A screening method based on UV–Visible spectroscopy and multivariate analysis to assess addition of filler juices and water to pomegranate juices

Consumer demand for pomegranate juice has considerably grown, during the last years, for its potential health benefits. Since it is an expensive functional food, cheaper fruit juices addition (i.e., grape and apple juices) or its simple dilution, or polyphenols subtraction are deceptively used.     

Naive probability: A mental model theory of extensional reasoning.

This article outlines a theory of naive probability. According to the theory, individuals who are unfamiliar with the probability calculus can infer the probabilities of events in an extensional way: They construct mental models of what is true in the various possibilities. Each model represents an equiprobable alternative unless individuals have beliefs to the contrary, in which case some models will have higher probabilities than others. The probability of an event depends on the proportion of models in which it occurs. The theory predicts several phenomena of reasoning about absolute probabilities, including typical biases. It correctly predicts certain cognitive illusions in inferences about relative probabilities. It accommodates reasoning based on numerical premises, and it explains how naive reasoners can infer posterior probabilities without relying on Bayes's theorem. Finally, it dispels some common misconceptions of probabilistic reasoning. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Deep cryogenic treatment of AISI 302 stainless steel: Part I – Hardness and tensile properties

The effects of deep cryogenic treatment (DCT) on the static mechanical properties of the AISI 302 austenitic stainless steel were investigated through experimental testing. The results of the tensile and hardness tests are discussed and compared to data and microstructural observations from the DCT literature concerning the same class of steel. In addition, the influence of two important treatment parameters, such as the soaking-time and the minimum temperature, is analysed through a full factorial design of experiments (DOE) and by means of a first approximation model in order to obtain confirmation and suggestions about the possible use of the DCT as a standard practice to improve the mechanical properties of stainless steels. A particular focus is given to the registered changes of the elastic modulus and of the hardness as representative measures of two different deformation mechanisms.     

Sull'ottimizzazione di un sistema idro-termo elettrico mediante utilizzazione del principio del massimo su calcolatore analogico

Sommario Il presente lavoro tratta nn'applicazione del principio del massimo all'ottimizzazione dell'esercizio di un sistema di potenza, comprendente una centrale idro-eletrica e una centrale termo-elettrica connesse fra loro dal lato rete. Dopo un breve richiamo della teoria dei processi ottimali, detta teoria viene applicata al sistema dinamico in questione di cui si esaminano in dettaglio gli aspetti connessi con il trattamento su calcolatore analogico. Il presente lavoro ha posto in luce, fra l'altro, alcune difficoltà dovute alla presenza di condizioni restrittive sul prodotto di variabili di stato e di controllo; tali difficoltà, connesse con la determinazione delle condizioni di giunzione sulle variabili aggiunte, al raggiungimento della frontiera, non sono menzionate dalla letteratura.

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This paper deals with an application of the maximum principle to the optimization of a hydro-termal system. Plants (a hydro-and a thermo-electric plant) are feeding power into a net work. After a very short survey of the theory of optimal processes, the theory has been applied to the above mentioned dynamic system. Computational aspects of the problem, connected with its treatment on an analogue computer, are examined in detail. This research points out some difficulties due to the presence of constraints on the product of state and control variables: these difficulties, connected with the determination of jump conditions on the adjoint variables when reaching the boundary, are not mentioned in the literature.

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C.C.R.-Euartom-ispra-C.E.T.I.S.     

Grass-based ruminant production methods and human bioconversion of vaccenic acid with estimations of maximal dietary intake of conjugated linoleic acids

Reports on human conjugated linoleic acids (CLAs) intake vary, and usually don't consider food production methods and vaccenic acid (VA)-induced CLA biosynthesis in humans. The aim of this review was to estimate the achievable CLA intake considering both food sources produced by feeding patterns natural to animals and human VA bioconversion. Exogenous CLA supply from milk, cheese, lamb, and beef from grass-based ruminant production methods, was calculated to be about double that of estimates based on modern production methods (respectively, from the four sources: 1.25, 1.50, 1.44, and 0.69% of total fatty acids). Using available human consumption data this resulted in an estimated achievable CLA intake (including VA bioconversion) of between 711 and 1107 mg d^?1. Intake of products from natural grass-fed ruminants leads to a several-fold higher CLA food content and, along with consideration of endogenously formed CLA from VA, results in a substantially higher CLA availability than previously estimated.     

High order harmonic generation: The role of the acceleration matrix elements and of the bound and continuum transitions

Abstract

The electromagnetic spectrum emitted by a one-dimensional atom driven by a strong laser field is obtained by use of the acceleration form and interpreted by means of few general properties of the matrix elements of the acceleration operator. We show that the emission occurs essentially in a region near the atomic core where the acceleration is significant and we investigate the role of the various emission channels arising from interference effects between transitions involving the bare atomic levels.     

Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments

Firms currently operate in highly competitive scenarios, where the environmental conditions evolve over time. Many factors intervene simultaneously and their hard-to-interpret interactions throughout the supply chain greatly complicate decision-making. The complexity clearly manifests itself in the field of inventory management, in which determining the optimal replenishment rule often becomes an intractable problem. This paper applies machine learning to help managers understand these complex scenarios and better manage the inventory flow. Building on a dynamic framework, we employ an inductive learning algorithm for setting the most appropriate replenishment policy over time by reacting to the environmental changes. This approach proves to be effective in a three-echelon supply chain where the scenario is defined by seven variables (cost structure, demand variability, three lead times, and two partners’ inventory policy). Considering four alternatives, the algorithm determines the best replenishment rule around 88% of the time. This leads to a noticeable reduction of operating costs against static alternatives. Interestingly, we observe that the nodes are much more sensitive to inventory decisions in the lower echelons than in the upper echelons of the supply chain.