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Crab cavities (CCs) constitute a key component of the High Luminosity LHC (HL-LHC) project. In case of a failure, they can induce significant transverse beam offsets within tens of microseconds, necessitating a fast removal of the circulating beam to avoid damage to accelerator components due to losses from the displaced beam halo. In preparation for the final design to be employed in the LHC, a series of tests were conducted on prototype crab cavities installed in the Super Proton Synchrotron (SPS) at CERN. This paper summarizes the machine protection requirements and observations during the first tests of crab cavities with proton beams in the SPS. In addition, the machine protection implications for future SPS tests and for the use of such equipment in the HL-LHC are discussed., Proceedings of the 10th Int. Particle Accelerator Conf., IPAC2019, Melbourne, Australia

A new type of fast luminosity separation scans (“emittance scans”) was introduced at the CERN Large Hadron Collider (LHC) in 2015. The scans were performed systematically in every fill with full-intensity beams in physics production conditions at the interaction point (IP) of the compact muon solenoid (CMS) experiment. They provide both transverse emittance and closed orbit measurements at a bunch-by-bunch level. The precise measurement of beam-beam closed orbit differences allowed a direct, quantitative observation of long-range beam-beam PACMAN effects, which agrees well with numerical simulations from an improved version of the TRAIN code. A new type of fast luminosity separation scans ("Emittance Scans") was introduced at the CERN Large Hadron Collider (LHC) in 2015. The scans were performed systematically in every fill with full-intensity beams in physics production conditions at the Interaction Point (IP) of the Compact Muon Solenoid (CMS) experiment. They provide both emittance and closed orbit measurements at a bunch-by-bunch level. The precise measurement of beam-beam closed orbit differences allowed a direct, quantitative observation of long-range beam-beam PACMAN effects, which agrees well with numerical simulations from an improved version of the TRAIN code.

Propolis is one of the most fascinating honey bee (Apis mellifera L.) products. It is a plant derived product that bees produce from resins that they collect from different plant organs and with which they mix beeswax. Propolis is a building material and a protective agent in the bee hive. It also plays an important role in honey bee social immunity, and is widely used by humans as an ingredient of nutraceuticals, over-the-counter preparations and cosmetics. Its chemical composition varies by geographic location, climatic zone and local flora. The understanding of the chemical diversity of propolis is very important in propolis research. In this manuscript, we give an overview of the available methods for studying propolis in different aspects: propolis in the bee colony; chemical composition and plant sources of propolis; biological activity of propolis with respect to bees and humans; and approaches for standardization and quality control for the purposes of industrial application. Fil: Bankova, Vassya. Institute Of Organic Chemistry With Centre Of Phytochemistry (ioccp) Bulgarian Academy Of Sciences; Bulgaria Fil: Bertelli, Davide. Universita Degli Studi Di Modena E Reggio Emilia; Fil: Borba, Renata. University Of Minnesota System; Fil: Conti, Bruno José. Unesp-universidade Estadual Paulista; Fil: da Silva Cunha, Ildenize Barbosa. Universidade Estadual de Campinas; Brasil Fil: Danert, Fátima Carolina. Universidad Nacional de Tucumán; Argentina Fil: Eberlin, Marcos Nogueira. Universidade Estadual de Campinas; Brasil Fil: Falcão, Soraia I.. Escola Superior Agraria Braganca; Portugal Fil: Isla, Maria Ines. Universidad Nacional de Tucumán; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Química del Noroeste. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia. Instituto de Química del Noroeste; Argentina Fil: Nieva Moreno, María Inés. Universidad Nacional de Tucumán; Argentina Fil: Papotti, Giulia. Universita Degli Studi Di Modena E Reggio Emilia; Fil: Popova, Milena. Institute Of Organic Chemistry With Centre Of Phytochemistry (ioccp) Bulgarian Academy Of Sciences; Bulgaria Fil: Basso Santiago, Karina. Unesp-universidade Estadual Paulista; Fil: Salas, Ana Lilia. Universidad Nacional de Tucumán; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Química del Noroeste. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia. Instituto de Química del Noroeste; Argentina Fil: Frankland Sawaya, Alexandra Christine Helena. Universidade Estadual de Campinas; Brasil Fil: Schwab, Nicolas Vilczaki. Universidade Estadual de Campinas; Brasil Fil: Sforcin, José Maurício. Unesp-universidade Estadual Paulista; Fil: Simone Finstrom, Michael. United States Department Of Agriculture. Agriculture Research Service; Estados Unidos Fil: Spivak, Marla. University Of Minnesota System; Fil: Trusheva, Boryana. Institute Of Organic Chemistry With Centre Of Phytochemistry (ioccp) Bulgarian Academy Of Sciences; Bulgaria Fil: Vilas Boas, Miguel. Escola Superior Agraria Braganca; Portugal Fil: Wilson, Michael. University Of Minnesota System; Fil: Zampini, Iris Catiana. Universidad Nacional de Tucumán; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Química del Noroeste. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia. Instituto de Química del Noroeste; Argentina

The aim of this work is to evaluate the possibility of using 2D-NMR for the construction of classification models for balsamic vinegars of Modena. The goal was to obtain an indirect indicator of authenticity and a quality control tool. The spectral data were analyzed by chemometric methods, aiming to discriminate the samples in relation to their origin. Application of general discriminant analysis (GDA) revealed a good discrimination; the two obtained models explained 83.9% and 97.3% of the total variance with a predictive capacity of 98.6% and 98.4%, respectively. The signals of 5-HMF, β-glucose, 2,3-butanediol, 6-acetyl glucose, and different aliphatic signals of sugars were the most significant variables. These results are very promising for giving an important contribution in quality control and characterization of such very valuable foods.

The Gamma Factory initiative proposes to use partially stripped ion (PSI) beams as drivers of a new type of high intensity photon source. As part of the ongoing Physics Beyond Collider studies, initial beam tests with PSI beams have been executed at CERN. On 25 July 2018 lead ions with one remaining electron (208Pb81+) were injected and accelerated in the LHC for the first time. After establishing the injection and circulation of a few208Pb81+bunches, beam lifetimes of about 50 hours could be established at 6.5 TeV proton equivalent energy. This paper describes the setup of the beam tests and observations made.

Summary Volatile compounds from 90 Italian citrus honeys of different varieties (lemon, Citrus limon (L.) Burm., orange, Citrus sinensis (L.) Osbeck, and citrus, Citrus spp.), 30 provided by CRA-API (Consiglio per la Ricerca e la Sperimentazione in Agricoltura-Unita di ricerca di apicoltura e bachicoltura) (Bologna, Italy) and 60 purchased on the markets, were analysed to classify them according to the characteristic aroma profiles. A HS-SPME-GC method previously developed and validated was applied. Factor analysis and general discriminant analysis (GDA) were carried out on peaks and intensity data. Statistical analyses revealed a good separation between samples; the best model based on peaks data shows 66.5% and 33.5% of total variance explained by the first and the second canonical functions and a predictive capacity of 78.9%. Regarding the intensity data, the CFs of the GDA model explain 53.8% and 46.2% of the total variance and the crossvalidation shows a predictive capacity of 96.7%.

Introduction Propolis is a resinous substance collected by bees from exudates of different plants that is rich in well-known health-relevant phenolic compounds such as flavonoids and phenolic acids. Propolis extracts are very complex matrices difficult to study. Different analytical methods are usable to analyse propolis extracts and to obtain chemical fingerprint but to our knowledge NMR has not previously been used for this purpose. Objective This study aims to demonstrate that it is possible to use 1H-NMR for the simultaneous recognition of phenolic compounds in complex matrices, such as propolis extracts, using appropriate tools for spectra pre-treatment and analysis. Methodology In this work 12 typical phenolic propolis compounds (apigenin, chrysin, galangin, kaempferol, quercetin, naringenin, pinocembrin, pinostrobin, caffeic acid, cinnamic acid, p-coumaric acid and ferulic acid) were considered as reference compounds and their presence in samples was verified by HPLC-MS. A simple 1H-NMR sequence was used to obtain spectra of samples. Spectra were pre-treated by using an appropriate tool for spectra alignment and analysed by using software for the study of spectra originated from complex matrices. Sixty-five propolis samples were used to test the proposed identification procedure. Results Ten out of 12 considered compounds were identified as statistically significant in most of the samples. Conclusion This work suggests that it is possible to efficiently use 1H-NMR, coupled with appropriate spectral analytical tools, for the simultaneous detection of phenolic compounds in complex matrices. Copyright © 2011 John Wiley & Sons, Ltd.

Summary Propolis has various biological activities closely related to the composition which varies according to environmental factors and also to the method of production. This study was aimed at determining whether or not HR-NMR and multivariate statistical analysis were able to classify propolis according to the method used to harvest it. Sixty propolis samples were analysed in all. The ethanolic propolis extracts were initially analysed for quantification of the main bioactive substances, balsams and waxes. The 1H NMR and heteronuclear multiple bond correlation spectra were then acquired. Spectral data were analysed by the application of multivariate statistical techniques (Factor Analysis and General Discriminant Analysis). The best results were obtained using the 1H NMR which furnishes a sufficiently effective model by analysing the spectral region between 4.50 and 13.00 ppm (predictive capacity: 96.7%).

The importance of honey adulteration detection has recently increased owing to the limited production levels in recent years and the relative high price of honey; therefore, this illegal practice has become more and more attractive to producers. Hence, the need has arisen for more effective analytical methods aiming at detecting honey adulteration. The present research presents an effective method to detect adulteration in honey falsified by intentional addition of different concentrations of commercial sugar syrups, using one-dimensional (1D) and two-dimensional (2D) nuclear magnetic resonance (NMR) coupled with multivariate statistical analysis. Sixty-three authentic and 63 adulterated honey samples were analyzed. To prepare adulterated honeys, seven different sugar syrups normally used for nutrition of bees were used. The best discriminant model was obtained by 1D spectra, and leave-one-out cross-validation showed a predictive capacity of 95.2%. 2D NMR also furnished acceptable results (cross-validation correct classification 90.5%), although the (1)H NMR sequence is preferable because it is the simplest and fastest NMR technique.

Summary An headspace solid phase microextraction-gas chromatography (HS-SPME-GC) method, previously developed and validated, was applied to the determination of the methyl anthranilate (MA) content of 75 Italian citrus honeys (11 of lemon, 44 of orange and 20 of Citrus spp.). Twenty-four samples were purchased on the local market and 51 were provided by CRA-API (Consiglio Nazionale per la Ricerca e Sperimentazione in Agricoltura-Istituto Nazionale di Apicoltura e Bachicoltura) (Bologna, Italy). All the samples had a MA content above the limit of detection (LOD) (0.149 μg g−1) of the analytical method. The concentration range was between 0.46 and 2.52 μg g−1 and the overall average MA content was 1.19 μg g−1. The honeys with the highest mean MA content were the orange honeys followed by Citrus spp. and lemon (1.29 ± 0.461, 1.12 ± 0.511 and 0.92 ± 0.39 μg g−1, respectively). No significant differences were measured between commercial and authenticated samples.

An efficient and simple method for determination of methyl anthranilate (MA) in Citrus spp. honeys by headspace-solid-phase microextraction-gas chromatography (HS-SPME-GC) was developed and validated. Experimental design was used to investigate the effects of the principal extraction parameters. The central composite design (CCD) and the desirability function were used to find the experimental conditions providing the optimal HS-SPME result. Validation was carried out in terms of specificity, linearity, limit of detection (LOD) and quantitation (LOQ) (0.149 and 0.324 μg/g, respectively), method precision (RSD 7%), LOQ precision (RSD 6.5%), and was resulted accurate and robust. Finally, the applicability of the method to the determination of MA in a number of commercial Citrus spp. honey samples was demonstrated, the content ranged from 0.63 to 3.26 μg/g.

Geographical origin and authenticity of food are topics of interest for both consumers and producers. Among the different indicators used for traceability studies, (87)Sr/(86)Sr isotopic ratio has provided excellent results. In this study, two analytical approaches for wine sample pre-treatment, microwave and low temperature mineralisation, were investigated to develop accurate and precise analytical method for (87)Sr/(86)Sr determination. The two procedures led to comparable results (paired t-test, with t

Balsamic vinegar of Modena (BVM) and traditional balsamic vinegar of Modena (TBVM) are highly appreciated typical Italian products. The quality control and authentication assurance of both these balsamic vinegars are very important topics. In the recent years, the interest to develop new and standardized analytical procedures, able to further enhance the quality and commercial value of these typical and unique products and to preserve them from possible sophistications and adulterations, is increased. In this work, 76 samples of both BVM and TBVM were analyzed by 1 H NMR spectroscopy coupled with multivariate data analysis. The spectral data were analyzed by principal component analysis (PCA), general discriminant analysis (GDA) and classification tree analysis (CTA). The best and very promising model was obtained by a GDA which shows 98.6% of total variance explained by the first canonical function and a predictive capacity of 98.4% with a good separation between clusters. The signals of 5-HMF, α-glucopyranose, malic acid, succinic and acetic acids and the signal at 3.3 ppm were found to be the most statistically significant variables.

Lambrusco is a Protected Designation of Origin (PDO) red wine of Modena (Italy) produced according to the production regulation (Decreto Ministeriale (DM) July 27, 2009; GU no. 184-187-188, 13/08/2009). Here the use of (1)H NMR spectroscopy as molecular fingerprints of several PDO Lambrusco wines was proposed to serve as indicators of authenticity and quality control. Application of partial least squares discriminant analysis (PLS-DA) revealed a good varietal discrimination by analyzing the low-frequency spectral region. This model explains 68.8% of the variance for the Y vector (classification factor: varietal source). In particular, the signals of 2,3-butanediol, lactic, succinic and malic acids, and threonine were found to be the most statistically significant variables in the model. These findings seem to be very promising in the attempt to extend the study to geographical discrimination.

The composition and antioxidant activity of Italian poplar propolis obtained using three harvesting methods and extracted with different solvents were evaluated. Waxes, balsams, and resins contents were determined. Flavones and flavonols, flavanones and dihydroflavonols, and total phenolics were also analyzed. To characterize the phenolic composition, the presence of 15 compounds was verified through HPLC-MS/MS. The antioxidant activity was evaluated through 1,1-diphenyl-2-picrylhydrazyl radical and reducing power assays. The ability of propolis to inhibit lipid oxidation was monitored by analyzing hydroperoxide and TBARS formation in lipids incorporated into an oil-in-water (O/W) emulsion. Acetone shows the highest extraction capacity. Wedge propolis has the highest concentration of active phenolic compounds (TP = 359.1 ± 16.3 GAEs/g; TFF = 5.83 ± 0.42%; TFD = 7.34 ± 1.8%) and seems to be the most promising for obtaining high-value propolis more suitable to prepare high-quality dietary supplements (TBARS = 0.012 ± 0.009 mmol std/g; RP = 0.77 ± 0.07 TEs/g).

Propolis is a resinous substance collected by bees from exudates of different plants that is rich in well-known health-relevant phenolic compounds such as flavonoids and phenolic acids. Propolis extracts are very complex matrices difficult to study. Different analytical methods are usable to analyse propolis extracts and to obtain chemical fingerprint but to our knowledge NMR has not previously been used for this purpose.This study aims to demonstrate that it is possible to use ¹H-NMR for the simultaneous recognition of phenolic compounds in complex matrices, such as propolis extracts, using appropriate tools for spectra pre-treatment and analysis.In this work 12 typical phenolic propolis compounds (apigenin, chrysin, galangin, kaempferol, quercetin, naringenin, pinocembrin, pinostrobin, caffeic acid, cinnamic acid, p-coumaric acid and ferulic acid) were considered as reference compounds and their presence in samples was verified by HPLC-MS. A simple ¹H-NMR sequence was used to obtain spectra of samples. Spectra were pre-treated by using an appropriate tool for spectra alignment and analysed by using software for the study of spectra originated from complex matrices. Sixty-five propolis samples were used to test the proposed identification procedure.Ten out of 12 considered compounds were identified as statistically significant in most of the samples.This work suggests that it is possible to efficiently use ¹H-NMR, coupled with appropriate spectral analytical tools, for the simultaneous detection of phenolic compounds in complex matrices.

The electron cloud (EC) can be formed in the beam pipe of a circular accelerator if the secondary emission yield (SEY) of the inner surface is larger than 1, and it can detrimentally affect the circulating beam. Understanding the underlying physics and defining the scaling laws of this effect is indispensable to steer the upgrade plans of the existing machines and the design of new ones. The single bunch EC instability (ECI) is shown to be strongly affected by the transverse beam size. Transversely, smaller beams going through an electron cloud generate higher electron peak densities and lower the intensity threshold to make the beam unstable. In particular, since higher energy beams have smaller transverse sizes (for equal normalized transverse emittances), the scaling of the ECI threshold with the beam energy turns out to be surprisingly unfavorable.