104 research outputs found

    Supporting change processes in design: Complexity, prediction and reliability

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    Change to existing products is fundamental to design processes. New products are often designed through change or modification to existing products. Specific parts or subsystems are changed to similar ones whilst others are directly reused. Design by modification applies particularly to safety critical products where the reuse of existing working parts and subsystems can reduce cost and risk. However change is rarely a matter of just reusing or modifying parts. Changing one part can propagate through the entire design leading to costly rework or jeopardising the integrity of the whole product. This paper characterises product change based on studies in the aerospace and automotive industry and introduces tools to aid designers in understanding the potential effects of change. Two ways of supporting designers are described: probabilistic prediction of the effects of change and visualisation of change propagation through product connectivities. Change propagation has uncertainties which are amplified by the choices designers make in practice as they implement change. Change prediction and visualisation is discussed with reference to complexity in three areas of product development: the structural backcloth of connectivities in the existing product (and its processes), the descriptions of the product used in design and the actions taken to carry out changes

    Testing in the incremental design and development of complex products

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    Testing is an important aspect of design and development which consumes significant time and resource in many companies. However, it has received less research attention than many other activities in product development, and especially, very few publications report empirical studies of engineering testing. Such studies are needed to establish the importance of testing and inform the development of pragmatic support methods. This paper combines insights from literature study with findings from three empirical studies of testing. The case studies concern incrementally developed complex products in the automotive domain. A description of testing practice as observed in these studies is provided, confirming that testing activities are used for multiple purposes depending on the context, and are intertwined with design from start to finish of the development process, not done after it as many models depict. Descriptive process models are developed to indicate some of the key insights, and opportunities for further research are suggested

    Dermanyssus gallinae in layer farms in Kosovo: a high risk for salmonella prevalence

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    Background The poultry red mite (PRM), Dermanyssus gallinae (D.g.) is a serious ectoparasitic pest of poultry and potential pathogen vector. The prevalence of D. g. and the prevalence of Salmonella spp. within mites on infested laying poultry farms were investigated in Kosovo. Findings In total, 14 populated layer farms located in the Southern Kosovo were assessed for D. g. presence. Another two farms in this region were investigated 6 months after depopulation. Investigated flocks were all maintained in cages, a common housing system in Kosovo. A total of eight farms were found to be infested with D. g. (50%) at varying levels, including the two depopulated farms. The detection of Salmonella spp. from D. g. was carried out using PCR. Out of the eight layer farms infested with D. g., Salmonella spp. was present in mites on three farms (37.5%). Conclusions This study confirms the high prevalence of D. g. in layer flocks in Kosovo and demonstrates the link between this mite and the presence of Salmonella spp. on infested farms

    Linking compact dwarf starburst galaxies in the resolve survey to downsized blue nuggets

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    Abstract We identify and characterize compact dwarf starburst (CDS) galaxies in the RESOLVE survey, a volume-limited census of galaxies in the local universe, to probe whether this population contains any residual “blue nuggets,” a class of intensely star-forming compact galaxies first identified at high redshift z. Our 50 low-z CDS galaxies are defined by dwarf masses (stellar mass M* < 109.5 M⊙), compact bulged-disk or spheroid-dominated morphologies (using a quantitative criterion, \mu _\Delta > 8.6), and specific star formation rates above the defining threshold for high-z blue nuggets (log SSFR [Gyr−1] > −0.5). Across redshifts, blue nuggets exhibit three defining properties: compactness relative to contemporaneous galaxies, abundant cold gas, and formation via compaction in mergers or colliding streams. Those with halo mass below Mhalo ∼ 1011.5 M⊙ may in theory evade permanent quenching and cyclically refuel until the present day. Selected only for compactness and starburst activity, our CDS galaxies generally have Mhalo ≲ 1011.5 M⊙ and gas-to-stellar mass ratio ≳1. Moreover, analysis of archival DECaLS photometry and new 3D spectroscopic observations for CDS galaxies reveals a high rate of photometric and kinematic disturbances suggestive of dwarf mergers. The SSFRs, surface mass densities, and number counts of CDS galaxies are compatible with theoretical and observational expectations for redshift evolution in blue nuggets. We argue that CDS galaxies represent a maximally-starbursting subset of traditional compact dwarf classes such as blue compact dwarfs and blue E/S0s. We conclude that CDS galaxies represent a low-z tail of the blue nugget phenomenon formed via a moderated compaction channel that leaves open the possibility of disk regrowth and evolution into normal disk galaxies

    The Baryonic Collapse Efficiency of Galaxy Groups in the RESOLVE and ECO Surveys

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    We examine the z = 0 group-integrated stellar and cold baryonic (stars + cold atomic gas) mass functions (group SMF and CBMF) and the baryonic collapse efficiency (group cold baryonic to dark matter halo mass ratio) using the RESOLVE and ECO survey galaxy group catalogs and a galform semi-analytic model (SAM) mock catalog. The group SMF and CBMF fall off more steeply at high masses and rise with a shallower low-mass slope than the theoretical halo mass function (HMF). The transition occurs at group-integrated cold baryonic mass M_coldbary ~ 10^11 Msun. The SAM, however, has significantly fewer groups at the transition mass ~ 10^11 Msun and a steeper low-mass slope than the data, suggesting that feedback is too weak in low-mass halos and conversely too strong near the transition mass. Using literature prescriptions to include hot halo gas and potential unobservable galaxy gas produces a group BMF with slope similar to the HMF even below the transition mass. Its normalization is lower by a factor of ~2, in agreement with estimates of warm-hot gas making up the remaining difference. We compute baryonic collapse efficiency with the halo mass calculated two ways, via halo abundance matching (HAM) and via dynamics (extended all the way to three-galaxy groups using stacking). Using HAM, we find that baryonic collapse efficiencies reach a flat maximum for groups across the halo mass range of M_halo ~ 10^11.4-12 Msun, which we label "nascent groups." Using dynamics, however, we find greater scatter in baryonic collapse efficiencies, likely indicating variation in group hot-to-cold baryon ratios. Similarly, we see higher scatter in baryonic collapse efficiencies in the SAM when using its true groups and their group halo masses as opposed to friends-of-friends groups and HAM masses

    Securing future decentralised industrial IoT infrastructures: challenges and free open source solutions

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    peer-reviewedThe next industrial revolution is said to be paved by the use of novel Internet of Things (IoT) technology. One important aspect of the modern IoT infrastructures is decentralised communication, often called Peer-to-Peer (P2P). In the context of industrial communication, P2P contributes to resilience and improved stability for industrial components. Current industrial facilities, however, still rely on centralised networking schemes which are considered to be mandatory to comply with security standards. In order to succeed, introduced industrial P2P technology must maintain the current level of protection and also consider possible new threats. The presented work starts with a short analysis of well-established industrial communication infrastructures and how these could benefit from decentralised structures. Subsequently, previously undefined Information Technology (IT) security requirements are derived from the new cloud based decentralised industrial automation model architecture presented in this paper. To meet those requirements, state-of-the-art communication schemes and their open source implementations are presented and assessed for their usability in the context of industrial IoT. Finally, derived building blocks for industrial IoT P2P security are presented which are qualified to comply with the stated industrial IoT security requirements

    Serodiagnosis of Echinococcus spp. Infection: Explorative Selection of Diagnostic Antigens by Peptide Microarray

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    Crude or purified, somatic or metabolic extracts of native antigens are routinely used for the serodiagnosis of human helminthic infections. These antigens are often cross-reactive, i.e., recognized by sera from patients infected with heterologous helminth species. To overcome limitations in antigen production, test sensitivity and specificity, chemically synthesized peptides offer a pure and standardized alternative, provided they yield acceptable operative characteristics. Ongoing genome and proteome work create new resources for the identification of antigens. Making use of the growing amount of genomic and proteomic data available in public databases, we tested a bioinformatic procedure for the selection of potentially antigenic peptides from a collection of protein sequences including conceptually translated nucleotide sequence data of Echinococcus multilocularis and E. granulosus (Plathyhelminthes, Cestoda). The in silico selection was combined with high-throughput screening of peptides on microarray and systematic validation of reactive candidates in enzyme-linked immunosorbent assay. Our study proved the applicability of this approach for selection of peptide antigens with good diagnostic characteristics. Our results suggested the pooling of several peptides to reach a high level of sensitivity required for reliable immunodiagnosis

    Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

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    The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the upcoming v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development

    GAMA/G10-COSMOS/3D-HST: The 0<z<5 cosmic star-formation history, stellar- and dust-mass densities

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    We use the energy-balance code MAGPHYS to determine stellar and dust masses, and dust corrected star-formation rates for over 200,000 GAMA galaxies, 170,000 G10-COSMOS galaxies and 200,000 3D-HST galaxies. Our values agree well with previously reported measurements and constitute a representative and homogeneous dataset spanning a broad range in stellar mass (10^8---10^12 Msol), dust mass (10^6---10^9 Msol), and star-formation rates (0.01---100 Msol per yr), and over a broad redshift range (0.0 < z < 5.0). We combine these data to measure the cosmic star-formation history (CSFH), the stellar-mass density (SMD), and the dust-mass density (DMD) over a 12 Gyr timeline. The data mostly agree with previous estimates, where they exist, and provide a quasi-homogeneous dataset using consistent mass and star-formation estimators with consistent underlying assumptions over the full time range. As a consequence our formal errors are significantly reduced when compared to the historic literature. Integrating our cosmic star-formation history we precisely reproduce the stellar-mass density with an ISM replenishment factor of 0.50 +/- 0.07, consistent with our choice of Chabrier IMF plus some modest amount of stripped stellar mass. Exploring the cosmic dust density evolution, we find a gradual increase in dust density with lookback time. We build a simple phenomenological model from the CSFH to account for the dust mass evolution, and infer two key conclusions: (1) For every unit of stellar mass which is formed 0.0065---0.004 units of dust mass is also formed; (2) Over the history of the Universe approximately 90 to 95 per cent of all dust formed has been destroyed and/or ejected
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