Supersymmetric CP-violating Currents and Electroweak Baryogenesis

In this work we compute the CP-violating currents of the right-handed stops and Higgsinos, induced by the presence of non-trivial vacuum expectation values of the Higgs fields within the context of the minimal supersymmetric extension of the Standard Model (MSSM) with explicit CP-violating phases. Using the Keldysh formalism, we perform the computation of the currents at finite temperature, in an expansion of derivatives of the Higgs fields. Contrary to previous works, we implement a resummation of the Higgs mass insertion effects to all orders in perturbation theory. While the components of the right-handed stop current j^\mu_{\widetilde t_R} become proportional to the difference H_2 \partial^{\mu}H_1-H_1 \partial^{\mu} H_2 (suppressed by \Delta\beta), the Higgsino currents, j^\mu_{\widetilde{H}_i}, present contributions proportional to both H_2 \partial^{\mu}H_1\pm H_1 \partial^{\mu} H_2. For large values of the charged Higgs mass and moderate values of \tan\beta the contribution to the source proportional to H_2 \partial^{\mu}H_1+H_1 \partial^{\mu} H_2 in the diffusion equations become sizeable, although it is suppressed by the Higgsino number violating interaction rate \Gamma_\mu^{-1/2}. For small values of the wall velocity, 0.04\simlt v_\omega \simlt 0.1, the total contribution leads to acceptable values of the baryon asymmetry for values of the CP-violating phases \phi_{CP} in the range 0.04\simlt|\sin\phi_{CP}|\simlt 1. Finally, we comment on the relevance of the latest results of Higgs searches at LEP2 for the mechanism of electroweak baryogenesis within the MSSM.Comment: 27 pages, 4 figures, latex2e. Typo corrected and references adde

Fluencia de tableros MDF sometidos a carga constante y condiciones cíclicas de humedad relativa. Influencia del revestimiento de superficies

Four different strategies of surface coating (based on 80 g m2 melamin impregnated papers) were used on 19 mm thick commercial MDF panels to assess its reological behaviour under cyclic humidity conditions (20ºC 30 % rh-20ºC 90 % rh). Three different levels of stress (20 %, 30 % and 40 %), based on the ultimate load in bending, were used. Tests were conducted by means of the three points load system. For the same stress level, the relative creep of MDF panels was higher than that in particle boards with similar characteristics. This behaviour was just the opposite than the one exhibited by the panels when the comparison is made based on the same level of load (kg) Melamin coating seems to strongly influence the creep behaviour of the raw material, especially when surface and edge coating were combined.Cuatro tipos de acabados superficiales distintos, aplicados sobre tableros MDF comerciales de 19 mm de espesor, son empleados en el estudio del comportamiento reológico de los tableros MDF ante condiciones alternantes de humedad relativa (20ºC/30 % hr-20ºC/90 % hr). Para el análisis del comportamiento reológico de los tableros se consideran tres niveles de tensión distintos (20 %, 30 %y 40 %), calculados en función de la carga última de rotura a flexión. Los ensayos son efectuados aplicando la carga en punto medio. La fluencia relativa de los tableros MDF resulta ser superior a la exhibida por los tableros de partículas de similares características, observándose que los revestimientos melamínicos aplicados superficialmente influyen eficazmente en la mejora de su comportamiento reológico. Cuando la comparación entre tableros MDF y de partículas se efectúa considerando idénticos niveles de carga aplicada en vez de tensión, el resultado de la comparación resulta ser, justamente, el contrario

Vascular liver anatomy and main variants: what the radiologist must know

Advances in surgical techniques are extremely demanding regarding the accuracy and level of detail expected for display of the vascular anatomy of the liver. Precise knowledge of the arterial, portal and hepatic vein territories are mandatory whenever a liver intervention is planned. Sectional anatomy can now be routinely performed on multidetector computed tomography (MDCT) with volumetric data and isotropic voxel display, by means of sub-millimetric slice thickness acquisition. The relevant vascular information can thus be gathered, reviewed and post-processed with unprecedented clarity, obviating the need for digital subtraction angiography. The scope of the present paper is to review the normal vascular liver anatomy, its most relevant variants including additional sources of vascular inflow. Apart from providing the surgeon with a detailed vascular and parenchymal roadmap knowledge of imaging findings may avoid potential confusion with pathologic processes

Differential response to dexamethasone on the TXB2 release in guinea-pig alveolar macrophages induced by zymosan and cytokines

Glucocorticosteroids reduce the production of inflammatory mediators but this effect may depend on the stimulus. We have compared the time course of the effect of dexamethasone on the thromboxane B2 (TXB2) release induced by cytokine stimulation and zymosan in guinea-pig alveolar macrophages. Interleukin-1β (IL-1β), tumour necrosis factor-α (TNF-α) and opsonized zymosan (OZ), all stimulate TXB2 release. High concentrations of dexamethasone (1–10 μM) inhibit the TXB2 production induced by both cytokines and OZ, but the time course of this response is different. Four hours of incubation with dexamethasone reduce the basal TXB2 release and that induced by IL-1β and TNF-α, but do not modify the TXB2 release induced by OZ. However, this stimulus was reduced after 24 h incubation. Our results suggest that the antiinflammatory activity of glucocorticosteroids shows some dependence on stimulus and, therefore, may have more than one mechanism involved

Contrastación de hipótesis en diseños multivariados split-plot con matrices de dispersión arbitrarias

El presente trabajo examina diversos procedimientos para contrastar hipótesis nulas globales, correspondientes a datos obtenidos mediante diseños multivariados split-plot cuando se incumple el supuesto de homogeneidad de las matrices de dispersión. Un examen de estos procedimientos para un amplio número de variables confirma, por un lado, la robustez del procedimiento multivariado de Welch-James dado por Johansen (1980) para probar el efecto principal de los ensayos y, por otro, la robustez de la generalización multivariada del procedimiento de Brown-Forsythe (1974) para probar la interacción de los grupos x los ensayos. Nuestros resultados también ponen de relieve que las diferencias de potencia eran pequeñas en aquellas condiciones en que tanto el procedimiento de Welch-James como de Brown-Forsythe controlaban las tasas de error de Tipo I

EGS4 and MCNP4b MC Simulation of a Siemens KD2 Accelerator in 6 MV Photon Mode

The geometry of a Siemens Mevatron KD2 linear accelerator in 6 MV photon mode was modeled with EGS4 and MCNP4b. Energy spectra and other phase space distributions have been extensively compared in different plans along the beam line. The differences found have been evaluated both qualitative and quantitatively. The final aim was that both codes, running in different operating systems and with a common set of simulation conditions, met the requirement of fitting the experimental depth dose curves and dose profiles, measured in water for different field sizes. Whereas depth dose calculations are in a certain extent insensible to some simulation parameters like electron nominal energy, dose profiles have revealed to be a much better indicator to appreciate that feature. Fine energy tuning has been tried and the best fit was obtained for a nominal electron energy of 6.15 MeV

Plant-wide modelling in wastewater treatment: showcasing experiences using the Biological Nutrient Removal Model

[EN] Plant-wide modelling can be considered an appropriate approach to represent the current complexity in water resource recovery facilities, reproducing all known phenomena in the different process units. Nonetheless, novel processes and new treatment schemes are still being developed and need to be fully incorporated in these models. This work presents a short chronological overview of some of the most relevant plant-wide models for wastewater treatment, as well as the authors' experience in plant-wide modelling using the general model BNRM (Biological Nutrient Removal Model), illustrating the key role of general models (also known as supermodels) in the field of wastewater treatment, both for engineering and research.Seco, A.; Ruano, MV.; Ruiz-Martínez, A.; Robles Martínez, Á.; Barat, R.; Serralta Sevilla, J.; Ferrer, J. (2020). Plant-wide modelling in wastewater treatment: showcasing experiences using the Biological Nutrient Removal Model. Water Science & Technology. 81(8):1700-1714. https://doi.org/10.2166/wst.2020.056S17001714818Barat, R., Montoya, T., Seco, A., & Ferrer, J. (2011). Modelling biological and chemically induced precipitation of calcium phosphate in enhanced biological phosphorus removal systems. Water Research, 45(12), 3744-3752. doi:10.1016/j.watres.2011.04.028Barat, R., Serralta, J., Ruano, M. V., Jiménez, E., Ribes, J., Seco, A., & Ferrer, J. (2013). Biological Nutrient Removal Model No. 2 (BNRM2): a general model for wastewater treatment plants. Water Science and Technology, 67(7), 1481-1489. doi:10.2166/wst.2013.004Batstone, D. J., Hülsen, T., Mehta, C. M., & Keller, J. (2015). Platforms for energy and nutrient recovery from domestic wastewater: A review. Chemosphere, 140, 2-11. doi:10.1016/j.chemosphere.2014.10.021Borrás F. L. 2008 Técnicas microbiológicas aplicadas a la identificación y cuantificación de organismos presentes en sistemas EBPR (Microbiological Techniques Applied to Identification and Quantification of Organisms Present in EBPR Systems). PhD Thesis, Universitat Politècnica de València, Valencia, Spain.Claros, J., Jiménez, E., Aguado, D., Ferrer, J., Seco, A., & Serralta, J. (2013). Effect of pH and HNO2 concentration on the activity of ammonia-oxidizing bacteria in a partial nitritation reactor. Water Science and Technology, 67(11), 2587-2594. doi:10.2166/wst.2013.132Copp, J. B., Jeppsson, U., & Rosen, C. (2003). TOWARDS AN ASM1 – ADM1 STATE VARIABLE INTERFACE FOR PLANT-WIDE WASTEWATER TREATMENT MODELING. Proceedings of the Water Environment Federation, 2003(7), 498-510. doi:10.2175/193864703784641207Dorofeev, A. G., Nikolaev, Y. A., Kozlov, M. N., Kevbrina, M. V., Agarev, A. M., Kallistova, A. Y., & Pimenov, N. V. (2017). Modeling of anammox process with the biowin software suite. Applied Biochemistry and Microbiology, 53(1), 78-84. doi:10.1134/s0003683817010100Drewnowski, J., Zaborowska, E., & Hernandez De Vega, C. (2018). Computer Simulation in Predicting Biochemical Processes and Energy Balance at WWTPs. E3S Web of Conferences, 30, 03007. doi:10.1051/e3sconf/20183003007Durán F. 2013 Modelación matemática del tratamiento anaerobio de aguas residuales urbanas incluyendo las bacterias sulfatorreductoras. Aplicación a un biorreactor anaerobio de membranas (Mathematical Model of Urban Wastewater Anaerobic Treatment Including Sulphate Reducing Bacteria. Application to an Anaerobic Membrane Bioreactor). PhD Thesis, Universitat Politècnica de València, Valencia, Spain.Ekama, G. A. (2009). Using bioprocess stoichiometry to build a plant-wide mass balance based steady-state WWTP model. Water Research, 43(8), 2101-2120. doi:10.1016/j.watres.2009.01.036EPA 2006 User's manual version 4.03 2006. Available from: https://www.epa.gov/ceam/minteqa2-equilibrium-speciation-model (accessed July 2019).Fernández-Arévalo, T., Lizarralde, I., Fdz-Polanco, F., Pérez-Elvira, S. I., Garrido, J. M., Puig, S., … Ayesa, E. (2017). Quantitative assessment of energy and resource recovery in wastewater treatment plants based on plant-wide simulations. Water Research, 118, 272-288. doi:10.1016/j.watres.2017.04.001Ferrer, J., Seco, A., Serralta, J., Ribes, J., Manga, J., Asensi, E., … Llavador, F. (2008). DESASS: A software tool for designing, simulating and optimising WWTPs. Environmental Modelling & Software, 23(1), 19-26. doi:10.1016/j.envsoft.2007.04.005Ferrer J., Seco A., Ruano M. V., Ribes J., Serralta J., Gómez T., Robles A. 2011 LoDif BioControl® Control Software, Intellectual Property. Main Institution: Universitat de València; Universitat Politècnica de València.Flores-Alsina, X., Corominas, L., Snip, L., & Vanrolleghem, P. A. (2011). Including greenhouse gas emissions during benchmarking of wastewater treatment plant control strategies. Water Research, 45(16), 4700-4710. doi:10.1016/j.watres.2011.04.040Flores-Alsina, X., Arnell, M., Amerlinck, Y., Corominas, L., Gernaey, K. V., Guo, L., … Jeppsson, U. (2014). Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs. Science of The Total Environment, 466-467, 616-624. doi:10.1016/j.scitotenv.2013.07.046Flores-Alsina, X., Kazadi Mbamba, C., Solon, K., Vrecko, D., Tait, S., Batstone, D. J., … Gernaey, K. V. (2015). A plant-wide aqueous phase chemistry module describing pH variations and ion speciation/pairing in wastewater treatment process models. Water Research, 85, 255-265. doi:10.1016/j.watres.2015.07.014Ge, Z. (2017). Review on data-driven modeling and monitoring for plant-wide industrial processes. Chemometrics and Intelligent Laboratory Systems, 171, 16-25. doi:10.1016/j.chemolab.2017.09.021Grau, P., de Gracia, M., Vanrolleghem, P. A., & Ayesa, E. (2007). A new plant-wide modelling methodology for WWTPs. Water Research, 41(19), 4357-4372. doi:10.1016/j.watres.2007.06.019Grau, P., Copp, J., Vanrolleghem, P. A., Takács, I., & Ayesa, E. (2009). A comparative analysis of different approaches for integrated WWTP modelling. Water Science and Technology, 59(1), 141-147. doi:10.2166/wst.2009.589Henze M., Gujer W., Mino T., van Loosdrecht M. C. M. 2000 Activated Sludge Models ASM1, ASM2, ASM2d and ASM3. IWA Scientific and Technical Report No.9. IWA Publishing, London, UK.Jeppsson, U., & Pons, M.-N. (2004). The COST benchmark simulation model—current state and future perspective. Control Engineering Practice, 12(3), 299-304. doi:10.1016/j.conengprac.2003.07.001Jeppsson, U., Rosen, C., Alex, J., Copp, J., Gernaey, K. V., Pons, M.-N., & Vanrolleghem, P. A. (2006). Towards a benchmark simulation model for plant-wide control strategy performance evaluation of WWTPs. Water Science and Technology, 53(1), 287-295. doi:10.2166/wst.2006.031Ji, X., Liu, Y., Zhang, J., Huang, D., Zhou, P., & Zheng, Z. (2018). Development of model simulation based on BioWin and dynamic analyses on advanced nitrate nitrogen removal in deep bed denitrification filter. Bioprocess and Biosystems Engineering, 42(2), 199-212. doi:10.1007/s00449-018-2025-xJiménez, E., Giménez, J. B., Ruano, M. V., Ferrer, J., & Serralta, J. (2011). Effect of pH and nitrite concentration on nitrite oxidation rate. Bioresource Technology, 102(19), 8741-8747. doi:10.1016/j.biortech.2011.07.092Jiménez, E., Giménez, J. B., Seco, A., Ferrer, J., & Serralta, J. (2012). Effect of pH, substrate and free nitrous acid concentrations on ammonium oxidation rate. Bioresource Technology, 124, 478-484. doi:10.1016/j.biortech.2012.07.079Kazadi Mbamba, C., Flores-Alsina, X., John Batstone, D., & Tait, S. (2016). Validation of a plant-wide phosphorus modelling approach with minerals precipitation in a full-scale WWTP. Water Research, 100, 169-183. doi:10.1016/j.watres.2016.05.003Kazadi Mbamba, C., Lindblom, E., Flores-Alsina, X., Tait, S., Anderson, S., Saagi, R., … Jeppsson, U. (2019). Plant-wide model-based analysis of iron dosage strategies for chemical phosphorus removal in wastewater treatment systems. Water Research, 155, 12-25. doi:10.1016/j.watres.2019.01.048Liu, Y., Peng, L., Ngo, H. H., Guo, W., Wang, D., Pan, Y., … Ni, B.-J. (2016). Evaluation of Nitrous Oxide Emission from Sulfide- and Sulfur-Based Autotrophic Denitrification Processes. Environmental Science & Technology, 50(17), 9407-9415. doi:10.1021/acs.est.6b02202Lizarralde, I., Fernández-Arévalo, T., Brouckaert, C., Vanrolleghem, P., Ikumi, D. S., Ekama, G. A., … Grau, P. (2015). A new general methodology for incorporating physico-chemical transformations into multi-phase wastewater treatment process models. Water Research, 74, 239-256. doi:10.1016/j.watres.2015.01.031Lizarralde, I., Fernández-Arévalo, T., Manas, A., Ayesa, E., & Grau, P. (2019). Model-based opti mization of phosphorus management strategies in Sur WWTP, Madrid. Water Research, 153, 39-52. doi:10.1016/j.watres.2018.12.056Maere, T., Verrecht, B., Moerenhout, S., Judd, S., & Nopens, I. (2011). BSM-MBR: A benchmark simulation model to compare control and operational strategies for membrane bioreactors. Water Research, 45(6), 2181-2190. doi:10.1016/j.watres.2011.01.006Mannina, G., Ekama, G., Caniani, D., Cosenza, A., Esposito, G., Gori, R., … Olsson, G. (2016). Greenhouse gases from wastewater treatment — A review of modelling tools. Science of The Total Environment, 551-552, 254-270. doi:10.1016/j.scitotenv.2016.01.163Martí, N., Barat, R., Seco, A., Pastor, L., & Bouzas, A. (2017). Sludge management modeling to enhance P-recovery as struvite in wastewater treatment plants. Journal of Environmental Management, 196, 340-346. doi:10.1016/j.jenvman.2016.12.074Moretti, P., Choubert, J.-M., Canler, J.-P., Buffière, P., Pétrimaux, O., & Lessard, P. (2017). Dynamic modeling of nitrogen removal for a three-stage integrated fixed-film activated sludge process treating municipal wastewater. Bioprocess and Biosystems Engineering, 41(2), 237-247. doi:10.1007/s00449-017-1862-3Nagy, J., Kaljunen, J., & Toth, A. J. (2019). Nitrogen recovery from wastewater and human urine with hydrophobic gas separation membrane: experiments and modelling. Chemical Papers, 73(8), 1903-1915. doi:10.1007/s11696-019-00740-xNewhart, K. B., Holloway, R. W., Hering, A. S., & Cath, T. Y. (2019). Data-driven performance analyses of wastewater treatment plants: A review. Water Research, 157, 498-513. doi:10.1016/j.watres.2019.03.030Nopens, I., Batstone, D. J., Copp, J. B., Jeppsson, U., Volcke, E., Alex, J., & Vanrolleghem, P. A. (2009). An ASM/ADM model interface for dynamic plant-wide simulation. Water Research, 43(7), 1913-1923. doi:10.1016/j.watres.2009.01.012Nopens, I., Benedetti, L., Jeppsson, U., Pons, M.-N., Alex, J., Copp, J. B., … Vanrolleghem, P. A. (2010). Benchmark Simulation Model No 2: finalisation of plant layout and default control strategy. Water Science and Technology, 62(9), 1967-1974. doi:10.2166/wst.2010.044Ontiveros, G. A., & Campanella, E. A. (2013). Environmental performance of biological nutrient removal processes from a life cycle perspective. Bioresource Technology, 150, 506-512. doi:10.1016/j.biortech.2013.08.059Penya-Roja, J. M., Seco, A., Ferrer, J., & Serralta, J. (2002). Calibration and Validation of Activated Sludge Model No.2d for Spanish Municipal Wastewater. Environmental Technology, 23(8), 849-862. doi:10.1080/09593332308618360Pretel, R., Robles, A., Ruano, M. V., Seco, A., & Ferrer, J. (2016). A plant-wide energy model for wastewater treatment plants: application to anaerobic membrane bioreactor technology. Environmental Technology, 37(18), 2298-2315. doi:10.1080/09593330.2016.1148903Pretel, R., Robles, A., Ruano, M. V., Seco, A., & Ferrer, J. (2016). Economic and environmental sustainability of submerged anaerobic MBR-based (AnMBR-based) technology as compared to aerobic-based technologies for moderate-/high-loaded urban wastewater treatment. Journal of Environmental Management, 166, 45-54. doi:10.1016/j.jenvman.2015.10.004Rehman, U., Audenaert, W., Amerlinck, Y., Maere, T., Arnaldos, M., & Nopens, I. (2017). How well-mixed is well mixed? Hydrodynamic-biokinetic model integration in an aerated tank of a full-scale water resource recovery facility. Water Science and Technology, 76(8), 1950-1965. doi:10.2166/wst.2017.330Rieger L., Gillot S., Langergraber G., Ohtsuki T., Shaw A., Takacs I., Winkler S. 2012 Guidelines for Using Activated Sludge Models Scientific and Technical report No. 21. EWA Task Group on Good Modelling Practice. IWA Publishing Volume 11.Robles, A., Ruano, M. V., Ribes, J., Seco, A., & Ferrer, J. (2014). Model-based automatic tuning of a filtration control system for submerged anaerobic membrane bioreactors (AnMBR). Journal of Membrane Science, 465, 14-26. doi:10.1016/j.memsci.2014.04.012Robles, A., Capson-Tojo, G., Ruano, M. V., Seco, A., & Ferrer, J. (2018). Real-time optimization of the key filtration parameters in an AnMBR: Urban wastewater mono-digestion vs. co-digestion with domestic food waste. Waste Management, 80, 299-309. doi:10.1016/j.wasman.2018.09.031Ruano, M. V., Serralta, J., Ribes, J., Garcia-Usach, F., Bouzas, A., Barat, R., … Ferrer, J. (2012). Application of the general model ‘Biological Nutrient Removal Model No. 1’ to upgrade two full-scale WWTPs. Environmental Technology, 33(9), 1005-1012. doi:10.1080/09593330.2011.604877Seco, A., Ribes, J., Serralta, J., & Ferrer, J. (2004). Biological nutrient removal model No.1 (BNRM1). Water Science and Technology, 50(6), 69-70. doi:10.2166/wst.2004.0361Serralta, J., Ferrer, J., Borrás, L., & Seco, A. (2004). An extension of ASM2d including pH calculation. Water Research, 38(19), 4029-4038. doi:10.1016/j.watres.2004.07.009Shoener, B. D., Schramm, S. M., Béline, F., Bernard, O., Martínez, C., Plósz, B. G., … Guest, J. S. (2019). Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review. Water Research X, 2, 100024. doi:10.1016/j.wroa.2018.100024Solon, K., Flores-Alsina, X., Kazadi Mbamba, C., Ikumi, D., Volcke, E. I. P., Vaneeckhaute, C., … Jeppsson, U. (2017). Plant-wide modelling of phosphorus transformations in wastewater treatment systems: Impacts of control and operational strategies. Water Research, 113, 97-110. doi:10.1016/j.watres.2017.02.007Solon, K., Jia, M., & Volcke, E. I. P. (2019). Process schemes for future energy-positive water resource recovery facilities. Water Science and Technology, 79(9), 1808-1820. doi:10.2166/wst.2019.183Vanrolleghem, P. A., Rosen, C., Zaher, U., Copp, J., Benedetti, L., Ayesa, E., & Jeppsson, U. (2005). Continuity-based interfacing of models for wastewater systems described by Petersen matrices. Water Science and Technology, 52(1-2), 493-500. doi:10.2166/wst.2005.055