9,023 research outputs found
Clouds, Clumps, Cores & Comets - a Cosmic Chemical Connection?
We discuss the connection between the chemistry of dense interstellar clouds
and those characteristics of cometary matter that could be remnants of it. The
chemical evolution observed to occur in molecular clouds is summarized and a
model for dense core collapse that can plausibly account for the isotopic
fractionation of hydrogen, nitrogen, oxygen and carbon measured in primitive
solar system materials is presented.Comment: to be published in Advances in Geoscience
Interplay of local hydrogen-bonding and long-ranged dipolar forces in simulations of confined water
Spherical truncations of Coulomb interactions in standard models for water
permit efficient molecular simulations and can give remarkably accurate results
for the structure of the uniform liquid. However truncations are known to
produce significant errors in nonuniform systems, particularly for
electrostatic properties. Local molecular field (LMF) theory corrects such
truncations by use of an effective or restructured electrostatic potential that
accounts for effects of the remaining long-ranged interactions through a
density-weighted mean field average and satisfies a modified Poisson's equation
defined with a Gaussian-smoothed charge density. We apply LMF theory to three
simple molecular systems that exhibit different aspects of the failure of a
naive application of spherical truncations -- water confined between
hydrophobic walls, water confined between atomically-corrugated hydrophilic
walls, and water confined between hydrophobic walls with an applied electric
field. Spherical truncations of 1/r fail spectacularly for the final system in
particular, and LMF theory corrects the failings for all three. Further, LMF
theory provides a more intuitive way to understand the balance between local
hydrogen bonding and longer-ranged electrostatics in molecular simulations
involving water.Comment: Submitted to PNA
Local molecular field theory for the treatment of electrostatics
We examine in detail the theoretical underpinnings of previous successful
applications of local molecular field (LMF) theory to charged systems. LMF
theory generally accounts for the averaged effects of long-ranged components of
the intermolecular interactions by using an effective or restructured external
field. The derivation starts from the exact Yvon-Born-Green hierarchy and shows
that the approximation can be very accurate when the interactions averaged over
are slowly varying at characteristic nearest-neighbor distances. Application of
LMF theory to Coulomb interactions alone allows for great simplifications of
the governing equations. LMF theory then reduces to a single equation for a
restructured electrostatic potential that satisfies Poisson's equation defined
with a smoothed charge density. Because of this charge smoothing by a Gaussian
of width sigma, this equation may be solved more simply than the detailed
simulation geometry might suggest. Proper choice of the smoothing length sigma
plays a major role in ensuring the accuracy of this approximation. We examine
the results of a basic confinement of water between corrugated wall and justify
the simple LMF equation used in a previous publication. We further generalize
these results to confinements that include fixed charges in order to
demonstrate the broader impact of charge smoothing by sigma. The slowly-varying
part of the restructured electrostatic potential will be more symmetric than
the local details of confinements.Comment: To be published in J Phys-Cond Matt; small misprint corrected in Eq.
(12) in V
Two-photon laser-induced fluorescence detection of OH
The TP-LIF OH sensor is based on the principle that a molecule having multiple energy states, all of which are bonding, can be pumped into the highest state with the resulting fluorescence being blue-shifted relative to all pumping wavelengths. In this way, one can successfully discriminate against virtually all noise sources in the system using long wavelength blocking filters in conjunction with solar-blind photomultiplier tubes. Thus, these systems tend to be signal limited rather than signal-to-noise limited as is true of the SP-LIF technique as well as other conventional analytical methods. The trick to achieving the above sampling scheme, with high efficiency, is in the use of high photon fluxes of short time duration. Obviously, the latter type of light source is fulfilled nicely by available pulsed lasers. From an operational point of view, however, this laser source needs to be tunable. The latter characteristic permits extremely high selectivity for the detection of a diatomic or simple polyatomic molecule by taking advantage of the high-resolution spectroscopic features of these type species
Examining the role of mental health and clinical issues within talent development
Although significant research supports the association between physical activity and mental wellbeing, current literature acknowledges that athletes are no less susceptible to mental illness than the general population. Despite welcomed initiatives aimed at improving mental health within elite sport, these programs often fail to target young athletes; an important concern given that the genesis of many mental illnesses are recognized to occur during this critical period. Given the importance of early intervention and effective treatment, and the potentially devastating consequences of clinical issues going undiagnosed, the implications for talent identification and development become obvious. With this in mind, this study sought to examine the range of mental health issues that may impact upon developing athletes and potential consequences for the development process, specific risk and protective factors associated with talent development, along with an examination of current practices concerning the identification of mental health issues in such environments. Qualitative interviews were conducted with purposively sampled clinicians (n = 8) experienced in working with adolescents and/or young athletes. Inductive content analysis was undertaken, identifying four main themes: key behavioral indicators; associated risk factors; associated protective factors; and issues around identification and diagnosis. Key behavioral indicators included behavioral change, along with behaviors associated with eating disorders, anxiety and depression. Risk factors centered on family background, the performance environment, and issues surrounding adolescence. Protective factors were primarily social in nature. Finally, a lack of awareness and understanding of clinical issues, multiple causes of symptoms, non-disclosure and the need for triangulation of assessment were identified. The need for improved identification and intervention strategies was apparent, with coaches identified as well placed to detect general ‘warning signs’ such as behavioral change. Short of integrating trained clinicians into talent development environments, as part of a triangulation process, ecologically validated assessment tools – coupled with appropriate training and signposting – could offer a practical way of flagging potential issues in developing athletes. The need for the development of such an instrument is therefore apparent. Finally, education around the influential role of family is also recommended in order to promote the protective elements and mitigate risk factors
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Self-organized Model for Modular Complex Networks: Division and Independence
We introduce a minimal network model which generates a modular structure in a self-organized way. To this end, we modify the Barabasi-Albert model into the one evolving under the principle of division and independence as well as growth and preferential attachment (PA). A newly added vertex chooses one of the modules composed of existing vertices, and attaches edges to vertices belonging to that module following the PA rule. When the module size reaches a proper size, the module is divided into two, and a new module is created. The karate club network studied by Zachary is a prototypical example. We find that the model can reproduce successfully the behavior of the hierarchical clustering coefficient of a vertex with degree k, C(k), in good agreement with empirical measurements of real world networks
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