Forage Systems Effect on Forage-Fed Beef Production

Locally produced forage-finished beef offers high value while enhancing economic, environmental, and social sustainability. It enhances environmental quality and the natural resource base, and makes good use of resources both on and off-farm. On the farm, it makes the most of the ability of cattle to convert grass to meat in a low-input system, making efficient use of solar energy, improving soil nutrient cycling, conserving soil and water, and limiting reliance on non-renewable resources (DeRamus 2004). Although the major causes of increased greenhouse gas emissions are due to population growth and industrialization, agriculture contributes to carbon dioxide (CO2) emissions through its use of fossil fuels during cultivation, and indirectly through energy-intensive inputs such as fertilizers. Since grassland agriculture is also a significant contributor of methane (CH4) and nitrous oxide N2O, there is now increasing pressure to curb emissions from livestock production. No-till forage establishment improves soil and air quality, minimizes surface runoff and soil erosion, enhances water quality, and reduces greenhouse gas contributions. An additional economic benefit is savings in fossil fuel costs due to reduced equipment use

Liver Transplantation Prevents Progressive Neurological Impairment in Argininemia

Argininemia is a rare hereditary disease due to a deficiency of hepatic arginase, which is the last enzyme of the urea cycle and hydrolyzes arginine to ornithine and urea. The onset of the disease is usually in childhood, and clinical manifestations include progressive spastic paraparesis and mental retardation. Liver involvement is less frequent and usually not as severe as observed in other UCDs. For this reason, and because usually there is a major neurological disease at diagnosis, patients with argininemia are rarely considered as candidates for OLT despite its capacity to replace the deficient enzyme by an active one. We report on long-term follow-up of two patients with argininemia. Patient 1 was diagnosed by the age of 20 months and despite appropriate conventional treatment progressed to spastic paraparesis with marked limp. OLT was performed at 10 years of age with normalization of plasmatic arginine levels and guanidino compounds. Ten years post-OLT, under free diet, there is no progression of neurological lesions. The second patient (previously reported by our group) was diagnosed at 2 months of age, during a neonatal cholestasis workup study. OLT was performed at the age of 7 years, due to liver cirrhosis with portal hypertension, in the absence of neurological lesions and an almost-normal brain MRI. After OLT, under free diet, there was normalization of plasmatic arginine levels and guanidino compounds. Twelve years post-OLT, she presents a normal neurological examination. We conclude that OLT prevents progressive neurological impairment in argininemia and should be considered when appropriate conventional treatment fails

Inhibition of StearoylCoA Desaturase Activity Blocks Cell Cycle Progression and Induces Programmed Cell Death in Lung Cancer Cells

Lung cancer is the most frequent form of cancer. The survival rate for patients with metastatic lung cancer is ∼5%, hence alternative therapeutic strategies to treat this disease are critically needed. Recent studies suggest that lipid biosynthetic pathways, particularly fatty acid synthesis and desaturation, are promising molecular targets for cancer therapy. We have previously reported that inhibition of stearoylCoA desaturase-1 (SCD1), the enzyme that produces monounsaturated fatty acids (MUFA), impairs lung cancer cell proliferation, survival and invasiveness, and dramatically reduces tumor formation in mice. In this report, we show that inhibition of SCD activity in human lung cancer cells with the small molecule SCD inhibitor CVT-11127 reduced lipid synthesis and impaired proliferation by blocking the progression of cell cycle through the G1/S boundary and by triggering programmed cell death. These alterations resulting from SCD blockade were fully reversed by either oleic (18:1n-9), palmitoleic acid (16:1n-7) or cis-vaccenic acid (18:1n-7) demonstrating that cis-MUFA are key molecules for cancer cell proliferation. Additionally, co-treatment of cells with CVT-11127 and CP-640186, a specific acetylCoA carboxylase (ACC) inhibitor, did not potentiate the growth inhibitory effect of these compounds, suggesting that inhibition of ACC or SCD1 affects a similar target critical for cell proliferation, likely MUFA, the common fatty acid product in the pathway. This hypothesis was further reinforced by the observation that exogenous oleic acid reverses the anti-growth effect of SCD and ACC inhibitors. Finally, exogenous oleic acid restored the globally decreased levels of cell lipids in cells undergoing a blockade of SCD activity, indicating that active lipid synthesis is required for the fatty acid-mediated restoration of proliferation in SCD1-inhibited cells. Altogether, these observations suggest that SCD1 controls cell cycle progression and apoptosis and, consequently, the overall rate of proliferation in cancer cells through MUFA-mediated activation of lipid synthesis

Dynamic optimization based on Fourier. Application to the biodiesel process

[EN] This work presents a novel methodology for the dynamic optimization of the biodiesel production process from vegetable oils in discontinuous mode. The proposed methodology has the particularity of using the Fourier series for the parameterization of the control action, and evolutionary algorithms for the optimization of parameters. The main advantages of this strategy are, on the one hand, that the profiles obtained are smooth, that is, continuous and differentiable, therefore they can be directly implemented in real systems, without the need to filter or soften the control signal; on the other hand, a minimum amount of parameters is required for optimization, avoiding over-parameterization, which can decrease the quality of the response. The proposed algorithms have been evaluated through simulations, obtaining very satisfactory results compared to those published in the literature.[ES] Este trabajo presenta una novedosa metodología para la optimización dinámica del proceso de producción de biodiesel a partir de aceites vegetales en modo discontinuo. La metodología propuesta tiene la particularidad de emplear la serie de Fourier para la parametrización de la acción de control, y algoritmos evolutivos para la optimización de parámetros. Las ventajas principales de esta estrategia son, por un lado, que los perfiles obtenidos son suaves, es decir, continuos y diferenciables, por lo tanto pueden implementarse directamente en sistemas reales, sin necesidad de filtrar o suavizar la señal de control; por otro lado, se requiere una mínima cantidad de parámetros para la optimización, evitando la sobre-parametrización, la cual puede disminuir la calidad de la respuesta. Los algoritmos propuestos han sido evaluados a través de simulaciones, obteniendo resultados muy satisfactorios comparados con los existentes en bibliografía.Agradecemos al Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET) por financiar este proyecto, y al Instituto de Ingeniería Química (IIQ) de la Universidad Nacional de San Juan (UNSJ) por su continua colaboración.Pantano, MN.; Fernández, MC.; Rodríguez, L.; Scaglia, GJ. (2020). Optimización dinámica basada en Fourier. Aplicación al proceso de biodiesel. Revista Iberoamericana de Automática e Informática industrial. 18(1):32-38. https://doi.org/10.4995/riai.2020.12920OJS3238181Benavides, P. T. & Diwekar, U., 2012a. Optimal control of biodiesel production in a batch reactor: Part I: Deterministic control. Fuel,94, 211- 217. https://doi.org/10.1016/j.fuel.2011.08.035Benavides, P. T. & Diwekar, U., 2012b. Optimal control of biodiesel production in a batch reactor: Part II: Stochastic control. Fuel,94, 218-226. https://doi.org/10.1016/j.fuel.2011.08.033Brásio, A. S., Romanenko, A., Leal, J., Santos, L. O. & Fernandes, N. C., 2013. Nonlinear model predictive control of biodiesel production via transesterification of used vegetable oils. Journal of Process Control,10,23, 1471-1479. https://doi.org/10.1016/j.jprocont.2013.09.023Cantrell, D. G., Gillie, L. J., Lee, A. F. & Wilson, K., 2005. Structure-reactivity correlations in MgAl hydrotalcite catalysts for biodiesel synthesis. Applied Catalysis A: General,2,287, 183-190. https://doi.org/10.1016/j.apcata.2005.03.027Fernández, Cecilia, M., Nadia Pantano, M., Rossomando, F. G., Alberto Ortiz, O. & Scaglia, G. J., 2019. State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system. Brazilian Journal of Chemical Engineering,1,36, 421-437. https://doi.org/10.1590/0104-6632.20190361s20170379Fernández, C., Pantano, N., Godoy, S., Serrano, E. & Scaglia, G., 2019a. Optimización de Parámetros Utilizando los Métodos de Monte Carlo y Algoritmos Evolutivos. Aplicación a un Controlador de Seguimiento de Trayectoria en Sistemas no Lineales. Revista Iberoamericana de Automática e Informática industrial,1,16, 89-99. https://doi.org/10.4995/riai.2018.8796Fernández M. C., P. M. N., Rodriguez L., Scaglia G., 2020. State Estimation and Nonlinear Tracking Control Simulation Approach. Application to a Bioethanol Production System. Bioprocess and Biosystems Engineering,In press.Fernández, M. C., Pantano, M. N., Machado, R. A. F., Ortiz, O. A. & Scaglia, G. J., 2019b. Nonlinear multivariable tracking control: application to an ethanol process. International Journal of Automation and Control,4,13, 440-468. https://doi.org/10.1504/IJAAC.2019.10020240Fernández, M. C., Pantano, M. N., Rómoli, S., Patiño, H. D., Ortiz, O. A. & Scaglia, G. J., 2019c. An algebra approach for nonlinear multivariable fedbatch bioprocess control. International Journal of Industrial and Systems Engineering,1,33, 38-57. https://doi.org/10.1504/IJISE.2019.10023564Fernández, M. C., Pantano, M. N., Serrano, E. & Scaglia, G., 2020. Multivariable Tracking Control of a Bioethanol Process under Uncertainties. Mathematical Problems in Engineering,2020. https://doi.org/10.1155/2020/8263690Ho, Y., Mjalli, F. & Yeoh, H., 2010. Multivariable adaptive predictive model based control of a biodiesel transesterification reactor. Journal of Applied Sciences,12,10, 1019-1027. https://doi.org/10.3923/jas.2010.1019.1027Ignat, R. M. & Kiss, A. A., 2013. Optimal design, dynamics and control of a reactive DWC for biodiesel production. Chemical Engineering Research and Design,9,91, 1760-1767. https://doi.org/10.1016/j.cherd.2013.02.009Kreyszig, E. 1978. Introductory functional analysis with applications, Wiley New York.Mjalli, F. S., Kim San, L., Chai Yin, K. & Azlan Hussain, M., 2009. Dynamics and control of a biodiesel transesterification reactor. Chemical Engineering & Technology,1,32, 13-26. https://doi.org/10.1002/ceat.200800243Nagle, R. K., Saff, E. B. & Snider, A. D. 2001. Ecuaciones diferenciales y problemas con valores en la frontera, Pearson Educación.Nasir, N., Daud, W. R. W., Kamarudin, S. & Yaakob, Z., 2013. Process system engineering in biodiesel production: A review. Renewable and Sustainable Energy Reviews,22, 631-639. https://doi.org/10.1016/j.rser.2013.01.036Nearing, J., 2006. Mathematical tools for physics.Pantano, M. N., Fernández, M. C., Serrano, M. E., Ortiz, O. A. & Scaglia, G. J. E., 2018. Tracking Control of Optimal Profiles in a Nonlinear Fed-Batch Bioprocess under Parametric Uncertainty and Process Disturbances. Industrial & Engineering Chemistry Research,32,57, 11130-11140.https://doi.org/10.1021/acs.iecr.8b01791Pantano, M. N., Serrano, M. E., Fernández, M. C., Rossomando, F. G., Ortiz, O. A. & Scaglia, G. J., 2017. Multivariable Control for Tracking Optimal Profiles in a Nonlinear Fed-Batch Bioprocess Integrated with State Estimation. Industrial & Engineering Chemistry Research,20,56, 6043- 6056. https://doi.org/10.1021/acs.iecr.7b00831Rajarathinam, K., Gomm, J. B., Yu, D.-L. & Abdelhadi, A. S., 2016. PID controller tuning for a multivariable glass furnace process by genetic algorithm. International Journal of Automation and Computing,1,13, 64- 72. https://doi.org/10.1007/s11633-015-0910-1Salvi, B. & Panwar, N., 2012. Biodiesel resources and production technologies-A review. Renewable and Sustainable Energy Reviews,6,16, 3680-3689. https://doi.org/10.1016/j.rser.2012.03.050Santori, G., Di Nicola, G., Moglie, M. & Polonara, F., 2012. A review analyzing the industrial biodiesel production practice starting from vegetable oil refining. Applied energy,92, 109-132. https://doi.org/10.1016/j.apenergy.2011.10.031Tempo, R. & Ishii, H., 2007. Monte Carlo and Las Vegas Randomized Algorithms for Systems and Control: An Introduction. European Journal of Control,2-3,13, 189-203. https://doi.org/10.3166/ejc.13.189-203Wali, W., Al-Shamma'a, A., Hassan, K. H. & Cullen, J., 2012. Online geneticANFIS temperature control for advanced microwave biodiesel reactor. Journal of Process Control,7,22, 1256-1272. https://doi.org/10.1016/j.jprocont.2012.05.013Wali, W., Hassan, K., Cullen, J., Shaw, A. & Al-Shamma'a, A., 2013. Real time monitoring and intelligent control for novel advanced microwave biodiesel reactor. Measurement,1,46, 823-839. https://doi.org/10.1016/j.measurement.2012.10.004Zhang, M., Gao, Z., Zheng, T., Ma, Y., Wang, Q., Gao, M. & Sun, X., 2016. A bibliometric analysis of biodiesel research during 1991-2015. Journal of Material Cycles and Waste Management, 1-9. https://doi.org/10.1007/s10163-016-0575-zZhang, Y., Dube, M., McLean, D. & Kates, M., 2003. Biodiesel production from waste cooking oil: 1. Process design and technological assessment. Bioresource technology,1,89, 1-16. https://doi.org/10.1016/S0960-8524(03)00040-

Year-Round Forage Systems for Beef Cows and Calves

Beef cow systems in the USA are based on forages with little or no concentrates fed. Tall fescue (Festuca arundinacea Schreb. L.) is one of the important pasture forages in the lower Northeast and upper South (Allen et al., 2001). Limited research has been conducted on year-round all forage systems based on cool season forages. Stockpiling tall fescue in late summer-early fall provides good quality forage that is usually grazed rather than harvested. Forage systems including tall fescue and clover (Trifolium repens L.) produced excellent performance in beef cows and calves, with minimum inputs (Allen et al., 2001). The present experiment is a component of a larger initiative, Pasture-based Forage Systems for Appalachia. The specific objective of this experiment is to evaluate different forage systems for beef cows and calves

Development of a tomato pomace biorefinery based on a CO2-supercritical extraction process for the production of a high value lycopene product, bioenergy and digestate

Tomato peels and seeds (TP) are the most abundant canning industry waste actually used to produce biogas. TP is rich in lycopene (lyc) and represent a more sustainable feedstock than tomato fruits actually employed. It was therefore chosen as feedstock together with supercritical CO2 extraction (SFE-CO2) technology to develop a TP-SFE-CO2 biorefinery, topic scarcely investigated. Two TP were tested and although TP-SFE-CO2 parameters were the same, lyc recoveries depended by peel structure changes occurred during pre -SFE-CO2 drying step. Higher moisture (102.7 g kg-1 wet weight) permitted 97 % lyc recovery and gave a water-in-oil emulsion as extract. Mass balance confirmed that lyc isomerisation did not cause lyc losses. After a significant oil extraction, exhaust TP showed a biodegradability 64% higher than the raw one, attributable to fibre structure disruption. The biorefinery proposed (SFE_CO2+anaerobic digestion) determined positive economic revenue (+787.9 \u20ac t-1 TP) on the contrary of the actual TP management

Linear Algebra Based trajectory control

[ES] En este tutorial se resumen las principales características de una nueva metodología de diseño de sistemas de control para el seguimiento de trayectorias en procesos no lineales. Esta metodología, denominada LAB (Linear Algebra Based), fue presentada por los autores hace más de diez años y ha tenido una fuerte repercusión por su sencillez y facilidad de aplicación, si bien no es aplicable para algunos problemas de seguimiento en sistemas no lineales. Se exponen las etapas en el diseño de un controlador LAB, tanto en tiempo continuo como en discreto. La aplicación al control de la trayectoria de un robot móvil, en tiempo continuo, sirve para ilustrar el desarrollo e implementación del control. Se analizan algunas propiedades del sistema controlado y se resaltan las condiciones de aplicación. Numerosas referencias facilitan el desarrollo de algunas características y su aplicación en diversos campos de la robótica y del control de procesos en general.[EN] In this tutorial, the main features of a new control design methodology for tracking control in nonlinear processes is summarized. The so called LAB (Linear Algebra Based) methodology was introduced by the authors more than ten years ago and it has been accepted and used by many researchers mainly due to its simplicity and easy application. Nevertheless, it is not applicable to all the tracking problems dealing with nonlinear systems. The LAB controller design procedure, both in continuous time and discretetime, is outlined. The design of the trajectory control of a mobile robot illustrates the procedure as well as its implementation. Some properties of the controlled process are discussed and the problem requirements for a successful application are pointed out. Several references allow a deeper analysis of the controlled plant features as well as its application in a variety of processes, either in robotics or in process control.Scaglia, GJE.; Serrano, ME.; Albertos Pérez, P. (2020). Control de trayectorias basado en álgebra lineal. Revista Iberoamericana de Automática e Informática industrial. 17(4):344-353. https://doi.org/10.4995/riai.2020.13584OJS344353174Apostol, T., 1967. CALCULUS, One -Variable Calculus, with an introduction to Linear Algebra. Blaisdell Publishing Company.Battilotti, S., Califano, C., 2004. A constructive condition for dynamic feedback linearization. Systems & control letters 52(5), 329-338. https://doi.org/10.1016/j.sysconle.2004.02.009Bouhenchir, H., Cabassud, M., Le Lann, M.-V., 2006. Predictive functional control for the temperature control of a chemical batch reactor. Computers & Chemical Engineering 30 (6-7), 1141-1154. https://doi.org/10.1016/j.compchemeng.2006.02.014Brockett, R., 1965. Poles, zeros, and feedback: State space interpretation. IEEE Transactions on Automatic Control 10(2), 129-135. https://doi.org/10.1109/TAC.1965.1098118Charlet, B., Levine, J., Marino, R., 1988. Dynamic feedback linearization with application to aircraft control. Proceedings of the 27th IEEE Conference on Decision and Control, Austin, TX, USA 1, 701-705.Chwa, D., 2004. Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates. IEEE transactions on control systems technology 12 (4), 637-644. https://doi.org/10.1109/TCST.2004.824953den Boom, T. J. J. V., 1998. On feedback linearization in LMI-based nonlinear MPC. In Proceedings of the 1998 American Control Conference 3, 1684-1688.Devasia, S., Chen, D., B., P., 1996. Nonlinear inversion-based output tracking. IEEE Transactions on Automatic Control 41(7), 930-942. https://doi.org/10.1109/9.508898Fernandez, M. C., Romoli, S., Pantano, M. N., Ortiz, O. A., Patiño, D., Scaglia,G. J., 2018. A new approach for nonlinear multivariable fed-batch bioprocess trajectory tracking control. Automatic Control and Computer Sciences 52 (1), 13-24. https://doi.org/10.3103/S0146411618010030Francis, B. A., 1977. The linear multivariable regulator problem. SIAM Journal on Control and Optimization 15(3), 486-505. https://doi.org/10.1137/0315033Fukao, T., Nakagawa, H., Adachi, N., 2000. Adaptive tracking control of a nonholonomic mobile robot. IEEE transactions on Robotics and Automation 16 (5), 609-615. https://doi.org/10.1109/70.880812Gandolfo, D., Rosales, C., Patiño, D., Scaglia, G., Jordan, M., 2014. Trajectory tracking control of a pvtol aircraft based on linear algebra theory. Asian Journal of Control 16 (6), 1849-1858.https://doi.org/10.1002/asjc.819Ghandan, R., Blankenship, G. L., 1993. Adaptive approximate tracking and regulation of nonlinear systems. Proceedings of 32nd IEEE Conference on Decision and Control 1, 2654-2659.Hepburn, J., Wonham, W., 1984. Error feedback and internal models on dierentiable manifolds. IEEE Transactions on Automatic Control 29(5), 397-403. https://doi.org/10.1109/TAC.1984.1103563Huang, R., Zhu, J. J., 2009. Time-varying high-gain trajectory linearization observer design. Proceedings of American Control Conference 1, 4628-4635. https://doi.org/10.1109/ACC.2009.5160252Isidori, A., Byrnes, C. I., 1990. Output regulation of nonlinear systems. IEEE transactions on Automatic Control, 35(2), 131-140. https://doi.org/10.1109/9.45168Kanayama, Y., Kimura, Y., Miyazaki, F., Noguchi, T., 1990. A stable tracking control method for an autonomous mobile robot. In: Proceedings. IEEE International Conference on Robotics and Automation. IEEE, pp. 384-389.Khalil, H., 2002. Nonlinear Systems. Prentice Hall.Lee, H. G., Arapostathis, A., I.Marcus, S., 2003. An algorithm for linearization of discrete-time systems via restricted dynamic feedback. In Proceedings of 42nd IEEE International Conference on Decision and Control 2, 1362-1367.Levine, J., Marino, R., 1990. On dynamic feedback linearization in r/sup 4. In Proceedings 29th IEEE Conference on Decision and Control IEEE. Honolulu, Hawaii. 1, 2088-2090. https://doi.org/10.1109/CDC.1990.203992Li, X. S., Li, Y. H., Li, X., Peng, J., Li, C. X., 2012. Robust trajectory linearization control design for unmanned aerial vehicle path following. Systems Engineering and Electronics 34(4), 767-772.Li, Z., Deng, J., Lu, R., Xu, Y., Bai, J., Su, C.-Y., 2015. Trajectory-tracking control of mobile robot systems incorporating neural-dynamic optimized model predictive approach. IEEE Transactions on Systems, Man, and Cybernetics: Systems 46 (6), 740-749. https://doi.org/10.1109/TSMC.2015.2465352Lustosa, L. R., Defaÿ, F., Moschetta, J. M., 2017. The feasibility issue in trajectory tracking by means of regions-of-attraction-based gain scheduling. IFAC-PapersOnLine 50(1), 11504-11508. https://doi.org/10.1016/j.ifacol.2017.08.1609Moore, J., Cory, R., Tedrake, R., 2014. Robust post-stall perching with a simple fixed-wing glider using LQR-Trees. Bioinspiration & biomimetics 9(2), 025013. https://doi.org/10.1088/1748-3182/9/2/025013Panahandeh, P., Alipour, K., Tarvirdizadeh, B., Hadi, A., 2019. A kinematic lyapunov-based controller to posture stabilization of wheeled mobile robots. Mechanical Systems and Signal Processing 134, 106319. https://doi.org/10.1016/j.ymssp.2019.106319Pantano, M. N., Fernandez, M. C., Serrano, M. E., Ortiz, O. A., Scaglia, G. J., 2018. Tracking control of optimal profiles in a nonlinear fed-catch bioprocess under parametric uncertainty and process disturbances. Industrial & Engineering Chemistry Research 57 (32), 11130-11140. https://doi.org/10.1021/acs.iecr.8b01791Pantano, M. N., Fernández, M. C., Serrano, M. E., Ortíz, O. A., Scaglia, G. J. E., 2019. Trajectory tracking controller for a nonlinear fed-batch bioprocess. Revista Ingeniería Electrónica, Automática y Comunicaciones ISSN:1815-5928 38 (1), 78.Proaño, P., Capito, L., Rosales, A., Camacho, O., 2015. Sliding mode control:Implementation like pid for trajectory-tracking for mobile robots. In: 2015 Asia-Pacific Conference on Computer Aided System Engineering. IEEE, pp.220-225. https://doi.org/10.1109/APCASE.2015.46Rojas, O. J., Goodwin, G. C., 2001. Preliminary analysis of a nonlinear control scheme related to feedback linearization. In Proceedings of the 40th IEEE Conference on Decision and Control 2, 1743-1748.Rosales, A., Scaglia, G., Mut, V., di Sciascio, F., 2009. Navegación de robots móviles en entornos no estructurados utilizando álgebra lineal. Revista Iberoamericana de Automática e Informática Industrial RIAI, 6(2), 79-88. https://doi.org/10.1016/S1697-7912(09)70096-2Rosales, C., Gandolfo, D., Scaglia, G., Jordan, M., Carelli, R., 2015. Trajectory tracking of a mini four-rotor helicopter in dynamic environments-a linear algebra approach. Robotica 33 (8), 1628-1652. https://doi.org/10.1017/S0263574714000952Scaglia, G., Montoya, L. Q., Mut, V., di Sciascio, F., 2009. Numerical methods based controller design for mobile robots. Robotica 27 (2), 269-279. https://doi.org/10.1017/S0263574708004669Scaglia, G., Quintero, O. L., Mut, V., di Sciascio, F., 2008. Numerical methods based controller design for mobile robots. IFAC Proceedings Volumes 41 (2), 4820 - 4827. https://doi.org/10.3182/20080706-5-KR-1001.00810Scaglia, G., Serrano, E., Rosales, A., Albertos, P., 2015. Linear interpolation based controller design for trajectory tracking under uncertainties: Application to mobile robots. Control Engineering Practice 45, 123-132. https://doi.org/10.1016/j.conengprac.2015.09.010Scaglia, G., Serrano, E., Rosales, A., Albertos, P., 2019. Tracking control design in nonlinear multivariable systems: Robotic applications. Mathematical Problems in Engineering 2019. https://doi.org/10.1155/2019/8643515Scaglia, G., Serrano, M., Albertos, P., 2020. Linear Algebra Based Controllers: Design and Applications. Springer International Publishing. URL: https://books.google.es/books?id=ELzoDwAAQBAJ , https://doi.org/10.1007/978-3-030-42818-1Serrano, M. E., Godoy, S. A., Quintero, L., Scaglia, G. J., 2017. Interpolation based controller for trajectory tracking in mobile robots. Journal of Intelligent & Robotic Systems 86 (3-4), 569-581. https://doi.org/10.1007/s10846-016-0422-4Serrano, M. E., Scaglia, G. J., Godoy, S. A., Mut, V., Ortiz, O. A., 2013. Trajectory tracking of underactuated surface vessels: A linear algebra approach. IEEE Transactions on Control Systems Technology 22 (3), 1103-1111. https://doi.org/10.1109/TCST.2013.2271505Silverman, L., 1968. Properties and application of inverse systems. IEEE transactions on Automatic Control 13(4), 436-437. https://doi.org/10.1109/TAC.1968.1098943Silverman, L., 1969. Inversion of multivariable linear systems. IEEE transactions on Automatic Control 14(3), 270-276. https://doi.org/10.1109/TAC.1969.1099169Sun, W., Tang, S., Gao, H., Zhao, J., 2016. Two time-scale tracking control of nonholonomic wheeled mobile robots. IEEE Transactions on Control Systems Technology 24 (6), 2059-2069. https://doi.org/10.1109/TCST.2016.2519282Xingling, S., Honglun, W., 2016. Trajectory linearization control based output tracking method for nonlinear uncertain system using linear extended state observer. Asian Journal of Control 18(1), 316-327. https://doi.org/10.1002/asjc.1053Zeng, G., Hunt, L. R., 2000. Stable inversion for nonlinear discrete-time systems. IEEE Transactions on Automatic Control 45(6), 1216-1220. https://doi.org/10.1109/9.863610Zhu, J. J., Banker, B., Hall, C., 2000. X-33 ascent flight control design by trajectory linearization-a singular perturbation approach. Proceedings of AIAA guidance, navigation, and control conference and exhibit 1, 4159. https://doi.org/10.2514/6.2000-4159Zhu, J. J., Funston, K., Hall, C. E., Hodel, A. S., 2001. X-33 entry flight control design by trajectory linearization- a singular perturbation approach. Guidanceand control 1, 151-170. https://doi.org/10.2514/6.2000-4159Zhu, L., Jiang, C. S., Xue, Y. L., 2008. Robust adaptive trajectory linearization control for aerospace vehicle using single hidden layer neutral networks. Acta Armamentarii 29(1), 52-56

Effect of Felisept spray® on signs of travel anxiety in cats

Car transport can be stressful for cats. Most frequently reported symptoms are vocalisations, restlessness, panting, trembling, salivation and vomiting1. These symptoms could be fear induced as a result of insufficient or bad experiences with car transport, but they could also result from motion sickness. However, the distinction between these two diagnosis is not very clear. Little research has been published on this area2,3. This study aims to evaluate the effects of the Felisept spray\uae on signs of travel-related problems in cats. 10 cats (6 males and 4 females) of different breeds, aged between 2 and 13 years, referred for problems when transported by car, were recruited. Owners were asked to fill in a questionnaire in order to understand cat behaviour during travel. Each cat was then filmed during two car transports of 15 min. The first transport was a routine transportation (baseline trial), in the second one Felisept\uae was sprayed in the pet carrier 10 minutes before the travel (treatment trial). An additional questionnaire was used to investigate cat behaviour during the treatment trial. The questionnaires analysis showed that vocalizations, tail close to body and mydriasis decreased after the administration of Felisept spray\uae (Wilcoxon, p<0.05), while panting and swallowing tend to decrease (Wilcoxon, p=0.66). Video analysis showed that restlessness, crouched position and mydriasis decreased after the administration of Felisept spray\uae (Wilcoxon, p<0.05). These results suggest that the use of Felisept\uae spray in the pet carrier 10 minutes before the transport could decrease transport-related signs of stress in cats

tRNAdb 2009: compilation of tRNA sequences and tRNA genes

One of the first specialized collections of nucleic acid sequences in life sciences was the ‘compilation of tRNA sequences and sequences of tRNA genes’ (http://www.trna.uni-bayreuth.de). Here, an updated and completely restructured version of this compilation is presented (http://trnadb.bioinf.uni-leipzig.de). The new database, tRNAdb, is hosted and maintained in cooperation between the universities of Leipzig, Marburg, and Strasbourg. Reimplemented as a relational database, tRNAdb will be updated periodically and is searchable in a highly flexible and user-friendly way. Currently, it contains more than 12 000 tRNA genes, classified into families according to amino acid specificity. Furthermore, the implementation of the NCBI taxonomy tree facilitates phylogeny-related queries. The database provides various services including graphical representations of tRNA secondary structures, a customizable output of aligned or un-aligned sequences with a variety of individual and combinable search criteria, as well as the construction of consensus sequences for any selected set of tRNAs