486 research outputs found

    Freight Operations Modelling for Urban Delivery and Pickup with Flexible Routing: Cluster Transport Modelling Incorporating Discrete-Event Simulation and GIS

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    Urban pickup and delivery (PUD) activities are important for logistics operations. Real operations for general freight involve a high degree of complexity due to daily variability. Discrete-event simulation (DES) is a method that can mimic real operations and include stochastic parameters. However, realistic vehicle routing is difficult to build in DES models. The objective is to create a DES model for realistic freight routing, which considers the driver’s routing decisions. Realistic models need to predict the delivery route (including time and distance) for variable consignment address and backhaul pickup. Geographic information systems (GIS) and DES were combined to develop freight PUD models. GIS was used to process geographical data. Two DES models were developed and compared. The first was a simple suburb model, and the second an intersection-based model. Real industrial data were applied including one-year consignment data and global positioning system (GPS) data. A case study of one delivery tour is shown, with results validated with actual GPS data. The DES results were also compared with conventional GIS models. The result shows the intersection-based model is adequate to mimic actual PUD routing. This work provides a method for combining GIS and DES to build freight operation models for urban PUD. This has the potential to help industry logistics practitioners better understand their current operations and experiment with different scenarios

    Minimum Viable Model (MVM) Methodology for Integration of Agile Methods into Operational Simulation of Logistics

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    Background: Logistics problems involve a large number of complexities, which makes the development of models challenging. While computer simulation models are developed for addressing complexities, it is essential to ensure that the necessary operational behaviours are captured, and that the architecture of the model is suitable to represent them. The early stage of simulation modelling, known as conceptual modelling (CM), is thus dependent on successfully extracting tacit operational knowledge and avoiding misunderstanding between the client (customer of the model) and simulation analyst. Objective: This paper developed a methodology for managing the knowledge-acquisition process needed to create a sufficient simulation model at the early or the CM stage to ensure the correctness of operation representation. Methods: A minimum viable model (MVM) methodology was proposed with five principles relevant to CM: iterative development, embedded communication, soliciting tacit knowledge, interactive face validity, and a sufficient model. The method was validated by a case study of freight operations, and the results were encouraging. Conclusions: The MVM method improved the architecture of the simulation model through eliciting tacit knowledge and clearing up communication misunderstandings. It also helped shape the architecture of the model towards the features most appreciated by the client, and features not needed in the model. Originality: The novel contribution of this work is the presentation of a method for eliciting tacit information from industrial clients, and building a minimally sufficient simulation model at the early modelling stage. The framework is demonstrated for logistics operations, though the principles may benefit simulation practitioners more generally.</jats:p

    LinkMind: Link Optimization in Swarming Mobile Sensor Networks

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    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation

    Neutrino Opacities in Neutron Stars with Kaon Condensates

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    The neutrino mean free paths in hot neutron-star matter are obtained in the presence of kaon condensates. The kaon-induced neutrino absorption process, which is allowed only in the presence of kaon condensates, is considered for both nondegenerate and degenerate neutrinos. The neutrino mean free path due to this process is compared with that for the neutrino-nucleon scattering. While the mean free path for the kaon-induced neutrino absorption process is shown to be shorter than the ordinary two-nucleon absorption process by several orders of magnitude when temperature is not very high, the neutrino-nucleon scattering process has still a dominant contribution to the neutrino opacity. Thus, the kaon-induced neutrino absorption process has a minor effect on the thermal and dynamical evolution of protoneutron stars.Comment: 35 pages, 4 figure

    Postglacial expansion of the arctic keystone copepod calanus glacialis

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    Calanus glacialis, a major contributor to zooplankton biomass in the Arctic shelf seas, is a key link between primary production and higher trophic levels that may be sensitive to climate warming. The aim of this study was to explore genetic variation in contemporary populations of this species to infer possible changes during the Quaternary period, and to assess its population structure in both space and time. Calanus glacialis was sampled in the fjords of Spitsbergen (Hornsund and Kongsfjorden) in 2003, 2004, 2006, 2009 and 2012. The sequence of a mitochondrial marker, belonging to the ND5 gene, selected for the study was 1249 base pairs long and distinguished 75 unique haplotypes among 140 individuals that formed three main clades. There was no detectable pattern in the distribution of haplotypes by geographic distance or over time. Interestingly, a Bayesian skyline plot suggested that a 1000-fold increase in population size occurred approximately 10,000 years before present, suggesting a species expansion after the Last Glacial Maximum.GAME from the National Science Centre, the Polish Ministry of Science and Higher Education Iuventus Plus [IP2014 050573]; FCT-PT [CCMAR/Multi/04326/2013]; [2011/03/B/NZ8/02876

    Identification of Different Donor-Acceptor Structures via Förster Resonance Energy Transfer (FRET) in Quantum-Dot-Perylene Bisimide Assemblies

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    Nanoassemblies are formed via self-assembly of ZnS capped CdSe quantum dots (QD) and perylene bisimide (PBI) dyes. Upon assembly formation the QD photoluminescence is quenched, as can be detected both via single particle detection and ensemble experiments in solution. Quenching has been assigned to FRET and NON-FRET processes. Analysis of FRET allows for a distinction between different geometries of the QD dye assemblies. Time-resolved single molecule spectroscopy reveals intrinsic fluctuations of the PBI fluorescence lifetime and spectrum, caused by rearrangement of the phenoxy side groups. The distribution of such molecular conformations and their changed dynamics upon assembly formation are discussed in the scope of FRET efficiency and surface ligand density

    Mitochondrial Cox1 Sequence Data Reliably Uncover Patterns of Insect Diversity But Suffer from High Lineage-Idiosyncratic Error Rates

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    The demand for scientific biodiversity data is increasing, but taxonomic expertise is often limited or not available. DNA sequencing is a potential remedy to overcome this taxonomic impediment. Mitochondrial DNA is most commonly used, e.g., for species identification ("DNA barcoding"). Here, we present the first study in arthropods based on a near-complete species sampling of a family-level taxon from the entire Australian region. We aimed to assess how reliably mtDNA data can capture species diversity when many sister species pairs are included. Then, we contrasted phylogenetic subsampling with the hitherto more commonly applied geographical subsampling, where sister species are not necessarily captured. We sequenced 800 bp cox1 for 1,439 individuals including 260 Australian species (78% species coverage). We used clustering with thresholds of 1 to 10% and general mixed Yule Coalescent (GMYC) analysis for the estimation of species richness. The performance metrics used were taxonomic accuracy and agreement between the morphological and molecular species richness estimation. Clustering (at the 3% level) and GMYC reliably estimated species diversity for single or multiple geographic regions, with an error for larger clades of lower than 10%, thus outperforming parataxonomy. However, the rates of error were higher for some individual genera, with values of up to 45% when very recent species formed nonmonophyletic clusters. Taxonomic accuracy was always lower, with error rates above 20% and a larger variation at the genus level (0 to 70%). Sørensen similarity indices calculated for morphospecies, 3% clusters and GMYC entities for different pairs of localities was consistent among methods and showed expected decrease over distance. Cox1 sequence data are a powerful tool for large-scale species richness estimation, with a great potential for use in ecology and β-diversity studies and for setting conservation priorities. However, error rates can be high in individual lineages

    Why the COI barcode should be the community DNA metabarcode for the Metazoa

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    Metabarcoding of complex metazoan communities is increasingly being used to measure biodiversity in terrestrial, freshwater, and marine ecosystems, revolutionizing our ability to observe patterns and infer processes regarding the origin and conservation of biodiversity. A fundamentally important question is which genetic marker to amplify, and although the mitochondrial cytochrome oxidase subunit I (COI) gene is one of the more widely used markers in metabarcoding for the Metazoa, doubts have recently been raised about its suitability. We argue that (i) the extensive coverage of reference‐sequence databases for COI, (ii) the variation it presents, (iii) the comparative advantages for denoising protein coding genes, and (iv) recent advances in DNA sequencing protocols argue in favour of standardising for the use of COI for metazoan community samples. We also highlight where research efforts should focus to maximise the utility of metabarcoding

    Metabarcoding of freshwater invertebrates to detect the effects of a pesticide spill

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    Biomonitoring underpins the environmental assessment of freshwater ecosystems and guides management and conservation. Current methodology for surveys of (macro)invertebrates uses coarse taxonomic identification where species-level resolution is difficult to obtain. Next-generation sequencing of entire assemblages (metabarcoding) provides a new approach for species detection, but requires further validation. We used metabarcoding of invertebrate assemblages with two fragments of the cox1 “barcode” and partial nuclear ribosomal (SSU) genes, to assess the effects of a pesticide spill in the River Kennet (southern England). Operational taxonomic unit (OTU) recovery was tested under 72 parameters (read denoising, filtering, pair merging and clustering). Similar taxonomic profiles were obtained under a broad range of parameters. The SSU marker recovered Platyhelminthes and Nematoda, missed by cox1, while Rotifera were only amplified with cox1. A reference set was created from all available barcode entries for Arthropoda in the BOLD database and clustered into OTUs. The River Kennet metabarcoding produced matches to 207 of these reference OTUs, five times the number of species recognized with morphological monitoring. The increase was due to the following: greater taxonomic resolution (e.g., splitting a single morphotaxon “Chironomidae” into 55 named OTUs); splitting of Linnaean binomials into multiple molecular OTUs; and the use of a filtration-flotation protocol for extraction of minute specimens (meiofauna). Community analyses revealed strong differences between “impacted” vs. “control” samples, detectable with each gene marker, for each major taxonomic group, and for meio- and macrofaunal samples separately. Thus, highly resolved taxonomic data can be extracted at a fraction of the time and cost of traditional nonmolecular methods, opening new avenues for freshwater invertebrate biodiversity monitoring and molecular ecology

    Evasion of anti-growth signaling: a key step in tumorigenesis and potential target for treatment and prophylaxis by natural compounds

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    The evasion of anti-growth signaling is an important characteristic of cancer cells. In order to continue to proliferate, cancer cells must somehow uncouple themselves from the many signals that exist to slow down cell growth. Here, we define the anti-growth signaling process, and review several important pathways involved in growth signaling: p53, phosphatase and tensin homolog (PTEN), retinoblastoma protein (Rb), Hippo, growth differentiation factor 15 (GDF15), AT-rich interactive domain 1A (ARID1A), Notch, insulin-like growth factor (IGF), and Krüppel-like factor 5 (KLF5) pathways. Aberrations in these processes in cancer cells involve mutations and thus the suppression of genes that prevent growth, as well as mutation and activation of genes involved in driving cell growth. Using these pathways as examples, we prioritize molecular targets that might be leveraged to promote anti-growth signaling in cancer cells. Interestingly, naturally-occurring phytochemicals found in human diets (either singly or as mixtures) may promote anti-growth signaling, and do so without the potentially adverse effects associated with synthetic chemicals. We review examples of naturally-occurring phytochemicals that may be applied to prevent cancer by antagonizing growth signaling, and propose one phytochemical for each pathway. These are: epigallocatechin-3-gallate (EGCG) for the Rb pathway, luteolin for p53, curcumin for PTEN, porphyrins for Hippo, genistein for GDF15, resveratrol for ARID1A, withaferin A for Notch and diguelin for the IGF1-receptor pathway. The coordination of anti-growth signaling and natural compound studies will provide insight into the future application of these compounds in the clinical setting
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