Synthesis and physicochemical characterization of a well-defined poly(butadiene 1,3)-block-poly(dimethylsiloxane) copolymer

For the first time, order-order and order-disorder transitions were detected and characterized in a model diblock copolymer of poly(butadiene-1,3) and poly(dimethylsiloxane) (PB-b-PDMS). This model PB-b-PDMS copolymer was synthesized by the sequential anionic polymerization (high vacuum techniques) of butadiene 1,3 (B) and hexamethylciclotrisiloxane (D₃), and subsequently characterized by nuclear magnetic resonance (¹H and ¹³C NMR), size exclusion chromatography (SEC), Fourier Transform infrared spectroscopy (FTIR), Small-Angle X-ray scattering (SAXS) and rheology. SAXS combined with rheological experiments shows that the order-order and order-disorder transitions are thermoreversible. This fact indicates that the copolymer has sufficient mobility at the timescale and at the temperatures of interest to reach their equilibrium morphologies.     

Towards efficient partial evaluation in logic programming

Partial evaluation is a symbolic manipulation technique used to produce efficient algorithms when part of the input to the algorithm is known. Other applications of partial evaluators such as universal compilation and compiler generation are also known to be possible. A partial evaluator receives as input a program and partially known input to that program, and outputs a residual program which should run at least as efficient as the input program with restricted input. In this paper we study the case where both the input and residual programs are logic programs, being the partial evaluator itself a logic program. Up to now, partial evaluators have failed to process large “non=toy” examples. Here we present extensions to partial evaluators whic will allow us to produce more efficient residual programs using less computing resources, during partial evaluation. First, the introduced extensions allow the processing of large examples, which is not possible with the previous techniques. This is now possible since the extensions use less CPU time and memory consumption during the partial evaluation process. Second, the extended partial evaluator produces smaller residual programs, producing important CPU time optimizing effects. With the standard techniques, a partial evaluator will most probably act as a pessimizer, not as an optimizer. Examples are given.     

The Role of Circulating Biomarkers in Peripheral Arterial Disease

Peripheral arterial disease (PAD) of the lower extremities is a chronic illness predominantly of atherosclerotic aetiology, associated to traditional cardiovascular (CV) risk factors. It is one of the most prevalent CV conditions worldwide in subjects >65 years, estimated to increase greatly with the aging of the population, becoming a severe socioeconomic problem in the future. The narrowing and thrombotic occlusion of the lower limb arteries impairs the walking function as the disease progresses, increasing the risk of CV events (myocardial infarction and stroke), amputation and death. Despite its poor prognosis, PAD patients are scarcely identified until the disease is advanced, highlighting the need for reliable biomarkers for PAD patient stratification, that might also contribute to define more personalized medical treatments. In this review, we will discuss the usefulness of inflammatory molecules, matrix metalloproteinases (MMPs), and cardiac damage markers, as well as novel components of the liquid biopsy, extracellular vesicles (EVs), and non-coding RNAs for lower limb PAD identification, stratification, and outcome assessment. We will also explore the potential of machine learning methods to build prediction models to refine PAD assessment. In this line, the usefulness of multimarker approaches to evaluate this complex multifactorial disease will be also discussed.     

Scheduling algorithms for fault-tolerance in hard-real-time systems

Many time-critical applications require predictable performance in the presence of failures. This paper considers a distributed system with independent periodic tasks which can checkpoint their state on some reliable medium in order to handle failures. The problem of preemptively scheduling a set of such tasks is discussed where every occurrence of a task has to be completely executed before the next occurrence of the same task can start. Efficient scheduling algorithms are proposed which yield sub-optimal schedules when there is provision for fault-tolerance. The performance of the solutions proposed is evaluated in terms of the number of processors and the cost of the checkpoints needed. Moreover, analytical studies are used to reveal interesting trade-offs associated with the scheduling algorithms.This work has been supported by grants from the Italian Ministero dell'Università e della Ricerca Scientifica e Tecnologica and the Consiglio Nazionale delle Ricerche-Progetto Finalizzato Sistemi Informatici e Calcolo Parallelo.     

A Novel Magnetic Hardening Mechanism for Nd-Fe-B Permanent Magnets Based on Solid-State Phase Transformation

Permanent magnets based on neodymium-iron-boron (Nd-Fe-B) alloys provide the highest performance and energy density, finding usage in many high-tech applications. Their magnetic performance relies on the intrinsic properties of the hard-magnetic Nd₂Fe₁₄B phase combined with control over the microstructure during production. In this study, a novel magnetic hardening mechanism is described in such materials based on a solid-state phase transformation. Using modified Nd-Fe-B alloys of the type Nd₁₆Fe_bal-x-y-zCo_xMo_yCu_zB₇ for the first time it is revealed how the microstructural transformation from the metastable Nd₂Fe₁₇B_x phase to the hard-magnetic Nd₂Fe₁₄B phase can be thermally controlled, leading to an astonishing increase in coercivity from ≈200 kAm⁻¹ to almost 700 kAm⁻¹. Furthermore, after thermally treating a quenched sample of Nd₁₆Fe₅₆Co₂₀Mo₂Cu₂B₇, the presence of Mo leads to the formation of fine FeMo₂B₂ precipitates, in the range from micrometers down to a few nanometers. These precipitates are responsible for the refinement of the Nd₂Fe₁₄B grains and so for the high coercivity. This mechanism can be incorporated into existing manufacturing processes and can prove to be applicable to novel fabrication routes for Nd-Fe-B magnets, such as additive manufacturing.     

Nanocrystalline Nd–Fe–B Anisotropic Magnets by Flash Spark Plasma Sintering

Flash spark plasma sintering (flash SPS) is an attractive method to obtain Nd–Fe–B magnets with anisotropic magnetic properties when starting from melt-spun powders. Compared to the benchmark processing route via hot pressing with subsequent die upsetting, flash SPS promises electroplasticity as an additional deformation mechanism and reduced tool wear, while maximizing magnetic properties by tailoring the microstructure—fully dense and high texture. A detailed parameter study is conducted to understand the influence of Flash SPS parameters on the densification and magnetic properties of commercial MQU-F powder. It is revealed that the presintering conditions and preheating temperature before applying the power pulse play a major role for tailoring grain size and texture in the case of hot deformation via Flash SPS. Detailed microstructure and magnetic domain evaluation disclose the texture enhancement with increasing flash SPS temperature at the expense of coercivity. The best compromise between remanence and coercivity (1.37 T and 1195 kA m⁻¹, respectively) is achieved through a combination of presintering at 500 °C for 120 s and preheating temperature of 600 °C, resulting in a magnet with energy product (BH)_max of 350 kJm⁻³. These findings show the potential of flash SPS to obtain fully dense anisotropic nanocrystalline magnets with high magnetic performance.     

P-Bandwidth Priority Queues on Reconfigurable Tree of Meshes

This paper shows a parallel implementation of a priority queue with bandwidthPand maximum sizenPby means of a network with reconfigurable buses. The proposed solution is based on a tree of meshes architecture ofO(nP²) processors andO(Plogn) maximum subbus length. The computational times required by the operations of a priority queue with bandwidthPareO(1) for all the operations, using the unit-time delay model for broadcasting, while they areO(1) for MIN andO(logP+ log logn) for both DELETEMIN and INSERT, using the log-time delay model. The proposed network can be laid out in a classical H-shaped manner to occupyO(nP²) area in the VLSI model. WhenP=O(1), the required area is optimal and, using the unit-time delay model, the resultingAT²is also optimal. The paper presents also a very simple and efficient way of merging two sorted sequences on a reconfigurable mesh, which is used in the implementation of the priority queue operations.     

Industrial Plant for Olive Mill Wastewater from Two-Phase Treatment by Chemical Oxidation

Olive-oil production generates high and variable amounts of wastewaters from the olives and olive-oil washing (OMW), resulting to great environmental impact. These waters are normally stored in large holding ponds for evaporation during the summer. The present study examines the chemical-oxidation process using ferric chloride catalyst for the activation of H2O2 (Fenton reaction). Tests have been made on an industrial scale. The final average value of chemical oxygen demand (COD) was close to 371?mg?O2?L?1 (%CODremoval = 86%, CODinitial = 2684?mg?O2?L?1), and the water produced can be used for irrigation or can be discharged directly into the municipal wastewater system for tertiary treatment.     

Contour-based focus of attention mechanism to speed up object detection and labeling in 3D scenes

In this paper, a contour-based focus of attention approach is presented. Fast to compute, contour based features are extracted from 3D scenes and matched to model parts of objects. Local reference frames associated with the features induce a translation and rotation, resulting in a vote being cast for the presence of the object in a certain position within the scene. In these positions, HoG features are extracted and SVM classification is applied. Detection results and computation times are compared to those corresponding to a sliding window approach.     

Structural and electrical properties of grain boundaries in Ce0.85Gd0.15O1.925 solid electrolyte modified by addition of transition metal ions

In this work we present studies on applicability of transition metal additives as sintering and electrical conductivity aids for cerium gadolinium oxide electrolyte. The nanosized Ce_0.85Gd_0.15O_1.925 powder obtained by coprecipitation method was modified with Cr³⁺, Fe³⁺, Ni²⁺ or Cu²⁺ ions. Using high-intensity high-resolution X-ray powder diffraction data we have determined that Cr, Fe and Ni ions do not incorporate into the cerium gadolinium oxide surface or bulk when sintered at 1300 °C, but react with Gd ions to form Cr_0.9Gd_0.1O, GdFeO₃ and GdNiO₃ phases, while Cu incorporates in the material up to 0.7 mol% with a significant fraction of remaining material showing poorly crystalline CuO phase. The nanosized Ce_0.85Gd_0.15O_1.925 material shows already improved sintering properties than previous reports but full sintering is not achieved below 1300 °C, however Cr, Fe and mainly Cu impregnation allows full sintering at 1300 °C. 0.5 mol% Ni impregnated material sintered at 1500 °C shows enhanced grain boundary conductivity that probably indicates that Ni incorporates into Ce_0.84Gd_0.15O_1.925 above 1300 °C. The global results indicate, however, that optimization of ceria microstructure is at least of equal importance for sinterability and grain boundary conductivity than impregnation of the material with transition metal ions.