On the formal foundations of cash management systems

[EN] Cash management aims to find a balance between what is held in cash and what is allocated in other investments in exchange for a given return. Dealing with cash management systems with multiple accounts and different links between them is a complex task. Current cash management models provide analytic solutions without exploring the underlying structure of accounts and its main properties. There is a need for a formal definition of cash management systems. In this work, we introduce a formal approach to manage cash with multiple accounts based on graph theory. Our approach allows a formal reasoning on the relation between accounts in cash management systems. A critical part of this formal reasoning is the characterization of desirable and non-desirable cash management policies. Novel theoretical results guide cash managers in the analysis of complex cash management systems.This work is partially funded by projects Logistar (H2020-769142), AI4EU (H2020-825619) and 2017 SGR 172.Salas-Molina, F.; Rodriguez-Aguilar, JA.; Pla Santamaría, D.; Garcia-Bernabeu, A. (2021). On the formal foundations of cash management systems. Operational Research. 21(2):1081-1095. https://doi.org/10.1007/s12351-019-00464-6S10811095212Baccarin S (2009) Optimal impulse control for a multidimensional cash management system with generalized cost functions. Eur J Oper Res 196(1):198–206Bollobás B (2013) Modern graph theory, vol 184. Springer, BerlinBondy JA, Murty USR (1976) Graph theory with applications, vol 290. Macmillan, LondonChartrand G, Oellermann OR (1993) Applied and algorithmic graph theory, vol 993. McGraw-Hill, New YorkConstantinides GM, Richard SF (1978) Existence of optimal simple policies for discounted-cost inventory and cash management in continuous time. Oper Res 26(4):620–636da Costa Moraes MB, Nagano MS, Sobreiro VA (2015) Stochastic cash flow management models: a literature review since the 1980s. In: Guarnieri P (ed) Decision models in engineering and management. Springer, Berlin, pp 11–28de Avila Pacheco JV, Morabito R (2011) Application of network flow models for the cash management of an agribusiness company. Comput Ind Eng 61(3):848–857Golden B, Liberatore M, Lieberman C (1979) Models and solution techniques for cash flow management. Comput Oper Res 6(1):13–20Gormley FM, Meade N (2007) The utility of cash flow forecasts in the management of corporate cash balances. Eur J Oper Res 182(2):923–935Gregory G (1976) Cash flow models: a review. Omega 4(6):643–656Makridakis S, Wheelwright SC, Hyndman RJ (2008) Forecasting methods and applications. Wiley, New YorkRighetto GM, Morabito R, Alem D (2016) A robust optimization approach for cash flow management in stationery companies. Comput Ind Eng 99:137–152Salas-Molina F (2017) Risk-sensitive control of cash management systems. Oper Res. https://doi.org/10.1007/s12351-017-0371-0Salas-Molina F, Pla-Santamaria D, Rodriguez-Aguilar JA (2018) A multi-objective approach to the cash management problem. Ann Oper Res 267(1):515–529Srinivasan V, Kim YH (1986) Deterministic cash flow management: state of the art and research directions. Omega 14(2):145–166Valiente G (2013) Algorithms on trees and graphs. Springer, Berli

miR-494-3p is a novel tumor driver of lung carcinogenesis

Lung cancer is the leading cause of tumor-related death worldwide and more efforts are needed to elucidate lung carcinogenesis. Here we investigated the expression of 641 miRNAs in lung tumorigenesis in a K-Ras(+/LSLG12Vgeo);RERTn(ert/ert) mouse model and 113 human tumors. The conserved miRNA cluster on chromosome 12qF1 was significantly and progressively upregulated during murine lung carcinogenesis. In particular, miR-494-3p expression was correlated with lung cancer progression in mice and with worse survival in lung cancer patients. Mechanistically, ectopic expression of miR-494-3p in A549 lung cancer cells boosted the tumor-initiating population, enhanced cancer cell motility, and increased the expression of stem cell-related genes. Importantly, miR-494-3p improved the ability of A549 cells to grow and metastasize in vivo, modulating NOTCH1 and PTEN/PI3K/AKT signaling.Overall, these data identify miR-494-3p as a key factor in lung cancer onset and progression and possible therapeutic target