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27 results for “Flavours”
Datasets for "Flavour-selective localization in interacting lattice fermions"
<p>This submission includes the datasets shown in the figures of journal article</p> <p>"Flavour-selective localization in interacting lattice fermions" by D. Tusi et al.<br> DOI: 10.1038/s41567-022-01726-5</p> <p>The naming of the files corresponds to the figure numbering in the original article.</p>
Dataset for flavour tagging R&D
<p>This is a dataset for flavour tagging R&D.</p> <p>It consists of b-jets, c-jets and light-jets in equal number and equal distributions of transverse momentum, pseudo-rapidity and track multiplicity. </p> <p>The jets are sampled from ttbar events produced from proton-proton collisions at 14 TeV, using Pythia8. An ATLAS-like detector is parameterized using Delphes. The anti-kT R=0.4 algorithm with calorimeter inputs is used to define the jets.</p> <p>Jets are labelled as b-jets if there is a b-hadron within dR<0.3 of the jet, otherwise as c-jets if there is a c-hadron within dR<0.3, otherwise as light-jets. </p> <p>Tracks are associated to jets if they are within dR<0.4. If this condition holds for more than one jet, only the closest one is considered. Tracks are represented by their perigee parameters (d0, z0, pt, phi, cotan(theta)), which are smeared according to track pt and track eta dependent uncertainties.</p> <p>This dataset is heavily based on the <a href="../records/4044628" target="_blank" rel="noopener">Secondary Vertex Finding in Jets Dataset</a> and we thank J. Shlomi for the code and input.</p>
A Nu Supersymmetric Anomaly-free Atlas: anomaly-free, flavour-dependent U(1) charge assignments for the Minimally Supersymmetric Standard Model plus three Standard Model-singlet superfields
<p>We present lists of anomaly-free charge assignments up to a maximum magnitude charge Qmax=10 for the chiral fermionic content of the MSSM plus 3 right-handed neutrinos. </p> <p>Due to the large number of solutions, we compress the list into the file MSSMnuRcharges_Qmax10.gz. Please note that the unzipped file is approximately 130GB in size. We additionally include a smaller file, MSSMnuRcharges_Qmax4, containing the subset of anomaly-free charge assignments up to a maximum magnitude charge Qmax=4.</p> <p>The files searchU1MSSM.cpp and searchU1MSSM.h contain C++ files (in the 2014 standard) to produce the solutions. runsearch.sh is a bash script that compiles the programs and then runs it for a sample set of inputs.</p> <p>We provide Mathematica notebooks Analytic_solution_generator.nb and Analytic_Checks.nb which respectively provide the parametrisation of the analytic solution and checks thereof.</p> <p>The files beginning 'filter' contain example programs that read in each line in the solution list, apply a filter and print only the solutions satisfying the conditions of that filter. runfilter.sh is a bash script that compiles the filters and then runs a single filter as an example.</p> <p>These data and programs are based on this paper: https://arxiv.org/abs/2107.07926.</p>
Fig. 4 in The Viability of Haemonchus Contortus (Nematoda, Strongylida) and Strongyloides Papillosus (Nematoda, Rhabditida) Larvae Exposed to Various Flavourings and Source Materials Used in Food Production
Fig. 4. The effect of alcohol flavourings and their compounds on the viability of larvae of nematodes of Ruminantia: а — β-Ionone, b — Citronellol, с — Acetoin; for explanations see fig. 1.
Fig. 2 in The Viability of Haemonchus Contortus (Nematoda, Strongylida) and Strongyloides Papillosus (Nematoda, Rhabditida) Larvae Exposed to Various Flavourings and Source Materials Used in Food Production
Fig. 2. The effect of acetate flavourings upon the viability of larvae of nematodes of Ruminantia: а — Ethyl acetate, b — Benzyl acetate; for explanations see fig. 1.
Fig. 3 in The Viability of Haemonchus Contortus (Nematoda, Strongylida) and Strongyloides Papillosus (Nematoda, Rhabditida) Larvae Exposed to Various Flavourings and Source Materials Used in Food Production
Fig. 3. The effect of alcohol flavourings and their compounds on the viability of larvae of nematodes of Ruminantia: а — α-Terpineol, b — Benzyl alcohol, с — Citral, d — L-Linalool; for explanations see fig. 1.
Fig. 1 in The Viability of Haemonchus Contortus (Nematoda, Strongylida) and Strongyloides Papillosus (Nematoda, Rhabditida) Larvae Exposed to Various Flavourings and Source Materials Used in Food Production
Fig. 1. The effect of aldehyde flavourings on the viability of larvae of nematodes of Ruminantia: а — p-Anisaldehyde; b — Benzaldehyde; с — γ-Undecalactone; d — Cinnamaldehyde; the ordinate axis indicates the percentage of living nematode larvae in 24-hour experiment; the abscissa axis indicates the concentration of the active substance (%); (К) control, where the concentration of the active substance is 0 %; (L3) infective larvae of S. papillosusor H. contortus; (L1, L2) non-infective larvae of S. papillosus; small square in the centre corresponds to the median, lower and upper edge of the large rectangle corresponds to first and third quartiles, respectively, the vertical segments, directed upward and downward from the rectangles, correspond to minimum and maximum values (n = 8).
Fig. 5 in The Viability of Haemonchus Contortus (Nematoda, Strongylida) and Strongyloides Papillosus (Nematoda, Rhabditida) Larvae Exposed to Various Flavourings and Source Materials Used in Food Production
Fig. 5. The effect of D-limonene on the viability of larvae of nematodes of Ruminantia: for explanations see fig. 1.
Anomaly-free, flavour-dependent U(1) charge assignments for Standard Model/Standard Model plus three right-handed neutrino fermionic content
<p>We present lists of anomaly-free charge combinations up to a maximum magnitude charge Qmax given by the number at the end of the filename. Filenames beginning "SMcharges" are for the Standard Model fermion content, whereas "SMnuRcharges" are for Standard Model plus three right-handed neutrino fermion content. Use the bunzip2 program to unpack the larger files with a bz2 suffix.</p> <p>The files searchU1.cpp and searchU1.h contain C++ files (in the 2014 standard) to produce the solutions. runme.sh is a bash script that compiles the programs and then runs it several times, once to produce each file.</p> <p>filterNeut.cpp contains an example program that reads in one of the solution lists, applies a filter to it, and only prints out solutions that satisfy the filter.</p> <p>These data and programs are based on this paper: https://arxiv.org/abs/1812.04602</p> <p> </p>
Top quark pair events for heavy flavour tagging and vertexing at the LHC
<p>This data contains jets from top anti-top decays. The event and parton shower are simulated in Pythia 8 with a centre of mass energy of 13 TeV, with detector response modelled in the Delphes framework. The detector response is modelled on the ATLAS detector, and a mean pileup of 50 was used.</p> <p>The dataset consists of jets, jet constituents, and truth heavy-flavour hadrons. For each jet, up to 50 charged constituents and 5 truth hadrons are included. Each constituent includes a link to the truth hadron associated, if such a link exists. </p> <p>Provided are 5 files, which are detailed below</p> <ul> <li>class_dict.yaml - Details the relative weights for classification labels, based on the frequency of occurrence for a given entry. Labels are detailed below.</li> <li>norm_dict.yaml - Contains the means and standard deviations of variables that can be used for training, allowing for scaling.</li> <li>pp_output_train.h5 - 13.5 million training jets, consisting of 4.5 million b-jets, c-jets, and light-flavoured jets. Resampling is applied over the jet pT and eta, to ensure equivalent kinematic distributions</li> <li>pp_output_val.h5 - 1.35 million jets for validation, consisting of 450,000 of each jet flavour. Kinematics are resampled in the same way as the training file.</li> <li>pp_output_test_ttbar.h5 - 1.35 million jets for evaluation, consisting of 450,000 of each jet flavour, with no kinematic resampling applied.</li> </ul> <p>Each h5 file contains the following groups:</p> <ul> <li>Jets - (N,) - N jets, including variables such as jet kinematics, flavours, and summary statistics on the number of hadrons and constituents in the jet.</li> <li>Consts (N,50) - Up to 50 charged constituents per jet. Includes details on constituent kinematics and identification. A variable 'valid' is True for tracks in the jet, and False for all other tracks. The additional variable 'truth_hadron_idx' details which hadron (if any) a constituent is associated to.</li> <li>Hadrons (N, 5) - Up to 5 truth heavy-flavour hadrons per jet. Each hadron includes details on kinematics. The variable 'hadron_idx' represents an ID for the hadron, and matches to the constituent variable 'truth_hadron_idx'.</li> </ul> <p>Each group contains both variables that can be used in training, and truth labels, which are as follows:</p> <ul> <li>Jets <ul> <li>flavour - Flavour ID of the jet, 5 for b-jets (containing at least 1 b-hadron within a 0.4 dR(jet, hadron) match), 4 for c-jets (no b-hadrons, and contains at least 1 c-hadron), 0 for light-flavoured jets (contains no b- or c-hadrons)</li> </ul> </li> <li>Consts <ul> <li>truth_hadron_idx - integer that refers to hadron that produced the constituent. '-1' for padded tracks, or tracks with no truth heavy flavour hadron (e.g, pileup, hadronisation).</li> <li>truth_vertex_idx - integer that refers to the vertex a constituent came from - if two tracks have an equivalent truth_vertex_idx, they originate from the same vertex.</li> </ul> </li> <li>Hadrons <ul> <li> <div>hadron_idx - The idx of the hadron, value is '-1' for padded hadrons, 0-4 for remaining hadrons. If a constituent 'truth_hadron_idx' matches with this value, then the constituent came from this heavy flavour hadron decay.</div> </li> <li>flavour - The flavour of the hadron. '5' if the hadron contains at least 1 b-quark, '4' if there is no b-quark but a c-quark is present, '-1' for padded hadrons</li> <li>pt, lxy, dr, mass - The transverse momentum (pt) [GeV], transverse distance between hadronic decay vertex and the primary vertex (lxy) [mm], dR(Jet, Hadron), and the hadron truth mass [GeV]</li> </ul> </li> </ul> <p><span>This dataset allows for studies into algorithms that aim to perform vertex reconstruction.</span></p>
Spent Coffee Grounds as a Sustainable Coffee Flavouring Ingredient in Muffins
<p>Data for the paper entitles: Spent Coffee Grounds as a Sustainable Coffee Flavouring Ingredient in Muffins <br>Published by Sina Breian Solberg and Svein Øivind Solberg<br>Journal: Exploration of Foods and Foodomics, December 2024</p> <p>Affiliation SBS: The National Bakery School, London South Bank University, London SE1 0AA, United Kingdom <br>Affiliation SØS: Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, Inland Norway University of Applied Sciences, Ridabu, Norway</p> <p>Correspondence: Svein Øivind Solberg, Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, Inland Norway University of Applied Sciences, 2322 Ridabu, Norway; svein.solberg@inn.no.</p>
Supplementary files for 'Adding 'flavour' to past cuisines: first steps towards a phytolith reference collection of modern Mediterranean herbs'
<p><strong>ESM1</strong>. Supplementary tables:</p> <ul> <li> <p><strong><span>Table S1</span></strong><span>. List of samples analysed in this study. </span><span>Phytolith concentration per gram of original plant tissue. BBG: Barcelona Botanical Garden. BGPC: Botanical Park & Gardens of Crete. PPFF: Park for the Preservation of Fauna and Flora of the Technical University of Crete. Aerial parts: mix of leaves and flowers/inflorescences.</span></p> </li> <li> <p><strong>Table S2</strong>. <span>Protocol for extracting phytoliths from modern plants.</span></p> </li> <li> <p><strong><span>Table S3</span></strong><span>. Weight (in grams) of the original dry plant tissue and the ash left after processing the samples, number of phytoliths observed in each sample and phytolith concentration per gram of original dry plant tissue.</span></p> </li> <li> <p><strong><span>Table S4</span></strong><span>. Code used for describing phytolith morphotypes and sub-morphotypes according to the ICPN 2.0 (ICPT 2019).</span></p> </li> <li><strong><span>Table S5</span></strong><span>. Results of the microscopic analysis of phytolith samples from modern Mediterranean herbs.</span></li> </ul> <p><span><strong>ESM2</strong>. Reference atlas of phytoliths observed in modern Mediterranean herbs.</span></p>
Flavour Stability of Sterilised Chickpeas Stored in Pouches
<p>Final data used for figures in the paper Noordraven, L. E.C., Petersen, M. A., Van Loey, A. M., & Bredie, W. L. (2021). Flavour stability of sterilised chickpeas stored in pouches. <em>Current Research in Food Science</em>.: <a href="https://doi.org/10.1016/j.crfs.2021.10.011?_ga=2.250986822.1988728626.1635610214-937081454.1617605331">https://doi.org/10.1016/j.crfs.2021.10.011</a></p>
The effect of element intensity that distinguishes flavour in a food packaging on the memory and perception of Peruvian millennials and centennials
<p><em>ABSTRACT</em><br> Background: Globalization has greatly facilitated access to all kinds of products and brands from different parts of the world, increasing consumer choices and, consequently, competition among packaged products. For this reason, a brand's packaging design to attract consumers must stand out among its competitors, especially if it is a new product or a new flavour. In this context, it becomes necessary to explore dimensions of packaging design that allow a high degree of differentiation. In that way, there are very efficient strategies and approaches used in the literature to perform this exploration in packagings, such as perception evaluations measured with attributes and eye-tracking technology that records direct information about visual attention on the most distinctive elements. Thus, the present study aims to determine the impact of the presentation of a new flavour on packaging by varying the intensity of the stimulus that represents it according to the Weber-Fechner law, using three main elements of the packaging: text, colour, and image.<br> Methods: The experiment exposed three groups of participants (n=30) to 3 stimuli, which were based on adding an element as the intensity of the flavour description of three products from three different food categories was intended to increase. This study used the RealEye webcam eye-tracking platform to measure attention, and a self-administered questionnaire was used to examine perception and recall. <br> Results: First, the results show that greater intensity expressed in a more significant number of visual elements facilitates flavour distinction. Second, the results reveal that perceived difficulty in flavour differentiation correlates strongly with the presence of colour and image. <br> Conclusions: Therefore, this study provides an approach to ways to optimize the intensity of flavour distinctiveness elements that may be useful, especially for less recognized brands.</p>
The Effect of Natural Food Flavourings on Gastrointestinal and Cardiovascular Physiological Responses.
ClinicalTrials.gov study NCT01350284. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Comparison of 5 Buffering Agents on Changes in Salivary pH in Individuals Previously Exposed to a Test Flavoured Milk
ClinicalTrials.gov study NCT03513575. IPD Sharing: UNDECIDED. Countries: 1. Publications: 7.
Iron-fortified Flavoured Skimmed Milk With or Without Vitamin D in Iron Deficient Women
ClinicalTrials.gov study NCT01739907. IPD Sharing: Not stated. Countries: 0. Publications: 6.
Warming Sensation Intensity and Acceptability of the Flavour, Local Tolerability of Paracetamol 500 mg + Pseudoephedrine 30 mg Syrup in Patients Suffering a URTI
ClinicalTrials.gov study NCT01586962. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Warming Sensation Intensity and Acceptability of the Flavour, Local Tolerability of Paracetamol 500 mg + Phenylephrine 10mg + Guaifenesin 200 mg Syrup in Patients Suffering a Upper Respiratory Tract I
ClinicalTrials.gov study NCT01576809. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Double-blind Study in Paediatric Epileptic to Compare the Subject Preference for ESL Suspension Formulation With Alternative Flavours
ClinicalTrials.gov study NCT02021461. IPD Sharing: Not stated. Countries: 2. Publications: 0.
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