Search

Distributed ledger technologies such as blockchains and smart contracts have the potential to transform many sectors ranging from the handling of health records to real estate. Here we discuss the value proposition of these technologies and crypto-currencies for science in general and academic publishing in specific. We outline concrete use cases, provide an informal model of how the Semantic Web journal’s peer-review workflow could benefit from distributed ledger technologies, and also point out challenges in implementing such a setup.

ABSTRACTGeoLink has leveraged linked data principles to create a dataset that allows users to seamlessly query and reason over some of the most prominent geoscience metadata repositories in the United States. The GeoLink dataset includes such diverse information as port calls made by oceanographic cruises, physical sample metadata, research project funding and staffing, and authorship of technical reports. The data has been published according to best practices for linked data and is publicly available via a SPARQL Protocol and RDF Query Language (SPARQL) end point that at present contains more than 45 million Resource Description Framework (RDF) triples together with a collection of ontologies and geo-visualization tools. This article describes the geoscience datasets, the modeling and publication process, and current uses of the dataset. The focus is on providing enough detail to enable researchers, application developers and others who wish to leverage the GeoLink data in their own work to do so. The dataset is available at http://hdl.handle.net/1912/9524.

Powder-bed based additive manufacturing techniques are of high interest for the medical sector and recent trial studies have shown their feasibility. Due to the rapid improvements made in the machinery and the related changes in the type and characteristics of the utilized power source, optimizations regarding the fabrication parameters tend to differ amongst various machines. In this study, a parameter optimization was undertaken for a biocompatible dental CoCrMo alloy on a SLM 280HL machine, featuring a 400 W fibre laser. It was shown that the availability of higher laser powers enables a more energy efficient fabrication. Moreover, parameter sets for fast and economic fabrication, as well as for high density and fine-grained microstructure, were defined.

Patients with myeloid leukemia of Down syndrome (ML-DS) have favorable event-free survival (EFS), but experience significant treatment-related morbidity and mortality. ML-DS blast cells ex vivo have increased sensitivity to cytarabine (araC) and daunorubicin, suggesting that optimizing drug dosing may improve outcomes while reducing toxicity. The Children’s Oncology Group (COG) AAML0431 trial consisted of 4 cycles of induction and 2 cycles of intensification therapy based on the treatment schema of the previous COG A2971 trial with several modifications. High-dose araC (HD-araC) was used in the second induction cycle instead of the intensification cycle, and 1 of 4 daunorubicin-containing induction cycles was eliminated. For 204 eligible patients, 5-year EFS was 89.9% and overall survival (OS) was 93.0%. The 5-year OS for 17 patients with refractory/relapsed leukemia was 34.3%. We determined the clinical significance of minimal residual disease (MRD) levels as measured by flow cytometry on day 28 of induction I. MRD measurements, available for 146 of the 204 patients, were highly predictive of treatment outcome; 5-year disease-free survival for MRD-negative patients (n = 125) was 92.7% vs 76.2% for MRD-positive patients (n = 21) (log-rank P = .011). Our results indicated that earlier use of HD-araC led to better EFS and OS in AAML0431 than in past COG studies. A 25% reduction in the cumulative daunorubicin dose did not impact outcome. MRD, identified as a new prognostic factor for ML-DS patients, can be used for risk stratification in future clinical trials. This trial was registered at www.clinicaltrials.gov as #NCT00369317.

In this work we introduce a content Ontology Design Pattern (ODP) to model and reason about material transformations, a concept that occurs in many different domains ranging from computational chemistry, biology, and industrial ecology to architecture. We model the relationships between inputs, outputs, and catalysts in the transformation process as well as the spatial and temporal constraints necessary for a transformation to occur. Both a graphical illustration and a formal axiomatization are provided, and the commonalities and differences to similar ontologies and patterns are discussed. Usage of the pattern is illustrated by applying it to an intuitive and familiar example and by discussing how the pattern is able to address a set of competency questions. Additionally, we present a detailed use case from the domain of sustainable construction that leverages the material transformation pattern in combination with the already-existing semantic trajectory ontology design pattern.

Additive manufacturing processes offer the ability to manufacture highly complex geometries, but are limited in terms of the achievable surface quality. These limitations are based on physical restrictions, especially the need of support and the powder-bed environment, and economic decisions. In this study, the development of the morphology of surfaces with varying inclination angles was investigated on the example of 316L stainless steel. Surfaces with low inclination angles to the manufacturing plane suffered extensively from the process related staircase effect, whereas perpendicular side faces revealed high dependencies on the interaction with the powder-bed.

Recent investigations revealed major fluctuations in the material properties of selective laser melted AlSi10Mg, which corresponded with the varying precipitation-hardening state of the microstructure, caused by the differing dwell times at elevated temperatures. It was indicated that a subsequent heat treatment balances the age-hardening and results in a homogenized material strength. In order to further investigate this statement selective laser melted AlSi10Mg samples were subject to multiple post-heat-treatments. Subsequently, the surface hardness and tensile strength was determined and compared with the as-built results. The post-heat-treatment led to an arbitrary occurrence of rupture, indicating a successful homogenization, coupled with a remarkable improvement in ductility, but to the costs of a lowered tensile strength, which was highly dependent on the chosen heat-treatment procedure.

Hyperleukocytosis in children with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) is associated with early morbidity and mortality. The benefit from leukapheresis is controversial, and its complications are not well defined. We analyzed the frequency of early complications in children with ALL and AML presenting with white blood cell (WBC) count >100×109/L, and the type and frequency of complications related to leukapheresis. During a 12-year period, 84 of 634 (13%) ALL and 18 of 143 (12.5%) AML patients presented with hyperleukocytosis. Leukapheresis was performed in 18 ALL and 12 AML patients. The median initial WBC was 474×109/L in the leukapheresis group compared with 175×109/L in the nonleukapheresis group. Neurological leukostasis occurred in 6 ALL (7.1%) and 4 AML (22.2%) patients. Pulmonary leukostasis occurred in 16 ALL (19%) and 4 AML patients (22.2%). Neurological symptoms improved in few patients after leukapheresis, except in patients with very high WBC (>650×109/L in ALL and >400×109/L in AML). Leukapheresis improved respiratory symptoms in some patients but caused worsening symptoms in others. Early death was associated with neurological complications, AML diagnosis, and coagulopathy. Leukapheresis did not delay initiation of chemotherapy, nor did it impact early response to chemotherapy or long-term survival. Complications included femoral vein thrombosis, electrolyte imbalances, and hemodynamic instability, which were all reversible. The role of leukapheresis as a cytoreductive procedure in childhood hyperleukocytic leukemia remains to be well defined.

Since 2012, the Semantic Web journal has been accepting papers in a novel Linked Dataset descriptiontrack. Here we motivate the track and provide some analysis of the papers accepted thus far. We look at the ratio of accepted papers in this time-frame that fall under this track, the relative impact of these papers in terms of citations, and we perform a technical analysis of the datasets they describe to see what sorts of resources they provide and to see if the datasets have remained available since publication. Based on a variety of such analyses, we present some lessons learnt and discuss some potential changes we could apply to the track in order to improve the overall quality of papers accepted.

While catchphrases such as big data, smart data, data‐intensive science, or smart dust highlight different aspects, they share a common theme — namely, a shift toward a data‐centered perspective in which the synthesis and analysis of data at an ever‐increasing spatial, temporal, and thematic resolution promise new insights, while, at the same time, reduce the need for strong domain theories as starting points. In terms of the envisioned methodologies, those catchphrases tend to emphasize the role of predictive analytics, that is, statistical techniques including data mining and machine learning, as well as supercomputing. Interestingly, however, while this perspective takes the availability of data as a given, it does not answer the question how one would discover the required data in today's chaotic information universe, how one would understand which data sets can be meaningfully integrated, and how to communicate the results to humans and machines alike. The semantic web addresses these questions. In the following, we argue why the data train needs semantic rails. We point out that making sense of data and gaining new insights work best if inductive and deductive techniques go hand‐in‐hand instead of competing over the prerogative of interpretation.