Consumers preferences for dairy-alternative beverage using home-scan data in Catalonia

The changing lifestyles and the growing health concerns towards the negative impact of the saturated fatty acids originating from animals has increased consumers’ preferences for dairy-alternative products. These products belong to the food and beverage classification that is similar to certain types of dairy-based products in terms of texture and flavor, and has similar nutritional benefits. In this context, we seek to identify the willingness to pay (WTP) for the most important attributes that consumers take into account when purchasing the dairy-alternative drinks. A revealed preference discrete choice experiment was carried out using home-scan data belonging to ©Kantar Worldpanel (Barcelona, Spain) regarding the consumption of dairy-alternative drinks in Catalonia (Spain) in 343 households. Furthermore, factors that affect the purchasing frequency of this type of product were analyzed through the Poisson and negative binomial models. Results showed that price was the major driving factor, followed by the original non-dairy beverage flavor attribute. The original non-dairy beverage flavor compared to other added ingredients and tastes showed higher WTP when purchasing the non-dairy alternative. Marketing strategies should promote products by focusing on the “original” and “pure” version of the product without additional ingredients, or through reduction of the undesirable compounds if they exist in these kinds of beveragesPostprint (published version

Policy impact on technical efficiency of Spanish olive farms located in Less Favored Area

Most of Spanish olive farms are concentrated in Less-Favoured Areas (LFA) with the majority of producer areas are under Objective 1 of the EU Regional Policy. The EU has long recognized such distinctive characteristics of those holdings with a specific support measures aiming to prevent the abandonment of olive groves as well as to support sustainable development of this sector. The main objective of this study is to evaluate the impact of LFA payment on the olive farms technical efficiency. Two sample farms located in LFA (63 farms receiving LFA payment support and 99 farms do not) have been observed from 2000 to 2004. A stochastic frontier production has been used. Results indicate that LFA payment, age of manager, tenure regimes of land, workforce composition and farm size affect efficiency levels. The LFA payment coefficient indicates a significant negative impact on the technical efficiency of Spanish olive farms. The farms that not receive the LFA payment has a technical efficiency rate 0.15 percentage units upper compared to those that receive this payment. Thus, the payment policy could decreases farms technical efficiency which could represents a handicap for farms economic survival and its persistence in the long term period.LFA payment, olive farm, technical efficiency, Production Economics, Productivity Analysis, Q180, D210,

A new Backdoor Attack in CNNs by training set corruption without label poisoning

Backdoor attacks against CNNs represent a new threat against deep learning systems, due to the possibility of corrupting the training set so to induce an incorrect behaviour at test time. To avoid that the trainer recognises the presence of the corrupted samples, the corruption of the training set must be as stealthy as possible. Previous works have focused on the stealthiness of the perturbation injected into the training samples, however they all assume that the labels of the corrupted samples are also poisoned. This greatly reduces the stealthiness of the attack, since samples whose content does not agree with the label can be identified by visual inspection of the training set or by running a pre-classification step. In this paper we present a new backdoor attack without label poisoning Since the attack works by corrupting only samples of the target class, it has the additional advantage that it does not need to identify beforehand the class of the samples to be attacked at test time. Results obtained on the MNIST digits recognition task and the traffic signs classification task show that backdoor attacks without label poisoning are indeed possible, thus raising a new alarm regarding the use of deep learning in security-critical applications

A Game-Theoretic Framework for Optimum Decision Fusion in the Presence of Byzantines

Optimum decision fusion in the presence of malicious nodes - often referred to as Byzantines - is hindered by the necessity of exactly knowing the statistical behavior of Byzantines. By focusing on a simple, yet widely studied, set-up in which a Fusion Center (FC) is asked to make a binary decision about a sequence of system states by relying on the possibly corrupted decisions provided by local nodes, we propose a game-theoretic framework which permits to exploit the superior performance provided by optimum decision fusion, while limiting the amount of a-priori knowledge required. We first derive the optimum decision strategy by assuming that the statistical behavior of the Byzantines is known. Then we relax such an assumption by casting the problem into a game-theoretic framework in which the FC tries to guess the behavior of the Byzantines, which, in turn, must fix their corruption strategy without knowing the guess made by the FC. We use numerical simulations to derive the equilibrium of the game, thus identifying the optimum behavior for both the FC and the Byzantines, and to evaluate the achievable performance at the equilibrium. We analyze several different setups, showing that in all cases the proposed solution permits to improve the accuracy of data fusion. We also show that, in some instances, it is preferable for the Byzantines to minimize the mutual information between the status of the observed system and the reports submitted to the FC, rather than always flipping the decision made by the local nodes as it is customarily assumed in previous works

A Message Passing Approach for Decision Fusion in Adversarial Multi-Sensor Networks

We consider a simple, yet widely studied, set-up in which a Fusion Center (FC) is asked to make a binary decision about a sequence of system states by relying on the possibly corrupted decisions provided by byzantine nodes, i.e. nodes which deliberately alter the result of the local decision to induce an error at the fusion center. When independent states are considered, the optimum fusion rule over a batch of observations has already been derived, however its complexity prevents its use in conjunction with large observation windows. In this paper, we propose a near-optimal algorithm based on message passing that greatly reduces the computational burden of the optimum fusion rule. In addition, the proposed algorithm retains very good performance also in the case of dependent system states. By first focusing on the case of small observation windows, we use numerical simulations to show that the proposed scheme introduces a negligible increase of the decision error probability compared to the optimum fusion rule. We then analyse the performance of the new scheme when the FC make its decision by relying on long observation windows. We do so by considering both the case of independent and Markovian system states and show that the obtained performance are superior to those obtained with prior suboptimal schemes. As an additional result, we confirm the previous finding that, in some cases, it is preferable for the byzantine nodes to minimise the mutual information between the sequence system states and the reports submitted to the FC, rather than always flipping the local decision

Characterization of antibodies to coagulation factor VIII

http://www.ester.ee/record=b4338686~S58*es

Effects of policy instruments on farm investments and production decisions in the Spanish cop sector

Our paper asses the impacts of the partially decoupled (PD) scheme, implemented during the 1990s and first half of the 2000s in the framework of the Common Agricultural Policy (CAP), on on-farm investment as well as on other production decisions. The Spanish COP sector was taken as a case study due to its economic and political relevance. The empirical analysis is applied on farm-level data from the Farm Accountancy Data Network (FADN), observed from 2000 to 2004, based on. We use a reduced-form application of the dual model of investment under uncertainty and a system of censored and non censored equations is estimated. PD payments are found to increase short-run production and to generate a statically significant increase in the investment in farm assets. Results also show the importance of assessing the effects of PD payments in a dynamic framework as the one applied in this paper.farm investments, Common Agricultural Policy, decoupling, production., Agricultural and Food Policy, Food Consumption/Nutrition/Food Safety,

Claiming the diaspora: Russia's compatriot policy and its reception by Estonian-Russian population

Nearly a decade ago Russia took a turn from declarative compatriot protection discourse to a more programmatic approach consolidating large Russophone1 populations abroad and connecting them more with Russia by employing the newly emerged concept of Russkiy Mir as a unifying factor for Russophones around the world. Most academic debates have since focused on analyzing Russkiy Mir as Russia’s soft power tool. This article looks at Russia’s compatriot policy from the perspective of the claimed compatriot populations themselves. It is a single empirical in - depth case study of Russia’s compatriot policy and its reception by the Russian-speaking community in Estonia. The focus is on Russia’s claims on the Russophone population of Estonia and the reactions and perceptions of Russia’s ambitions by the Estonian-Russians themselves