633 research outputs found

    Effect of Corticosteroids on C-Reactive Protein in Patients with Severe Community-Acquired Pneumonia and High Inflammatory Response: The Effect of Lymphopenia

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    Background: Lymphopenic patients with community-acquired pneumonia (CAP) have shown high mortality rates. Corticosteroids have immunomodulatory properties and regulate cytokine storm in CAP. However, it is not known whether their modulatory effect on cytokine secretion differs in lymphopenic and non-lymphopenic patients with CAP. Therefore, we aimed to test whether the presence of lymphopenia may modify the response to corticosteroids (mainly in C reactive protein (CRP)) in patients with severe CAP and high inflammatory status). Methods: A post hoc analysis of a randomized controlled trial (NCT00908713) which evaluated the effect of corticosteroids in patients with severe CAP and high inflammatory response (CRP > 15 mg/dL). Patients were clustered according to the presence of lymphopenia (lymphocyte count below 1000 cell/mm3 ). Results: At day 1, 35 patients (59%) in the placebo group presented with lymphopenia, compared to 44 patients (73%) in the corticosteroid group. The adjusted mean changes from day 1 showed an increase of 1.19 natural logarithm (ln) cell/mm3 in the corticosteroid group and an increase of 0.67 ln cell/mm3 in the placebo group (LS mean difference of the changes in ln (methylprednisolone minus placebo) 0.51, 95% CI (0.02 to 1.01), p = 0.043). A significant effect was also found for the interaction (p = 0.043) between corticosteroids and lymphopenia in CRP values at day 3, with lower values in patients without lymphopenia receiving corticosteroids after adjustments for potential confounders. Conclusion: In this exploratory post hoc analysis from ramdomized controlled trial (RCT) data, the response to corticosteroids, measured by CRP, may differ according to lymphocyte count. Further larger studies are needed to confirm this data

    Astrophysical constraints on superlight gravitinos

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    I review the constraints on the mass of gravitinos that follow from considerations on energy loss in stars and from Big Bang Nucleosynthesis arguments.Comment: Invited talk at the 5th Workshop on High Energy Physics Phenomenology(WHEPP-5), Pune, India, 12-26 January 199

    Gravitinos from Gravitational Collapse

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    We reanalyse the limits on the gravitino mass m3/2m_{3/2} in superlight gravitino scenarios derived from arguments on energy-loss during gravitational collapse. We conclude that the mass range 10−6eV≀m3/2≀2.3×10−5eV10^{-6}eV\leq m_{3/2}\leq2.3\times10^{-5}eV is excluded by SN1987A data. In terms of the scale of supersymmetry breaking Λ\Lambda, the range 70GeV≀Λ≀300GeV70GeV\leq\Lambda \leq 300GeV is not allowed.Comment: 6 pages, latex, no figures. Numerical typo correcte

    Vascular interstitial cells in retinal arteriolar annuli are altered during hypertension

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    The authors thank Veronica Melgarejo, Lorena Noya, and Angel Vazquez for technical assistance. Supported by grants from Instituto de Salud Carlos III (PI12/00605, PI16/00719, SAF2014-59945-R, and Red de InvestigaciĂłn Renal REDinREN 12/0021/0013), Spain; Fundação para a CiĂȘncia e a Tecnologia (SFRH/BPD/102573/2014, SFRH/BD/95330/2013), Ministerio da Educação e CiĂȘncia, Portugal; and Fondo Europeo de Desarrollo Regional (FEDER).Supported by grants from Instituto de Salud Carlos III (PI12/00605, PI16/00719, SAF2014-59945-R, and Red de Investigacion Renal REDinREN 12/0021/0013), Spain; Fundacao para a Ciencia e a Tecnologia (SFRH/BPD/102573/2014, SFRH/BD/95330/2013), Ministerio da Educacao e Ciencia, Portugal; and Fondo Europeo de Desarrollo Regional (FEDER).PURPOSE. It has been suggested that arteriolar annuli localized in retinal arterioles regulate retinal blood flow acting as sphincters. Here, the morphology and protein expression profile of arteriolar annuli have been analyzed under physiologic conditions in the retina of wildtype, ÎČ-actin-Egfp, and Nestin-gfp transgenic mice. Additionally, to study the effect of hypertension, the KAP transgenic mouse has been used. METHODS. Cellular architecture has been studied using digested whole mount retinas and transmission electron microscopy. The profile of protein expression has been analyzed on paraffin sections and whole mount retinas by immunofluorescence and histochemistry. RESULTS. The ultrastructural analysis of arteriolar annuli showed a different cell population found between endothelial and muscle cells that matched most of the morphologic criteria established to define interstitial Cajal cells. The profile of protein expression of these vascular interstitial cells (VICs) was similar to that of interstitial Cajal cells and different from the endothelial and smooth muscle cells, because they expressed b-actin, nestin, and CD44, but they did not express CD31 and a-SMA or scarcely express F-actin. Furthermore, VICs share with pericytes the expression of NG2 and platelet-derived growth factor receptor beta (PDGFR-ÎČ). The high expression of Ano1 and high activity of nicotinamide adenine dinucleotide phosphate (NADPH)-diaphorase observed in VICs was diminished during hypertensive retinopathy suggesting that these cells might play a role on the motility of arteriolar annuli and that this function is altered during hypertension. CONCLUSIONS. A novel type of VICs has been described in the arteriolar annuli of mouse retina. Remarkably, these cells undergo important molecular modifications during hypertensive retinopathy and might thus be a therapeutic target against this disease

    QED Logarithms in the Electroweak Corrections to the Muon Anomalous Magnetic Moment

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    We employ an effective Lagrangian approach to derive the leading-logarithm two-loop electroweak contributions to the muon anomalous magnetic moment, a_mu. We show that these corrections can be obtained using known results on the anomalous dimensions of composite operators. We confirm the result of Czarnecki et al. for the bosonic part and present the complete sin^2 \theta_W dependence of the fermionic contribution. The approach is then used to compute the leading-logarithm three-loop electroweak contribution to a_mu. Finally we derive, in a fairly model-independent way, the QED improvement of new-physics contributions to a_mu and to the electric dipole moment (EDM) of the electron. We find that the QED corrections reduce the effect of new physics at the electroweak scale by 6% (for a_mu) and by 11% (for the electron EDM).Comment: 13 page

    Remodeling of Bone Marrow Hematopoietic Stem Cell Niches Promotes Myeloid Cell Expansion during Premature or Physiological Aging

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    Hematopoietic stem cells (HSCs) residing in the bone marrow (BM) accumulate during aging but are functionally impaired. However, the role of HSC-intrinsic and -extrinsic aging mechanisms remains debated. Megakaryocytes promote quiescence of neighboring HSCs. Nonetheless, whether megakaryocyte-HSC interactions change during pathological/natural aging is unclear. Premature aging in Hutchinson-Gilford progeria syndrome recapitulates physiological aging features, but whether these arise from altered stem or niche cells is unknown. Here, we show that the BM microenvironment promotes myelopoiesis in premature/physiological aging. During physiological aging, HSC-supporting niches decrease near bone but expand further from bone. Increased BM noradrenergic innervation promotes ÎČ2-adrenergic-receptor(AR)-interleukin-6-dependent megakaryopoiesis. Reduced ÎČ3-AR-Nos1 activity correlates with decreased endosteal niches and megakaryocyte apposition to sinusoids. However, chronic treatment of progeroid mice with ÎČ3-AR agonist decreases premature myeloid and HSC expansion and restores the proximal association of HSCs to megakaryocytes. Therefore, normal/premature aging of BM niches promotes myeloid expansion and can be improved by targeting the microenvironment.Y.-H.O. received fellowships from Alborada Scholar-ship (University of Cambridge), Trinity-Henry Barlow Scholarship (Universityof Cambridge), and R.O.C. Government Scholarship to Study Abroad (GSSA). A.G.G. received fellowships from the Ramon Areces Foundationand the LaCaixa Foundation. C.K. was supported by Marie Curie Career Inte-gration (H2020-MSCA-IF-2015-70841). S.M.-F. was supported by Red TerCel (ISCIII-Spanish Cell Therapy Network). V.A. is supported by grants from theSpanish Ministerio de Economıa,Industria y Competitividad (MEIC) with co-funding from the Fondo Europeo de Desarrollo Regional (FEDER, ‘‘Una manerade hacer Europa’’) (SAF2016-79490-R), the Instituto de Salud Carlos III (AC16/00091 and AC17/00067), the Fundacio Marato TV3 (122/C/2015), and the Progeria Research Foundation (Established Investigator Award 2014–52). TheCNIC is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia, Innovacion y Universidades (MCIU), and the Pro CNIC Foundation,and is a Severo Ochoa Center of Excellence (SEV-2015-0505). This work wassupported by core support grants from the Wellcome Trust and the MRC to theCambridge Stem Cell Institute, MEIC (SAF-2011-30308), Ramon y Cajal Program Grant (RYC-2009-04703), ConSEPOC-Comunidad de Madrid (S2010/BMD-2542), National Health Service Blood and Transplant (United Kingdom), European Union’s Horizon 2020 research (ERC-2014-CoG-64765 and MarieCurie Career Integration grant FP7-PEOPLE-2011-RG-294096), and a Programme Foundation Award from Cancer Research UK to S.M.-F., who wasalso supported in part by an International Early Career Scientist grant fromthe Howard Hughes Medical Institute.S

    Instrumentation and control of anaerobic digestion processes: a review and some research challenges

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11157-015-9382-6[EN] To enhance energy production from methane or resource recovery from digestate, anaerobic digestion processes require advanced instrumentation and control tools. Over the years, research on these topics has evolved and followed the main fields of application of anaerobic digestion processes: from municipal sewage sludge to liquid mainly industrial then municipal organic fraction of solid waste and agricultural residues. Time constants of the processes have also changed with respect to the treated waste from minutes or hours to weeks or months. Since fast closed loop control is needed for short time constant processes, human operator is now included in the loop when taking decisions to optimize anaerobic digestion plants dealing with complex solid waste over a long retention time. Control objectives have also moved from the regulation of key variables measured online to the prediction of overall process perfor- mance based on global off-line measurements to optimize the feeding of the processes. Additionally, the need for more accurate prediction of methane production and organic matter biodegradation has impacted the complexity of instrumentation and should include a more detailed characterization of the waste (e.g., biochemical fractions like proteins, lipids and carbohydrates)andtheirbioaccessibility andbiodegradability characteristics. However, even if in the literature several methodologies have been developed to determine biodegradability based on organic matter characterization, only a few papers deal with bioaccessibility assessment. In this review, we emphasize the high potential of some promising techniques, such as spectral analysis, and we discuss issues that could appear in the near future concerning control of AD processes.The authors acknowledge the financial support of INRA (the French National Institute for Agricultural Research), the French National Research Agency (ANR) for the "Phycover" project (project ANR-14-CE04-0011) and ADEME for Inter-laboratory assay financial support.Jimenez, J.; Latrille, E.; Harmand, J.; Robles MartĂ­nez, Á.; Ferrer Polo, J.; Gaida, D.; Wolf, C.... (2015). Instrumentation and control of anaerobic digestion processes: a review and some research challenges. Reviews in Environmental Science and Biotechnology. 14(4):615-648. doi:10.1007/s11157-015-9382-6S615648144Aceves-Lara CA, Latrille E, Steyer JP (2010) Optimal control of hydrogen production in a continuous anaerobic fermentation bioreactor. Int J Hydrogen Energ 35:10710–10718Aguado D, Montoya T, Ferrer J, Seco A (2006) Relating ions concentration variations to conductivity variations in a sequencing batch reactor operated for enhanced biological phosphorus removal. Environ Modell Softw 21:845–851Aguilar-Garnica E, Dochain D, Alcaraz-GonzĂĄlez V, GonzĂĄlez-Álvarez V (2009) A multivariable control scheme in a two-stage anaerobic digestion system described by partial differential equations. J Process Contr 19:1324–1332Ahring BK, Angelidaki I, Johansen K (1992) Anaerobic treatment of manure together with industrial waste. Water Sci Technol 25:311–318Ajeej A, Thanikal JV, Narayanan CM, Senthil Kumar R (2015) An overview of bio augmentation of methane by anaerobic co-digestion of municipal sludge along with microalgae and waste paper. Renew Sustain Energy Rev 50:270–276Alcaraz-GonzĂĄlez V, GonzĂĄlez-Álvarez V (2007) Selected topics in dynamics and control of chemical and biological processes. Springer, BerlinAlcaraz-GonzĂĄlez V, Harmand J, Rapaport A, Steyer JP, GonzĂĄlez-Álvarez V, Pelayo-Ortiz C (2005a) Robust interval-based regulation for anaerobic digestion processes. Water Sci Technol 52:449–456Alcaraz-GonzĂĄlez V, Salazar-Peña R, GonzĂĄlez-Alvarez V, GouzĂ© JL, Steyer JP (2005b) A tunable multivariable nonlinear robust observer for biological systems. C R Biol 328:317–325Alferes J, Irizar I (2010) Combination of extremum-seeking algorithms with effective hydraulic handling of equalization tanks to control anaerobic digesters. Water Sci Technol 61:2825–2834Alferes J, GarcĂ­a-Heras JL, Roca E, GarcĂ­a C, Irizar I (2008) Integration of equalisation tanks within control strategies for anaerobic reactors. Validation based on ADM1 simulations. Water Sci Technol 57:747–752Alimahmoodi M, Mulligan CN (2008) Anaerobic bioconversion of carbon dioxide to biogas in an upflow anaerobic sludge blanket reactor. J Air Waste Manage Assoc 58:95–103Alvarez JA, Otero L, Lema JM (2010) A methodology for optimising feed composition for anaerobic co-digestion of agro-industrial wastes. Bioresour Technol 101:1153–1158Alvarez-Ramirez J, Meraz M, Monroy O, Velasco A (2002) Feedback control design for an anaerobic digestion process. J Chem Technol Biotechnol 77:725–734Anderson GK, Yang G (1992) Determination of bicarbonate and total volatile acid concentration in anaerobic digesters using a simple titration. Water Environ Res 64:53–59Andrews JF, Graef SP (1971) Dynamic modelling and simulation of the AD process. Advances in chemistry series no. 105, Anaerobic Biological Treatment Processes. American Chemical Society, Washington, DC, p 126Andrews JF, Pearson EA (1965) Kinetics and characteristics of volatile acid production in anaerobic fermentation processes. Air Water Pollut 9:439–461Angelidaki I, Sanders W (2004) Assessment of the anaerobic biodegradability of macropllutants. Rev Environ Sci Biotechnol 3:117–129Antila J, Tuohiniemi M, Rissanen A, KantojĂ€rvi U, Lahti M, Viherkanto K, Kaarre M, Malinen J (2014) MEMS- and MOEMS-based near-infrared spectrometers. Encycl Anal Chem 1–36. doi: 10.1002/9780470027318.a9376Antoniades CD, Christofides P (2001) Integrating nonlinear output feedback control and optimal actuator/sensor placement for transport-reaction processes. Chem Eng Sci 56:4517–4535APHA (2005) American Public Health Association/American Water Works Association/Water Environmental Federation, Standard methods for the Examination of Water and Wastewater, 21st edn. Washington, DC, USAAppels L, Baeyens J, DegrĂšve J, Dewil R (2008) Principles and potential of the anaerobic digestion of waste-activated sludge. Prog Energ Combust 34:755–781Appels L, Lauwers J, Gins G, Degreve J, Van Impe J, Dewil R (2011) Parameter identification and modeling of the biochemical methane potential of waste activated sludge. Environ Sci Technol 45:4173–4178Aquino SF, Chernicharo CAL, Soares H, Takemoto SY, Vazoller RF (2008) Methodologies for determining the bioavailability and biodegradability of sludges. Environ Technol 29:855–862Astals S, Esteban-GutiĂ©rrez M, FernĂĄndez-ArĂ©valo T, Aymerich E, GarcĂ­a-Heras JL, Mata-Alvarez J (2013a) Anaerobic digestion of seven different sewage sludges: a biodegradability and modelling study. Water Res 47:6033–6043Astals S, Nolla-ArdĂšvol V, Mata-Alvarez J (2013b) Thermophilic co-digestion of pig manure and crude glycerol: process performance and digestate stability. J Biotechnol 166:97–104Babary JP, Julien S, NihtilĂ€ MT et al (1999) New boundary conditions and adaptive control of fixed-bed bioreactors. Chem Eng Process Process Intensif 38:35–44Barat R, Serralta J, Ruano MV, JimĂ©nez E, Ribes J, Seco A, Ferrer J (2012) Biological nutrient removal model No 2 (BNRM2): a general model for wastewater treatment plants. Water Sci Technol 67:1481–1489Bastin G, Dochain D (1990) On-line estimation and adaptive control of bioreactors. Elsevier Science, AmsterdamBatstone DJ (2013) Modelling and control in anaerobic digestion: achievements and challenges. 13th IWA World Congress on Anaerobic Digestion (AD 13), pp 1–6Batstone DJ, Keller J, Angelidaki I et al (2002) Anaerobic digestion model No. 1. (ADM1). IWA Scientific and Technical Report No. 13. IWABatstone DJ, Tait S, Starrenburg D (2009) Estimation of hydrolysis parameters in full-scale anaerobic digesters. Biotechnol Bioeng 102:1513–1520Batstone DJ, Amerlinck Y, Ekama G et al (2012) Towards a generalized physicochemical framework. Water Sci Technol 66:1147–1161Baumann WT, Rugh WJ (1986) Feedback control of nonlinear systems by extended linearization. IEEE Trans Automat Contr AC-31:40–46Benyahia B, Campillo F, Cherki B, Harmand J (2012) Particle filtring for the chemostat. In: MED’12, Barcelone, SpainBernard O (2011) Hurdles and challenges for modelling and control of microalgae for CO2 mitigation and biofuel production. J Process Control 21:1378–1389Bernard O, GouzĂ© JL (2004) Closed loop observers bundle for uncertain biotechnological models. J Process Control 14:765–774Bernard O, Hadj-Sadok Z, Dochain D et al (2001a) Dynamical model development and parameter identification for an anaerobic wastewater treatment process. Biotechnol Bioeng 75:424–438Bernard O, Polit M, Hadj-Sadok Z, Pengov M, Dochain D, Estaben M, Labat P (2001b) Advanced monitoring and control of anaerobic wastewater treatment plants: software sensors and controllers for an anaerobic digester. Water Sci Technol 43:175–182Bernard O, Chachuat B, HĂ©lias A, Rodriguez J (2005a) Can we assess the model complexity for a bioprocess? Theory and example of the anaerobic digestion process. Water Sci Technol 53:85–92Bernard O, Chachuat B, HĂ©lias A, Le Dantec B, Sialve B, Steyer JP, Lavigne JF (2005b) An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet. Water Sci Technol 52:457–464Björnsson L, Hörnsten EG, Mattiasson B (2001a) Utilization of a palladium–metal oxide semiconductor (Pd-MOS) sensor for on-line monitoring of dissolved hydrogen in anaerobic digestion. Biotechnol Bioeng 73:35–43Björnsson L, Murto M, Jantsch TG, Mattiasson B (2001b) Evaluation of new methods for the monitoring of alkalinity, dissolved hydrogen and the microbial community in anaerobic digestion. Water Res 35:2833–2840Boe K (2006) Online monitoring and control of the biogas process. Technical University of DenmarkBoe K, Batstone D, Angelidaki I (2007) An innovative online VFA monitoring system for the anerobic process, based on headspace gas chromatography. Biotechnol Bioeng 96:712–721Boe K, Steyer JP, Angelidaki I (2008) Monitoring and control of the biogas process based on propionate concentration using online VFA measurement. Water Sci Technol 57:661–766Boe K, Batstone DJ, Steyer JP, Angelidaki I (2010) State indicators for monitoring the anaerobic digestion process. Water Res 44:5973–5980Bradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72:248–254Brinkmann K, Blaschke L, Polle A (2002) Comparison of different methods for lignin determination as a basis for calibration of near-infrared reflectance spectroscopy and implications of lignoproteins. J Chem Ecol 28:2483–2501BuendĂ­a IM, FernĂĄndez FJ, Villaseñor J, RodrĂ­guez L (2008) Biodegradability of meat industry wastes under anaerobic and aerobic conditions. Water Res 42:3767–3774Buffiere P, Loisel D, Bernet N, Delgenes JP (2006) Towards new indicators for the prediction of solid waste anaerobic digestion properties. Water Sci Technol 53:233–241Cao Y, Pawlowski A (2012) Sewage sludge-to-energy approaches based on anaerobic digestion and pyrolysis: brief overview and energy efficiency assessment. Renew Sust Energ Rev 16:1657–1665Carballa M, Regueiro L, Lema JM (2015) Microbial management of anaerobic digestion: exploiting the microbiome-functionality nexus. Curr Opin Biotechnol 33:103–111Carlos-Hernandez S, Beteau JF, Sanchez EN (2007) Intelligent control strategy for an anaerobic fluidized bed reactor. In: Michel P (ed) Computer applications in biotechnology, vol 1. Cancun, Mexico, pp 73–78Carlos-Hernandez S, Sanchez EN, Bueno JA (2010) Neurofuzzy control strategy for an abattoir wastewater treatment process. In: Banga JR, Bogaerts P, Van Impe J, Dochain D, Smets I (eds) 11th International symposium on computer applications in biotechnology. Leuven, Belgium, pp 84–89Chandler JA, Jewell WJ, Gossett JM (1980) Predicting methane fermentation biodegradability. Biotechnol Bioeng Symp 10:93–107Chen YH (1990) Adaptive robust observers for non-linear uncertain systems. Int J Syst Sci 21:803–814Chen Y, Cheng JJ, Creamer KS (2008) Inhibition of anaerobic digestion process: a review. Bioresour Technol 99:4044–4064Chynoweth DP, Turick CE, Owens JM, Jerger DE, Peck MW (1993) Biochemical methane potential of biomass and waste feedstocks. Biomass Bioenerg 5:95–111Cirne DG, van der Zee FP, Fernandez-Polanco M, Fernandez-Polanco F (2008) Control of sulphide during anaerobic treatment of S-containing wastewaters by adding limited amounts of oxygen or nitrate. Rev Environ Sci Biotechnol 7:93–105ColombiĂ© S, Latrille E, Sablayrolles JM (2007) Online estimation of assimilable nitrogen by electrical conductivity measurement during alcoholic fermentation in enological conditions. J Biosci Bioeng 103:229–235Cord-Ruwisch R, Mercz TI, Hoh CY, Strong GE (1997) Dissolved hydrogen concentration as an on-line control parameter for the automated operation and optimization of anaerobic digesters. Biotechnol Bioeng 56:626–634Cossu R, Raga R (2008) Test methods for assessing the biological stability of biodegradable waste. Waste Manage 28:381–388Cresson R, Pommier S, BĂ©line F et al (2014) Etude interlaboratoires pour l’harmonisation des protocoles de mesure du potentiel bio-mĂ©thanogĂšne des matrices solides hĂ©tĂ©rogĂšnes—Final report (in French) ADEMEDalmau J, Comas J, RodrĂ­guez-Roda I, Pagilla K, Steyer JP (2010) Model development and simulation for predicting risk of foaming in anaerobic digestion systems. Bioresour Technol 101:4306–4314Davidsson A, Gruvberger C, Christensen TH, Hansen TL, Jansen J (2007) Methane yield in source-sorted organic fraction of municipal solid waste. Waste Manage 27:406–414De Baere L (2000) Anaerobic digestion of solid waste: state-of-the-art. Water Sci Technol 41:283–290De Baere L (2008) Partial stream digestion of residual municipal solid waste. Water Sci Technol 57:1073–1077De Gracia M, Grau P, Huete E et al (2009) New generic mathematical model for WWTP sludge digesters operating under aerobic and anaerobic conditions: model building and experimental verification. Water Res 43:4626–4642De Vrieze J, Verstraete W, Boon N (2013) Repeated pulse feeding induces functional stability in anaerobic digestion. Microb Biotechnol 6:414–424Delattre C, Dochain D, Winkin J (2004) Observability analysis of nonlinear tubular (bio)reactor models: a case study. J Process Control 14:661–669Di Pinto AC, Limoni N, Passino R, Rozzi A, Tomei MC (1990) Instrumentation, control and automation of water and wastewater treatment and transport systems. In: Proceedings of the 5th IAWPRC workshop, pp 51–58DĂ­az I, PĂ©rez C, Alfaro N, Fdz-Polanco F (2015) A feasibility study on the bioconversion of CO2 and H2 to biomethane by gas sparging through polymeric membranes. Bioresour Technol 185:246–253Dochain D (2003) State and parameter estimation in chemical and biochemical processes: a tutorial. J Process Control 13:801–818Dochain D, Tali-Maamar N, Babary JP (1997) On modelling, monitoring and control of fixed bed bioreactors. Comput Chem Eng 21:1255–1266Dochain D, Perrier M, Guay M (2011) Extremum seeking control and its application to process and reaction systems: a survey. Math Comput Simulat 82:369–380Donoso-Bravo A, Garcia G, PĂ©rez-Elvira S, Fernandez-Polanco F (2011) Initial rates technique as a procedure to predict the anaerobic digester operation. Biochem Eng J 53(3):275–280Doublet J, Boulanger A, Ponthieux A, Laroche C, Poitrenaud M, Cacho Rivero JA (2013) Predicting the biochemical methane potential of wide range of organic substrates by near infrared spectroscopy. Bioresour Technol 128:252–258Dreywood R (1946) Qualitative test for carbohydrate material. Industrial & Engineering Chemistry Analytical Edition. Am Chem Soc 18:499Dubois M, Gilles KA, Hamilton JK, Rebers PA, Smith F (1956) Colorimetric method for determination of sugars and related substances. Anal Chem 28:350–356Ekama GA, Sotemann SW, Wentzel MC (2007) Biodegradability of activated sludge organics under anaerobic conditions. Water Res 41:244–252Ellison WJ, Pedarros-Caubet F, Caubet R (2007) Automatic and rapid measurement of microbial suspension growth parameters: application to the evaluation of effector agents. J Rapid Meth Aut Mic 15:369–410Fang HHP (2012) Bioenergy production from waste and wastewater in China. In: Technical proceedings of the 2012 NSTI nanotechnology conference and expo, NSTI-nanotech 2012, pp 381–383Fannin KF, Chynoweth DP, Isaacson R (1987) Start-up, operation, stability, and control. Anaerob Dig Biomass 171–196Fdz-Polanco M, DĂ­az I, PĂ©rez SI, Lopes AC, Fdz-Polanco F (2009a) Hydrogen sulphide removal in the anaerobic digestion of sludge by micro-aerobic processes: pilot plant experience. Water Sci Technol 60:3045–3050Fdz-Polanco M, PĂ©rez-Elvira SI, DĂ­az I, GarcĂ­a L, TorĂ­o R, Acevedo AF (2009b) EliminaciĂłn de H2S en digestiĂłn anaerobia de lodos por procesos microaerofĂ­licos: experiencia en planta piloto. Tecnol del Agua 29:58–64Feitkenhauer H, von Sachs J, Meyer U (2002) On-line titration of volatile fatty acids for the process control of anaerobic digestion plants. Water Res 36:212–218FernĂĄndez YB, Soares A, Villa R, Vale P, Cartmell E (2014) Carbon capture and biogas enhancement by carbon dioxide enrichment of anaerobic digesters treating sewage sludge or food waste. Bioresour Technol 159:1–7Fountoulakis MS, Stamatelatou K, Lyberatos G (2008) The effect of pharmaceuticals on the kinetics of methanogenesis and acetogenesis. Bioresour Technol 99:7083–7090Francioso O, Rodriguez-Estrada MT, Montecchio D, Salomoni C, Caputo A, Palenzona D (2010) Chemical characterization of municipal wastewater sludges produced by two-phase anaerobic digestion for biogas production. J Hazard Mater 175:740–746Frigon JC, Roy C, Guiot SR (2012) Anaerobic co-digestion of dairy manure with mulched switchgrass for improvement of the methane yield. Bioprocess Biosyst Eng 35:341–349Frings CS, Dunn RT (1970) A colorimetric method for determination of total serum lipids based on the sulfo-phospho-vanillin reaction. Am J Clin Pathol 53:89–91FrĂžlund B, Palmgren R, Keiding K, Nielsen PH (1996) Extraction of extracellular polymers from activated sludge using a cation exchange resin. Water Res 30:1749–1758Gaida D, Wolf C, Meyer C, Stuhlsatz A, Lippel J, BĂ€ck T, Bongards M, McLoone S (2012) State estimation for anaerobic digesters using the ADM1. Water Sci Technol 66:1088–1095Ganesh R, Torrijos M, Sousbie P et al (2013) Anaerobic co-digestion of solid waste: effect of increasing organic loading rates and characterization of the solubilised organic matter. Bioresource Technol 130:559–569GarcĂ­a-DiĂ©guez C, Molina F, Roca E (2011) Multi-objective cascade controller for an anaerobic digester. Process Biochem 46:900–909GarcĂ­a-Gen (2015) Modelling, optimisation and control of anaerobic co-digestion processes (2015), Ph.D. Thesis, Universidad de Santiago de Compostela, Departamento de IngenierĂ­a QuĂ­micaGarcĂ­a-Gen S, Sousbie P, Rangaraj G et al (2015) Kinetic modelling of anaerobic hydrolysis of solid wastes, including disintegration processes. Waste Manag 35:96–104Gauthier JP, Kupka IAK (1994) Observability and observers for nonlinear systems. SIAM J Control Optim 32:975–994Gauthier JP, Hammouri H, Othman S (1992) A simple observer for nonlinear systems applications to bioreactors. Autom Control IEEE Trans 37:875–880Ge H, Jensen PD, Batstone DJ (2011) Increased temperature in the thermophilic stage in temperature phased anaerobic digestion (TPAD) improves degradability of waste activated sludge. J Hazard Mater 187:355–361Gendron S, Perrier M, Barrett J, Legault N (1993) Adaptive control of brightness: the model weighting approach. Annual meeting—technical section, Canadian Pulp and Paper Association, Preprints. Publ by Canadian Pulp & Paper AssocGhosh S, Conrad JR, Klass DL (1975) Anaerobic acidogenesis of waste activated sludge, WPCF 47Goffaux G, Van de Wouwer A (2005) Bioprocess state estimation: some classical and less classical approaches. Springer, BerlinGornall AG, Bardawill CJ, David MM (1949) Determination of serum proteins by means of the biuret reaction. J Biochem Chem 177:751–766GouzĂ© JL, Rapaport A, Hadj-Sadok MZ (2000) Interval observers for uncertain biological systems. Ecol Model 133:45–56Grau P, de Gracia M, Vanrolleghem PA, Ayesa E (2007) A new plant-wide modelling methodology for WWTPs. Water Res 41:4357–4372Gregersen KH (2003) Økonomien i biogasfĂŠllesanlĂŠg, Udvikling og status medio (2002) Report no. 150. Institute of Food and Resource Economic, Rolighedsvej 25, DK 1958, Frederiksberg C, DenmarkGrepmeier M (2002) Experimentelle Untersuchungen an einer zweistufigen fuzzy-geregelten anaeroben Abwasserreinigungsanlage mit neuartigem Festbettmaterial. TU MunichGuay M, Dochain D, Perrier M (2004) Adaptive extremum seeking control of continuous stirred tank bioreactors with unknown growth kinetics. Automatica 40:881–888Gunaseelan VN (2007) Regression models of ultimate methane yields of fruits and vegetable solid wastes, sorghum and napiergrass on chemical composition. Bioresour Technol 98:1270–1277Gunaseelan VN (2009) Predicting ultimate methane yields of Jatropha curcus and Morus indica from their chemical composition. Bioresour Technol 100:3426–3429Guwy AJ, Hawkes FR, Wilcox SJ, Hawkes DL (1997) Neural network and on-off control of bicarbonate alkalinity in a fluidised-bed anaerobic digester. Water Res 31:2019–2025Guwy AJ, Dinsdale RM, Kim JR et al (2011) Fermentative biohydrogen production systems integration. Bioresour Technol 102:8534–8542Hao OJ (2003) Sulphate-reducing bacteria. In: Mara D, Horan N (eds) Handbook of water and wastewater microbiology. Academic Press Inc, London, pp 459–468HarremoĂ«s P, Capodaglio AG, H
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