60 research outputs found

    Why and How Knowledge Discovery Can Be Useful for Solving Problems with CBR

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    International audienceIn this talk, we discuss and illustrate links existing between knowledge discovery in databases (KDD), knowledge representation and reasoning (KRR), and case-based reasoning (CBR). KDD techniques especially based on Formal Concept Analysis (FCA) are well formalized and allow the design of concept lattices from binary and complex data. These concept lattices provide a realistic basis for knowledge base organization and ontology engineering. More generally, they can be used for representing knowledge and reasoning in knowledge systems and CBR systems as well

    Large scale genome-wide association and LDLA mapping study identifies QTLs for boar taint and related sex steroids

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    <p>Abstract</p> <p>Background</p> <p>Boar taint is observed in a high proportion of uncastrated male pigs and is characterized by an unpleasant odor/flavor in cooked meat, primarily caused by elevated levels of androstenone and skatole. Androstenone is a steroid produced in the testis in parallel with biosynthesis of other sex steroids like testosterone and estrogens. This represents a challenge when performing selection against androstenone in breeding programs, without simultaneously decreasing levels of other steroids. The aim of this study was to use high-density genome wide association (GWA) in combination with linkage disequilibrium-linkage analysis (LDLA) to identify quantitative trait loci (QTL) associated with boar taint compounds and related sex steroids in commercial Landrace (n = 1,251) and Duroc (n = 918) breeds.</p> <p>Results</p> <p>Altogether, 14 genome wide significant (GWS) QTL regions for androstenone in subcutaneous fat were obtained from the LDLA study in Landrace and 14 GWS QTL regions in Duroc. LDLA analysis revealed that 7 of these QTL regions, located on SSC 1, 2, 3, 7 and 15, were obtained in both breeds. All 14 GWS androstenone QTLs in Landrace are also affecting the estrogens at chromosome wise significance (CWS) or GWS levels, while in Duroc, 3 of the 14 QTLs affect androstenone without affecting any of the estrogens. For skatole, 10 and 4 QTLs were GWS in the LDLA analysis for Landrace and Duroc respectively, with 4 of these detected in both breeds. The GWS QTLs for skatole obtained by LDLA are located at SSC 1, 5, 6, 7, 10, 11, 13 and 14.</p> <p>Conclusion</p> <p>This is the first report applying the Porcine 60 K SNP array for simultaneous analysis of boar taint compounds and related sex hormones, using both GWA and LDLA approaches. Several QTLs are involved in regulation of androstenone and skatole, and most of the QTLs for androstenone are also affecting the levels of estrogens. Seven QTLs for androstenone were detected in one breed and confirmed in the other, i.e. in an independent sample, although the majority of QTLs are breed specific. Most QTLs for skatole do not negatively affect other sex hormones and should be easier to implement into the breeding scheme.</p

    Observations of the Crab Nebula and Pulsar with the Large-sized Telescope Prototype of the Cherenkov Telescope Array

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    The Cherenkov Telescope Array (CTA) is a next-generation ground-based observatory for gamma-ray astronomy at very high energies. The Large-Sized Telescope prototype (LST-1) is located at the CTA-North site, on the Canary Island of La Palma. LSTs are designed to provide optimal performance in the lowest part of the energy range covered by CTA, down to ≃20 GeV. LST-1 started performing astronomical observations in 2019 November, during its commissioning phase, and it has been taking data ever since. We present the first LST-1 observations of the Crab Nebula, the standard candle of very-high-energy gamma-ray astronomy, and use them, together with simulations, to assess the performance of the telescope. LST-1 has reached the expected performance during its commissioning period—only a minor adjustment of the preexisting simulations was needed to match the telescope’s behavior. The energy threshold at trigger level is around 20 GeV, rising to ≃30 GeV after data analysis. Performance parameters depend strongly on energy, and on the strength of the gamma-ray selection cuts in the analysis: angular resolution ranges from 0.°12-0.°40, and energy resolution from 15%-50%. Flux sensitivity is around 1.1% of the Crab Nebula flux above 250 GeV for a 50 hr observation (12% for 30 minutes). The spectral energy distribution (in the 0.03-30 TeV range) and the light curve obtained for the Crab Nebula agree with previous measurements, considering statistical and systematic uncertainties. A clear periodic signal is also detected from the pulsar at the center of the Nebula

    Multi-messenger observations of a binary neutron star merger

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    On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

    Multiwavelength study of the galactic PeVatron candidate LHAASO J2108+5157

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    Context. Several new ultrahigh-energy (UHE) γ-ray sources have recently been discovered by the Large High Altitude Air Shower Observatory (LHAASO) collaboration. These represent a step forward in the search for the so-called Galactic PeVatrons, the enigmatic sources of the Galactic cosmic rays up to PeV energies. However, it has been shown that multi-TeV γ-ray emission does not necessarily prove the existence of a hadronic accelerator in the source; indeed this emission could also be explained as inverse Compton scattering from electrons in a radiation-dominated environment. A clear distinction between the two major emission mechanisms would only be made possible by taking into account multi-wavelength data and detailed morphology of the source. Aims. We aim to understand the nature of the unidentified source LHAASO J2108+5157, which is one of the few known UHE sources with no very high-energy (VHE) counterpart. Methods. We observed LHAASO J2108+5157 in the X-ray band with XMM-Newton in 2021 for a total of 3.8 hours and at TeV energies with the Large-Sized Telescope prototype (LST-1), yielding 49 hours of good-quality data. In addition, we analyzed 12 years of Fermi-LAT data, to better constrain emission of its high-energy (HE) counterpart 4FGL J2108.0+5155. We used naima and jetset software packages to examine the leptonic and hadronic scenario of the multi-wavelength emission of the source. Results. We found an excess (3.7σ) in the LST-1 data at energies E &gt; 3 TeV. Further analysis of the whole LST-1 energy range, assuming a point-like source, resulted in a hint (2.2σ) of hard emission, which can be described with a single power law with a photon index of Σ = 1.6 ± 0.2 the range of 0.3 - 100 TeV. We did not find any significant extended emission that could be related to a supernova remnant (SNR) or pulsar wind nebula (PWN) in the XMM-Newton data, which puts strong constraints on possible synchrotron emission of relativistic electrons. We revealed a new potential hard source in Fermi-LAT data with a significance of 4σ and a photon index of Σ = 1.9 ± 0.2, which is not spatially correlated with LHAASO J2108+5157, but including it in the source model we were able to improve spectral representation of the HE counterpart 4FGL J2108.0+5155. Conclusions. The LST-1 and LHAASO observations can be explained as inverse Compton-dominated leptonic emission of relativistic electrons with a cutoff energy of 100-30+70 TeV. The low magnetic field in the source imposed by the X-ray upper limits on synchrotron emission is compatible with a hypothesis of a PWN or a TeV halo. Furthermore, the spectral properties of the HE counterpart are consistent with a Geminga-like pulsar, which would be able to power the VHE-UHE emission. Nevertheless, the lack of a pulsar in the neighborhood of the UHE source is a challenge to the PWN/TeV-halo scenario. The UHE γ rays can also be explained as π0 decay-dominated hadronic emission due to interaction of relativistic protons with one of the two known molecular clouds in the direction of the source. Indeed, the hard spectrum in the LST-1 band is compatible with protons escaping a shock around a middle-aged SNR because of their high low-energy cut-off, but the origin of the HE γ-ray emission remains an open question

    Southern African Large Telescope Spectroscopy of BL Lacs for the CTA project

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    In the last two decades, very-high-energy gamma-ray astronomy has reached maturity: over 200 sources have been detected, both Galactic and extragalactic, by ground-based experiments. At present, Active Galactic Nuclei (AGN) make up about 40% of the more than 200 sources detected at very high energies with ground-based telescopes, the majority of which are blazars, i.e. their jets are closely aligned with the line of sight to Earth and three quarters of which are classified as high-frequency peaked BL Lac objects. One challenge to studies of the cosmological evolution of BL Lacs is the difficulty of obtaining redshifts from their nearly featureless, continuum-dominated spectra. It is expected that a significant fraction of the AGN to be detected with the future Cherenkov Telescope Array (CTA) observatory will have no spectroscopic redshifts, compromising the reliability of BL Lac population studies, particularly of their cosmic evolution. We started an effort in 2019 to measure the redshifts of a large fraction of the AGN that are likely to be detected with CTA, using the Southern African Large Telescope (SALT). In this contribution, we present two results from an on-going SALT program focused on the determination of BL Lac object redshifts that will be relevant for the CTA observatory

    Star tracking for pointing determination of Imaging Atmospheric Cherenkov Telescopes: Application to the Large-Sized Telescope of the Cherenkov Telescope Array

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    We present a novel approach to the determination of the pointing of Imaging Atmospheric Cherenkov Telescopes (IACTs) using the trajectories of the stars in their camera s field of view. The method starts with the reconstruction of the star positions from the Cherenkov camera data, taking into account the point spread function of the telescope, to achieve a satisfying reconstruction accuracy of the pointing position. A simultaneous fit of all reconstructed star trajectories is then performed with the orthogonal distance regression (ODR) method. ODR allows us to correctly include the star position uncertainties and use the time as an independent variable. Having the time as an independent variable in the fit makes it better suitable for various star trajectories. This method can be applied to any IACT and requires neither specific hardware nor interface or special data-taking mode. In this paper, we use the Large-Sized Telescope (LST) data to validate it as a useful tool to improve the determination of the pointing direction during regular data taking. The simulation studies show that the accuracy and precision of the method are comparable with the design requirements on the pointing accuracy of the LST (=14''). With the typical LST event acquisition rate of 10 kHz, the method can achieve up to 50 Hz pointing monitoring rate, compared to O(1) Hz achievable with standard techniques. The application of the method to the LST prototype (LST-1) commissioning data shows the stable pointing performance of the telescope

    Performance of the joint LST-1 and MAGIC observations evaluated with Crab Nebula data

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    Aims. Large-Sized Telescope 1 (LST-1), the prototype for the Large-Sized Telescope at the upcoming Cherenkov Telescope Array Observatory, is concluding its commissioning phase at the Observatorio del Roque de los Muchachos on the island of La Palma. The proximity of LST-1 to the two MAGIC (Major Atmospheric Gamma Imaging Cherenkov) telescopes makes it possible to carry out observations of the same gamma-ray events with both systems. Methods. We describe the joint LST-1+MAGIC analysis pipeline and used simultaneous Crab Nebula observations and Monte Carlo simulations to assess the performance of the three-telescope system. The addition of the LST-1 telescope allows for the recovery of events in which one of the MAGIC images is too dim to survive analysis quality cuts. Results. Thanks to the resulting increase in the collection area and stronger background rejection, we found a significant improvement in sensitivity, allowing for the detection of 30% weaker fluxes in the energy range between 200 GeV and 3 TeV. The spectrum of the Crab Nebula, reconstructed in the energy range between ∼60 GeV and ∼10 TeV, is in agreement with previous measurements

    Hepatic levels of S-adenosylmethionine regulate the adaptive response to fasting

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    26 p.-6 fig.-1 tab.-1 graph. abst.There has been an intense focus to uncover the molecular mechanisms by which fasting triggers the adaptive cellular responses in the major organs of the body. Here, we show that in mice, hepatic S-adenosylmethionine (SAMe)—the principal methyl donor—acts as a metabolic sensor of nutrition to fine-tune the catabolic-fasting response by modulating phosphatidylethanolamine N-methyltransferase (PEMT) activity, endoplasmic reticulum-mitochondria contacts, β-oxidation, and ATP production in the liver, together with FGF21-mediated lipolysis and thermogenesis in adipose tissues. Notably, we show that glucagon induces the expression of the hepatic SAMe-synthesizing enzyme methionine adenosyltransferase α1 (MAT1A), which translocates to mitochondria-associated membranes. This leads to the production of this metabolite at these sites, which acts as a brake to prevent excessive β-oxidation and mitochondrial ATP synthesis and thereby endoplasmic reticulum stress and liver injury. This work provides important insights into the previously undescribed function of SAMe as a new arm of the metabolic adaptation to fasting.M.V.-R. is supported by Proyecto PID2020-119486RB-100 (funded by MCIN/AEI/10.13039/501100011033), Gilead Sciences International Research Scholars Program in Liver Disease, Acción Estratégica Ciberehd Emergentes 2018 (ISCIII), Fundación BBVA, HORIZON-TMA-MSCA-Doctoral Networks 2021 (101073094), and Redes de Investigación 2022 (RED2022-134485-T). M.L.M.-C. is supported by La CAIXA Foundation (LCF/PR/HP17/52190004), Proyecto PID2020-117116RB-I00 (funded by MCIN/AEI/10.13039/501100011033), Ayudas Fundación BBVA a equipos de investigación científica (Umbrella 2018), and AECC Scientific Foundation (Rare Cancers 2017). A.W. is supported by RTI2018-097503-B-I00 and PID2021-127169OB-I00, (funded by MCIN/AEI/10.13039/501100011033) and by “ERDF A way of making Europe,” Xunta de Galicia (Ayudas PRO-ERC), Fundación Mutua Madrileña, and European Community’s H2020 Framework Programme (ERC Consolidator grant no. 865157 and MSCA Doctoral Networks 2021 no. 101073094). C.M. is supported by CIBERNED. P.A. is supported by Ayudas para apoyar grupos de investigación del sistema Universitario Vasco (IT1476-22), PID2021-124425OB-I00 (funded by MCIN/AEI/10.13039/501100011033 and “ERDF A way of making Europe,” MCI/UE/ISCiii [PMP21/00080], and UPV/EHU [COLAB20/01]). M.F. and M.G.B. are supported by PID2019-105739GB-I00 and PID2020-115472GB-I00, respectively (funded by MCIN/AEI/10.13039/501100011033). M.G.B. is supported by Xunta de Galicia (ED431C 2019/013). C.A., T.L.-D., and J.B.-V. are recipients of pre-doctoral fellowships from Xunta de Galicia (ED481A-2020/046, ED481A-2018/042, and ED481A 2021/244, respectively). T.C.D. is supported by Fundación Científica AECC. A.T.-R. is a recipient of a pre-doctoral fellowship from Fundación Científica AECC. S.V.A. and C.R. are recipients of Margarita Salas postdoc grants under the “Plan de Recuperación Transformación” program funded by the Spanish Ministry of Universities with European Union’s NextGeneration EU funds (2021/PER/00020 and MU-21-UP2021-03071902373A, respectively). T.C.D., A.S.-R., and M.T.-C. are recipients of Ayuda RYC2020-029316-I, PRE2019/088960, and BES-2016/078493, respectively, supported by MCIN/AEI/10.13039/501100011033 and by El FSE invierte en tu futuro. S.L.-O. is a recipient of a pre-doctoral fellowship from the Departamento de Educación del Gobierno Vasco (PRE_2018_1_0372). P.A.-G. is recipient of a FPU pre-doctoral fellowship from the Ministry of Education (FPU19/02704). CIC bioGUNE is supported by Ayuda CEX2021-001136-S financiada por MCIN/AEI/10.13039/501100011033. A.B.-C. was funded by predoctoral contract PFIS (FI19/00240) from Instituto de Salud Carlos III (ISCIII) co-funded by Fondo Social Europeo (FSE), and A.D.-L. was funded by contract Juan Rodés (JR17/00016) from ISCIII. A.B.-C. is a Miguel Servet researcher (CPII22/00008) from ISCIII.Peer reviewe

    Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

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    Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified
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