Evolución en la formación de radicales lipídicos y pérdida de volátiles en nueces de Brasil empaquetadas al vacío y almacenadas a temperatura ambiente o refrigeradas

The Brazil nut is an important product from the Amazonian region and its productive chain is an income source for local communities. The effect of combinations of packaging atmospheres (loose or vacuum-packed) and storage temperatures (4±1 °C or 24±2 °C) on the tendency of lipid radical formation and on volatiles was investigated for the first time in shelled Brazil nut kernels. It was observed that refrigeration, whether combined with lose packing or vacuum packing, was effective to reduce the tendency for lipid radical formation, as detected by spin-trapping electron spin resonance (ESR) spectroscopy, as well as peroxides, conjugated dienes and 3-octen-2-one. However, the combination of refrigeration with vacuum packing, even using low-density polyethylene (LDPE) pouches with a high oxygen transmission rate (OTR), also reduced the formation of hexanal, which is a major off-flavor volatile, and thus should be recommended for the storage of Brazil nut kernels for the studied period.La nuez de Brasil es un producto importante de la región amazónica y su cadena productiva es fuente de ingresos para las comunidades locales. Se investigó por la primera vez el efecto de combinaciones de atmósferas de empaquetado (sueltas o empaquetadas al vacío) y temperaturas de almacenamiento (4 ± 1 °C o 24 ± 2 °C) sobre la evolución de la formación de radicales lipídicos y en los volátiles en nueces de Brasil. Se observó que la refrigeración, en combinación con envasado solo o al vacío, fue eficaz para reducir la formación de radicales lipídicos, como se detectó mediante espectroscopía de resonancia magnética de espín (ESR), así como de peróxidos, dienos conjugados y 3-octen-2-ona. Sin embargo, la combinación de refrigeración con envasado al vacío, incluso utilizando bolsas de polietileno de baja densidad (LDPE) con alta velocidad de transmisión de oxígeno (OTR), también redujo la formación de hexanal, que es un volátil de sabor desagradable, por lo que debería recomendarse para el almacenamiento de almendras de Brasil durante el período estudiado

Efficacy of methyl ester of conjugated linoleic acid (t10,c12 isomer) for sows and cows for reproduction

A mixture of methylated conjugated linoleic acid (CLA) isomers (t10,c12 and c9,t11) in equal proportions is the subject of this assessment. The active substance is considered to be CLA (t10,c12) methyl ester (ME). The Panel on Additives and Products or Substances used in Animal Feed (FEEDAP) of EFSA previously issued an opinion on the safety and efficacy of the product, in which it could not conclude on the efficacy of this additive for sows for reproduction and for cows for reproduction. The European Commission asked EFSA to deliver an opinion on the efficacy of this additive for sows and cows for reproduction, based on additional data submitted by the applicant. The FEEDAP Panel has performed the assessment of the new data following an approach in line with the principles laid down in Regulation (EC) No 429/2008 and the relevant guidance documents. In relation to the data on efficacy in sows for reproduction, owing to methodological shortcomings of the study submitted, including the duration of the study and the limited biological relevance of the effect observed, the FEEDAP Panel cannot conclude on the efficacy of CLA (t10,c12)-ME for sows for reproduction. The data related to dairy cows indicate that dietary CLA (t10,c12)-ME supplementation in the late dry period and/or lactation period showed an increase of the probability of pregnancy and a reduction of time to conception in the same reproductive cycle. However, considering that the minimum duration of efficacy studies for reproductive parameters is of at least two reproductive cycles, the FEEDAP Panel is not in a position to conclude on the efficacy of the additive for cows for reproduction

Performance of the CMS Level-1 trigger in proton-proton collisions at √s = 13 TeV

At the start of Run 2 in 2015, the LHC delivered proton-proton collisions at a center-of-mass energy of 13\TeV. During Run 2 (years 2015–2018) the LHC eventually reached a luminosity of 2.1× 10$^{34}$ cm$^{-2}$s$^{-1}$, almost three times that reached during Run 1 (2009–2013) and a factor of two larger than the LHC design value, leading to events with up to a mean of about 50 simultaneous inelastic proton-proton collisions per bunch crossing (pileup). The CMS Level-1 trigger was upgraded prior to 2016 to improve the selection of physics events in the challenging conditions posed by the second run of the LHC. This paper describes the performance of the CMS Level-1 trigger upgrade during the data taking period of 2016–2018. The upgraded trigger implements pattern recognition and boosted decision tree regression techniques for muon reconstruction, includes pileup subtraction for jets and energy sums, and incorporates pileup-dependent isolation requirements for electrons and tau leptons. In addition, the new trigger calculates high-level quantities such as the invariant mass of pairs of reconstructed particles. The upgrade reduces the trigger rate from background processes and improves the trigger efficiency for a wide variety of physics signals

Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques

Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The identification performances of a variety of algorithms are characterized in simulated events and directly compared with data. The algorithms are validated using proton-proton collision data at √s = 13TeV, corresponding to an integrated luminosity of 35.9 fb−1. Systematic uncertainties are assessed by comparing the results obtained using simulation and collision data. The new techniques studied in this paper provide significant performance improvements over non-ML techniques, reducing the background rate by up to an order of magnitude at the same signal efficiency

Pileup mitigation at CMS in 13 TeV data

With increasing instantaneous luminosity at the LHC come additional reconstruction challenges. At high luminosity, many collisions occur simultaneously within one proton-proton bunch crossing. The isolation of an interesting collision from the additional "pileup" collisions is needed for effective physics performance. In the CMS Collaboration, several techniques capable of mitigating the impact of these pileup collisions have been developed. Such methods include charged-hadron subtraction, pileup jet identification, isospin-based neutral particle "δβ" correction, and, most recently, pileup per particle identification. This paper surveys the performance of these techniques for jet and missing transverse momentum reconstruction, as well as muon isolation. The analysis makes use of data corresponding to 35.9 fb$^{-1}$ collected with the CMS experiment in 2016 at a center-of-mass energy of 13 TeV. The performance of each algorithm is discussed for up to 70 simultaneous collisions per bunch crossing. Significant improvements are found in the identification of pileup jets, the jet energy, mass, and angular resolution, missing transverse momentum resolution, and muon isolation when using pileup per particle identification