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The demand for liquified natural gas grows as it is an energy resource that has more flexible means of transport than non-liquefied natural gas, and is more eco-friendly than other fossil fuels. This paper focused on comparing five different mixed-refrigerant liquefaction processes to determine which one is the most efficient in energetic and economic terms for four different natural gas processing scales (20,000 kg/h and 2, 4, and 8 MTPA of natural gas feed). Simpler processes with one or two refrigerant cycles (single mixed refrigerant, propane pre-cooled mixed refrigerant, and dual mixed refrigerant) and more complex processes with three cycles (mixed fluid cascade and AP-X) were analyzed. All processes were simulated in Aspen HYSYS, and the energy consumption was optimized by a communication between the simulator and an optimization algorithm based on Particle Swarm Optimization coded in MATLAB. The economic analysis was performed using the CAPCOST technique and the rule of six-tenths for upscaling. In the best-optimized scenario, the results show that the most complex process, AP-X, consumes the lowest amount of energy (0.2367 kWh/kg-LNG) while the simplest one, the single mixed refrigerant, consumes the highest value (0.2561 kWh/kg-LNG). In the economic analysis, the results indicate that energetically better processes may not provide a higher economic return even on large scales. The authors acknowledge the National Council for Scientific and Technological Development – CNPq (Brazil), processes 117948/2020-9, 307958/2021-3, 200305/2020-4, 148184/2019-7, 311807/2018-6, and 428650/2018-0, and Coordination for the Improvement of Higher Education Personnel – CAPES (Brazil) for the financial support. J.A. Caballero wants to acknowledge the financial support of the ‘Generalitat Valenciana’ under project PROMETEO 064/2020 and the Ministerio de Ciencia e Innovación, under project PID2021-124139NB-C21.

The present work proposes a careful study of the effects of different operational factors on the electrocoagulation process of synthetic oil-water emulsions. The experimental conditions used were the pH of the solution, current density, electrolyte concentration, oil concentration, and distance between the electrodes. The results showed that the proposed process is efficient for de-emulsification and oil removal, as it reached 100% removal in some conditions. Furthermore, the experiments showed that the first two variables were the most impactful ones in the efficiency of COD removal. To determine the optimal conditions in which the electrocoagulation should operate, two different models were developed: a polynomial one, using Genetic Algorithm to optimize its coefficients, and an Artificial Neural Network one, which used the input variables to predict the amount of oil removed. The modelling results showed good agreements, as the polynomial and ANN models had R2 values of 0.89 and 0.99, respectively, showing that the neural model is the most suitable one to predict the COD removal and optimize the operational conditions. The SSE values of 1979.08 (polynomial) and 4.92 (ANN) also indicate the neural model is the best one.

This study describes a computationally efficient model for the optimal sizing and siting of Electrical Energy Storage Devices (EESDs) in Smart Grids (SG), accounting for the presence of time-varying electricity tariffs due to Demand Response Program (DRP) participation. The joint planning and operation problem for optimal siting and sizing of the EESD is proposed in a two-stage optimization problem. In this regard, the long-term decision variables deal were the size and location of the EESDs and have been considered at the master level while the operating point of the generation units and EESDs is determined by the slave stage of the model utilizing a standard mixed-integer linear programming model. To examine the effectiveness of the model in the slave sub-problem, the operation model is solved for different working days of different seasons. Binary Particle Swarm Optimization (BPSO) and Binary Genetic Algorithm (BGA) have been used at the master level to propose different scenarios for investment in the planning stage. The slave problem optimizes the model in terms of the short-term horizon (day-ahead). Additionally, the slave problem determines the optimal schedule for an SG considering the presence of EESD (with sizes and locations provided by the upper level). The electricity price fluctuates throughout the day, according to a Time-of-Use (ToU) DRP pricing scheme. Moreover, the impacts of DRPs have been addressed in the slave stage. The proposed model is examined on a modified IEEE 24-Bus test system.

This paper presents a pool trading model within a local energy community considering home energy management systems (HEMSs) and other consumers. A transparent mechanism for market clearing is proposed to incentivise active prosumers to trade their surplus energy within a rule-based pool market in the local energy community. A price-based demand response program (PBDRP) is considered to increase the consumers’ willingness to modify their consumption. The mathematical optimization problem is a standard mixed-integer linear programming (MILP) problem to allow for rapid assessment of the trading market for real energy communities which have a considerable number of consumers. This allows for novel energy trading strategies amongst different clients in the model and for the integration of a pool energy trading model at the level of the local energy community. The objective function of the energy community is to minimize the overall bills of all participants while fulfilling their demands. Two different scenarios have been evaluated, independent and integrated operation modes, to show the impacts of coordination amongst different end-users. Results show that through cooperation, end-users in the local energy community market can reduce the total electricity bill. This is shown in a 16.63% cost reduction in the independent operation and a 21.38% reduction in the integrated case. Revenues for active consumers under coordination increased compared to independent operation of the HEMS.

Continental-arc igneous rock compositions change in response to the transition from subduction to collision and these changes can reveal how the crust, lithosphere and magma sources evolved. Neotethys-related Late Cretaceous to Pleistocene subduction- and collision-related magmatic rocks from the ~350 km long southeast Urumieh-Dokhtar Magmatic Belt (UDMB) of Iran provide an excellent natural laboratory to better understand these changes. These igneous rocks are well-exposed and moderately eroded to reveal a nearly complete record since subduction initiation at ~95 Ma. We analyzed new samples for major and trace elements (83 samples), Srsingle bondNd isotopic compositions (47 samples), and Usingle bondPb zircon ages (26 samples) and compiled geochemical and geochronological data on the southeast segment of the UDMB. The geochronological data reveal two magmatic pulses at ~80–70 Ma and ~50–0 Ma. Important changes in magmatic compositions reflect initial collision with Arabia at ~32 Ma, changing from normal calc-alkaline to increasingly adakitic immediately after collision began. Five stages can be identified: 1) normal continental-arc magmatism during the Late Cretaceous; 2) arc quiescence in Paleocene and Early Eocene time; 3) Middle-Late Eocene extensional arc magmatism related to slab rollback; 4) early collision and crustal thickening during the Early Oligocene; and 5) slab breakoff, asthenospheric upwelling, and associated adakitic magmatism from Middle Miocene onward. Temporal changes in UDMB magmas reflect the response of the overriding plate to changes in the geometry of the subducting Neotethyan lithosphere and to collision between Arabia and Iran. Crustal thickening and arc narrowing during Miocene to Pleistocene post-collisional magmatism caused adakitic magmatism and associated Cu mineralization. Zircon O-Hf and apatite O isotopes as well as bulk-rock Nd isotopes of Cu-bearing adakitic rocks are similar to other barren rocks, but nearly all fertile rocks have higher Hf/Y, Eu/Eu⁎(n) in zircon and higher Sr/Y, V/Y, Eu/Eu⁎(n) in apatite than barren rocks. published

Zinc oxide (ZnO) nanostructures have been widely used in biosensor applications. However, little attention has been given to the interaction of ZnO structures with physiological buffer solutions. In the present work, it is shown that the use of buffers containing phosphate ions leads to the modification of the ZnO tetrapodal micro/nanostructures when immersed in such solutions for several hours, even at the physiological pH (7.4). ZnO samples designed to be used as transducers in biosensors were immersed in phosphate buffers for several durations at pH = 5.8 and pH = 7.4. Their detailed morphological, structural and optical characterization was carried out to demonstrate the effect of the ZnO interaction with the phosphate ions. The pH had an important role in the ZnO conversion into zinc phosphate, with lower pH promoting a more pronounced effect. After 72 h and at pH = 5.8, a significant amount of the ZnO structures were converted into crystalline zinc phosphate, while immersion during the same time at pH = 7.4 resulted predominantly in amorphous zinc phosphate particles mixed with the original ZnO tetrapods. Photoluminescence spectra show remarkable changes with prolonged immersion times, particularly when the luminescence of the sample was investigated at 14 K. These findings highlight the importance of a careful analysis of the sensing results when phosphate-based buffer solutions are in contact with the ZnO transducers, as the changes observed on the transduction signal during sensing experiments may also comprise a non-negligible contribution from a phosphate-induced transformation of ZnO, which can hamper an accurate assessment of the sensing behavior.

A surrogate-based multi-objective optimization framework is employed in the design of natural gas liquefaction processes using reliable, black-box process simulation. The conflicting objectives are minimizing both power consumption and heat exchanger area utilization. The Pareto solutions of the single-mixed refrigerant (SMR) and propane-precooled mixed refrigerant (C3MR) processes are compared to determine the suitability of each process in terms of energy consumption and heat exchanger area. Kriging models and the ɛ-constraint methodology are used to sequentially provide simple surrogate optimization subproblems, whose minimizers are promising feasible and non-dominated solutions to the original black-box problem. The surrogate-based ɛ-constrained optimization subproblems are solved in GAMS using CONOPT. The Pareto Fronts achieved with the surrogate-based framework dominate the results from the NSGA-II, a well-established meta-heuristics of multi-objective optimization. The objective functions of non-dominated solutions go as low as 1045 and 980.3 kJ/kg-LNG and specific UA values of 212.2 and 266.9 kJ/(°C kg-LNG) for SMR and C3MR, respectively. The trade-off solutions that present the minimum sum of relative objectives are analyzed as well as the dominance of C3MR over SMR at low power consumption values and conversely at low heat exchanger area utilization. The authors LFS, CBBC, and MASSR acknowledge the National Council for Scientific and Technological Development–CNPq (Brazil), processes 200305/2020-4, 148184/2019-7, 440047/2019-6, 311807/2018-6, 428650/2018-0, 307958/2021-3 and Coordination for the Improvement of Higher Education Personnel–CAPES (Brazil) for the financial support. The author JAC acknowledges financial support from the “Generalitat Valenciana” under project PROMETEO 2020/064 and the Ministerio de Ciencia e Innovación , under project PID2021-124139NB-C21.

Background: Chagas disease (caused by Trypanosoma cruzi infection) evolves to chronic chagasic cardiomyopathy (CCC) affecting 1.8 million people worldwide. This is the first randomized, placebo-controlled, double-blinded, clinical trial designed to estimate efficacy and safety of selenium (Se) treatment in CCC. Methods: 66 patients with CCC stages B1 (left ventricular ejection fraction [LVEF] > 45% and no heart failure; n = 54) or B2 (LVEF < 45% and no heart failure; n = 12) were randomly assigned to receive 100 mcg/day sodium selenite (Se, n = 32) or placebo (Pla, n = 34) for one year (study period: May 2014-September 2018). LVEF changes over time and adverse effects were investigated. Trial registration number: NCT00875173 (clinicaltrials.gov). Findings: No significant differences between the two groups were observed for the primary outcome: mean LVEF after 6 (β= +1.1 p = 0.51 for Se vs Pla) and 12 months (β= +2.1; p = 0.23). In a subgroup analysis, statistically significant longitudinal changes were observed for mean LVEF in the stage B2 subgroup (β= +10.1; p = 0.02 for Se [n = 4] vs Pla [n = 8]). Se treatment was safe for CCC patients, and the few adverse effects observed were similarly distributed across the two groups. Interpretation: Se treatment did not improve cardiac function (evaluated from LVEF) in CCC. However, in the subgroup of patients at B2 stage, a potential beneficial influence of Se was observed. Complementary studies are necessary to explore diverse Se dose and/or associations in different CCC stages (B2 and C), as well as in A and B1 stages with longer follow-up. Funding: Brazilian Ministry of Health, Fiocruz, CNPq, FAPERJ.

Introducao Aproximadamente dois bilhoes de pessoas sofrem de anemia no mundo. Pesquisas sugerem que compostos endovenosos sao mais tolerados que os orais, com tempo de atuacao mais rapido, bem como a correcao dos estoques. Carboximaltose ferrica e utilizada em grande parte dos pacientes, por seu perfil de tolerabilidade, posologia facilitada e reposicao rapida dos estoques, porem um dos efeitos colaterais e a hipofosfatemia, que ocorre entre 2-5 semanas da administracao. Nosso intuito e relatar o caso de um paciente com diagnostico de osteomalacia associada ao uso cronico de carboximaltose ferrica. Apresentacao do caso: Paciente, 51a, admitida em janeiro de 2021 por historia de lombalgia associada a febre. Apresentava refratariedade a tratamentos tradicionais com analgesicos, necessitando de abordagens com neuromodulacao e infiltracao. Investigacoes revelaram anemia, com discreta plaquetose, perfil de ferro dentro da normalidade, com marcadores de hemolise negativos. Pelo diagnostico de Telangiectasia hemorragica hereditaria, paciente apresentava-se com anemia ferropriva cronica recidivante e necessidade de uso de terapia com ferro endovenoso (carboximaltose ferrica desde 2017). Constatou-se que paciente apresentava quadro de espondilodiscite (L2-L3) em ressonância magnetica. Foi solicitado painel osteometabolico pelo quadro de osteoporose, onde se evidenciou aumento importante do PTH, com hiperparatireoidismo secundario, hipofosfatemia e calcio dentro dos valores de normalidade. Devido ao uso cronico de carboximaltose ferrica por mais de quatro anos, com frequencia mensal, aventou-se a possibilidade de Osteomalacia secundaria a carboximaltose ferrica. Em relacao aos exames laboratoriais osteo metabolicos, constatou-se um hiperparatireoidismo secundario, com calcio normal e hipofosfatemia, tambem hipovitaminose D, corroborando para o diagnostico de osteomalacia por hipofosfatemia secundaria ao uso de Carboximaltose Ferrica. A paciente foi tratada para espondilodiscite com antimicrobianos e foram realizadas reposicao oral de fosforo, calcio e vitamina D alem da suspensao da Carboximaltose ferrica e preferencia por reposicao de ferro por via oral e transfusoes se necessario. Tambem iniciou uso de antifibrinoliticos topicos e enterais, quando necessario. E nas semanas subsequentes, apresentou melhora da dor, com queda dos valores de PTH, normalizacao do calcio e fosforo. Discussao Em uma revisao sistematica sobre hipofosfatemia associada a terapias de ferro intravenoso para anemia ferropriva, que incluiu 40 estudos, a hipofosfatemia ocorreu em ate 92.1% das reposicoes feitas com Carboximaltose ferrica, com incidencias muito inferiores para sucrose, ferumoxitol e dextran. Pacientes com hipofosfatemia aguda desenvolviam principalmente fadiga e aqueles com necessidade repetida de reposicao de ferro com Carboximaltose ferrica desenvolveram hipofosfatemia cronica associada a osteomalacia e deformidades osseas. Na literatura nao ha padronizacao para monitorar os niveis de fosfato. Apesar de multiplos casos documentados de consequencias clinicas graves associadas a certas composicoes endovenosas de ferro, os trabalhos nao trazem informacoes consistentes sobre frequencia e severidade, podendo subestimar sua prevalencia. Conclusao O diagnostico da hipofosfatemia requer suspeita clinica. Em pacientes com reposicao endovenosa cronica de ferro sugerimos monitoramento dos niveis de fosfato, PTH, calcio ionico e vitamina D para que iniciemos as profilaxias ou alternativas terapeuticas antes de causar maleficio no paciente, seguindo a recomendacao do Pai da Medicina: Primo non nocere. Palavras-chave: Anemia ferropriva; Ferropenia; Osteomalacia; Teleangectasia; Hemorragica hereitaria.

In recent years molecules involved on the immune synapse became successful targets for therapeutic immune modulation. CD6 has been extensively studied, yet, results regarding CD6 biology have been controversial, in spite of the ubiquitous presence of this molecule on virtually all CD4 T cells. We investigated the outcome of murine and human antibodies targeting CD6 domain 1. We found that CD6-targeting had a major impact on the functional specialization of CD4 cells, both human and murine. Differentiation of CD4 T cells towards a Foxp3+ Treg fate was prevented with increasing doses of anti-CD6, while Th1 polarization was favoured. No impact was observed on Th2 or Th17 specialization. These in vitro results provided an explanation for the dose-dependent outcome of in vivo anti-CD6 administration where the anti-inflammatory action is lost at the highest doses. Our data show that therapeutic targeting of the immune synapse may lead to paradoxical dose-dependent effects due to modification of T cell fate. Keywords: CD6, CD4 T cells, Treg cells, Foxp3, EAE, T-cell polarization

Mineral flotation using microorganisms and/or their derived products is called “bioflotation.” This is a promising process due to its low environmental impact; however, it is also a very complicated process, due to its multidisciplinary character, involving mineralogy, chemistry, and biology. So, the optimization of this process is an important challenge. This study assessed the implementation of a quadratic model and an artificial neural network (ANN) for the optimization of hematite and quartz floatability and recovery. The flotation process was carried out using a biosurfactant extracted from the Rhodococcus erythropolis bacteria. Quadratic model was adjusted by genetic algorithms techniques and validated using analysis of variance (ANOVA). Multilayered feed-forward networks were trained using a backpropagation algorithm, implemented using MATLAB R2017a. The topologies of the neural networks included 2 neurons in the input layer and 1 neuron in the output layer in both models, while the hidden layer varied according to the performance of the model. The results showed that the ANN model can predict the experimental results with good accuracy, when compared to quadratic model. Sensitivity analysis showed that the studied variables (pH and biosurfactant concentration) have an effect on the mineral recovery. Keywords: Bioflotation, Hematite, Quartz, Biosurfactant, Neural network

Convection enhanced drug delivery (CED) is a technique used to make therapeutic agents reach, through a catheter, sites of difficult access. The name of this technique comes from the convective flow originated by a pressure gradient induced at the tip of the catheter. This flow enhances passive diffusion and allows a more efficient spread of the agents by the target site. CED is particularly useful in the treatment of diseases that affect the central nervous system, where the blood-brain barrier prevents the diffusion of most therapeutic agents from the cerebral blood vessels to the brain interstitial space. In this work we deal with the numerical analysis of a coupled system of partial differential equations that can be used to simulate CED in an elastic medium like brain tissue. The model variables are the fluid velocity, the pressure, the tissue deformation, and the agents concentration. We prove the stability of the coupled problem and from the numerical point of view we propose a fully discrete piecewise linear finite element method (FEM). The convergence analysis shows that the method has second order convergence for the pressure, displacement, and concentration. Numerical experiments illustrating the theoretical convergence rates and the behavior of the system are also given. UIDB/00324/2020; UIDB/04621/2020 info:eu-repo/semantics/publishedVersion

This paper presents a surrogate-assisted framework to solve constrained black-box optimization problems, which is applied to the optimal single-mixed refrigerant natural gas liquefaction processes design. This approach uses kriging models as cheap-to-evaluate, reliable surrogates of the process-simulator-dependent black-box functions of the optimization problem. From kriging prediction and estimated error, the probability of feasible improvement acquisition function is derived and optimized to search forfeasible and improving candidates to perform local search in the penalized simulation. The kriging-assisted global search scheme is efficient to find promising candidates for local refinement, and it improves previous results that used only local optimization by 3.36 and 5.32 %. The surrogate model reduces the time to evaluate the functions from 0.9933 ± 0.0815 to 3.515e-4 ± 8.353e-5 seconds. The kriging approximation mean squared errors assessed in a k-fold cross-validation is 7.271e-7 ± 1.297e-7 for the objective function and 0.3099 ± 0.0856 for the constraint. The authors acknowledge the National Council for Scientific and Technological Development–CNPq (Brazil), processes 148184/2019-7, 440047/2019-6, 311807/2018-6, 428650/2018-0, 305055/2017-8, and Coordination for the Improvement of Higher Education Personnel–CAPES (Brazil) for the financial support.

[EN] Although sometimes controversial, the use of Pb isotope data in geological research of ore deposits and metal provenance studies in archaeology has proved a useful tool for investigation of the relations between ore sources and raw materials used by humans. Users of this kind of information have often asked for complete datasets that would include not only numerical values of isotope ratios but also mineralogical and geological information about the samples analysed so as to allow for conscientious data comparison. The IBERLID database here presented has been designed to include available information for nearly 3000 samples from the Iberian Peninsula and Balearic Islands in a unique, complete to the extent possible, upgradable dataset using standardized variables. This allows to compare data and establish groups based upon isotopic ratios, mineralogy and other geological characteristics of the samples. The database is available through an online interactive public tool (www.ehu.eus/ibercron/iberlid) that provides for data search, comparison and graphics design, and may be furthermore exported for enhanced statistical treatment. By direct use of the proposed standardized variables, the compiled results allow to discern among 3 main mineralization events within the Iberian realm, while interpolation of Pb isotope data allow to draw the first maps of model age, mu and kappa parameters. The problem of radiogenic lead in some compiled data requires additional analyses of elemental concentrations, which so far has been generally neglected. Financial support was provided by the Spanish Ministry of Economy, Industry and Competitiveness, and the European Regional Development Fund (MINECO/ERDF CGL2015-63530-P) , and by the UPV/EHU (GIU15/05) . The authors are grateful to Sabine Klein and two anony-mous reviewers for constructive comments which improved this manuscript, and to Huayong Chen for suggestions and editorial handling.

Phosphorus (P) is a non-renewable resource, irreplaceable for life and food production, and currently considered a Critical Raw Material to the European Union (EU). Due to concerns about the rate of consumption and limited reserves in countries with sensitive geopolitical contexts, it is urgent to recover P from urban and industrial flows. Indeed, the municipal wastewater treatment plants (WWTP) are considered relevant sources with several hot spots, especially sewage sludge with estimated recovery efficiencies of >80%. The most promising recovery strategies are based on thermal treatments (e.g., incineration of sludge) following by wet-chemical or thermochemical leaching, precipitation, and adsorption. The direct application of sludge on soil is no longer a primary route for P reintegration in the value-chain for countries as Switzerland, Germany, and The Netherlands. In fact, Switzerland and Austria paved the way for implementing P recovery legislation, focusing on recovery from raw sewage sludge or ashes. Indeed, industrial technologies with sludge ash as input show high recovery efficiencies (Ashdec® and Leachphos® with 98 and 79%) and lower environmental impacts, whereas Pearl® technology has about 12% recovery efficiency with wastewater as input. After all, struvite emerges as the most recovered product with recent access to the internal market of EU fertilisers and similar growth performance compared to triple-super-phosphate. However, several studies leave open the possibility of introducing loaded adsorbents with P as soil amendments as a new alternative to conventional desorption. Briefly, P recovery should be a compromise between efficiency, environmental impacts, and economic revenues from the final products info:eu-repo/semantics/publishedVersion

Metal oxide semiconductors, and particularly zinc oxide (ZnO), are amongst the most investigated materials to be applied as transducer elements in biosensing devices due to properties as biochemical stability, biocompatibility and functionalisation simplicity. In the present work, ZnO nanotetrapods were produced by the laser-assisted flow deposition technique to be used as transducers in a photoluminescence (PL)-based immunosensor to detect the human chorionic gonadotropin (hCG) hormone. The produced nanostructures were analysed by electron microscopy, Raman and PL spectroscopies. The ZnO tetrapods exhibit an intense PL in both the ultraviolet and visible range, whose intensity changed after the direct immobilisation of the anti-hCG antibodies into the semiconductor’s surface. The changes in the PL intensity after the interaction of the immobilised antibodies with hCG were used as the transduction mechanism for the envisaged sensors. It was observed that when antibody-antigen interactions occur, charge rearrangement at the surface of the semiconductor leads to a reduction in overall intensity of the PL signal with increasing hCG concentration, allowing to establish a correlation between the PL output and the probed concentration. Therefore, such behaviour suggests the adequacy of the developed ZnO-based transducers to be incorporated into optical biosensors. Additionally, the possible interaction mechanisms between the ZnO surface and the immobilised molecules responsible for the changes in the PL spectra were discussed.

We report a clinical case of a 39-year old male, without any known previous medical condition but with occupational exposure to paints and dust cement, who presented an autoimmune pulmonary alveolar proteinosis (PAP) triggered by exposure to toxic inhalation at his workplace. PAP is a rare lung disease characterized by intra-alveolar abnormal accumulation of surfactant. The presence of a crazy-paving pattern in high-resolution computed tomography scan brings the suspicion of PAP although histopathology results of bronchoalveolar lavage are always required for its final diagnosis. The autoimmune form of PAP due to toxic inhalation, such as the one here described, is rare and it is usually difficult to establish a causal relationship.

This work aims to obtain multifunctional nanocomplexes with a superparamagnetic core and an upconversion luminescent shell, by synthesizing superparamagnetic iron oxide nanoparticles (SPIONs) functionalized with lanthanide ions. These materials may be used in numerous applications, e.g. in the biomedical and environmental fields. Three distinct nanocomplexes were synthesized: SPIONs@LaF3:Yb3+/Er3+, SPIONs@NaYF4:Yb3+/Er3+ and SPIONs@NaYF4:Yb3+/Ho3+. The first was obtained using the microemulsion and co-precipitation methods and the latter using the thermal decomposition method. A heat treatment was also applied to the SPIONs@LaF3:Yb3+/Er3+ nanocomplex. VSM revealed the superparamagnetic character of the nanocomplexes, and the saturation magnetization was 10.2emu·g−1, 8.4emu·g−1, 8.3emu·g−1 and 14.0emu·g−1 for SPIONs@LaF3:Yb3+/Er3+ without and with heat treatment, SPIONs@NaYF4:Yb3+/Er3+ and SPIONs@NaYF4:Yb3+/Ho3+ nanocomplexes, respectively. The upconversion process in these materials was confirmed by multiphoton microscopy. For SPIONs@NaYF4:Yb3+/Er3+, three peaks of emission were obtained, at 520nm, 540nm and 657nm, while for SPIONs@NaYF4:Yb3+/Ho3+ and SPIONs@LaF3:Yb3+/Er3+ samples only two peaks were observed, at 540nm and 647nm for the first, and at 540nm and 657nm for the latter. The results for the nanocomplex which uses Ho3+ ions as activators are very promising, since similar nanocomplexes are yet to be reported and good magnetic and luminescent properties were achieved. Keywords: Fluorescence, Upconversion, Superparamagnetism, Lanthanides, Nanocomplexes, Iron oxide

Superstructure-based optimization models have been used as important approaches in solving process systems engineering problems. Despite its promising results, mixed-integer nonlinear programming (MINLP) optimization models are usually complex, once they involve integer and continuous variables, and nonlinear, non-convex functions. For work and heat exchange networks (WHEN) synthesis, even in problems of few process streams, the derived MINLP models have large combinatorial and continuous search spaces. In the present paper, the search spaces of two equivalents MINLP models for WHEN synthesis are analyzed to test their influence on optimization performance. The models are derived from the same superstructure, but one of those uses strategies to reduce the number of decision variables that provides a considerable diminution of combinatorial problem. The same bi-level meta-heuristic optimization approach in which Simulated Annealing deals with the combinatorial level and Particle Swarm Optimization with the continuous one is used to solve both MINLP problems. The mean values of total annualized cost and elapsed time from several optimization runs of both models are compared. The results show that the decision-variable-reduced model is more efficient and consistent than the standard-decision-variable one. It can be concluded that combinatorial search space reduction is important for optimization performance of highly complex decision-making problems such as WHEN synthesis and should be addressed in WHEN modeling because the problem’s complexity increases exponentially with the number of the model binary variables.

A comprehensive review is presented, regarding the most significant developments and recent progress on one-dimensional (1-D) photonic crystals (PCs) like Bragg mirrors (BMs) and Fabry–Perot microcavities (F–P MCs) based on silica or silicate glass and titania, produced by sol–gel (SG). SG processing, deposition and characterization techniques, including simulations, are described, highlighting their potential for applications in optoelectronic materials and devices. Special emphasis is placed on lanthanide (Ln)-doped 1-D PCs, where the active layer includes elements like Ce, Tb, Er and Yb, corresponding to the defect layer of MC structures. A comparison is also made with similar structures prepared by other methods (e.g. sputtering).

Highlights • Mycobacterium chelonae infection may occur in chronic treatment with steroids. • The most common presentation form is disseminated cutaneous infection. • First-line treatment should be a triple antibiotics association for at least 4 months. • Macrolides, fluoroquinolones and other antibiotics may exacerbate myasthenia gravis., Mycobacterium chelonae can cause chronic skin, soft-tissue or bone infections. and is often associated with the immunocompromised state.We describe a case of a 58-year-old male patient with myasthenia gravis, chronically immunosuppressed, with a four month progression of growing erythematous, nodular and hard cutaneous lesions in the left forearm, leg and foot. He was receiving immunoglobulin every four weeks (2 g/kg) and prednisolone 25 mg/day and had an important previous history of several opportunistic infections while he was receiving corticosteroids. Histopathological examination of a biopsy showed acid-fast bacilli and tissue culture identified a Mycobacterium spp. within seven days of incubation, with Mycobacterium chelonae being identified by polymerase chain reaction assay. Antimicrobial susceptibility testing was performed showing no resistance and the patient was successfully treated during four months with ciprofloxacin, clarithromycin and trimethoprim-sulfamethoxazole with regression of the lesions, leaving some hyperpigmentation scars and without unbalancing his neurological disease. Patients with myasthenia gravis should be closely monitored because first line treatments for M. chelonae infection may be associated with myasthenic crisis.

Integrating the energy available in industrial processes in the form of heat and work is fundamental to achieve higher energy efficiencies as well as to reduce process costs and environmental impacts. To perform this integration, a new framework for the optimal synthesis of work and heat exchange networks (WHEN) aiming to reduce capital and operating costs is presented. The main contribution of this paper is the elaboration of a new WHEN superstructure and mixed-integer nonlinear programming (MINLP) derived model. Strategies of changing variables are applied to reduce the number of decision variables from the model. The MINLP problem with a reduced number of decision variables is solved with a two-level meta-heuristic optimization approach, using Simulated Annealing in the combinatorial problem and Particle Swarm Optimization in the nonlinear programming problem. For the sake of validation, this methodology is applied to three case studies comprising two, five, and six process streams. Economic savings achieved outperform results reported in the literature from 1.0 to 7.2%. Also, the solutions obtained present non-intuitive WHENs that shows the importance of using superstructure-based mathematical programming for such a difficult decision-making task. The authors would like to acknowledge the Coordination for the Improvement of Higher Education Personnel - CAPES (Brazil), processes 88887.217374/2018-00 and 88881.171419/2018-01, and the National Council for Scientific and Technological Development – CNPq (Brazil), processes 148184/2019-7, 305055/2017-8, 428650/2018-0 and 440047/2019-6, for the financial support.

This chapter provides a panorama of potential applications of the blockchain technology to the energy sector. The chapter provides an introduction to the blockchain technology covering the main technological characteristics and providing some context to what is a rapidly emerging technology. Some limitations of the technology are also discussed along with key issues relating to the regulation of the technology. The chapter then highlights how the blockchain technology could impact the energy sector in five distinct subsectors, these being energy trading, environmental attribute management, electric mobility, and financing considerations. The chapter then concludes by providing an up-to-date list of all nearly 150 companies working on the blockchain in energy space.

An overview of advances in sol–gel processing methods for phosphors with different possible optical applications will be presented, highlighting examples based on lanthanide-doped materials. Specifically, new emerging applications have been promoted, using spectral conversion phosphors based on down-shifting, down-conversion or quantum-cutting and up-conversion processes. A brief perspective is given in particular on the potential of sol–gel derived lanthanide-doped materials for down-conversion and up-conversion for integration with photovoltaic solar cells in order to reduce the thermalization and transparency problems, which limit their efficiency, as well as their application in other optoelectronic technologies. This chapter shows the potential of sol–gel method to obtain down and up conversion materials based on a variety of compositions such as fluorides, oxides and oxyfluorides with different geometries.

The Caribbean has suitable conditions for a significant wind energy development, which makes a good planning for the future renewable energy mix essential. The impact of climate change on Caribbean wind power has been analyzed by means of an ensemble of CORDEX regional climate models (RCMs) under the RCP8.5 warming scenario. The offshore wind energy resource was classified for the historical period and for the future considering wind energy factors, environmental risk factors and cost factors whose weights were estimated by a Delphi method. Future projections show a maximum annual wind increase, ∼0.4 ms−1 (8%), in most of the Caribbean, except in the Yucatan Basin. This increment occurs mainly during the wet season, ∼0.5 ms−1 (∼10%), associated with changes in the extension of the North Atlantic Subtropical High, which will strengthen the Caribbean low-level jet. Additionally, the moderate wind increase, ∼0.2 ms−1 (∼4%), projected during the dry season is restricted to the southeastern coast and it is associated with an increment in the land-ocean temperature difference (∼1 °C), which will intensify local easterly winds. The low-level jet region was classified as the richest wind energy resource in the Caribbean for the future with a larger extension compared to the historical period.

Solid state lighting (SSL) revolutionized the light sources and displays market. Challenges include the seek for low cost and efficient materials able to emit pure colours (red, green and blue). Herein, we report amine-functionalized organic/inorganic di-ureasil hybrids consisting of a siliceous skeleton and oligopolyether chains, d-U(600), modified by distinct concentration values of a blue emitting uncharged polyfluorene (poly (9,9-dioctylfluorene)-co-phenylene) (PF). Structural and thermal studies reveal that the interaction between the PF and the d-U(600) yield to an enhancement of the PF thermal stability. The optical characterization shows that the emission is strongly dependent on the excitation energy presenting a red-shift as the excitation wavelength increases, enabling a fine tuning of the emission colour coordinates. Under UV excitation, a maximum emission quantum yield value 0.44 ± 0.04 was attained, which is remarkably higher when compared to the value found for the undoped d-U(600), 0.13 ± 0.01, an analogous to the value found for the isolated PF, pointing out that the incorporation into the hybrid host did not yield to an emission efficiency quenching. A commercial LED chip emitting at 365 nm was coated by the PF-doped d-U(600) showing a wall-plug efficiency of 0.04% and a luminous efficacy of 0.003 lm⋅W−1, demonstrating the applicability of these materials as blue-emitting phosphors to be applied in SSL.

International audience; The volatility and cohesive energy of fluorinated ionic liquids, FILs, was evaluated and used to explored and understand the effect of fluorination of the ILs cations and anions on the cohesive interaction and structuration. For this, the vapour pressures at different temperatures using a Knudsen effusion apparatus coupled with a quartz crystal microbalance were measured for three fluorinated imidazolium-based ionic liquids. The enthalpies and entropies of vaporization were derived from the temperature dependence of the vapour pressures. The degree of fluorination of the ions leads to an increase of the IL volatility following the order: [C8mim][NTf2]

Floods are a significant threat for several countries, endangering the safety and the well-being of populations. Civil protection authorities are in charge of flood emergency evacuation, providing means to help the evacuation and ensuring that people have comfortable and safe places to stay. This work presents a multi-period location-allocation approach that identifies where and when to open a predefined number of shelters, when to send evacuation orders, and how to assign evacuees to shelters over time. The objective is to minimize the overall network distances that evacuees have to travel to reach the shelters. The multi-period optimization model takes into account that the travel times vary over time depending on the road conditions. People’s reaction to the flood evolution is also considered to be dynamic. We also assume that shelters become available in different time periods and have a limited capacity. We present a mathematical formulation for this model which can be solved using an off-the-shelf commercial optimization solver, but only for small instances. For real size problems, given the dynamic characteristics of the problem, obtaining an optimal solution can take several hours of computing time. Thus, a simulated annealing heuristic is proposed. The efficiency of the heuristic is demonstrated with a comparison between the heuristic and the solver solutions for a set of random problems. The applicability of the multi-period model and of the heuristic is illustrated using a case study which highlights the importance and the benefits of adopting a dynamic approach for optimizing emergency response operations.

Retentate is a by-product of the concentrate apple juice industry, resultant from clarification through an ultrafiltration process. It has a liquid to sludgy appearance, with 8% of total solids content, usually discarded as industrial waste, conveyed as wastewater directly to the sewage plant. However, its origin and expected composition may allow to define its use as a source of valuable compounds as well as its application in food and feed. The present work shows that retentate is very rich in carbohydrates, namely 40% fructose (dry weight), glucose (8%), oligosaccharides (5%), and polysaccharides (3%). It is also rich in protein (8%) and an available and inexpensive source of β-sitosterol (0.6%). This was the major sterol identified, accounting for 21% of total lipophilic compounds recovered by n-hexane. The retentate suspension was successfully used as nutritive medium for production of cider by a microbrewery and the protein-rich water insoluble material (28% of protein) was successfully used in feed formulations for racing pigeons.

The limited efficiency of conventional drugs has been instigated the development of new and more effective drug delivery systems (DDS). Transdermal DDS, are associated with numerous advantages such its painless application and less frequent replacement and greater flexibility of dosing, features that triggered the research and development of such devices. Such systems have been produced using either biopolymer; or synthetic polymers. Although the first ones are safer, biocompatible and present a controlled degradation by human enzymes or water, the second ones are the most currently available in the market due to their greater mechanical resistance and flexibility, and non-degradation over time. This review highlights the most recent advances (mainly in the last five years) of patches aimed for transdermal drug delivery, focusing on the different materials (natural, synthetic and blends) and latest designs for the development of such devices, emphasizing also their combination with drug carriers that enable enhanced drug solubility and a more controlled release of the drug over the time. The benefits and limitations of different patches formulations are considered with reference to their appliance to transdermal drug delivery. Furthermore, a record of the currently available patches on the market is given, featuring their most relevant characteristics. Finally, a list of most recent/ongoing clinical trials regarding the use of patches for skin disorders is detailed and critical insights on the current state of patches for transdermal drug delivery are also provided.

Considering the importance of monitoring piping systems, the aim of this work is to develop a technique to detect gas leaks in pipes, based on acoustic method. A copper tubing ½ in diameter and 53 m in length was assembled in laboratory, operating with continuous supply of compressed air, under various operating conditions with initial pressure of 1 kgf / cm2. We analysed the signals of five microphones, installed inside the tubing, generated by the occurrence of gas leakage. The microphone signals in the time domain were converted to the frequency domain via the fast Fourier transform (FFT). The microphone signals in the frequency domain used as an input of the artificial neural network (ANN) of the type Echo State Network (ESN) to determine the occurrence or not of leakage (model output). From the results, it was observed that the leaks were adequately detected. The neural model presented a percentage of correctness of approximately 81% indicating the occurrence or not of leakage in the line.

[EN] The present study shows the application of the nanoindentation technique to evaluate the properties of the cellulose fiber-cement matrix interfacial zone in composites prepared with an auger extruder. The degree of strength of the bond between fiber and matrix is recognized as important variable that influences macro-mechanical properties, such as modulus of rupture and toughness of cement based composites. The nanoindentation measurements showed the highest hardness and elastic modulus in the part inner of the cellulosic fiber after hydration process due to precipitation and re-precipitation of cement hydration products. These results indicate that mineralization of the cellulosic fibers can affect the stress distribution and interfacial bond strength in the cement based composite., The authors acknowledge by financial support provided by Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP, process no 2013/03823-8), Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES, process no 3886/2014) and Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq, process no 152069/2016), in Brazil. Special thanks for Fibria and Infibra for providing raw materials the development of this work.

This study evaluated the use of artificial neural networks (ANN) as tools to predict and identify the experimental conditions used in the process of delignification of sugarcane bagasse using supercritical carbon dioxide (ScCO2). The experimental conditions varied from 35 – 100°C to temperature, 75 – 300 bar to pressure and 0 – 100% to ethanol content, used as co-solvent in the extraction. HPLC and determination of insoluble lignin (Klason lignin) analysis were performed to evaluate the efficiency of the process. A database was constructed with the information of the experiments, dividing them into groups of training (70%) and test (30%). The models were obtained using toolbox of the MATLAB R2016b. In the developed neural network, the data obtained by the different techniques of analysis were used as neurons in the input layer and the percentage of insoluble lignin was used as neuron in the output layer. The performance of the neural network was evaluated by the correlation coefficient (R2) and the error indexes (MSE and SSE). The process of sugarcane bagasse delignification using ScCO2 showed good yields. The model developed from the neural network was satisfactory, since the R2 value was 99.58% and the error index values were 0.176 to SSE and 0.0147 to MSE.

Although various kinds of kinetic models were proposed to describe the dynamic behaviour of biologically reacting systems, very little studies have been carried about biosurfactant formation. Its sustainable production, in renewable culture medium, is even more complex. In this sense, emerges the Genetic Algorithm (GA), an effective stochastic global search algorithm inspired in the evolution theory that has been showing a great potential to find optimal solutions in complex systems. This work aims to evaluate the GA’s estimation of parameters involved in biosurfactant production from agro-industrial waste using Bacillus subtilis. Three different models were proposed to describe biomass growth, substrate consumption, biosurfactant synthesis and dissolved oxygen in the medium. The technique’s quality was evaluated by the sum of squared errors (SSE) and correlation coefficient (R2). The results indicated that the best model to describe the system’s dynamics obtained SSE lower than 1 and R2 superior to 0.97 for almost all the variables.

Left ventricular noncompaction (LVNC) is now recognized as a distinct form of cardiomyopathy with a clinical presentation and natural history of its own. Common manifestations of LVNC include heart failure, ventricular arrhythmias and embolic events, but serious atrioventricular conduction disturbances are rarely reported in the literature. The authors describe the case of a 40-year-old woman who went to the emergency department due to syncope. The ECG revealed left bundle branch block (LBBB) and 2:1 atrioventricular block (AVB) and the patient was admitted for pacemaker implantation. During hospitalization she developed torsade de pointes and complete AVB with increased QTc. The echocardiogram showed images compatible with LVNC. This case provides additional evidence that LVNC may be complicated by 2:1 (or complete) AVB, intraventricular conduction disturbances (LBBB) and repolarization abnormalities (long QT). This combination of electrocardiographic changes has rarely been reported in the literature. We describe a series of affected patients, focusing on electrocardiographic characteristics. Resumo: O ventrículo esquerdo não compactado (VENC) tem sido reconhecido como uma forma distinta de miocardiopatia com uma apresentação clínica e história natural próprias. As manifestações comuns de VENC são insuficiência cardíaca, arritmias ventriculares e eventos embólicos. A presença de perturbações da condução auriculoventricular de maior gravidade encontra-se raramente descrita na literatura. Os autores descrevem o caso clínico de uma paciente com 40 anos de idade, que recorreu ao Serviço de Urgência por síncope. O ECG revelou bloqueio completo de ramo esquerdo do feixe de His e bloqueio auriculoventricular (BAV) 2:1, tendo sido internada para implantação de pacemaker. Durante o internamento, desenvolve fenómenos de torsade de pointes e de BAV completo com aumento do intervalo QTc. O ecocardiograma revelou imagens compatíveis com VENC. Com este caso, os autores fornecem evidência adicional de que a presença de VENC pode ser complicada por BAV 2:1 (ou completo), perturbações da condução intraventricular (BCRE) e da repolarização (QT longo), alterações eletrocardiográficas concomitantes pouco descritas na literatura. Descreve-se uma série de pacientes afetados, com foco nas características eletrocardiográficas. Keywords: Left ventricular noncompaction, Atrioventricular block, Torsade de pointes, Palavras-chave: Ventrículo esquerdo não compactado, Bloqueio auriculoventricular, Torsade de pointes