Fatty acid esters with short‐chain alcohols in two‐phase olive pomace oils

Two‐phase decanter olive pomace (TPOP) is the by‐product of a centrifugation system, used to produce olive oil, that separates olive oil and moist pomace. The water content in these olive pomaces is about 70%, while it was 45‐50% in the olive pomace stemming from three‐phase systems (oil, water, and pomace) and 30% in the old press system. The aim of this work is focused on quantification and changes undergone during olive pomace storage in ponds of esters of fatty acids with short‐chain linear alcohols, which can be considered as a refining loss. The results indicate that oil deterioration increases very rapidly, in particular when oil is extracted from the TPOP surface. Special attention should be paid to the storage of TPOP, establishing a maximum of 2 months in all cases.     

Manganese ferrite nanoparticles synthesized through a nanocasting route as a highly active Fenton catalyst

Spinel ferrite MnFe₂O₄ nanoparticles were synthesized by means of a nanocasting technique using a low-cost mesoporous silica gel as a hard template. The magnetic nanoparticles, of <10 nm diameter and with a surface area of around 100 m²/g, were tested as a heterogeneous Fenton catalyst for the decomposition of hydrogen peroxide under neutral and basic conditions. This catalyst shows a much higher activity than previous heterogeneous catalysts reported in the literature, which is mainly ascribed to its small particle size. Furthermore, the magnetic catalyst can be easily separated from the reaction medium by means of an external magnetic field. The effects of residual silica and the purity of the catalyst (hematite formation) on catalytic activity have been studied and correlated. The results obtained show this catalyst to be a suitable candidate for the removal of pollutants in wastewaters by means of the Fenton heterogeneous reaction.     

Separation and determination of mono-, Di-, and triglycerides in monoglyceride concentrates

Summary Monoglyceride concentrates are quantitatively separated into mono-, di-, and triglyceride components on silica gel columns by an adsorption chromatographic technique. The separated glycerides are determined gravimetrically. The adsorption on silica gel is dependent on the number of hydroxyl groups in the molecule, and the influence of unsaturation and chain length is minimized. Combinations of benzene and ethyl ether are used for elution, thus preventing isomerization, which frequently results when polar solvents such as alcohols are used. The procedure for the chromatographic separation is simple and straightforward. The equipment used is easily obtainable. The silica gel adsorbent requires only adjustment of its water content before use. Mixtures of both saturated and unsaturated glycerides and those having different fatty acid chain length have been separated. Known mixtures have also been analyzed. For a known mixture containing 15% tripalmitin, 45% distearin, and 38% monopalmitin the average deviations from the calculated values were 0.4%, 0.2%, and 0.6%, respectively     

Effect of elemental sulfur in the crosslinking reaction of poly(vinyl chloride) with tetramethyl thiuram disulfide

The effect of elemental sulfur (S₈) and tetramethyl thiuram disulfide (TMTD) on the chemical crosslinking of PVC is studied. The tensile strength, elongation at break, and gel content of crosslinked and uncrosslinked PVC molded samples, cured at different times in hot air, are evaluated. It was found that crosslinking PVC with TMTD improves its mechanical properties, and adding S₈ produces a slight improvement. Also, the S₈ presence accelerated the PVC/TMTD crosslinking reaction when the crosslinking reaction was carried out under shear forces, but not when the curing was done in hot air, where the S₈ retards the process.     

Evaluation of messaging middleware for high-performance cloud computing

Cloud computing is posing several challenges, such as security, fault tolerance, access interface singularity, and network constraints, both in terms of latency and bandwidth. In this scenario, the performance of communications depends both on the network fabric and its efficient support in virtualized environments, which ultimately determines the overall system performance. To solve the current network constraints in cloud services, their providers are deploying high-speed networks, such as 10 Gigabit Ethernet. This paper presents an evaluation of high-performance computing message-passing middleware on a cloud computing infrastructure, Amazon EC2 cluster compute instances, equipped with 10 Gigabit Ethernet. The analysis of the experimental results, confronted with a similar testbed, has shown the significant impact that virtualized environments still have on communication performance, which demands more efficient communication middleware support to get over the current cloud network limitations.     

Using k-nn and discriminant analyses to classify rain forest types in a Landsat TM image over northern Costa Rica

Conservation and land use planning in humid tropical lowland forests urgently need accurate remote sensing techniques to distinguish among floristically different forest types. We investigated the degree to which floristically and structurally defined Costa Rican lowland rain forest types can be accurately discriminated by a non-parametric k nearest neighbors (k-nn) classifier or linear discriminant analysis. Pixel values of Landsat Thematic Mapper (TM) image and Shuttle Radar Topography Mission (SRTM) elevation model extracted from segments or from 5 × 5 pixel windows were employed in the classifications. 104 field plots were classified into three floristic and one structural type of forest (regrowth forest). Three floristically defined forest types were formed through clustering the old-growth forest plots (n = 52) by their species specific importance values. An error assessment of the image classification was conducted via cross-validation and error matrices, and overall percent accuracy and Kappa scores were used as measures of accuracy. Image classification of the four forest types did not adequately distinguish two old-growth forest classes, so they were merged into a single forest class. The resulting three forest classes were most accurately classified by the k-nn classifier using segmented image data (overall accuracy 91%). The second best method, with respect to accuracy, was the k-nn with 5 × 5 pixel windows data (89% accuracy), followed by the canonical discriminant analysis using the 5 × 5 pixel window data (86%) and the segment data (82%). We conclude the k-nn classifier can accurately distinguish floristically and structurally different rain forest types. The classification accuracies were higher for the k-nn classifier than for the canonical discriminant analysis, but the differences in Kappa scores were not statistically significant. The segmentation did not increase classification accuracy in this study.     

A constant-time dynamic storage allocator for real-time systems

Dynamic memory allocation has been used for decades. However, it has seldom been used in real-time systems since the worst case of spatial and temporal requirements for allocation and deallocation operations is either unbounded or bounded but with a very large bound. In this paper, a new allocator called TLSF (Two Level Segregated Fit) is presented. TLSF is designed and implemented to accommodate real-time constraints. The proposed allocator exhibits time-bounded behaviour, O(1), and maintains a very good execution time. This paper describes in detail the data structures and functions provided by TLSF. We also compare TLSF with a representative set of allocators regarding their temporal cost and fragmentation. Although the paper is mainly focused on timing analysis, a brief study and comparative analysis of fragmentation incurred by the allocators has been also included in order to provide a global view of the behaviour of the allocators. The temporal and spatial results showed that TLSF is also a fast allocator and produces a fragmentation close to that caused by the best existing allocators.

Optimal infinite scheduling for multi-priced timed automata

This paper is concerned with the derivation of infinite schedules for timed automata that are in some sense optimal. To cover a wide class of optimality criteria we start out by introducing an extension of the (priced) timed automata model that includes both costs and rewards as separate modelling features. A precise definition is then given of what constitutes optimal infinite behaviours for this class of models. We subsequently show that the derivation of optimal non-terminating schedules for such double-priced timed automata is computable. This is done by a reduction of the problem to the determination of optimal mean-cycles in finite graphs with weighted edges. This reduction is obtained by introducing the so-called corner-point abstraction, a powerful abstraction technique of which we show that it preserves optimal schedules. This work has been mostly done while visiting CISS at Aalborg University in Denmark and has been supported by CISS and by ACI Cortos, a program of the French Ministry of Research.