Effects of seasonal changes in feeding management under part-time grazing on the evolution of the composition and coagulation properties of raw milk from ewes

Ewe raw milk composition, rennet coagulation parameters, and curd texture were monitored throughout the milk production season in 11 commercial flocks reared under a part-time grazing system. Milking season lasted from February to July. During that period, the diet of the animals shifted from indoor feeding, consisting of concentrate and forage, to an outdoor grazing diet. Lean dry matter, fat, protein, calcium, and magnesium contents increased throughout the milking season, as did rennet coagulation time, curd firmness, and curd resistance to compression. However, lean dry matter, protein content, and curd resistance to compression stabilized when sheep started to graze. Principal component analysis correlated curd resistance to compression and proteins, whereas curd firmness was highly correlated with fat content and minerals. Discriminant analysis distributed milk samples according to the feeding management. Curd firmness, fat, and magnesium turned out to be discriminant variables. Those variables reflected the evolution of the composition and coagulation parameters when fresh pasture prevailed over other feeds in the diet of the flocks. The present study shows that seasonal changes associated with feeding management influence milk technological quality and that milk of good processing quality can be obtained under part-time grazing.     

Efficiency measurement of research groups using Data Envelopment Analysis and Bayesian networks

Applications of non-parametric frontier production methods such as Data Envelopment Analysis (DEA) have gained popularity and recognition in scientometrics. DEA seems to be a useful method to assess the efficiency of research units in different fields and disciplines. However, DEA results give only a synthetic measurement that does not expose the multiple relationships between scientific production variables by discipline. Although some papers mention the need for studies by discipline, they do not show how to take those differences into account in the analysis. Some studies tend to homogenize the behaviour of different practice communities. In this paper we propose a framework to make inferences about DEA efficiencies, recognizing the underlying relationships between production variables and efficiency by discipline, using Bayesian Network (BN) analysis. Two different DEA extensions are applied to calculate the efficiency of research groups: one called CCRO and the other Cross Efficiency (CE). A BN model is proposed as a method to analyze the results obtained from DEA. BNs allow us to recognize peculiarities of each discipline in terms of scientific production and the efficiency frontier. Besides, BNs provide the possibility for a manager to propose what-if scenarios based on the relations found.     

Kinetic study of the decomposition of 2‐butanol on carbon‐based acid catalyst

The catalytic conversion of 2‐butanol on a carbon‐based acid catalyst prepared by chemical activation of olive stone with phosphoric acid was investigated. The carbon catalyst showed a considerable amount of surface phosphorus, presumably in form of phosphate groups, as revealed by XPS, despite a washing step carried out after the activation process. Conversion of 2‐butanol yields mainly dehydration products, mostly cis‐2‐butene and trans‐2‐butene with lower amounts of 1‐butene, and a very small amount of mek as dehydrogenation product. Kinetic interpretation of the experimental data was performed using two elimination mechanisms for the dehydration reaction; an E1‐mechanism (two‐step mechanism) and an E2‐mechanism (one‐step mechanism). The rate expressions derived from both models fit properly the experimental results, suggesting that probably the two mechanisms occur simultaneously. This is supported by the similar rate constant obtained for the formation of the carbocation and the olefins in the E1 and E2 mechanisms, respectively. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

An analysis of the key role of human and technological development in the smart specialization of smart European regions

ABSTRACT

The Europe 2020 development strategy prioritizes the so-called Smart Regions, reflecting the European Commission's commitment to geographical ‘specialization.’ Accordingly, the European regions have developed innovation strategies for smart specialization. A key element in these development strategies is the technological factor, which is clearly influenced by the level of human development in the region. This article analyses the convergence between citizens’ capacities and technological development in a region. Specifically, we analyse 129 NUTS 2 regions in Europe, using official data provided by Eurostat. To measure human development, this article proposes a Smart Human Index based on a synthetic indicator incorporating three dimensions; in addition, we use two dimensions to construct an indicator of regional technological development. The results show that a region's technological capacity clearly depends on its inhabitants’ degree of formal education, while their use of technologies depends on the citizens’ degree of social openness and cultural level.     

Hopfield-K-Means clustering algorithm: A proposal for the segmentation of electricity customers

Customer classification aims at providing electric utilities with a volume of information to enable them to establish different types of tariffs. Several methods have been used to segment electricity customers, including, among others, the hierarchical clustering, Modified Follow the Leader and K-Means methods. These, however, entail problems with the pre-allocation of the number of clusters (Follow the Leader), randomness of the solution (K-Means) and improvement of the solution obtained (hierarchical algorithm). Another segmentation method used is Hopfield's autonomous recurrent neural network, although the solution obtained only guarantees that it is a local minimum. In this paper, we present the Hopfield-K-Means algorithm in order to overcome these limitations. This approach eliminates the randomness of the initial solution provided by K-Means based algorithms and it moves closer to the global optimun. The proposed algorithm is also compared against other customer segmentation and characterization techniques, on the basis of relative validation indexes. Finally, the results obtained by this algorithm with a set of 230 electricity customers (residential, industrial and administrative) are presented.     

Reductive cleavage of chlorine from 6-chloronicotinic acid on mercury electrodes

This paper presents polarographic (direct current, dc, and differential pulse, DP) and voltammetric (linear-sweep cyclic voltammetry) studies on the electroreduction of 6-chloronicotinic acid (6CNA) on mercury electrodes. In order to obtain the dissociation constants of 6CNA, UV–vis spectra were recorded as a function of pH. pK values of −0.80 ± 0.05 (–COOH group) and 3.2 ± 0.1 (pyridinic nitrogen) were obtained. The electrochemical studies were performed in the acidity range 6 M H₂SO₄ to pH 8. Above the last pH value no signals were obtained. Electrolysis made at potentials corresponding to the limiting current of the first wave indicates that there is a reductive cleavage of chlorine from the molecule. This was confirmed by dc and DP polarografic results and also by voltammetric results. Kinetic parameters such as Tafel slopes and electrochemical reaction orders have been determined at potentials corresponding to the foot of the waves. From these results, together with those obtained by cyclic voltammetry, a reaction pathway is proposed, in which the rate-determining step of the process is the release of a chloride ion from the radical formed after the uptake of a H⁺ ion and an electron.     

Nanoplates forced alignment of multi-walled carbon nanotubes in alumina composite with high strength and toughness

Although the strengthening and toughening effects on ceramic composites are expected to be maximized by alignment of multi-walled carbon nanotubes (MWCNTs) in matrices, this concept has been rarely realized in practice due to the lack of convenient processing strategy. Here, the alignment of MWCNTs in alumina composite can be readily obtained by using α-Al₂O₃ nanoplates as raw powder. With the assistance of vacuum filtration and pressure in sintering, the highly aligned MWCNTs in alumina matrix are formed in in-plane direction. Accordingly, the strength and toughness in 1.5 wt% MWCNTs/alumina composite are improved by 58 % and 66 % with respect to monolithic alumina, respectively. Transmission electron microscopy observation reveals that the MWCNTs under great compressive residual stress are mainly embedded inside the grains, leading to much stronger grain boundaries. Meanwhile, the toughening effect is mainly attributed to the highly energy dissipating bridging and pullout, owing to the very effective load transfer.     

Lysyl oxidase from jumbo squid (Dosidicus gigas) muscle: purification and partial characterization

Lysyl oxidase (LOX; E.C.1.4.3.13) was purified from jumbo squid muscle (Dosidicus gigas) with 1900‐fold and yield 1.9%, and characterized for the first time. The purification procedure consisted of fractionation with urea and a combination of size‐exclusion and anion‐exchange chromatography. The enzyme had a molecular weight of 32 kDa, as estimated by SDS‐PAGE. Using a specific LOX substrate (1,5‐diaminopentane), its optimum activity was determined at pH 8.2 and 65 °C. Activation energy (E_a) of the enzyme was 69.94 kJ K^?1 mol^?1. The enzyme was strongly inhibited by β‐aminopropionitrile fumarate (BAPN), a specific LOX inhibitor. Moreover, purified LOX was able to work at different temperatures (20–90 °C) at pH 8.2. Although further research is needed, the results from this work suggest that based on LOX activity, this enzyme may be of practical use in preventing textural changes in jumbo squid during storage or processing.     

Lightfastness assessment of Levantine rock art by means of microfading spectrometry

The documentation of archeological sites requires the adoption of non‐destructive techniques to safeguard the unique legacy coming from prehistoric periods. This article tackles the assessment of lightfastness properties on a rock art site to determine the behavior of motif's color deterioration over time in Remígia Cave, Castellón (Spain), which is considered part of a UNESCO World Heritage Site. The measurements were performed using a microfade testing device to analyze the spectral characteristics and the aging properties of the colorant system and various substrates on site. Two scenarios have been identified depending on whether the lightness (L*) parameter of the rocky substrate changes or not in relation with the painted motifs. If the substrate remains stable without any change, red motifs containing iron oxide pigments will become more visible. If the substrate becomes lighter, the pigments will experience similar changes. Therefore, the contrast between paintings and support will be considerably enhanced.