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 “core dataset” 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 article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s 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 mappings’ 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 COVID‐19 intensive care admissions in the Netherlands for policy advice: February 2020 to January 2021

Model projections of COVID‐19 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 short‐term projections of COVID‐19 intensive care unit (ICU) admissions, which were produced using an age‐structured transmission model. A consistent, incremental update procedure that integrated all new data was conducted on a weekly basis. First, up‐to‐date estimates for most parameter values were obtained through re‐analysis of all data sources. Then, estimates were made for changes in the age‐specific 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