Dispatcher3 D4.2 - Prototype package (first release) - User manual

This deliverable along with deliverable D4.1. Technical documentation first release consists of the release of the first prototype of Dispatcher3. The release consists of the binaries and Docker version of the prototype (sent to the Topic Manager). The first release prototype package consists of a set on individual machine learning models which can be executed using Jupyter notebooks. It also includes the integration of the outcome of some of these individual models into a visualisation which would be part of the advice generator to provide high-level information to the end users. All models described in the Deliverable D4.1 will be available and executable in this release. Data required to run the models (with some examples) are also provided. If data are public raw sample values are provided, otherwise pre-computed features are delivered so that the models can be run on individual flight examples. The prototypes can be run using local data (provided in the release) or with data stored in cloud storage (Amazon Web Services (AWS)). This deliverable serves as a manual for the execution of the first release prototype software

Pre-Tactical Prediction of Atfm Delay for Individual Flights

The day prior operations, the operation plan is drawn generating a first set of flight plans with the objective of identifying potential network issues and preparing pre-tactical preventing measures. During the day of operation flight plans will be updated and pre-tactical actions implemented if needed by the duty manager, in order to minimise the propagation of disruption in the network. This paper focuses on the estimation of ATFM delay for individual flights during the pre-tactical phase. The main objective is to anticipate which flights might be affected by ATFM regulations and the amount of delay will be assigned to them

Dispatcher3 – Machine learning to support flight planning processes

This poster will present the final results of the Clean Sky 2 project Dispatcher3. Dispatcher3 focuses on the use of machine learning techniques to support flight operations prior departure with holding predictions, runway at arrival estimation and fuel deviations pre-departure to support the flight crew, and ATFM and reactionary delays on D-1 to support the duty manage

Dispatcher3 – Machine learning for efficient flight planning - Approach and challenges for data-driven prototypes in air transport

Machine learning techniques to support decision making processes are in trend. These are particularly relevant in the context of flight management where large datasets of planned and realised operations are available. Current operations experience discrepancies between planned and executed flight plan, these might be due to external factors (e.g. weather, congestion) and might lead to sub-optimal decisions (e.g. recovering delay (burning extra fuel) when no holding is expected at arrival and therefore it was no needed). Dispatcher3 produces a set of machine learning models to support flight crew pre-departure, with estimations on expected holding at arrival, runway in use and fuel usage, and the airline’s duty manager on pre-tactical actions, with models trained with a larger look ahead time for ATFM and reactionary delay estimations. This paper describes the prototype architecture and approach of Dispatcher3 with particular focus on the challenges faced by this type of data-driven machine learning models in the field of air transport ranging: from technical aspects such as data leakage to operational requirements such as the consideration and estimation of uncertainty. These considerations should be relevant for projects which try to use machine learning in the field of aviation in general

Paper-based chromatic toxicity bioassay by analysis of bacterial ferricyanide reduction

Water quality assessment requires a continuous and strict analysis of samples to guarantee compliance with established standards. Nowadays, the increasing number of pollutants and their synergistic effects lead to the development general toxicity bioassays capable to analyse water pollution as a whole. Current general toxicity methods, e.g. Microtox®, rely on long operation protocols, the use of complex and expensive instrumentation and sample pre-treatment, which should be transported to the laboratory for analysis. These requirements delay sample analysis and hence, the response to avoid an environmental catastrophe. In an attempt to solve it, a fast (15 min) and low-cost toxicity bioassay based on the chromatic changes associated to bacterial ferricyanide reduction is here presented. E. coli cells (used as model bacteria) were stably trapped on low-cost paper matrices (cellulose-based paper discs, PDs) and remained viable for long times (1 month at -20 °C). Apart from bacterial carrier, paper matrices also acted as a fluidic element, allowing fluid management without the need of external pumps. Bioassay evaluation was performed using copper as model toxic agent. Chromatic changes associated to bacterial ferricyanide reduction were determined by three different transduction methods, i.e. (i) optical reflectometry (as reference method), (ii) image analysis and (iii) visual inspection. In all cases, bioassay results (in terms of half maximal effective concentrations, EC50) were in agreement with already reported data, confirming the good performance of the bioassay. The validation of the bioassay was performed by analysis of real samples from natural sources, which were analysed and compared with a reference method (i.e. Microtox). Obtained results showed agreement for about 70% of toxic samples and 80% of non-toxic samples, which may validate the use of this simple and quick protocol in the determination of general toxicity. The minimum instrumentation requirements and the simplicity of the bioassay open the possibility of in-situ water toxicity assessment with a fast and low-cost protocolPostprint (author's final draft

QTL mapping of melon fruit quality traits using a high-density GBS-based genetic map

Background Melon shows a broad diversity in fruit morphology and quality, which is still underexploited in breeding programs. The knowledge of the genetic basis of fruit quality traits is important for identifying new alleles that may be introduced in elite material by highly efficient molecular breeding tools. Results In order to identify QTLs controlling fruit quality, a recombinant inbred line population was developed using two commercial cultivars as parental lines: “Védrantais”, from the cantalupensis group, and “Piel de Sapo”, from the inodorus group. Both have desirable quality traits for the market, but their fruits differ in traits such as rind and flesh color, sugar content, ripening behavior, size and shape. We used a genotyping-by-sequencing strategy to construct a dense genetic map, which included around five thousand variants distributed in 824 bins. The RIL population was phenotyped for quality and morphology traits, and we mapped 33 stable QTLs involved in sugar and carotenoid content, fruit and seed morphology and major loci controlling external color of immature fruit and mottled rind. The median confidence interval of the QTLs was 942 kb, suggesting that the high density of the genetic map helped in increasing the mapping resolution. Some of these intervals contained less than a hundred annotated genes, and an integrative strategy combining gene expression and resequencing data enabled identification of candidate genes for some of these traits. Conclusion Several QTLs controlling fruit quality traits in melon were identified and delimited to narrow genomic intervals, using a RIL population and a GBS-based genetic map. Keywords Quantitative trait loci Melon Fruit quality Fruit morphology Genotyping-by-sequencing Genetic mapinfo:eu-repo/semantics/publishedVersio

Transverse sphericity of primary charged particles in minimum bias proton-proton collisions at s=0.9\sqrt{s}=0.9, 2.76 and 7 TeV

Measurements of the sphericity of primary charged particles in minimum bias proton--proton collisions at $\sqrt{s}=0.9$, 2.76 and 7 TeV with the ALICE detector at the LHC are presented. The observable is linearized to be collinear safe and is measured in the plane perpendicular to the beam direction using primary charged tracks with $p_{\rm T}\geq0.5$ GeV/c in $|\eta|\leq0.8$. The mean sphericity as a function of the charged particle multiplicity at mid-rapidity ($N_{\rm ch}$) is reported for events with different $p_{\rm T}$ scales ("soft" and "hard") defined by the transverse momentum of the leading particle. In addition, the mean charged particle transverse momentum versus multiplicity is presented for the different event classes, and the sphericity distributions in bins of multiplicity are presented. The data are compared with calculations of standard Monte Carlo event generators. The transverse sphericity is found to grow with multiplicity at all collision energies, with a steeper rise at low $N_{\rm ch}$, whereas the event generators show the opposite tendency. The combined study of the sphericity and the mean $p_{\rm T}$ with multiplicity indicates that most of the tested event generators produce events with higher multiplicity by generating more back-to-back jets resulting in decreased sphericity (and isotropy). The PYTHIA6 generator with tune PERUGIA-2011 exhibits a noticeable improvement in describing the data, compared to the other tested generators.Comment: 21 pages, 9 captioned figures, 3 tables, authors from page 16, published version, figures from http://aliceinfo.cern.ch/ArtSubmission/node/308

Anisotropic flow of charged hadrons, pions and (anti-)protons measured at high transverse momentum in Pb-Pb collisions at sNN=2.76\sqrt{s_{\rm NN}}=2.76 TeV

The elliptic, $v_2$, triangular, $v_3$, and quadrangular, $v_4$, azimuthal anisotropic flow coefficients are measured for unidentified charged particles, pions and (anti-)protons in Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV with the ALICE detector at the Large Hadron Collider. Results obtained with the event plane and four-particle cumulant methods are reported for the pseudo-rapidity range $|\eta|<0.8$ at different collision centralities and as a function of transverse momentum, $p_{\rm T}$, out to $p_{\rm T}=20$ GeV/$c$. The observed non-zero elliptic and triangular flow depends only weakly on transverse momentum for $p_{\rm T}>8$ GeV/$c$. The small $p_{\rm T}$ dependence of the difference between elliptic flow results obtained from the event plane and four-particle cumulant methods suggests a common origin of flow fluctuations up to $p_{\rm T}=8$ GeV/$c$. The magnitude of the (anti-)proton elliptic and triangular flow is larger than that of pions out to at least $p_{\rm T}=8$ GeV/$c$ indicating that the particle type dependence persists out to high $p_{\rm T}$.Comment: 16 pages, 5 captioned figures, authors from page 11, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/186

Particle-yield modification in jet-like azimuthal di-hadron correlations in Pb-Pb collisions at sNN\sqrt{s_{\rm NN}} = 2.76 TeV

The yield of charged particles associated with high-$p_{\rm T}$ trigger particles ($8 < p_{\rm T} < 15$ GeV/$c$) is measured with the ALICE detector in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 2.76 TeV relative to proton-proton collisions at the same energy. The conditional per-trigger yields are extracted from the narrow jet-like correlation peaks in azimuthal di-hadron correlations. In the 5% most central collisions, we observe that the yield of associated charged particles with transverse momenta $p_{\rm T}> 3$ GeV/$c$ on the away-side drops to about 60% of that observed in pp collisions, while on the near-side a moderate enhancement of 20-30% is found.Comment: 15 pages, 2 captioned figures, 1 table, authors from page 10, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/350

Towards a TILLING platform for functional genomics in Piel de Sapo melons

Background The availability of genetic and genomic resources for melon has increased significantly, but functional genomics resources are still limited for this crop. TILLING is a powerful reverse genetics approach that can be utilized to generate novel mutations in candidate genes. A TILLING resource is available for cantalupensis melons, but not for inodorus melons, the other main commercial group. Results A new ethyl methanesulfonate-mutagenized (EMS) melon population was generated for the first time in an andromonoecious non-climacteric inodorus Piel de Sapo genetic background. Diverse mutant phenotypes in seedlings, vines and fruits were observed, some of which were of possible commercial interest. The population was first screened for mutations in three target genes involved in disease resistance and fruit quality (Cm-PDS, Cm-eIF4E and Cm-eIFI(iso)4E). The same genes were also tilled in the available monoecious and climacteric cantalupensis EMS melon population. The overall mutation density in this first Piel de Sapo TILLING platform was estimated to be 1 mutation/1.5 Mb by screening four additional genes (Cm-ACO1, Cm-NOR, Cm-DET1 and Cm-DHS). Thirty-three point mutations were found for the seven gene targets, six of which were predicted to have an impact on the function of the protein. The genotype/phenotype correlation was demonstrated for a loss-of-function mutation in the Phytoene desaturase gene, which is involved in carotenoid biosynthesis. Conclusions The TILLING approach was successful at providing new mutations in the genetic background of Piel de Sapo in most of the analyzed genes, even in genes for which natural variation is extremely low. This new resource will facilitate reverse genetics studies in non-climacteric melons, contributing materially to future genomic and breeding studies.González, M.; Xu, M.; Esteras Gómez, C.; Roig Montaner, MC.; Monforte Gilabert, AJ.; Troadec, C.; Pujol, M.... (2011). 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