On a branch-and-bound approach for a Huff-like Stackelberg location problem

Modelling the location decision of two competing firms that intend to build a new facility in a planar market can be done by a Huff-like Stackelberg location problem. In a Huff-like model, the market share captured by a firm is given by a gravity model determined by distance calculations to facilities. In a Stackelberg model, the leader is the firm that locates first and takes into account the actions of the competing chain (follower) locating a new facility after the leader. The follower problem is known to be a hard global optimisation problem. The leader problem is even harder, since the leader has to decide on location given the optimal action of the follower. So far, in literature only heuristic approaches have been tested to solve the leader problem. Our research question is to solve the leader problem rigorously in the sense of having a guarantee on the reached accuracy. To answer this question, we develop a branch-and-bound approach. Essentially, the bounding is based on the zero sum concept: what is gain for one chain is loss for the other. We also discuss several ways of creating bounds for the underlying (follower) sub-problems, and show their performance for numerical cases

A study of the antioxidant capacity of oak wood used in wine ageing and the correlation with polyphenol composition

The antioxidant capacity of oak wood used in the ageing of wine was studied by four different methods: measurement of scavenging capacity against a given radical (ABTS, DPPH), oxygen radical absorbance capacity (ORAC) and the ferric reducing antioxidant power (FRAP). Although, the four methods tested gave comparable results for the antioxidant capacity measured in oak wood extracts, the ORAC method gave results with some differences from the other methods. Non-toasted oak wood samples displayed more antioxidant power than toasted ones due to differences in the polyphenol compositon. A correlation analysis revealed that ellagitannins were the compounds mainly responsible for the antioxidant capacity of oak wood. Some phenolic acids, mainly gallic acid, also showed a significant correlation with antioxidant capacity

Self-improving Poincaré-Sobolev type functionals in product spaces

In this paper we give a geometric condition which ensures that (q, p)-Poincar´e-Sobolev inequalities are implied from generalized (1, 1)-Poincar´e inequalities related to L 1 norms in the context of product spaces. The concept of eccentricity plays a central role in the paper. We provide several (1, 1)-Poincar´e type inequalities adapted to different geometries and then show that our selfimproving method can be applied to obtain special interesting Poincar´e-Sobolev estimates. Among other results, we prove that for each rectangle R of the form R = I1 ×I2 ⊂ R n where I1 ⊂ R n1 and I2 ⊂ R n2 are cubes with sides parallel to the coordinate axes, we have that 1 w(R) Z R |f − fR| p ∗ δ,w wdx 1 p∗ δ,w ≤ c (1−δ) 1 p [w] 1 p A1,R a1(R)+a2(R) , where δ ∈ (0, 1), w ∈ A1,R, 1 p − 1 p ∗ δ,w = δ n 1 1+log[w]A1,R and ai(R) are bilinear analog of the fractional Sobolev seminorms [u]Wδ,p (Q) (See Theorem 2.18). This is a biparameter weighted version of the celebrated fractional Poincar´e-Sobolev estimates with the gain (1 − δ) 1 p due to Bourgain-Brezis-Minorescu

Wine science in the metabolomic era: wine-omics research

Las figuras y tablas que contiene el documento se localizan al final del mismo.Metabolomics approaches have proved valuable in a wide range of areas of knowledge. This review covers the latest advances in the past five years concerning wine chemistry, thanks to the development of metabolomics approaches. The combination of powerful, robust analytical techniques (NMR, LC-MS, GC-MS, FTICR, UHPLC, and CE) provides high-dimensional data that require advanced chemometric tools in order to handle these datasets appropriately and to assess the chemical composition holistically. Metabolomics studies offer the analysis of as many metabolites as possible to carry out unbiased discrimination and/or classification according to variety, origin, vintage and quality and to enable integration of all time-related metabolic changes of wine history throughout its elaborate processing to assure wine authentication and to preclude adulteration.The authors are grateful to the Spanish Ministry of Economy and Competitiveness (MINECO) (Project AGL2012-04172-C02-01) and the Comunidad Autónoma of Madrid (Spain) and European funding from FEDER program (Project S2013/ABI-3028, AVANSECAL-CM) for financial support. M.E. Alañón would like to thank Fundación Alfonso Martín Escudero for the post-doctoral fellowship awarde

Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring.

Background and Aims: Continuous glucose monitoring (CGM) devices could be useful for real-time management of diabetes therapy. In particular, CGM information could be used in real time to predict future glucose levels in order to prevent hypo-/hyperglycemic events. This article proposes a new online method for predicting future glucose concentration levels from CGM data. Methods: The predictor is implemented with an artificial neural network model (NNM). The inputs of the NNM are the values provided by the CGM sensor during the preceding 20 min, while the output is the prediction of glucose concentration at the chosen prediction horizon (PH) time. The method performance is assessed using datasets from two different CGM systems (nine subjects using the Medtronic [Northridge, CA] Guardian® and six subjects using the Abbott [Abbott Park, IL] Navigator®). Three different PHs are used: 15, 30, and 45 min. The NNM accuracy has been estimated by using the root mean square error (RMSE) and prediction delay. Results: The RMSE is around 10, 18, and 27 mg/dL for 15, 30, and 45 min of PH, respectively. The prediction delay is around 4, 9, and 14 min for upward trends and 5, 15, and 26 min for downward trends, respectively. A comparison with a previously published technique, based on an autoregressive model (ARM), has been performed. The comparison shows that the proposed NNM is more accurate than the ARM, with no significant deterioration in the prediction delay

Vector-valued operators, optimal weighted estimates and the CpC_p condition

In this paper some new results concerning the $C_p$ classes introduced by Muckenhoupt and later extended by Sawyer, are provided. In particular we extend the result to the full range expected $p>0$, to the weak norm, to other operators and to their vector-valued extensions. Some of those results rely upon sparse domination results that in some cases we provide as well. We will also provide sharp weighted estimates for vector valued extensions relying on those sparse domination results.UNLP 11/X752 and PICT 2014-1771 ANPCYT, Argentina. Juan de la Cierva - Formaci\'on 2015 FJCI-2015-24547. CONICET PIP 11220130100329CO, Argentina