Superconducting nano-mechanical diamond resonators

In this work we present the fabrication and characterization of superconducting nano-mechanical resonators made from nanocrystalline boron doped diamond (BDD). The oscillators can be driven and read out in their superconducting state and show quality factors as high as 40,000 at a resonance frequency of around 10 MHz. Mechanical damping is studied for magnetic fields up to 3 T where the resonators still show superconducting properties. Due to their simple fabrication procedure, the devices can easily be coupled to other superconducting circuits and their performance is comparable with state-of-the-art technology.Comment: 5 pages 6 figures, Accepted for publication in Carbo

Transient Trajectory Control of Permanent Magnet Synchronous Machines with Nonlinear Magnetics

High performance interior permanent magnet synchronous machines show nonlinear magnetics due to saturation and cross-coupling. Nonlinear differential equations describe these phenomena and make feedback control challenging. This paper presents a predictive control method to precisely control the dynamics of these machines. Four real-time capable strategies to online identify transient trajectories are proposed: Two straight line trajectories, a strategy that yields a fast torque response and a strategy that reaches the reference values in a short amount of time. A predictive control method to force the machine to precisely follow the selected trajectory is developed and analyzed using simulations and test bench measurements. Thus, advantages and disadvantages of specific trajectories are identified. This allows the selection of a proper strategy depending on the drive requirements

The Dynamic Library

"The Dynamic Library presents essays in translation from an interdisciplinary symposium on the classification and organization of knowledge held at Sitterwerk, St.Gallen in Switzerland. Home to over 25,000 volumes on art, architecture, design, and photography, the Sitterwerk’s Kunstbibliothek (art library) began with the bequest of book collector and connoisseur Daniel Rohner (1948–2007). The question of how to systematically organize this idiosyncratic collection into a publicly accessible library was a fundamental concern, and a solution was found in a dynamic system of organization powered by RFID technology, which relies on digital tracking. The essays gathered in The Dynamic Library contextualize the Sitterwerk’s associative classification system amid artistic and historical systems of order while pointing to future methods for incorporating subjectivity and serendipity into the organization of knowledge." -- Publisher's website

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A Second Gamma-Glutamylpolyamine Synthetase, GlnA2, Is Involved in Polyamine Catabolism in Streptomyces coelicolor

Krysenko S, Okoniewski N, Nentwich M, et al. A Second Gamma-Glutamylpolyamine Synthetase, GlnA2, Is Involved in Polyamine Catabolism in Streptomyces coelicolor. International journal of molecular sciences. 2022;23(7): 3752.Streptomyces coelicolor is a soil bacterium living in a habitat with very changeable nutrient availability. This organism possesses a complex nitrogen metabolism and is able to utilize the polyamines putrescine, cadaverine, spermidine, and spermine and the monoamine ethanolamine. We demonstrated that GlnA2 (SCO2241) facilitates S. coelicolor to survive under high toxic polyamine concentrations. GlnA2 is a gamma-glutamylpolyamine synthetase, an enzyme catalyzing the first step in polyamine catabolism. The role of GlnA2 was confirmed in phenotypical studies with a glnA2 deletion mutant as well as in transcriptional and biochemical analyses. Among all GS-like enzymes in S. coelicolor, GlnA2 possesses the highest specificity towards short-chain polyamines (putrescine and cadaverine), while its functional homolog GlnA3 (SCO6962) prefers long-chain polyamines (spermidine and spermine) and GlnA4 (SCO1613) accepts only monoamines. The genome-wide RNAseq analysis in the presence of the polyamines putrescine, cadaverine, spermidine, or spermine revealed indication of the occurrence of different routes for polyamine catabolism in S. coelicolor involving GlnA2 and GlnA3. Furthermore, GlnA2 and GlnA3 are differently regulated. From our results, we can propose a complemented model of polyamine catabolism in S. coelicolor, which involves the gamma-glutamylation pathway as well as other alternative utilization pathways

Multimodal Bone Metastasis-associated Epidermal Growth Factor Receptor Imaging in an Orthotopic Rat Model

Purpose: To develop multimodality imaging techniques for measuring epidermal growth factor receptor (EGFR) as a therapy-relevant and metastasis-associated molecular marker in triple-negative mammary adenocarcinoma metastases. Materials and Methods: An orthotopic bone metastasis EGFR-positive, triple-negative breast cancer (TNBC) model in rats was used for bioluminescence imaging, SPECT/CT, PET/CT, and MRI with quantitative analysis of transcripts (n = 22 rats). Receptor-specific MRI of EGFR expression in vivo was performed by acquiring spin-echo T1-weighted images after sequential administration of a pair of anti-EGFR antigen binding fragments, F(ab\u27)2, conjugated to either horseradish peroxidase or glucose oxidase, which have complementing activities, as well as paramagnetic (gadolinium[III]-mono-5-hydroxytryptamide of 2,2\u27,2\u27\u27-(10-(2,6-dioxotetrahydro-2H-pyran-3-yl)-1,4,7,10-tetraazacyclododecane-1 ,4,7-triyl)triacetic acid, or Gd-5HT-DOTAGA) or positron-emitting (gallium 68-5HT-DOTAGA) substrates for MRI and PET/CT imaging, respectively. EGFR expression was confirmed by quantitative reverse transcriptase polymerase chain reaction and immunohistochemical analyses to compare with image findings. Results: After surgical intraarterial delivery of TNBC cells, rats developed tumors that diverged into either rapidly growing osteolytic or slow-growing nonosteolytic tumors. Both tumor types showed receptor-specific initial MRI signal enhancement (contrast-to-noise ratio) that was three to six times higher than that of normal bone marrow (29.4 vs 4.9; P \u3c .01). Micro PET/CT imaging of EGFR expression demonstrated a high level of heterogeneity with regional uptake of the tracer, which corresponded to region-of-interest MRI signal intensity elevation (121.1 vs 93.3; P \u3c .001). Analysis of metastases with corroboration of imaging results showed high levels of EGFR protein and messenger RNA, or mRNA, expression in the invasive tumor. Conclusion: Convergence of multimodal molecular receptor imaging enabled comprehensive assessment of EGFR overexpression in an orthotopic model of TNBC metastasis