2,724 research outputs found
Intrinsic Magnetism in Nanosheets of SnO: A First-principles Study
We propose intrinsic magnetism in nanosheets of SnO, based on
first-principles calculations. The electronic structure and spin density reveal
that orbitals of the oxygen atoms, surrounding Sn vacancies, have a non
itinerant nature which gives birth to localized magnetism. A giant decrease in
defect formation energies of Sn vacancies in nanosheets is observed. We,
therefore, believe that native defects can be stabilized without any chemical
doping. Nanosheets of different thicknesses are also studied, and it is found
that it is easier to create vacancies, which are magnetic, at the surface of
the sheets. SnO nanosheets can, therefore, open new opportunities in the
field of spintronics.Comment: J. Magn. Magn. Mate. 2012 (Accepted
First-principles study of electron transport through the single-molecule magnet Mn12
We examine electron transport through a single-molecule magnet Mn12 bridged
between Au electrodes using the first-principles method. We find crucial
features which were inaccessible in model Hamiltonian studies: spin filtering
and a strong dependence of charge distribution on local environments. The spin
filtering remains robust with different molecular geometries and interfaces,
and strong electron correlations, while the charge distribution over the Mn12
strongly depends on them. We point out a qualitative difference between locally
charged and free-electron charged Mn12
Effects of bonding type and interface geometry on coherent transport through the single-molecule magnet Mn12
We examine theoretically coherent electron transport through the
single-molecule magnet Mn, bridged between Au(111) electrodes, using the
non-equilibrium Green's function method and the density-functional theory. We
analyze the effects of bonding type, molecular orientation, and geometry
relaxation on the electronic properties and charge and spin transport across
the single-molecule junction. We consider nine interface geometries leading to
five bonding mechanisms and two molecular orientations: (i) Au-C bonding, (ii)
Au-Au bonding, (iii) Au-S bonding, (iv) Au-H bonding, and (v) physisorption via
van der Waals forces. The two molecular orientations of Mn correspond to
the magnetic easy axis of the molecule aligned perpendicular [hereafter denoted
as orientation (1)] or parallel [orientation (2)] to the direction of electron
transport. We find that the electron transport is carried by the lowest
unoccupied molecular orbital (LUMO) level in all the cases that we have
simulated. Relaxation of the junction geometries mainly shifts the relevant
occupied molecular levels toward the Fermi energy as well as slightly reduces
the broadening of the LUMO level. As a result, the current slightly decreases
at low bias voltage. Our calculations also show that placing the molecule in
the orientation (1) broadens the LUMO level much more than in the orientation
(2), due to the internal structure of the Mn. Consequently, junctions
with the former orientation yield a higher current than those with the latter.
Among all of the bonding types considered, the Au-C bonding gives rise to the
highest current (about one order of magnitude higher than the Au-S bonding),
for a given distance between the electrodes. The current through the junction
with other bonding types decreases in the order of Au-Au, Au-S, and Au-H.
Importantly, the spin-filtering effect in all the nine geometries stays robust
and their ratios of the majority-spin to the minority-spin transmission
coefficients are in the range of 10 to 10. The general trend in
transport among the different bonding types and molecular orientations obtained
from this study may be applied to other single-molecular magnets.Comment: Accepted for publication in Phys. Rev. B
Stabilizing intrinsic defects in SnO
TThe magnetism and electronic structure of Li-doped SnO are
investigated using first-principles LDA/LDA calculations. We find that Li
induces magnetism in SnO when doped at the Sn site but becomes
non-magnetic when doped at the O and interstitial sites. The calculated
formation energies show that Li prefers the Sn site as compared with the O
site, in agreement with previous experimental works. The interaction of Li with
native defects (Sn V and O V vacancies) is also
studied, and we find that Li not only behaves as a spin polarizer, but also a
vacancy stabilizer, i.e. Li significantly reduces the defect formation energies
of the native defects and helps the stabilization of magnetic oxygen vacancies.
The electronic densities of states reveals that these systems, where the Fermi
level touches the conduction (valence) band, are non-magnetic
(magnetic).cancies. The electronic densities of states reveal that those
systems, where the Fermi levels touch the conduction (valence) band, are
non-magnetic (magnetic).Comment: Phys. Rev. B (2013), Accepte
Nematode infection on beef cattle in two different productive regions of Argentina's Northwest
Cattle production in northwest Argentina (NOA) in the last 10 years has grown in importance. However, this growth of livestock brought productive and health constraints such as infection with gastrointestinal nematodes (GIN). Nematode infection may reduce productivity of grazing cattle [1-5]. Free-living forms of GIN exhibit a close relationship with climatic factors, the environment and animal management, affecting GIN development, survival and final infestation rate of pastures [1-7].Inst. Investigación Animal del Chaco SemiáridoFil: Suarez, Víctor Humberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Investigación Animal del Chaco Semiárido; Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Martinez, Gabriela Marcela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Micheloud, Juan Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentin
Epidemiology of Goat Nematode Infections in Different Ecological Regions of Argentina´S Northwest
The aim of this work was to study the etiology and epidemiology of gastrointestinal nematodes (GIN) of goat from the Arid valleys and canyons (AVC), Tempered valleys (TV) and the Semiarid Chaco (SC) regions of northwestern Argentina. Ten flocks were studied and 35 to 40 goats per flock (total= 420 goats) were fecal matter sampled each 30-40 days. Individual eggs per gram of faeces (epg) and faeces cultures were performed. Differences among epg were compared using Kruskal–Wallis non-parametric test. The epg of the three regions showed the same trend: an increment from February reaching the highest average epg peak in April-May and then a fall towards the summer. Goat flocks of TV region showed the highest epg compared to the other two regions, which generally showed low epg values. Haemonchus sp. and Trichostrongylus spp. were the predominant nematode genera recovered in the three regions, although in a smaller proportion Teladorsagia, Oesophagostomum, Nematodirus, Trichuris, Skrjabinema and Strongyloides genera were also recovered. These results show that GIN would be a limiting factor of caprine production in the TV and only during critical periods and under some breeding systems in the other regions.Instituto de Investigación Animal del Chaco SemiáridoFil: Suarez, Victor Humberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Investigación Animal del Chaco Semiárido. Área de Investigación en Salud Animal; ArgentinaFil: Martinez, Gabriela Marcela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Olmos, Leandro Hipolito. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Investigación Animal del Chaco Semiárido. Área de Investigación en Salud Animal; Argentin
Representing Black Male Innocence
The course is an elective of specialization that seeks to develop the general competence of innovative thinking and specific ABET competence (j.3) that lets you know and apply contemporary issues of supply chain aligned to industry trends that will allow you more dominance in the professional field of industrial engineering.SCM course is important because permit to student understand and apply models and best practices of logistics in Supply Chain. Different issues regarding to the logistics operations marketing procurement warehousing and information technology will be discussed and proposed. The results from strategies in Supply Chain collaborative and alliance 3PL order management and fulfillment and others key issues will be studied. The course concludes with trends and challenges for supply chain in the future
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation
Diagnostic or procedural coding of clinical notes aims to derive a coded
summary of disease-related information about patients. Such coding is usually
done manually in hospitals but could potentially be automated to improve the
efficiency and accuracy of medical coding. Recent studies on deep learning for
automated medical coding achieved promising performances. However, the
explainability of these models is usually poor, preventing them to be used
confidently in supporting clinical practice. Another limitation is that these
models mostly assume independence among labels, ignoring the complex
correlation among medical codes which can potentially be exploited to improve
the performance. We propose a Hierarchical Label-wise Attention Network (HLAN),
which aimed to interpret the model by quantifying importance (as attention
weights) of words and sentences related to each of the labels. Secondly, we
propose to enhance the major deep learning models with a label embedding (LE)
initialisation approach, which learns a dense, continuous vector representation
and then injects the representation into the final layers and the label-wise
attention layers in the models. We evaluated the methods using three settings
on the MIMIC-III discharge summaries: full codes, top-50 codes, and the UK NHS
COVID-19 shielding codes. Experiments were conducted to compare HLAN and LE
initialisation to the state-of-the-art neural network based methods. HLAN
achieved the best Micro-level AUC and on the top-50 code prediction and
comparable results on the NHS COVID-19 shielding code prediction to other
models. By highlighting the most salient words and sentences for each label,
HLAN showed more meaningful and comprehensive model interpretation compared to
its downgraded baselines and the CNN-based models. LE initialisation
consistently boosted most deep learning models for automated medical coding.Comment: Accepted to Journal of Biomedical Informatics, structured abstract in
full text, 21 pages, 5 figures, 4 supplementary materials (4 extra pages
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