A semantic framework for automatic generation of computational workflows using distributed data and component catalogues

Computational workflows are a powerful paradigm to represent and manage complex applications, particularly in large-scale distributed scientific data analysis. Workflows represent application components that result in individual computations as well as their interdependences in terms of dataflow. Workflow systems use these representations to manage various aspects of workflow creation and execution for users, such as the automatic assignment of execution resources. This article describes an approach to automating a new aspect of the process: the selection of application components and data sources. We present a novel approach that enables users to specify varying degrees of detail and amount of constraints in a workflow request, including the specification of constraints on input, intermediate or output data in the workflow, abstract workflow component classes rather than specific component implementations, and generic reusable workflow templates that express a pre-defined combination of components. The algorithm elaborates the user request into a set of fully ground workflows with specific choices of data sources and codes to be used so that they can be submitted for mapping and execution. The algorithm searches through the space of possible candidate workflows by creating increasingly more specialized versions of the original template and eliminating candidates that violate constraints cumulated in the candidate workflow as components and data sources are selected. A novel feature of our approach is that it assumes a distributed architecture where data and component catalogues are separate from the workflow system. The algorithm explicitly poses queries to external catalogues, and therefore any reasoning regarding data or component properties is not assumed to occur within the workflow system. We describe our implementation of this approach in the Wings workflow system. This implementation uses the W3C Web Ontology Language and associated reasoners to implement the workflow system as well as the data and component catalogues. This research demonstrates the use of artificial intelligence techniques to support the kinds of automation envisioned by the scientific community for large-scale distributed scientific data analysis.     

Schrifttumsberichte

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Schrifttumsberichte

Ohne Zusammenfassung     

Schrifttumsberichte

Ohne Zusammenfassung     

Light‐Induced Surface Modification of Natural Plant Microparticles: Toward Colloidal Science and Cellular Adhesion Applications

Playing an instrumental role in the life of plants, pollen microparticles are one of the most fascinating biological materials in existence, with abundant and renewable supply, ultrahigh durability, and unique, species‐specific architectural features. Aside from their biological role, pollen microparticles also demonstrate broad utility as functional materials for drug delivery and microencapsulation, and increasingly for emulsion‐type applications. As natural pollen microparticles are predominantly hydrophobic, developing robust surface functionalization strategies to increase surface hydrophilicity would increase the range of colloidal science applications, including opening the door to interfacing microparticles with biological cells. This research investigates the extraction and light‐induced surface modification of discrete pollen microparticles from bee‐collected pollen granules toward achieving functional control over the responses elicited from discrete particles in colloidal science and cellular applications. Ultraviolet–ozone treatment is shown to increase the proportion of surface elemental oxygen and ketones, leading to increased surface hydrophilicity, enhanced particle dispersibility, tunable control over Pickering emulsion characteristics, and enhanced cellular adhesion. In summary, the findings demonstrate that light‐induced surface modification improves the functional properties of pollen microparticles, and such insights also have broad implications across materials science and environmental science applications.     

Multi-heterojunction large area HgCdTe long wavelength infrared photovoltaic detector for operation at near room temperatures

This paper describes a new multi-heterojunction n ⁺pp photovoltaic infrared photodetector. The device has been developed specifically for operation at temperatures of 200–300K in the long wavelength (8–14 μm) range of the infrared spectrum. The new structure solves the perennial problems of poor quantum efficiency and low dynamic resistance found in conventional long wavelength infrared photovoltaic detectors when operated near room temperature. Computer simulations show that devices with properly optimized multiple heterojunctions are capable of achieving the performance limits imposed by the statistical nature of thermal generation-recombination processes. In order to demonstrate the technology, multiple heterojunction devices have been fabricated on epilayers grown by isothermal vapor phase epitaxy of HgCdTe and in situ As p-type doping. The detector structures were formed using a combination of conventional dry etching, angled ion milling, and angled thermal evaporation for contact metal deposition. These multi-junction n ⁺pp HgCdTe heterostructure devices exhibit performances which make them useful for many applications. D* of optically immersed multiple heterostructure photovoltaic detectors exceeding 10⁸cmHz^1/2/W were measured at λ=10.6 μm and T=300K.     

CX3CL1 Action on Microglia Protects from Diet-Induced Obesity by Restoring POMC Neuronal Excitability and Melanocortin System Activity Impaired by High-Fat Diet Feeding

Both hypothalamic microglial inflammation and melanocortin pathway dysfunction contribute to diet-induced obesity (DIO) pathogenesis. Previous studies involving models of altered microglial signaling demonstrate altered DIO susceptibility with corresponding POMC neuron cytological changes, suggesting a link between microglia and the melanocortin system. We addressed this hypothesis using the specific microglial silencing molecule, CX3CL1 (fractalkine), to determine whether reducing hypothalamic microglial activation can restore POMC/melanocortin signaling to protect against DIO. We performed metabolic analyses in high fat diet (HFD)-fed mice with targeted viral overexpression of CX3CL1 in the hypothalamus. Electrophysiologic recording in hypothalamic slices from POMC-MAPT-GFP mice was used to determine the effects of HFD feeding and microglial silencing via minocycline or CX3CL1 on GFP-labeled POMC neurons. Finally, mice with hypothalamic overexpression of CX3CL1 received central treatment with the melanocortin receptor antagonist SHU9119 to determine whether melanocortin signaling is required for the metabolic benefits of CX3CL1. Hypothalamic overexpression of CX3CL1 increased leptin sensitivity and POMC gene expression, while reducing weight gain in animals fed an HFD. In electrophysiological recordings from hypothalamic slice preparations, HFD feeding was associated with reduced POMC neuron excitability and increased amplitude of inhibitory postsynaptic currents. Microglial silencing using minocycline or CX3CL1 treatment reversed these HFD-induced changes in POMC neuron electrophysiologic properties. Correspondingly, blockade of melanocortin receptor signaling in vivo prevented both the acute and chronic reduction in food intake and body weight mediated by CX3CL1. Our results show that suppressing microglial activation during HFD feeding reduces DIO susceptibility via a mechanism involving increased POMC neuron excitability and melanocortin signaling.     

Generalized Approach towards Secretion-Based Protein Production via Neutralization of Secretion-Preventing Cationic Substrate Residues

Many heterologous proteins can be secreted by bacterial ATP-binding cassette (ABC) transporters, provided that they are fused with the C-terminal signal sequence, but some proteins are not secretable even though they carry the right signal sequence. The invention of a method to secrete these non-secretable proteins would be valuable both for understanding the secretory physiology of ABC transporters and for industrial applications. Herein, we postulate that cationic “supercharged” regions within the target substrate protein block the secretion by ABC transporters. We also suggest that the secretion of such substrate proteins can be rescued by neutralizing those cationic supercharged regions via structure-preserving point mutageneses. Surface-protruding, non-structural cationic amino acids within the cationic supercharged regions were replaced by anionic or neutral hydrophilic amino acids, reducing the cationic charge density. The examples of rescued secretions we provide include the spike protein of SARS-CoV-2, glutathione-S-transferase, streptavidin, lipase, tyrosinase, cutinase, growth factors, etc. In summary, our study provides a method to predict the secretability and a tool to rescue the secretion by correcting the secretion-blocking regions, making a significant step in understanding the physiological properties of ABC transporter-dependent protein secretion and laying the foundation for the development of a secretion-based protein-producing platform.