1,660 research outputs found
Magnetism in heavy-fermion U(Pt,Pd)3 studied by mSR
We report mSR experiments carried out on a series of heavy-electron
pseudobinary compounds U(Pt1-xPdx)3 (x<=0.05). For x<=0.005 the zero-field muon
depolarisation is described by the Kubo-Toyabe function. However the
temperature variation of the Kubo-Toyabe relaxation rate does not show any sign
of the small-moment antiferromagnetic phase with TN~6 K (signalled by neutron
diffraction), in contrast to previous reports. The failure to detect the small
ordered moment suggests it has a fluctuating (> 10 MHz) nature, which is
consistent with the interpretation of NMR data. For 0.01<=x<=0.05 the muon
depolarisation in the ordered state is described by two terms of equal
amplitude: an exponentially damped spontaneous oscillation and a Lorentzian
Kubo-Toyabe function. These terms are associated with antiferromagnetic order
with substantial moments. The Knight-shift measured in a magnetic field of 0.6
T on single-crystalline U(Pt0.95Pd0.05)3 in the paramagnetic state shows two
signals for B perpendicular to c, while only one signal is observed for B||c.
The observation of two signals for B perpendicular to c, while there is only
one muon localisation site (0,0,0), points to the presence of two spatially
distinct regions of different magnetic response.Comment: 25 pages including 12 figures (PS), J. Phys.: Condens. Matter, in
prin
Development of a National Core Dataset for Preoperative Assessment
Objective:To define a core dataset for preoperative assessment to leverage uniform data
collection in this domain. This uniformity is a
prerequisite for data exchange between care
providers and semantic interoperability between health record systems.
Methods: To design this core dataset a combination of literature review and expert consensus meetings were used. In the first meeting a working definition for âcore datasetâ was
specified. Subgroups were formed to address
major headings of the core dataset. In the following eight meetings data items for each
subheading were discussed. The items in the
resulting draft of the dataset were compared
to those retrieved from an earlier literature review study. In the last two expert meetings modifications of the dataset were performed
based on the result of this literature study.
Results: Based on expert consensus a draft
dataset including 82 data items was designed. Seventy-six percent of data items in
the draft dataset were covered by the literature study. Nine data items were modified in
the draft and 14 data items were added to the
dataset based on input from the literature review. The final dataset of 93 data items covers
patient history, physical examination, supplementary examination and consultation, and
final judgment.
Conclusions: This preoperative-assessment
dataset was defined based on expert con -
sensus and literature review. Both methods
proved to be valuable and complementary.
This dataset opens the door for creating standardized approaches in data collection in the
preoperative assessment field which will
facilitate interoperability between different
electronic health records and different users
Construction of an Interface Terminology on SNOMED CT Generic Approach and Its Application in Intensive...
Objective: To provide a generic approach for
developing a domain-specific interface terminology on SNOMED CT and to apply this
approach to the domain of intensive care.
Methods:The process of developing an interface terminology on SNOMED CT can be regarded as six sequential phases: domain
analysis, mapping from the domain con -
cepts to SNOMED CT concepts, creating the
SNOMED CT subset guided by the mapping,
extending the subset with non-covered concepts, constraining the subset by removing
irrelevant content, and deploying the subset
in a terminology server.
Results:The APACHE IV classification, a standard in the intensive care with 445 diagnostic
categories, served as the starting point for designing the interface terminology. The majority (89.2%) of the diagnostic categories from
APACHE IV could be mapped to SNOMED CT
concepts and for the remaining concepts a
partial match was identified. The resulting initial set of mapped concepts consisted of 404
SNOMED CT concepts. This set could be extended to 83,125 concepts if all taxonomic
children of these concepts were included. Also
including all concepts that are referred to in
the definition of other concepts lead to a subset of 233,782 concepts. An evaluation of the
interface terminology should reveal what
level of detail in the subset is suitable for the
intensive care domain and whether parts
need further constraining. In the final phase,
the interface terminology is implemented in
the intensive care in a locally developed terminology server to collect the reasons for intensive care admission.
Conclusions: We provide a structure for the
process of identifying a domain-specific interface terminology on SNOMED CT. We use this
approach to design an interface terminology
on SNOMED CT for the intensive care domain.
This work is of value for other researchers who
intend to build a domain-specific interface
terminology on SNOMED CT
Performance assessment of ontology matching systems for FAIR data
© The Author(s). 2022 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the articleâs Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the articleâs Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Background: Ontology matching should contribute to the interoperability aspect of FAIR data (Findable, Accessible, Interoperable, and Reusable). Multiple data sources can use different ontologies for annotating their data and, thus, creating the need for dynamic ontology matching services. In this experimental study, we assessed the performance of ontology matching systems in the context of a real-life application from the rare disease domain. Additionally, we present a method for analyzing top-level classes to improve precision.
Results: We included three ontologies (NCIt, SNOMED CT, ORDO) and three matching systems (AgreementMakerLight 2.0, FCA-Map, LogMap 2.0). We evaluated the performance of the matching systems against reference alignments from BioPortal and the Unified Medical Language System Metathesaurus (UMLS). Then, we analyzed the top-level ancestors of matched classes, to detect incorrect mappings without consulting a reference alignment. To detect such incorrect mappings, we manually matched semantically equivalent top-level classes of ontology pairs. AgreementMakerLight 2.0, FCA-Map, and LogMap 2.0 had F1-scores of 0.55, 0.46, 0.55 for BioPortal and 0.66, 0.53, 0.58 for the UMLS respectively. Using vote-based consensus alignments increased performance across the board. Evaluation with manually created top-level hierarchy mappings revealed that on average 90% of the mappingsâ classes belonged to top-level classes that matched.
Conclusions: Our findings show that the included ontology matching systems automatically produced mappings that were modestly accurate according to our evaluation. The hierarchical analysis of mappings seems promising when no reference alignments are available. All in all, the systems show potential to be implemented as part of an ontology matching service for querying FAIR data. Future research should focus on developing methods for the evaluation of mappings used in such mapping services, leading to their implementation in a FAIR data ecosystem
General Non-equilibrium Theory of Colloid Dynamics
A non-equilibrium extension of Onsager's canonical theory of thermal
fluctuations is employed to derive a self-consistent theory for the description
of the statistical properties of the instantaneous local concentration profile
n(r,t) of a colloidal liquid in terms of the coupled time evolution equations
of its mean value n(r,t) and of the covariance {\sigma}(r,r';t) \equiv
of its fluctuations {\delta}n(r, t) = n(r, t) -
n(r, t). These two coarse-grained equations involve a local mobility function
b(r, t) which, in its turn, is written in terms of the memory function of the
two-time correlation function C(r, r' ; t, t') \equiv <{\delta}n(r,
t){\delta}n(r',t')>. For given effective interactions between colloidal
particles and applied external fields, the resulting self-consistent theory is
aimed at describing the evolution of a strongly correlated colloidal liquid
from an initial state with arbitrary mean and covariance n^0(r) and
{\sigma}^0(r,r') towards its equilibrium state characterized by the equilibrium
local concentration profile n^(eq)(r) and equilibrium covariance
{\sigma}^(eq)(r,r').
This theory also provides a general theoretical framework to describe
irreversible processes associated with dynamic arrest transitions, such as
aging, and the effects of spatial heterogeneities
Superconductivity in heavy-fermion U(Pt,Pd)3 and its interplay with magnetism
The effect of Pd doping on the superconducting phase diagram of the
unconventional superconductor UPt3 has been measured by (magneto)resistance,
specific heat, thermal expansion and magnetostriction. Experiments on single-
and polycrystalline U(Pt1-xPdx)3 for x<= 0.006 show that the superconducting
transition temperatures of the A phase, Tc+, and of the B phase, Tc-, both
decrease, while the splitting DTc increases at a rate of 0.30(2)K/at.%Pd. We
find that DTc(x) correlates with an increase of the weak magnetic moment m(x)
upon Pd doping. This provides further evidence for Ginzburg-Landau scenarios
with magnetism as the symmetry breaking field, i.e. the 2D E representation and
the 1D odd parity model. Only for small splittings DTc is proportional to
m^2(Tc+) (DTc<= 0.05 K) as predicted. The results at larger splittings call for
Ginzburg-Landau expansions beyond 4th order. The tetracritical point in the B-T
plane persists till at least x= 0.002 for B perpendicular to c, while it is
rapidly suppressed for B||c. Upon alloying the A and B phases gain stability at
the expense of the C phase.Comment: 25 pages text (PS), 8 pages with 14 figures (PS), submitted to
Phys.Rev.
Bias in protein and potassium intake collected with 24-h recalls (EPIC-Soft) is rather comparable across European populations
Purpose: We investigated whether group-level bias of a 24-h recall estimate of protein and potassium intake, as compared to biomarkers, varied across European centers and whether this was influenced by characteristics of individuals or centers. Methods: The combined data from EFCOVAL and EPIC studies included 14 centers from 9 countries (n = 1,841). Dietary data were collected using a computerized 24-h recall (EPIC-Soft). Nitrogen and potassium in 24-h urine collections were used as reference method. Multilevel linear regression analysis was performed, including individual-level (e.g., BMI) and center-level (e.g., food pattern index) variables. Results: For protein intake, no between-center variation in bias was observed in men while it was 5.7% in women. For potassium intake, the between-center variation in bias was 8.9% in men and null in women. BMI was an important factor influencing the biases across centers (p <0.01 in all analyses). In addition, mode of administration (p = 0.06 in women) and day of the week (p = 0.03 in men and p = 0.06 in women) may have influenced the bias in protein intake across centers. After inclusion of these individual variables, between-center variation in bias in protein intake disappeared for women, whereas for potassium, it increased slightly in men (to 9.5%). Center-level variables did not influence the results. Conclusion: The results suggest that group-level bias in protein and potassium (for women) collected with 24-h recalls does not vary across centers and to a certain extent varies for potassium in men. BMI and study design aspects, rather than center-level characteristics, affected the biases across center
Projecting COVIDâ19 intensive care admissions in the Netherlands for policy advice: February 2020 to January 2021
Model projections of COVIDâ19 incidence into the future help policy makers about decisions to implement or lift control measures. During 2020, policy makers in the Netherlands were informed on a weekly basis with shortâterm projections of COVIDâ19 intensive care unit (ICU) admissions, which were produced using an ageâstructured transmission model. A consistent, incremental update procedure that integrated all new data was conducted on a weekly basis. First, upâtoâdate estimates for most parameter values were obtained through reâanalysis of all data sources. Then, estimates were made for changes in the ageâspecific contact rates in response to policy changes. Finally, a piecewise constant transmission rate was estimated by fitting the model to reported daily ICU admissions, with a change point analysis guided by Akaike's Information Criterion. This procedure allowed us to make weekly projections, accounting for recent and future policy changes, and to adapt the estimated effectiveness of the policy changes based only on the natural accumulation of incoming data
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