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     

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.     

A principled approach to programming with nested types in Haskell

Initial algebra semantics is one of the cornerstones of the theory of modern functional programming languages. For each inductive data type, it provides a Church encoding for that type, a build combinator which constructs data of that type, a fold combinator which encapsulates structured recursion over data of that type, and a fold/build rule which optimises modular programs by eliminating from them data constructed using the buildcombinator, and immediately consumed using the foldcombinator, for that type. It has long been thought that initial algebra semantics is not expressive enough to provide a similar foundation for programming with nested types in Haskell. Specifically, the standard folds derived from initial algebra semantics have been considered too weak to capture commonly occurring patterns of recursion over data of nested types in Haskell, and no build combinators or fold/build rules have until now been defined for nested types. This paper shows that standard folds are, in fact, sufficiently expressive for programming with nested types in Haskell. It also defines buildcombinators and fold/build fusion rules for nested types. It thus shows how initial algebra semantics provides a principled, expressive, and elegant foundation for programming with nested types in Haskell.     

SPIDER: An availability-aware framework for the service function chain placement in distributed scenarios

The network function virtualization (NFV) paradigm replaces hardware-dependent network functions by virtual network functions (VNFs) that can be deployed in commodity hardware, including legacy servers. Consequently, the use of NFV is expected to reduce operating and capital expenses, as well as improve service deployment operation and management flexibility. For many use cases, the VNFs must be visited and invoked following a specific order of execution in order to compose a complete network service, named service function chain (SFC). Nonetheless, despite the benefits from NFV and SFC virtualization technologies, their introduction must not harm network performance and service availability. On the one hand, redundancy is seen by network service planners as a mechanism well established to combat availability issues. At same time, there is a goal to optimize resource utilization in order to reduce operational expenditure. In this article, we share our experience in the design use of a framework, named SPIDER, focused on SFC placement that considers the network infrastructure condition and the required SFC availability to define the placement strategy. The SPIDER monitors the status of infrastructure nodes and links and defines which servers the VNFs should be placed on and the number of redundant replicas needed. We present a proof-of-concept of SPIDER using Kubernetes to launch the VNFs as containers. We also use Kubernetes to forward the traffic between the VNFs, composing the service chain. We perform experiments to evaluate the runtime of SPIDER and the SFC delay under different network conditions.     

Determinants of internal and external R&D offshoring: evidence from Spanish firms

This paper analyses the determinants of R&D offshoring of Spanish firms using information from the Panel of Technological Innovation. We find that being an exporter, international technological cooperation, continuous R&D engagement, applying for patents, being a foreign subsidiary, and firm size are factors that positively affect the decision to offshore R&D. In addition, we find that a lack of financing is an obstacle relatively more important for independent firms than for firms that belong to business groups. For these latter, we also obtain that the factors that influence the decision to offshore R&D differ depending on whether the firm purchases the R&D services within the group or through the market: a higher degree of importance assigned to internal sources of information for innovation as compared to market sources increases (decreases) the probability of R&D offshoring only through the group (market).     

Hybrid Nanoscopy of Hybrid Nanomaterials

The combination of complementary techniques to characterize materials at the nanoscale is crucial to gain a more complete picture of their structure, a key step to design and fabricate new materials with improved properties and diverse functions. Here it is shown that correlative atomic force microscopy (AFM) and localization‐based super‐resolution microscopy is a useful tool that provides insight into the structure and emissive properties of fluorescent β‐lactoglobulin (βLG) amyloid‐like fibrils. These hybrid materials are made by functionalization of βLG with organic fluorophores and quantum dots, the latter being relevant for the production of 1D inorganic nanostructures templated by self‐assembling peptides. Simultaneous functionalization of βLG fibers by QD655 and QD525 allows for correlative AFM and two‐color super‐resolution fluorescence imaging of these hybrid materials. These experiments allow the combination of information about the topography and number of filaments that compose a fibril, as well as the emissive properties and nanoscale spatial distribution of the attached fluorophores. This study represents an important step forward in the characterization of multifunctionalized hybrid materials, a key challenge in nanoscience.