Performance and Functionality Based Design Methods for Improved and Novel Aircraft Engine Components for Additive Manufacturing

For aircraft engine manufacturers the technology of AM appears promising. AM provides the opportunity for a highly flexible and a cost effective part production. Furthermore AM offers new potentials and possibilities for lightweight designs. The implementation and applications of AM can be divided in three different strategic application levels. The first level includes manufacturing simple existing parts; these kinds of parts are already in production. In the second level, new design tools, such as structural optimization, are used to improve an existing part by benefiting from the new design freedom but without changing its functionality. The third level includes novel parts with new functionality. This paper presents design methods for AM parts for the second and third level: performance and solution based approach, respectively. Also the safety classification of engine parts is looked into. Step-by-step design methods are presented, accompanied by case studies that demonstrate improvement to the initial design: a light weight, topology optimized turbine guide vane (level two) and an aircraft engine casing design that has an improved tip clearance behavior under transient operating cycles (level three).Mechanical Engineerin

Audition in vampire bats, Desmodus rotundus

1. Within the tonotopic organization of the inferior colliculus two frequency ranges are well represented: a frequency range within that of the echolocation signals from 50 to 100 kHz, and a frequency band below that of the echolocation sounds, from 10 to 35 kHz. The frequency range between these two bands, from about 40 to 50 kHz is distinctly underrepresented (Fig. 3B). 2. Units with BFs in the lower frequency range (10–25 kHz) were most sensitive with thresholds of -5 to -11 dB SPL, and units with BFs within the frequency range of the echolocation signals had minimal thresholds around 0 dB SPL (Fig. 1). 3. In the medial part of the rostral inferior colliculus units were encountered which preferentially or exclusively responded to noise stimuli. — Seven neurons were found which were only excited by human breathing noises and not by pure tones, frequency modulated signals or various noise bands. These neurons were considered as a subspeciality of the larger sample of noise-sensitive neurons. — The maximal auditory sensitivity in the frequency range below that of echolocation, and the conspicuous existence of noise and breathing-noise sensitive units in the inferior colliculus are discussed in context with the foraging behavior of vampire bats

Soil control on runoff response to climate change in regional climate model simulations

Simulations with seven regional climate models driven by a common control climate simulation of a GCM carried out for Europe in the context of the (European Union) EU-funded Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project were analyzed with respect to land surface hydrology in the Rhine basin. In particular, the annual cycle of the terrestrial water storage was compared to analyses based on the 40-yr ECMWF Re-Analysis (ERA-40) atmospheric convergence and observed Rhine discharge data. In addition, an analysis was made of the partitioning of convergence anomalies over anomalies in runoff and storage. This analysis revealed that most models underestimate the size of the water storage and consequently overestimated the response of runoff to anomalies in net convergence. The partitioning of these anomalies over runoff and storage was indicative for the response of the simulated runoff to a projected climate change consistent with the greenhouse gas A2 Synthesis Report on Emission Scenarios (SRES). In particular, the annual cycle of runoff is affected largely by the terrestrial storage reservoir. Larger storage capacity leads to smaller changes in both wintertime and summertime monthly mean runoff. The sustained summertime evaporation resulting from larger storage reservoirs may have a noticeable impact on the summertime surface temperature projections

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

Acknowledgments We thank Reik V. Donner for inspiring suggestions that initialized the work presented herein. Jan H. Feldhoff is credited for providing us with the STARS simulation data and for his contributions to fruitful discussions. Comments by the anonymous reviewers are gratefully acknowledged as they led to substantial improvements of the manuscript.Peer reviewedPublisher PD

Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies.

Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades. We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease. Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues. Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions

A framework for a net environmental benefit analysis based comparative assessment of decommissioning options for anthropogenic subsea structures: A North Sea case study

Taxpayers and operators worldwide have significant current liabilities associated with decommissioning of offshore Oil & Gas (O&G) assets. Consequently, decommissioning is at the forefront of industrial, governmental, and non-governmental agendas. Decommissioning is a highly complex activity with health, safety, environmental, social, economic, and technical implications. Increasing scientific evidence supports that manmade subsea structures create hard, artificial reef habitats that provide ecological and social benefits to society. Given the significant uncertainty regarding how subsea structures should be retired at the end of their operational lifetimes, it is necessary for governments, taxpayers, and operators to understand the risks and benefits associated with potential decommissioning options. Currently, the North Sea decommissioning process is based on the policies and direction of the Oslo and Paris Convention’s (OSPAR) Decision 98/3 and follow comparative assessment (CA) multiple-criteria decision analysis (MCDA) guidelines to determine the best overall strategy for decommissioning subsea structures; however, CA MCDA processes can be biased, ambiguous, difficult to use, interpret, and replicate, and limited in their consideration of multigenerational benefits. Consequently, to assist decision-makers in understanding and evaluating options and associated benefits for decommissioning subsea structures, this study adapted the net environmental benefit analysis (NEBA) framework to supplement and strengthen the CA process for evaluating decommissioning options for offshore O&G facilities. The net environmental benefit analysis based comparative assessment (NEBA-CA) framework is presented that addresses the growing need for a practical, quantitative, scientifically robust, defendable, and transparent MCDA approach to determine optimized decommissioning strategies for subsea assets. Increased transparency in CAs will provide an additional layer of credibility with regulators and society. The approach is data driven and a desktop analysis mainly relying on existing data. Using a North Sea case study, this work demonstrates the ability of NEBA-CA to resolve inherent complexity in comparing decommissioning options, thereby supporting operators in working with regulators to decommission assets in a way that maximizes ecosystem service benefits to society while managing site-related risks and costs. The NEBA-CA framework supplements and strengthens the standard CA process by 1) incorporating quantified metrics including multigenerational ecosystem service benefits and risks, 2) excluding front ranking (scoring) or weighting of metrics, and 3) providing consistent graphical displays to support visual differentiation of options and metrics

Sequencing identifies a distinct signature of circulating microRNAs in early radiographic knee osteoarthritis

OBJECTIVE: MicroRNAs act locally and systemically to impact osteoarthritis (OA) pathophysiology, but comprehensive profiling of the circulating miRNome in early vs late stages of OA has yet to be conducted. Sequencing has emerged as the preferred method for microRNA profiling since it offers high sensitivity and specificity. Our objective is to sequence the miRNome in plasma from 91 patients with early [Kellgren-Lawrence (KL) grade 0 or 1 (n = 41)] or late [KL grade 3 or 4 (n = 50)] symptomatic radiographic knee OA to identify unique microRNA signatures in each disease state. DESIGN: MicroRNA libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the Illumina NextSeq 550.Counts were produced for microRNAs captured in miRBase and for novel microRNAs. Statistical, bioinformatics, and computational biology approaches were used to refine and interpret the final list of microRNAs. RESULTS: From 215 differentially expressed microRNAs (FDR \u3c 0.01), 97 microRNAs showed an increase or decrease in expression in ≥85% of samples in the early OA group as compared to the median expression in the late OA group. Increasing this threshold to ≥95%, seven microRNAs were identified: hsa-miR-335-3p, hsa-miR-199a-5p, hsa-miR-671-3p, hsa-miR-1260b, hsa-miR-191-3p, hsa-miR-335-5p, and hsa-miR-543. Four novel microRNAs were present in ≥50% of early OA samples and had 27 predicted gene targets in common with the prioritized set of predicted gene targets from the 97 microRNAs, suggesting common underlying mechanisms. CONCLUSION: Applying sequencing to well-characterized patient cohorts produced unbiased profiling of the circulating miRNome and identified a unique panel of 11 microRNAs in early radiographic knee OA

Effects of external nutrient sources and extreme weather events on the nutrient budget of a Southern European coastal lagoon

The seasonal and annual nitrogen (N), phosphorus (P), and carbon (C) budgets of the mesotidal Ria Formosa lagoon, southern Portugal, were estimated to reveal the main inputs and outputs, the seasonal patterns, and how they may influence the ecological functioning of the system. The effects of extreme weather events such as long-lasting strong winds causing upwelling and strong rainfall were assessed. External nutrient inputs were quantified; ocean exchange was assessed in 24-h sampling campaigns, and final calculations were made using a hydrodynamic model of the lagoon. Rain and stream inputs were the main freshwater sources to the lagoon. However, wastewater treatment plant and groundwater discharges dominated nutrient input, together accounting for 98, 96, and 88 % of total C, N, and P input, respectively. Organic matter and nutrients were continuously exported to the ocean. This pattern was reversed following extreme events, such as strong winds in early summer that caused upwelling and after a period of heavy rainfall in late autumn. A principal component analysis (PCA) revealed that ammonium and organic N and C exchange were positively associated with temperature as opposed to pH and nitrate. These variables reflected mostly the benthic lagoon metabolism, whereas particulate P exchange was correlated to Chl a, indicating that this was more related to phytoplankton dynamics. The increase of stochastic events, as expected in climate change scenarios, may have strong effects on the ecological functioning of coastal lagoons, altering the C and nutrient budgets.Portuguese Science and Technology Foundation (FCT) [POCI/MAR/58427/2004, PPCDT/MAR/58427/2004]; Portuguese Science and Technology Foundation (FCT

The RACE Project: Robustness by Autonomous Competence Enhancement

This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system

Tropical and subtropical cloud transitions in weather and climate prediction models: The GCSS/WGNE pacific cross-section intercomparison (GPCI)

International audienceA model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ-the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June-July-August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yrECMWFRe-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models. © 2011 American Meteorological Society