Determination of chloride diffusivity through partially saturated Portland cement concrete by a simplified procedure

A recently proposed methodology for measuring the diffusion coefficient of chloride ions through concrete partially saturated with water, has been applied to five high-early-strength Portland cement mortars. The method is based on putting solid NaCl in contact with the concrete surface during the diffusion test. The results obtained indicate a strong dependence of the diffusion coefficient on the water saturation degree. The ionic diffusivities through these mortars are higher than those obtained with the same approach for five pozzolanic cement mortars of similar compositions. It has been also shown that the proposed test methodology and a different one based on the interaction of HCl(g) with the tested concrete surface, can yield comparable results. The D values obtained are of similar magnitude, and the same type of dependence on the water saturation degree is found through both methods, when applied to similar Portland cement concrete mixes with cement content of about 350 kg/m3 and water/cement ratios between 0.5 and 0.6

A hybrid metaheuristic with learning for a real supply chain scheduling problem

In recent decades, research on supply chain management (SCM) has enabled companies to improve their environmental, social, and economic performance. This paper presents an industrial application of logistics that can be classified as an inventory-route problem. The problem consists of assigning orders to the available warehouses. The orders are composed of items that must be loaded within a week. The warehouses provide an inventory of the number of items available for each day of the week, so the objective is to minimize the total transportation costs and the costs of producing extra stock to satisfy the weekly demand. To solve this problem a formal mathematical model is proposed. Then a hybrid approach that involves two metaheuristics: a greedy randomized adaptive search procedure (GRASP) and a genetic algorithm (GA) is proposed. Additionally, a meta-learning tuning method is incorporated into our hybridized approach, which yields better results but with a longer computation time. Thus, the trade-off of using it is analyzed. An extensive evaluation was carried out over realistic instances provided by an industrial partner. The proposed technique was evaluated and compared with several complete and incomplete solvers from the state of the art (CP Optimizer, Yuck, OR-Tools, etc.). The results showed that our hybrid metaheuristic outperformed the behavior of these well-known solvers, mainly in large-scale instances (2000 orders per week). This hybrid algorithm provides the company with a powerful tool to solve its supply chain management problem, delivering significant economic benefits every week.The authors gratefully acknowledge the financial support of the European Social Fund (Investing In Your Future), the Spanish Ministry of Science (project PID2021-125919NB-I00), and valgrAI - Valencian Graduate School and Research Network of Artificial Intelligence and the Generalitat Valenciana, Spain, and co-funded by the European Union. The authors also thank the industrial partner Logifruit for its support in the problem specification and the permission to generate randomized data for evaluating the proposed algorithm

Early colonization of sessile megabenthos on electrolytic carbonated structures (Alicante's harbor, Western Mediterranean)

Biofouling in different artificial substrata was done to determine the differences in biofouling assemblages among different substrates. However, studies on biofouling on natural substrates like electrolytic carbonated ones are lacking. These substrates have a great potential for coral reef restoration in tropical areas and for biofilter construction. Thus, this study was done to examine the colonization of sessile macrofouling in the port of Alicante (SE Spain, Western Mediterranean) on two types of substrata: electrolytic carbonated and bare steel (as control) over three months of immersion (October 2019–January 2020). The community diversity was studied through different biotic parameters and abundance of assemblages, and preference of organisms according to their status and functional group (active filter feeders). Univariate and multivariate analyses (PERMANOVA and SIMPER) were also done to examine the differences between carbonate and control substrata. The carbonated substrate had a more structured community and higher abundance, recruitment, and diversity indexes than the bare steel. Moreover, filter feeders (Porifera, Bivalvia, and Ascidiacea) were more abundant, and most of them only appeared in the carbonated substrate. These results show the potential of carbonated structures as biofilters.This study forms part of the ThinkInAzul program and was supported by Ministerio de Ciencia e Innovación with funding from European Union NextGenerationEU (PRTRC17.I1) and by Generalitat Valenciana (THINKINAZUL/2021/014)

Robustness and stability in Constraint Programming under dynamism and uncertainty

Many real life problems that can be solved by constraint programming, come from uncertain and dynamic environments. Because of the dynamism, the original problem may change over time, and thus the solution found for the original problem may become invalid. For this reason, dealing with such problems has become an important issue in the fields of constraint programming. In some cases, there exist extant knowledge about the uncertain and dynamic environment. In other cases, this information is fragmentary or unknown. In this paper, we extend the concept of robustness and stability for Constraint Satisfaction Problems (CSPs) with ordered domains, where only limited assumptions need to be made as to possible changes. We present a search algorithm that searches for both robust and stable solutions for CSPs of this nature. It is well-known that meeting both criteria simultaneously is a desirable objective for constraint solving in uncertain and dynamic environments. We also present compelling evidence that our search algorithm outperforms other general-purpose algorithms for dynamic CSPs using random instances and benchmarks derived from real life problems

Solving Inaccuracies in Anatomical Models for Electrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality

[EN] Electrocardiographic Imaging has become an increasingly used technique for non-invasive diagnosis of cardiac arrhythmias, although the need for medical imaging technology to determine the anatomy hinders its introduction in the clinical practice. This paper explores the ability of a new metric based on the inverse reconstruction quality for the location and orientation of the atrial surface inside the torso. Body surface electrical signals from 31 realistic mathematical models and four AF patients were used to estimate the optimal position of the atria inside the torso. The curvature of the L-curve from the Tikhonov method, which was found to be related to the inverse reconstruction quality, was measured after application of deviations in atrial position and orientation. Independent deviations in the atrial position were solved by finding the maximal L-curve curvature with an error of 1.7 +/- 2.4 mm in mathematical models and 9.1 +/- 11.5 mm in patients. For the case of independent angular deviations, the error in location by using the L-curve was 5.8 +/- 7.1 degrees in mathematical models and 12.4 degrees +/- 13.2 degrees in patients. The ability of the L-curve curvature was tested also under superimposed uncertainties in the three axis of translation and in the three axis of rotation, and the error in location was of 2.3 +/- 3.2 mm and 6.4 degrees +/- 7.1 degrees in mathematical models, and 7.9 +/- 10.7 mm and 12.1 degrees +/- 15.5 degrees in patients. The curvature of L-curve is a useful marker for the atrial position and would allow emending the inaccuracies in its location.This work was supported in part by Generalitat Valenciana under Grant ACIF/2013/021, in part by the Instituto de Salud Carlos III, Ministry of Economy and Competitiveness, Spain, under Grant PI13-01882, Grant PI13-00903, Grant PI14/00857, Grant TEC2013-46067-R, and Grant DTS16/00160, in part by the Spanish Society of Cardiology (Grant for Clinical Research in Cardiology 2015), and in part by the Spanish Ministry of Science and Innovation (Red RIC) under Grant PLE2009-0152.Rodrigo Bort, M.; Climent, AM.; Liberos Mascarell, A.; Hernández-Romero, I.; Arenal, A.; Bermejo, J.; Fernández-Avilés, F.... (2018). Solving Inaccuracies in Anatomical Models for Electrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality. IEEE Transactions on Medical Imaging. 37(3):733-740. https://doi.org/10.1109/TMI.2017.2707413S73374037

Disminución de la reserva de flujo coronario en pacientes con insuficiencia cardíaca no isquémica

Introduction and objectives. Coronary flow reserve (CFR) is impaired not only in ischemic heart disease, but also in cardiac diseases that may or may not course with heart failure. The aim of the present study was to determine if the severity of heart failure can influence CFR impairment. Methods. Forty patients with non-ischemic heart disease and heart failure were studied 41 times. Four groups were established: 1. 10 patients in functional class III-IV; 2. 10 patients in functional class II not taking beta-blockers; 3. 11 patients in class II treated with carvedilol, and 4. 10 patients in class I. These patients had a history of heart failure and systolic dysfunction. Myocardial blood flow (MBF) was measured with positron emission tomography (PET) and N-13 ammonia at rest (r) and during adenosine triphosphate (ATP) infusion. Results. MBF and CFR were significantly higher in group 4 (1.95 ± 0.58 and 2.40 ± 0.95 ml/min/g) than in group 1 (1.02 ± 0.52 and 1.46 ± 0.48 ml/min/g). CFR tended to be higher in groups 2 (1.73 ± 0.72), and 3 (1.89 ± 0.75) vs group 1. No significant correlation was found between CFR and the following variables: age, systolic blood pressure, ventricular mass index, ventricular volume indexes, and ejection fraction. Conclusions. Coronary microvascular function is impaired in non-ischemic heart failure, and the impairment is related to functional class, regardless of the underlying responsible heart disease

An alternative approach to implement a recursive interpolation

Peer ReviewedPostprint (published version

Mantle-cell lymphoma genotypes identified with CGH to BAC microarrays define a leukemic subgroup of disease and predict patient outcome

To identify recurrent genomic changes in mantle cell lymphoma (MCL), we used high-resolution comparative genomic hybridization (CGH) to bacterial artificial chromosome (BAC) microarrays in 68 patients and 9 MCL-derived cell lines. Array CGH defined an MCL genomic signature distinct from other B-cell lymphomas, including deletions of 1p21 and 11q22.3-ATM gene with coincident 10p12-BMI1 gene amplification and 10p14 deletion, along with a previously unidentified loss within 9q21-q22. Specific genomic alterations were associated with different subgroups of disease. Notably, 11 patients with leukemic MCL showed a different genomic profile than nodal cases, including 8p21.3 deletion at tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) receptor gene cluster (55% versus 19%; P = .01) and gain of 8q24.1 at MYC locus (46% versus 14%; P = .015). Additionally, leukemic MCL exhibited frequent IGVH mutation (64% versus 21%; P = .009) with preferential VH4-39 use (36% versus 4%; P = .005) and followed a more indolent clinical course. Blastoid variants, increased number of genomic gains, and deletions of P16/INK4a and TP53 genes correlated with poorer outcomes, while 1p21 loss was associated with prolonged survival (P = .02). In multivariate analysis, deletion of 9q21-q22 was the strongest predictor for inferior survival (hazard ratio [HR], 6; confidence interval [CI], 2.3 to 15.7). Our study highlights the genomic profile as a predictor for clinical outcome and suggests that "genome scanning" of chromosomes 1p21, 9q21-q22, 9p21.3-P16/INK4a, and 17p13.1-TP53 may be clinically useful in MCL

Switchable All Inorganic Halide Perovskite Nanocrystalline Photoelectrodes for Solar-Driven Organic Transformations

All inorganic halide perovskite nanocrystals (NCs) are considered as fascinating materials for a wide range of optoelectronic applications encompassing photovoltaics, lasing, sensing, and photocatalysis due to their outstanding optoelectronic properties. Herein, it is demonstrated that the photoelectrochemical behavior of CsPbBr3 NC films can be tailored through engineering the selective contacts and accepting species in the electrolyte. This concept has been successfully applied to the photoelectrochemical oxidation of benzyl alcohol (BzOH) to benzyl aldehyde (BzCHO) and the reverse photoelectrochemical reduction of BzCHO to BzOH, demonstrating that CsPbBr3 NCs activate both reactions with photocurrents up to 40 μA cm 2 toward BzCHO production and 5 μA cm 2 for the reverse reaction at 0.15 V versus normal hydrogen electrode. The obtained results highlight the huge potential and versatility of halide perovskite NCs for photoelectrocatalytic applications, validating the implementation of these materials for a wide range of solar-driven complex organic transformations, and emphasizing the urgent need for stabilization strategies to move beyond the proof-of-concept stage to relevant technological developments

Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings

Constraint programming is a paradigm wherein relations between variables are stated in the form of constraints. Many real life problems come from uncertain and dynamic environments, where the initial constraints and domains may change during its execution. Thus, the solution found for the problem may become invalid. The search forrobustsolutions for constraint satisfaction problems (CSPs) has become an important issue in the ¿eld of constraint programming. In some cases, there exists knowledge about the uncertain and dynamic environment. In other cases, this information is unknown or hard to obtain. In this paper, we consider CSPs with discrete and ordered domains where changes only involve restrictions or expansions of domains or constraints. To this end, we model CSPs as weighted CSPs (WCSPs) by assigning weights to each valid tuple of the problem constraints and domains. The weight of each valid tuple is based on its distance from the borders of the space of valid tuples in the corresponding constraint/domain. This distance is estimated by a new concept introduced in this paper: coverings. Thus, the best solution for the modeled WCSP can be considered as a most robust solution for the original CSP according to these assumptionsThis work has been partially supported by the research projects TIN2010-20976-C02-01 (Min. de Ciencia e Innovacion, Spain) and P19/08 (Min. de Fomento, Spain-FEDER), and the fellowship program FPU.Climent Aunés, LI.; Wallace, RJ.; Salido Gregorio, MA.; Barber Sanchís, F. (2013). Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings. Artificial Intelligence Review. 1-26. https://doi.org/10.1007/s10462-013-9420-0S126Climent L, Salido M, Barber F (2011) Reformulating dynamic linear constraint satisfaction problems as weighted csps for searching robust solutions. 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