Lithofacies and depositional environment of volcano-sedimentary deposits of SE Mayo Oulo basin

The study of volcano-sedimentary deposits of Mangbai in SE Mayo Oulo basin-Cameroon leads to the identification of five major distinct lithofacies types. From the coarset to the finest lithofacies, there are : Gb-clast supported by massive coble and boulder, Gg-granule to massive gravel, Sm-massive sand, Shhorizontal layered sandstones, Fml-massive laminated claystones. Coarse facies (Gb, Gg, Sm) are cemented with volcanic matrix while the finest facies (Sh, Fml) are normal sedimentary compacted deposits. The coarsest facies distribution is identified on the top SE of the mountain while the medium to finest facies deposits are located at the base of the sequence. The formation of the volcano-sedimentary deposits of Mangbai are associated to the development and establishment of Africa major rift system while sedimentary deposits in the Mayo Oulo basin are more recent and date from Lower Cretaceous

Evaluating Tisza River Basin Development Plans Using Multiattribute Utility Theory

Selecting a plan to develop the water resources of a region involves the consideration of economic, environmental, social, and technical objectives. Twelve attributes are defined to indicate the degree to which these objectives are achieved in the Tisza River basin of Hungary. A preliminary multiattribute utility function is assessed over these attributes. This is combined with existing information describing the possible consequences of five alternative development plans to yield an overall rating of their desirability. The utility function explicitly indicates the preference tradeoffs among attributes. Discussion indicates further uses of the utility function in the planning and evaluation processes

Homomultimeric structure by assembly of sirv2 p98 proteins or p98 variants, conjugate and uses thereof

The present invention relates to a homomultimeric protein structure constituted by assembled monomers of the P98 protein of Sulfolobus islandicus rod-shaped virus 2 (SIRV2) or assembled monomer variants of said P98 protein. In a particular embodiment, this homomultimeric protein structure has a seven-fold rotational symmetry, and is found in an open conformation or closed conformation. A particular structure has the form of baseless 7-face pyramid. The invention also relates to a conjugate comprising or consisting of a homomultimeric protein structure of the invention to which one or more heterologous molecule(s) is attached. Furthermore, the invention also concerns a homomultimeric protein structure or a conjugate of the invention, inserted into or exposed at the surface of a lipid layer or bilayer, of a vesicle or of a cell, and their uses thereof

Homomultimeric structure by assembly of sirv2 p98 proteins or p98 variants, conjugate and uses thereof

The present invention relates to a homomultimeric protein structure constituted by assembled monomers of the P98 protein of Sulfolobus islandicus rod-shaped virus 2 (SIRV2) or assembled monomer variants of said P98 protein. In a particular embodiment, this homomultimeric protein structure has a seven-fold rotational symmetry, and is found in an open conformation or closed conformation. A particular structure has the form of baseless 7-face pyramid. The invention also relates to a conjugate comprising or consisting of a homomultimeric protein structure of the invention to which one or more heterologous molecule(s) is attached. Furthermore, the invention also concerns a homomultimeric protein structure or a conjugate of the invention, inserted into or exposed at the surface of a lipid layer or bilayer, of a vesicle or of a cell, and their uses thereof

Boundless multiobjective models for cash management

"This is an Accepted Manuscript of an article published by Taylor & Francis in Engineering Economist on 31-05-2018, available online: https://doi.org/10.1080/0013791X.2018.1456596"[EN] Cash management models are usually based on a set of bounds that complicate the selection of the optimal policies due to nonlinearity. We here propose to linearize cash management models to guarantee optimality through linear-quadratic multiobjective compromise programming models. We illustrate our approach through a reformulation of the suboptimal state-of-the-art Gormley-Meade¿s model to achieve optimality. Furthermore, we introduce a much simpler formulation that we call the boundless model that also provides optimal solutions without using bounds. Results from a sensitivity analysis using real data sets from 54 different companies show that our boundless model is highly robust to cash flow prediction errors.Generalitat de Catalunya [2014 SGR 118]; Ministerio de Economia y Competitividad [Collectiveware TIN2015-66863-C2-1-R].Salas-Molina, F.; Rodriguez-Aguilar, JA.; Pla Santamaría, D. (2018). Boundless multiobjective models for cash management. Engineering Economist (Online). 63(4):363-381. https://doi.org/10.1080/0013791X.2018.1456596S363381634Artzner, P., Delbaen, F., Eber, J.-M., & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203-228. doi:10.1111/1467-9965.00068Baccarin, S. (2009). Optimal impulse control for a multidimensional cash management system with generalized cost functions. European Journal of Operational Research, 196(1), 198-206. doi:10.1016/j.ejor.2008.02.040Ballestero, E., & Romero, C. (1998). Multiple Criteria Decision Making and its Applications to Economic Problems. doi:10.1007/978-1-4757-2827-9Bar-Ilan, A., Perry, D., & Stadje, W. (2004). A generalized impulse control model of cash management. Journal of Economic Dynamics and Control, 28(6), 1013-1033. doi:10.1016/s0165-1889(03)00064-2Baumol, W. J. (1952). The Transactions Demand for Cash: An Inventory Theoretic Approach. The Quarterly Journal of Economics, 66(4), 545. doi:10.2307/1882104Bemporad, A., & Morari, M. (1999). Control of systems integrating logic, dynamics, and constraints. Automatica, 35(3), 407-427. doi:10.1016/s0005-1098(98)00178-2Ben-Tal, A., El Ghaoui, L., & Nemirovski, A. (2009). Robust Optimization. doi:10.1515/9781400831050Branke, J., Deb, K., Miettinen, K., & Słowiński, R. (Eds.). (2008). Multiobjective Optimization. Lecture Notes in Computer Science. doi:10.1007/978-3-540-88908-3Chelouah, R., & Siarry, P. (2000). Journal of Heuristics, 6(2), 191-213. doi:10.1023/a:1009626110229Chen, X., & Simchi-Levi, D. (2009). A NEW APPROACH FOR THE STOCHASTIC CASH BALANCE PROBLEM WITH FIXED COSTS. Probability in the Engineering and Informational Sciences, 23(4), 545-562. doi:10.1017/s0269964809000242Constantinides, G. M., & Richard, S. F. (1978). Existence of Optimal Simple Policies for Discounted-Cost Inventory and Cash Management in Continuous Time. Operations Research, 26(4), 620-636. doi:10.1287/opre.26.4.620Moraes, M. B. da C., & Nagano, M. S. (2014). Evolutionary models in cash management policies with multiple assets. Economic Modelling, 39, 1-7. doi:10.1016/j.econmod.2014.02.010Da Costa Moraes, M. B., Nagano, M. S., & Sobreiro, V. A. (2015). Stochastic Cash Flow Management Models: A Literature Review Since the 1980s. Decision Engineering, 11-28. doi:10.1007/978-3-319-11949-6_2De Avila Pacheco, J. V., & Morabito, R. (2011). Application of network flow models for the cash management of an agribusiness company. Computers & Industrial Engineering, 61(3), 848-857. doi:10.1016/j.cie.2011.05.018Girgis, N. M. (1968). Optimal Cash Balance Levels. Management Science, 15(3), 130-140. doi:10.1287/mnsc.15.3.130Golden, B., Liberatore, M., & Lieberman, C. (1979). Models and solution techniques for cash flow management. Computers & Operations Research, 6(1), 13-20. doi:10.1016/0305-0548(79)90010-8Gormley, F. M., & Meade, N. (2007). The utility of cash flow forecasts in the management of corporate cash balances. European Journal of Operational Research, 182(2), 923-935. doi:10.1016/j.ejor.2006.07.041Gregory, G. (1976). Cash flow models: A review. Omega, 4(6), 643-656. doi:10.1016/0305-0483(76)90092-xGurobi Optimization, Inc (2017) Gurobi optimizer reference manual, Houston.Keown, A. J., & Martin, J. D. (1977). A Chance Constrained Goal Programming Model for Working Capital Management. The Engineering Economist, 22(3), 153-174. doi:10.1080/00137917708965174Miller, M. H., & Orr, D. (1966). A Model of the Demand for Money by Firms. The Quarterly Journal of Economics, 80(3), 413. doi:10.2307/1880728Neave, E. H. (1970). The Stochastic Cash Balance Problem with Fixed Costs for Increases and Decreases. Management Science, 16(7), 472-490. doi:10.1287/mnsc.16.7.472PARK, C. S., & HERATH, H. S. B. (2000). EXPLOITING UNCERTAINTY—INVESTMENT OPPORTUNITIES AS REAL OPTIONS: A NEW WAY OF THINKING IN ENGINEERING ECONOMICS. The Engineering Economist, 45(1), 1-36. doi:10.1080/00137910008967534Penttinen, M. J. (1991). Myopic and stationary solutions for stochastic cash balance problems. European Journal of Operational Research, 52(2), 155-166. doi:10.1016/0377-2217(91)90077-9Rockafellar, R. T., & Uryasev, S. (2002). Conditional value-at-risk for general loss distributions. Journal of Banking & Finance, 26(7), 1443-1471. doi:10.1016/s0378-4266(02)00271-6Salas-Molina, F., Martin, F. J., Rodríguez-Aguilar, J. A., Serrà, J., & Arcos, J. L. (2017). Empowering cash managers to achieve cost savings by improving predictive accuracy. International Journal of Forecasting, 33(2), 403-415. doi:10.1016/j.ijforecast.2016.11.002Salas-Molina, F., Pla-Santamaria, D., & Rodriguez-Aguilar, J. A. (2016). A multi-objective approach to the cash management problem. Annals of Operations Research, 267(1-2), 515-529. doi:10.1007/s10479-016-2359-1Srinivasan, V., & Kim, Y. H. (1986). Deterministic cash flow management: State of the art and research directions. Omega, 14(2), 145-166. doi:10.1016/0305-0483(86)90017-4Stone, B. K. (1972). The Use of Forecasts and Smoothing in Control-Limit Models for Cash Management. Financial Management, 1(1), 72. doi:10.2307/3664955Stone, B. K., & Miller, T. W. (1987). Daily Cash Forecasting with Multiplicative Models of Cash Flow Patterns. Financial Management, 16(4), 45. doi:10.2307/3666108Xu, X., & Birge, J. R. (2008). Operational Decisions, Capital Structure, and Managerial Compensation: A News Vendor Perspective. The Engineering Economist, 53(3), 173-196. doi:10.1080/00137910802262887Yu, P.-L. (1985). Multiple-Criteria Decision Making. doi:10.1007/978-1-4684-8395-

Dysregulation of alternative poly-adenylation as a potential player in Autism Spectrum Disorder

We present here the hypothesis that alternative poly-adenylation (APA) is dysregulated in the brains of individuals affected by Autism Spectrum Disorder (ASD), due to disruptions in the calcium signaling networks. APA, the process of selecting different poly-adenylation sites on the same gene, yielding transcripts with different-length 3′ untranslated regions (UTRs), has been documented in different tissues, stages of development and pathologic conditions. Differential use of poly-adenylation sites has been shown to regulate the function, stability, localization and translation efficiency of target RNAs. However, the role of APA remains rather unexplored in neurodevelopmental conditions. In the human brain, where transcripts have the longest 3′ UTRs and are thus likely to be under more complex post-transcriptional regulation, erratic APA could be particularly detrimental. In the context of ASD, a condition that affects individuals in markedly different ways and whose symptoms exhibit a spectrum of severity, APA dysregulation could be amplified or dampened depending on the individual and the extent of the effect on specific genes would likely vary with genetic and environmental factors. If this hypothesis is correct, dysregulated APA events might be responsible for certain aspects of the phenotypes associated with ASD. Evidence supporting our hypothesis is derived from standard RNA-seq transcriptomic data but we suggest that future experiments should focus on techniques that probe the actual poly-adenylation site (3′ sequencing). To address issues arising from the use of post-mortem tissue and low numbers of heterogeneous samples affected by confounding factors (such as the age, gender and health of the individuals), carefully controlled in vitro systems will be required to model the effect of calcium signaling dysregulation in the ASD brain

Feedback methods for inverse simulation of dynamic models for engineering systems applications

Inverse simulation is a form of inverse modelling in which computer simulation methods are used to find the time histories of input variables that, for a given model, match a set of required output responses. Conventional inverse simulation methods for dynamic models are computationally intensive and can present difficulties for high-speed applications. This paper includes a review of established methods of inverse simulation,giving some emphasis to iterative techniques that were first developed for aeronautical applications. It goes on to discuss the application of a different approach which is based on feedback principles. This feedback method is suitable for a wide range of linear and nonlinear dynamic models and involves two distinct stages. The first stage involves design of a feedback loop around the given simulation model and, in the second stage, that closed-loop system is used for inversion of the model. Issues of robustness within closed-loop systems used in inverse simulation are not significant as there are no plant uncertainties or external disturbances. Thus the process is simpler than that required for the development of a control system of equivalent complexity. Engineering applications of this feedback approach to inverse simulation are described through case studies that put particular emphasis on nonlinear and multi-input multi-output models

Observational constraints on an inflation model with a running mass

We explore a model of inflation where the inflaton mass-squared is generated at a high scale by gravity-mediated soft supersymmetry breaking, and runs at lower scales to the small value required for slow-roll inflation. The running is supposed to come from the coupling of the inflaton to a non-Abelian gauge field. In contrast with earlier work, we do not constrain the magnitude of the supersymmetry breaking scale, and we find that the model might work even if squark and slepton masses come from gauge-mediated supersymmetry breaking. With the inflaton and gaugino masses in the expected range, and $\alpha = g^2/4\pi$ in the range $10^{-2}$ to $10^{-3}$ (all at the high scale) the model can give the observed cosmic microwave anisotropy, and a spectral index in the observed range. The latter has significant variation with scale, which can confirm or rule out the model in the forseeable future.Comment: Latex, 19 pages, 14 figures, uses epsf.st