acceleration in a turbulent environment. Fluid, test-particle, and particle-in-cell approaches are used and results compared. While these studies show considerable promise in accounting for the various observational manifestations of solar flares, they are limited by a number of factors, mostly relating to available computational power. Not the least of these issues is the need to explicitly incorporate the electrodynamic feedback of the accelerated particles themselves on the environment in which they are accelerated. A brief prognosis for future advancement is offered.Comment: This is a chapter in a monograph on the physics of solar flares, inspired by RHESSI observations. The individual articles are to appear in Space Science Reviews (2011

    Measurement of ΜˉΌ\bar{\nu}_{\mu} and ΜΌ\nu_{\mu} charged current inclusive cross sections and their ratio with the T2K off-axis near detector

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    We report a measurement of cross section σ(ΜΌ+nucleus→Ό−+X)\sigma(\nu_{\mu}+{\rm nucleus}\rightarrow\mu^{-}+X) and the first measurements of the cross section σ(ΜˉΌ+nucleus→Ό++X)\sigma(\bar{\nu}_{\mu}+{\rm nucleus}\rightarrow\mu^{+}+X) and their ratio R(σ(Μˉ)σ(Îœ))R(\frac{\sigma(\bar \nu)}{\sigma(\nu)}) at (anti-)neutrino energies below 1.5 GeV. We determine the single momentum bin cross section measurements, averaged over the T2K Μˉ/Îœ\bar{\nu}/\nu-flux, for the detector target material (mainly Carbon, Oxygen, Hydrogen and Copper) with phase space restricted laboratory frame kinematics of ΞΌ\theta_{\mu}500 MeV/c. The results are σ(Μˉ)=(0.900±0.029(stat.)±0.088(syst.))×10−39\sigma(\bar{\nu})=\left( 0.900\pm0.029{\rm (stat.)}\pm0.088{\rm (syst.)}\right)\times10^{-39} and $\sigma(\nu)=\left( 2.41\ \pm0.022{\rm{(stat.)}}\pm0.231{\rm (syst.)}\ \right)\times10^{-39}inunitsofcm in units of cm^{2}/nucleonand/nucleon and R\left(\frac{\sigma(\bar{\nu})}{\sigma(\nu)}\right)= 0.373\pm0.012{\rm (stat.)}\pm0.015{\rm (syst.)}$.Comment: 18 pages, 8 figure
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