76 results match your criteria: "CSC-It-center for science[Affiliation]"

In the present paper, we introduce a high-resolution spatiotemporal point cloud time series, acquired using a LiDAR sensor mounted 30 metres above ground on a flux observation tower monitoring a boreal forest. The dataset comprises a 18-month long (April 2020 - September 2021) time series with an average interval of 3.5 days between observations.

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We have performed direct kinetic measurements to determine the thermal unimolecular-decay rate coefficient of (CH)COO as a function of temperature (223-296 K) and pressure (4-100 torr) using time-resolved UV-absorption spectroscopy. The stabilised (CH)COO Criegee intermediate was produced by photolysing 3-bromo-3-iodopentane ((CH)CIBr) with 213 nm radiation in the presence of O. We performed quantum-chemistry calculations and master-equation simulations to complement the experimental work.

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The effect of hydrogen bonding on the π depletion and the π-π stacking interaction.

Phys Chem Chem Phys

November 2024

Department of Chemistry, Faculty of Science, University of Helsinki, A.I. Virtasen aukio 1, P.O. Box 55, FI-00014, Finland.

Non-covalent interactions such as hydrogen bonding and π-π stacking are essential types of interactions governing molecular self-assembly. The π-π stacking ability of aromatic rings depends on the electron density of the π orbitals, which is affected by the electron-withdrawing or electron-donating properties of the substituents. We have here studied the effect of hydrogen bonding on the strength of the π-π stacking interactions by calculating the binding energies at the explicitly correlated Møller-Plesset (MP2-F12) perturbation theory level using polarized triple- quality basis sets.

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Article Synopsis
  • Research data management (RDM) is crucial for implementing FAIR and Open Science principles, leading to the development of valuable tools and resources for effective data management in scientific research.
  • Despite the valuable resources produced by ELIXIR Platforms and Nodes, they are currently scattered, creating challenges in their application and dissemination, highlighting the need for coordinated RDM efforts.
  • The proposed ELIXIR RDM Community aims to unify RDM experts, enhance knowledge exchange, provide training, and develop best practices, thereby strengthening RDM skills and addressing the evolving needs within the scientific community.
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Implementation of pharmacogenetic testing in clinical care has been slow and with few exceptions is hindered by the lack of real-world evidence on how to best target testing. In this retrospective register-based study, we analyzed a nationwide cohort of 1,425,000 patients discharged from internal medicine or surgical wards and a cohort of 2,178 university hospital patients for purchases and prescriptions of pharmacogenetically actionable drugs. Pharmacogenetic variants were obtained from whole genome genotype data for a subset (n = 930) of the university hospital patients.

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Molecular self-assembly provides the means for creating large supramolecular structures, extending beyond the capability of standard chemical synthesis. To harness the power of self-assembly, it is necessary to understand its driving forces. A potent method is to exploit self-complementary hydrogen bonding, where a molecule interacts with its own copy by suitable positions of hydrogen-bond donor (D) and acceptor (A) groups.

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Accelerating joint species distribution modelling with Hmsc-HPC by GPU porting.

PLoS Comput Biol

September 2024

Department of Biological and Environmental Science, Faculty of Mathematics and Science, University of Jyväskylä, Jyväskylä, Finland.

Joint species distribution modelling (JSDM) is a widely used statistical method that analyzes combined patterns of all species in a community, linking empirical data to ecological theory and enhancing community-wide prediction tasks. However, fitting JSDMs to large datasets is often computationally demanding and time-consuming. Recent studies have introduced new statistical and machine learning techniques to provide more scalable fitting algorithms, but extending these to complex JSDM structures that account for spatial dependencies or multi-level sampling designs remains challenging.

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Background: Research and researchers are heavily evaluated, and over the past decade it has become widely acknowledged that the consequences of evaluating the research enterprise and particularly individual researchers are considerable. This has resulted in the publishing of several guidelines and principles to support moving towards more responsible research assessment (RRA). To ensure that research evaluation is meaningful, responsible, and effective the International Network of Research Management Societies (INORMS) Research Evaluation Group created the SCOPE framework enabling evaluators to deliver on existing principles of RRA.

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Article Synopsis
  • GPAW is a powerful, open-source Python program for studying how electrons behave in materials using a method called density functional theory (DFT).
  • It can use different ways to represent these electron states, making it very flexible compared to other similar programs.
  • GPAW can also do advanced calculations for things like excited states, magnetic properties, and has recently added support to work faster with special computer hardware called GPUs.
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FAIR data retrieval for sensitive clinical research data in Galaxy.

Gigascience

January 2024

Clinical Bioinformatics Group, Department of Pathology, Erasmus Medical Center, 3015 CN, Rotterdam, the Netherlands.

Background: In clinical research, data have to be accessible and reproducible, but the generated data are becoming larger and analysis complex. Here we propose a platform for Findable, Accessible, Interoperable, and Reusable (FAIR) data access and creating reproducible findings. Standardized access to a major genomic repository, the European Genome-Phenome Archive (EGA), has been achieved with API services like PyEGA3.

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Model of a 3D Magnetic Permeability Tensor Considering Rotation and Saturation States in Materials with Axial Anisotropy.

Materials (Basel)

April 2023

Institute of Metrology and Biomedical Engineering, Faculty of Mechatronics, Warsaw University of Technology, sw. A. Boboli 8, 02-525 Warsaw, Poland.

The paper proposes a 3D extension of the linear tensor model of magnetic permeability for axially anisotropic materials. In the proposed model, all phases of a magnetization process are considered: linear magnetization, magnetization rotation, and magnetic saturation. The model of the magnetization rotation process is based on the analyses of both anisotropic energy and magnetostatic energy, which directly connect the proposed description with physical phenomena occurring during a magnetization process.

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Quantifying the benefits of reducing synthetic nitrogen application policy on ecosystem carbon sequestration and biodiversity.

Sci Rep

December 2022

Laboratoire des Sciences du Climat et de l`Environnement LSCE/IPSL, Unité Mixte CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif-Sur-Yvette, France.

Synthetic Nitrogen (N) usage in agriculture has greatly increased food supply over the past century. However, the intensive use of N fertilizer is nevertheless the source of numerous environmental issues and remains a major challenge for policymakers to understand, measure, and quantify the interactions and trade-offs between ecosystem carbon and terrestrial biodiversity loss. In this study, we investigate the impacts of a public policy scenario that aims to halve N fertilizer application across European Union (EU) agriculture on both carbon (C) sequestration and biodiversity changes.

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Year-Long Microbial Succession on Microplastics in Wastewater: Chaotic Dynamics Outweigh Preferential Growth.

Microorganisms

September 2022

Institute of Human Genetics, University Hospital Düsseldorf, Heinrich Heine University, Moorenstrasse 5, 40225 Düsseldorf, Germany.

Microplastics are a globally-ubiquitous aquatic pollutant and have been heavily studied over the last decade. Of particular interest are the interactions between microplastics and microorganisms, especially the pursuit to discover a plastic-specific biome, the so-called plastisphere. To follow this up, a year-long microcosm experimental setup was deployed to expose five different microplastic types (and silica beads control) to activated aerobic wastewater in controlled conditions, with microbial communities being measured four times over the course of the year using 16S rDNA (bacterial) and ITS (fungal) amplicon sequencing.

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Glucose- and sodium-dependent glucose transporters (GLUTs and SGLTs) play vital roles in human biology. Of the 14 GLUTs and 12 SGLTs, the GLUT1 transporter has gained the most widespread recognition because GLUT1 is overexpressed in several cancers and is a clinically valid therapeutic target. We have been pursuing a GLUT1-targeting approach in boron neutron capture therapy (BNCT).

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A major challenge within material science is the proper modeling of force transmission through fragmenting materials under compression. A particularly demanding material is sea ice, which on small scales is an anisotropic material with quasibrittle characteristics under failure. Here we use the particle-based model HiDEM and laboratory-scale experiments on saline ice to develop a material model for fragmenting ice.

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Beacon is a basic data discovery protocol issued by the Global Alliance for Genomics and Health (GA4GH). The main goal addressed by version 1 of the Beacon protocol was to test the feasibility of broadly sharing human genomic data, through providing simple "yes" or "no" responses to queries about the presence of a given variant in datasets hosted by Beacon providers. The popularity of this concept has fostered the design of a version 2, that better serves real-world requirements and addresses the needs of clinical genomics research and healthcare, as assessed by several contributing projects and organizations.

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Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment.

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We promote a shared vision and guide for how and when to federate genomic and health-related data sharing, enabling connections and insights across independent, secure databases. The GA4GH encourages a federated approach wherein data providers have the mandate and resources to share, but where data cannot move for legal or technical reasons. We recommend a federated approach to connect national genomics initiatives into a global network and precision medicine resource.

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The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution.

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The Human Exposome Assessment Platform (HEAP) is a research resource for the integrated and efficient management and analysis of human exposome data. The project will provide the complete workflow for obtaining exposome actionable knowledge from population-based cohorts. HEAP is a state-of-the-science service composed of computational resources from partner institutions, accessed through a software framework that provides the world's fastest Hadoop platform for data warehousing and applied artificial intelligence (AI).

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The Global Alliance for Genomics and Health (GA4GH) supports international standards that enable a federated data sharing model for the research community while respecting data security, ethical and regulatory frameworks, and data authorization and access processes for sensitive data. The GA4GH Passport standard (Passport) defines a machine-readable digital identity that conveys roles and data access permissions (called "visas") for individual users. Visas are issued by data stewards, including data access committees (DACs) working with public databases, the entities responsible for the quality, integrity, and access arrangements for the datasets in the management of human biomedical data.

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Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard.

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Lessons learned from urgent computing in Europe: Tackling the COVID-19 pandemic.

Proc Natl Acad Sci U S A

November 2021

Partnership for Advanced Computing in Europe 1050 Bruxelles, Belgium.

PRACE (Partnership for Advanced Computing in Europe), an international not-for-profit association that brings together the five largest European supercomputing centers and involves 26 European countries, has allocated more than half a billion core hours to computer simulations to fight the COVID-19 pandemic. Alongside experiments, these simulations are a pillar of research to assess the risks of different scenarios and investigate mitigation strategies. While the world deals with the subsequent waves of the pandemic, we present a reflection on the use of urgent supercomputing for global societal challenges and crisis management.

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