Optimised planning and scheduling of grid resources

This article will present the concept and implementation of a resource management system (RMS). The central component of the RMS is the resource broker GORBA that plans resource allocation by a combination of heuristic processes and evolutionary algorithms. For resource planning, schedules are generated, which distribute the grid jobs to the grid resources in a defined time window. A test environment with extensive visualisation options was developed for GORBA, which will be presented in detail. Using this test environment, benchmark runs were carried out, which are needed to evaluate and further develop GORBA. Automated resource planning and the graphic visualisation options facilitate the usability of a grid environment

Optimised planning and scheduling of grid resources

This article will present the concept and implementation of a resource management system (RMS). The central component of the RMS is the resource broker GORBA that plans resource allocation by a combination of heuristic processes and evolutionary algorithms. For resource planning, schedules are generated, which distribute the grid jobs to the grid resources in a defined time window. A test environment with extensive visualisation options was developed for GORBA, which will be presented in detail. Using this test environment, benchmark runs were carried out, which are needed to evaluate and further develop GORBA. Automated resource planning and the graphic visualisation options facilitate the usability of a grid environment

Not ‘Islands, Entire of Themselves’: Exploring the Spatial Context of City-level Robbery Rates

The current study examines spatial dependence in robbery rates for a sample of 1,056 cities with 25,000 or more residents over the 2000–2003 period. Although commonly considered in some macro-level research, spatial processes have not been examined in relation to city-level variation in robbery. The results of our regression analyses suggest that city robbery rates are not spatially independent. We find that spatial dependence is better accounted for by spatial error models than by spatial lag models. Further exploration of various spatial weights matrices indicates that robbery rates of cities within the same state are related to robbery rates of other cities within the same state, regardless of their proximity. Our analyses illustrate how systematic inquiry into spatial processes can alert researchers to important omitted variable biases and identify intriguing problems for future research

Clotting activity of polyphosphate-functionalized silica nanoparticles

We present a silica nanoparticle (SNP) functionalized with polyphosphate (polyP) that accelerates the natural clotting process of the body. SNPs initiate the contact pathway of the blood-clotting system; short-chain polyP accelerates the common pathway by the rapid formation of thrombin, which enhances the overall blood-clotting system, both by accelerating fibrin generation and by facilitating the regulatory anticoagulation mechanisms essential for hemostasis. Analysis of the clotting properties of bare SNPs, bare polyP, and polyP-functionalized SNPs in plasma demonstrated that the attachment of polyP to SNPs to form polyP-SNPs creates a substantially enhanced synergistic effect that lowers clotting time and increases thrombin production at low concentrations. PolyP-SNP even retains its clotting function at ambient temperature. The polyP-SNP system has the potential to significantly improve trauma-treatment protocols and outcomes in hospital and prehospital settings

Helmholtz Metadata Collaboration (HMC) - FAIr Metadata for Energy = FAIRe Metadaten für die Energieforschung

Ein Teil des Helmholtz-Inkubators Information und Data Science ist die Helmholtz Metadata Collaboration (HMC). HMC soll die Beschreibung von Forschungsdaten durch Metadaten zu deren besseren Auffindbarkeit vorantreiben sowie organisatorisch und technisch umsetzen. Metadaten sind essentielle Infor¬mationen über Forschungsdaten, die für deren Auffinden und Verstehen sowie für deren Vernetzung und Nachnut¬zung im Sinne der FAIR-Prinzipien erforderlich sind. Zur Umsetzung wird die wissenschaftliche Expertise zum Thema Metadaten aus einzelnen Fachdomainen in sogenannten Metadata Hubs der einzelnen Forschungsbereiche zusammengefasst, auf übergeordneter Ebene harmonisiert und, mit Hilfe zentral entwickelter Methoden und Werkzeugen, Metadatenplattformen bereitgestellt. Für den Forschungsbereich Energie ist der HMC Hub Energie verantwortlich. Aufgabe ist hierbei die vorhandenen Standards zur Energiedaten- und Metadatenbeschreibung, etablierte Beschreibungs- und Erfassungsprozesse sowie zugehörige Softwarewerkzeuge zu erfassen, Lücken zu identifizieren und Szenarien zur Ergänzung und Weiterentwicklung in der Domäne Energie zu entwerfen. Einheitliche Ziele von HMC sind die einfache und FAIRe Erschließung und Nutzung vorhandener und zukünftiger Datensammlungen der Forschungsbereiche sowie die Befähigung der Forschenden FAIRe Daten (semi-) automatisch zu erstellen. Das Poster beschreibt die Struktur von HMC allgemein und dem Hub Energie im speziellen, die entwickelten Methoden und Werkzeuge und gibt anhand von Anwendungsbeispielen Impulse für die Umsetzung der Methoden und Werkzeuge hin zu FAIRen Metadaten. Weiterhin werden Verknüpfungen zu Trainings- und Schulungsunterlagen von HMC hergestellt. Das Poster soll dazu einladen mit dem HMC Hub Energie Kontakt aufzunehmen um von den Arbeiten von HMC profitieren zu können

Sulfur-Functionalized Mesoporous Carbons as Sulfur Hosts in Li–S Batteries: Increasing the Affinity of Polysulfide Intermediates to Enhance Performance

The Li–S system offers a tantalizing battery for electric vehicles and renewable energy storage due to its high theoretical capacity of 1675 mAh g^(–1) and its employment of abundant and available materials. One major challenge in this system stems from the formation of soluble polysulfides during the reduction of S_8, the active cathode material, during discharge. The ability to deploy this system hinges on the ability to control the behavior of these polysulfides by containing them in the cathode and allowing for further redox. Here, we exploit the high surface areas and good electrical conductivity of mesoporous carbons (MC) to achieve high sulfur utilization while functionalizing the MC with sulfur (S–MC) in order to modify the surface chemistry and attract polysulfides to the carbon material. S–MC materials show enhanced capacity and cyclability trending as a function of sulfur functionality, specifically a 50% enhancement in discharge capacity is observed at high cycles (60–100 cycles). Impedance spectroscopy suggests that the S-MC materials exhibit a lower charge-transfer resistance compared with MC materials which allows for more efficient electrochemistry with species in solution at the cathode. Isothermal titration calorimetry shows that the change in surface chemistry from unfunctionalized to S-functionalized carbons results in an increased affinity of the polysulfide intermediates for the S–MC materials, which is the likely cause for enhanced cyclability

A Chemogenetic Approach for the Optical Monitoring of Voltage in Neurons

Optical monitoring of neuronal voltage using fluorescent indicators is a powerful approach for the interrogation of the cellular and molecular logic of the nervous system. Herein, a semisynthetic tethered voltage indicator (STeVI1) based upon nile red is described that displays voltage sensitivity when genetically targeted to neuronal membranes. This environmentally sensitive probe allows for wash-free imaging and faithfully detects supra- and sub-threshold activity in neurons

Machine learning using digitized herbarium specimens to advance phenological research

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens—preserved plant material curated in natural history collections—but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth

The factor structure of the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen distinct populations

There is considerable evidence that self-criticism plays a major role in the vulnerability to and recovery from psychopathology. Methods to measure this process, and its change over time, are therefore important for research in psychopathology and well-being. This study examined the factor structure of a widely used measure, the Forms of Self-Criticising/Attacking & Self-Reassuring Scale in thirteen nonclinical samples (N = 7510) from twelve different countries: Australia (N = 319), Canada (N = 383), Switzerland (N = 230), Israel (N = 476), Italy (N = 389), Japan (N = 264), the Netherlands (N = 360), Portugal (N = 764), Slovakia (N = 1326), Taiwan (N = 417), the United Kingdom 1 (N = 1570), the United Kingdom 2 (N = 883), and USA (N = 331). This study used more advanced analyses than prior reports: a bifactor item-response theory model, a two-tier item-response theory model, and a non-parametric item-response theory (Mokken) scale analysis. Although the original three-factor solution for the FSCRS (distinguishing between Inadequate-Self, Hated-Self, and Reassured-Self) had an acceptable fit, two-tier models, with two general factors (Self-criticism and Self-reassurance) demonstrated the best fit across all samples. This study provides preliminary evidence suggesting that this two-factor structure can be used in a range of nonclinical contexts across countries and cultures. Inadequate-Self and Hated-Self might not by distinct factors in nonclinical samples. Future work may benefit from distinguishing between self-correction versus shame-based self-criticism.Peer reviewe

End points for sickle cell disease clinical trials: patient-reported outcomes, pain, and the brain

To address the global burden of sickle cell disease (SCD) and the need for novel therapies, the American Society of Hematology partnered with the US Food and Drug Administration to engage the work of 7 panels of clinicians, investigators, and patients to develop consensus recommendations for clinical trial end points. The panels conducted their work through literature reviews, assessment of available evidence, and expert judgment focusing on end points related to: patient-reported outcomes (PROs), pain (non-PROs), the brain, end-organ considerations, biomarkers, measurement of cure, and low-resource settings. This article presents the findings and recommendations of the PROs, pain, and brain panels, as well as relevant findings and recommendations from the biomarkers panel. The panels identify end points, where there were supporting data, to use in clinical trials of SCD. In addition, the panels discuss where further research is needed to support the development and validation of additional clinical trial end points