1,858 research outputs found
Self-monitoring for improving control of blood pressue in patients with hypertension
The objective of this review is to determine the effect of SBPM in adults with hypertension on blood pressure control as compared to OBPM or usual care
Microscopic calculations of Λ single-particle energies
A binding energy data for total baryon number A ≤ 208 and for Λ angular momenta ℓΛ ≤ 3 are analyzed in terms of phenomenological (but generally consistent with meson-exchange) ΛN and ΛNN potentials. The Fermi hypernetted chain technique is used to calculate the expectation values for the Λ binding to nuclear matter. Accurate effective ΛN and ΛNN potentials are obtained which are folded with the core-nucleus nucleon densities to calculate the Λ single-particle potential UΛ (r). We use a dispersive ANN potential but also include an explicit ρ dependence to allow for reduced repulsion in the surface, and the best fits have a large ρ dependence giving consistency with the variational Monte Carlo calculations for 5ΛHe. The exchange fraction of the ΛN space-exchange potential is found to be 0.2-0.3 corresponding to m*Λ ≃ (0.74 - 0.82)mΛ. Charge-symmetry breaking is found to be significant for heavy hypernuclei with a large neutron excess, with a strength consistent with that obtained from the A = 4 hypernuclei
Hanbury Brown-Twiss effect and thermal light ghost imaging
We show that the essential physics of the Hanbury Brown-Twiss (HBT) and the
thermal light ghost imaging experiments is the same, i.e., due to the intensity
fluctuations of the thermal light. However, in the ghost imaging experiments, a
large number of bits information needs to be treated together, whereas in the
HBT there is only one bit information required to be obtained. In the HBT
experiment far field is used for the purpose of easy detection, while in the
ghost image experiment near (or not-far) field is used for good quality image.Comment: 10 pages, 3 figure
Missense mutations at homologous positions in the fourth and fifth laminin A G-like domains of eyes shut homolog cause autosomal recessive retinitis pigmentosa
Purpose: To describe two novel mutations in the eyes shut homolog (EYS) gene in two families with autosomal recessive
retinitis pigmentosa (arRP) from Pakistan and Indonesia.
Methods: Genome-wide linkage and homozygosity mapping were performed using single nucleotide polymorphism microarray analysis in affected members of the two arRP families. Sequence analysis was performed to identify genetic changes in protein coding exons of EYS.
Results: In the Indonesian and Pakistani families, homozygous regions encompassing the EYS gene at 6q12 were identified, with maximum LOD scores of 1.8 and 3.6, respectively. Novel missense variants in the EYS gene (p.D2767Y and p.D3028Y) were found in the Pakistani and Indonesian families, respectively, that co-segregate with the disease phenotype. Interestingly, the missense variants are located at the same homologous position within the fourth and fifth laminin A G-like domains of EYS.
Conclusions: To date, mostly protein-truncating mutations have been described in EYS, while only few patients have been described with pathogenic compound heterozygous missense mutations. The mutations p.D2767Y and p.D3028Y described in this study affect highly conserved residues at homologous positions in laminin A G-like domains and support the notion that missense mutations in EYS can cause arRP
Integration of tools for binding archetypes to SNOMED CT
Background The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems. Methods Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings. Results An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source. Conclusion Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail. Background The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems. Methods Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings. Results An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source. Conclusion Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.Original Publication: Erik Sundvall, Rahil Qamar, Mikael Nyström, Mattias Forss, Håkan Petersson, Hans Åhlfeldt and Alan Rector, Integration of Tools for Binding Archetypes to SNOMED CT, 2008, BMC Medical Informatics and Decision Making, (8), S7. http://dx.doi.org/10.1186/1472-6947-8-S1-S7 Licensee: BioMed Central http://www.biomedcentral.com/</p
Nano strain-amplifier: making ultra-sensitive piezoresistance in nanowires possible without the need of quantum and surface charge effects
This paper presents an innovative nano strain-amplifier employed to
significantly enhance the sensitivity of piezoresistive strain sensors.
Inspired from the dogbone structure, the nano strain-amplifier consists of a
nano thin frame released from the substrate, where nanowires were formed at the
centre of the frame. Analytical and numerical results indicated that a nano
strain-amplifier significantly increases the strain induced into a free
standing nanowire, resulting in a large change in their electrical conductance.
The proposed structure was demonstrated in p-type cubic silicon carbide
nanowires fabricated using a top down process. The experimental data showed
that the nano strain-amplifier can enhance the sensitivity of SiC strain
sensors at least 5.4 times larger than that of the conventional structures.
This result indicates the potential of the proposed strain-amplifier for
ultra-sensitive mechanical sensing applications.Comment: 4 pages, 5 figure
Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems
The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics.We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor
cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5[plus-over-minus sign]0.5 s (mean[plus-over-minus sign]s.d.) . The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing
rates of 25[plus-over-minus sign]3 single units by a factor of 7.0[plus-over-minus sign]0.9. We expect that the gain in computational efficiency will be much higher in
systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future
large-dimensional, multisignal neural interface systems.National Institutes of Health (U.S.) (Grant R01 DC009899)National Institutes of Health (U.S.) (Grant RC1 HD063931)National Institutes of Health (U.S.) (Grant N01 HD053403)National Institutes of Health (U.S.) (Grant 5K01 NS057389)National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant R01-EB006385)United States. Dept. of Veterans Affairs (Office of Research and Development, Rehabilitation R&D Service)Massachusetts General Hospital (Deane Institute for Integrated Research on Atrial Fibrillation and Stroke)Doris Duke Charitable FoundationSpaulding Rehabilitation Hospita
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